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Leucylleucine

Leucylleucine is a dipeptide composed of two leucine amino acid residues.
It is involved in various biological processes and is of interest for researchers studying peptide-based therapies and protein structure.
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Example 2

Analysis Populations

The “Discovery-Full Analysis Set” (“Discovery FAS”) consisted of pilot study patients with clinical data and a CT-based designation of either Revascularization CAD case, Native CAD case, or Control (N=748 for the Discovery-FAS group).

The “Discovery-Native CAD Set” was the subset of the Discovery-FAS with Native CAD as verified by CT, who had analyte (metabolomic) data (N=366 for the Discovery-Native CAD Set). These were subjects without previous revascularization procedures, such as percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG).

The “Discovery-Revasc CAD Set” was the subset of the Discovery-FAS who had undergone previous revascularization, such as percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG), and who had analyte data (N=44).

The “Discovery-All CAD Set” was the union of the Discovery-Native CAD Set and the Discovery-Revasc CAD Set (N=410).

The “Discovery-Control Set” was the subset of Discovery-FAS who had a calcium score of zero and were designated a Control after inspection of CT data, and who had analyte data. (N=338 for the Discovery-Control Set.)

The “Validation-Full Analysis Set” (“Validation-FAS”) consisted of pilot study patients with clinical data and a CT-based designation of either Revascularization CAD case, Native CAD case, or Control (N=348 for the Validation-FAS group).

The “Validation-Native CAD Set” was the subset of the Validation-FAS with Native CAD as verified by CT, who had analyte (metabolomic) data (N=207 for the Validation-Native CAD Set). These were subjects without previous revascularization procedures, such as percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG).

The “Validation-Revasc CAD Set” was the subset of the Validation-FAS who had undergone previous revascularization, such as percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG), and who had analyte data (N=15).

The “Validation-All CAD Set” was the union of the Validation-Native CAD Set and the Validation-Revasc CAD Set (N=222).

The “Validation-Control Set” was the subset of Validation-FAS who had a calcium score of zero and were designated a Control after inspection of CT data, and who had analyte data. (N=126 for the Validation-Control Set)

It is noted that by design, the only racial group represented in the study was White. Therefore, race-based sub-populations were not defined.

A. Study Endpoints

For the GLOBAL Pilot Discovery Cohort, there were four primary endpoints in the analysis: (1) Native CAD; (2) All CAD (Native or Revascularization); (3) 50% Stenosis without Revascularization; (4) 50% Stenosis or Revascularization. All analyses were applied to all primary endpoints.

B. Statistical Hypothesis

The null hypothesis of no association, between the metabolite or lipid and the endpoint, was tested against the two-sided alternative that association exists.

C. Multiple Comparisons and Multiplicity

False discovery rate (FDR) q-values were calculated (Benjamini and Hochberg, 1995). Associations with FDR q<0.05 were considered preliminary associations. In some circumstances, test results with raw p<0.05 were reported as well.

D. Missing Data

Endpoint data was not imputed. Potential covariates with more than 5% missing data were excluded. Potential covariates with less than 5% missing data were imputed to the mean.

Metabolites with more than 10% missing data were excluded from the main analyses. Missing values for metabolites and lipids with less than 10% missing were imputed to the observed minimum after normalization.

E. Analysis of Subgroups

The first and third primary endpoints were addressed using a subset of the FAS. Specifically the Native CAS Set and the Control Set were considered to the exclusion of the Revasc. CAD Set. For the purposes of discovery, further subsets were created on the basis of participants' fasting status, where patients were categorized as Fasting if they had not eaten for eight or more hours. The remainder, either known not to be fasted, or with unknown fasting status were categorized as ‘Non-Fasting’. See FIG. 50.

I. Demographic and Baseline Characteristics

The baseline and demographic characteristics of patients in the pilot study were tabulated. Continuous variables were summarized by the mean and standard error; binary variables were summarized by the count and percentage.

Table 27 shows general patient characteristics for the Discovery Set by clinical group (Revasc CAD vs. Native CAD vs. Control). A Kruskall-Wallis test was performed to investigate homogeneity of continuous measures; a Pearson's chi-squared test was conducted for binary measures; unadjusted p-values are reported.

Table 28 shows general patient characteristics for the Validation Set by clinical group (Revasc CAD vs. Native CAD vs. Control). A Kruskall-Wallis test was performed to investigate homogeneity of continuous measures; a Pearson's chi-squared test was conducted for binary measures; unadjusted p-values are reported.

TABLE 27
All ControlsNative CADRevasc CADP-value
N33836644
Age
mean (SE)53.8 (0.57) 58.02 (0.54) 59.55 (1.40)  3.93E−07
SBP
mean (SE)129.62 (0.91)  132.6 (0.92) 128.09 (2.32)  0.0550
DBP
mean (SE)79.03 (0.56) 79.73 (0.58) 75.12 (1.57)  0.0402
Male
N (%)151 (44.67)195 (53.28)30 (68.18)0.0037
Hypertension
N (%)172 (51.04)244 (66.85)40 (90.91)1.61E−08
Dyslipidemia
N (%)184 (55.42)259 (71.15) 43 (100.00)4.95E−10
Diabetes (Any)
N (%)25 (7.40) 54 (14.75)10 (22.73)8.00E−04
Type I Diabetes
N (%) 1 (0.30) 1 (0.27)0 (0.00)0.9377
Type II Diabetes
N (%)24 (7.10) 53 (14.48)10 (22.73)6.00E−04
Current Smoker
N (%) 39 (11.54) 67 (18.31) 5 (11.36)0.0331
Former Smoker
N (%) 84 (24.85)130 (35.52)21 (47.73)5.00E−04
Chest Pain
N (%)221 (65.38)212 (57.92)30 (68.18)0.0850
Angina
Equivalent
N (%)126 (37.28)122 (33.33)19 (43.18)0.3115
Shortness of Breath
N (%) 74 (21.89) 71 (19.40) 8 (18.18)0.6635
Family History of CAD
N (%)179 (52.96)223 (60.93)28 (63.64)0.0710
Fasting
N (%)120 (35.50)207 (56.56) 44 (100.00)8.28E−18
Statin
N (%)111 (32.84)184 (50.27)38 (86.36)1.28E−12
Niacin
N (%) 5 (1.48) 4 (1.09)3 (6.82)0.0164
Fibrate
N (%)12 (3.55)21 (5.74)3 (6.82)0.3254
Ezetimibe
N (%) 6 (1.78)11 (3.01) 8 (18.18)7.97E−08
Fish Oil
N (%)26 (7.69) 50 (13.66) 5 (11.36)0.0388
Bile Acid Sequestrant
N (%) 3 (0.89) 4 (1.09)0 (0.00)0.7705
Aspirin
N (%) 98 (28.99)157 (42.90)34 (77.27)3.15E−10
Clopidogrel
N (%) 7 (2.07)11 (3.01)15 (34.09)5.21E−22
Vitamin K Antagonist
N (%) 7 (2.07)17 (4.64)2 (4.55)0.1629
Nitrate
N (%) 7 (2.07)16 (4.37)11 (25.00)5.57E−11
Beta Blocker
N (%)114 (33.73)140 (38.25)34 (77.27)1.68E−07
ACE Inhibitor
N (%) 63 (18.64)106 (28.96)24 (54.55)3.13E−07

TABLE 28
All ControlsNative CADRevasc CADP-value
N12620715
Age
mean (SE)49.48 (0.93)  60.83 (0.59)  68.6 (2.05) 3.35E−22
SBP
mean (SE)127.25 (1.55)  131.46 (1.10)  131.8 (4.16)  0.0276
DBP
mean (SE)77.33 (0.98)  78.99 (0.77)  78.87 (3.16)  0.2091
Male
N (%)46 (36.51)138 (66.67)  15 (100.00)1.36E−09
Hypertension
N (%)51 (40.48)132 (63.77) 13 (86.67)9.44E−06
Dyslipidemia
N (%)65 (53.72)152 (74.88)  14 (100.00)1.33E−05
Diabetes (Any)
N (%)12 (9.52) 44 (21.36) 4 (26.67)0.0134
Type I Diabetes
N (%)1 (0.79)3 (1.45)1 (6.67)0.1954
Type II Diabetes
N (%)11 (8.73) 41 (19.81) 3 (20.00)0.0244
Current Smoker
N (%)20 (15.87)28 (13.53)0 (0.00)0.238
Former Smoker
N (%)25 (19.84)78 (37.68) 8 (53.33)6.00E−04
Chest Pain
N (%)96 (76.19)110 (53.14)  7 (46.67)7.78E−05
Angina Equivalent
N (%)46 (36.51)53 (25.60) 5 (33.33)0.1037
Shortness of Breath
N (%)28 (22.22)30 (14.49) 7 (46.67)0.0038
Family History of CAD
N (%)53 (42.06)129 (62.32)  6 (40.00)8.00E−04
Fasting
N (%)126 (100.00)207 (100.00) 15 (100.00)NA
Statin
N (%)39 (30.95)125 (60.39) 13 (86.67)2.28E−08
Niacin
N (%)1 (0.79)3 (1.45)0 (0.00)0.7872
Fibrate
N (%)4 (3.17)7 (3.38)1 (6.67)0.7797
Ezetimibe
N (%)1 (0.79)5 (2.42)0 (0.00)0.4745
Fish Oil
N (%)8 (6.35)23 (11.11)1 (6.67)0.3251
Bile Acid Sequestrant
N (%)0 (0.00)0 (0.00)0 (0.00)NA
Aspirin
N (%)28 (22.22)99 (47.83) 9 (60.00)4.91E−06
Clopidogrel
N (%)1 (0.79)2 (0.97) 4 (26.67)3.16E−11
Vitamin K Antagonist
N (%)6 (4.76)3 (1.45)1 (6.67)0.1432
Nitrate
N (%)3 (2.38)10 (4.83)  3 (20.00)0.0084
Beta Blocker
N (%)36 (28.57)77 (37.20)12 (80.00)4.00E−04
ACE Inhibitor
N (%)26 (20.63)59 (28.50) 9 (60.00)0.0039
II. Exploratory Data Analyses for Metabolites

Sample preparation and mass spectrometry analyses were conducted by Metabolon, Inc. The raw data contained a total of 1088 analytes, measured for 1096 pilot study participants.

Of the 1088 analytes (including unnamed metabolites and complex lipids), 481 named metabolites had less than 10% missing data. All 1096 patients had less than 10% missing data for these metabolites. Statistical analyses were therefore applied to 481 analytes and 1096 patients. The data was normalized in advance of receipt. A logarithm (base 2) transformation was applied and histograms were created to show the distribution of expression by analyte (data not shown).

The metabolomics data were generated in multiple batches; however, a principal components analysis (PCA) showed no evidence of any systematic site effects.

III. Prediction Modeling for Primary Endpoints

Methods. Patients in the Discovery-FAS Set were categorized according to whether they had fasted for at least eight hours. By this criteria, a total of 377 participants were Fasted and 371 were Non-Fasted. Association testing, with adjustment for age and gender was conducted for the four primary endpoints, and nominal associations were defined in three ways as follows:

    • 1 Significant in Fasting and Non-Fasting combined
    • 2 Significant in Fasting and Non-Fasting independently
    • 3 Significant in Fasting alone

It is emphasized that, at this stage, ‘significant’ pertains to any association with raw, unadjusted p<0.05.

In this way, twelve scenarios were considered as follows:

    • a) Atherosclerosis in Native CAD—AnCAD
      • c. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • c. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • c. Significant in Fasting—[Figure (not displayed)]
    • b) Atherosclerosis in All CAD (including revascularization)—AaCAD
      • c. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • c. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • c. Significant in Fasting—[Figure (not displayed)]
    • c) 50% stenosis in Native CAD—SnCAD
      • c. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • c. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • c. Significant in Fasting—[Figure (not displayed)]
    • d) 50% stenosis in ALL CAD (including revascularization)—SaCAD
      • c. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • c. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • c. Analytes Significant in Fasting—[Figure (not displayed)].

When more than 9 variables had p<0.05, Age and Gender were added to the variables, and gradient boosting (see below) was applied to select 9 predictors.

Twelve prediction models were obtained by generalized linear (logistic) regression as follows. When fewer than nine variables had p<0.05, Age and Gender were added to the variables, and the full model was fitted. Otherwise, the nine variables selected by gradient boosting variables were combined with Age and Gender in a generalized linear (logistic) model.

Gradient boosting is an approach to determine a regression function that minimizes the expectation of a loss function. (Freidman J H (2001) and Friedman J H (2002)) It is an iterative method, in which the negative gradient of the loss function is calculated, a regression model is fitted, the gradient descent step size is selected, and the regression function is updated. The gradient is approximated by means of a regression tree, which makes use of covariate information, and at each iteration the gradient determines the direction in which the function needs to move, in order to improve the fit to the data.

The loss function was assumed Bernoulli, due to the binary nature of the primary endpoints. A learning rate (λ) was introduced to dampen proposed moves and to protect against over-fitting. The optimal number of iterations, given by T, was determined by 5-fold cross-validation. The minimum number of observations in each terminal node was 10. Two-way interactions were allowed. Random sub-sampling, without replacement, of half of the observations was applied to achieve variance reduction in gradient estimation.

For current purposes, 50 rounds of gradient boosting were run for each scenario, and the nine variables most often showing highest estimated relative influence were taken forwards to generalized linear modeling.

The twelve models were used to generate probability predictions for each patient in the Validation-FAS. For each model, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for the range of predicted probability thresholds. A Receiver Operating Characteristic (ROC) curve was generated to plot sensitivity as a function of (1-specificity). The optimal classification threshold was determined on the basis of accuracy, defined as the proportion of correct predictions. In addition, the Area Under the Curve (AUC) and accuracy was estimated (Tables 27, 28, 29, 30 for the four primary endpoints, respectively).

The performance of model-based predictions were compared to the performance of probability predictions obtained by Diamond-Forrester scoring. (Diamond and Forrester (1979)).

Detailed Results for Native CAD

The results show that the Diamond-Forrester score provides poor prediction of the GLOBAL phenotypes (FIGS. 34, 38, 42, 46). The estimates of AUC and accuracy for prediction of Native CAD indicate that performance is no better than assigning all patients as ‘at risk’ of disease, by which 62% of predictions in the Validation Set for Native CAD (Validation-Native CAD plus Validation-Control) are correct, and 64% of predictions in the Validation Set for All CAD (Validation Native CAD plus Validation-Revasc. CAD plus Validation-Control), are correct.

Metabolomics Model

I. Atherosclerosis in Native CAD—A nnCAD

    • a. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 83 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 29 provides a list of the 83 metabolomic variables for [Figure (not displayed)].

TABLE 29
glutamateserylleucine1-linoleoyl-GPC (18:2)
acisoga3-methoxytyrosine1-methylguanosine
threonateprolylhydroxyproline12 13-DiHOME
uratevalerylcarnitine (C5)O-sulfo-L-tyrosine
mannosecaproate (6:0)erucamide
oleic ethanolamidetigloylglycineinositol 1-phosphate
(l1P)
cysteine-glutathione disulfideguanidinosuccinateisoleucylvaline
pyroglutamylglutamineisobutyrylglycine (C4)gamma-tocopherol
valylleucineglycocholenate sulfate*1-
eicosenoylglycerophosp
hocholine (20:1n9)*
butyrylcarnitine (C4)o-cresol sulfatetyrosylglutamine
cytidineN-acetylthreonineindolepropionate
palmitoyl ethanolamideleucylglycinegamma-glutamylvaline
phenylalanylvaline2-hydroxybutyrate (AHB)2-aminoadipate
hydroxybutyrylcarnitine*leucylaspartateaspartate
1-1-arachidoyl-GPC (20:0)N6-
nonadecanoylglycerophosphocholinecarbamoylthreonyladenosine
(19:0)
glycineN6-methyladenosinemethyl glucopyranoside
(alpha + beta)
propionylglycine (C3)hexanoylcarnitine (C6)myo-inositol
pseudouridinevalylisoleucinealpha-ketobutyrate
ADSGEGDFXAEGGGVR*beta-alanineS-adenosylhomocysteine
(SAH)
2-hydroxyhippurate (salicylurate)1-linoleoyl-GPE (18:2)*1-oleoylglycerol (18:1)
alpha-glutamyltyrosinegamma-glutamylglutamatetartronate
(hydroxymalonate)
fucose3-hydroxy-2-ethylpropionate3-
methylglutarylcarnitine-2
glucuronateadenine1-methylurate
3-methylglutarylcarnitine-1xylitolN-acetyl-beta-alanine
xanthineN2 N2-dimethylguanosinehistidyltryptophan
12-HETEmethyl indole-3-acetate1-oleoyl-GPC (18:1)*
glucosehomostachydrine*3-hydroxydecanoate
salicylatephenylacetylglutamine
Of the 83 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 30 provides the relative influence of the eight metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 35 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 53 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 30
VariableRelative InfluenceDirection of Change
valylleucine28.88Decreased
glutamate14.47Elevated
acisoga14.25Elevated
urate10.39Elevated
glucuronate9.26Elevated
age6.68Elevated
fucose6.18Elevated
Butyrylcarnitine (C4)4.72Elevated
mannose4.46Elevated
Male gender0.70Present§
§The term “present” conveys that male gender was taken into account in the prediction model, with ‘relative influence’ denoting the association of male gender with the outcome (i.e., ASCAD or the presents of a coronary atherosclerotic plaque).
    • b. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 4 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 31 provides a list of the 4 metabolomic variables for [Figure (not displayed)].

TABLE 31
acisogao.cresol.sulfateCysteine.glutathione.disulfide
threonate

Of the 4 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)]; a panel of all four metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 32 provides the relative influence of the four metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 36 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 53 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 32
VariableRelative InfluenceDirection of Change
acisoga40.74Elevated
age20.77Elevated
cysteine.glutathione.disulfide18.87Decreased
threonate12.67Decreased
o-cresol.sulfate4.49Elevated
Male gender2.45Present
    • c. Significant in Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 34 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 33 provides a list of the 34 metabolomic variables for [Figure (not displayed)].

TABLE 33
xylitolvalylleucinecysteine-glutathione
disulfide
3-carboxy-4-methyl-N-acetylleucinethreonate
5-propyl-2-
furanpropanoate
(CMPF)
serylleucinealpha-glutamyltyrosinefucose
phenylalanylvaline4-androsten-3alphaadenosine
17alpha-diol
monosulfate 2
12-HETEinositol 1-phosphate (I1P)valylisoleucine
glycocholenate1-docosahexaenoyl-GPC*phenylalanylserine
sulfate*(22:6)*
oleic ethanolamide2-hydroxyhippurategamma-tocopherol
(salicylurate)
acisogasalicylatepalmitoyl
ethanolamide
leucylglycinephenylalanylglycinehydroquinone sulfate
N-glycylphenylalaninepropionylglycine (C3)
acetylphenylalanine
o-cresol sulfate3-methoxytyrosine
histidyltryptophanadenine

Of the 34 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 34 provides the relative influence of the eight metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 37 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 53 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 34
Direction
VariableRelative Influenceof Change
N-acetylphenylalanine22.27Elevated
age18.18Elevated
valylleucine17.61Decreased
xylitol8.07Elevated
2-hydroxyhippurate6.97Elevated
(salicylurate)
N-acetylleucine6.15Elevated
serylleucine6.15Decreased
fucose6.06Elevated
glycylphenylalanine4.97Decreased
Male gender3.56Present

II. Atherosclerosis in All CAD (inc revasc)—AaCAD

    • a. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 92 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 41 provides a filtered list of the 92 metabolomic variables for [Figure (not displayed)].

TABLE 41
acisogatyrosylglutamineN6-
carbamoylthreonyladenosine
Glutamatexanthine2-linoleoyl-GPC* (18:2)*
Threonatebeta-alanine3-methyl-2-oxobutyrate
Mannoseisobutyrylglycine (C4)methyl glucopyranoside
(alpha + beta)
Urate3-methylglutarylcarnitine-1serylleucine
cysteine-glutathione disulfidevalerylcarnitine (C5)caproate (6:0)
oleic ethanolamide1-linoleoyl-GPC (18:2)N-methyl proline
pyroglutamylglutaminehexanoylcarnitine (C6)laurylcarnitine (C12)*
butyrylcarnitine (C4)2-hydroxybutyrate (AHB)o-cresol sulfate
Cytidine1-arachidoyl-GPC (20:0)gamma-
glutamylglutamate
hydroxybutyrylcarnitine*guanidinosuccinateN-acetyl-beta-alanine
alpha-glutamyltyrosinefucose1-
eicosenoylglycerophosphocholine
(20:1n9)*
2-hydroxyhippurate (salicylurate)phenylacetylglutamineN-acetylglycine
Valylleucine3-methylglutarylcarnitine-2seryltyrosine
propionylglycine (C3)glycohyocholate4-guanidinobutanoate
1-N6-methyladenosineS-methylcysteine
nonadecanoylglycerophosphocholine
(19:0)
GlycineN2 N2-dimethylguanosineisoleucylvaline
12-HETEgamma-glutamylvalineadenine
pseudouridineleucylaspartate1-methylurate
Salicylate2-hydroxyoctanoatexylitol
Glucosealpha-ketobutyratephenylalanylalanine
ADSGEGDFXAEGGGVR*glycocholenate sulfate*O-sulfo-L-tyrosine
1-linoleoyl-GPE (18:2)*valylisoleucineerucamide
Phenylalanylvalinehomostachydrine*pregnanediol-3-
glucuronide
Tigloylglycinemethyl indole-3-acetate3-hydroxy-2-
ethylpropionate
Glucuronateleucylglycinepyridoxal
palmitoyl ethanolamideN-acetylthreonine1-oleoyl-GPC (18:1)*
1-oleoylglycerol (18:1)2-hydroxydecanoate2prime-deoxyuridine
12 13-DiHOME1-methylguanosinethreonylphenylalanine
3-methoxytyrosineprolylhydroxyproline2-aminoadipate
2-linoleoyl-GPE* (18:2)*prolylglycine

Of the 92 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 36 provides the relative influence of the eight metabolomic variables combined with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 39 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 54 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 36
VariableRelative InfluenceDirection of Change
valylleucine26.79Decreased
acisoga16.87Elevated
glutamate13.93Elevated
urate9.74Elevated
glucuronate8.74Elevated
mannose7.13Elevated
age6.24Elevated
12-HETE5.03Decreased
Valerylcarnitine (C5)4.81Elevated
Male gender0.72Present
    • b. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 6 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 37 provides a list of the 6 metabolomic variables for [Figure (not displayed)].

TABLE 37
threonatethreonatecysteine-glutathione
disulfide
o-cresol1-glucose
sulfatenonadecanoylglycerophosphocholine
(19:0)

Of the 6 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of all six metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 38 provides the relative influence of the six metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 40 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 54 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 38
Direction
VariableRelative Influenceof Change
acisoga39.32Elevated
age17.31Elevated
1.nonadecanoylglycerophosphocholine12.00Decreased
(19:0)
cysteine-glutathione disulfide10.91Decreased
threonate10.71Decreased
glucose6.64Elevated
Male gender2.06Present
o-cresol sulfate1.05Elevated
    • c. Significant in Fasting —[Figure (not displayed)]
      • i. Of the 481 analytes measured, 48 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 39 provides a list of the 48 metabolomic variables for [Figure (not displayed)].

TABLE 39
12-HETEN-acetylphenylalanine1-arachidonylglycerol
alpha-glutamyltyrosineN-acetylleucinePyroglutamylvaline
salicylate4-androsten-3alpha 17alpha-phenylalanyltryptophan
diol monosulfate 2
2-hydroxyhippurate (salicylurate)o-cresol sulfatemethyl indole-3-acetate
acisogaphenylalanylvalineHistidyltryptophan
3-carboxy-4-methyl-5-propyl-2-leucylglycine4-ethylphenyl sulfate
furanpropanoate (CMPF)
threonatephenylalanylglycine1-myristoylglycerol
(14:0)
glycocholenate sulfate*propionylglycine (C3)inositol 1-phosphate
(I1P)
xylitolmannitol1-
nonadecanoylglycerophosphocholine
(19:0)
1-docosahexaenoyl-GPC* (22:6)*serylleucineGlucose
phenylalanylserinehydroquinone sulfateN-stearoyltaurine
3-methoxytyrosineadenosineValylisoleucine
oleic ethanolamide2-hydroxydecanoatebeta-alanine
cysteine-glutathione disulfidetyrosylglutamineN-acetylglycine
glycylphenylalanineN-octanoylglycineAllantoin
valylleucineadeninePhenylalanylphenylalanine

Of the 48 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of seven metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 40 provides the relative influence of the seven metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 41 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 54 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 40
Direction
VariableRelative Influenceof Change
age21.21Elevated
valylleucine20.76Decreased
N-acetylphenylalanine18.59Elevated
2-hydroxyhippurate12.20Elevated
(salicylurate)
N-acetylleucine6.10Elevated
12-HETE5.96Decreased
xylitol5.40Elevated
glycylphenylalanine5.39Decreased
Male gender4.40Present

III. 50% stenosis in Native CAD—SnCAD

    • a. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 49 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 41 provides a list of the 49 metabolomic variables for [Figure (not displayed)].

TABLE 41
threonateserotonin (5HT)5alpha-androstan-3alpha
17beta-diol disulfate
N-acetylglycinexanthine1-stearoyl-GPC (18:0)
glycerate2-oleoyl-GPE* (18:1)*serine
isobutyrylglycine (C4)4-guanidinobutanoateacisoga
valerylcarnitine (C5)leucylleucinemannose
fumaratecholatevalylleucine
1-propionylglycine (C3)gamma-tocopherol
nonadecanoylglycerophosphocholine
(19:0)
tartronate (hydroxymalonate)glycocholate3-ethylphenylsulfate
2-hydroxyhippurateN-octanoylglycineglutamate
(salicylurate)
1-arachidoyl-GPC (20:0)glycoursodeoxycholatesphingosine 1-phosphate
threitolisovalerylglycinecarnitine
N-(2-furoyl)glycinepregnanediol-3-glucuronidearabonate
tigloylglycine5alpha-androstan-3betacyclo(leu-pro)
17beta-diol monosulfate 2
salicylatearabinoseindoleacetylglutamine
N-acetylthreonine1-linoleoyl-GPE (18:2)*prolylglycine
xylonate5-HETE
xylosehydroquinone sulfate

Of the 49 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 42 provides the relative influence of the eight metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 43 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 55 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 42
VariableRelative InfluenceDirection of Change
Age37.04Elevated
valerylcarnitine (C5)14.32Elevated
N-acetylthreonine10.39Elevated
tigloylglycine8.72Decreased
2-hydroxyhippurate7.06Elevated
(salicylurate)
glycerate6.42Decreased
salicylate5.67Decreased
threonate5.58Decreased
tartronate (hydroxymalonated);4.25Elevated
Male gender0.55Present
    • b. Independently Significant in Fasting and Non-Fasting —[Figure (not displayed)]
      • i. Of the 481 analytes measured, 2 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 43 provides a list of the 2 metabolomic variables for [Figure (not displayed)].

TABLE 43
N-acetylglycine3-ethylphenylsulfate

Of the 2 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of both variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 44 provides the relative influence of the two metabolomic variables in combination with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 44 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 55 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 44
VariableRelative InfluenceDirection of Change
age67.33Elevated
N-acetylglycine14.67Decreased
3-ethylphenylsulfate12.88Elevated
Male gender5.12Elevated
    • c. Significant in Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 28 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 45 provides a filtered list of the 28 metabolomic variables for [Figure (not displayed)].

TABLE 45
leucylleucinevalylisoleucine7-methylguanine
asparagineglycocholenate sulfate*cyclo(leu-pro)
glyceratearabitolMethionine
threitolN-acetylglycinepropionylglycine (C3)
cholateserotonin (5HT)Serine
N-octanoylglycinexylose2-oleoyl-GPE* (18:1)*
xylonateN-acetylputrescineTigloylglycine
isobutyrylglycine (C4)arabonate3-ethylphenylsulfate
isovalerylglycinelysine
fumarateN-(2-furoyl)glycine

Of the 28 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; they were combined with age and gender in a prediction model for CAD. Table 46 provides the relative influence of the eight metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 45 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 55 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 46
VariableRelative InfluenceDirection of Change
age24.44Elevated
leucylleucine21.83Decreased
serotonin (5HT)11.37Elevated
N-acetylputrescine9.68Decreased
glycocholenate sulfate8.56Decreased
propionylglycine (C3)6.95Decreased
cholate6.14Decreased
asparagine5.73Elevated
3-ethylphenylsulfate4.79Elevated
Male gender0.50Present

IV. 50% stenosis in ALL CAD (inc revasc)—SaCAD

    • a. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 72 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 47 provides a list of the 72 metabolomic variables for [Figure (not displayed)].

TABLE 47
threonateprolylglycine2-hydroxydecanoate
1-linoleoyl-GPE (18:2)*N-octanoylglycineglutamate
N-acetylglycinethreitolN-acetylthreonine
glycoursodeoxycholatefumaratetaurine
2-hydroxyhippurate (salicylurate)pregnanediol-3-glucuronide1-
oleoylplasmenylethanol
amine*
salicylate1-oleoyl-GPI (18:1)*1-palmitoyl-GPE (16:0)
2-linoleoyl-GPE* (18:2)*serotonin (5HT)N-acetylglutamate
mannosexylonate13-HODE + 9-HODE
tigloylglycinecyclo(leu-pro)1-palmitoyl-GPI* (16:0)*
2-glyceratehydroquinone sulfate
linolenoylglycerophosphocholine (18:3n3)*
1-tartronate (hydroxymalonate)caprylate (8:0)
nonadecanoylglycerophosphocholine
(19:0)
2-oleoyl-GPE* (18:1)*xylose1-stearoyl-GPC (18:0)
isovalerylglycineglycohyocholateglycochenodeoxycholate
isobutyrylglycine (C4)glucosep-cresol sulfate
N-(2-furoyl)glycinexanthine12-HETE
glycocholatecyclo(L-phe-L-pro)5-hydroxyindoleacetate
acisogabeta-alaninearabonate
4-guanidinobutanoatepyridoxate2-hydroxyoctanoate
1-arachidoyl-GPC (20:0)tartarateurate
propionylglycine (C3)1-linoleoyl-GPC (18:2)valylleucine
valerylcarnitine (C5)pyridoxalcarnitine
1-oleoylglycerol (18:1)cholate1-linoleoyl-GPI* (18:2)*
1-oleoyl-GPE (18:1)serineN-acetylputrescine
arabinosehomostachydrine*succinate

Of the 72 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 48 provides the relative influence of the eight metabolomic variables in combination with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 47 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 56 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 48
Direction
VariableRelative Influenceof Change
Age18.38Elevated
glycoursodeoxycholate16.52Decreased
acisoga12.81Elevated
2-hydroxyhippurate10.33Elevated
(salicylurate)
1-linoleoyl.GPE (18:2)10.26Decreased
valerylcarnitine (C5),8.91Elevated
threonate7.13Decreased
mannose7.12Elevated
salicylate7.02Elevated
Male gender1.52Present
    • b. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 5 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 49 provides a filtered list of the 5 metabolomic variables for [Figure (not displayed)].

TABLE 49
N-acetylglycinethreonateSalicylate
2-hydroxyhippurate (salicylurate)3-ethylphenylsulfate

Of the 5 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of all five metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 50 provides the relative influence of the five metabolomic variables in combination with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 48 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 56 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 50
VariableRelative InfluenceDirection of Change
Age40.82Elevated
2-hydroxyhippurate19.56Elevated
(salicylurate)
threonate14.84Decreased
salicylate12.23Elevated
Male gender7.00Present
N-acetylglycine3.13Decreased
3-ethylphenylsulfate2.42Elevated
    • c. Analytes Significant in Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 40 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 51 provides a filtered list of the 40 metabolomic variables for [Figure (not displayed)].

TABLE 51
N-octanoylglycinesalicylateDimethylglycine
1-oleoylglycerol (18:1)7-methylguaninexylonite
isovalerylglycinelysinePhenylalanylphenylalanine
N-acetylglycineglycoursodeoxycholateValylisoleucine
2-3-indoxyl sulfateGlycerate
linolenoylglycerophosphocholine(18:3n3)*
asparagine6-oxopiperidine-2-carboxylic1-arachidonylglycerol
acid
isobutyrylglycine (C4)1-Fumarate
arachidonoylglyercophosphate
cyclo (leu-pro)2-hydroxyhippurate3-ethylphenylsulfate
(salicylurate)
cholatethreitol7-HOCA
serotonin (5HT)methionineTaurine
threonateacisogaCholesterol
N-acetylputrescinetigloylglycineArabitol
propionylglycine (C3)1-linoleoylglycerol (18:2)
2-oleoyl-GPE* (18:1)*1-oleoyl-GPI (18:1)*

Of the 40 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 52 provides the relative influence of the eight metabolomic variables in combination with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 49 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 56 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 52
RelativeDirection
VariableInfluenceof Change
age15.37Elevated
cholesterol15.19Decreased
1-oleoylglycerol (18:1)15.12Elevated
acisoga14.01Elevated
2.hydroxyhippurate (salicylurate)9.47Elevated
asparagine8.18Elevated
taurine7.93Decreased
6-oxopiperidine-2-carboxylic acid7.50Elevated
propionylglycine (C3)6.66Decreased
Male gender0.56Present

For each model below, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for the range of predicted probability thresholds (Tables 53, 54, 55, 56). A Receiver Operating Characteristic (ROC) curve was generated to plot sensitivity as a function of (1-specificity). The optimal classification threshold was determined on the basis of accuracy, defined as the proportion of correct predictions. In addition, the Area Under the Curve (AUC) and accuracy was estimated (Tables 53, 54, 55, 56 for Native CAD, All CAD, 50% stenosis in Native CAD, and 50% stenosis in All CAD, respectively). The first row for each model indicates the performance of the maximum accuracy threshold, the optimal balance between sensitivity and specificity. Those models with a second row were optimized for a high negative predictive value (NPV).

TABLE 53
PositiveNegative
Sensi-Speci-PredictivePredictive
ModelAUCtivityficityValueValueAccuracy
DF0.451.000.000.62N/A0.62
AFNFnCAD0.820.850.610.780.710.76
0.990.090.640.920.65
AIFNFnCAD0.800.850.640.800.720.77
1.000.100.650.930.66
AFnCAD0.810.870.580.770.740.76
0.990.260.690.940.72
DF = Diamond-Forrester

TABLE 54
PositiveNegative
Sensi-Speci-PredictivePredictive
ModelAUCtivityficityValueValueAccuracy
DF0.451.000.000.64N/A0.64
AFNFaCAD0.830.930.500.770.810.78
1.000.160.680.950.69
AIFNFaCAD0.810.850.660.810.710.78
1.000.070.650.900.66
AFaCAD0.820.830.640.800.680.76
1.000.160.680.950.69
DF = Diamond-Forrester

TABLE 55
PositiveNegative
Sensi-Speci-PredictivePredictive
ModelAUCtivityficityValueValueAccuracy
DF0.450.031.001.000.780.78
SFNFnCAD0.730.210.960.640.800.79
0.950.300.290.950.45
SIFNFnCAD0.760.300.960.720.820.81
0.930.370.310.950.50
SFnCAD0.670.041.001.000.780.78
0.960.200.260.950.38
DF = Diamond-Forrester

TABLE 56
PositiveNegative
Sensi-Speci-PredictivePredictive
ModelAUCtivityficityValueValueAccuracy
DF0.450.031.001.000.740.75
SFNFaCAD0.780.340.940.660.800.78
0.960.300.330.950.47
SIFNFaCAD0.780.230.970.720.780.77
0.960.300.330.950.47
SFaCAD0.740.220.960.690.780.77
0.970.220.310.950.42
DF = Diamond-Forrester

Full text: Click here
Patent 2019

Example 1

Assessing the degree of gingivitis in a person is typically achieved with clinical measures such as gum redness, gum bleeding or pocket depth. While the measures are based on professionally developed scales, the actual values can vary due to examiner differences. It is desirable to have objective readings free from human errors. This sample collection method enabled the taking of samples for objective measurements non-invasively and site-specifically.

Non-invasive gingival sample collection: Brush samples were taken from the upper, front gums and buccal surface of 4 volunteers, all female, ages 43-48. Interdental Gum Brushes (Sunstar America Inc, Chicago, Ill.), or A MasterAmp™ Buccal Brush (Catalog #MB100SP; Epicentre Technologies Corp., Madison, Wis.) brushes were used to sample 6 marginal gingiva, as shown in FIG. 1, and 6 buccal areas, one brush per sample site. At each sample site a brush was swabbed back-forth 10 times with the brush-head horizontally oriented parallel to the gum line. Each brush head was clipped off with sterile scissors and placed into a 15 ml conical tube with 800 μl DPBS (Dulbecco's phosphate-buffered saline; Lifetechnologies, Grand Island, N.Y.) containing protease inhibitors, including AEBSF (4-(2-Aminoethyl) benzenesulfonyl fluoride hydrochloride) 2 mM, aprotinin 0.3 μM, Bestatin 130 μM, EDTA (Ethylenediaminetetraacetic acid) 1 mM, E-64 1 μM, and leupeptin 1 μM.

Metabolites and protein extraction from gingival samples: All gingival swabs from a given volunteer were pooled into the same collection tube. Similarly all buccal swabs from a given volunteer were pooled into a separate, single collection tube. All collection tubes were vigorously shaken on a multi-tube vortexer for 15 min at 4° C. to extract materials, including metabolites and proteins, from the harvested gingival and buccal samples. Using sterile tweezers the brush heads were dabbed to the side of the tube to collect as much lysate as possible and subsequently discarded. The extracted materials were then centrifuged at 5000 RPM (revolutions per minute) in a Refrigerated at 4° C. table top centrifuge Sigma 4k15 (SIGMA Laborzentrifugen GmbH P.O. Box 1713-37507 Osterode/Germany) to separate the soluble and insoluble fractions. The separated samples were stored at −80° C. in a freezer.

Upon analysis of the samples for total protein the samples appeared to have sufficient protein for further analysis, such as proteomics or metabonomics. Interdental gum brushes appeared to collect enough gingival tissue for further quantifiable molecular analysis.

Example 2

A randomized, parallel group clinical study was conducted with 69 volunteers (35 in the negative control group and 34 in the test regimen group). Volunteers were 39 years old on average, ranging from 20 to 69, and 46% of the volunteers were female. Treatment groups were well balanced, since there were no statistically significant (p≥0.395) differences for demographic characteristics (age, ethnicity, gender) or starting measurements for Gingival Bleeding Index (GBI); mean=29.957 with at least 20 bleeding sites, and Modified Gingival Index (MGI); mean=2.086. All 69 volunteers attended each visit and completed the research. The following treatment groups were compared over a 6-week period: Test regimen: Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse. Control regimen (negative control): Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush.

The test regimen group demonstrated significantly (p<0.0001) lower mean bleeding (GBI) and inflammation (MGI) relative to the negative control group at Weeks 1, 3 and 6 as shown in FIG. 2.

Dental plaques were also collected from the same volunteers in the test regimen in this clinical study. A supragingival sample was taken from each volunteer with a sterile curette at the tooth/gum interface, using care to avoid contact with the oral soft tissue. Plaques were sampled from all available natural teeth (upper arch only) until no plaque was visible. Following sampling, plaques were released from the curettes by shaking with into a pre-labeled (volunteer ID, sample initials, visit, and date) Eppendorf tube 1.5 ml with 1 ml of PBS/Glycerol buffer (20% glyceroal) and about 30 sterile 1 mm glass beads stored on ice until all samples were collected. The samples were then transferred to a −70° C. freezer for storage until further processing. Genomic DNA was isolated from supragingival plaque samples using QIAamp® genomic DNA kits (Qiagen, Valencia, Calif.) following manufacturer's instruction. Metasequencing was carried out in BGI Americas Corporation (Cambridge, Mass.). All data was analyzed at Global Biotech of Procter & Gamble Company in Mason, Ohio.

The Amount of bacterial and host DNA was changed in the supragingival plaques in the 6 week treatments as shown in FIG. 3. Certain bacteria, such as Porphyromonas sp oral taxon 279 and Prevotella pallens, were decreased in weeks 1 and 3 (FIG. 4). The amount of each bacterial species was plotted over the four time periods of the treatment. The amount of certain bacteria, such as Peptostreptococcus stomatis and Prevotella intermedia was reduced from baseline to week 3. The amount of Prevotella intermedia was not statistically different at week 6 from the baseline in relative percentage abundance, but the absolute abundance of Prevotella intermedia was far lower at week 6 than at baseline since the total amount of bacterial DNA decreased dramatically at week 6 (FIGS. 3 and 4).

Example 3

Gingival-brush samples were collected using the procedures described in EXAMPLE 1, from the same volunteers as in EXAMPLE 2. Before sampling, volunteers rinsed their mouths for 30 seconds with water. A dental hygienist then sampled the area just above the gumline using a buccal swab brush (Epicentre Biotechnologies, Madison, Wis., cat. #MB100SP). The swab was immediately placed into 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Lifetechnologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube vortexed for 30 seconds, and immediately frozen on dry ice and stored in a −80 C freezer until analysis. The samples were taken out of the freezer, thawed and extracted by placing the samples on a tube shaker for 30 minutes at 4° C. The tubes were centrifuged at 15000 RPM for 10 min in Eppendorf Centrifuge 5417R (Eppendorf, Ontario, Canada) to pellet any debris. The extract (800 μl) was analyzed for protein concentrations using the Bio-Rad protein assay (BioRad, Hercules, Calif.).

Forty proteins were measured in the gingival samples using V-PLEX Human Biomarker 40-Plex Kit (Meso Scale Diagnostics Rockville, Md.). The assay was performed following the manufacturer's instruction.

V-PLEX Human Biomarker 40-Plex Kit was divided into four panels, or four 96-well plates. Among the proteins measured in the gingival samples, most proteins had significant changes in their abundance during the 6-week treatment (TABLE 1). Those include FN-γ, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, GM-CSF, IL-5, IL-16, IL-7, IL-12/IL-23p40, IL-1α, VEGF-A, IL-17A, IL-15, TNF-β, IL-8 (HA), MCP-1, MCP-4, Eotaxin, IP-10, MDC, Eotaxin-3, TARC, MIP-1α, MIP-1β, VEGF-C, VEGF-D, Tie-2, Flt-1/VEGFR1, P1GF, FGF (basic), SAA, CRP, VCAM-1, and ICAM-1. ICAM-1 and VCAM-1 are high in gingivae having gingivitis, as shown in TABLE 1.

TABLE 1
Changes in abundance of proteins in the gingival-brush samples.
Meanα = 0.05
BaselineWeek 1Week 3Week 6BaselineWeek 1Week 3Week 6
ICAM-116.03512.20910.0909.767ABB, CC
IL-1α3.5542.3312.1811.891AA, BB, CC
IL-1β53.66635.57524.29524.440ABCC
TNF-β0.00130.00100.00080.0007ABCC
IL-12p700.1720.1480.1180.127AA, BCB, C
IL-130.8050.7620.6240.648AA, BCB, C
IL-40.1270.1150.0900.096AA, BCB, C
IL-50.0040.0030.0020.003ABCB, C
CRP15.63712.74312.3855.809AAAB
Eotaxin0.0770.0640.0590.059AA, BBB
GM-CSF0.0100.0080.0080.008ABBB
IFNγ0.5300.4460.3780.386AA, BBB
IL-100.8750.4900.4230.244AA, BBB
IL-150.0050.0030.0030.003ABBB
IL-160.4660.3450.3420.295ABBB
IL-60.1960.1920.1680.150AAA, BB
IL-70.0040.0030.0030.003ABBB
IL-8856.276652.066567.361572.602ABBB
MCP-10.0530.0470.0390.039AA, BBB
MDC0.3990.4070.3450.339AABB
SAA7.0396.9056.0925.162AAA, BB
Tie-20.2730.2390.2670.221AA, BAB
VCAM-14.9713.7063.1562.892ABBB
VEGF0.6250.5110.4780.480ABBB
VEGF 20.7720.6610.6200.582ABBB
VEGF-D0.0570.0520.0510.045AA, BA, BB
VEGF-C0.1450.1490.1250.137A, BABA, B
TARC0.0200.0290.0190.019ABAA
bFGF0.0200.0150.0120.013AAAA
Eotaxin-30.0950.1080.0910.094AAAA
Flt-10.3900.5180.4330.415ABA, BA
IL-12p400.0390.0310.0280.031AAAA
IL-20.1660.1990.2100.162AAAA
IL-8 (HA)47.50844.36241.26039.119AAAA
IP-100.5401.6880.7400.606AAAA
MCP-40.0230.0230.0200.022AAAA
MIP-1α0.0910.0910.0840.080AAAA
MIP-1β0.0910.1000.1100.094AAAA
TNFα2.0092.0672.0211.670AAAA

Example 4

The same gingival-brush samples as described in EXAMPLE 3 were used for metabonomic analyses. Fourteen volunteers were selected randomly from treatment or control regimen (Test regimen: Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse; Control regimen (negative control): Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush), to determine if any metabolite concentrations were changed in gingival samples during the first 3 weeks of treatment. Both baseline and week 3 samples were sent in dry ice to Metabolon, Inc. (Durham, N.C.) for metabonomic measurement. 170 metabolites were identified and quantified. As shown in TABLE 2, some metabolite concentrations were changed during the first 3 weeks of treatment. Citrulline concentrations in the gingival samples were reduced after 3 weeks of treatment in the treatment regimen group. Similarly, ornithine was also reduced in the treatment regimen group after 3 weeks of treatment. Reduction of citrulline and ornithine was likely associated with alleviation of gingivitis as citrulline was reported to be associated with endotoxin treatment (Tannahill GM1, Curtis A M, Adamik J, Palsson-McDermott E M, McGettrick A F, Goel G, Frezza C, Bernard N J, Kelly B, Foley N H, Zheng L, Gardet A, Tong Z, Jany S S, Corr S C, Haneklaus M, Caffrey B E, Pierce K, Walmsley S, Beasley F C, Cummins E, Nizet V, Whyte M, Taylor C T, Lin H, Masters S L, Gottlieb E, Kelly V P, Clish C, Auron P E, Xavier R J, O'Neill L A. Succinate is an inflammatory signal that induces IL-1β through HIF-1α. Nature. 2013 Apr. 11; 496(7444):238-42. doi: 10.1038/nature11986. Epub 2013 Mar. 24.). As shown in TABLE 2, deoxycarnitine was higher in gingivitis (baseline), indicative of abnormal β-oxidation of fatty acid. Succinate is an intermediate in the citric acid cycle. Succinate (which is an intermediate in the citric acid cycle) levels increased in gingivitis, as shown in TABLE 2.

TABLE 2
Comparison of metabolites in gingival brush samples between
baseline and week 3 during gingivitis treatment
3
Base-3week/
lineweekbase-p-q-
Biochemical NamemeanmeanlinevaluevalueMass
13-HODE +1.08770.70880.650.06010.1338295.2
9-HODE
1-arachidonoyl-1.22940.82740.670.0380.1035500.3
glycerophospho-
ethanolamine
1-oleoylglycero-0.73781.07471.460.07670.1548478.3
phosphoethanol-
amine
2-methylbutyryl-1.77690.69970.390.00340.0546246.1
carnitine (C5)
adenosine 5′-1.40920.84510.60.02950.0956348.1
monophosphate
(AMP)
alanine0.87211.1021.260.03180.0973115.9
arginylleucine1.44470.68190.470.00840.0777288.3
arginylphenyl-0.96160.33350.350.01190.0777322.2
alanine
asparagylleucine0.92950.61220.660.06980.1465246.2
citrulline1.01470.710.70.01040.0777176.1
deoxycarnitine3.23810.60880.190.00030.0168146.1
EDTA1.59850.83840.520.01380.0777291.1
erythritol1.6250.80850.50.05820.1325217
fructose1.99331.11060.560.08470.1605217
glutamine1.24590.83660.670.03740.1035147.2
glutathione,1.01611.46691.440.0870.1605613.1
oxidized (GSSG)
glycerol1.37830.83080.60.03910.1035205
lauryl sulfate1.6850.86230.510.03970.1035265.2
leucine1.21580.93590.770.06130.1338132.2
leucylleucine0.95050.43930.460.02510.0877245.1
lysylleucine1.20090.52750.440.00360.0546260.2
lysylphenylalanine1.16820.45630.390.00950.0777294.3
maltose0.87271.44811.660.0220.0877204.1
maltotriose1.04561.83471.750.08580.1605204
mannitol1.30040.79820.610.0420.107319.1
ornithine1.29160.70690.550.03670.1035141.9
palatinitol1.43950.82720.570.07820.1549204
phosphate1.40080.83760.60.02080.0877298.9
proline1.4050.990.70.00330.0546116.1
propionylcarnitine1.25650.76880.610.02010.0877218.2
pyroglutamine1.34240.78730.590.01360.0777129.2
serylisoleucine1.17530.71690.610.08140.1583219.2
spermidine1.16130.86780.750.06870.1465146.2
succinate1.29290.81130.630.07540.1548247
threonylleucine1.15130.49310.430.00440.0594231.2
threonylphenyl-1.76930.9180.520.02330.0877267.2
alanine
trehalose2.35630.90840.390.00540.0647361.2
tryptophan1.15180.90890.790.04870.1185205.1
tyrosine1.3831.02990.740.01610.0787182.1
valine1.15980.92710.80.03040.0956118.1
valylvaline0.93470.82310.880.05080.1207215.2
X- 136710.50350.9181.820.05450.1267315.3
X- 145881.36470.83780.610.0240.0877151
X- 161031.36430.84610.620.02970.095699.3
X- 172661.31580.5760.440.00030.0168530.4
X- 173751.47850.83870.570.01890.0877357.1
X- 184720.61381.14411.860.00110.0405827.1
X- 187791.37560.80350.580.01620.0787209.1
X- 196071.52370.71670.470.0020.0537366.1
X- 196091.32840.77210.580.0160.0787204
X- 196121.38960.78430.560.010.0777427.2
X- 196131.34120.75350.560.00990.0777429.3
X- 196141.33780.73430.550.04540.113570.1
X- 198071.34780.84110.620.02440.087793
X- 198081.33480.83680.630.02540.087795
X- 198501.35760.75190.550.0110.0777334.2
X- 198571.33570.80320.60.0380.1035230
X- 200001.27840.75360.590.01330.077781.2

Example 5

Quantitation of citrulline and ornithine from the extracts of the same Gingival-brush samples as described in EXAMPLE 2, was conducted using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). The gingival-brush samples were placed into extraction buffer as described in EXAMPLE 1. The supernatants were subject to both HILIC/MS/MS and BCA analysis. For free citrulline and ornithine analysis, the extracts of the Gingival-brush samples were analyzed either directly (50 μl of gingival brush extract with 50 μl sample solution sample solution (50/50 acetonitrile/ultra-pure water with 0.754% formic acid) or diluted 5 fold with sample solution. For total citrulline and ornithine analysis, the extracts of the Gingival-brush samples were first hydrolyzed using 6 N HCl (50 μL of extract with 450 μL of 6N HCl), no shaking, and placed on a hot plate at 110° C. for 16 hours. The hydrolyzed samples were then dried down under vacuum at room temperature (Savant speedvac of Lifetechnology, Grand Island, N.Y.) and then reconstituted in 1 ml of dilution solution (50/50 acetonitrile/ultra-pure water with 0.754% formic acid) for analysis. The standards and the samples were analyzed using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Analytes and the corresponding ISTDs (stable isotope labeled internal standard) were monitored by electrospray ionization (ESI) in positive mode using the selected-reaction-monitoring schemes shown in TABLE 3. A standard curve was constructed by plotting the signal, defined here as the peak area ratio (peak area analyte/peak area ISTD), for each standard versus the mass of each analyte for the corresponding standard. The mass of each analyte in the calibration standards and Gingival-brush extract samples were then back-calculated using the generated regression equation. The concentration of protein bound citrulline or ornithine was calculated as the result of subtracting the concentration of free citrulline or ornithine from the concentration of total citrulline or ornithine, respectively. As shown in TABLE 3, the result was reported as the concentration of citrulline or ornithine or the result was standardized by dividing by the amount of citrulline or ornithine by the amount of the total proteins that were found in the extract.

TABLE 3
Multiple Reaction Monitoring (MRM) transitions for analytes and
their corresponding stable isotope labeled internal standards
AnalytesMRMInternal StandardsMRM
Citrulline176 → 159d7-Citrulline181 → 164
Ornithine133 → 70d6-Ornithine139 → 76

All samples in the regimen treatment, as described in EXAMPLE 2, were analyzed. As shown in FIG. 5, citrulline levels reduced rapidly in the first week of treatment, and then continued to decline gradually in weeks 3 and 6 of treatment. These results are consistent with clinical observations, where gingival bleeding sites (GBI) and the gingival inflammation (MGI) were reduced over the 6-week treatment period.

Example 6

The same gingival-brush samples were collected using the procedures described in EXAMPLE 1, from the same volunteers as in EXAMPLE 2. Before sampling, volunteers rinsed their mouths for 30 seconds with water. A dental hygienist then sampled the area just above the gumline using a buccal swab brush (Epicentre Biotechnologies, Madison, Wis., cat. #MB100SP). The swab was immediately placed into 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Lifetechnologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube vortexed for 30 seconds, and immediately frozen on dry ice and stored in a −80 C freezer until analysis. The samples were taken out of the freezer, thawed and extracted by placing the samples on a tube shaker for 30 minutes at 4° C. The tubes were centrifuged at 15000 RPM for 10 min in Eppendorf Centrifuge 5417R (Eppendorf, Ontario, Canada) to pellet any debris. The extract (800 μl) was analyzed for protein concentrations using the Bio-Rad protein assay (BioRad, Hercules, Calif.). Subjects with gingivitis followed test regimen for 6 weeks (Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse). Baseline (BL) represents diseased status. Symptoms of gingivitis, such as bleeding and inflammation were alleviated at week 1 to week 6 treatments. Protein bound ornithine (the difference between total and the free ornithine) was higher in gingivitis as shown in FIG. 6. Protein bound ornithine was reduced gradually as gingivitis was decreased in severity.

Example 7

Separate gingival samples were collected as described in EXAMPLES 1 and 3, from the same volunteers as in EXAMPLE 2, and were used to examine the expression of genes during 6 weeks of treatment. After harvesting the samples, the brush was completely immersed in RNAlater solution (1 ml in in a 1.5 ml Eppendorf tube) to prevent RNA degradation during transport and storage (Qiagen, Valencia, Calif.). The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

The ornithine-citrulline-arginine cycle consists of four enzymes (FIG. 7). The main feature of the cycle is that three amino acids can be converted to each other. The first enzyme is ornithine carbmoyltranferase, which transfers a carbamoyl group from carbamoyl phosphate to ornithine to generate citrulline. This reaction occurs in the matrix of the mitochondria. Expression of ornithine carbmoyltranferase was reduced in the treatment (FIG. 8). The second enzyme is argininosuccinate synthase. This enzyme uses ATP to activate citrulline by forming a citrullyl-AMP intermediate, which is attacked by the amino group of an aspartate residue to generate argininosuccinate. This reaction and the subsequent two reactions (argininosuccinate to arginine and arginine to ornithine) occur in cytosol. Again, expression of argininosuccinate synthetase decreased during the treatment. The third enzyme is argininosuccinate lyase, which catalyzes cleavage of argininosuccinate into fumarate and arginine. The last enzyme is argininase. Argininases cleave arginine to produce urea and ornithine. In a contrast to the decreased expression of both ornithine carbmoyltranferase and argininosuccinate synthetase genes, argininase I (liver) and II increased (FIG. 8).

Arginine is also a substrate for nitric oxide synthases, which oxidizes arginine to produce citrulline and nitric oxide. Expression of nitric oxide synthase 3 gene increased too (FIG. 8).

Example 8

Experimental gingivitis: Another clinical study was carried out to determine whether citrulline is increased in experimentally induced gingivitis in healthy human volunteers. This was a case-control study enrolling 60 volunteers. The study population included two groups as follows: Group 1 or high bleeders group, thirty (30) volunteers with at least 20 bleeding sites, where bleeding is a GBI site score of 1 or 2 at baseline. Group 2, or low bleeders group, thirty (30) volunteers with 2 or less bleeding sites, where bleeding is a GBI site score of 1 or 2.

The study consisted of two Phases: Health/Rigorous Hygiene Phase with a dental cleaning procedure to thoroughly clean the teeth, polishing and rigorous oral hygiene; and induced gingivitis phase without oral hygiene. At the Screening visit, volunteers underwent an oral soft tissue assessment and had a gingivitis evaluation (Modified Gingival Index (MGI) and Gingival Bleeding Index (GBI). At Visit 2 (following the screening visit) participants received an oral soft tissue exam followed by a gingivitis evaluation, and gingival samples were collected, as described below, for host biomarker analysis. Following that, all volunteers entered the Health/Rigorous Hygiene Phase, lasting two weeks. After two weeks of rigorous hygiene, all volunteers entered the Induced Gingivitis Phase, lasting for three weeks. Oral soft tissue exams and gingivitis were re-evaluated and all gingival samples were collected at Baseline, WK0 and WK2.

Gingival sample collection—A gingival brush sample was collected from each side of the upper arch using the procedures as described in EXAMPLE 1. Gingival brush samples were collected close to the gumline from the buccal sites only (preferably from four adjacent teeth—preferably from premolar and molar areas). Volunteers rinsed for 30 seconds with 15 ml of Listerine rinse to clean the surface of sampling area. After the Listerine rinse, volunteers rinsed for 30 seconds with 20 ml of water. Following that, selected sites were isolated with a cotton roll and gently dried with an air syringe and two gum swabs were taken with collection brushes/swabs from the gingiva region close to the gumline of the selected teeth. The samples were placed in a pre-labeled (volunteer ID, sample ID, visit, and date) vial containing 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Life Technologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube. The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. Samples from three visits were analyzed using the procedures as described as in EXAMPLE 5, and shown in FIG. 9. Those three visits were baseline, Week 0, (right after the Health/Rigorous Hygiene Phase and before the induced gingivitis phase) and week 2 (at the end of Induced Gingivitis Phase). Free citrulline levels were low in both the high and low bleeders groups at the baseline and week 0, but rose quickly in the induced gingivitis in both groups at week 2.

Example 9

The same procedures were used as described in EXAMPLE 5. The samples were the same as described in EXAMPLE 8. Protein bound citrulline was lower at the baseline than that at week 0 in both high and low bleeders groups, as shown in FIG. 10 in gingival tissue. It was low in experimental gingivitis in both groups at week 2.

Example 10

The same gingival brush samples from experimental gingivitis, as described in EXAMPLE 8 were analyzed using the procedures described in EXAMPLE 5. The bound ornithine was the lowest at week 0 (FIG. 11) in both groups. Its levels at the baseline were higher than those at week 0. The bound ornithine reached peaks when gingivitis was induced in both groups at week 2. Also it is worth noting the total ornithine (Free and protein bound ornithine) was increased in the induced gingivitis (FIG. 12) in both groups.

Example 11

Levels of Proteins Containing Arginine Decreased in Gingival Samples in Experimentally Induced Gingivitis

The same gingival brush samples from experimental gingivitis, as described in EXAMPLE 8 were analyzed using the procedures as described in EXAMPLE 5. The protein bound arginine was the lowest in induced gingivitis (FIG. 13) in both groups. Its levels were higher in WK0 than that at baseline in both groups. The total arginine in the gingival brush samples displayed the same patterns as the protein bound one (FIG. 14).

Example 12

Human primary blood mononuclear cells were isolated from blood obtained from Gulf Coast Regional Blood Center, Houston, Tex., USA, using Histopaque 1077 (Sigma Aldrich Co., St. Louis, Mo.) and Leucosep tubes (Greiner Bio-One, Monroe, N.C.). The cells were cultured in 200 μl of Roswell Park Memorial Institute (RPMI) 1640 medium in each well of a 90-well plate (ThermoFisher Scientific, Inc., Grand Island, N.Y.) containing 10% fetal bovine serum and 1% penicillin/streptomycin antibiotics at 37° C. with a 5% CO2 atmosphere. B. subtilis LTA, S. aureus LTA, P. gingivalis LPS and E. coli LPS were purchased from Invivogen (San Diego, Calif.). Human dental plaques were harvested in a controlled clinical examiner-blind study. Forty (40) volunteers were used, twenty (20) of which were qualified as healthy—each having up to 3 bleeding sites and with all pockets less than or equal to 2 mm deep; and twenty (20) volunteers were qualified as unhealthy—greater than 20 bleeding sites with at least 3 pockets greater than or equal to 3 mm but not deeper than 4 mm with bleeding, and at least 3 pockets less than or equal to 2 mm deep with no bleeding for sampling. Volunteers had up to 6 sites identified as “sampling sites”. “Sampling sites” had supragingival and subgingival plaque collected at Baseline, Week 2 and Week 4. Subgingival plaque samples were taken from a gingival sulcus from the pre-identified sites. Prior to sample collection, the site had supragingival plaque removed with a curette. The site was dried and subgingival plaque sample were collected with another dental curette (e.g., Gracey 13/14, 15/16, 11/12, 7/8, 1/2). Samples from each site were placed in a pre-labeled 2.0 ml sterile tube containing 300 μl DPBS buffer with about 30 glass beads of 1 mM in diameter. Samples were stored at 4° C. and shipped overnight at 4° C. The subgingival samples were stored at −80° C. freezer until being analyzed. The samples were thawed and dispersed in a TissueLyser II (Qiagen, Valencia, Calif., USA) at 30 shakes per second for 3 min. Protein concentrations of the dispersed subgingival samples were measured using a Pierce microBCA Protein kit (ThermoFisher Scientific, Grand Island, N.Y., USA) following the manufacturer's instruction.

The cells were seeded onto 96-well at 100,000 cells per well in 200 μl of RPMI 1640 medium in each well (ThermoFisher Scientific, Inc., Grand Island, N.Y., USA) containing 10% fetal bovine serum and 1% penicillin/streptomycin antibiotics, and treated with clinical samples and bacterial components. The cells were then incubated for 24 hours at 37° C. with a 5% CO2 atmosphere. Cells were harvested with medium into a 15 ml polypropylene conical tube at the end of experiment. Cells were separated from medium by centrifugation at 1000 RPM for 10 min at 4° C., and immediately frozen and stored at −80° C. until analysis. The samples were analyzed using the procedures as described in EXAMPLE 5.

The human subgingival plaques were pooled from 60 subgingival plaques of bleeding sites. The pooled samples stimulated production of citrulline, arginine and ornithine in primary human peripheral blood mononuclear cells (TABLE 4). Similarly, they also increased malic acid, fumaric acid and succinic acid in the same cells. LPS and LTA also increased production of citrulline, ornithine, arginine and succinic acid in the human primary peripheral blood cells.

TABLE 4
Human subgingival plaques, LPS and LTA increased production of citrulline, ornithine,
arginine and succinic acid in human primary peripheral blood mononuclear cells.
MalicFumaricSuccinic
Treatment DoseArginineCitrullineOrnithineAcidAcidAcid
Sample Treatmentng/mlng/mlng/mlng/mlng/mlng/mlng/ml
LPS-E. coli900 ng/ml2810040826975651161140
LPS-P. gingivalis100 ng/ml4293127143676501291740
LTA-S. aureus900 ng/ml3891954441456281371290
LTA-B. subtilis900 ng/ml3541530342007881791300
human subgingival plaques 19 ng/ml proteins5927953975809192022530
Cells OnlyCulture medium237331212394559127825

Example 13

Separate gingival samples were collected as described in EXAMPLES 1 and 3, from the same volunteers as in EXAMPLE 2, and were used to examine the expression of genes during the six week treatment. After harvesting the samples, the brush was completely immersed in the RNAlater solution to prevent RNA degradation during transport and storage (Qiagen, Valencia, Calif.). The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

Claudins are a family of proteins that are the most important components of the tight junctions, where they establish the paracellular barrier that controls the flow of molecules in the intercellular space between the cells of an epithelium. They have four transmembrane domains, with the N-terminus and the C-terminus in the cytoplasm. Similar to keratins, different claudins are expressed in different layers of keratincoytes during differentiation. Claudins are important components in barrier functions. As shown in TABLE 5, CLDN 1 and 12 decreased during the treatment while CLDN17 and 23 increased. Those changes can be explored as biomarkers in gingivitis.

TABLE 5
Expression of genes for claudins in gingival brush samples during
treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
claudin 111728234_a_atCLDN16.946.536.466.300.000.000.00
claudin 1211720206_s_atCLDN126.436.276.266.220.010.000.00
claudin 1711738572_atCLDN177.428.108.278.100.000.000.00
claudin 2311728603_a_atCLDN237.267.527.567.580.000.000.00

Peptidylarginine deiminases catalyze a form of post translational modification called arginine de-imination or citrullination. These family members have distinct substrate specificities and tissue-specific expression patterns. Peptidyl arginine deiminase, type I, also known as PADI1 is involved in the late stages of epidermal differentiation, where it deiminates filaggrin and keratin K1, which maintains hydration of the stratum corneum, and hence the cutaneous barrier function. PADI2 is widely expressed. Its known substrates for PADI2 include myelin basic protein in the central nervous system and vimentin in skeletal muscle and macrophages. PADI3 is involved in both hair and skin differentiation. As shown in TABLE 6, PADI1 increased while PADI2 decreased during the treatment periods. Those changes can be used as biomarkers of gingivitis severity.

TABLE 6
Expression of genes for peptidylarginine deiminases in gingival brush
samples during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
peptidyl arginine deiminase, type I11751221_a_atPADI18.728.809.029.050.0000.0000.000
peptidyl arginine deiminase, type I11751731_a_atPADI17.557.717.907.920.0010.0000.000
peptidyl arginine deiminase, type I11729333_atPADI110.1710.1310.3210.370.0020.0000.003
peptidyl arginine deiminase, type II11727597_atPADI26.986.746.616.510.0080.0000.000
peptidyl arginine deiminase, type II11745141_a_atPADI26.616.556.576.550.0110.0270.003
peptidyl arginine deiminase, type III11736978_atPADI36.676.736.916.870.0050.0010.000
peptidyl arginine deiminase, type VI11741173_atPADI64.544.524.514.530.0100.0080.219

Keratin is a family of fibrous structural proteins, the key structural material making up the outer layer of human skin, oral mucosa and gingivae. Keratins provide the necessary strength and barrier functions. Keratin monomers assemble into bundles to form intermediate filaments. Keratin compositions change in keratinocytes when they move outward from stratum basale, to spinosum, granulosum and corneum. As shown in TABLE 7, expression of keratin genes changed significantly during the treatment period. Those changes can be used as biomarkers of gingivitis severity.

TABLE 7
Expression of genes for keratins in gingival brush samples during
treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
keratin 1311747755_a_atKRT1311.7211.9311.9411.940.000.000.00
keratin 1511728288_a_atKRT159.178.858.778.710.090.000.00
keratin 1811757905_x_atKRT188.188.578.708.700.000.000.00
keratin 3111731269_atKRT315.405.525.615.610.160.000.00
keratin 411739440_a_atKRT410.9811.3911.4811.570.000.000.00
keratin 6A11747769_x_atKRT6A10.0510.3810.2710.250.020.050.14
keratin 6B11723983_atKRT6B7.808.368.248.110.010.000.09
keratin 6C11727492_atKRT6C7.878.548.238.130.000.050.25
keratin 711715683_a_atKRT76.486.236.235.890.140.000.00
keratin 8011728960_a_atKRT807.928.118.208.130.000.000.00

To provide protection against external environment and microbial, gingival keratinocytes undergo differentiation. Expression of differentiation genes, such as involucrin, loricrin, filaggrin, envoplakin and periplakin genes, are elevated as keratinocytes migrate outward from stratum basale to corneum. As shown in TABLE 8, expression of those differentiation genes was elevated during treatment. The increased expression of keratinocyte differentiation genes can be used as biomarkers of gingivitis severity.

TABLE 8
Expression of genes for keratinocyte differentiation in gingival brush
samples during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group meansAnalysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
envoplakin11726123_a_atEVPL7.618.038.128.150.000.000.00
filaggrin11741116_atFLG9.139.459.489.490.000.000.00
involucrin11731653_a_atIVL8.819.369.559.550.000.000.00
loricrin11731852_atLOR5.956.366.336.630.120.110.01
periplakin11722429_s_atPPL8.328.798.868.850.000.000.00
periplakin11750591_a_atPPL7.197.687.797.780.000.000.00
periplakin11722428_a_atPPL7.598.098.168.160.000.000.00
periplakin11722430_atPPL11.2711.3411.4311.410.000.000.00

Example 14

The same gingival samples, as described as in EXAMPLE 13, were used to examine the expression of genes during the six week treatment. After harvesting the samples, the brush was completely immersed in the RNAlater solution to prevent RNA degradation during transport and storage (Qiagen, Valencia, Calif.). The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

15-Lipoxygenase and 5-lipoxygenase are highly regulated lipid-peroxidating enzymes whose expression and their metabolites are implicated in several important inflammatory conditions. As shown in TABLE 9, ALOX15B, ALOX5, ALOX5AP and PTGS2 decreased during treatment. Their changes can be used as biomarkers of gingivitis severity.

TABLE 9
Expression of genes for metabolizing polyunsaturated fatty acids in gingival
brush samples during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
arachidonate 15-lipoxygenase, type B11734619_x_atALOX15B6.105.735.615.660.000.000.00
arachidonate 15-lipoxygenase, type B11752283_a_atALOX15B5.555.295.235.250.020.000.00
arachidonate 5-lipoxygenase11726337_a_atALOX55.114.974.974.930.000.000.00
arachidonate 5-lipoxygenase-activating11719479_atALOX5AP7.196.846.756.740.000.000.00
protein
prostaglandin-endoperoxide synthase 211724037_atPTGS27.807.307.137.060.050.000.00

Example 15

The same gingival samples, as described in EXAMPLE 13, were used to examine the expression of genes during the six week treatment. After harvesting the samples, a brush was completely immersed in RNAlater solution to prevent RNA degradation during transport and storage (Qiagen, Valencia, Calif.). The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Banos S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

Glutathione peroxidase (GPX) was increased during treatment. It is an enzyme with peroxidase activity. Its main biological role is to protect the organism from oxidative damage. The biochemical function of glutathione peroxidase is to reduce lipid hydroperoxides to their corresponding alcohols and to reduce free hydrogen peroxide to water. As shown in TABLE 10, both GPX1 and GPX3 were increased during treatment. Their changes represent reduction in gingivitis severity.

TABLE 10
Expression of genes for glutathione peroxidases in gingival brush samples
during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
glutathione peroxidase 111725346_x_atGPX16.436.766.606.560.000.000.01
glutathione peroxidase 311730170_a_atGPX35.565.996.046.020.000.000.00
(plasma)

Example 16

The same gingival samples were collected and analyzed as described in EXAMPLE 13. β-oxidation is the catabolic process in which chain fatty acid molecules with different lengths are cleaved in the cytosol in the mitochondria in eukaryotes to generate acetyl-CoA. The latter enters the citric acid cycle and results in production of ATP subsequently.

Many enzymes are involved in this process. As shown in TABLE 11, expression of those genes increased during treatment. Increase in their expression is indicative of the improvement in ATP production in the gingival tissue.

TABLE 11
Expression of genes for the citric acid cycle, β-oxidation, and oxidative phosphorylation
in gingival brush samples during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
Group means (log2)(Surrogate Variable
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
acyl-CoA dehydrogenase, C-4 to C-1211722357_a_atACADM7.187.527.467.450.000.000.00
straight chain
acyl-CoA dehydrogenase, C-4 to C-1211757536_s_atACADM7.738.057.957.850.000.000.00
straight chain
carnitine O-octanoyltransferase11720743_x_atCROT6.296.436.566.510.000.000.00
carnitine O-octanoyltransferase11720744_a_atCROT4.854.894.934.920.070.000.07
electron-transferring-flavoprotein11749144_s_atETFDH6.126.426.476.450.000.000.00
dehydrogenase
NADPH dependent diflavin oxidoreductase 111734007_s_atNDOR16.887.167.297.070.000.000.00
NADH dehydrogenase (ubiquinone) 1 alpha11716354_a_atNDUFA117.177.417.437.330.000.000.00
subcomplex, 11, 14.7 kDa
NADH dehydrogenase (ubiquinone) 1 alpha11717202_x_atNDUFA4L26.386.836.856.850.000.000.00
subcomplex, 4-like 2
NADH dehydrogenase (ubiquinone) 1 alpha11718765_a_atNDUFA66.436.796.866.780.000.000.00
subcomplex, 6, 14 kDa
NADH dehydrogenase (ubiquinone) 1 beta11717251_s_atNDUFB118.458.898.918.860.000.000.00
subcomplex, 11, 17.3 kDa
NADH dehydrogenase (ubiquinone) 1 beta11745384_s_atNDUFB47.037.387.357.270.000.000.00
subcomplex, 4, 15 kDa
succinate dehydrogenase complex, subunit11749757_x_atSDHA7.677.948.117.990.000.000.00
A, flavoprotein (Fp)
succinate dehydrogenase complex, subunit11747868_x_atSDHA7.617.917.987.970.000.000.00
A, flavoprotein (Fp)
ubiquinol-cytochrome c reductase, complex11757670_a_atUQCR106.436.676.656.550.000.000.00
III subunit X
ubiquinol-cytochrome c reductase, complex11757334_a_atUQCR117.067.277.267.250.000.000.00
III subunit XI

The dimensions and values disclosed herein are not to be understood as being strictly limited to the exact numerical values recited. Instead, unless otherwise specified, each such dimension is intended to mean both the recited value and a functionally equivalent range surrounding that value. For example, a dimension disclosed as “40 mm” is intended to mean “about 40 mm.”

Every document cited herein, including any cross referenced or related patent or application and any patent application or patent to which this application claims priority or benefit thereof, is hereby incorporated herein by reference in its entirety unless expressly excluded or otherwise limited. The citation of any document is not an admission that it is prior art with respect to any invention disclosed or claimed herein or that it alone, or in any combination with any other reference or references, teaches, suggests or discloses any such invention. Further, to the extent that any meaning or definition of a term in this document conflicts with any meaning or definition of the same term in a document incorporated by reference, the meaning or definition assigned to that term in this document shall govern.

While particular embodiments of the present invention have been illustrated and described, it would be obvious to those skilled in the art that various other changes and modifications can be made without departing from the spirit and scope of the invention. It is therefore intended to cover in the appended claims all such changes and modifications that are within the scope of this invention.

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Patent 2018

Example 1

Growth of bacteria: A 1 ml aliquot of a 24 hour culture of E. coli ATCC 8739 was used to inoculate 100 ml of Luria-Bertani (LB) broth in a 250 ml baffled flask. This culture was then incubated at 37° C. with agitation (220 rpm) and sampled at 30 minute intervals. Samples were assessed for turbidity (OD600) in a SpectraMax platereader M3 (Molecular Devices, Sunnydale, Calif.), which is one method of monitoring the growth and physiological state of microorganisms. The sample turbidity was then recorded and the samples were centrifuged at 5000 RPM for 10 min at room temperature. The supernatant, thereinafter referred to as “supernatant of bacterial culture”, was subsequently analyzed for LPS content using the procedure as described below.

Twenty ml aliquots of MTGE broth (Anaerobe Systems, Morgan Hill, Calif.) were inoculated with P. gingivalis ATCC 33277, P. pallens ATCC 700821, or P. nigrescens ATCC 25261. These cultures were incubated overnight in a Whitely A45 Anaerobic Workstation (Don Whitley Scientific, Frederick, Md.) at 37° C. with an 85:10:5 N2:CO2:H2 gas ratio. One ml aliquots of these starter cultures were then used to inoculate 99 ml of membrane-Tryptone Glucose Extract (m-TGE) broth in a 250 ml baffled flask. These cultures were then incubated under agitation (200 rpm) as previously described and sampled at regular intervals. Samples were assessed for turbidity (OD600) in a Tecan Infinite m200 Pro (Tecan Trading AG, Switzerland) and then centrifuged at 16,100×g for 10 min at room temperature. Supernatants were decanted and passed through a 0.22 μM filter prior to analysis for LPS content.

In the experiment, only OD600 was measured. For the sake of consistency in following experiments, we converted OD600 readings into bacterial numbers, even though the relationship between OD600 readings and bacterial numbers is varied for each bacterium. The number of bacteria was estimated based on spectrophotometer readings at OD600 (OD600 of 1.0=8×108 cells/ml).

The Limulus Amebocyte Lysate Assay (LAL) is an assay to determine the total amount of lipopolysaccharide (LPS) in the sample tested (Pierce LAL Chromogenic Endotoxin Quantitation Kit, ThermoFischer Scientific, Waltham, Mass.). The assay was performed following manufacturer's instruction. Ninety-six-well microplates were first equilibrated in a heating block for 10 min at 37° C. Fifty μl each of standard or sample was dispensed into the microplate wells and incubated with plate covered for 5 min at 37° C. Then 50 μl LAL was added to each well. Plates were shaken gently and incubated for 10 min at 37° C. 100 μl of chromogenic substrate was added and incubated for 6 min at 37° C. Finally, 50 μl Stop Reagent was added and the absorbance was measured at 405-410 nm on Spectramax M3 platereader (Molecular Device, Sunnyvale, Calif.).

FIGS. 1A, 1C, and 1D show the ability of microbes to shed LPS as part of their normal growth cycle. This data shows the need to deliver chemistry to the subgingival plaque to effectively mitigate the LPS, since tooth brushing generally does not remove the subgingival plaque.

The LPS, as measured by the LAL kit reported in endotoxin unit per ml (EU/ml), was shed by the bacteria (E. coli K12) as depicted in FIG. 1A. The growth media began to be depleted of complex sugars around 120 minutes, as reflected in the bacterial growth curve in FIG. 1B, where the LPS shedding started to decline. This data gave a reason to believe that a mature biofilm/plaque could supply a constant level of LPS to the host cells, if food sources were present. The LPS would then have the ability to induce an inflammatory response from the host cells.

Importantly, LPS are secreted into the supernatant of bacterial culture (FIG. 1D). LPS also exists in bacterial walls (FIG. 1E). Again, this data further enforce the need to deliver chemistry to the subgingival plaque to effectively mitigate the LPS, since tooth brushing generally does not remove the subgingival plaque.

Example 2

Seven panelists, with at least three bleeding sites, took part in the testing. A licensed dental hygienist collected subgingival plaque samples. Samples were taken at the tooth/gum interface (buccal surfaces only) using care to avoid contact with the oral soft tissues. Six subgingival plaque sites were sampled from each panelist (3 healthy and 3 unhealthy sites). Unhealthy teeth had bleeding sites with pockets greater than 3 mm and healthy sites had no bleeding with pocket depth less than 2 mm Prior to sampling, panelists were instructed to abstain for 12 hours from oral hygiene and refrain from eating, chewing gum, drinking (except small sips of water). Next, panelists had their marginal plaque collected with a curette at the sampling sites. Then, from the same site, subgingival plaque samples were collected with 3 consecutive paper points as shown in FIG. 1F. The sampling sites were isolated with cotton rolls and gently air-dried. Paper points (PROFLOW incorporated, Amityville, N.Y.) were gently placed for 10 seconds into the pocket until a minimum of resistance was felt. After 10 seconds, paper points were removed and placed into pre-labeled 1.5 ml tubes. The same sampling procedure was repeated with 2 more paper points (paper points go into separate tubes). The first, second and third sample paper points from a healthy site of all panelists were pooled separately into three tubes, labeled as paper point 1, 2 and 3, respectively. Similarly the unhealthy site samples were also pooled.

TABLE 1 showed that unhealthy dental plaques contained more endotoxins than the healthy dental plaques. One m1 PBS was added to each pooled sample in the 1.5 ml tube. Bacteria were lysed in a MolBio Fast Prep bead beater (MP Biomedicals, Santa Ana, Calif.). Samples were centrifuged for 10 min at 10,000 RPM at 4° C., supernatants were collected and analyzed with LAL assay kits following manufacturer's instruction as described in EXAMPLE 1.

TABLE 1
Protein concentrations and endotoxin
levels in the pooled dental plaque samples.
Endotoxin
Dental plaque(endotoxin unit)
Healthy paperpoint 1 sub plaque1284
Healthy paperpoint 2 sub plaque476
Healthy paperpoint 3 sub plaque361
Healthy Marginal Plaque23180
Unhealthy paperpoint 1 sub plaque3371
Unhealthy paperpoint 2 sub plaque1732
Unhealthy paperpoint 3 sub plaque16111
Unhealthy Marginal Plaque80277

It was expected that the marginal plaques in unhealthy sites had more endotoxins than those in the healthy sites (TABLE1) within the same subjects. Three samples were taken from subgingival pockets with three paper points sequentially, named paper point 1, 2 and 3. Again, the subgingival plaques taken by the paper point 1 had more endotoxins in the unhealthy sites than in the healthy sites (TABLE 1). The same is true for the samples taken by paper point 2 and 3. Importantly, dental plaques in the unhealthy subgingival pockets possessed more endotoxins than plaques from healthy pockets. This may explain why unhealthy gingiva are prone to bleeding upon probing.

Example 3

The LAL assay, as described in EXAMPLE 1, was modified for development of technology which inhibits LPS from activating a proenzyme in the LAL assay. The Thermo Scientific Pierce LAL Chromogenic Endotoxin Quantitation Kit is a quantitative endpoint assay for the detection of LPS, which catalyzes the activation of a proenzyme in the modified Limulus Amebocyte Lysate (LAL). The activated proenzyme then splits p-Nitroaniline (pNA) from the colorless substrate, Ac-Ile-Glu-Ala-Arg-pNA. The product pNA is photometrically measured at 405-410 nm. If SnF2 binds to LPS, the latter can't react with the proenzyme in the LAL kit. Consequently, the proenzyme is not activated, and the colorless substrate Ac-Ile-Glu-Ala-Arg-pNA will not split and no color product is produced. P. gingivalis LPS 1690 (1 ng/ml), or E. coli LPS (1 ng/ml), and stannous fluoride and other materials (50 and 500 μM), as listed in TABLE 2, were dissolved in endotoxin-free water. Then 50 μl LAL was added to each well. Plates were shaken gently and incubated for 10 min at 37° C. 100 μl of chromogenic substrate was added and incubated for 6 min at 37° C. Finally, 50 μl Stop Reagent was added and the absorbance was measured at 405-410 nm on Spectramax M3 plate reader (Molecular Device, Sunnyvale, Calif.).

As shown in TABLE 2, SnF2 and some other compounds inhibited LPS activities in LAL assays

TABLE 2
Inhibition of LPS activities on LAL Assays
Inhibition of LAL activity %
P. gingivalis LPSE. coli LPS
1690 1 ng/ml1 ng/ml
Samples500 uM50 uM500 uM50 uM
Tin (II) fluoride60499287
stannous chloride48218965
Cetylpyridinium chloride1037710346
monohydrate
Chlorhexidine102389757
zinc citrate, dihydrate1045710482
zinc lactate580660
potassium oxalate8016
Triclosan (irgasan)00100
1-Hydroxypyridine-2-thone0026
zinc salt
sodium fluoride0045
Carboxymethyl cellulose0020
sodium

Example 5

Reporter gene cell lines, human HEK 293T cells, were purchased from Invivogen of San Diego, Calif. The HEK 293T cells were stably transfected with at least two exogenous genes, a TLR4 structural gene, and a SEAP reporter gene, which is under the control of NFkB transcriptional factors. The cell line is named here as TLR4-SEAP. The reporter gene encodes a secreted enzyme, called embryonic alkaline phosphatase or SEAP. The SEAP reporter is placed under the control of the interferon-β minimal promoter fused to five NFkB and AP-1-binding sites. Furthermore, the TLR4-SEAP cell line also contains a CD14 co-receptor gene, which is needed to transfer LPS to TLR4 receptors. The recombinant TLR binds its ligand, or distinct pathogen-associated molecule, initiates a chain of responses, leading to recruitment of NFkB and AP1 transcription factors to the reporter gene promoter, which induce expression of SEAP.

Cell culture and treatment: 500,000 gene reporter cells were grown and maintained in 15 ml growth medium, comprised of DMEM medium supplemented with 10% fetal calf serum in T75 flasks for three days at 37° C., 5% CO2, and 95% humidity. For treatment, wells of a 96-well plate were seeded with 10,000 cells/well in 100 μL of growth medium. The cells were incubated for 72 hours at 37° C., 5% CO2, and 95% humidity until day 4. On day 4, medium was changed to assay medium (90 μl), which is the DMEM medium without fetal calf serum. LPS, bacteria and the culture medium of bacterial growth, as described in EXAMPLE 1, were first resolved or mixed with the assay medium. 10 μl of the bacteria, LPS and culture medium of bacterial growth were added to the TLR4-SEAP cells. Samples were taken 24 hours later, following addition of LPS, bacteria, and culture medium. Expression of the reporter gene (SEAP) was quantified with a commercially available kit (SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich.).

EC50 was calculated using GraphPad Prism software (GraphPad Software, La Jolla, Calif.). Samples with lower EC50 are more potent in activating the TLR4 reporter gene than those with higher EC50. As shown in FIG. 2A, LPS from E. coli has lower EC50 than P. gingivalis, thus, was far more potent than P. gingivalis (Pg). Salmonella Minnesota LPS is not as potent as that of E. coli, but is far more potent than those of P. gingivalis LPS 1690 and 1435. Each species of bacteria produces multiple forms of LPS. Each form of LPS from the same species of bacteria has different potency in stimulating TLR4-downstream signaling pathways. For example, Pg 1690 LPS is more potent than Pg1435/50. LPS is a component in bacterial cell walls. Likely, E. coli cell wall is more virulent in inducing production of proinflammatory cytokines in host cells than P. gingivalis when they are in direct contact with host blood cells. P. gingivalis had far higher EC50 than P. pallens and P. nigrescens as shown in FIG. 2B in stimulating TLR4 reporter gene expression, suggesting that P. pallens and P. nigrescens are more likely to promote production of proinflammatory cytokines in host cells than P. gingivalis.

Bacteria release LPS into the supernatant of bacterial culture. As shown in FIG. 2C, the supernatant of P. pallens has an EC50 that is similar to that of P. nigrescens, but far lower than that of P. gingivalis, in stimulating expression of TLR4 reporter gene. Again, those results imply that the products of P. pallens and P. nigrescens are more likely to promote production of proinflammatory cytokines in host cells than those of P. gingivalis.

Example 6

Stannous fluoride is a leading anti-gingivitis technology in P&G toothpaste products. Tests were conducted to understand whether stannous fluoride could reduce LPS's ability to trigger proinflammatory responses in host cells. TLR4-SEAP reporter cells were prepared using the same conditions as described in EXAMPLE 5 in the presence or absence of LPS. Production of SEAP was quantified also as described in EXAMPLE 5.

FIG. 3 shows the effect of stannous at various concentrations from 62.5 uM to 1,000 uM on 100 ng/ml E. coli LPS, as reported by activation of TLR-4. At stannous concentrations of 500 uM or higher, the level of E. coli induction of TLR-4 was decreased.

FIG. 4 shows the effects of stannous at various concentrations from 62.5 uM to 1,000 uM on P. gingivalis LPS, as reported by activation of TLR-2. At stannous concentrations of 1000 uM, the level of P. gingivalis induction of TLR-2 was decreased.

The data in FIG. 5 shows reduction of LPS activity by the stannous ion, from a stannous fluoride salt. The data showed that stannous fluoride, at 1.6 mM and 3.2 mM, reduce about 50% of P. gingivalis LPS (500 ng/ml) activation on the TLR4 reporter system (One asterisk means P<0.05, two asterisks mean P<0.01).

Example 7

The method described in EXAMPLE 5 is effective at determining the potency of LPS from different bacteria. The same method was used to determine the EC50 of clinical samples, as described in EXAMPLE 2. As shown in FIG. 6, dental plaques from unhealthy sites had a smaller EC50 than those from healthy sites, suggesting the dental plaques from unhealthy sites contain more virulence factors.

The same method described in EXAMPLE 5 was used to examine the clinical samples in another study. A clinical study was conducted to evaluate sample collection methods and measurement procedures. It was a controlled, examiner-blind study. Forty panelists met the inclusion criteria, wherein in order to be included in the study, each panelist must:

    • Provide written informed consent to participate in the study;
    • Be 18 years of age or older;
    • Agree not to participate in any other oral/dental product studies during the course of this study;
    • Agree to delay any elective dentistry (including dental prophylaxis) until the study has been completed;
    • Agree to refrain from any form of non-specified oral hygiene during the treatment periods, including but not limited to the use of products such as floss or whitening products;
    • Agree to return for all scheduled visits and follow study procedures;
    • Must have at least 16 natural teeth;
    • Be in good general health, as determined by the Investigator/designee based on a review of the health history/update for participation in the study.

For Unhealthy Group (high bleeder group):

    • Have at least 20 bleeding sites (sites with a score of 1 or 2 on the GBI index); Have minimum 3 sampling sites with bleeding and pocket depth >3 mm but not deeper than 4 mm;
    • Have minimum 3 sampling sites without bleeding and with pocket depth <2 mm

For Healthy Group (low bleeder group):

    • Have maximum 3 bleeding sites (sites with a score of 1 or 2 on the GBI index);
    • No pockets deeper than 2 mm. Twenty (20) panelists were qualified as healthy—with up to 3 bleeding sites and with all pockets less than or equal to 2 mm deep and twenty (20) panelists were qualified as unhealthy—with greater than 20 bleeding sites with at least 3 pockets greater than or equal to 3 mm but not deeper than 4 mm with bleeding, and at least 3 pockets less than or equal to 2 mm deep with no bleeding for sampling. All panelists had up to 6 sites identified as “sampling sites.” The “sampling sites” had supragingival and subgingival plaque collected at Baseline, Week 2 and Week 4. Subgingival plaque samples were taken from a gingival sulcus from the pre-identified sites. Prior to sample collection, the site had supragingival plaque removed with a curette. The site was dried and subgingival plaque samples were collected with another dental curette (e.g., Gracey 13/14, 15/16, 11/12, 7/8, ½.) Each Gracey curette is designed to adapt to a specific area or tooth surface. For example, Gracey 13/14 is designed to adapt to the distal surfaces of posterior teeth. Samples from each site were placed in a pre-labeled 2.0 ml sterile tube containing 300 μl of DPBS buffer with about 50 of sterile 1 mm glass beads. Samples were stored at 4° C. The subgingival samples were stored at −80° C. until analyzed. The samples were thawed at room temperature and dispersed in a TissueLyser II (Qiagen, Valencia, Calif., USA) at 30 shakes per second for 3 min. Protein concentrations of the dispersed subgingival samples were measured using a Pierce microBCA Protein kit (ThermoFisher Scientific, Grand Island, N.Y., USA) following the manufacturer's instruction.

Oral lavage samples were collected at wake up (one per panelist) by rinsing with 4 ml of water for 30 seconds and then expectorating the contents of the mouth into a centrifuge tube. These samples were frozen at home until they were brought into the site in a cold pack. Each panelist collected up to 15 samples throughout the study. Saliva samples were frozen at −70° C. from submission.

All panelists were given investigational products: Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush. Panelists continued their regular oral hygiene routine, and did not use any new products starting from the baseline to the end of four week treatment study. During the four week treatment period, panelists brushed their teeth twice daily, morning and evening, in their customary manner using the assigned dentifrice and soft manual toothbrush.

The subgingival plaques from the above clinical study were applied to the TLR4 reporter cells in a procedure as described in EXAMPLE 5. FIG. 7A shows the results of a four-week study of 40 panelists going from baseline out over four weeks of treatment with Crest ProHealth Clinical toothpaste. The subgingival plaque samples in bleeding sites on the high bleeders group stimulated high expression of TLR4 reporter gene. More virulence in a sample elicits higher RLU (relative luminescent units) readings in the TLR4 reporter gene assay. As shown in FIG. 7A, the baseline samples of the high bleeders group had higher RLU than those of the low bleeders on both the bleeding and non-bleeding sites. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and lower bleeders groups at both bleeding and non-bleeding sites.

The oral lavage samples were applied to the TLR4 reporter cells in a procedure as described in EXAMPLE 5. As shown in FIG. 7B, oral lavage (Healthy vs. Gingivitis) samples were evaluated in the TLR4-SEAP reporter assay. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the high bleeder group.

Example 8

The reporter gene cell lines, human HEK 293T cells, were purchased from Invivogen of San Diego, Calif. The HEK 293T cells were stably transfected with at least two exogenous genes, a TLR2 structural gene, and SEAP reporter gene which is under the control of NFkB transcriptional factors. The cell line is named here as TLR2-SEAP. The reporter gene encodes a secreted enzyme, called embryonic alkaline phosphatase or SEAP. The SEAP reporter is placed under the control of the interferon-β minimal promoter fused to five NFkB and AP-1-binding sites. Furthermore, a CD14 co-receptor gene was transfected into the reporter gene cells expressing TLR2, as CD14 has been identified as a co-receptor for TLR2 ligands to enhance the TLR response. The CD14 co-receptor is needed to transfer LTA to TLR2 receptors. The recombinant TLR2 binds its ligand, or distinct pathogen-associated molecule, initiates a chain of responses, leading to recruitment of NFkB and AP1 transcription factors to the reporter gene promoter, which induce expression of SEAP.

Cell culture and treatment: 500,000 gene reporter cells were grown and maintained in 15 ml growth medium, comprising DMEM medium supplemented with 10% fetal calf serum in T75 flasks for three days at 37° C., 5% CO2, and 95% humidity. For treatment with LTA, wells of a 96-well plate were seeded with 10,000 cells/well in 100 μL of growth medium. The cells were incubated for 72 hours at 37° C., 5% CO2, and 95% humidity until day 4. On day 4, medium (100 μL) was changed to DMEM medium without fetal calf serum. LTA, LPS and bacterial cells, as described in EXAMPLE 7, were added. Samples were taken 24 hours later, following addition of samples. Expression of the reporter gene (SEAP) was quantified with a commercially available kit (SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich.).

As shown in FIGS. 8A, 8B, 8C and 8D, LTA, LPS, bacteria and the supernatant of bacterial culture could bind to TLR2 and activate TLR2 downstream signaling pathways in a dose-dependent manner. As shown in FIG. 8A, B. subtilis (BS) LTA is more potent than that of Enterococccus hirae. As shown in FIG. 8B, P. gingivalis LPS also activated expression of the TLR2 reporter gene. For example, Pg1690, as shown in FIG. 8B, activated TLR2-SEAP signal transduction, and stimulated SEAP production. But as shown in FIG. 8B, E. coli LPS did not activate the TLR2-SEAP reporter cells. It should also be noted that P. pallens, P. nigrescens and P. gingivalis have similar EC50 in stimulating expression of TLR2 reporter gene (FIG. 8C). However, the released TLR2 ligands from the three different bacteria have very different EC50 on activation of TLR2 reporter gene (FIG. 8D).

Example 9

The method described in EXAMPLE 8 is effective in determining the EC50 of LTA and other TLR2 ligands from different bacteria. The same method was used to determine the EC50 of clinical samples, as described in EXAMPLE 2. As shown in FIG. 9, dental plaques from unhealthy (bleeding) sites had smaller EC50 than those from healthy (non-bleeding) sites, suggesting the dental plaques from unhealthy sites contain more virulence factors.

Clinical samples as described for FIG. 7A of EXAMPLE 7 were examined using the TLR2-SEAP reporter gene assay. The results are shown in FIG. 10A. The subgingival samples in unhealthy (bleeding) sites from the unhealthy group (high bleeders) had more virulence factors than other sites. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders on both the bleeding and non-bleeding sites. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and low bleeders groups at both bleeding sites.

The clinical samples as described for FIG. 7B of EXAMPLE 7 were examined using the TLR2-SEAP reporter gene assay. As shown in FIG. 10B, oral lavage (Healthy vs. Gingivitis) was evaluated. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the high bleeder group.

Example 11

Bacterial cell wall and membrane components are recognized by TLR2. TLR2 recognizes the microbial motifs PGN (peptidoglycan)/lipoproteins/dectin and LPS. TLR1 and TLR6 form heterodimers with TLR2 and bind to triacylated lipoproteins and diacylated lipoproteins, respectively. THP1 NFkB-SEAP and IRF-Lucia™ Reporter Monocytes were purchased from Invivogen, San Diego, Calif. THP1-Dual cells were derived from the human THP-1 monocyte cell line by stable integration of two inducible reporter constructs. THP1-Dual cells feature the Lucia gene under the control of an ISG54 (interferon-stimulated gene) minimal promoter in conjunction with five interferon-stimulated response elements. THP1-Dual cells also express a SEAP reporter gene driven by an IFN-b minimal promoter fused to five copies of the NF-kB consensus transcriptional response element and three copies of the c-Rel binding site. As a result, THP1-Dual cells allow the simultaneous study of the NFkB pathway, by monitoring the activity of SEAP, and the interferon regulatory factor (IRF) pathway, by assessing the activity of Lucia (IRF-Luc). Both reporter proteins are readily measurable in the cell culture supernatant. This THP-1 cell line possesses functional TLR1, TLR2, TLR4, TLR5, TLR6 and TLR8, purchased from Invivogen. TLR4 senses LPS from Gram-negative bacteria while TLR5 recognizes bacterial flagellin from both Gram-positive and Gram-negative bacteria, TLR8 detects long single-stranded RNA.

Culture and treatment: The THP1-dual cells were cultured in 15 ml growth medium (RPMI 1640 with 10% heat-inactivated fetal bovine serum) in a T75 flask at 37° C. and 5% CO2. Cells were passed every 3 to 4 days by inoculating 300,000-500,000 cells/ml into a fresh T75 flask with 15 ml of fresh growth medium. To determine the effect of bacterial components on reporter gene expression, wells in 96-well plates were seeded at 100,000 cells in 90 μl of growth medium. 10 μl of bacterial wall and membrane components, or heat-killed whole bacteria, were added to each well. After incubation for 18 hours at 37° C. and 5% CO2, secreted luciferase and SEAP were quantified with commercially available assay kits (QUANTI-Luc of Invivogen, San Diego, Calif. for luciferase; SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich. for SEAP).

DHP1-dual reporter cells were treated with three different preparations of LPS as shown in FIG. 12A. All three LPS (ng/ml) activated production of NFkB-SEAP reporter genes in a dose-dependent manner. In addition, Pg 1690 LPS and E. coli LPS also stimulated expression of the IRF-luciferase reporter gene. TLR4 ligands, upon binding to TLR4 receptors, activate at least two signaling pathways. One is a common pathway NFkB-SEAP, which can be activated by all TLR ligands upon binding to their specific receptors. For example, TLR2 ligand, LTA, can bind to TLR2 receptors and activate the NFkB-SEAP signaling pathway. Similarly, TLR4 ligand, LPS, upon binding to TLR4 receptors, also is able to activate the NFkB-SEAP signaling transduction. As shown in FIG. 12A, E. coli LPS is a more potent ligand than P. gingivalis 1690 LPS on activation of both NFkB-SEAP and IRF-luciferase signaling transduction. THP-1 cells produce several functional TLR receptors. And all TLR receptors can activate the NFkB pathway, thus promoting expression of the NFkB-SEAP reporter gene. The reading of NFkB-SEAP is the collective actions of all TLR receptors, such as TLR2, TLR1, TLR6 and TLR4. All LPS from different bacteria stimulated NFkB-SEAP reporter gene. IRF-luciferase reporter gene, on the other hand, is driven by a limited number of TLR receptors, primarily TLR3, TLR4, TLR7, TLR8 and TLR9. Both P. gingivalis LPS 1690 and E. coli LPS stimulated expression of IRF-luciferase in a dose-dependent fashion.

The THP-1 reporter cells were used to examine the clinical samples as described for FIG. 7B of EXAMPLE 7. As shown in FIG. 12B, oral lavage (Healthy vs. Gingivitis) was evaluated using the IRF-Luc reporter gene in THP-1 cells. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and lower bleeders groups.

The THP-1 reporter cells were used to examine the clinical samples as described for FIG. 7A of EXAMPLE 7. As shown in FIG. 12C, the subgingival Plaque (Healthy vs. Gingivitis) was examined using the NFkB reporter gene in THP-1 cells. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the bleeding sites in both high and lower bleeders groups.

Example 12

THP1 dual reporter cells also express TLR2, TLR1 and TLR6 receptors. Bacterial cell wall and some membrane components are recognized by TLR2, TLR1 and TLR6. TLR2 recognizes the microbial motifs PGN (peptidoglycan)/lipoproteins/dectin and LPS. To determine whether LTA from different bacteria have different effects on stimulating NFkB-SEAP reporter gene expression in the THP1 dual reporter cells, the cells were prepared and treated in the same procedures as described in EXAMPLE 11. As shown in FIG. 13, LTA from both B. subtilis and S. aureus had similar potency in promoting reporter gene expression in the THP1 dual reporter cells.

Example 14

A randomized, two-group clinical study was conducted with 69 panelists (35 in the negative control group and 34 in the test regimen group). Panelists were 39 years old on average, ranging from 20 to 69, and 46% of the panelists were female. Treatment groups were well balanced, since there were no statistically significant (p≥0.395) differences for demographic characteristics (age, ethnicity, gender) or starting measurements for Gingival Bleeding Index (GBI); mean=29.957 with at least 20 bleeding sites, and Modified Gingival Index (MGI); mean=2.086. All sixty-nine panelists attended each visit and completed the treatment process. The following treatment groups were compared over a 6-week period:

Test regimen: Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse. Control regimen: Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush.

Dental plaques were collected from the same panelists in the test regimen in the clinical study as described in EXAMPLE 2. A supragingival sample was taken from each panelist with a sterile curette at the tooth/gum interface, using care to avoid contact with the oral soft tissue. Plaques were sampled from all available natural teeth (upper arch only) until no plaque was visible. Following sampling, the plaque samples were placed into a pre-labeled (panelist ID, sample initials, visit, and date) Eppendorf tube with 1 ml of PBS/Glycerol buffer and about 50 of sterile 1 mm glass beads, stored on ice until all samples were collected. The samples were then transferred to a −70° C. freezer for storage until further processing. Genomic DNA was isolated from supragingival plaque samples using QIAamp® genomic DNA kits (Qiagen, Germany) following manufacturer's instruction. Metasequencing was carried out at BGI Americas Corporation (Cambridge, Mass.). All data were analyzed at Global Biotech of Procter & Gamble Company in Mason, Ohio.

Clinical measurements: Bleeding sites (GBI) were decreased in the test regimen significantly on week 1, 3 and 6 in comparison to the control regimen (FIG. 14). Similarly, Inflammation (MGI) grades also decreased in the test regimen (FIG. 14).

Genomic DNA of the supragingival plaques in the test regimen was sequenced. As shown in FIG. 15, abundance of certain bacteria in the supragingival plaques changed in the six week treatments. Certain bacteria, such as Porphyromonas sp oral taxon 279 and Prevotella pallens, were decreased in weeks 1 and 3 (FIG. 15). The amount of each bacterial species was plotted over the four time periods of the treatment. The amount of certain bacteria, such as Peptostreptococcus stomatis and Prevotella intermedia, was reduced during the six week of treatment as shown in FIG. 15. This is also shown in FIG. 16A-1, FIG. 16A-2, and FIG. 16A-3.

Example 15

In the same clinical study as described in EXAMPLE 14, gingival-brush samples were collected from the same panelists as in EXAMPLE 14. Before sampling, panelists rinsed their mouths for 30 seconds with water. A dental hygienist then sampled the area just above the gumline using a buccal swab brush (Epicentre Biotechnologies cat.# MB100SP). The swab was immediately placed into 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Lifetechnologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube vortexed for 30 seconds, and immediately frozen on dry ice and stored in a −80 C freezer until analysis. The samples were taken out of freezer, thawed and extracted by placing the samples on a tube shaker for 30 minutes at 4° C. The tubes were centrifuged at 15000 RPM for 10 min in Eppendorf Centrifuge 5417R (Eppendorf, Ontario, Canada) to pellet any debris. The extract (800 μl) was analyzed for protein concentrations using the Bio-Rad protein assay (BioRad, Hercules, Calif.).

Forty proteins were measured in the gingival samples using V-PLEX Human Biomarker 40-Plex Kit (Meso Scale Diagnostics Rockville, Md.). The assay was performed following the manufacturer's instruction.

Among the proteins measured in the gingival samples, most proteins in the Proinflammatory Panel 1 (human), Cytokine Panel 1 (human), Chemokine Panel 1 (human), Angiogenesis Panel 1 (human), and Vascular Injury Panel 2 (human) had significant changes in their abundance during the 6-week treatment (TABLE 6). Those include FN-γ, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, GM-CSF, IL-5, IL-16, IL-7, IL-12/IL-23p40, IL-1α, VEGF-A, IL-17A, IL-15, TNF-β, IL-8 (HA), MCP-1, MCP-4, Eotaxin, IP-10, MDC, Eotaxin-3, TARC, MIP-1α, MIP-1β, VEGF-C, VEGF-D, Tie-2, Flt-1/VEGFR1, PlGF, FGF (basic), SAA, CRP, VCAM-1, and ICAM-1.

TABLE 6
Changes in abundance of proteins in the gingival-brush samples
Meanα = 0.05
BaselineWeek 1Week 3Week 6BaselineWeek 1Week 3Week 6
ICAM-116.03512.20910.0909.767ABB, CC
IL-1α3.5542.3312.1811.891AA, BB, CC
IL-1β53.66635.57524.29524.440ABCC
TNF-β0.00130.00100.00080.0007ABCC
IL-12p700.1720.1480.1180.127AA, BCB, C
IL-130.8050.7620.6240.648AA, BCB, C
IL-40.1270.1150.0900.096AA, BCB, C
IL-50.0040.0030.0020.003ABCB, C
CRP15.63712.74312.3855.809AAAB
Eotaxin0.0770.0640.0590.059AA, BBB
GM-CSF0.0100.0080.0080.008ABBB
IFN [Figure (not displayed)] 0.5300.4460.3780.386AA, BBB
IL-100.8750.4900.4230.244AA, BBB
IL-150.0050.0030.0030.003ABBB
IL-160.4660.3450.3420.295ABBB
IL-60.1960.1920.1680.150AAA, BB
IL-70.0040.0030.0030.003ABBB
IL-8856.276652.066567.361572.602ABBB
MCP-10.0530.0470.0390.039AA, BBB
MDC0.3990.4070.3450.339AABB
Meanα = 0.05
BaselineWeek 1Week 3Week 6BaselineWeek 1Week 3Week 6
SAA7.0396.9056.0925.162AAA, BB
Tie-20.2730.2390.2670.221AA, BAB
VCAM-14.9713.7063.1562.892ABBB
VEGF0.6250.5110.4780.480ABBB
VEGF 20.7720.6610.6200.582ABBB
VEGF-D0.0570.0520.0510.045AA, BA, BB
VEGF-C0.1450.1490.1250.137A, BABA, B
TARC0.0200.0290.0190.019ABAA
bFGF0.0200.0150.0120.013AAAA
Eotaxin-30.0950.1080.0910.094AAAA
Flt-10.3900.5180.4330.415ABA, BA
IL-12p400.0390.0310.0280.031AAAA
IL-20.1660.1990.2100.162AAAA
IL-8 (HA)47.50844.36241.26039.119AAAA
IP-100.5401.6880.7400.606AAAA
MCP-40.0230.0230.0200.022AAAA
MIP-1α0.0910.0910.0840.080AAAA
MIP-1β0.0910.1000.1100.094AAAA
TNFα2.0092.0672.0211.670AAAA

Example 16

The same gingival-brush samples as described in EXAMPLE 15 were used for metabonomic analyses. Fourteen panelists were selected randomly from each treatment group to determine if any metabolite concentrations were changed in gingival samples during the first 3 weeks of treatment. Both baseline and week 3 samples were sent to Metabolon, Inc. (Durham, N.C.) for metabonomic measurement. 170 metabolites were identified and quantified. As shown in TABLE 7, some metabolite concentrations were changed during the first 3 weeks of treatment. Citrulline concentrations in the gingival samples were reduced after three weeks of treatment in the treatment regimen group. Similarly, ornithine was also reduced in the treatment regimen group after three weeks of treatment. Reduction of citrulline and ornithine was likely associated with alleviation of gingivitis.

TABLE 7
Comparison of metabolites in gingival brush samples between baseline and week 3
during gingivitis treatment
Baseline3 week3 week/
Biochemical Namemeanmeanbaselinep-valueq-valueMass
13-HODE + 9-HODE1.08770.70880.650.06010.1338295.2
1-1.22940.82740.670.0380.1035500.3
arachidonoylglycerophosphoethanolamine
1-0.73781.07471.460.07670.1548478.3
oleoylglycerophosphoethanolamine
2-methylbutyrylcarnitine1.77690.69970.390.00340.0546246.1
(C5)
adenosine 5′-1.40920.84510.60.02950.0956348.1
monophosphate (AMP)
alanine0.87211.1021.260.03180.0973115.9
arginylleucine1.44470.68190.470.00840.0777288.3
arginylphenylalanine0.96160.33350.350.01190.0777322.2
asparagylleucine0.92950.61220.660.06980.1465246.2
citrulline1.01470.710.70.01040.0777176.1
deoxycarnitine3.23810.60880.190.00030.0168146.1
EDTA1.59850.83840.520.01380.0777291.1
erythritol1.6250.80850.50.05820.1325217
fructose1.99331.11060.560.08470.1605217
glutamine1.24590.83660.670.03740.1035147.2
glutathione, oxidized1.01611.46691.440.0870.1605613.1
(GSSG)
glycerol1.37830.83080.60.03910.1035205
lauryl sulfate1.6850.86230.510.03970.1035265.2
leucine1.21580.93590.770.06130.1338132.2
leucylleucine0.95050.43930.460.02510.0877245.1
lysylleucine1.20090.52750.440.00360.0546260.2
lysylphenylalanine1.16820.45630.390.00950.0777294.3
maltose0.87271.44811.660.0220.0877204.1
maltotriose1.04561.83471.750.08580.1605204
mannitol1.30040.79820.610.0420.107319.1
ornithine1.29160.70690.550.03670.1035141.9
palatinitol1.43950.82720.570.07820.1549204
phosphate1.40080.83760.60.02080.0877298.9
proline1.4050.990.70.00330.0546116.1
propionylcarnitine1.25650.76880.610.02010.0877218.2
pyroglutamine1.34240.78730.590.01360.0777129.2
serylisoleucine1.17530.71690.610.08140.1583219.2
spermidine1.16130.86780.750.06870.1465146.2
succinate1.29290.81130.630.07540.1548247
threonylleucine1.15130.49310.430.00440.0594231.2
threonylphenylalanine1.76930.9180.520.02330.0877267.2
trehalose2.35630.90840.390.00540.0647361.2
tryptophan1.15180.90890.790.04870.1185205.1
tyrosine1.3831.02990.740.01610.0787182.1
valine1.15980.92710.80.03040.0956118.1
valylvaline0.93470.82310.880.05080.1207215.2
X-136710.50350.9181.820.05450.1267315.3
X-145881.36470.83780.610.0240.0877151
X-161031.36430.84610.620.02970.095699.3
X-172661.31580.5760.440.00030.0168530.4
X-173751.47850.83870.570.01890.0877357.1
X-184720.61381.14411.860.00110.0405827.1
X-187791.37560.80350.580.01620.0787209.1
X-196071.52370.71670.470.0020.0537366.1
X-196091.32840.77210.580.0160.0787204
X-196121.38960.78430.560.010.0777427.2
X-196131.34120.75350.560.00990.0777429.3
X-196141.33780.73430.550.04540.113570.1
X-198071.34780.84110.620.02440.087793
X-198081.33480.83680.630.02540.087795
X-198501.35760.75190.550.0110.0777334.2
X-198571.33570.80320.60.0380.1035230
X-200001.27840.75360.590.01330.077781.2

Example 17

Quantitation of citrulline and ornithine from the extracts of the Gingival-brush samples was conducted using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Gingival-brush samples were obtained from the same human panelists in the clinical study as described in EXAMPLE 14, and were placed into extraction buffer as described in EXAMPLE 15. The supernatants were subject to both HILIC/MS/MS and BCA analysis. For free citrulline and ornithine analysis, the extracts of the Gingival-brush samples were analyzed either directly (50 μl undiluted sample solution) in 50/50 acetonitrile/ultra-pure water with 0.754% formic acid or diluted fivefold. For total citrulline and ornithine analysis, the extracts of the Gingival-brush samples were first hydrolyzed using 6 N HCl (50 μL of extract with 450 μL of 6N HCl), no shaking, and placed on a hot plate at 110° C. for 16 hours. The hydrolyzed samples were then dried down under vacuum at room temperature (Savant speedvac of Lifetechnology, Grand Island, N.Y.) and then reconstituted in 1 ml of dilution solution (50/50 acetonitrile/ultra-pure water with 0.754% formic acid) for analysis. The standards and the samples were analyzed using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Analytes and the corresponding ISTDs (stable isotope labeled internal standard) were monitored by electrospray ionization (ESI) in positive mode using the selected-reaction-monitoring schemes shown in TABLE 8. A standard curve was constructed by plotting the signal, defined here as the peak area ratio (peak area analyte/peak area ISTD), for each standard versus the mass of each analyte for the corresponding standard. The mass of each analyte in the calibration standards and Gingival-brush extract samples were then back-calculated using the generated regression equation. The concentration of protein bound citrulline or ornithine was calculated as the result of subtracting the concentration of free citrulline or ornithine from the concentration of total citrulline or ornithine, respectively. The result was reported as the concentration of citrulline or ornithine or the result was standardized by dividing by the amount of citrulline or ornithine by the amount of the total proteins that were found in the extract.

TABLE 8
Multiple Reaction Monitoring (MRM) transitions
for analytes and their corresponding stable
isotope labeled internal standards
AnalytesMRMInternal StandardsMRM
Citrulline176 → 159d7-Citrulline181 → 164
Ornithine133 → 70d6-Ornithine139 → 76

All samples from all panelists of the Test regimen [Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse] were analyzed. As shown in FIG. 16, citrulline levels reduced rapidly in the first week of treatment, and then continued to decline gradually in weeks 3 and 6 of treatment. These results are consistent with clinical observations, where gingival bleeding sites (GBI) and the gingival inflammation (MGI) were reduced over the 6-week treatment period.

Example 18

The same samples as described in EXAMPLE 17 were analyzed using procedures as described in EXAMPLE 17. Gingivitis was treated for 6 weeks. Baseline (BL) represents diseased status. Symptoms of gingivitis were alleviated from week 1 to week 6 treatments. Protein bound ornithine (the difference between total and the free ornithine) was higher in gingivitis as shown in FIG. 17. Protein bound ornithine was reduced gradually as gingivitis was decreased in severity.

Example 19

Gingival samples were collected as described in EXAMPLES 15, from the same panelists as in EXAMPLE 15, and were used to examine the expression of genes during 6 weeks of treatments with Test regimen [Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse] and Control regimen [Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush].

After harvesting the samples, the brush was completely immersed in the RNAlater solution (1 ml in a 1.5 ml Eppendorf tube) for keeping RNA from degrading during transport and storage (Qiagen, Valencia, Calif.). The microcentrifuge tubes were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

The ornithine-citrulline-arginine cycle consists of four enzymes (FIG. 18). The main feature of the cycle is that three amino acids (arginine, ornithine, and citrulline) can be converted to each other. The first enzyme is ornithine transcarbamoylase, which transfers a carbamoyl group from carbamoyl phosphate to ornithine to generate citrulline. This reaction occurs in the matrix of the mitochondria. Expression of ornithine transcarbamoylase was reduced in the treatment (FIG. 19). The second enzyme is argininosuccinate synthetase. This enzyme uses ATP to activate citrulline by forming a citrullyl-AMP intermediate, which is attacked by the amino group of an aspartate residue to generate argininosuccinate. This and subsequent two reactions occur in the cytosol. Again, expression of argininosuccinate synthetase decreased during the treatment. The third enzyme is argininosuccinate lyase, which catalyzes cleavage of argininosuccinate into fumarate and arginine. The last enzyme is argininase. Argininases cleave arginine to produce urea and ornithine. In a contrast to the decreased expression of ornithine transcarbamoylase and argininosuccinate synthetase genes, argininase I and II increased (FIG. 19).

Arginine is also a substrate for nitric oxide synthase, which oxidizes arginine to produce citrulline and nitric oxide. Expression of nitric oxide synthase gene increased too (FIG. 19).

Example 20

Experimental gingivitis: Another clinical study was carried out to determine whether citrulline is increased in experimentally induced gingivitis in healthy human panelists. This was a case-control study enrolling 60 panelists. The study population included two groups as follows: Group 1 or high bleeders group, thirty (30) panelists with at least 20 bleeding sites, where bleeding is a GBI site score of 1 or 2 at baseline. Group 2 or low bleeders group, thirty (30) panelists with 2 or less bleeding sites, where bleeding is a GBI site score of 1 or 2.

The study consisted of two Phases: Health/Rigorous Hygiene Phase with dental prophylaxis, polishing and rigorous oral hygiene; and Induced Gingivitis Phase without oral hygiene. At the Screening visit, panelists underwent an oral soft tissue assessment and had a gingivitis evaluation (Modified Gingival Index (MGI) and Gingival Bleeding Index (GBI). At Visit 2 qualifying panelists received an oral soft tissue exam followed by a gingivitis evaluation and gingival plaques and gum swabs were collected for the qPCR, protein and RNA host biomarker analysis. Following that, all panelists received dental prophylaxis and entered the Health/Rigorous Hygiene Phase, lasting two weeks. After two weeks of rigorous hygiene, panelists entered the Induced Gingivitis Phase, lasting for three weeks. Oral soft tissue exams and gingivitis were re-evaluated and all samples (gum swabs) were collected at Baseline, WK0 and WK2.

Gingival sample collection—A gum swab was collected from each side of the upper arch using the procedures as described in EXAMPLE 15. Gum swabs were collected close to the gum line from the buccal sites only (preferably from four adjacent teeth—preferably from premolar and molar areas). Panelists rinsed for 30 seconds with 15 ml of Listerine rinse to clean the surface of sampling area. After the Listerine rinse, panelists rinsed for 30 seconds with 20 ml of water. Following that, selected sites were isolated with a cotton roll and gently dried with an air syringe and two gum swabs were taken with collection brushes/swabs from the gingiva region close to the gumline of the selected teeth. The samples were placed in a pre-labeled (panelist ID, sample ID, visit, and date) 1.5 ml micro-centrifuge tube containing 800 ul DPBS (Dulbecco's phosphate-buffered saline) (Lifetechnologies, Grand Island, N.Y.) with protease inhibitors, including AEBSF (4-(2-Aminoethyl) benzenesulfonyl fluoride hydrochloride) 2 mM, aprotinin 0.3 μM, Bestatin 130 μM, EDTA (Ethylenediaminetetraacetic acid) 1 mM, E-64 1 μM, and leupeptin 1 μM. The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. Samples from three visits were analyzed using the procedures described in EXAMPLE 17, and shown in FIG. 20. Those three visits were baseline, Week 0, (right after the Health/Rigorous Hygiene Phase and before the induced gingivitis phase) and week 2 (at the end of Induced Gingivitis Phase). Free citrulline levels were low in both the high and low bleeders groups at the baseline and week 0, but rose quickly in the induced gingivitis in both groups at week 2.

Example 21

The same procedures were used as described in EXAMPLE 17. The samples were the same as described in EXAMPLE 20. Protein bound citrulline was lower at the baseline than that at week 0 in both high and low bleeders groups as shown in FIG. 21 in gingival tissue. It was low in experimental gingivitis in both groups at week 2.

Example 22

The same clinical samples from experimental gingivitis (EXAMPLE 20) were analyzed using the procedures described in EXAMPLE 17. The bound ornithine was the lowest at week 0 (FIG. 22) in both groups. Its levels at the baseline were higher than those at week 0. The bound ornithine reached peaks when gingivitis was induced in both groups at week 2. Also it is worth noting the total ornithine (Free and protein bound ornithine) was increased in the induced gingivitis (FIG. 23) in both groups.

Example 23

The same procedures were used as described in EXAMPLE 17. The samples were the same as described in EXAMPLE 20. The protein bound arginine was the lowest in induced gingivitis (FIG. 24) in both groups. Its levels were higher in WK0 than at Baseline in both groups. The total arginine in the gingival brush samples displayed the same patterns as the protein bound one (FIG. 25).

Example 24

Citrulline was purchased from Sigma-Aldrich (St. Louis, Mo.). THP1-Dual™ cells were purchased from Invivogen (San Diego, Calif.). Cells were cultured following the manufacturer's instruction, as described in EXAMPLE 11. For treatment, 0.3 mM to 9 mM of citrulline were first added to the culture medium. Then, 300 ng/ml of P. gingivalis LPS 1690 were added 60 minutes later. After 24 hours of treatment, media was collected and analyzed for cytokine production using 9-plex kit (Meso Scale Diagnostics Rockville, Md.).

P. gingivalis LPS 1690 stimulated cytokine production, as shown in FIG. 26. Citrulline inhibited P. gingivalis LPS 1690 effects on proinflammatory cytokine production in a dose-dependent manner. Those cytokines include IL-6, TNF-α, IL-12p70, IL-10, IL-2, IFN-r and IL-1β.

Example 26

Growth of bacteria: Two bacteria, Bacterium A and Bacterium B, were cultured in Tryptic Soy Broth medium (Sigma-Aldrich, St. Louis, Mo.) at 37° C. with shaking at 200 rpm. The bacteria were harvested at 24 hours, and suspended in 0.5 ml of phosphate-buffered saline, labeled “live”. Half ml of “Live” bacteria was transferred to a 1.5 ml microtube, and heated to 80° C. for 30 min. The heat-treated bacteria were labeled “Heat-Inactivated”, or “Dead”.

Measurement of TLR responses in THP-1 gene reporter cells (NFkB-SEAP): The Live and Heat-Inactivated bacteria were applied to THP-1 cells as described in EXAMPLE 11. As shown in FIG. 31, EC50 of Bacterium A and B on activation of NFkB-SEAP reporter gene in THP-1 cells was determined. Both Live and Heat-inactivated (Dead) bacteria stimulated expression of the NFkB-SEAP reporter gene. Bacterium B had a lower EC50 than Bacterium A in activating expression of the NFkB-SEAP reporter gene.

Cytokine production and measurement: Human peripheral bleed mononuclear cells (hPBMC) were obtained from All Cells company (All Cells, Alameda, Calif.) as Leukapheresed blood. Leukapheresed blood was mixed with an equal part of DMEM+glutaGRO supplemented with 9.1% fetal bovine serum and 1% penicillin/streptomycin (Thermo Fisher, Waltham, Mass.). hPBMC were isolated from the 1:1 mixture of blood and culture medium by collecting the buffy coat of a centrifuged Histopaque®-1077 (Sigma-Aldrich, St. Louis, Mo.) buffer density gradient. The cells (200,000 cells) were cultured in 200 μl of DMEM+glutaGRO supplemented with 9.1% fetal bovine serum and 1% penicillin/streptomycin, and treated with Live and Heat-Inactive bacteria (6,250,000 colony-forming units). The medium was harvested at 24 hours after adding the bacteria, and analyzed for proinflammatory cytokines in a kit following manufacturer's instruction (Meso Scale Diagnostics, Rockville, Md.).

As shown in TABLE 9, both live bacterium A and B stimulated production of cytokines in hPBMC. Bacteriun B was far more potent than Bacterium A in promoting production of IFN-γ, IL-10, IL-12p70, IL-1β, IL-6, IL-8 and TNF-α in hPBMC.

Live Live
StatisticsCytokinesBacterium ABacterium
MeanIFN-γ867.1612734.36
MeanIL-1068.35412.51
MeanIL-12p7023.75253.47
MeanIL-1β2300.866969.31
MeanIL-244.2465.17
MeanIL-63431.059963.84
MeanIL-865742.9170357.25
MeanTNF-α3710.6613825.49
Std DevIFN-γ488.118200.13
Std DevIL-1033.56314.23
Std DevIL-12p7014.71283.33
Std DevIL-1β1569.727691.93
Std DevIL-232.9736.29
Std DevIL-62212.626552.12
Std DevIL-818689.2413669.28
Std DevTNF-α2503.258302.26

The dimensions and values disclosed herein are not to be understood as being strictly limited to the exact numerical values recited. Instead, unless otherwise specified, each such dimension is intended to mean both the recited value and a functionally equivalent range surrounding that value. For example, a dimension disclosed as “40 mm” is intended to mean “about 40 mm.”

Every document cited herein, including any cross referenced or related patent or application and any patent application or patent to which this application claims priority or benefit thereof, is hereby incorporated herein by reference in its entirety unless expressly excluded or otherwise limited. The citation of any document is not an admission that it is prior art with respect to any invention disclosed or claimed herein or that it alone, or in any combination with any other reference or references, teaches, suggests or discloses any such invention. Further, to the extent that any meaning or definition of a term in this document conflicts with any meaning or definition of the same term in a document incorporated by reference, the meaning or definition assigned to that term in this document shall govern.

While particular embodiments of the present invention have been illustrated and described, it would be obvious to those skilled in the art that various other changes and modifications can be made without departing from the spirit and scope of the invention. It is therefore intended to cover in the appended claims all such changes and modifications that are within the scope of this invention.

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Example 1

Growth of bacteria: A 1 ml aliquot of a 24 hour culture of E. coli ATCC 8739 was used to inoculate 100 ml of Luria-Bertani (LB) broth in a 250 ml baffled flask. This culture was then incubated at 37° C. with agitation (220 rpm) and sampled at 30 minute intervals. Samples were assessed for turbidity (OD600) in a SpectraMax platereader M3 (Molecular Devices, Sunnydale, Calif.), which is one method of monitoring the growth and physiological state of microorganisms. The sample turbidity was then recorded and the samples were centrifuged at 5000 RPM for 10 min at room temperature. The supernatant, thereinafter referred to as “supernatant of bacterial culture”, was subsequently analyzed for LPS content using the procedure as described below.

Twenty ml aliquots of MTGE broth (Anaerobe Systems, Morgan Hill, Calif.) were inoculated with P. gingivalis ATCC 33277, P. pallens ATCC 700821, or P. nigrescens ATCC 25261. These cultures were incubated overnight in a Whitely A45 Anaerobic Workstation (Don Whitley Scientific, Frederick, Md.) at 37° C. with an 85:10:5 N2:CO2:H2 gas ratio. One ml aliquots of these starter cultures were then used to inoculate 99 ml of membrane-Tryptone Glucose Extract (m-TGE) broth in a 250 ml baffled flask. These cultures were then incubated under agitation (200 rpm) as previously described and sampled at regular intervals. Samples were assessed for turbidity (OD600) in a Tecan Infinite m200 Pro (Tecan Trading AG, Switzerland) and then centrifuged at 16,100×g for 10 min at room temperature. Supernatants were decanted and passed through a 0.22 μM filter prior to analysis for LPS content.

In the experiment, only OD600 was measured. For the sake of consistency in following experiments, we converted OD600 readings into bacterial numbers, even though the relationship between OD600 readings and bacterial numbers is varied for each bacterium. The number of bacteria was estimated based on spectrophotometer readings at OD600 (OD600 of 1.0=8×108 cells/ml).

The Limulus Amebocyte Lysate Assay (LAL) is an assay to determine the total amount of lipopolysaccharide (LPS) in the sample tested (Pierce LAL Chromogenic Endotoxin Quantitation Kit, ThermoFischer Scientific, Waltham, Mass.). The assay was performed following manufacturer's instruction. Ninety-six-well microplates were first equilibrated in a heating block for 10 min at 37° C. Fifty μl each of standard or sample was dispensed into the microplate wells and incubated with plate covered for 5 min at 37° C. Then 50 μl LAL was added to each well. Plates were shaken gently and incubated for 10 min at 37° C. 100 μl of chromogenic substrate was added and incubated for 6 min at 37° C. Finally, 50 μl Stop Reagent was added and the absorbance was measured at 405-410 nm on Spectramax M3 platereader (Molecular Device, Sunnyvale, Calif.).

FIGS. 1A, 1C, and 1D show the ability of microbes to shed LPS as part of their normal growth cycle. This data shows the need to deliver chemistry to the subgingival plaque to effectively mitigate the LPS, since tooth brushing generally does not remove the subgingival plaque.

The LPS, as measured by the LAL kit reported in endotoxin unit per ml (EU/ml), was shed by the bacteria (E. coli K12) as depicted in FIG. 1A. The growth media began to be depleted of complex sugars around 120 minutes, as reflected in the bacterial growth curve in FIG. 1B, where the LPS shedding started to decline. This data gave a reason to believe that a mature biofilm/plaque could supply a constant level of LPS to the host cells, if food sources were present. The LPS would then have the ability to induce an inflammatory response from the host cells.

Importantly, LPS are secreted into the supernatant of bacterial culture (FIG. 1D). LPS also exists in bacterial walls (FIG. 1E). Again, this data further enforce the need to deliver chemistry to the subgingival plaque to effectively mitigate the LPS, since tooth brushing generally does not remove the subgingival plaque.

Example 2

Seven panelists, with at least three bleeding sites, took part in the testing. A licensed dental hygienist collected subgingival plaque samples. Samples were taken at the tooth/gum interface (buccal surfaces only) using care to avoid contact with the oral soft tissues. Six subgingival plaque sites were sampled from each panelist (3 healthy and 3 unhealthy sites). Unhealthy teeth had bleeding sites with pockets greater than 3 mm and healthy sites had no bleeding with pocket depth less than 2 mm Prior to sampling, panelists were instructed to abstain for 12 hours from oral hygiene and refrain from eating, chewing gum, drinking (except small sips of water). Next, panelists had their marginal plaque collected with a curette at the sampling sites. Then, from the same site, subgingival plaque samples were collected with 3 consecutive paper points as shown in FIG. 1F. The sampling sites were isolated with cotton rolls and gently air-dried. Paper points (PROFLOW incorporated, Amityville, N.Y.) were gently placed for 10 seconds into the pocket until a minimum of resistance was felt. After 10 seconds, paper points were removed and placed into pre-labeled 1.5 ml tubes. The same sampling procedure was repeated with 2 more paper points (paper points go into separate tubes). The first, second and third sample paper points from a healthy site of all panelists were pooled separately into three tubes, labeled as paper point 1, 2 and 3, respectively. Similarly the unhealthy site samples were also pooled.

TABLE 1 showed that unhealthy dental plaques contained more endotoxins than the healthy dental plaques. One ml PBS was added to each pooled sample in the 1.5 ml tube. Bacteria were lysed in a MolBio Fast Prep bead beater (MP Biomedicals, Santa Ana, Calif.). Samples were centrifuged for 10 min at 10,000 RPM at 4° C., supernatants were collected and analyzed with LAL assay kits following manufacturer's instruction as described in EXAMPLE 1.

TABLE 1
Protein concentrations and endotoxin levels
in the pooled dental plaque samples.
Endotoxin
Dental plaque(endotoxin unit)
Healthy paperpoint 1 sub plaque1284
Healthy paperpoint 2 sub plaque476
Healthy paperpoint 3 sub plaque361
Healthy Marginal Plaque23180
Unhealthy paperpoint 1 sub plaque3371
Unhealthy paperpoint 2 sub plaque1732
Unhealthy paperpoint 3 sub plaque1644
Unhealthy Marginal Plaque80277

It was expected that the marginal plaques in unhealthy sites had more endotoxins than those in the healthy sites (TABLE1) within the same subjects. Three samples were taken from subgingival pockets with three paper points sequentially, named paper point 1, 2 and 3. Again, the subgingival plaques taken by the paper point 1 had more endotoxins in the unhealthy sites than in the healthy sites (TABLE 1). The same is true for the samples taken by paper point 2 and 3 Importantly, dental plaques in the unhealthy subgingival pockets possessed more endotoxins than plaques from healthy pockets. This may explain why unhealthy gingiva are prone to bleeding upon probing.

Example 3

The LAL assay, as described in EXAMPLE 1, was modified for development of technology which inhibits LPS from activating a proenzyme in the LAL assay. The Thermo Scientific Pierce LAL Chromogenic Endotoxin Quantitation Kit is a quantitative endpoint assay for the detection of LPS, which catalyzes the activation of a proenzyme in the modified Limulus Amebocyte Lysate (LAL). The activated proenzyme then splits p-Nitroaniline (pNA) from the colorless substrate, Ac-Ile-Glu-Ala-Arg-pNA. The product pNA is photometrically measured at 405-410 nm. If SnF2 binds to LPS, the latter can't react with the proenzyme in the LAL kit. Consequently, the proenzyme is not activated, and the colorless substrate Ac-Ile-Glu-Ala-Arg-pNA will not split and no color product is produced. P. gingivalis LPS 1690 (1 ng/ml), or E. coli LPS (1 ng/ml), and stannous fluoride and other materials (50 and 500 μM), as listed in TABLE 2, were dissolved in endotoxin-free water. Then 50 μl LAL was added to each well. Plates were shaken gently and incubated for 10 min at 37° C. 100 μl of chromogenic substrate was added and incubated for 6 min at 37° C. Finally, 50 μl Stop Reagent was added and the absorbance was measured at 405-410 nm on Spectramax M3 plate reader (Molecular Device, Sunnyvale, Calif.).

As shown in TABLE 2, SnF2 and some other compounds inhibited LPS activities in LAL assays

TABLE 2
Inhibition of LPS activities on LAL Assays
Inhibition of LAL activity %
P. gingivalis LPSE. coli LPS
1690 1 ng/ml1 ng/ml
Samples500 uM50 uM500 uM50 uM
Tin (II) fluoride60499287
stannous chloride48218965
Cetylpyridinium chloride1037710346
monohydrate
Chlorhexidine102389757
zinc citrate, dihydrate1045710482
zinc lactate580660
potassium oxalate8016
Triclosan (irgasan)00100
1-Hydroxypyridine-2-thone0026
zinc salt
sodium fluoride0045
Carboxymethyl cellulose0020
sodium

Example 5

Reporter gene cell lines, human HEK 293T cells, were purchased from Invivogen of San Diego, Calif. The HEK 293T cells were stably transfected with at least two exogenous genes, a TLR4 structural gene, and a SEAP reporter gene, which is under the control of NFkB transcriptional factors. The cell line is named here as TLR4-SEAP. The reporter gene encodes a secreted enzyme, called embryonic alkaline phosphatase or SEAP. The SEAP reporter is placed under the control of the interferon-β minimal promoter fused to five NFkB and AP-1-binding sites. Furthermore, the TLR4-SEAP cell line also contains a CD14 co-receptor gene, which is needed to transfer LPS to TLR4 receptors. The recombinant TLR binds its ligand, or distinct pathogen-associated molecule, initiates a chain of responses, leading to recruitment of NFkB and AP1 transcription factors to the reporter gene promoter, which induce expression of SEAP.

Cell culture and treatment: 500,000 gene reporter cells were grown and maintained in 15 ml growth medium, comprised of DMEM medium supplemented with 10% fetal calf serum in T75 flasks for three days at 37° C., 5% CO2, and 95% humidity. For treatment, wells of a 96-well plate were seeded with 10,000 cells/well in 100 μL, of growth medium. The cells were incubated for 72 hours at 37° C., 5% CO2, and 95% humidity until day 4. On day 4, medium was changed to assay medium (90 μl), which is the DMEM medium without fetal calf serum. LPS, bacteria and the culture medium of bacterial growth, as described in EXAMPLE 1, were first resolved or mixed with the assay medium. 10 μl of the bacteria, LPS and culture medium of bacterial growth were added to the TLR4-SEAP cells. Samples were taken 24 hours later, following addition of LPS, bacteria, and culture medium. Expression of the reporter gene (SEAP) was quantified with a commercially available kit (SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich.).

EC50 was calculated using GraphPad Prism software (GraphPad Software, La Jolla, Calif.). Samples with lower EC50 are more potent in activating the TLR4 reporter gene than those with higher EC50. As shown in FIG. 2A, LPS from E. coli has lower EC50 than P. gingivalis, thus, was far more potent than P. gingivalis (Pg). Salmonella Minnesota LPS is not as potent as that of E. coli, but is far more potent than those of P. gingivalis LPS 1690 and 1435. Each species of bacteria produces multiple forms of LPS. Each form of LPS from the same species of bacteria has different potency in stimulating TLR4-downstream signaling pathways. For example, Pg 1690 LPS is more potent than Pg1435/50. LPS is a component in bacterial cell walls. Likely, E. coli cell wall is more virulent in inducing production of proinflammatory cytokines in host cells than P. gingivalis when they are in direct contact with host blood cells. P. gingivalis had far higher EC50 than P. pallens and P. nigrescens as shown in FIG. 2B in stimulating TLR4 reporter gene expression, suggesting that P. pallens and P. nigrescens are more likely to promote production of proinflammatory cytokines in host cells than P. gingivalis.

Bacteria release LPS into the supernatant of bacterial culture. As shown in FIG. 2C, the supernatant of P. pallens has an EC50 that is similar to that of P. nigrescens, but far lower than that of P. gingivalis, in stimulating expression of TLR4 reporter gene. Again, those results imply that the products of P. pallens and P. nigrescens are more likely to promote production of proinflammatory cytokines in host cells than those of P. gingivalis.

Example 6

Stannous fluoride is a leading anti-gingivitis technology in P&G toothpaste products. Tests were conducted to understand whether stannous fluoride could reduce LPS's ability to trigger proinflammatory responses in host cells. TLR4-SEAP reporter cells were prepared using the same conditions as described in EXAMPLE 5 in the presence or absence of LPS. Production of SEAP was quantified also as described in EXAMPLE 5.

FIG. 3 shows the effect of stannous at various concentrations from 62.5 uM to 1,000 uM on 100 ng/ml E. coli LPS, as reported by activation of TLR-4. At stannous concentrations of 500 uM or higher, the level of E. coli induction of TLR-4 was decreased.

FIG. 4 shows the effects of stannous at various concentrations from 62.5 uM to 1,000 uM on P. gingivalis LPS, as reported by activation of TLR-2. At stannous concentrations of 1000 uM, the level of P. gingivalis induction of TLR-2 was decreased.

The data in FIG. 5 shows reduction of LPS activity by the stannous ion, from a stannous fluoride salt. The data showed that stannous fluoride, at 1.6 mM and 3.2 mM, reduce about 50% of P. gingivalis LPS (500 ng/ml) activation on the TLR4 reporter system (One asterisk means P<0.05, two asterisks mean P<0.01).

Example 7

The method described in EXAMPLE 5 is effective at determining the potency of LPS from different bacteria. The same method was used to determine the EC50 of clinical samples, as described in EXAMPLE 2. As shown in FIG. 6, dental plaques from unhealthy sites had a smaller EC50 than those from healthy sites, suggesting the dental plaques from unhealthy sites contain more virulence factors.

The same method described in EXAMPLE 5 was used to examine the clinical samples in another study. A clinical study was conducted to evaluate sample collection methods and measurement procedures. It was a controlled, examiner-blind study. Forty panelists met the inclusion criteria, wherein in order to be included in the study, each panelist must:

    • Provide written informed consent to participate in the study;
    • Be 18 years of age or older;
    • Agree not to participate in any other oral/dental product studies during the course of this study;
    • Agree to delay any elective dentistry (including dental prophylaxis) until the study has been completed;
    • Agree to refrain from any form of non-specified oral hygiene during the treatment periods, including but not limited to the use of products such as floss or whitening products;
    • Agree to return for all scheduled visits and follow study procedures;
    • Must have at least 16 natural teeth;
    • Be in good general health, as determined by the Investigator/designee based on a review of the health history/update for participation in the study.

For Unhealthy Group (high bleeder group):

    • Have at least 20 bleeding sites (sites with a score of 1 or 2 on the GBI index); Have minimum 3 sampling sites with bleeding and pocket depth >3 mm but not deeper than 4 mm;
    • Have minimum 3 sampling sites without bleeding and with pocket depth <2 mm

For Healthy Group (low bleeder group):

    • Have maximum 3 bleeding sites (sites with a score of 1 or 2 on the GBI index);
    • No pockets deeper than 2 mm. Twenty (20) panelists were qualified as healthy—with up to 3 bleeding sites and with all pockets less than or equal to 2 mm deep and twenty (20) panelists were qualified as unhealthy—with greater than 20 bleeding sites with at least 3 pockets greater than or equal to 3 mm but not deeper than 4 mm with bleeding, and at least 3 pockets less than or equal to 2 mm deep with no bleeding for sampling. All panelists had up to 6 sites identified as “sampling sites.” The “sampling sites” had supragingival and subgingival plaque collected at Baseline, Week 2 and Week 4. Subgingival plaque samples were taken from a gingival sulcus from the pre-identified sites. Prior to sample collection, the site had supragingival plaque removed with a curette. The site was dried and subgingival plaque samples were collected with another dental curette (e.g., Gracey 13/14, 15/16, 11/12, ⅞, ½.) Each Gracey curette is designed to adapt to a specific area or tooth surface. For example, Gracey 13/14 is designed to adapt to the distal surfaces of posterior teeth. Samples from each site were placed in a pre-labeled 2.0 ml sterile tube containing 300 μl of DPBS buffer with about 50 of sterile 1 mm glass beads. Samples were stored at 4° C. The subgingival samples were stored at −80° C. until analyzed. The samples were thawed at room temperature and dispersed in a TissueLyser II (Qiagen, Valencia, Calif., USA) at 30 shakes per second for 3 min Protein concentrations of the dispersed subgingival samples were measured using a Pierce microBCA Protein kit (ThermoFisher Scientific, Grand Island, N.Y., USA) following the manufacturer's instruction.

Oral lavage samples were collected at wake up (one per panelist) by rinsing with 4 ml of water for 30 seconds and then expectorating the contents of the mouth into a centrifuge tube. These samples were frozen at home until they were brought into the site in a cold pack. Each panelist collected up to 15 samples throughout the study. Saliva samples were frozen at −70° C. from submission.

All panelists were given investigational products: Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush. Panelists continued their regular oral hygiene routine, and did not use any new products starting from the baseline to the end of four week treatment study. During the four week treatment period, panelists brushed their teeth twice daily, morning and evening, in their customary manner using the assigned dentifrice and soft manual toothbrush.

The subgingival plaques from the above clinical study were applied to the TLR4 reporter cells in a procedure as described in EXAMPLE 5. FIG. 7A shows the results of a four-week study of 40 panelists going from baseline out over four weeks of treatment with Crest ProHealth Clinical toothpaste. The subgingival plaque samples in bleeding sites on the high bleeders group stimulated high expression of TLR4 reporter gene. More virulence in a sample elicits higher RLU (relative luminescent units) readings in the TLR4 reporter gene assay. As shown in FIG. 7A, the baseline samples of the high bleeders group had higher RLU than those of the low bleeders on both the bleeding and non-bleeding sites. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and lower bleeders groups at both bleeding and non-bleeding sites.

The oral lavage samples were applied to the TLR4 reporter cells in a procedure as described in EXAMPLE 5. As shown in FIG. 7B, oral lavage (Healthy vs. Gingivitis) samples were evaluated in the TLR4-SEAP reporter assay. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the high bleeder group.

Example 8

The reporter gene cell lines, human HEK 293T cells, were purchased from Invivogen of San Diego, Calif. The HEK 293T cells were stably transfected with at least two exogenous genes, a TLR2 structural gene, and SEAP reporter gene which is under the control of NFkB transcriptional factors. The cell line is named here as TLR2-SEAP. The reporter gene encodes a secreted enzyme, called embryonic alkaline phosphatase or SEAP. The SEAP reporter is placed under the control of the interferon-β minimal promoter fused to five NFkB and AP-1-binding sites. Furthermore, a CD14 co-receptor gene was transfected into the reporter gene cells expressing TLR2, as CD14 has been identified as a co-receptor for TLR2 ligands to enhance the TLR response. The CD14 co-receptor is needed to transfer LTA to TLR2 receptors. The recombinant TLR2 binds its ligand, or distinct pathogen-associated molecule, initiates a chain of responses, leading to recruitment of NFkB and AP1 transcription factors to the reporter gene promoter, which induce expression of SEAP.

Cell culture and treatment: 500,000 gene reporter cells were grown and maintained in 15 ml growth medium, comprising DMEM medium supplemented with 10% fetal calf serum in T75 flasks for three days at 37° C., 5% CO2, and 95% humidity. For treatment with LTA, wells of a 96-well plate were seeded with 10,000 cells/well in 100 μL, of growth medium. The cells were incubated for 72 hours at 37° C., 5% CO2, and 95% humidity until day 4. On day 4, medium (100 μL) was changed to DMEM medium without fetal calf serum. LTA, LPS and bacterial cells, as described in EXAMPLE 7, were added. Samples were taken 24 hours later, following addition of samples. Expression of the reporter gene (SEAP) was quantified with a commercially available kit (SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich.).

As shown in FIGS. 8A, 8B, 8C and 8D, LTA, LPS, bacteria and the supernatant of bacterial culture could bind to TLR2 and activate TLR2 downstream signaling pathways in a dose-dependent manner. As shown in FIG. 8A, B. subtilis (BS) LTA is more potent than that of Enterococccus hirae. As shown in FIG. 8B, P. gingivalis LPS also activated expression of the TLR2 reporter gene. For example, Pg1690, as shown in FIG. 8B, activated TLR2-SEAP signal transduction, and stimulated SEAP production. But as shown in FIG. 8B, E. coli LPS did not activate the TLR2-SEAP reporter cells. It should also be noted that P. pallens, P. nigrescens and P. gingivalis have similar EC50 in stimulating expression of TLR2 reporter gene (FIG. 8C). However, the released TLR2 ligands from the three different bacteria have very different EC50 on activation of TLR2 reporter gene (FIG. 8D).

Example 9

The method described in EXAMPLE 8 is effective in determining the EC50 of LTA and other TLR2 ligands from different bacteria. The same method was used to determine the EC50 of clinical samples, as described in EXAMPLE 2. As shown in FIG. 9, dental plaques from unhealthy (bleeding) sites had smaller EC50 than those from healthy (non-bleeding) sites, suggesting the dental plaques from unhealthy sites contain more virulence factors.

Clinical samples as described for FIG. 7A of EXAMPLE 7 were examined using the TLR2-SEAP reporter gene assay. The results are shown in FIG. 10A. The subgingival samples in unhealthy (bleeding) sites from the unhealthy group (high bleeders) had more virulence factors than other sites. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders on both the bleeding and non-bleeding sites. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and low bleeders groups at both bleeding sites.

The clinical samples as described for FIG. 7B of EXAMPLE 7 were examined using the TLR2-SEAP reporter gene assay. As shown in FIG. 10B, oral lavage (Healthy vs. Gingivitis) was evaluated. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the high bleeder group.

Example 11

Bacterial cell wall and membrane components are recognized by TLR2. TLR2 recognizes the microbial motifs PGN (peptidoglycan)/lipoproteins/dectin and LPS. TLR1 and TLR6 form heterodimers with TLR2 and bind to triacylated lipoproteins and diacylated lipoproteins, respectively. THP1 NFkB-SEAP and IRF-Lucia™ Reporter Monocytes were purchased from Invivogen, San Diego, Calif. THP1-Dual cells were derived from the human THP-1 monocyte cell line by stable integration of two inducible reporter constructs. THP1-Dual cells feature the Lucia gene under the control of an ISG54 (interferon-stimulated gene) minimal promoter in conjunction with five interferon-stimulated response elements. THP1-Dual cells also express a SEAP reporter gene driven by an IFN-b minimal promoter fused to five copies of the NF-kB consensus transcriptional response element and three copies of the c-Rel binding site. As a result, THP1-Dual cells allow the simultaneous study of the NFkB pathway, by monitoring the activity of SEAP, and the interferon regulatory factor (IRF) pathway, by assessing the activity of Lucia (IRF-Luc). Both reporter proteins are readily measurable in the cell culture supernatant. This THP-1 cell line possesses functional TLR1, TLR2, TLR4, TLR5, TLR6 and TLR8, purchased from Invivogen. TLR4 senses LPS from Gram-negative bacteria while TLR5 recognizes bacterial flagellin from both Gram-positive and Gram-negative bacteria, TLR8 detects long single-stranded RNA.

Culture and treatment: The THP1-dual cells were cultured in 15 ml growth medium (RPMI 1640 with 10% heat-inactivated fetal bovine serum) in a T75 flask at 37° C. and 5% CO2. Cells were passed every 3 to 4 days by inoculating 300,000-500,000 cells/ml into a fresh T75 flask with 15 ml of fresh growth medium. To determine the effect of bacterial components on reporter gene expression, wells in 96-well plates were seeded at 100,000 cells in 90 μl of growth medium. 10 μl of bacterial wall and membrane components, or heat-killed whole bacteria, were added to each well. After incubation for 18 hours at 37° C. and 5% CO2, secreted luciferase and SEAP were quantified with commercially available assay kits (QUANTI-Luc of Invivogen, San Diego, Calif. for luciferase; SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich. for SEAP).

DHP1-dual reporter cells were treated with three different preparations of LPS as shown in FIG. 12A. All three LPS (ng/ml) activated production of NFkB-SEAP reporter genes in a dose-dependent manner. In addition, Pg 1690 LPS and E. coli LPS also stimulated expression of the IRF-luciferase reporter gene. TLR4 ligands, upon binding to TLR4 receptors, activate at least two signaling pathways. One is a common pathway NFkB-SEAP, which can be activated by all TLR ligands upon binding to their specific receptors. For example, TLR2 ligand, LTA, can bind to TLR2 receptors and activate the NFkB-SEAP signaling pathway. Similarly, TLR4 ligand, LPS, upon binding to TLR4 receptors, also is able to activate the NFkB-SEAP signaling transduction. As shown in FIG. 12A, E. coli LPS is a more potent ligand than P. gingivalis 1690 LPS on activation of both NFkB-SEAP and IRF-luciferase signaling transduction. THP-1 cells produce several functional TLR receptors. And all TLR receptors can activate the NFkB pathway, thus promoting expression of the NFkB-SEAP reporter gene. The reading of NFkB-SEAP is the collective actions of all TLR receptors, such as TLR2, TLR1, TLR6 and TLR4. All LPS from different bacteria stimulated NFkB-SEAP reporter gene. IRF-luciferase reporter gene, on the other hand, is driven by a limited number of TLR receptors, primarily TLR3, TLR4, TLR7, TLR8 and TLR9. Both P. gingivalis LPS 1690 and E. coli LPS stimulated expression of IRF-luciferase in a dose-dependent fashion.

The THP-1 reporter cells were used to examine the clinical samples as described for FIG. 7B of EXAMPLE 7. As shown in FIG. 12B, oral lavage (Healthy vs. Gingivitis) was evaluated using the IRF-Luc reporter gene in THP-1 cells. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and lower bleeders groups.

The THP-1 reporter cells were used to examine the clinical samples as described for FIG. 7A of EXAMPLE 7. As shown in FIG. 12C, the subgingival Plaque (Healthy vs. Gingivitis) was examined using the NFkB reporter gene in THP-1 cells. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the bleeding sites in both high and lower bleeders groups.

Example 12

THP1 dual reporter cells also express TLR2, TLR1 and TLR6 receptors. Bacterial cell wall and some membrane components are recognized by TLR2, TLR1 and TLR6. TLR2 recognizes the microbial motifs PGN (peptidoglycan)/lipoproteins/dectin and LPS. To determine whether LTA from different bacteria have different effects on stimulating NFkB-SEAP reporter gene expression in the THP1 dual reporter cells, the cells were prepared and treated in the same procedures as described in EXAMPLE 11. As shown in FIG. 13, LTA from both B. subtilis and S. aureus had similar potency in promoting reporter gene expression in the THP1 dual reporter cells.

Example 14

A randomized, two-group clinical study was conducted with 69 panelists (35 in the negative control group and 34 in the test regimen group). Panelists were 39 years old on average, ranging from 20 to 69, and 46% of the panelists were female. Treatment groups were well balanced, since there were no statistically significant (p>0.395) differences for demographic characteristics (age, ethnicity, gender) or starting measurements for Gingival Bleeding Index (GBI); mean=29.957 with at least 20 bleeding sites, and Modified Gingival Index (MGI); mean=2.086. All sixty-nine panelists attended each visit and completed the treatment process. The following treatment groups were compared over a 6-week period:

Test regimen: Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse. Control regimen: Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush.

Dental plaques were collected from the same panelists in the test regimen in the clinical study as described in EXAMPLE 2. A supragingival sample was taken from each panelist with a sterile curette at the tooth/gum interface, using care to avoid contact with the oral soft tissue. Plaques were sampled from all available natural teeth (upper arch only) until no plaque was visible. Following sampling, the plaque samples were placed into a pre-labeled (panelist ID, sample initials, visit, and date) Eppendorf tube with 1 ml of PBS/Glycerol buffer and about 50 of sterile 1 mm glass beads, stored on ice until all samples were collected. The samples were then transferred to a −70° C. freezer for storage until further processing. Genomic DNA was isolated from supragingival plaque samples using QIAamp® genomic DNA kits (Qiagen, Germany) following manufacturer's instruction. Metasequencing was carried out at BGI Americas Corporation (Cambridge, Mass.). All data were analyzed at Global Biotech of Procter & Gamble Company in Mason, Ohio.

Clinical measurements: Bleeding sites (GBI) were decreased in the test regimen significantly on week 1, 3 and 6 in comparison to the control regimen (FIG. 14). Similarly, Inflammation (MGI) grades also decreased in the test regimen (FIG. 14).

Genomic DNA of the supragingival plaques in the test regimen was sequenced. As shown in FIG. 15, abundance of certain bacteria in the supragingival plaques changed in the six week treatments. Certain bacteria, such as Porphyromonas sp oral taxon 279 and Prevotella pallens, were decreased in weeks 1 and 3 (FIG. 15). The amount of each bacterial species was plotted over the four time periods of the treatment. The amount of certain bacteria, such as Peptostreptococcus stomatis and Prevotella intermedia, was reduced during the six week of treatment as shown in FIG. 15.

Example 15

In the same clinical study as described in EXAMPLE 14, gingival-brush samples were collected from the same panelists as in EXAMPLE 14. Before sampling, panelists rinsed their mouths for 30 seconds with water. A dental hygienist then sampled the area just above the gumline using a buccal swab brush (Epicentre Biotechnologies cat.# MB 100SP). The swab was immediately placed into 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Lifetechnologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube vortexed for 30 seconds, and immediately frozen on dry ice and stored in a −80 C freezer until analysis. The samples were taken out of freezer, thawed and extracted by placing the samples on a tube shaker for 30 minutes at 4° C. The tubes were centrifuged at 15000 RPM for 10 min in Eppendorf Centrifuge 5417R (Eppendorf, Ontario, Canada) to pellet any debris. The extract (800 μl) was analyzed for protein concentrations using the Bio-Rad protein assay (BioRad, Hercules, Calif.).

Forty proteins were measured in the gingival samples using V-PLEX Human Biomarker 40-Plex Kit (Meso Scale Diagnostics Rockville, Md.). The assay was performed following the manufacturer's instruction.

Among the proteins measured in the gingival samples, most proteins in the Proinflammatory Panel 1 (human), Cytokine Panel 1 (human), Chemokine Panel 1 (human), Angiogenesis Panel 1 (human), and Vascular Injury Panel 2 (human) had significant changes in their abundance during the 6-week treatment (TABLE 6). Those include FN-γ, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, GM-CSF, IL-5, IL-16, IL-7, IL-12/IL-23p40, IL-1α, VEGF-A, IL-17A, IL-15, TNF-β, IL-8 (HA), MCP-1, MCP-4, Eotaxin, IP-10, MDC, Eotaxin-3, TARC, MIP-1α, MIP-1β, VEGF-C, VEGF-D, Tie-2, Flt-1/VEGFR1, PlGF, FGF (basic), SAA, CRP, VCAM-1, and ICAM-1.

TABLE 6
Changes in abundance of proteins in the gingival-brush samples
Meanα = 0.05
BaselineWeek 1Week 3Week 6BaselineWeek 1Week 3Week 6
ICAM-116.03512.20910.0909.767ABB, CC
IL-1α3.5542.3312.1811.891AA, BB, CC
IL-1β53.66635.57524.29524.440ABCC
TNF-β0.00130.00100.00080.0007ABCC
IL-12p700.1720.1480.1180.127AA, BCB, C
IL-130.8050.7620.6240.648AA, BCB, C
IL-40.1270.1150.0900.096AA, BCB, C
IL-50.0040.0030.0020.003ABCB, C
CRP15.63712.74312.3855.809AAAB
Eotaxin0.0770.0640.0590.059AA, BBB
GM-CSF0.0100.0080.0080.008ABBB
IFNγ0.5300.4460.3780.386AA, BBB
IL-100.8750.4900.4230.244AA, BBB
IL-150.0050.0030.0030.003ABBB
IL-160.4660.3450.3420.295ABBB
IL-60.1960.1920.1680.150AAA, BB
IL-70.0040.0030.0030.003ABBB
IL-8856.276652.066567.361572.602ABBB
MCP-10.0530.0470.0390.039AA, BBB
MDC0.3990.4070.3450.339AABB
SAA7.0396.9056.0925.162AAA, BB
Tie-20.2730.2390.2670.221AA, BAB
VCAM-14.9713.7063.1562.892ABBB
VEGF0.6250.5110.4780.480ABBB
VEGF 20.7720.6610.6200.582ABBB
VEGF-D0.0570.0520.0510.045AA, BA, BB
VEGF-C0.1450.1490.1250.137A, BABA, B
TARC0.0200.0290.0190.019ABAA
bFGF0.0200.0150.0120.013AAAA
Eotaxin-30.0950.1080.0910.094AAAA
Flt-10.3900.5180.4330.415ABA, BA
IL-12p400.0390.0310.0280.031AAAA
IL-20.1660.1990.2100.162AAAA
IL-8 (HA)47.50844.36241.26039.119AAAA
IP-100.5401.6880.7400.606AAAA
MCP-40.0230.0230.0200.022AAAA
MIP-1α0.0910.0910.0840.080AAAA
MIP-10.0910.1000.1100.094AAAA
TNFα2.0092.0672.0211.670AAAA

Example 16

The same gingival-brush samples as described in EXAMPLE 15 were used for metabonomic analyses. Fourteen panelists were selected randomly from each treatment group to determine if any metabolite concentrations were changed in gingival samples during the first 3 weeks of treatment. Both baseline and week 3 samples were sent to Metabolon, Inc. (Durham, N.C.) for metabonomic measurement. 170 metabolites were identified and quantified. As shown in TABLE 7, some metabolite concentrations were changed during the first 3 weeks of treatment. Citrulline concentrations in the gingival samples were reduced after three weeks of treatment in the treatment regimen group. Similarly, ornithine was also reduced in the treatment regimen group after three weeks of treatment. Reduction of citrulline and ornithine was likely associated with alleviation of gingivitis.

TABLE 7
Comparison of metabolites in gingival brush samples between baseline and week 3 during gingivitis treatment
Baseline3 week 3 week/
Biochemical Namemeanmeanbaselinep-value q-valueMass
13-HODE + 9-HODE1.08770.70880.650.06010.1338295.2
1-arachidonoylglycero-1.22940.82740.670.0380.1035500.3
phosphoethanolamine
1-oleoylglycero-0.73781.07471.460.07670.1548478.3
phosphoethanolamine
2-methylbutyrylcarnitine1.77690.69970.390.00340.0546246.1
(C5)
adenosine 5′-monophosphate1.40920.84510.60.02950.0956348.1
(AMP)
alanine0.87211.1021.260.03180.0973115.9
arginylleucine1.44470.68190.470.00840.0777288.3
arginylphenylalanine0.96160.33350.350.01190.0777322.2
asparagylleucine0.92950.61220.660.06980.1465246.2
citrulline1.01470.710.70.01040.0777176.1
deoxycarnitine3.23810.60880.190.00030.0168146.1
EDTA1.59850.83840.520.01380.0777291.1
erythritol1.6250.80850.50.05820.1325217
fructose1.99331.11060.560.08470.1605217
glutamine1.24590.83660.670.03740.1035147.2
glutathione, oxidized (GSSG)1.01611.46691.440.0870.1605613.1
glycerol1.37830.83080.60.03910.1035205
lauryl sulfate1.6850.86230.510.03970.1035265.2
leucine1.21580.93590.770.06130.1338132.2
leucylleucine0.95050.43930.460.02510.0877245.1
lysylleucine1.20090.52750.440.00360.0546260.2
lysylphenylalanine1.16820.45630.390.00950.0777294.3
maltose0.87271.44811.660.0220.0877204.1
maltotriose1.04561.83471.750.08580.1605204
mannitol1.30040.79820.610.0420.107319.1
ornithine1.29160.70690.550.03670.1035141.9
palatinitol1.43950.82720.570.07820.1549204
phosphate1.40080.83760.60.02080.0877298.9
proline1.4050.990.70.00330.0546116.1
propionylcarnitine1.25650.76880.610.02010.0877218.2
pyroglutamine1.34240.78730.590.01360.0777129.2
serylisoleucine1.17530.71690.610.08140.1583219.2
spermidine1.16130.86780.750.06870.1465146.2
succinate1.29290.81130.630.07540.1548247
threonylleucine1.15130.49310.430.00440.0594231.2
threonylphenylalanine1.76930.9180.520.02330.0877267.2
trehalose2.35630.90840.390.00540.0647361.2
tryptophan1.15180.90890.790.04870.1185205.1
tyrosine1.3831.02990.740.01610.0787182.1
valine1.15980.92710.80.03040.0956118.1
valylvaline0.93470.82310.880.05080.1207215.2
X-136710.50350.9181.820.05450.1267315.3
X-145881.36470.83780.610.0240.0877151
X-161031.36430.84610.620.02970.095699.3
X-172661.31580.5760.440.00030.0168530.4
X-173751.47850.83870.570.01890.0877357.1
X-184720.61381.14411.860.00110.0405827.1
X-187791.37560.80350.580.01620.0787209.1
X-196071.52370.71670.470.0020.0537366.1
X-196091.32840.77210.580.0160.0787204
X-196121.38960.78430.560.010.0777427.2
X-196131.34120.75350.560.00990.0777429.3
X-196141.33780.73430.550.04540.113570.1
X-198071.34780.84110.620.02440.087793
X-198081.33480.83680.630.02540.087795
X-198501.35760.75190.550.0110.0777334.2
X-198571.33570.80320.60.0380.1035230
X-200001.27840.75360.590.01330.077781.2

Example 17

Quantitation of citrulline and ornithine from the extracts of the Gingival-brush samples was conducted using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Gingival-brush samples were obtained from the same human panelists in the clinical study as described in EXAMPLE 14, and were placed into extraction buffer as described in EXAMPLE 15. The supernatants were subject to both HILIC/MS/MS and BCA analysis. For free citrulline and ornithine analysis, the extracts of the Gingival-brush samples were analyzed either directly (50 μl undiluted sample solution) in 50/50 acetonitrile/ultra-pure water with 0.754% formic acid or diluted fivefold. For total citrulline and ornithine analysis, the extracts of the Gingival-brush samples were first hydrolyzed using 6 N HCl (50 μL of extract with 450 μL of 6N HCl), no shaking, and placed on a hot plate at 110° C. for 16 hours. The hydrolyzed samples were then dried down under vacuum at room temperature (Savant speedvac of Lifetechnology, Grand Island, N.Y.) and then reconstituted in 1 ml of dilution solution (50/50 acetonitrile/ultra-pure water with 0.754% formic acid) for analysis. The standards and the samples were analyzed using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Analytes and the corresponding ISTDs (stable isotope labeled internal standard) were monitored by electrospray ionization (ESI) in positive mode using the selected-reaction-monitoring schemes shown in TABLE 8. A standard curve was constructed by plotting the signal, defined here as the peak area ratio (peak area analyte/peak area ISTD), for each standard versus the mass of each analyte for the corresponding standard. The mass of each analyte in the calibration standards and Gingival-brush extract samples were then back-calculated using the generated regression equation. The concentration of protein bound citrulline or ornithine was calculated as the result of subtracting the concentration of free citrulline or ornithine from the concentration of total citrulline or ornithine, respectively. The result was reported as the concentration of citrulline or ornithine or the result was standardized by dividing by the amount of citrulline or ornithine by the amount of the total proteins that were found in the extract.

TABLE 8
Multiple Reaction Monitoring (MRM) transitions for analytes and
their corresponding stable isotope labeled internal standards
AnalytesMRMInternal StandardsMRM
Citrulline176 → 159d7-Citrulline181 → 164
Ornithine133 → 70 d6-Ornithine139 → 76 

All samples from all panelists of the Test regimen [Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse] were analyzed. As shown in FIG. 16, citrulline levels reduced rapidly in the first week of treatment, and then continued to decline gradually in weeks 3 and 6 of treatment. These results are consistent with clinical observations, where gingival bleeding sites (GBI) and the gingival inflammation (MGI) were reduced over the 6-week treatment period.

Example 18

The same samples as described in EXAMPLE 17 were analyzed using procedures as described in EXAMPLE 17. Gingivitis was treated for 6 weeks. Baseline (BL) represents diseased status. Symptoms of gingivitis were alleviated from week 1 to week 6 treatments. Protein bound ornithine (the difference between total and the free ornithine) was higher in gingivitis as shown in FIG. 17. Protein bound ornithine was reduced gradually as gingivitis was decreased in severity.

Example 19

Gingival samples were collected as described in EXAMPLES 15, from the same panelists as in EXAMPLE 15, and were used to examine the expression of genes during 6 weeks of treatments with Test regimen [Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse] and Control regimen [Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush].

After harvesting the samples, the brush was completely immersed in the RNAlater solution (1 ml in in a 1.5 ml Eppendorf tube) for keeping RNA from degrading during transport and storage (Qiagen, Valencia, Calif.). The microcentrifuge tubes were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12): 1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

The ornithine-citrulline-arginine cycle consists of four enzymes (FIG. 18). The main feature of the cycle is that three amino acids (arginine, ornithine, and citrulline) can be converted to each other. The first enzyme is ornithine transcarbamoylase, which transfers a carbamoyl group from carbamoyl phosphate to ornithine to generate citrulline. This reaction occurs in the matrix of the mitochondria. Expression of ornithine transcarbamoylase was reduced in the treatment (FIG. 19). The second enzyme is argininosuccinate synthetase. This enzyme uses ATP to activate citrulline by forming a citrullyl-AMP intermediate, which is attacked by the amino group of an aspartate residue to generate argininosuccinate. This and subsequent two reactions occur in the cytosol. Again, expression of argininosuccinate synthetase decreased during the treatment. The third enzyme is argininosuccinate lyase, which catalyzes cleavage of argininosuccinate into fumarate and arginine. The last enzyme is argininase. Argininases cleave arginine to produce urea and ornithine. In a contrast to the decreased expression of ornithine transcarbamoylase and argininosuccinate synthetase genes, argininase I and II increased (FIG. 19).

Arginine is also a substrate for nitric oxide synthase, which oxidizes arginine to produce citrulline and nitric oxide. Expression of nitric oxide synthase gene increased too (FIG. 19).

Example 20

Experimental Gingivitis:

Another clinical study was carried out to determine whether citrulline is increased in experimentally induced gingivitis in healthy human panelists. This was a case-control study enrolling 60 panelists. The study population included two groups as follows: Group 1 or high bleeders group, thirty (30) panelists with at least 20 bleeding sites, where bleeding is a GBI site score of 1 or 2 at baseline. Group 2 or low bleeders group, thirty (30) panelists with 2 or less bleeding sites, where bleeding is a GBI site score of 1 or 2.

The Study Consisted of Two Phases:

Health/Rigorous Hygiene Phase with dental prophylaxis, polishing and rigorous oral hygiene; and Induced Gingivitis Phase without oral hygiene. At the Screening visit, panelists underwent an oral soft tissue assessment and had a gingivitis evaluation (Modified Gingival Index (MGI) and Gingival Bleeding Index (GBI). At Visit 2 qualifying panelists received an oral soft tissue exam followed by a gingivitis evaluation and gingival plaques and gum swabs were collected for the qPCR, protein and RNA host biomarker analysis. Following that, all panelists received dental prophylaxis and entered the Health/Rigorous Hygiene Phase, lasting two weeks. After two weeks of rigorous hygiene, panelists entered the Induced Gingivitis Phase, lasting for three weeks. Oral soft tissue exams and gingivitis were re-evaluated and all samples (gum swabs) were collected at Baseline, WK0 and WK2.

Gingival Sample Collection—

A gum swab was collected from each side of the upper arch using the procedures as described in EXAMPLE 15. Gum swabs were collected close to the gum line from the buccal sites only (preferably from four adjacent teeth—preferably from premolar and molar areas). Panelists rinsed for 30 seconds with 15 ml of Listerine rinse to clean the surface of sampling area. After the Listerine rinse, panelists rinsed for 30 seconds with 20 ml of water. Following that, selected sites were isolated with a cotton roll and gently dried with an air syringe and two gum swabs were taken with collection brushes/swabs from the gingiva region close to the gumline of the selected teeth. The samples were placed in a pre-labeled (panelist ID, sample ID, visit, and date) 1.5 ml micro-centrifuge tube containing 800 ul DPBS (Dulbecco's phosphate-buffered saline) (Lifetechnologies, Grand Island, N.Y.) with protease inhibitors, including AEBSF (4-(2-Aminoethyl)benzenesulfonyl fluoride hydrochloride) 2 mM, aprotinin 0.3 μM, Bestatin 130 μM, EDTA (Ethylenediaminetetraacetic acid) 1 mM, E-64 1 μM, and leupeptin 1 μM. The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. Samples from three visits were analyzed using the procedures described in EXAMPLE 17, and shown in FIG. 20. Those three visits were baseline, Week 0, (right after the Health/Rigorous Hygiene Phase and before the induced gingivitis phase) and week 2 (at the end of Induced Gingivitis Phase). Free citrulline levels were low in both the high and low bleeders groups at the baseline and week 0, but rose quickly in the induced gingivitis in both groups at week 2.

Example 21

The same procedures were used as described in EXAMPLE 17. The samples were the same as described in EXAMPLE 20. Protein bound citrulline was lower at the baseline than that at week 0 in both high and low bleeders groups as shown in FIG. 21 in gingival tissue. It was low in experimental gingivitis in both groups at week 2.

Example 22

The same clinical samples from experimental gingivitis (EXAMPLE 20) were analyzed using the procedures described in EXAMPLE 17. The bound ornithine was the lowest at week 0 (FIG. 22) in both groups. Its levels at the baseline were higher than those at week 0. The bound ornithine reached peaks when gingivitis was induced in both groups at week 2. Also it is worth noting the total ornithine (Free and protein bound ornithine) was increased in the induced gingivitis (FIG. 23) in both groups.

Example 23

The same procedures were used as described in EXAMPLE 17. The samples were the same as described in EXAMPLE 20. The protein bound arginine was the lowest in induced gingivitis (FIG. 24) in both groups. Its levels were higher in WK0 than at Baseline in both groups. The total arginine in the gingival brush samples displayed the same patterns as the protein bound one (FIG. 25).

Example 24

Citrulline was purchased from Sigma-Aldrich (St. Louis, Mo.). THP1-Dual™ cells were purchased from Invivogen (San Diego, Calif.). Cells were cultured following the manufacturer's instruction, as described in EXAMPLE 11. For treatment, 0.3 mM to 9 mM of citrulline were first added to the culture medium. Then, 300 ng/ml of P. gingivalis LPS 1690 were added 60 minutes later. After 24 hours of treatment, media was collected and analyzed for cytokine production using 9-plex kit (Meso Scale Diagnostics Rockville, Md.).

P. gingivalis LPS 1690 stimulated cytokine production, as shown in FIG. 26. Citrulline inhibited P. gingivalis LPS 1690 effects on proinflammatory cytokine production in a dose-dependent manner. Those cytokines include IL-6, TNF-α, IL-12p70, IL-10, IL-2, IFN-r and IL-1β.

Example 26

Growth of bacteria: Two bacteria, Bacterium A and Bacterium B, were cultured in Tryptic Soy Broth medium (Sigma-Aldrich, St. Louis, Mo.) at 37° C. with shaking at 200 rpm. The bacteria were harvested at 24 hours, and suspended in 0.5 ml of phosphate-buffered saline, labeled “live”. Half ml of “Live” bacteria was transferred to a 1.5 ml microtube, and heated to 80° C. for 30 min. The heat-treated bacteria were labeled “Heat-Inactivated”, or “Dead”.

Measurement of TLR responses in THP-1 gene reporter cells (NFkB-SEAP): The Live and Heat-Inactivated bacteria were applied to THP-1 cells as described in EXAMPLE 11. As shown in FIG. 31, EC50 of Bacterium A and B on activation of NFkB-SEAP reporter gene in THP-1 cells was determined. Both Live and Heat-inactivated (Dead) bacteria stimulated expression of the NFkB-SEAP reporter gene. Bacterium B had a lower EC50 than Bacterium A in activating expression of the NFkB-SEAP reporter gene.

Cytokine production and measurement: Human peripheral bleed mononuclear cells (hPBMC) were obtained from All Cells company (All Cells, Alameda, Calif.) as Leukapheresed blood. Leukapheresed blood was mixed with an equal part of DMEM+glutaGRO supplemented with 9.1% fetal bovine serum and 1% penicillin/streptomycin (Thermo Fisher, Waltham, Mass.). hPBMC were isolated from the 1:1 mixture of blood and culture medium by collecting the buffy coat of a centrifuged Histopaque®-1077 (Sigma-Aldrich, St. Louis, Mo.) buffer density gradient. The cells (200,000 cells) were cultured in 200 μl of DMEM+glutaGRO supplemented with 9.1% fetal bovine serum and 1% penicillin/streptomycin, and treated with Live and Heat-Inactive bacteria (6,250,000 colony-forming units). The medium was harvested at 24 hours after adding the bacteria, and analyzed for proinflammatory cytokines in a kit following manufacturer's instruction (Meso Scale Diagnostics, Rockville, Md.).

As shown in TABLE 9, both live bacterium A and B stimulated production of cytokines in hPBMC. Bacteriun B was far more potent than Bacterium A in promoting production of IFN-T, IL-10, IL-12p70, IL-1β, IL-6, IL-8 and TNF-α in hPBMC.

StatisticsCytokinesLive Bacterium ALive Bacterium
MeanIFN-γ867.1612734.36
MeanIL-1068.35412.51
MeanIL-12p7023.75253.47
MeanIL-1β2300.866969.31
MeanIL-244.2465.17
MeanIL-63431.059963.84
MeanIL-865742.9170357.25
MeanTNF-α3710.6613825.49
Std DevIFN-γ488.118200.13
Std DevIL-1033.56314.23
Std DevIL-12p7014.71283.33
Std DevIL-1β1569.727691.93
Std DevIL-232.9736.29
Std DevIL-62212.626552.12
Std DevIL-818689.2413669.28
Std DevTNF-α2503.258302.26

The dimensions and values disclosed herein are not to be understood as being strictly limited to the exact numerical values recited. Instead, unless otherwise specified, each such dimension is intended to mean both the recited value and a functionally equivalent range surrounding that value. For example, a dimension disclosed as “40 mm” is intended to mean “about 40 mm.”

Every document cited herein, including any cross referenced or related patent or application and any patent application or patent to which this application claims priority or benefit thereof, is hereby incorporated herein by reference in its entirety unless expressly excluded or otherwise limited. The citation of any document is not an admission that it is prior art with respect to any invention disclosed or claimed herein or that it alone, or in any combination with any other reference or references, teaches, suggests or discloses any such invention. Further, to the extent that any meaning or definition of a term in this document conflicts with any meaning or definition of the same term in a document incorporated by reference, the meaning or definition assigned to that term in this document shall govern.

While particular embodiments of the present invention have been illustrated and described, it would be obvious to those skilled in the art that various other changes and modifications can be made without departing from the spirit and scope of the invention. It is therefore intended to cover in the appended claims all such changes and modifications that are within the scope of this invention.

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Patent 2018
Samples -A total of 48 T. cruzi stocks from T. infestans and three from Rhodnius pictipes captured in various Bolivian areas in domestic and peridomestic sites were isolated. The digestive tract of each insect was placed in NNN biphasic medium supplemented with 1.5 ml of LIT medium and incubated at 28 o C without shaking. Then subcultures of parasites were processed in small volumes of LIT medium (3 ml) until their adaptation. Mass cultures were obtained by subcultures in higher LIT medium volumes (10 to 50 ml) at 28 o C without shaking. Finally, the adequate quantity of parasites for isoenzyme electrophoresis (20-50 mg of parasite pellet) was obtained after 4 to 6 weeks. The genetic characterization of the stocks by isoenzyme and PCR/hybridization was done from the same collection of cultured parasites.
All fecal samples presented flagellates (direct microscopical observation) and before isolation of the stocks, a drop of feces from each insect was collected in appropriate PCR conditions and preserved at -20 o C for further determination of the clonal composition by PCR/hybridization.
Identification of clonet 20 and 39 by PCR/ hybridization -The procedures for feces collection, extraction and PCR were according to Brenière et al. (1992 Brenière et al. ( , 1995)) , using primers (Genset, Paris, France) chosen to amplify the hyper variable region of the kinetoplast minicircles (HVRm). After electrophoresis the PCR products were transferred on to membranes and successively hybridized with the specific clonet probes 20 and 39 (Veas et al. 1991 , Brenière et al. 1992 ). Total DNAs were purified by phenol/chloroform extraction from parasite pellets of each stock and similarly, the clonets were detected by hybridization of the PCR products amplified from total DNAs.
Isoenzyme characterization -The electrophoretic study was carried out on cellulose acetate plates, according to Ben Abderrazak et al. (1993) with slight modifications. Twelve enzymes systems were surveyed (13 enzymatic loci): glutamate oxaloacetate transaminase (GOT, EC 2.6.1.1), glucose-6-phosphate dehydrogenase (G6PD, EC 1.1.1.49), glucose phosphate isomerase (GPI, EC 5.3.1.9), glutamate dehydrogenase NAD+ (GDH NAD+, EC 1.4.1.2), glutamate dehydrogenase NADP+ (GDH NADP+, EC 1.4.1.4), isocitrate dehydrogenase (IDH, EC 1.1.1.42), malate dehydrogenase (MDH, EC 1.1.1.37), malic enzyme (ME, EC 1.1.1.40), peptidases (substrates: L-leucylleucine-leucine and L-leucyl-L-alanine) (PEP, EC 3.4.11 or 13.*), 6-phospho-gluconate dehydrogenase ( PGDH, EC 1.1.1.44), and phosphoglucomutase (PGM, EC 2.7.5.1). Jaccard's distances (Jaccard 1908) were used to estimate the phenetic divergence between the stocks. The UPGMA method [unweighted pair-group method with arithmetic averages, Sneath and Sokal (1973) ] was used to cluster the zymodemes according to their Jaccard's distances. The dendrogram was obtained using the Mac Dendro software computer program (Thioulouse 1989) .
Publication 2000

Most recents protocols related to «Leucylleucine»

Example 2

Analysis Populations

The “Discovery-Full Analysis Set” (“Discovery FAS”) consisted of pilot study patients with clinical data and a CT-based designation of either Revascularization CAD case, Native CAD case, or Control (N=748 for the Discovery-FAS group).

The “Discovery-Native CAD Set” was the subset of the Discovery-FAS with Native CAD as verified by CT, who had analyte (metabolomic) data (N=366 for the Discovery-Native CAD Set). These were subjects without previous revascularization procedures, such as percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG).

The “Discovery-Revasc CAD Set” was the subset of the Discovery-FAS who had undergone previous revascularization, such as percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG), and who had analyte data (N=44).

The “Discovery-All CAD Set” was the union of the Discovery-Native CAD Set and the Discovery-Revasc CAD Set (N=410).

The “Discovery-Control Set” was the subset of Discovery-FAS who had a calcium score of zero and were designated a Control after inspection of CT data, and who had analyte data. (N=338 for the Discovery-Control Set.)

The “Validation-Full Analysis Set” (“Validation-FAS”) consisted of pilot study patients with clinical data and a CT-based designation of either Revascularization CAD case, Native CAD case, or Control (N=348 for the Validation-FAS group).

The “Validation-Native CAD Set” was the subset of the Validation-FAS with Native CAD as verified by CT, who had analyte (metabolomic) data (N=207 for the Validation-Native CAD Set). These were subjects without previous revascularization procedures, such as percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG).

The “Validation-Revasc CAD Set” was the subset of the Validation-FAS who had undergone previous revascularization, such as percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG), and who had analyte data (N=15).

The “Validation-All CAD Set” was the union of the Validation-Native CAD Set and the Validation-Revasc CAD Set (N=222).

The “Validation-Control Set” was the subset of Validation-FAS who had a calcium score of zero and were designated a Control after inspection of CT data, and who had analyte data. (N=126 for the Validation-Control Set)

It is noted that by design, the only racial group represented in the study was White. Therefore, race-based sub-populations were not defined.

A. Study Endpoints

For the GLOBAL Pilot Discovery Cohort, there were four primary endpoints in the analysis: (1) Native CAD; (2) All CAD (Native or Revascularization); (3) 50% Stenosis without Revascularization; (4) 50% Stenosis or Revascularization. All analyses were applied to all primary endpoints.

B. Statistical Hypothesis

The null hypothesis of no association, between the metabolite or lipid and the endpoint, was tested against the two-sided alternative that association exists.

C. Multiple Comparisons and Multiplicity

False discovery rate (FDR) q-values were calculated (Benjamini and Hochberg, 1995). Associations with FDR q<0.05 were considered preliminary associations. In some circumstances, test results with raw p<0.05 were reported as well.

D. Missing Data

Endpoint data was not imputed. Potential covariates with more than 5% missing data were excluded. Potential covariates with less than 5% missing data were imputed to the mean.

Metabolites with more than 10% missing data were excluded from the main analyses. Missing values for metabolites and lipids with less than 10% missing were imputed to the observed minimum after normalization.

E. Analysis of Subgroups

The first and third primary endpoints were addressed using a subset of the FAS. Specifically the Native CAS Set and the Control Set were considered to the exclusion of the Revasc. CAD Set. For the purposes of discovery, further subsets were created on the basis of participants' fasting status, where patients were categorized as Fasting if they had not eaten for eight or more hours. The remainder, either known not to be fasted, or with unknown fasting status were categorized as ‘Non-Fasting’. See FIG. 50.

I. Demographic and Baseline Characteristics

The baseline and demographic characteristics of patients in the pilot study were tabulated. Continuous variables were summarized by the mean and standard error; binary variables were summarized by the count and percentage.

Table 27 shows general patient characteristics for the Discovery Set by clinical group (Revasc CAD vs. Native CAD vs. Control). A Kruskall-Wallis test was performed to investigate homogeneity of continuous measures; a Pearson's chi-squared test was conducted for binary measures; unadjusted p-values are reported.

Table 28 shows general patient characteristics for the Validation Set by clinical group (Revasc CAD vs. Native CAD vs. Control). A Kruskall-Wallis test was performed to investigate homogeneity of continuous measures; a Pearson's chi-squared test was conducted for binary measures; unadjusted p-values are reported.

TABLE 27
All ControlsNative CADRevasc CADP-value
N33836644
Age
mean (SE)53.8 (0.57) 58.02 (0.54) 59.55 (1.40)  3.93E−07
SBP
mean (SE)129.62 (0.91)  132.6 (0.92) 128.09 (2.32)  0.0550
DBP
mean (SE)79.03 (0.56) 79.73 (0.58) 75.12 (1.57)  0.0402
Male
N (%)151 (44.67)195 (53.28)30 (68.18)0.0037
Hypertension
N (%)172 (51.04)244 (66.85)40 (90.91)1.61E−08
Dyslipidemia
N (%)184 (55.42)259 (71.15) 43 (100.00)4.95E−10
Diabetes (Any)
N (%)25 (7.40) 54 (14.75)10 (22.73)8.00E−04
Type I Diabetes
N (%) 1 (0.30) 1 (0.27)0 (0.00)0.9377
Type II Diabetes
N (%)24 (7.10) 53 (14.48)10 (22.73)6.00E−04
Current Smoker
N (%) 39 (11.54) 67 (18.31) 5 (11.36)0.0331
Former Smoker
N (%) 84 (24.85)130 (35.52)21 (47.73)5.00E−04
Chest Pain
N (%)221 (65.38)212 (57.92)30 (68.18)0.0850
Angina
Equivalent
N (%)126 (37.28)122 (33.33)19 (43.18)0.3115
Shortness of Breath
N (%) 74 (21.89) 71 (19.40) 8 (18.18)0.6635
Family History of CAD
N (%)179 (52.96)223 (60.93)28 (63.64)0.0710
Fasting
N (%)120 (35.50)207 (56.56) 44 (100.00)8.28E−18
Statin
N (%)111 (32.84)184 (50.27)38 (86.36)1.28E−12
Niacin
N (%) 5 (1.48) 4 (1.09)3 (6.82)0.0164
Fibrate
N (%)12 (3.55)21 (5.74)3 (6.82)0.3254
Ezetimibe
N (%) 6 (1.78)11 (3.01) 8 (18.18)7.97E−08
Fish Oil
N (%)26 (7.69) 50 (13.66) 5 (11.36)0.0388
Bile Acid Sequestrant
N (%) 3 (0.89) 4 (1.09)0 (0.00)0.7705
Aspirin
N (%) 98 (28.99)157 (42.90)34 (77.27)3.15E−10
Clopidogrel
N (%) 7 (2.07)11 (3.01)15 (34.09)5.21E−22
Vitamin K Antagonist
N (%) 7 (2.07)17 (4.64)2 (4.55)0.1629
Nitrate
N (%) 7 (2.07)16 (4.37)11 (25.00)5.57E−11
Beta Blocker
N (%)114 (33.73)140 (38.25)34 (77.27)1.68E−07
ACE Inhibitor
N (%) 63 (18.64)106 (28.96)24 (54.55)3.13E−07

TABLE 28
All ControlsNative CADRevasc CADP-value
N12620715
Age
mean (SE)49.48 (0.93)  60.83 (0.59)  68.6 (2.05) 3.35E−22
SBP
mean (SE)127.25 (1.55)  131.46 (1.10)  131.8 (4.16)  0.0276
DBP
mean (SE)77.33 (0.98)  78.99 (0.77)  78.87 (3.16)  0.2091
Male
N (%)46 (36.51)138 (66.67)  15 (100.00)1.36E−09
Hypertension
N (%)51 (40.48)132 (63.77) 13 (86.67)9.44E−06
Dyslipidemia
N (%)65 (53.72)152 (74.88)  14 (100.00)1.33E−05
Diabetes (Any)
N (%)12 (9.52) 44 (21.36) 4 (26.67)0.0134
Type I Diabetes
N (%)1 (0.79)3 (1.45)1 (6.67)0.1954
Type II Diabetes
N (%)11 (8.73) 41 (19.81) 3 (20.00)0.0244
Current Smoker
N (%)20 (15.87)28 (13.53)0 (0.00)0.238
Former Smoker
N (%)25 (19.84)78 (37.68) 8 (53.33)6.00E−04
Chest Pain
N (%)96 (76.19)110 (53.14)  7 (46.67)7.78E−05
Angina Equivalent
N (%)46 (36.51)53 (25.60) 5 (33.33)0.1037
Shortness of Breath
N (%)28 (22.22)30 (14.49) 7 (46.67)0.0038
Family History of CAD
N (%)53 (42.06)129 (62.32)  6 (40.00)8.00E−04
Fasting
N (%)126 (100.00)207 (100.00) 15 (100.00)NA
Statin
N (%)39 (30.95)125 (60.39) 13 (86.67)2.28E−08
Niacin
N (%)1 (0.79)3 (1.45)0 (0.00)0.7872
Fibrate
N (%)4 (3.17)7 (3.38)1 (6.67)0.7797
Ezetimibe
N (%)1 (0.79)5 (2.42)0 (0.00)0.4745
Fish Oil
N (%)8 (6.35)23 (11.11)1 (6.67)0.3251
Bile Acid Sequestrant
N (%)0 (0.00)0 (0.00)0 (0.00)NA
Aspirin
N (%)28 (22.22)99 (47.83) 9 (60.00)4.91E−06
Clopidogrel
N (%)1 (0.79)2 (0.97) 4 (26.67)3.16E−11
Vitamin K Antagonist
N (%)6 (4.76)3 (1.45)1 (6.67)0.1432
Nitrate
N (%)3 (2.38)10 (4.83)  3 (20.00)0.0084
Beta Blocker
N (%)36 (28.57)77 (37.20)12 (80.00)4.00E−04
ACE Inhibitor
N (%)26 (20.63)59 (28.50) 9 (60.00)0.0039
II. Exploratory Data Analyses for Metabolites

Sample preparation and mass spectrometry analyses were conducted by Metabolon, Inc. The raw data contained a total of 1088 analytes, measured for 1096 pilot study participants.

Of the 1088 analytes (including unnamed metabolites and complex lipids), 481 named metabolites had less than 10% missing data. All 1096 patients had less than 10% missing data for these metabolites. Statistical analyses were therefore applied to 481 analytes and 1096 patients. The data was normalized in advance of receipt. A logarithm (base 2) transformation was applied and histograms were created to show the distribution of expression by analyte (data not shown).

The metabolomics data were generated in multiple batches; however, a principal components analysis (PCA) showed no evidence of any systematic site effects.

III. Prediction Modeling for Primary Endpoints

Methods. Patients in the Discovery-FAS Set were categorized according to whether they had fasted for at least eight hours. By this criteria, a total of 377 participants were Fasted and 371 were Non-Fasted. Association testing, with adjustment for age and gender was conducted for the four primary endpoints, and nominal associations were defined in three ways as follows:

    • 1 Significant in Fasting and Non-Fasting combined
    • 2 Significant in Fasting and Non-Fasting independently
    • 3 Significant in Fasting alone

It is emphasized that, at this stage, ‘significant’ pertains to any association with raw, unadjusted p<0.05.

In this way, twelve scenarios were considered as follows:

    • a) Atherosclerosis in Native CAD—AnCAD
      • c. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • c. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • c. Significant in Fasting—[Figure (not displayed)]
    • b) Atherosclerosis in All CAD (including revascularization)—AaCAD
      • c. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • c. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • c. Significant in Fasting—[Figure (not displayed)]
    • c) 50% stenosis in Native CAD—SnCAD
      • c. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • c. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • c. Significant in Fasting—[Figure (not displayed)]
    • d) 50% stenosis in ALL CAD (including revascularization)—SaCAD
      • c. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • c. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • c. Analytes Significant in Fasting—[Figure (not displayed)].

When more than 9 variables had p<0.05, Age and Gender were added to the variables, and gradient boosting (see below) was applied to select 9 predictors.

Twelve prediction models were obtained by generalized linear (logistic) regression as follows. When fewer than nine variables had p<0.05, Age and Gender were added to the variables, and the full model was fitted. Otherwise, the nine variables selected by gradient boosting variables were combined with Age and Gender in a generalized linear (logistic) model.

Gradient boosting is an approach to determine a regression function that minimizes the expectation of a loss function. (Freidman J H (2001) and Friedman J H (2002)) It is an iterative method, in which the negative gradient of the loss function is calculated, a regression model is fitted, the gradient descent step size is selected, and the regression function is updated. The gradient is approximated by means of a regression tree, which makes use of covariate information, and at each iteration the gradient determines the direction in which the function needs to move, in order to improve the fit to the data.

The loss function was assumed Bernoulli, due to the binary nature of the primary endpoints. A learning rate (λ) was introduced to dampen proposed moves and to protect against over-fitting. The optimal number of iterations, given by T, was determined by 5-fold cross-validation. The minimum number of observations in each terminal node was 10. Two-way interactions were allowed. Random sub-sampling, without replacement, of half of the observations was applied to achieve variance reduction in gradient estimation.

For current purposes, 50 rounds of gradient boosting were run for each scenario, and the nine variables most often showing highest estimated relative influence were taken forwards to generalized linear modeling.

The twelve models were used to generate probability predictions for each patient in the Validation-FAS. For each model, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for the range of predicted probability thresholds. A Receiver Operating Characteristic (ROC) curve was generated to plot sensitivity as a function of (1-specificity). The optimal classification threshold was determined on the basis of accuracy, defined as the proportion of correct predictions. In addition, the Area Under the Curve (AUC) and accuracy was estimated (Tables 27, 28, 29, 30 for the four primary endpoints, respectively).

The performance of model-based predictions were compared to the performance of probability predictions obtained by Diamond-Forrester scoring. (Diamond and Forrester (1979)).

Detailed Results for Native CAD

The results show that the Diamond-Forrester score provides poor prediction of the GLOBAL phenotypes (FIGS. 34, 38, 42, 46). The estimates of AUC and accuracy for prediction of Native CAD indicate that performance is no better than assigning all patients as ‘at risk’ of disease, by which 62% of predictions in the Validation Set for Native CAD (Validation-Native CAD plus Validation-Control) are correct, and 64% of predictions in the Validation Set for All CAD (Validation Native CAD plus Validation-Revasc. CAD plus Validation-Control), are correct.

Metabolomics Model

I. Atherosclerosis in Native CAD—A nnCAD

    • a. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 83 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 29 provides a list of the 83 metabolomic variables for [Figure (not displayed)].

TABLE 29
glutamateserylleucine1-linoleoyl-GPC (18:2)
acisoga3-methoxytyrosine1-methylguanosine
threonateprolylhydroxyproline12 13-DiHOME
uratevalerylcarnitine (C5)O-sulfo-L-tyrosine
mannosecaproate (6:0)erucamide
oleic ethanolamidetigloylglycineinositol 1-phosphate
(l1P)
cysteine-glutathione disulfideguanidinosuccinateisoleucylvaline
pyroglutamylglutamineisobutyrylglycine (C4)gamma-tocopherol
valylleucineglycocholenate sulfate*1-
eicosenoylglycerophosp
hocholine (20:1n9)*
butyrylcarnitine (C4)o-cresol sulfatetyrosylglutamine
cytidineN-acetylthreonineindolepropionate
palmitoyl ethanolamideleucylglycinegamma-glutamylvaline
phenylalanylvaline2-hydroxybutyrate (AHB)2-aminoadipate
hydroxybutyrylcarnitine*leucylaspartateaspartate
1-1-arachidoyl-GPC (20:0)N6-
nonadecanoylglycerophosphocholinecarbamoylthreonyladenosine
(19:0)
glycineN6-methyladenosinemethyl glucopyranoside
(alpha + beta)
propionylglycine (C3)hexanoylcarnitine (C6)myo-inositol
pseudouridinevalylisoleucinealpha-ketobutyrate
ADSGEGDFXAEGGGVR*beta-alanineS-adenosylhomocysteine
(SAH)
2-hydroxyhippurate (salicylurate)1-linoleoyl-GPE (18:2)*1-oleoylglycerol (18:1)
alpha-glutamyltyrosinegamma-glutamylglutamatetartronate
(hydroxymalonate)
fucose3-hydroxy-2-ethylpropionate3-
methylglutarylcarnitine-2
glucuronateadenine1-methylurate
3-methylglutarylcarnitine-1xylitolN-acetyl-beta-alanine
xanthineN2 N2-dimethylguanosinehistidyltryptophan
12-HETEmethyl indole-3-acetate1-oleoyl-GPC (18:1)*
glucosehomostachydrine*3-hydroxydecanoate
salicylatephenylacetylglutamine
Of the 83 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 30 provides the relative influence of the eight metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 35 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 53 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 30
VariableRelative InfluenceDirection of Change
valylleucine28.88Decreased
glutamate14.47Elevated
acisoga14.25Elevated
urate10.39Elevated
glucuronate9.26Elevated
age6.68Elevated
fucose6.18Elevated
Butyrylcarnitine (C4)4.72Elevated
mannose4.46Elevated
Male gender0.70Present§
§The term “present” conveys that male gender was taken into account in the prediction model, with ‘relative influence’ denoting the association of male gender with the outcome (i.e., ASCAD or the presents of a coronary atherosclerotic plaque).
    • b. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 4 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 31 provides a list of the 4 metabolomic variables for [Figure (not displayed)].

TABLE 31
acisogao.cresol.sulfateCysteine.glutathione.disulfide
threonate

Of the 4 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)]; a panel of all four metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 32 provides the relative influence of the four metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 36 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 53 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 32
VariableRelative InfluenceDirection of Change
acisoga40.74Elevated
age20.77Elevated
cysteine.glutathione.disulfide18.87Decreased
threonate12.67Decreased
o-cresol.sulfate4.49Elevated
Male gender2.45Present
    • c. Significant in Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 34 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 33 provides a list of the 34 metabolomic variables for [Figure (not displayed)].

TABLE 33
xylitolvalylleucinecysteine-glutathione
disulfide
3-carboxy-4-methyl-N-acetylleucinethreonate
5-propyl-2-
furanpropanoate
(CMPF)
serylleucinealpha-glutamyltyrosinefucose
phenylalanylvaline4-androsten-3alphaadenosine
17alpha-diol
monosulfate 2
12-HETEinositol 1-phosphate (I1P)valylisoleucine
glycocholenate1-docosahexaenoyl-GPC*phenylalanylserine
sulfate*(22:6)*
oleic ethanolamide2-hydroxyhippurategamma-tocopherol
(salicylurate)
acisogasalicylatepalmitoyl
ethanolamide
leucylglycinephenylalanylglycinehydroquinone sulfate
N-glycylphenylalaninepropionylglycine (C3)
acetylphenylalanine
o-cresol sulfate3-methoxytyrosine
histidyltryptophanadenine

Of the 34 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 34 provides the relative influence of the eight metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 37 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 53 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 34
Direction
VariableRelative Influenceof Change
N-acetylphenylalanine22.27Elevated
age18.18Elevated
valylleucine17.61Decreased
xylitol8.07Elevated
2-hydroxyhippurate6.97Elevated
(salicylurate)
N-acetylleucine6.15Elevated
serylleucine6.15Decreased
fucose6.06Elevated
glycylphenylalanine4.97Decreased
Male gender3.56Present

II. Atherosclerosis in All CAD (inc revasc)—AaCAD

    • a. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 92 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 41 provides a filtered list of the 92 metabolomic variables for [Figure (not displayed)].

TABLE 41
acisogatyrosylglutamineN6-
carbamoylthreonyladenosine
Glutamatexanthine2-linoleoyl-GPC* (18:2)*
Threonatebeta-alanine3-methyl-2-oxobutyrate
Mannoseisobutyrylglycine (C4)methyl glucopyranoside
(alpha + beta)
Urate3-methylglutarylcarnitine-1serylleucine
cysteine-glutathione disulfidevalerylcarnitine (C5)caproate (6:0)
oleic ethanolamide1-linoleoyl-GPC (18:2)N-methyl proline
pyroglutamylglutaminehexanoylcarnitine (C6)laurylcarnitine (C12)*
butyrylcarnitine (C4)2-hydroxybutyrate (AHB)o-cresol sulfate
Cytidine1-arachidoyl-GPC (20:0)gamma-
glutamylglutamate
hydroxybutyrylcarnitine*guanidinosuccinateN-acetyl-beta-alanine
alpha-glutamyltyrosinefucose1-
eicosenoylglycerophosphocholine
(20:1n9)*
2-hydroxyhippurate (salicylurate)phenylacetylglutamineN-acetylglycine
Valylleucine3-methylglutarylcarnitine-2seryltyrosine
propionylglycine (C3)glycohyocholate4-guanidinobutanoate
1-N6-methyladenosineS-methylcysteine
nonadecanoylglycerophosphocholine
(19:0)
GlycineN2 N2-dimethylguanosineisoleucylvaline
12-HETEgamma-glutamylvalineadenine
pseudouridineleucylaspartate1-methylurate
Salicylate2-hydroxyoctanoatexylitol
Glucosealpha-ketobutyratephenylalanylalanine
ADSGEGDFXAEGGGVR*glycocholenate sulfate*O-sulfo-L-tyrosine
1-linoleoyl-GPE (18:2)*valylisoleucineerucamide
Phenylalanylvalinehomostachydrine*pregnanediol-3-
glucuronide
Tigloylglycinemethyl indole-3-acetate3-hydroxy-2-
ethylpropionate
Glucuronateleucylglycinepyridoxal
palmitoyl ethanolamideN-acetylthreonine1-oleoyl-GPC (18:1)*
1-oleoylglycerol (18:1)2-hydroxydecanoate2prime-deoxyuridine
12 13-DiHOME1-methylguanosinethreonylphenylalanine
3-methoxytyrosineprolylhydroxyproline2-aminoadipate
2-linoleoyl-GPE* (18:2)*prolylglycine

Of the 92 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 36 provides the relative influence of the eight metabolomic variables combined with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 39 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 54 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 36
VariableRelative InfluenceDirection of Change
valylleucine26.79Decreased
acisoga16.87Elevated
glutamate13.93Elevated
urate9.74Elevated
glucuronate8.74Elevated
mannose7.13Elevated
age6.24Elevated
12-HETE5.03Decreased
Valerylcarnitine (C5)4.81Elevated
Male gender0.72Present
    • b. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 6 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 37 provides a list of the 6 metabolomic variables for [Figure (not displayed)].

TABLE 37
threonatethreonatecysteine-glutathione
disulfide
o-cresol1-glucose
sulfatenonadecanoylglycerophosphocholine
(19:0)

Of the 6 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of all six metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 38 provides the relative influence of the six metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 40 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 54 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 38
Direction
VariableRelative Influenceof Change
acisoga39.32Elevated
age17.31Elevated
1.nonadecanoylglycerophosphocholine12.00Decreased
(19:0)
cysteine-glutathione disulfide10.91Decreased
threonate10.71Decreased
glucose6.64Elevated
Male gender2.06Present
o-cresol sulfate1.05Elevated
    • c. Significant in Fasting —[Figure (not displayed)]
      • i. Of the 481 analytes measured, 48 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 39 provides a list of the 48 metabolomic variables for [Figure (not displayed)].

TABLE 39
12-HETEN-acetylphenylalanine1-arachidonylglycerol
alpha-glutamyltyrosineN-acetylleucinePyroglutamylvaline
salicylate4-androsten-3alpha 17alpha-phenylalanyltryptophan
diol monosulfate 2
2-hydroxyhippurate (salicylurate)o-cresol sulfatemethyl indole-3-acetate
acisogaphenylalanylvalineHistidyltryptophan
3-carboxy-4-methyl-5-propyl-2-leucylglycine4-ethylphenyl sulfate
furanpropanoate (CMPF)
threonatephenylalanylglycine1-myristoylglycerol
(14:0)
glycocholenate sulfate*propionylglycine (C3)inositol 1-phosphate
(I1P)
xylitolmannitol1-
nonadecanoylglycerophosphocholine
(19:0)
1-docosahexaenoyl-GPC* (22:6)*serylleucineGlucose
phenylalanylserinehydroquinone sulfateN-stearoyltaurine
3-methoxytyrosineadenosineValylisoleucine
oleic ethanolamide2-hydroxydecanoatebeta-alanine
cysteine-glutathione disulfidetyrosylglutamineN-acetylglycine
glycylphenylalanineN-octanoylglycineAllantoin
valylleucineadeninePhenylalanylphenylalanine

Of the 48 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of seven metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 40 provides the relative influence of the seven metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 41 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 54 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 40
Direction
VariableRelative Influenceof Change
age21.21Elevated
valylleucine20.76Decreased
N-acetylphenylalanine18.59Elevated
2-hydroxyhippurate12.20Elevated
(salicylurate)
N-acetylleucine6.10Elevated
12-HETE5.96Decreased
xylitol5.40Elevated
glycylphenylalanine5.39Decreased
Male gender4.40Present

III. 50% stenosis in Native CAD—SnCAD

    • a. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 49 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 41 provides a list of the 49 metabolomic variables for [Figure (not displayed)].

TABLE 41
threonateserotonin (5HT)5alpha-androstan-3alpha
17beta-diol disulfate
N-acetylglycinexanthine1-stearoyl-GPC (18:0)
glycerate2-oleoyl-GPE* (18:1)*serine
isobutyrylglycine (C4)4-guanidinobutanoateacisoga
valerylcarnitine (C5)leucylleucinemannose
fumaratecholatevalylleucine
1-propionylglycine (C3)gamma-tocopherol
nonadecanoylglycerophosphocholine
(19:0)
tartronate (hydroxymalonate)glycocholate3-ethylphenylsulfate
2-hydroxyhippurateN-octanoylglycineglutamate
(salicylurate)
1-arachidoyl-GPC (20:0)glycoursodeoxycholatesphingosine 1-phosphate
threitolisovalerylglycinecarnitine
N-(2-furoyl)glycinepregnanediol-3-glucuronidearabonate
tigloylglycine5alpha-androstan-3betacyclo(leu-pro)
17beta-diol monosulfate 2
salicylatearabinoseindoleacetylglutamine
N-acetylthreonine1-linoleoyl-GPE (18:2)*prolylglycine
xylonate5-HETE
xylosehydroquinone sulfate

Of the 49 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 42 provides the relative influence of the eight metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 43 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 55 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 42
VariableRelative InfluenceDirection of Change
Age37.04Elevated
valerylcarnitine (C5)14.32Elevated
N-acetylthreonine10.39Elevated
tigloylglycine8.72Decreased
2-hydroxyhippurate7.06Elevated
(salicylurate)
glycerate6.42Decreased
salicylate5.67Decreased
threonate5.58Decreased
tartronate (hydroxymalonated);4.25Elevated
Male gender0.55Present
    • b. Independently Significant in Fasting and Non-Fasting —[Figure (not displayed)]
      • i. Of the 481 analytes measured, 2 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 43 provides a list of the 2 metabolomic variables for [Figure (not displayed)].

TABLE 43
N-acetylglycine3-ethylphenylsulfate

Of the 2 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of both variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 44 provides the relative influence of the two metabolomic variables in combination with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 44 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 55 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 44
VariableRelative InfluenceDirection of Change
age67.33Elevated
N-acetylglycine14.67Decreased
3-ethylphenylsulfate12.88Elevated
Male gender5.12Elevated
    • c. Significant in Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 28 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 45 provides a filtered list of the 28 metabolomic variables for [Figure (not displayed)].

TABLE 45
leucylleucinevalylisoleucine7-methylguanine
asparagineglycocholenate sulfate*cyclo(leu-pro)
glyceratearabitolMethionine
threitolN-acetylglycinepropionylglycine (C3)
cholateserotonin (5HT)Serine
N-octanoylglycinexylose2-oleoyl-GPE* (18:1)*
xylonateN-acetylputrescineTigloylglycine
isobutyrylglycine (C4)arabonate3-ethylphenylsulfate
isovalerylglycinelysine
fumarateN-(2-furoyl)glycine

Of the 28 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; they were combined with age and gender in a prediction model for CAD. Table 46 provides the relative influence of the eight metabolomic variables, in combination with age and gender, for the Metabolomics Model of [Figure (not displayed)]. FIG. 45 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 55 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 46
VariableRelative InfluenceDirection of Change
age24.44Elevated
leucylleucine21.83Decreased
serotonin (5HT)11.37Elevated
N-acetylputrescine9.68Decreased
glycocholenate sulfate8.56Decreased
propionylglycine (C3)6.95Decreased
cholate6.14Decreased
asparagine5.73Elevated
3-ethylphenylsulfate4.79Elevated
Male gender0.50Present

IV. 50% stenosis in ALL CAD (inc revasc)—SaCAD

    • a. Significant in Fasting & Non-Fasting Combined—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 72 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 47 provides a list of the 72 metabolomic variables for [Figure (not displayed)].

TABLE 47
threonateprolylglycine2-hydroxydecanoate
1-linoleoyl-GPE (18:2)*N-octanoylglycineglutamate
N-acetylglycinethreitolN-acetylthreonine
glycoursodeoxycholatefumaratetaurine
2-hydroxyhippurate (salicylurate)pregnanediol-3-glucuronide1-
oleoylplasmenylethanol
amine*
salicylate1-oleoyl-GPI (18:1)*1-palmitoyl-GPE (16:0)
2-linoleoyl-GPE* (18:2)*serotonin (5HT)N-acetylglutamate
mannosexylonate13-HODE + 9-HODE
tigloylglycinecyclo(leu-pro)1-palmitoyl-GPI* (16:0)*
2-glyceratehydroquinone sulfate
linolenoylglycerophosphocholine (18:3n3)*
1-tartronate (hydroxymalonate)caprylate (8:0)
nonadecanoylglycerophosphocholine
(19:0)
2-oleoyl-GPE* (18:1)*xylose1-stearoyl-GPC (18:0)
isovalerylglycineglycohyocholateglycochenodeoxycholate
isobutyrylglycine (C4)glucosep-cresol sulfate
N-(2-furoyl)glycinexanthine12-HETE
glycocholatecyclo(L-phe-L-pro)5-hydroxyindoleacetate
acisogabeta-alaninearabonate
4-guanidinobutanoatepyridoxate2-hydroxyoctanoate
1-arachidoyl-GPC (20:0)tartarateurate
propionylglycine (C3)1-linoleoyl-GPC (18:2)valylleucine
valerylcarnitine (C5)pyridoxalcarnitine
1-oleoylglycerol (18:1)cholate1-linoleoyl-GPI* (18:2)*
1-oleoyl-GPE (18:1)serineN-acetylputrescine
arabinosehomostachydrine*succinate

Of the 72 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 48 provides the relative influence of the eight metabolomic variables in combination with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 47 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 56 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 48
Direction
VariableRelative Influenceof Change
Age18.38Elevated
glycoursodeoxycholate16.52Decreased
acisoga12.81Elevated
2-hydroxyhippurate10.33Elevated
(salicylurate)
1-linoleoyl.GPE (18:2)10.26Decreased
valerylcarnitine (C5),8.91Elevated
threonate7.13Decreased
mannose7.12Elevated
salicylate7.02Elevated
Male gender1.52Present
    • b. Independently Significant in Fasting and Non-Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 5 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 49 provides a filtered list of the 5 metabolomic variables for [Figure (not displayed)].

TABLE 49
N-acetylglycinethreonateSalicylate
2-hydroxyhippurate (salicylurate)3-ethylphenylsulfate

Of the 5 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of all five metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 50 provides the relative influence of the five metabolomic variables in combination with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 48 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 56 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 50
VariableRelative InfluenceDirection of Change
Age40.82Elevated
2-hydroxyhippurate19.56Elevated
(salicylurate)
threonate14.84Decreased
salicylate12.23Elevated
Male gender7.00Present
N-acetylglycine3.13Decreased
3-ethylphenylsulfate2.42Elevated
    • c. Analytes Significant in Fasting—[Figure (not displayed)]
      • i. Of the 481 analytes measured, 40 metabolomic variables exhibited a nominal univariate association (raw p<0.05) for [Figure (not displayed)]. Table 51 provides a filtered list of the 40 metabolomic variables for [Figure (not displayed)].

TABLE 51
N-octanoylglycinesalicylateDimethylglycine
1-oleoylglycerol (18:1)7-methylguaninexylonite
isovalerylglycinelysinePhenylalanylphenylalanine
N-acetylglycineglycoursodeoxycholateValylisoleucine
2-3-indoxyl sulfateGlycerate
linolenoylglycerophosphocholine(18:3n3)*
asparagine6-oxopiperidine-2-carboxylic1-arachidonylglycerol
acid
isobutyrylglycine (C4)1-Fumarate
arachidonoylglyercophosphate
cyclo (leu-pro)2-hydroxyhippurate3-ethylphenylsulfate
(salicylurate)
cholatethreitol7-HOCA
serotonin (5HT)methionineTaurine
threonateacisogaCholesterol
N-acetylputrescinetigloylglycineArabitol
propionylglycine (C3)1-linoleoylglycerol (18:2)
2-oleoyl-GPE* (18:1)*1-oleoyl-GPI (18:1)*

Of the 40 metabolomic variables exhibiting a nominal univariate association for [Figure (not displayed)], a panel of eight metabolomic variables were selected as best predictors; these were combined with age and gender in a prediction model for CAD. Table 52 provides the relative influence of the eight metabolomic variables in combination with age and gender for the Metabolomics Model of [Figure (not displayed)]. FIG. 49 provides a ROC curve for the Metabolomics Model of [Figure (not displayed)]. Table 56 provides the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the range of predicted probability thresholds; Area Under the Curve (AUC) and accuracy was estimated.

TABLE 52
RelativeDirection
VariableInfluenceof Change
age15.37Elevated
cholesterol15.19Decreased
1-oleoylglycerol (18:1)15.12Elevated
acisoga14.01Elevated
2.hydroxyhippurate (salicylurate)9.47Elevated
asparagine8.18Elevated
taurine7.93Decreased
6-oxopiperidine-2-carboxylic acid7.50Elevated
propionylglycine (C3)6.66Decreased
Male gender0.56Present

For each model below, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for the range of predicted probability thresholds (Tables 53, 54, 55, 56). A Receiver Operating Characteristic (ROC) curve was generated to plot sensitivity as a function of (1-specificity). The optimal classification threshold was determined on the basis of accuracy, defined as the proportion of correct predictions. In addition, the Area Under the Curve (AUC) and accuracy was estimated (Tables 53, 54, 55, 56 for Native CAD, All CAD, 50% stenosis in Native CAD, and 50% stenosis in All CAD, respectively). The first row for each model indicates the performance of the maximum accuracy threshold, the optimal balance between sensitivity and specificity. Those models with a second row were optimized for a high negative predictive value (NPV).

TABLE 53
PositiveNegative
Sensi-Speci-PredictivePredictive
ModelAUCtivityficityValueValueAccuracy
DF0.451.000.000.62N/A0.62
AFNFnCAD0.820.850.610.780.710.76
0.990.090.640.920.65
AIFNFnCAD0.800.850.640.800.720.77
1.000.100.650.930.66
AFnCAD0.810.870.580.770.740.76
0.990.260.690.940.72
DF = Diamond-Forrester

TABLE 54
PositiveNegative
Sensi-Speci-PredictivePredictive
ModelAUCtivityficityValueValueAccuracy
DF0.451.000.000.64N/A0.64
AFNFaCAD0.830.930.500.770.810.78
1.000.160.680.950.69
AIFNFaCAD0.810.850.660.810.710.78
1.000.070.650.900.66
AFaCAD0.820.830.640.800.680.76
1.000.160.680.950.69
DF = Diamond-Forrester

TABLE 55
PositiveNegative
Sensi-Speci-PredictivePredictive
ModelAUCtivityficityValueValueAccuracy
DF0.450.031.001.000.780.78
SFNFnCAD0.730.210.960.640.800.79
0.950.300.290.950.45
SIFNFnCAD0.760.300.960.720.820.81
0.930.370.310.950.50
SFnCAD0.670.041.001.000.780.78
0.960.200.260.950.38
DF = Diamond-Forrester

TABLE 56
PositiveNegative
Sensi-Speci-PredictivePredictive
ModelAUCtivityficityValueValueAccuracy
DF0.450.031.001.000.740.75
SFNFaCAD0.780.340.940.660.800.78
0.960.300.330.950.47
SIFNFaCAD0.780.230.970.720.780.77
0.960.300.330.950.47
SFaCAD0.740.220.960.690.780.77
0.970.220.310.950.42
DF = Diamond-Forrester

Full text: Click here
Patent 2019

Example 1

Growth of bacteria: A 1 ml aliquot of a 24 hour culture of E. coli ATCC 8739 was used to inoculate 100 ml of Luria-Bertani (LB) broth in a 250 ml baffled flask. This culture was then incubated at 37° C. with agitation (220 rpm) and sampled at 30 minute intervals. Samples were assessed for turbidity (OD600) in a SpectraMax platereader M3 (Molecular Devices, Sunnydale, Calif.), which is one method of monitoring the growth and physiological state of microorganisms. The sample turbidity was then recorded and the samples were centrifuged at 5000 RPM for 10 min at room temperature. The supernatant, thereinafter referred to as “supernatant of bacterial culture”, was subsequently analyzed for LPS content using the procedure as described below.

Twenty ml aliquots of MTGE broth (Anaerobe Systems, Morgan Hill, Calif.) were inoculated with P. gingivalis ATCC 33277, P. pallens ATCC 700821, or P. nigrescens ATCC 25261. These cultures were incubated overnight in a Whitely A45 Anaerobic Workstation (Don Whitley Scientific, Frederick, Md.) at 37° C. with an 85:10:5 N2:CO2:H2 gas ratio. One ml aliquots of these starter cultures were then used to inoculate 99 ml of membrane-Tryptone Glucose Extract (m-TGE) broth in a 250 ml baffled flask. These cultures were then incubated under agitation (200 rpm) as previously described and sampled at regular intervals. Samples were assessed for turbidity (OD600) in a Tecan Infinite m200 Pro (Tecan Trading AG, Switzerland) and then centrifuged at 16,100×g for 10 min at room temperature. Supernatants were decanted and passed through a 0.22 μM filter prior to analysis for LPS content.

In the experiment, only OD600 was measured. For the sake of consistency in following experiments, we converted OD600 readings into bacterial numbers, even though the relationship between OD600 readings and bacterial numbers is varied for each bacterium. The number of bacteria was estimated based on spectrophotometer readings at OD600 (OD600 of 1.0=8×108 cells/ml).

The Limulus Amebocyte Lysate Assay (LAL) is an assay to determine the total amount of lipopolysaccharide (LPS) in the sample tested (Pierce LAL Chromogenic Endotoxin Quantitation Kit, ThermoFischer Scientific, Waltham, Mass.). The assay was performed following manufacturer's instruction. Ninety-six-well microplates were first equilibrated in a heating block for 10 min at 37° C. Fifty μl each of standard or sample was dispensed into the microplate wells and incubated with plate covered for 5 min at 37° C. Then 50 μl LAL was added to each well. Plates were shaken gently and incubated for 10 min at 37° C. 100 μl of chromogenic substrate was added and incubated for 6 min at 37° C. Finally, 50 μl Stop Reagent was added and the absorbance was measured at 405-410 nm on Spectramax M3 platereader (Molecular Device, Sunnyvale, Calif.).

FIGS. 1A, 1C, and 1D show the ability of microbes to shed LPS as part of their normal growth cycle. This data shows the need to deliver chemistry to the subgingival plaque to effectively mitigate the LPS, since tooth brushing generally does not remove the subgingival plaque.

The LPS, as measured by the LAL kit reported in endotoxin unit per ml (EU/ml), was shed by the bacteria (E. coli K12) as depicted in FIG. 1A. The growth media began to be depleted of complex sugars around 120 minutes, as reflected in the bacterial growth curve in FIG. 1B, where the LPS shedding started to decline. This data gave a reason to believe that a mature biofilm/plaque could supply a constant level of LPS to the host cells, if food sources were present. The LPS would then have the ability to induce an inflammatory response from the host cells.

Importantly, LPS are secreted into the supernatant of bacterial culture (FIG. 1D). LPS also exists in bacterial walls (FIG. 1E). Again, this data further enforce the need to deliver chemistry to the subgingival plaque to effectively mitigate the LPS, since tooth brushing generally does not remove the subgingival plaque.

Example 2

Seven panelists, with at least three bleeding sites, took part in the testing. A licensed dental hygienist collected subgingival plaque samples. Samples were taken at the tooth/gum interface (buccal surfaces only) using care to avoid contact with the oral soft tissues. Six subgingival plaque sites were sampled from each panelist (3 healthy and 3 unhealthy sites). Unhealthy teeth had bleeding sites with pockets greater than 3 mm and healthy sites had no bleeding with pocket depth less than 2 mm Prior to sampling, panelists were instructed to abstain for 12 hours from oral hygiene and refrain from eating, chewing gum, drinking (except small sips of water). Next, panelists had their marginal plaque collected with a curette at the sampling sites. Then, from the same site, subgingival plaque samples were collected with 3 consecutive paper points as shown in FIG. 1F. The sampling sites were isolated with cotton rolls and gently air-dried. Paper points (PROFLOW incorporated, Amityville, N.Y.) were gently placed for 10 seconds into the pocket until a minimum of resistance was felt. After 10 seconds, paper points were removed and placed into pre-labeled 1.5 ml tubes. The same sampling procedure was repeated with 2 more paper points (paper points go into separate tubes). The first, second and third sample paper points from a healthy site of all panelists were pooled separately into three tubes, labeled as paper point 1, 2 and 3, respectively. Similarly the unhealthy site samples were also pooled.

TABLE 1 showed that unhealthy dental plaques contained more endotoxins than the healthy dental plaques. One m1 PBS was added to each pooled sample in the 1.5 ml tube. Bacteria were lysed in a MolBio Fast Prep bead beater (MP Biomedicals, Santa Ana, Calif.). Samples were centrifuged for 10 min at 10,000 RPM at 4° C., supernatants were collected and analyzed with LAL assay kits following manufacturer's instruction as described in EXAMPLE 1.

TABLE 1
Protein concentrations and endotoxin
levels in the pooled dental plaque samples.
Endotoxin
Dental plaque(endotoxin unit)
Healthy paperpoint 1 sub plaque1284
Healthy paperpoint 2 sub plaque476
Healthy paperpoint 3 sub plaque361
Healthy Marginal Plaque23180
Unhealthy paperpoint 1 sub plaque3371
Unhealthy paperpoint 2 sub plaque1732
Unhealthy paperpoint 3 sub plaque16111
Unhealthy Marginal Plaque80277

It was expected that the marginal plaques in unhealthy sites had more endotoxins than those in the healthy sites (TABLE1) within the same subjects. Three samples were taken from subgingival pockets with three paper points sequentially, named paper point 1, 2 and 3. Again, the subgingival plaques taken by the paper point 1 had more endotoxins in the unhealthy sites than in the healthy sites (TABLE 1). The same is true for the samples taken by paper point 2 and 3. Importantly, dental plaques in the unhealthy subgingival pockets possessed more endotoxins than plaques from healthy pockets. This may explain why unhealthy gingiva are prone to bleeding upon probing.

Example 3

The LAL assay, as described in EXAMPLE 1, was modified for development of technology which inhibits LPS from activating a proenzyme in the LAL assay. The Thermo Scientific Pierce LAL Chromogenic Endotoxin Quantitation Kit is a quantitative endpoint assay for the detection of LPS, which catalyzes the activation of a proenzyme in the modified Limulus Amebocyte Lysate (LAL). The activated proenzyme then splits p-Nitroaniline (pNA) from the colorless substrate, Ac-Ile-Glu-Ala-Arg-pNA. The product pNA is photometrically measured at 405-410 nm. If SnF2 binds to LPS, the latter can't react with the proenzyme in the LAL kit. Consequently, the proenzyme is not activated, and the colorless substrate Ac-Ile-Glu-Ala-Arg-pNA will not split and no color product is produced. P. gingivalis LPS 1690 (1 ng/ml), or E. coli LPS (1 ng/ml), and stannous fluoride and other materials (50 and 500 μM), as listed in TABLE 2, were dissolved in endotoxin-free water. Then 50 μl LAL was added to each well. Plates were shaken gently and incubated for 10 min at 37° C. 100 μl of chromogenic substrate was added and incubated for 6 min at 37° C. Finally, 50 μl Stop Reagent was added and the absorbance was measured at 405-410 nm on Spectramax M3 plate reader (Molecular Device, Sunnyvale, Calif.).

As shown in TABLE 2, SnF2 and some other compounds inhibited LPS activities in LAL assays

TABLE 2
Inhibition of LPS activities on LAL Assays
Inhibition of LAL activity %
P. gingivalis LPSE. coli LPS
1690 1 ng/ml1 ng/ml
Samples500 uM50 uM500 uM50 uM
Tin (II) fluoride60499287
stannous chloride48218965
Cetylpyridinium chloride1037710346
monohydrate
Chlorhexidine102389757
zinc citrate, dihydrate1045710482
zinc lactate580660
potassium oxalate8016
Triclosan (irgasan)00100
1-Hydroxypyridine-2-thone0026
zinc salt
sodium fluoride0045
Carboxymethyl cellulose0020
sodium

Example 5

Reporter gene cell lines, human HEK 293T cells, were purchased from Invivogen of San Diego, Calif. The HEK 293T cells were stably transfected with at least two exogenous genes, a TLR4 structural gene, and a SEAP reporter gene, which is under the control of NFkB transcriptional factors. The cell line is named here as TLR4-SEAP. The reporter gene encodes a secreted enzyme, called embryonic alkaline phosphatase or SEAP. The SEAP reporter is placed under the control of the interferon-β minimal promoter fused to five NFkB and AP-1-binding sites. Furthermore, the TLR4-SEAP cell line also contains a CD14 co-receptor gene, which is needed to transfer LPS to TLR4 receptors. The recombinant TLR binds its ligand, or distinct pathogen-associated molecule, initiates a chain of responses, leading to recruitment of NFkB and AP1 transcription factors to the reporter gene promoter, which induce expression of SEAP.

Cell culture and treatment: 500,000 gene reporter cells were grown and maintained in 15 ml growth medium, comprised of DMEM medium supplemented with 10% fetal calf serum in T75 flasks for three days at 37° C., 5% CO2, and 95% humidity. For treatment, wells of a 96-well plate were seeded with 10,000 cells/well in 100 μL of growth medium. The cells were incubated for 72 hours at 37° C., 5% CO2, and 95% humidity until day 4. On day 4, medium was changed to assay medium (90 μl), which is the DMEM medium without fetal calf serum. LPS, bacteria and the culture medium of bacterial growth, as described in EXAMPLE 1, were first resolved or mixed with the assay medium. 10 μl of the bacteria, LPS and culture medium of bacterial growth were added to the TLR4-SEAP cells. Samples were taken 24 hours later, following addition of LPS, bacteria, and culture medium. Expression of the reporter gene (SEAP) was quantified with a commercially available kit (SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich.).

EC50 was calculated using GraphPad Prism software (GraphPad Software, La Jolla, Calif.). Samples with lower EC50 are more potent in activating the TLR4 reporter gene than those with higher EC50. As shown in FIG. 2A, LPS from E. coli has lower EC50 than P. gingivalis, thus, was far more potent than P. gingivalis (Pg). Salmonella Minnesota LPS is not as potent as that of E. coli, but is far more potent than those of P. gingivalis LPS 1690 and 1435. Each species of bacteria produces multiple forms of LPS. Each form of LPS from the same species of bacteria has different potency in stimulating TLR4-downstream signaling pathways. For example, Pg 1690 LPS is more potent than Pg1435/50. LPS is a component in bacterial cell walls. Likely, E. coli cell wall is more virulent in inducing production of proinflammatory cytokines in host cells than P. gingivalis when they are in direct contact with host blood cells. P. gingivalis had far higher EC50 than P. pallens and P. nigrescens as shown in FIG. 2B in stimulating TLR4 reporter gene expression, suggesting that P. pallens and P. nigrescens are more likely to promote production of proinflammatory cytokines in host cells than P. gingivalis.

Bacteria release LPS into the supernatant of bacterial culture. As shown in FIG. 2C, the supernatant of P. pallens has an EC50 that is similar to that of P. nigrescens, but far lower than that of P. gingivalis, in stimulating expression of TLR4 reporter gene. Again, those results imply that the products of P. pallens and P. nigrescens are more likely to promote production of proinflammatory cytokines in host cells than those of P. gingivalis.

Example 6

Stannous fluoride is a leading anti-gingivitis technology in P&G toothpaste products. Tests were conducted to understand whether stannous fluoride could reduce LPS's ability to trigger proinflammatory responses in host cells. TLR4-SEAP reporter cells were prepared using the same conditions as described in EXAMPLE 5 in the presence or absence of LPS. Production of SEAP was quantified also as described in EXAMPLE 5.

FIG. 3 shows the effect of stannous at various concentrations from 62.5 uM to 1,000 uM on 100 ng/ml E. coli LPS, as reported by activation of TLR-4. At stannous concentrations of 500 uM or higher, the level of E. coli induction of TLR-4 was decreased.

FIG. 4 shows the effects of stannous at various concentrations from 62.5 uM to 1,000 uM on P. gingivalis LPS, as reported by activation of TLR-2. At stannous concentrations of 1000 uM, the level of P. gingivalis induction of TLR-2 was decreased.

The data in FIG. 5 shows reduction of LPS activity by the stannous ion, from a stannous fluoride salt. The data showed that stannous fluoride, at 1.6 mM and 3.2 mM, reduce about 50% of P. gingivalis LPS (500 ng/ml) activation on the TLR4 reporter system (One asterisk means P<0.05, two asterisks mean P<0.01).

Example 7

The method described in EXAMPLE 5 is effective at determining the potency of LPS from different bacteria. The same method was used to determine the EC50 of clinical samples, as described in EXAMPLE 2. As shown in FIG. 6, dental plaques from unhealthy sites had a smaller EC50 than those from healthy sites, suggesting the dental plaques from unhealthy sites contain more virulence factors.

The same method described in EXAMPLE 5 was used to examine the clinical samples in another study. A clinical study was conducted to evaluate sample collection methods and measurement procedures. It was a controlled, examiner-blind study. Forty panelists met the inclusion criteria, wherein in order to be included in the study, each panelist must:

    • Provide written informed consent to participate in the study;
    • Be 18 years of age or older;
    • Agree not to participate in any other oral/dental product studies during the course of this study;
    • Agree to delay any elective dentistry (including dental prophylaxis) until the study has been completed;
    • Agree to refrain from any form of non-specified oral hygiene during the treatment periods, including but not limited to the use of products such as floss or whitening products;
    • Agree to return for all scheduled visits and follow study procedures;
    • Must have at least 16 natural teeth;
    • Be in good general health, as determined by the Investigator/designee based on a review of the health history/update for participation in the study.

For Unhealthy Group (high bleeder group):

    • Have at least 20 bleeding sites (sites with a score of 1 or 2 on the GBI index); Have minimum 3 sampling sites with bleeding and pocket depth >3 mm but not deeper than 4 mm;
    • Have minimum 3 sampling sites without bleeding and with pocket depth <2 mm

For Healthy Group (low bleeder group):

    • Have maximum 3 bleeding sites (sites with a score of 1 or 2 on the GBI index);
    • No pockets deeper than 2 mm. Twenty (20) panelists were qualified as healthy—with up to 3 bleeding sites and with all pockets less than or equal to 2 mm deep and twenty (20) panelists were qualified as unhealthy—with greater than 20 bleeding sites with at least 3 pockets greater than or equal to 3 mm but not deeper than 4 mm with bleeding, and at least 3 pockets less than or equal to 2 mm deep with no bleeding for sampling. All panelists had up to 6 sites identified as “sampling sites.” The “sampling sites” had supragingival and subgingival plaque collected at Baseline, Week 2 and Week 4. Subgingival plaque samples were taken from a gingival sulcus from the pre-identified sites. Prior to sample collection, the site had supragingival plaque removed with a curette. The site was dried and subgingival plaque samples were collected with another dental curette (e.g., Gracey 13/14, 15/16, 11/12, 7/8, ½.) Each Gracey curette is designed to adapt to a specific area or tooth surface. For example, Gracey 13/14 is designed to adapt to the distal surfaces of posterior teeth. Samples from each site were placed in a pre-labeled 2.0 ml sterile tube containing 300 μl of DPBS buffer with about 50 of sterile 1 mm glass beads. Samples were stored at 4° C. The subgingival samples were stored at −80° C. until analyzed. The samples were thawed at room temperature and dispersed in a TissueLyser II (Qiagen, Valencia, Calif., USA) at 30 shakes per second for 3 min. Protein concentrations of the dispersed subgingival samples were measured using a Pierce microBCA Protein kit (ThermoFisher Scientific, Grand Island, N.Y., USA) following the manufacturer's instruction.

Oral lavage samples were collected at wake up (one per panelist) by rinsing with 4 ml of water for 30 seconds and then expectorating the contents of the mouth into a centrifuge tube. These samples were frozen at home until they were brought into the site in a cold pack. Each panelist collected up to 15 samples throughout the study. Saliva samples were frozen at −70° C. from submission.

All panelists were given investigational products: Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush. Panelists continued their regular oral hygiene routine, and did not use any new products starting from the baseline to the end of four week treatment study. During the four week treatment period, panelists brushed their teeth twice daily, morning and evening, in their customary manner using the assigned dentifrice and soft manual toothbrush.

The subgingival plaques from the above clinical study were applied to the TLR4 reporter cells in a procedure as described in EXAMPLE 5. FIG. 7A shows the results of a four-week study of 40 panelists going from baseline out over four weeks of treatment with Crest ProHealth Clinical toothpaste. The subgingival plaque samples in bleeding sites on the high bleeders group stimulated high expression of TLR4 reporter gene. More virulence in a sample elicits higher RLU (relative luminescent units) readings in the TLR4 reporter gene assay. As shown in FIG. 7A, the baseline samples of the high bleeders group had higher RLU than those of the low bleeders on both the bleeding and non-bleeding sites. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and lower bleeders groups at both bleeding and non-bleeding sites.

The oral lavage samples were applied to the TLR4 reporter cells in a procedure as described in EXAMPLE 5. As shown in FIG. 7B, oral lavage (Healthy vs. Gingivitis) samples were evaluated in the TLR4-SEAP reporter assay. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the high bleeder group.

Example 8

The reporter gene cell lines, human HEK 293T cells, were purchased from Invivogen of San Diego, Calif. The HEK 293T cells were stably transfected with at least two exogenous genes, a TLR2 structural gene, and SEAP reporter gene which is under the control of NFkB transcriptional factors. The cell line is named here as TLR2-SEAP. The reporter gene encodes a secreted enzyme, called embryonic alkaline phosphatase or SEAP. The SEAP reporter is placed under the control of the interferon-β minimal promoter fused to five NFkB and AP-1-binding sites. Furthermore, a CD14 co-receptor gene was transfected into the reporter gene cells expressing TLR2, as CD14 has been identified as a co-receptor for TLR2 ligands to enhance the TLR response. The CD14 co-receptor is needed to transfer LTA to TLR2 receptors. The recombinant TLR2 binds its ligand, or distinct pathogen-associated molecule, initiates a chain of responses, leading to recruitment of NFkB and AP1 transcription factors to the reporter gene promoter, which induce expression of SEAP.

Cell culture and treatment: 500,000 gene reporter cells were grown and maintained in 15 ml growth medium, comprising DMEM medium supplemented with 10% fetal calf serum in T75 flasks for three days at 37° C., 5% CO2, and 95% humidity. For treatment with LTA, wells of a 96-well plate were seeded with 10,000 cells/well in 100 μL of growth medium. The cells were incubated for 72 hours at 37° C., 5% CO2, and 95% humidity until day 4. On day 4, medium (100 μL) was changed to DMEM medium without fetal calf serum. LTA, LPS and bacterial cells, as described in EXAMPLE 7, were added. Samples were taken 24 hours later, following addition of samples. Expression of the reporter gene (SEAP) was quantified with a commercially available kit (SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich.).

As shown in FIGS. 8A, 8B, 8C and 8D, LTA, LPS, bacteria and the supernatant of bacterial culture could bind to TLR2 and activate TLR2 downstream signaling pathways in a dose-dependent manner. As shown in FIG. 8A, B. subtilis (BS) LTA is more potent than that of Enterococccus hirae. As shown in FIG. 8B, P. gingivalis LPS also activated expression of the TLR2 reporter gene. For example, Pg1690, as shown in FIG. 8B, activated TLR2-SEAP signal transduction, and stimulated SEAP production. But as shown in FIG. 8B, E. coli LPS did not activate the TLR2-SEAP reporter cells. It should also be noted that P. pallens, P. nigrescens and P. gingivalis have similar EC50 in stimulating expression of TLR2 reporter gene (FIG. 8C). However, the released TLR2 ligands from the three different bacteria have very different EC50 on activation of TLR2 reporter gene (FIG. 8D).

Example 9

The method described in EXAMPLE 8 is effective in determining the EC50 of LTA and other TLR2 ligands from different bacteria. The same method was used to determine the EC50 of clinical samples, as described in EXAMPLE 2. As shown in FIG. 9, dental plaques from unhealthy (bleeding) sites had smaller EC50 than those from healthy (non-bleeding) sites, suggesting the dental plaques from unhealthy sites contain more virulence factors.

Clinical samples as described for FIG. 7A of EXAMPLE 7 were examined using the TLR2-SEAP reporter gene assay. The results are shown in FIG. 10A. The subgingival samples in unhealthy (bleeding) sites from the unhealthy group (high bleeders) had more virulence factors than other sites. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders on both the bleeding and non-bleeding sites. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and low bleeders groups at both bleeding sites.

The clinical samples as described for FIG. 7B of EXAMPLE 7 were examined using the TLR2-SEAP reporter gene assay. As shown in FIG. 10B, oral lavage (Healthy vs. Gingivitis) was evaluated. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the high bleeder group.

Example 11

Bacterial cell wall and membrane components are recognized by TLR2. TLR2 recognizes the microbial motifs PGN (peptidoglycan)/lipoproteins/dectin and LPS. TLR1 and TLR6 form heterodimers with TLR2 and bind to triacylated lipoproteins and diacylated lipoproteins, respectively. THP1 NFkB-SEAP and IRF-Lucia™ Reporter Monocytes were purchased from Invivogen, San Diego, Calif. THP1-Dual cells were derived from the human THP-1 monocyte cell line by stable integration of two inducible reporter constructs. THP1-Dual cells feature the Lucia gene under the control of an ISG54 (interferon-stimulated gene) minimal promoter in conjunction with five interferon-stimulated response elements. THP1-Dual cells also express a SEAP reporter gene driven by an IFN-b minimal promoter fused to five copies of the NF-kB consensus transcriptional response element and three copies of the c-Rel binding site. As a result, THP1-Dual cells allow the simultaneous study of the NFkB pathway, by monitoring the activity of SEAP, and the interferon regulatory factor (IRF) pathway, by assessing the activity of Lucia (IRF-Luc). Both reporter proteins are readily measurable in the cell culture supernatant. This THP-1 cell line possesses functional TLR1, TLR2, TLR4, TLR5, TLR6 and TLR8, purchased from Invivogen. TLR4 senses LPS from Gram-negative bacteria while TLR5 recognizes bacterial flagellin from both Gram-positive and Gram-negative bacteria, TLR8 detects long single-stranded RNA.

Culture and treatment: The THP1-dual cells were cultured in 15 ml growth medium (RPMI 1640 with 10% heat-inactivated fetal bovine serum) in a T75 flask at 37° C. and 5% CO2. Cells were passed every 3 to 4 days by inoculating 300,000-500,000 cells/ml into a fresh T75 flask with 15 ml of fresh growth medium. To determine the effect of bacterial components on reporter gene expression, wells in 96-well plates were seeded at 100,000 cells in 90 μl of growth medium. 10 μl of bacterial wall and membrane components, or heat-killed whole bacteria, were added to each well. After incubation for 18 hours at 37° C. and 5% CO2, secreted luciferase and SEAP were quantified with commercially available assay kits (QUANTI-Luc of Invivogen, San Diego, Calif. for luciferase; SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich. for SEAP).

DHP1-dual reporter cells were treated with three different preparations of LPS as shown in FIG. 12A. All three LPS (ng/ml) activated production of NFkB-SEAP reporter genes in a dose-dependent manner. In addition, Pg 1690 LPS and E. coli LPS also stimulated expression of the IRF-luciferase reporter gene. TLR4 ligands, upon binding to TLR4 receptors, activate at least two signaling pathways. One is a common pathway NFkB-SEAP, which can be activated by all TLR ligands upon binding to their specific receptors. For example, TLR2 ligand, LTA, can bind to TLR2 receptors and activate the NFkB-SEAP signaling pathway. Similarly, TLR4 ligand, LPS, upon binding to TLR4 receptors, also is able to activate the NFkB-SEAP signaling transduction. As shown in FIG. 12A, E. coli LPS is a more potent ligand than P. gingivalis 1690 LPS on activation of both NFkB-SEAP and IRF-luciferase signaling transduction. THP-1 cells produce several functional TLR receptors. And all TLR receptors can activate the NFkB pathway, thus promoting expression of the NFkB-SEAP reporter gene. The reading of NFkB-SEAP is the collective actions of all TLR receptors, such as TLR2, TLR1, TLR6 and TLR4. All LPS from different bacteria stimulated NFkB-SEAP reporter gene. IRF-luciferase reporter gene, on the other hand, is driven by a limited number of TLR receptors, primarily TLR3, TLR4, TLR7, TLR8 and TLR9. Both P. gingivalis LPS 1690 and E. coli LPS stimulated expression of IRF-luciferase in a dose-dependent fashion.

The THP-1 reporter cells were used to examine the clinical samples as described for FIG. 7B of EXAMPLE 7. As shown in FIG. 12B, oral lavage (Healthy vs. Gingivitis) was evaluated using the IRF-Luc reporter gene in THP-1 cells. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and lower bleeders groups.

The THP-1 reporter cells were used to examine the clinical samples as described for FIG. 7A of EXAMPLE 7. As shown in FIG. 12C, the subgingival Plaque (Healthy vs. Gingivitis) was examined using the NFkB reporter gene in THP-1 cells. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the bleeding sites in both high and lower bleeders groups.

Example 12

THP1 dual reporter cells also express TLR2, TLR1 and TLR6 receptors. Bacterial cell wall and some membrane components are recognized by TLR2, TLR1 and TLR6. TLR2 recognizes the microbial motifs PGN (peptidoglycan)/lipoproteins/dectin and LPS. To determine whether LTA from different bacteria have different effects on stimulating NFkB-SEAP reporter gene expression in the THP1 dual reporter cells, the cells were prepared and treated in the same procedures as described in EXAMPLE 11. As shown in FIG. 13, LTA from both B. subtilis and S. aureus had similar potency in promoting reporter gene expression in the THP1 dual reporter cells.

Example 14

A randomized, two-group clinical study was conducted with 69 panelists (35 in the negative control group and 34 in the test regimen group). Panelists were 39 years old on average, ranging from 20 to 69, and 46% of the panelists were female. Treatment groups were well balanced, since there were no statistically significant (p≥0.395) differences for demographic characteristics (age, ethnicity, gender) or starting measurements for Gingival Bleeding Index (GBI); mean=29.957 with at least 20 bleeding sites, and Modified Gingival Index (MGI); mean=2.086. All sixty-nine panelists attended each visit and completed the treatment process. The following treatment groups were compared over a 6-week period:

Test regimen: Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse. Control regimen: Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush.

Dental plaques were collected from the same panelists in the test regimen in the clinical study as described in EXAMPLE 2. A supragingival sample was taken from each panelist with a sterile curette at the tooth/gum interface, using care to avoid contact with the oral soft tissue. Plaques were sampled from all available natural teeth (upper arch only) until no plaque was visible. Following sampling, the plaque samples were placed into a pre-labeled (panelist ID, sample initials, visit, and date) Eppendorf tube with 1 ml of PBS/Glycerol buffer and about 50 of sterile 1 mm glass beads, stored on ice until all samples were collected. The samples were then transferred to a −70° C. freezer for storage until further processing. Genomic DNA was isolated from supragingival plaque samples using QIAamp® genomic DNA kits (Qiagen, Germany) following manufacturer's instruction. Metasequencing was carried out at BGI Americas Corporation (Cambridge, Mass.). All data were analyzed at Global Biotech of Procter & Gamble Company in Mason, Ohio.

Clinical measurements: Bleeding sites (GBI) were decreased in the test regimen significantly on week 1, 3 and 6 in comparison to the control regimen (FIG. 14). Similarly, Inflammation (MGI) grades also decreased in the test regimen (FIG. 14).

Genomic DNA of the supragingival plaques in the test regimen was sequenced. As shown in FIG. 15, abundance of certain bacteria in the supragingival plaques changed in the six week treatments. Certain bacteria, such as Porphyromonas sp oral taxon 279 and Prevotella pallens, were decreased in weeks 1 and 3 (FIG. 15). The amount of each bacterial species was plotted over the four time periods of the treatment. The amount of certain bacteria, such as Peptostreptococcus stomatis and Prevotella intermedia, was reduced during the six week of treatment as shown in FIG. 15. This is also shown in FIG. 16A-1, FIG. 16A-2, and FIG. 16A-3.

Example 15

In the same clinical study as described in EXAMPLE 14, gingival-brush samples were collected from the same panelists as in EXAMPLE 14. Before sampling, panelists rinsed their mouths for 30 seconds with water. A dental hygienist then sampled the area just above the gumline using a buccal swab brush (Epicentre Biotechnologies cat.# MB100SP). The swab was immediately placed into 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Lifetechnologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube vortexed for 30 seconds, and immediately frozen on dry ice and stored in a −80 C freezer until analysis. The samples were taken out of freezer, thawed and extracted by placing the samples on a tube shaker for 30 minutes at 4° C. The tubes were centrifuged at 15000 RPM for 10 min in Eppendorf Centrifuge 5417R (Eppendorf, Ontario, Canada) to pellet any debris. The extract (800 μl) was analyzed for protein concentrations using the Bio-Rad protein assay (BioRad, Hercules, Calif.).

Forty proteins were measured in the gingival samples using V-PLEX Human Biomarker 40-Plex Kit (Meso Scale Diagnostics Rockville, Md.). The assay was performed following the manufacturer's instruction.

Among the proteins measured in the gingival samples, most proteins in the Proinflammatory Panel 1 (human), Cytokine Panel 1 (human), Chemokine Panel 1 (human), Angiogenesis Panel 1 (human), and Vascular Injury Panel 2 (human) had significant changes in their abundance during the 6-week treatment (TABLE 6). Those include FN-γ, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, GM-CSF, IL-5, IL-16, IL-7, IL-12/IL-23p40, IL-1α, VEGF-A, IL-17A, IL-15, TNF-β, IL-8 (HA), MCP-1, MCP-4, Eotaxin, IP-10, MDC, Eotaxin-3, TARC, MIP-1α, MIP-1β, VEGF-C, VEGF-D, Tie-2, Flt-1/VEGFR1, PlGF, FGF (basic), SAA, CRP, VCAM-1, and ICAM-1.

TABLE 6
Changes in abundance of proteins in the gingival-brush samples
Meanα = 0.05
BaselineWeek 1Week 3Week 6BaselineWeek 1Week 3Week 6
ICAM-116.03512.20910.0909.767ABB, CC
IL-1α3.5542.3312.1811.891AA, BB, CC
IL-1β53.66635.57524.29524.440ABCC
TNF-β0.00130.00100.00080.0007ABCC
IL-12p700.1720.1480.1180.127AA, BCB, C
IL-130.8050.7620.6240.648AA, BCB, C
IL-40.1270.1150.0900.096AA, BCB, C
IL-50.0040.0030.0020.003ABCB, C
CRP15.63712.74312.3855.809AAAB
Eotaxin0.0770.0640.0590.059AA, BBB
GM-CSF0.0100.0080.0080.008ABBB
IFN [Figure (not displayed)] 0.5300.4460.3780.386AA, BBB
IL-100.8750.4900.4230.244AA, BBB
IL-150.0050.0030.0030.003ABBB
IL-160.4660.3450.3420.295ABBB
IL-60.1960.1920.1680.150AAA, BB
IL-70.0040.0030.0030.003ABBB
IL-8856.276652.066567.361572.602ABBB
MCP-10.0530.0470.0390.039AA, BBB
MDC0.3990.4070.3450.339AABB
Meanα = 0.05
BaselineWeek 1Week 3Week 6BaselineWeek 1Week 3Week 6
SAA7.0396.9056.0925.162AAA, BB
Tie-20.2730.2390.2670.221AA, BAB
VCAM-14.9713.7063.1562.892ABBB
VEGF0.6250.5110.4780.480ABBB
VEGF 20.7720.6610.6200.582ABBB
VEGF-D0.0570.0520.0510.045AA, BA, BB
VEGF-C0.1450.1490.1250.137A, BABA, B
TARC0.0200.0290.0190.019ABAA
bFGF0.0200.0150.0120.013AAAA
Eotaxin-30.0950.1080.0910.094AAAA
Flt-10.3900.5180.4330.415ABA, BA
IL-12p400.0390.0310.0280.031AAAA
IL-20.1660.1990.2100.162AAAA
IL-8 (HA)47.50844.36241.26039.119AAAA
IP-100.5401.6880.7400.606AAAA
MCP-40.0230.0230.0200.022AAAA
MIP-1α0.0910.0910.0840.080AAAA
MIP-1β0.0910.1000.1100.094AAAA
TNFα2.0092.0672.0211.670AAAA

Example 16

The same gingival-brush samples as described in EXAMPLE 15 were used for metabonomic analyses. Fourteen panelists were selected randomly from each treatment group to determine if any metabolite concentrations were changed in gingival samples during the first 3 weeks of treatment. Both baseline and week 3 samples were sent to Metabolon, Inc. (Durham, N.C.) for metabonomic measurement. 170 metabolites were identified and quantified. As shown in TABLE 7, some metabolite concentrations were changed during the first 3 weeks of treatment. Citrulline concentrations in the gingival samples were reduced after three weeks of treatment in the treatment regimen group. Similarly, ornithine was also reduced in the treatment regimen group after three weeks of treatment. Reduction of citrulline and ornithine was likely associated with alleviation of gingivitis.

TABLE 7
Comparison of metabolites in gingival brush samples between baseline and week 3
during gingivitis treatment
Baseline3 week3 week/
Biochemical Namemeanmeanbaselinep-valueq-valueMass
13-HODE + 9-HODE1.08770.70880.650.06010.1338295.2
1-1.22940.82740.670.0380.1035500.3
arachidonoylglycerophosphoethanolamine
1-0.73781.07471.460.07670.1548478.3
oleoylglycerophosphoethanolamine
2-methylbutyrylcarnitine1.77690.69970.390.00340.0546246.1
(C5)
adenosine 5′-1.40920.84510.60.02950.0956348.1
monophosphate (AMP)
alanine0.87211.1021.260.03180.0973115.9
arginylleucine1.44470.68190.470.00840.0777288.3
arginylphenylalanine0.96160.33350.350.01190.0777322.2
asparagylleucine0.92950.61220.660.06980.1465246.2
citrulline1.01470.710.70.01040.0777176.1
deoxycarnitine3.23810.60880.190.00030.0168146.1
EDTA1.59850.83840.520.01380.0777291.1
erythritol1.6250.80850.50.05820.1325217
fructose1.99331.11060.560.08470.1605217
glutamine1.24590.83660.670.03740.1035147.2
glutathione, oxidized1.01611.46691.440.0870.1605613.1
(GSSG)
glycerol1.37830.83080.60.03910.1035205
lauryl sulfate1.6850.86230.510.03970.1035265.2
leucine1.21580.93590.770.06130.1338132.2
leucylleucine0.95050.43930.460.02510.0877245.1
lysylleucine1.20090.52750.440.00360.0546260.2
lysylphenylalanine1.16820.45630.390.00950.0777294.3
maltose0.87271.44811.660.0220.0877204.1
maltotriose1.04561.83471.750.08580.1605204
mannitol1.30040.79820.610.0420.107319.1
ornithine1.29160.70690.550.03670.1035141.9
palatinitol1.43950.82720.570.07820.1549204
phosphate1.40080.83760.60.02080.0877298.9
proline1.4050.990.70.00330.0546116.1
propionylcarnitine1.25650.76880.610.02010.0877218.2
pyroglutamine1.34240.78730.590.01360.0777129.2
serylisoleucine1.17530.71690.610.08140.1583219.2
spermidine1.16130.86780.750.06870.1465146.2
succinate1.29290.81130.630.07540.1548247
threonylleucine1.15130.49310.430.00440.0594231.2
threonylphenylalanine1.76930.9180.520.02330.0877267.2
trehalose2.35630.90840.390.00540.0647361.2
tryptophan1.15180.90890.790.04870.1185205.1
tyrosine1.3831.02990.740.01610.0787182.1
valine1.15980.92710.80.03040.0956118.1
valylvaline0.93470.82310.880.05080.1207215.2
X-136710.50350.9181.820.05450.1267315.3
X-145881.36470.83780.610.0240.0877151
X-161031.36430.84610.620.02970.095699.3
X-172661.31580.5760.440.00030.0168530.4
X-173751.47850.83870.570.01890.0877357.1
X-184720.61381.14411.860.00110.0405827.1
X-187791.37560.80350.580.01620.0787209.1
X-196071.52370.71670.470.0020.0537366.1
X-196091.32840.77210.580.0160.0787204
X-196121.38960.78430.560.010.0777427.2
X-196131.34120.75350.560.00990.0777429.3
X-196141.33780.73430.550.04540.113570.1
X-198071.34780.84110.620.02440.087793
X-198081.33480.83680.630.02540.087795
X-198501.35760.75190.550.0110.0777334.2
X-198571.33570.80320.60.0380.1035230
X-200001.27840.75360.590.01330.077781.2

Example 17

Quantitation of citrulline and ornithine from the extracts of the Gingival-brush samples was conducted using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Gingival-brush samples were obtained from the same human panelists in the clinical study as described in EXAMPLE 14, and were placed into extraction buffer as described in EXAMPLE 15. The supernatants were subject to both HILIC/MS/MS and BCA analysis. For free citrulline and ornithine analysis, the extracts of the Gingival-brush samples were analyzed either directly (50 μl undiluted sample solution) in 50/50 acetonitrile/ultra-pure water with 0.754% formic acid or diluted fivefold. For total citrulline and ornithine analysis, the extracts of the Gingival-brush samples were first hydrolyzed using 6 N HCl (50 μL of extract with 450 μL of 6N HCl), no shaking, and placed on a hot plate at 110° C. for 16 hours. The hydrolyzed samples were then dried down under vacuum at room temperature (Savant speedvac of Lifetechnology, Grand Island, N.Y.) and then reconstituted in 1 ml of dilution solution (50/50 acetonitrile/ultra-pure water with 0.754% formic acid) for analysis. The standards and the samples were analyzed using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Analytes and the corresponding ISTDs (stable isotope labeled internal standard) were monitored by electrospray ionization (ESI) in positive mode using the selected-reaction-monitoring schemes shown in TABLE 8. A standard curve was constructed by plotting the signal, defined here as the peak area ratio (peak area analyte/peak area ISTD), for each standard versus the mass of each analyte for the corresponding standard. The mass of each analyte in the calibration standards and Gingival-brush extract samples were then back-calculated using the generated regression equation. The concentration of protein bound citrulline or ornithine was calculated as the result of subtracting the concentration of free citrulline or ornithine from the concentration of total citrulline or ornithine, respectively. The result was reported as the concentration of citrulline or ornithine or the result was standardized by dividing by the amount of citrulline or ornithine by the amount of the total proteins that were found in the extract.

TABLE 8
Multiple Reaction Monitoring (MRM) transitions
for analytes and their corresponding stable
isotope labeled internal standards
AnalytesMRMInternal StandardsMRM
Citrulline176 → 159d7-Citrulline181 → 164
Ornithine133 → 70d6-Ornithine139 → 76

All samples from all panelists of the Test regimen [Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse] were analyzed. As shown in FIG. 16, citrulline levels reduced rapidly in the first week of treatment, and then continued to decline gradually in weeks 3 and 6 of treatment. These results are consistent with clinical observations, where gingival bleeding sites (GBI) and the gingival inflammation (MGI) were reduced over the 6-week treatment period.

Example 18

The same samples as described in EXAMPLE 17 were analyzed using procedures as described in EXAMPLE 17. Gingivitis was treated for 6 weeks. Baseline (BL) represents diseased status. Symptoms of gingivitis were alleviated from week 1 to week 6 treatments. Protein bound ornithine (the difference between total and the free ornithine) was higher in gingivitis as shown in FIG. 17. Protein bound ornithine was reduced gradually as gingivitis was decreased in severity.

Example 19

Gingival samples were collected as described in EXAMPLES 15, from the same panelists as in EXAMPLE 15, and were used to examine the expression of genes during 6 weeks of treatments with Test regimen [Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse] and Control regimen [Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush].

After harvesting the samples, the brush was completely immersed in the RNAlater solution (1 ml in a 1.5 ml Eppendorf tube) for keeping RNA from degrading during transport and storage (Qiagen, Valencia, Calif.). The microcentrifuge tubes were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

The ornithine-citrulline-arginine cycle consists of four enzymes (FIG. 18). The main feature of the cycle is that three amino acids (arginine, ornithine, and citrulline) can be converted to each other. The first enzyme is ornithine transcarbamoylase, which transfers a carbamoyl group from carbamoyl phosphate to ornithine to generate citrulline. This reaction occurs in the matrix of the mitochondria. Expression of ornithine transcarbamoylase was reduced in the treatment (FIG. 19). The second enzyme is argininosuccinate synthetase. This enzyme uses ATP to activate citrulline by forming a citrullyl-AMP intermediate, which is attacked by the amino group of an aspartate residue to generate argininosuccinate. This and subsequent two reactions occur in the cytosol. Again, expression of argininosuccinate synthetase decreased during the treatment. The third enzyme is argininosuccinate lyase, which catalyzes cleavage of argininosuccinate into fumarate and arginine. The last enzyme is argininase. Argininases cleave arginine to produce urea and ornithine. In a contrast to the decreased expression of ornithine transcarbamoylase and argininosuccinate synthetase genes, argininase I and II increased (FIG. 19).

Arginine is also a substrate for nitric oxide synthase, which oxidizes arginine to produce citrulline and nitric oxide. Expression of nitric oxide synthase gene increased too (FIG. 19).

Example 20

Experimental gingivitis: Another clinical study was carried out to determine whether citrulline is increased in experimentally induced gingivitis in healthy human panelists. This was a case-control study enrolling 60 panelists. The study population included two groups as follows: Group 1 or high bleeders group, thirty (30) panelists with at least 20 bleeding sites, where bleeding is a GBI site score of 1 or 2 at baseline. Group 2 or low bleeders group, thirty (30) panelists with 2 or less bleeding sites, where bleeding is a GBI site score of 1 or 2.

The study consisted of two Phases: Health/Rigorous Hygiene Phase with dental prophylaxis, polishing and rigorous oral hygiene; and Induced Gingivitis Phase without oral hygiene. At the Screening visit, panelists underwent an oral soft tissue assessment and had a gingivitis evaluation (Modified Gingival Index (MGI) and Gingival Bleeding Index (GBI). At Visit 2 qualifying panelists received an oral soft tissue exam followed by a gingivitis evaluation and gingival plaques and gum swabs were collected for the qPCR, protein and RNA host biomarker analysis. Following that, all panelists received dental prophylaxis and entered the Health/Rigorous Hygiene Phase, lasting two weeks. After two weeks of rigorous hygiene, panelists entered the Induced Gingivitis Phase, lasting for three weeks. Oral soft tissue exams and gingivitis were re-evaluated and all samples (gum swabs) were collected at Baseline, WK0 and WK2.

Gingival sample collection—A gum swab was collected from each side of the upper arch using the procedures as described in EXAMPLE 15. Gum swabs were collected close to the gum line from the buccal sites only (preferably from four adjacent teeth—preferably from premolar and molar areas). Panelists rinsed for 30 seconds with 15 ml of Listerine rinse to clean the surface of sampling area. After the Listerine rinse, panelists rinsed for 30 seconds with 20 ml of water. Following that, selected sites were isolated with a cotton roll and gently dried with an air syringe and two gum swabs were taken with collection brushes/swabs from the gingiva region close to the gumline of the selected teeth. The samples were placed in a pre-labeled (panelist ID, sample ID, visit, and date) 1.5 ml micro-centrifuge tube containing 800 ul DPBS (Dulbecco's phosphate-buffered saline) (Lifetechnologies, Grand Island, N.Y.) with protease inhibitors, including AEBSF (4-(2-Aminoethyl) benzenesulfonyl fluoride hydrochloride) 2 mM, aprotinin 0.3 μM, Bestatin 130 μM, EDTA (Ethylenediaminetetraacetic acid) 1 mM, E-64 1 μM, and leupeptin 1 μM. The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. Samples from three visits were analyzed using the procedures described in EXAMPLE 17, and shown in FIG. 20. Those three visits were baseline, Week 0, (right after the Health/Rigorous Hygiene Phase and before the induced gingivitis phase) and week 2 (at the end of Induced Gingivitis Phase). Free citrulline levels were low in both the high and low bleeders groups at the baseline and week 0, but rose quickly in the induced gingivitis in both groups at week 2.

Example 21

The same procedures were used as described in EXAMPLE 17. The samples were the same as described in EXAMPLE 20. Protein bound citrulline was lower at the baseline than that at week 0 in both high and low bleeders groups as shown in FIG. 21 in gingival tissue. It was low in experimental gingivitis in both groups at week 2.

Example 22

The same clinical samples from experimental gingivitis (EXAMPLE 20) were analyzed using the procedures described in EXAMPLE 17. The bound ornithine was the lowest at week 0 (FIG. 22) in both groups. Its levels at the baseline were higher than those at week 0. The bound ornithine reached peaks when gingivitis was induced in both groups at week 2. Also it is worth noting the total ornithine (Free and protein bound ornithine) was increased in the induced gingivitis (FIG. 23) in both groups.

Example 23

The same procedures were used as described in EXAMPLE 17. The samples were the same as described in EXAMPLE 20. The protein bound arginine was the lowest in induced gingivitis (FIG. 24) in both groups. Its levels were higher in WK0 than at Baseline in both groups. The total arginine in the gingival brush samples displayed the same patterns as the protein bound one (FIG. 25).

Example 24

Citrulline was purchased from Sigma-Aldrich (St. Louis, Mo.). THP1-Dual™ cells were purchased from Invivogen (San Diego, Calif.). Cells were cultured following the manufacturer's instruction, as described in EXAMPLE 11. For treatment, 0.3 mM to 9 mM of citrulline were first added to the culture medium. Then, 300 ng/ml of P. gingivalis LPS 1690 were added 60 minutes later. After 24 hours of treatment, media was collected and analyzed for cytokine production using 9-plex kit (Meso Scale Diagnostics Rockville, Md.).

P. gingivalis LPS 1690 stimulated cytokine production, as shown in FIG. 26. Citrulline inhibited P. gingivalis LPS 1690 effects on proinflammatory cytokine production in a dose-dependent manner. Those cytokines include IL-6, TNF-α, IL-12p70, IL-10, IL-2, IFN-r and IL-1β.

Example 26

Growth of bacteria: Two bacteria, Bacterium A and Bacterium B, were cultured in Tryptic Soy Broth medium (Sigma-Aldrich, St. Louis, Mo.) at 37° C. with shaking at 200 rpm. The bacteria were harvested at 24 hours, and suspended in 0.5 ml of phosphate-buffered saline, labeled “live”. Half ml of “Live” bacteria was transferred to a 1.5 ml microtube, and heated to 80° C. for 30 min. The heat-treated bacteria were labeled “Heat-Inactivated”, or “Dead”.

Measurement of TLR responses in THP-1 gene reporter cells (NFkB-SEAP): The Live and Heat-Inactivated bacteria were applied to THP-1 cells as described in EXAMPLE 11. As shown in FIG. 31, EC50 of Bacterium A and B on activation of NFkB-SEAP reporter gene in THP-1 cells was determined. Both Live and Heat-inactivated (Dead) bacteria stimulated expression of the NFkB-SEAP reporter gene. Bacterium B had a lower EC50 than Bacterium A in activating expression of the NFkB-SEAP reporter gene.

Cytokine production and measurement: Human peripheral bleed mononuclear cells (hPBMC) were obtained from All Cells company (All Cells, Alameda, Calif.) as Leukapheresed blood. Leukapheresed blood was mixed with an equal part of DMEM+glutaGRO supplemented with 9.1% fetal bovine serum and 1% penicillin/streptomycin (Thermo Fisher, Waltham, Mass.). hPBMC were isolated from the 1:1 mixture of blood and culture medium by collecting the buffy coat of a centrifuged Histopaque®-1077 (Sigma-Aldrich, St. Louis, Mo.) buffer density gradient. The cells (200,000 cells) were cultured in 200 μl of DMEM+glutaGRO supplemented with 9.1% fetal bovine serum and 1% penicillin/streptomycin, and treated with Live and Heat-Inactive bacteria (6,250,000 colony-forming units). The medium was harvested at 24 hours after adding the bacteria, and analyzed for proinflammatory cytokines in a kit following manufacturer's instruction (Meso Scale Diagnostics, Rockville, Md.).

As shown in TABLE 9, both live bacterium A and B stimulated production of cytokines in hPBMC. Bacteriun B was far more potent than Bacterium A in promoting production of IFN-γ, IL-10, IL-12p70, IL-1β, IL-6, IL-8 and TNF-α in hPBMC.

Live Live
StatisticsCytokinesBacterium ABacterium
MeanIFN-γ867.1612734.36
MeanIL-1068.35412.51
MeanIL-12p7023.75253.47
MeanIL-1β2300.866969.31
MeanIL-244.2465.17
MeanIL-63431.059963.84
MeanIL-865742.9170357.25
MeanTNF-α3710.6613825.49
Std DevIFN-γ488.118200.13
Std DevIL-1033.56314.23
Std DevIL-12p7014.71283.33
Std DevIL-1β1569.727691.93
Std DevIL-232.9736.29
Std DevIL-62212.626552.12
Std DevIL-818689.2413669.28
Std DevTNF-α2503.258302.26

The dimensions and values disclosed herein are not to be understood as being strictly limited to the exact numerical values recited. Instead, unless otherwise specified, each such dimension is intended to mean both the recited value and a functionally equivalent range surrounding that value. For example, a dimension disclosed as “40 mm” is intended to mean “about 40 mm.”

Every document cited herein, including any cross referenced or related patent or application and any patent application or patent to which this application claims priority or benefit thereof, is hereby incorporated herein by reference in its entirety unless expressly excluded or otherwise limited. The citation of any document is not an admission that it is prior art with respect to any invention disclosed or claimed herein or that it alone, or in any combination with any other reference or references, teaches, suggests or discloses any such invention. Further, to the extent that any meaning or definition of a term in this document conflicts with any meaning or definition of the same term in a document incorporated by reference, the meaning or definition assigned to that term in this document shall govern.

While particular embodiments of the present invention have been illustrated and described, it would be obvious to those skilled in the art that various other changes and modifications can be made without departing from the spirit and scope of the invention. It is therefore intended to cover in the appended claims all such changes and modifications that are within the scope of this invention.

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Patent 2019

Example 1

Assessing the degree of gingivitis in a person is typically achieved with clinical measures such as gum redness, gum bleeding or pocket depth. While the measures are based on professionally developed scales, the actual values can vary due to examiner differences. It is desirable to have objective readings free from human errors. This sample collection method enabled the taking of samples for objective measurements non-invasively and site-specifically.

Non-invasive gingival sample collection: Brush samples were taken from the upper, front gums and buccal surface of 4 volunteers, all female, ages 43-48. Interdental Gum Brushes (Sunstar America Inc, Chicago, Ill.), or A MasterAmp™ Buccal Brush (Catalog #MB100SP; Epicentre Technologies Corp., Madison, Wis.) brushes were used to sample 6 marginal gingiva, as shown in FIG. 1, and 6 buccal areas, one brush per sample site. At each sample site a brush was swabbed back-forth 10 times with the brush-head horizontally oriented parallel to the gum line. Each brush head was clipped off with sterile scissors and placed into a 15 ml conical tube with 800 μl DPBS (Dulbecco's phosphate-buffered saline; Lifetechnologies, Grand Island, N.Y.) containing protease inhibitors, including AEBSF (4-(2-Aminoethyl) benzenesulfonyl fluoride hydrochloride) 2 mM, aprotinin 0.3 μM, Bestatin 130 μM, EDTA (Ethylenediaminetetraacetic acid) 1 mM, E-64 1 μM, and leupeptin 1 μM.

Metabolites and protein extraction from gingival samples: All gingival swabs from a given volunteer were pooled into the same collection tube. Similarly all buccal swabs from a given volunteer were pooled into a separate, single collection tube. All collection tubes were vigorously shaken on a multi-tube vortexer for 15 min at 4° C. to extract materials, including metabolites and proteins, from the harvested gingival and buccal samples. Using sterile tweezers the brush heads were dabbed to the side of the tube to collect as much lysate as possible and subsequently discarded. The extracted materials were then centrifuged at 5000 RPM (revolutions per minute) in a Refrigerated at 4° C. table top centrifuge Sigma 4k15 (SIGMA Laborzentrifugen GmbH P.O. Box 1713-37507 Osterode/Germany) to separate the soluble and insoluble fractions. The separated samples were stored at −80° C. in a freezer.

Upon analysis of the samples for total protein the samples appeared to have sufficient protein for further analysis, such as proteomics or metabonomics. Interdental gum brushes appeared to collect enough gingival tissue for further quantifiable molecular analysis.

Example 2

A randomized, parallel group clinical study was conducted with 69 volunteers (35 in the negative control group and 34 in the test regimen group). Volunteers were 39 years old on average, ranging from 20 to 69, and 46% of the volunteers were female. Treatment groups were well balanced, since there were no statistically significant (p≥0.395) differences for demographic characteristics (age, ethnicity, gender) or starting measurements for Gingival Bleeding Index (GBI); mean=29.957 with at least 20 bleeding sites, and Modified Gingival Index (MGI); mean=2.086. All 69 volunteers attended each visit and completed the research. The following treatment groups were compared over a 6-week period: Test regimen: Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse. Control regimen (negative control): Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush.

The test regimen group demonstrated significantly (p<0.0001) lower mean bleeding (GBI) and inflammation (MGI) relative to the negative control group at Weeks 1, 3 and 6 as shown in FIG. 2.

Dental plaques were also collected from the same volunteers in the test regimen in this clinical study. A supragingival sample was taken from each volunteer with a sterile curette at the tooth/gum interface, using care to avoid contact with the oral soft tissue. Plaques were sampled from all available natural teeth (upper arch only) until no plaque was visible. Following sampling, plaques were released from the curettes by shaking with into a pre-labeled (volunteer ID, sample initials, visit, and date) Eppendorf tube 1.5 ml with 1 ml of PBS/Glycerol buffer (20% glyceroal) and about 30 sterile 1 mm glass beads stored on ice until all samples were collected. The samples were then transferred to a −70° C. freezer for storage until further processing. Genomic DNA was isolated from supragingival plaque samples using QIAamp® genomic DNA kits (Qiagen, Valencia, Calif.) following manufacturer's instruction. Metasequencing was carried out in BGI Americas Corporation (Cambridge, Mass.). All data was analyzed at Global Biotech of Procter & Gamble Company in Mason, Ohio.

The Amount of bacterial and host DNA was changed in the supragingival plaques in the 6 week treatments as shown in FIG. 3. Certain bacteria, such as Porphyromonas sp oral taxon 279 and Prevotella pallens, were decreased in weeks 1 and 3 (FIG. 4). The amount of each bacterial species was plotted over the four time periods of the treatment. The amount of certain bacteria, such as Peptostreptococcus stomatis and Prevotella intermedia was reduced from baseline to week 3. The amount of Prevotella intermedia was not statistically different at week 6 from the baseline in relative percentage abundance, but the absolute abundance of Prevotella intermedia was far lower at week 6 than at baseline since the total amount of bacterial DNA decreased dramatically at week 6 (FIGS. 3 and 4).

Example 3

Gingival-brush samples were collected using the procedures described in EXAMPLE 1, from the same volunteers as in EXAMPLE 2. Before sampling, volunteers rinsed their mouths for 30 seconds with water. A dental hygienist then sampled the area just above the gumline using a buccal swab brush (Epicentre Biotechnologies, Madison, Wis., cat. #MB100SP). The swab was immediately placed into 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Lifetechnologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube vortexed for 30 seconds, and immediately frozen on dry ice and stored in a −80 C freezer until analysis. The samples were taken out of the freezer, thawed and extracted by placing the samples on a tube shaker for 30 minutes at 4° C. The tubes were centrifuged at 15000 RPM for 10 min in Eppendorf Centrifuge 5417R (Eppendorf, Ontario, Canada) to pellet any debris. The extract (800 μl) was analyzed for protein concentrations using the Bio-Rad protein assay (BioRad, Hercules, Calif.).

Forty proteins were measured in the gingival samples using V-PLEX Human Biomarker 40-Plex Kit (Meso Scale Diagnostics Rockville, Md.). The assay was performed following the manufacturer's instruction.

V-PLEX Human Biomarker 40-Plex Kit was divided into four panels, or four 96-well plates. Among the proteins measured in the gingival samples, most proteins had significant changes in their abundance during the 6-week treatment (TABLE 1). Those include FN-γ, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, GM-CSF, IL-5, IL-16, IL-7, IL-12/IL-23p40, IL-1α, VEGF-A, IL-17A, IL-15, TNF-β, IL-8 (HA), MCP-1, MCP-4, Eotaxin, IP-10, MDC, Eotaxin-3, TARC, MIP-1α, MIP-1β, VEGF-C, VEGF-D, Tie-2, Flt-1/VEGFR1, P1GF, FGF (basic), SAA, CRP, VCAM-1, and ICAM-1. ICAM-1 and VCAM-1 are high in gingivae having gingivitis, as shown in TABLE 1.

TABLE 1
Changes in abundance of proteins in the gingival-brush samples.
Meanα = 0.05
BaselineWeek 1Week 3Week 6BaselineWeek 1Week 3Week 6
ICAM-116.03512.20910.0909.767ABB, CC
IL-1α3.5542.3312.1811.891AA, BB, CC
IL-1β53.66635.57524.29524.440ABCC
TNF-β0.00130.00100.00080.0007ABCC
IL-12p700.1720.1480.1180.127AA, BCB, C
IL-130.8050.7620.6240.648AA, BCB, C
IL-40.1270.1150.0900.096AA, BCB, C
IL-50.0040.0030.0020.003ABCB, C
CRP15.63712.74312.3855.809AAAB
Eotaxin0.0770.0640.0590.059AA, BBB
GM-CSF0.0100.0080.0080.008ABBB
IFNγ0.5300.4460.3780.386AA, BBB
IL-100.8750.4900.4230.244AA, BBB
IL-150.0050.0030.0030.003ABBB
IL-160.4660.3450.3420.295ABBB
IL-60.1960.1920.1680.150AAA, BB
IL-70.0040.0030.0030.003ABBB
IL-8856.276652.066567.361572.602ABBB
MCP-10.0530.0470.0390.039AA, BBB
MDC0.3990.4070.3450.339AABB
SAA7.0396.9056.0925.162AAA, BB
Tie-20.2730.2390.2670.221AA, BAB
VCAM-14.9713.7063.1562.892ABBB
VEGF0.6250.5110.4780.480ABBB
VEGF 20.7720.6610.6200.582ABBB
VEGF-D0.0570.0520.0510.045AA, BA, BB
VEGF-C0.1450.1490.1250.137A, BABA, B
TARC0.0200.0290.0190.019ABAA
bFGF0.0200.0150.0120.013AAAA
Eotaxin-30.0950.1080.0910.094AAAA
Flt-10.3900.5180.4330.415ABA, BA
IL-12p400.0390.0310.0280.031AAAA
IL-20.1660.1990.2100.162AAAA
IL-8 (HA)47.50844.36241.26039.119AAAA
IP-100.5401.6880.7400.606AAAA
MCP-40.0230.0230.0200.022AAAA
MIP-1α0.0910.0910.0840.080AAAA
MIP-1β0.0910.1000.1100.094AAAA
TNFα2.0092.0672.0211.670AAAA

Example 4

The same gingival-brush samples as described in EXAMPLE 3 were used for metabonomic analyses. Fourteen volunteers were selected randomly from treatment or control regimen (Test regimen: Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse; Control regimen (negative control): Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush), to determine if any metabolite concentrations were changed in gingival samples during the first 3 weeks of treatment. Both baseline and week 3 samples were sent in dry ice to Metabolon, Inc. (Durham, N.C.) for metabonomic measurement. 170 metabolites were identified and quantified. As shown in TABLE 2, some metabolite concentrations were changed during the first 3 weeks of treatment. Citrulline concentrations in the gingival samples were reduced after 3 weeks of treatment in the treatment regimen group. Similarly, ornithine was also reduced in the treatment regimen group after 3 weeks of treatment. Reduction of citrulline and ornithine was likely associated with alleviation of gingivitis as citrulline was reported to be associated with endotoxin treatment (Tannahill GM1, Curtis A M, Adamik J, Palsson-McDermott E M, McGettrick A F, Goel G, Frezza C, Bernard N J, Kelly B, Foley N H, Zheng L, Gardet A, Tong Z, Jany S S, Corr S C, Haneklaus M, Caffrey B E, Pierce K, Walmsley S, Beasley F C, Cummins E, Nizet V, Whyte M, Taylor C T, Lin H, Masters S L, Gottlieb E, Kelly V P, Clish C, Auron P E, Xavier R J, O'Neill L A. Succinate is an inflammatory signal that induces IL-1β through HIF-1α. Nature. 2013 Apr. 11; 496(7444):238-42. doi: 10.1038/nature11986. Epub 2013 Mar. 24.). As shown in TABLE 2, deoxycarnitine was higher in gingivitis (baseline), indicative of abnormal β-oxidation of fatty acid. Succinate is an intermediate in the citric acid cycle. Succinate (which is an intermediate in the citric acid cycle) levels increased in gingivitis, as shown in TABLE 2.

TABLE 2
Comparison of metabolites in gingival brush samples between
baseline and week 3 during gingivitis treatment
3
Base-3week/
lineweekbase-p-q-
Biochemical NamemeanmeanlinevaluevalueMass
13-HODE +1.08770.70880.650.06010.1338295.2
9-HODE
1-arachidonoyl-1.22940.82740.670.0380.1035500.3
glycerophospho-
ethanolamine
1-oleoylglycero-0.73781.07471.460.07670.1548478.3
phosphoethanol-
amine
2-methylbutyryl-1.77690.69970.390.00340.0546246.1
carnitine (C5)
adenosine 5′-1.40920.84510.60.02950.0956348.1
monophosphate
(AMP)
alanine0.87211.1021.260.03180.0973115.9
arginylleucine1.44470.68190.470.00840.0777288.3
arginylphenyl-0.96160.33350.350.01190.0777322.2
alanine
asparagylleucine0.92950.61220.660.06980.1465246.2
citrulline1.01470.710.70.01040.0777176.1
deoxycarnitine3.23810.60880.190.00030.0168146.1
EDTA1.59850.83840.520.01380.0777291.1
erythritol1.6250.80850.50.05820.1325217
fructose1.99331.11060.560.08470.1605217
glutamine1.24590.83660.670.03740.1035147.2
glutathione,1.01611.46691.440.0870.1605613.1
oxidized (GSSG)
glycerol1.37830.83080.60.03910.1035205
lauryl sulfate1.6850.86230.510.03970.1035265.2
leucine1.21580.93590.770.06130.1338132.2
leucylleucine0.95050.43930.460.02510.0877245.1
lysylleucine1.20090.52750.440.00360.0546260.2
lysylphenylalanine1.16820.45630.390.00950.0777294.3
maltose0.87271.44811.660.0220.0877204.1
maltotriose1.04561.83471.750.08580.1605204
mannitol1.30040.79820.610.0420.107319.1
ornithine1.29160.70690.550.03670.1035141.9
palatinitol1.43950.82720.570.07820.1549204
phosphate1.40080.83760.60.02080.0877298.9
proline1.4050.990.70.00330.0546116.1
propionylcarnitine1.25650.76880.610.02010.0877218.2
pyroglutamine1.34240.78730.590.01360.0777129.2
serylisoleucine1.17530.71690.610.08140.1583219.2
spermidine1.16130.86780.750.06870.1465146.2
succinate1.29290.81130.630.07540.1548247
threonylleucine1.15130.49310.430.00440.0594231.2
threonylphenyl-1.76930.9180.520.02330.0877267.2
alanine
trehalose2.35630.90840.390.00540.0647361.2
tryptophan1.15180.90890.790.04870.1185205.1
tyrosine1.3831.02990.740.01610.0787182.1
valine1.15980.92710.80.03040.0956118.1
valylvaline0.93470.82310.880.05080.1207215.2
X- 136710.50350.9181.820.05450.1267315.3
X- 145881.36470.83780.610.0240.0877151
X- 161031.36430.84610.620.02970.095699.3
X- 172661.31580.5760.440.00030.0168530.4
X- 173751.47850.83870.570.01890.0877357.1
X- 184720.61381.14411.860.00110.0405827.1
X- 187791.37560.80350.580.01620.0787209.1
X- 196071.52370.71670.470.0020.0537366.1
X- 196091.32840.77210.580.0160.0787204
X- 196121.38960.78430.560.010.0777427.2
X- 196131.34120.75350.560.00990.0777429.3
X- 196141.33780.73430.550.04540.113570.1
X- 198071.34780.84110.620.02440.087793
X- 198081.33480.83680.630.02540.087795
X- 198501.35760.75190.550.0110.0777334.2
X- 198571.33570.80320.60.0380.1035230
X- 200001.27840.75360.590.01330.077781.2

Example 5

Quantitation of citrulline and ornithine from the extracts of the same Gingival-brush samples as described in EXAMPLE 2, was conducted using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). The gingival-brush samples were placed into extraction buffer as described in EXAMPLE 1. The supernatants were subject to both HILIC/MS/MS and BCA analysis. For free citrulline and ornithine analysis, the extracts of the Gingival-brush samples were analyzed either directly (50 μl of gingival brush extract with 50 μl sample solution sample solution (50/50 acetonitrile/ultra-pure water with 0.754% formic acid) or diluted 5 fold with sample solution. For total citrulline and ornithine analysis, the extracts of the Gingival-brush samples were first hydrolyzed using 6 N HCl (50 μL of extract with 450 μL of 6N HCl), no shaking, and placed on a hot plate at 110° C. for 16 hours. The hydrolyzed samples were then dried down under vacuum at room temperature (Savant speedvac of Lifetechnology, Grand Island, N.Y.) and then reconstituted in 1 ml of dilution solution (50/50 acetonitrile/ultra-pure water with 0.754% formic acid) for analysis. The standards and the samples were analyzed using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Analytes and the corresponding ISTDs (stable isotope labeled internal standard) were monitored by electrospray ionization (ESI) in positive mode using the selected-reaction-monitoring schemes shown in TABLE 3. A standard curve was constructed by plotting the signal, defined here as the peak area ratio (peak area analyte/peak area ISTD), for each standard versus the mass of each analyte for the corresponding standard. The mass of each analyte in the calibration standards and Gingival-brush extract samples were then back-calculated using the generated regression equation. The concentration of protein bound citrulline or ornithine was calculated as the result of subtracting the concentration of free citrulline or ornithine from the concentration of total citrulline or ornithine, respectively. As shown in TABLE 3, the result was reported as the concentration of citrulline or ornithine or the result was standardized by dividing by the amount of citrulline or ornithine by the amount of the total proteins that were found in the extract.

TABLE 3
Multiple Reaction Monitoring (MRM) transitions for analytes and
their corresponding stable isotope labeled internal standards
AnalytesMRMInternal StandardsMRM
Citrulline176 → 159d7-Citrulline181 → 164
Ornithine133 → 70d6-Ornithine139 → 76

All samples in the regimen treatment, as described in EXAMPLE 2, were analyzed. As shown in FIG. 5, citrulline levels reduced rapidly in the first week of treatment, and then continued to decline gradually in weeks 3 and 6 of treatment. These results are consistent with clinical observations, where gingival bleeding sites (GBI) and the gingival inflammation (MGI) were reduced over the 6-week treatment period.

Example 6

The same gingival-brush samples were collected using the procedures described in EXAMPLE 1, from the same volunteers as in EXAMPLE 2. Before sampling, volunteers rinsed their mouths for 30 seconds with water. A dental hygienist then sampled the area just above the gumline using a buccal swab brush (Epicentre Biotechnologies, Madison, Wis., cat. #MB100SP). The swab was immediately placed into 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Lifetechnologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube vortexed for 30 seconds, and immediately frozen on dry ice and stored in a −80 C freezer until analysis. The samples were taken out of the freezer, thawed and extracted by placing the samples on a tube shaker for 30 minutes at 4° C. The tubes were centrifuged at 15000 RPM for 10 min in Eppendorf Centrifuge 5417R (Eppendorf, Ontario, Canada) to pellet any debris. The extract (800 μl) was analyzed for protein concentrations using the Bio-Rad protein assay (BioRad, Hercules, Calif.). Subjects with gingivitis followed test regimen for 6 weeks (Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse). Baseline (BL) represents diseased status. Symptoms of gingivitis, such as bleeding and inflammation were alleviated at week 1 to week 6 treatments. Protein bound ornithine (the difference between total and the free ornithine) was higher in gingivitis as shown in FIG. 6. Protein bound ornithine was reduced gradually as gingivitis was decreased in severity.

Example 7

Separate gingival samples were collected as described in EXAMPLES 1 and 3, from the same volunteers as in EXAMPLE 2, and were used to examine the expression of genes during 6 weeks of treatment. After harvesting the samples, the brush was completely immersed in RNAlater solution (1 ml in in a 1.5 ml Eppendorf tube) to prevent RNA degradation during transport and storage (Qiagen, Valencia, Calif.). The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

The ornithine-citrulline-arginine cycle consists of four enzymes (FIG. 7). The main feature of the cycle is that three amino acids can be converted to each other. The first enzyme is ornithine carbmoyltranferase, which transfers a carbamoyl group from carbamoyl phosphate to ornithine to generate citrulline. This reaction occurs in the matrix of the mitochondria. Expression of ornithine carbmoyltranferase was reduced in the treatment (FIG. 8). The second enzyme is argininosuccinate synthase. This enzyme uses ATP to activate citrulline by forming a citrullyl-AMP intermediate, which is attacked by the amino group of an aspartate residue to generate argininosuccinate. This reaction and the subsequent two reactions (argininosuccinate to arginine and arginine to ornithine) occur in cytosol. Again, expression of argininosuccinate synthetase decreased during the treatment. The third enzyme is argininosuccinate lyase, which catalyzes cleavage of argininosuccinate into fumarate and arginine. The last enzyme is argininase. Argininases cleave arginine to produce urea and ornithine. In a contrast to the decreased expression of both ornithine carbmoyltranferase and argininosuccinate synthetase genes, argininase I (liver) and II increased (FIG. 8).

Arginine is also a substrate for nitric oxide synthases, which oxidizes arginine to produce citrulline and nitric oxide. Expression of nitric oxide synthase 3 gene increased too (FIG. 8).

Example 8

Experimental gingivitis: Another clinical study was carried out to determine whether citrulline is increased in experimentally induced gingivitis in healthy human volunteers. This was a case-control study enrolling 60 volunteers. The study population included two groups as follows: Group 1 or high bleeders group, thirty (30) volunteers with at least 20 bleeding sites, where bleeding is a GBI site score of 1 or 2 at baseline. Group 2, or low bleeders group, thirty (30) volunteers with 2 or less bleeding sites, where bleeding is a GBI site score of 1 or 2.

The study consisted of two Phases: Health/Rigorous Hygiene Phase with a dental cleaning procedure to thoroughly clean the teeth, polishing and rigorous oral hygiene; and induced gingivitis phase without oral hygiene. At the Screening visit, volunteers underwent an oral soft tissue assessment and had a gingivitis evaluation (Modified Gingival Index (MGI) and Gingival Bleeding Index (GBI). At Visit 2 (following the screening visit) participants received an oral soft tissue exam followed by a gingivitis evaluation, and gingival samples were collected, as described below, for host biomarker analysis. Following that, all volunteers entered the Health/Rigorous Hygiene Phase, lasting two weeks. After two weeks of rigorous hygiene, all volunteers entered the Induced Gingivitis Phase, lasting for three weeks. Oral soft tissue exams and gingivitis were re-evaluated and all gingival samples were collected at Baseline, WK0 and WK2.

Gingival sample collection—A gingival brush sample was collected from each side of the upper arch using the procedures as described in EXAMPLE 1. Gingival brush samples were collected close to the gumline from the buccal sites only (preferably from four adjacent teeth—preferably from premolar and molar areas). Volunteers rinsed for 30 seconds with 15 ml of Listerine rinse to clean the surface of sampling area. After the Listerine rinse, volunteers rinsed for 30 seconds with 20 ml of water. Following that, selected sites were isolated with a cotton roll and gently dried with an air syringe and two gum swabs were taken with collection brushes/swabs from the gingiva region close to the gumline of the selected teeth. The samples were placed in a pre-labeled (volunteer ID, sample ID, visit, and date) vial containing 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Life Technologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube. The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. Samples from three visits were analyzed using the procedures as described as in EXAMPLE 5, and shown in FIG. 9. Those three visits were baseline, Week 0, (right after the Health/Rigorous Hygiene Phase and before the induced gingivitis phase) and week 2 (at the end of Induced Gingivitis Phase). Free citrulline levels were low in both the high and low bleeders groups at the baseline and week 0, but rose quickly in the induced gingivitis in both groups at week 2.

Example 9

The same procedures were used as described in EXAMPLE 5. The samples were the same as described in EXAMPLE 8. Protein bound citrulline was lower at the baseline than that at week 0 in both high and low bleeders groups, as shown in FIG. 10 in gingival tissue. It was low in experimental gingivitis in both groups at week 2.

Example 10

The same gingival brush samples from experimental gingivitis, as described in EXAMPLE 8 were analyzed using the procedures described in EXAMPLE 5. The bound ornithine was the lowest at week 0 (FIG. 11) in both groups. Its levels at the baseline were higher than those at week 0. The bound ornithine reached peaks when gingivitis was induced in both groups at week 2. Also it is worth noting the total ornithine (Free and protein bound ornithine) was increased in the induced gingivitis (FIG. 12) in both groups.

Example 11

Levels of Proteins Containing Arginine Decreased in Gingival Samples in Experimentally Induced Gingivitis

The same gingival brush samples from experimental gingivitis, as described in EXAMPLE 8 were analyzed using the procedures as described in EXAMPLE 5. The protein bound arginine was the lowest in induced gingivitis (FIG. 13) in both groups. Its levels were higher in WK0 than that at baseline in both groups. The total arginine in the gingival brush samples displayed the same patterns as the protein bound one (FIG. 14).

Example 12

Human primary blood mononuclear cells were isolated from blood obtained from Gulf Coast Regional Blood Center, Houston, Tex., USA, using Histopaque 1077 (Sigma Aldrich Co., St. Louis, Mo.) and Leucosep tubes (Greiner Bio-One, Monroe, N.C.). The cells were cultured in 200 μl of Roswell Park Memorial Institute (RPMI) 1640 medium in each well of a 90-well plate (ThermoFisher Scientific, Inc., Grand Island, N.Y.) containing 10% fetal bovine serum and 1% penicillin/streptomycin antibiotics at 37° C. with a 5% CO2 atmosphere. B. subtilis LTA, S. aureus LTA, P. gingivalis LPS and E. coli LPS were purchased from Invivogen (San Diego, Calif.). Human dental plaques were harvested in a controlled clinical examiner-blind study. Forty (40) volunteers were used, twenty (20) of which were qualified as healthy—each having up to 3 bleeding sites and with all pockets less than or equal to 2 mm deep; and twenty (20) volunteers were qualified as unhealthy—greater than 20 bleeding sites with at least 3 pockets greater than or equal to 3 mm but not deeper than 4 mm with bleeding, and at least 3 pockets less than or equal to 2 mm deep with no bleeding for sampling. Volunteers had up to 6 sites identified as “sampling sites”. “Sampling sites” had supragingival and subgingival plaque collected at Baseline, Week 2 and Week 4. Subgingival plaque samples were taken from a gingival sulcus from the pre-identified sites. Prior to sample collection, the site had supragingival plaque removed with a curette. The site was dried and subgingival plaque sample were collected with another dental curette (e.g., Gracey 13/14, 15/16, 11/12, 7/8, 1/2). Samples from each site were placed in a pre-labeled 2.0 ml sterile tube containing 300 μl DPBS buffer with about 30 glass beads of 1 mM in diameter. Samples were stored at 4° C. and shipped overnight at 4° C. The subgingival samples were stored at −80° C. freezer until being analyzed. The samples were thawed and dispersed in a TissueLyser II (Qiagen, Valencia, Calif., USA) at 30 shakes per second for 3 min. Protein concentrations of the dispersed subgingival samples were measured using a Pierce microBCA Protein kit (ThermoFisher Scientific, Grand Island, N.Y., USA) following the manufacturer's instruction.

The cells were seeded onto 96-well at 100,000 cells per well in 200 μl of RPMI 1640 medium in each well (ThermoFisher Scientific, Inc., Grand Island, N.Y., USA) containing 10% fetal bovine serum and 1% penicillin/streptomycin antibiotics, and treated with clinical samples and bacterial components. The cells were then incubated for 24 hours at 37° C. with a 5% CO2 atmosphere. Cells were harvested with medium into a 15 ml polypropylene conical tube at the end of experiment. Cells were separated from medium by centrifugation at 1000 RPM for 10 min at 4° C., and immediately frozen and stored at −80° C. until analysis. The samples were analyzed using the procedures as described in EXAMPLE 5.

The human subgingival plaques were pooled from 60 subgingival plaques of bleeding sites. The pooled samples stimulated production of citrulline, arginine and ornithine in primary human peripheral blood mononuclear cells (TABLE 4). Similarly, they also increased malic acid, fumaric acid and succinic acid in the same cells. LPS and LTA also increased production of citrulline, ornithine, arginine and succinic acid in the human primary peripheral blood cells.

TABLE 4
Human subgingival plaques, LPS and LTA increased production of citrulline, ornithine,
arginine and succinic acid in human primary peripheral blood mononuclear cells.
MalicFumaricSuccinic
Treatment DoseArginineCitrullineOrnithineAcidAcidAcid
Sample Treatmentng/mlng/mlng/mlng/mlng/mlng/mlng/ml
LPS-E. coli900 ng/ml2810040826975651161140
LPS-P. gingivalis100 ng/ml4293127143676501291740
LTA-S. aureus900 ng/ml3891954441456281371290
LTA-B. subtilis900 ng/ml3541530342007881791300
human subgingival plaques 19 ng/ml proteins5927953975809192022530
Cells OnlyCulture medium237331212394559127825

Example 13

Separate gingival samples were collected as described in EXAMPLES 1 and 3, from the same volunteers as in EXAMPLE 2, and were used to examine the expression of genes during the six week treatment. After harvesting the samples, the brush was completely immersed in the RNAlater solution to prevent RNA degradation during transport and storage (Qiagen, Valencia, Calif.). The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

Claudins are a family of proteins that are the most important components of the tight junctions, where they establish the paracellular barrier that controls the flow of molecules in the intercellular space between the cells of an epithelium. They have four transmembrane domains, with the N-terminus and the C-terminus in the cytoplasm. Similar to keratins, different claudins are expressed in different layers of keratincoytes during differentiation. Claudins are important components in barrier functions. As shown in TABLE 5, CLDN 1 and 12 decreased during the treatment while CLDN17 and 23 increased. Those changes can be explored as biomarkers in gingivitis.

TABLE 5
Expression of genes for claudins in gingival brush samples during
treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
claudin 111728234_a_atCLDN16.946.536.466.300.000.000.00
claudin 1211720206_s_atCLDN126.436.276.266.220.010.000.00
claudin 1711738572_atCLDN177.428.108.278.100.000.000.00
claudin 2311728603_a_atCLDN237.267.527.567.580.000.000.00

Peptidylarginine deiminases catalyze a form of post translational modification called arginine de-imination or citrullination. These family members have distinct substrate specificities and tissue-specific expression patterns. Peptidyl arginine deiminase, type I, also known as PADI1 is involved in the late stages of epidermal differentiation, where it deiminates filaggrin and keratin K1, which maintains hydration of the stratum corneum, and hence the cutaneous barrier function. PADI2 is widely expressed. Its known substrates for PADI2 include myelin basic protein in the central nervous system and vimentin in skeletal muscle and macrophages. PADI3 is involved in both hair and skin differentiation. As shown in TABLE 6, PADI1 increased while PADI2 decreased during the treatment periods. Those changes can be used as biomarkers of gingivitis severity.

TABLE 6
Expression of genes for peptidylarginine deiminases in gingival brush
samples during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
peptidyl arginine deiminase, type I11751221_a_atPADI18.728.809.029.050.0000.0000.000
peptidyl arginine deiminase, type I11751731_a_atPADI17.557.717.907.920.0010.0000.000
peptidyl arginine deiminase, type I11729333_atPADI110.1710.1310.3210.370.0020.0000.003
peptidyl arginine deiminase, type II11727597_atPADI26.986.746.616.510.0080.0000.000
peptidyl arginine deiminase, type II11745141_a_atPADI26.616.556.576.550.0110.0270.003
peptidyl arginine deiminase, type III11736978_atPADI36.676.736.916.870.0050.0010.000
peptidyl arginine deiminase, type VI11741173_atPADI64.544.524.514.530.0100.0080.219

Keratin is a family of fibrous structural proteins, the key structural material making up the outer layer of human skin, oral mucosa and gingivae. Keratins provide the necessary strength and barrier functions. Keratin monomers assemble into bundles to form intermediate filaments. Keratin compositions change in keratinocytes when they move outward from stratum basale, to spinosum, granulosum and corneum. As shown in TABLE 7, expression of keratin genes changed significantly during the treatment period. Those changes can be used as biomarkers of gingivitis severity.

TABLE 7
Expression of genes for keratins in gingival brush samples during
treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
keratin 1311747755_a_atKRT1311.7211.9311.9411.940.000.000.00
keratin 1511728288_a_atKRT159.178.858.778.710.090.000.00
keratin 1811757905_x_atKRT188.188.578.708.700.000.000.00
keratin 3111731269_atKRT315.405.525.615.610.160.000.00
keratin 411739440_a_atKRT410.9811.3911.4811.570.000.000.00
keratin 6A11747769_x_atKRT6A10.0510.3810.2710.250.020.050.14
keratin 6B11723983_atKRT6B7.808.368.248.110.010.000.09
keratin 6C11727492_atKRT6C7.878.548.238.130.000.050.25
keratin 711715683_a_atKRT76.486.236.235.890.140.000.00
keratin 8011728960_a_atKRT807.928.118.208.130.000.000.00

To provide protection against external environment and microbial, gingival keratinocytes undergo differentiation. Expression of differentiation genes, such as involucrin, loricrin, filaggrin, envoplakin and periplakin genes, are elevated as keratinocytes migrate outward from stratum basale to corneum. As shown in TABLE 8, expression of those differentiation genes was elevated during treatment. The increased expression of keratinocyte differentiation genes can be used as biomarkers of gingivitis severity.

TABLE 8
Expression of genes for keratinocyte differentiation in gingival brush
samples during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group meansAnalysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
envoplakin11726123_a_atEVPL7.618.038.128.150.000.000.00
filaggrin11741116_atFLG9.139.459.489.490.000.000.00
involucrin11731653_a_atIVL8.819.369.559.550.000.000.00
loricrin11731852_atLOR5.956.366.336.630.120.110.01
periplakin11722429_s_atPPL8.328.798.868.850.000.000.00
periplakin11750591_a_atPPL7.197.687.797.780.000.000.00
periplakin11722428_a_atPPL7.598.098.168.160.000.000.00
periplakin11722430_atPPL11.2711.3411.4311.410.000.000.00

Example 14

The same gingival samples, as described as in EXAMPLE 13, were used to examine the expression of genes during the six week treatment. After harvesting the samples, the brush was completely immersed in the RNAlater solution to prevent RNA degradation during transport and storage (Qiagen, Valencia, Calif.). The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

15-Lipoxygenase and 5-lipoxygenase are highly regulated lipid-peroxidating enzymes whose expression and their metabolites are implicated in several important inflammatory conditions. As shown in TABLE 9, ALOX15B, ALOX5, ALOX5AP and PTGS2 decreased during treatment. Their changes can be used as biomarkers of gingivitis severity.

TABLE 9
Expression of genes for metabolizing polyunsaturated fatty acids in gingival
brush samples during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
arachidonate 15-lipoxygenase, type B11734619_x_atALOX15B6.105.735.615.660.000.000.00
arachidonate 15-lipoxygenase, type B11752283_a_atALOX15B5.555.295.235.250.020.000.00
arachidonate 5-lipoxygenase11726337_a_atALOX55.114.974.974.930.000.000.00
arachidonate 5-lipoxygenase-activating11719479_atALOX5AP7.196.846.756.740.000.000.00
protein
prostaglandin-endoperoxide synthase 211724037_atPTGS27.807.307.137.060.050.000.00

Example 15

The same gingival samples, as described in EXAMPLE 13, were used to examine the expression of genes during the six week treatment. After harvesting the samples, a brush was completely immersed in RNAlater solution to prevent RNA degradation during transport and storage (Qiagen, Valencia, Calif.). The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Banos S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12):1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

Glutathione peroxidase (GPX) was increased during treatment. It is an enzyme with peroxidase activity. Its main biological role is to protect the organism from oxidative damage. The biochemical function of glutathione peroxidase is to reduce lipid hydroperoxides to their corresponding alcohols and to reduce free hydrogen peroxide to water. As shown in TABLE 10, both GPX1 and GPX3 were increased during treatment. Their changes represent reduction in gingivitis severity.

TABLE 10
Expression of genes for glutathione peroxidases in gingival brush samples
during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
(Surrogate Variable
Group means (log2)Analysis)
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
glutathione peroxidase 111725346_x_atGPX16.436.766.606.560.000.000.01
glutathione peroxidase 311730170_a_atGPX35.565.996.046.020.000.000.00
(plasma)

Example 16

The same gingival samples were collected and analyzed as described in EXAMPLE 13. β-oxidation is the catabolic process in which chain fatty acid molecules with different lengths are cleaved in the cytosol in the mitochondria in eukaryotes to generate acetyl-CoA. The latter enters the citric acid cycle and results in production of ATP subsequently.

Many enzymes are involved in this process. As shown in TABLE 11, expression of those genes increased during treatment. Increase in their expression is indicative of the improvement in ATP production in the gingival tissue.

TABLE 11
Expression of genes for the citric acid cycle, β-oxidation, and oxidative phosphorylation
in gingival brush samples during treatment of gingivitis at baseline, weeks 1, 3 and 6.
Group change from
Baseline P-values
Group means (log2)(Surrogate Variable
gene_nameprobe_idsymbolBaselineWeek 1Week 3Week 6Week 1Week 3Week 6
acyl-CoA dehydrogenase, C-4 to C-1211722357_a_atACADM7.187.527.467.450.000.000.00
straight chain
acyl-CoA dehydrogenase, C-4 to C-1211757536_s_atACADM7.738.057.957.850.000.000.00
straight chain
carnitine O-octanoyltransferase11720743_x_atCROT6.296.436.566.510.000.000.00
carnitine O-octanoyltransferase11720744_a_atCROT4.854.894.934.920.070.000.07
electron-transferring-flavoprotein11749144_s_atETFDH6.126.426.476.450.000.000.00
dehydrogenase
NADPH dependent diflavin oxidoreductase 111734007_s_atNDOR16.887.167.297.070.000.000.00
NADH dehydrogenase (ubiquinone) 1 alpha11716354_a_atNDUFA117.177.417.437.330.000.000.00
subcomplex, 11, 14.7 kDa
NADH dehydrogenase (ubiquinone) 1 alpha11717202_x_atNDUFA4L26.386.836.856.850.000.000.00
subcomplex, 4-like 2
NADH dehydrogenase (ubiquinone) 1 alpha11718765_a_atNDUFA66.436.796.866.780.000.000.00
subcomplex, 6, 14 kDa
NADH dehydrogenase (ubiquinone) 1 beta11717251_s_atNDUFB118.458.898.918.860.000.000.00
subcomplex, 11, 17.3 kDa
NADH dehydrogenase (ubiquinone) 1 beta11745384_s_atNDUFB47.037.387.357.270.000.000.00
subcomplex, 4, 15 kDa
succinate dehydrogenase complex, subunit11749757_x_atSDHA7.677.948.117.990.000.000.00
A, flavoprotein (Fp)
succinate dehydrogenase complex, subunit11747868_x_atSDHA7.617.917.987.970.000.000.00
A, flavoprotein (Fp)
ubiquinol-cytochrome c reductase, complex11757670_a_atUQCR106.436.676.656.550.000.000.00
III subunit X
ubiquinol-cytochrome c reductase, complex11757334_a_atUQCR117.067.277.267.250.000.000.00
III subunit XI

The dimensions and values disclosed herein are not to be understood as being strictly limited to the exact numerical values recited. Instead, unless otherwise specified, each such dimension is intended to mean both the recited value and a functionally equivalent range surrounding that value. For example, a dimension disclosed as “40 mm” is intended to mean “about 40 mm.”

Every document cited herein, including any cross referenced or related patent or application and any patent application or patent to which this application claims priority or benefit thereof, is hereby incorporated herein by reference in its entirety unless expressly excluded or otherwise limited. The citation of any document is not an admission that it is prior art with respect to any invention disclosed or claimed herein or that it alone, or in any combination with any other reference or references, teaches, suggests or discloses any such invention. Further, to the extent that any meaning or definition of a term in this document conflicts with any meaning or definition of the same term in a document incorporated by reference, the meaning or definition assigned to that term in this document shall govern.

While particular embodiments of the present invention have been illustrated and described, it would be obvious to those skilled in the art that various other changes and modifications can be made without departing from the spirit and scope of the invention. It is therefore intended to cover in the appended claims all such changes and modifications that are within the scope of this invention.

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Example 1

Growth of bacteria: A 1 ml aliquot of a 24 hour culture of E. coli ATCC 8739 was used to inoculate 100 ml of Luria-Bertani (LB) broth in a 250 ml baffled flask. This culture was then incubated at 37° C. with agitation (220 rpm) and sampled at 30 minute intervals. Samples were assessed for turbidity (OD600) in a SpectraMax platereader M3 (Molecular Devices, Sunnydale, Calif.), which is one method of monitoring the growth and physiological state of microorganisms. The sample turbidity was then recorded and the samples were centrifuged at 5000 RPM for 10 min at room temperature. The supernatant, thereinafter referred to as “supernatant of bacterial culture”, was subsequently analyzed for LPS content using the procedure as described below.

Twenty ml aliquots of MTGE broth (Anaerobe Systems, Morgan Hill, Calif.) were inoculated with P. gingivalis ATCC 33277, P. pallens ATCC 700821, or P. nigrescens ATCC 25261. These cultures were incubated overnight in a Whitely A45 Anaerobic Workstation (Don Whitley Scientific, Frederick, Md.) at 37° C. with an 85:10:5 N2:CO2:H2 gas ratio. One ml aliquots of these starter cultures were then used to inoculate 99 ml of membrane-Tryptone Glucose Extract (m-TGE) broth in a 250 ml baffled flask. These cultures were then incubated under agitation (200 rpm) as previously described and sampled at regular intervals. Samples were assessed for turbidity (OD600) in a Tecan Infinite m200 Pro (Tecan Trading AG, Switzerland) and then centrifuged at 16,100×g for 10 min at room temperature. Supernatants were decanted and passed through a 0.22 μM filter prior to analysis for LPS content.

In the experiment, only OD600 was measured. For the sake of consistency in following experiments, we converted OD600 readings into bacterial numbers, even though the relationship between OD600 readings and bacterial numbers is varied for each bacterium. The number of bacteria was estimated based on spectrophotometer readings at OD600 (OD600 of 1.0=8×108 cells/ml).

The Limulus Amebocyte Lysate Assay (LAL) is an assay to determine the total amount of lipopolysaccharide (LPS) in the sample tested (Pierce LAL Chromogenic Endotoxin Quantitation Kit, ThermoFischer Scientific, Waltham, Mass.). The assay was performed following manufacturer's instruction. Ninety-six-well microplates were first equilibrated in a heating block for 10 min at 37° C. Fifty μl each of standard or sample was dispensed into the microplate wells and incubated with plate covered for 5 min at 37° C. Then 50 μl LAL was added to each well. Plates were shaken gently and incubated for 10 min at 37° C. 100 μl of chromogenic substrate was added and incubated for 6 min at 37° C. Finally, 50 μl Stop Reagent was added and the absorbance was measured at 405-410 nm on Spectramax M3 platereader (Molecular Device, Sunnyvale, Calif.).

FIGS. 1A, 1C, and 1D show the ability of microbes to shed LPS as part of their normal growth cycle. This data shows the need to deliver chemistry to the subgingival plaque to effectively mitigate the LPS, since tooth brushing generally does not remove the subgingival plaque.

The LPS, as measured by the LAL kit reported in endotoxin unit per ml (EU/ml), was shed by the bacteria (E. coli K12) as depicted in FIG. 1A. The growth media began to be depleted of complex sugars around 120 minutes, as reflected in the bacterial growth curve in FIG. 1B, where the LPS shedding started to decline. This data gave a reason to believe that a mature biofilm/plaque could supply a constant level of LPS to the host cells, if food sources were present. The LPS would then have the ability to induce an inflammatory response from the host cells.

Importantly, LPS are secreted into the supernatant of bacterial culture (FIG. 1D). LPS also exists in bacterial walls (FIG. 1E). Again, this data further enforce the need to deliver chemistry to the subgingival plaque to effectively mitigate the LPS, since tooth brushing generally does not remove the subgingival plaque.

Example 2

Seven panelists, with at least three bleeding sites, took part in the testing. A licensed dental hygienist collected subgingival plaque samples. Samples were taken at the tooth/gum interface (buccal surfaces only) using care to avoid contact with the oral soft tissues. Six subgingival plaque sites were sampled from each panelist (3 healthy and 3 unhealthy sites). Unhealthy teeth had bleeding sites with pockets greater than 3 mm and healthy sites had no bleeding with pocket depth less than 2 mm Prior to sampling, panelists were instructed to abstain for 12 hours from oral hygiene and refrain from eating, chewing gum, drinking (except small sips of water). Next, panelists had their marginal plaque collected with a curette at the sampling sites. Then, from the same site, subgingival plaque samples were collected with 3 consecutive paper points as shown in FIG. 1F. The sampling sites were isolated with cotton rolls and gently air-dried. Paper points (PROFLOW incorporated, Amityville, N.Y.) were gently placed for 10 seconds into the pocket until a minimum of resistance was felt. After 10 seconds, paper points were removed and placed into pre-labeled 1.5 ml tubes. The same sampling procedure was repeated with 2 more paper points (paper points go into separate tubes). The first, second and third sample paper points from a healthy site of all panelists were pooled separately into three tubes, labeled as paper point 1, 2 and 3, respectively. Similarly the unhealthy site samples were also pooled.

TABLE 1 showed that unhealthy dental plaques contained more endotoxins than the healthy dental plaques. One ml PBS was added to each pooled sample in the 1.5 ml tube. Bacteria were lysed in a MolBio Fast Prep bead beater (MP Biomedicals, Santa Ana, Calif.). Samples were centrifuged for 10 min at 10,000 RPM at 4° C., supernatants were collected and analyzed with LAL assay kits following manufacturer's instruction as described in EXAMPLE 1.

TABLE 1
Protein concentrations and endotoxin levels
in the pooled dental plaque samples.
Endotoxin
Dental plaque(endotoxin unit)
Healthy paperpoint 1 sub plaque1284
Healthy paperpoint 2 sub plaque476
Healthy paperpoint 3 sub plaque361
Healthy Marginal Plaque23180
Unhealthy paperpoint 1 sub plaque3371
Unhealthy paperpoint 2 sub plaque1732
Unhealthy paperpoint 3 sub plaque1644
Unhealthy Marginal Plaque80277

It was expected that the marginal plaques in unhealthy sites had more endotoxins than those in the healthy sites (TABLE1) within the same subjects. Three samples were taken from subgingival pockets with three paper points sequentially, named paper point 1, 2 and 3. Again, the subgingival plaques taken by the paper point 1 had more endotoxins in the unhealthy sites than in the healthy sites (TABLE 1). The same is true for the samples taken by paper point 2 and 3 Importantly, dental plaques in the unhealthy subgingival pockets possessed more endotoxins than plaques from healthy pockets. This may explain why unhealthy gingiva are prone to bleeding upon probing.

Example 3

The LAL assay, as described in EXAMPLE 1, was modified for development of technology which inhibits LPS from activating a proenzyme in the LAL assay. The Thermo Scientific Pierce LAL Chromogenic Endotoxin Quantitation Kit is a quantitative endpoint assay for the detection of LPS, which catalyzes the activation of a proenzyme in the modified Limulus Amebocyte Lysate (LAL). The activated proenzyme then splits p-Nitroaniline (pNA) from the colorless substrate, Ac-Ile-Glu-Ala-Arg-pNA. The product pNA is photometrically measured at 405-410 nm. If SnF2 binds to LPS, the latter can't react with the proenzyme in the LAL kit. Consequently, the proenzyme is not activated, and the colorless substrate Ac-Ile-Glu-Ala-Arg-pNA will not split and no color product is produced. P. gingivalis LPS 1690 (1 ng/ml), or E. coli LPS (1 ng/ml), and stannous fluoride and other materials (50 and 500 μM), as listed in TABLE 2, were dissolved in endotoxin-free water. Then 50 μl LAL was added to each well. Plates were shaken gently and incubated for 10 min at 37° C. 100 μl of chromogenic substrate was added and incubated for 6 min at 37° C. Finally, 50 μl Stop Reagent was added and the absorbance was measured at 405-410 nm on Spectramax M3 plate reader (Molecular Device, Sunnyvale, Calif.).

As shown in TABLE 2, SnF2 and some other compounds inhibited LPS activities in LAL assays

TABLE 2
Inhibition of LPS activities on LAL Assays
Inhibition of LAL activity %
P. gingivalis LPSE. coli LPS
1690 1 ng/ml1 ng/ml
Samples500 uM50 uM500 uM50 uM
Tin (II) fluoride60499287
stannous chloride48218965
Cetylpyridinium chloride1037710346
monohydrate
Chlorhexidine102389757
zinc citrate, dihydrate1045710482
zinc lactate580660
potassium oxalate8016
Triclosan (irgasan)00100
1-Hydroxypyridine-2-thone0026
zinc salt
sodium fluoride0045
Carboxymethyl cellulose0020
sodium

Example 5

Reporter gene cell lines, human HEK 293T cells, were purchased from Invivogen of San Diego, Calif. The HEK 293T cells were stably transfected with at least two exogenous genes, a TLR4 structural gene, and a SEAP reporter gene, which is under the control of NFkB transcriptional factors. The cell line is named here as TLR4-SEAP. The reporter gene encodes a secreted enzyme, called embryonic alkaline phosphatase or SEAP. The SEAP reporter is placed under the control of the interferon-β minimal promoter fused to five NFkB and AP-1-binding sites. Furthermore, the TLR4-SEAP cell line also contains a CD14 co-receptor gene, which is needed to transfer LPS to TLR4 receptors. The recombinant TLR binds its ligand, or distinct pathogen-associated molecule, initiates a chain of responses, leading to recruitment of NFkB and AP1 transcription factors to the reporter gene promoter, which induce expression of SEAP.

Cell culture and treatment: 500,000 gene reporter cells were grown and maintained in 15 ml growth medium, comprised of DMEM medium supplemented with 10% fetal calf serum in T75 flasks for three days at 37° C., 5% CO2, and 95% humidity. For treatment, wells of a 96-well plate were seeded with 10,000 cells/well in 100 μL, of growth medium. The cells were incubated for 72 hours at 37° C., 5% CO2, and 95% humidity until day 4. On day 4, medium was changed to assay medium (90 μl), which is the DMEM medium without fetal calf serum. LPS, bacteria and the culture medium of bacterial growth, as described in EXAMPLE 1, were first resolved or mixed with the assay medium. 10 μl of the bacteria, LPS and culture medium of bacterial growth were added to the TLR4-SEAP cells. Samples were taken 24 hours later, following addition of LPS, bacteria, and culture medium. Expression of the reporter gene (SEAP) was quantified with a commercially available kit (SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich.).

EC50 was calculated using GraphPad Prism software (GraphPad Software, La Jolla, Calif.). Samples with lower EC50 are more potent in activating the TLR4 reporter gene than those with higher EC50. As shown in FIG. 2A, LPS from E. coli has lower EC50 than P. gingivalis, thus, was far more potent than P. gingivalis (Pg). Salmonella Minnesota LPS is not as potent as that of E. coli, but is far more potent than those of P. gingivalis LPS 1690 and 1435. Each species of bacteria produces multiple forms of LPS. Each form of LPS from the same species of bacteria has different potency in stimulating TLR4-downstream signaling pathways. For example, Pg 1690 LPS is more potent than Pg1435/50. LPS is a component in bacterial cell walls. Likely, E. coli cell wall is more virulent in inducing production of proinflammatory cytokines in host cells than P. gingivalis when they are in direct contact with host blood cells. P. gingivalis had far higher EC50 than P. pallens and P. nigrescens as shown in FIG. 2B in stimulating TLR4 reporter gene expression, suggesting that P. pallens and P. nigrescens are more likely to promote production of proinflammatory cytokines in host cells than P. gingivalis.

Bacteria release LPS into the supernatant of bacterial culture. As shown in FIG. 2C, the supernatant of P. pallens has an EC50 that is similar to that of P. nigrescens, but far lower than that of P. gingivalis, in stimulating expression of TLR4 reporter gene. Again, those results imply that the products of P. pallens and P. nigrescens are more likely to promote production of proinflammatory cytokines in host cells than those of P. gingivalis.

Example 6

Stannous fluoride is a leading anti-gingivitis technology in P&G toothpaste products. Tests were conducted to understand whether stannous fluoride could reduce LPS's ability to trigger proinflammatory responses in host cells. TLR4-SEAP reporter cells were prepared using the same conditions as described in EXAMPLE 5 in the presence or absence of LPS. Production of SEAP was quantified also as described in EXAMPLE 5.

FIG. 3 shows the effect of stannous at various concentrations from 62.5 uM to 1,000 uM on 100 ng/ml E. coli LPS, as reported by activation of TLR-4. At stannous concentrations of 500 uM or higher, the level of E. coli induction of TLR-4 was decreased.

FIG. 4 shows the effects of stannous at various concentrations from 62.5 uM to 1,000 uM on P. gingivalis LPS, as reported by activation of TLR-2. At stannous concentrations of 1000 uM, the level of P. gingivalis induction of TLR-2 was decreased.

The data in FIG. 5 shows reduction of LPS activity by the stannous ion, from a stannous fluoride salt. The data showed that stannous fluoride, at 1.6 mM and 3.2 mM, reduce about 50% of P. gingivalis LPS (500 ng/ml) activation on the TLR4 reporter system (One asterisk means P<0.05, two asterisks mean P<0.01).

Example 7

The method described in EXAMPLE 5 is effective at determining the potency of LPS from different bacteria. The same method was used to determine the EC50 of clinical samples, as described in EXAMPLE 2. As shown in FIG. 6, dental plaques from unhealthy sites had a smaller EC50 than those from healthy sites, suggesting the dental plaques from unhealthy sites contain more virulence factors.

The same method described in EXAMPLE 5 was used to examine the clinical samples in another study. A clinical study was conducted to evaluate sample collection methods and measurement procedures. It was a controlled, examiner-blind study. Forty panelists met the inclusion criteria, wherein in order to be included in the study, each panelist must:

    • Provide written informed consent to participate in the study;
    • Be 18 years of age or older;
    • Agree not to participate in any other oral/dental product studies during the course of this study;
    • Agree to delay any elective dentistry (including dental prophylaxis) until the study has been completed;
    • Agree to refrain from any form of non-specified oral hygiene during the treatment periods, including but not limited to the use of products such as floss or whitening products;
    • Agree to return for all scheduled visits and follow study procedures;
    • Must have at least 16 natural teeth;
    • Be in good general health, as determined by the Investigator/designee based on a review of the health history/update for participation in the study.

For Unhealthy Group (high bleeder group):

    • Have at least 20 bleeding sites (sites with a score of 1 or 2 on the GBI index); Have minimum 3 sampling sites with bleeding and pocket depth >3 mm but not deeper than 4 mm;
    • Have minimum 3 sampling sites without bleeding and with pocket depth <2 mm

For Healthy Group (low bleeder group):

    • Have maximum 3 bleeding sites (sites with a score of 1 or 2 on the GBI index);
    • No pockets deeper than 2 mm. Twenty (20) panelists were qualified as healthy—with up to 3 bleeding sites and with all pockets less than or equal to 2 mm deep and twenty (20) panelists were qualified as unhealthy—with greater than 20 bleeding sites with at least 3 pockets greater than or equal to 3 mm but not deeper than 4 mm with bleeding, and at least 3 pockets less than or equal to 2 mm deep with no bleeding for sampling. All panelists had up to 6 sites identified as “sampling sites.” The “sampling sites” had supragingival and subgingival plaque collected at Baseline, Week 2 and Week 4. Subgingival plaque samples were taken from a gingival sulcus from the pre-identified sites. Prior to sample collection, the site had supragingival plaque removed with a curette. The site was dried and subgingival plaque samples were collected with another dental curette (e.g., Gracey 13/14, 15/16, 11/12, ⅞, ½.) Each Gracey curette is designed to adapt to a specific area or tooth surface. For example, Gracey 13/14 is designed to adapt to the distal surfaces of posterior teeth. Samples from each site were placed in a pre-labeled 2.0 ml sterile tube containing 300 μl of DPBS buffer with about 50 of sterile 1 mm glass beads. Samples were stored at 4° C. The subgingival samples were stored at −80° C. until analyzed. The samples were thawed at room temperature and dispersed in a TissueLyser II (Qiagen, Valencia, Calif., USA) at 30 shakes per second for 3 min Protein concentrations of the dispersed subgingival samples were measured using a Pierce microBCA Protein kit (ThermoFisher Scientific, Grand Island, N.Y., USA) following the manufacturer's instruction.

Oral lavage samples were collected at wake up (one per panelist) by rinsing with 4 ml of water for 30 seconds and then expectorating the contents of the mouth into a centrifuge tube. These samples were frozen at home until they were brought into the site in a cold pack. Each panelist collected up to 15 samples throughout the study. Saliva samples were frozen at −70° C. from submission.

All panelists were given investigational products: Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush. Panelists continued their regular oral hygiene routine, and did not use any new products starting from the baseline to the end of four week treatment study. During the four week treatment period, panelists brushed their teeth twice daily, morning and evening, in their customary manner using the assigned dentifrice and soft manual toothbrush.

The subgingival plaques from the above clinical study were applied to the TLR4 reporter cells in a procedure as described in EXAMPLE 5. FIG. 7A shows the results of a four-week study of 40 panelists going from baseline out over four weeks of treatment with Crest ProHealth Clinical toothpaste. The subgingival plaque samples in bleeding sites on the high bleeders group stimulated high expression of TLR4 reporter gene. More virulence in a sample elicits higher RLU (relative luminescent units) readings in the TLR4 reporter gene assay. As shown in FIG. 7A, the baseline samples of the high bleeders group had higher RLU than those of the low bleeders on both the bleeding and non-bleeding sites. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and lower bleeders groups at both bleeding and non-bleeding sites.

The oral lavage samples were applied to the TLR4 reporter cells in a procedure as described in EXAMPLE 5. As shown in FIG. 7B, oral lavage (Healthy vs. Gingivitis) samples were evaluated in the TLR4-SEAP reporter assay. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the high bleeder group.

Example 8

The reporter gene cell lines, human HEK 293T cells, were purchased from Invivogen of San Diego, Calif. The HEK 293T cells were stably transfected with at least two exogenous genes, a TLR2 structural gene, and SEAP reporter gene which is under the control of NFkB transcriptional factors. The cell line is named here as TLR2-SEAP. The reporter gene encodes a secreted enzyme, called embryonic alkaline phosphatase or SEAP. The SEAP reporter is placed under the control of the interferon-β minimal promoter fused to five NFkB and AP-1-binding sites. Furthermore, a CD14 co-receptor gene was transfected into the reporter gene cells expressing TLR2, as CD14 has been identified as a co-receptor for TLR2 ligands to enhance the TLR response. The CD14 co-receptor is needed to transfer LTA to TLR2 receptors. The recombinant TLR2 binds its ligand, or distinct pathogen-associated molecule, initiates a chain of responses, leading to recruitment of NFkB and AP1 transcription factors to the reporter gene promoter, which induce expression of SEAP.

Cell culture and treatment: 500,000 gene reporter cells were grown and maintained in 15 ml growth medium, comprising DMEM medium supplemented with 10% fetal calf serum in T75 flasks for three days at 37° C., 5% CO2, and 95% humidity. For treatment with LTA, wells of a 96-well plate were seeded with 10,000 cells/well in 100 μL, of growth medium. The cells were incubated for 72 hours at 37° C., 5% CO2, and 95% humidity until day 4. On day 4, medium (100 μL) was changed to DMEM medium without fetal calf serum. LTA, LPS and bacterial cells, as described in EXAMPLE 7, were added. Samples were taken 24 hours later, following addition of samples. Expression of the reporter gene (SEAP) was quantified with a commercially available kit (SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich.).

As shown in FIGS. 8A, 8B, 8C and 8D, LTA, LPS, bacteria and the supernatant of bacterial culture could bind to TLR2 and activate TLR2 downstream signaling pathways in a dose-dependent manner. As shown in FIG. 8A, B. subtilis (BS) LTA is more potent than that of Enterococccus hirae. As shown in FIG. 8B, P. gingivalis LPS also activated expression of the TLR2 reporter gene. For example, Pg1690, as shown in FIG. 8B, activated TLR2-SEAP signal transduction, and stimulated SEAP production. But as shown in FIG. 8B, E. coli LPS did not activate the TLR2-SEAP reporter cells. It should also be noted that P. pallens, P. nigrescens and P. gingivalis have similar EC50 in stimulating expression of TLR2 reporter gene (FIG. 8C). However, the released TLR2 ligands from the three different bacteria have very different EC50 on activation of TLR2 reporter gene (FIG. 8D).

Example 9

The method described in EXAMPLE 8 is effective in determining the EC50 of LTA and other TLR2 ligands from different bacteria. The same method was used to determine the EC50 of clinical samples, as described in EXAMPLE 2. As shown in FIG. 9, dental plaques from unhealthy (bleeding) sites had smaller EC50 than those from healthy (non-bleeding) sites, suggesting the dental plaques from unhealthy sites contain more virulence factors.

Clinical samples as described for FIG. 7A of EXAMPLE 7 were examined using the TLR2-SEAP reporter gene assay. The results are shown in FIG. 10A. The subgingival samples in unhealthy (bleeding) sites from the unhealthy group (high bleeders) had more virulence factors than other sites. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders on both the bleeding and non-bleeding sites. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and low bleeders groups at both bleeding sites.

The clinical samples as described for FIG. 7B of EXAMPLE 7 were examined using the TLR2-SEAP reporter gene assay. As shown in FIG. 10B, oral lavage (Healthy vs. Gingivitis) was evaluated. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the high bleeder group.

Example 11

Bacterial cell wall and membrane components are recognized by TLR2. TLR2 recognizes the microbial motifs PGN (peptidoglycan)/lipoproteins/dectin and LPS. TLR1 and TLR6 form heterodimers with TLR2 and bind to triacylated lipoproteins and diacylated lipoproteins, respectively. THP1 NFkB-SEAP and IRF-Lucia™ Reporter Monocytes were purchased from Invivogen, San Diego, Calif. THP1-Dual cells were derived from the human THP-1 monocyte cell line by stable integration of two inducible reporter constructs. THP1-Dual cells feature the Lucia gene under the control of an ISG54 (interferon-stimulated gene) minimal promoter in conjunction with five interferon-stimulated response elements. THP1-Dual cells also express a SEAP reporter gene driven by an IFN-b minimal promoter fused to five copies of the NF-kB consensus transcriptional response element and three copies of the c-Rel binding site. As a result, THP1-Dual cells allow the simultaneous study of the NFkB pathway, by monitoring the activity of SEAP, and the interferon regulatory factor (IRF) pathway, by assessing the activity of Lucia (IRF-Luc). Both reporter proteins are readily measurable in the cell culture supernatant. This THP-1 cell line possesses functional TLR1, TLR2, TLR4, TLR5, TLR6 and TLR8, purchased from Invivogen. TLR4 senses LPS from Gram-negative bacteria while TLR5 recognizes bacterial flagellin from both Gram-positive and Gram-negative bacteria, TLR8 detects long single-stranded RNA.

Culture and treatment: The THP1-dual cells were cultured in 15 ml growth medium (RPMI 1640 with 10% heat-inactivated fetal bovine serum) in a T75 flask at 37° C. and 5% CO2. Cells were passed every 3 to 4 days by inoculating 300,000-500,000 cells/ml into a fresh T75 flask with 15 ml of fresh growth medium. To determine the effect of bacterial components on reporter gene expression, wells in 96-well plates were seeded at 100,000 cells in 90 μl of growth medium. 10 μl of bacterial wall and membrane components, or heat-killed whole bacteria, were added to each well. After incubation for 18 hours at 37° C. and 5% CO2, secreted luciferase and SEAP were quantified with commercially available assay kits (QUANTI-Luc of Invivogen, San Diego, Calif. for luciferase; SEAP Reporter Gene Assay of Cayman Chemical Co., Ann Arbor, Mich. for SEAP).

DHP1-dual reporter cells were treated with three different preparations of LPS as shown in FIG. 12A. All three LPS (ng/ml) activated production of NFkB-SEAP reporter genes in a dose-dependent manner. In addition, Pg 1690 LPS and E. coli LPS also stimulated expression of the IRF-luciferase reporter gene. TLR4 ligands, upon binding to TLR4 receptors, activate at least two signaling pathways. One is a common pathway NFkB-SEAP, which can be activated by all TLR ligands upon binding to their specific receptors. For example, TLR2 ligand, LTA, can bind to TLR2 receptors and activate the NFkB-SEAP signaling pathway. Similarly, TLR4 ligand, LPS, upon binding to TLR4 receptors, also is able to activate the NFkB-SEAP signaling transduction. As shown in FIG. 12A, E. coli LPS is a more potent ligand than P. gingivalis 1690 LPS on activation of both NFkB-SEAP and IRF-luciferase signaling transduction. THP-1 cells produce several functional TLR receptors. And all TLR receptors can activate the NFkB pathway, thus promoting expression of the NFkB-SEAP reporter gene. The reading of NFkB-SEAP is the collective actions of all TLR receptors, such as TLR2, TLR1, TLR6 and TLR4. All LPS from different bacteria stimulated NFkB-SEAP reporter gene. IRF-luciferase reporter gene, on the other hand, is driven by a limited number of TLR receptors, primarily TLR3, TLR4, TLR7, TLR8 and TLR9. Both P. gingivalis LPS 1690 and E. coli LPS stimulated expression of IRF-luciferase in a dose-dependent fashion.

The THP-1 reporter cells were used to examine the clinical samples as described for FIG. 7B of EXAMPLE 7. As shown in FIG. 12B, oral lavage (Healthy vs. Gingivitis) was evaluated using the IRF-Luc reporter gene in THP-1 cells. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in both high and lower bleeders groups.

The THP-1 reporter cells were used to examine the clinical samples as described for FIG. 7A of EXAMPLE 7. As shown in FIG. 12C, the subgingival Plaque (Healthy vs. Gingivitis) was examined using the NFkB reporter gene in THP-1 cells. The baseline samples of the high bleeders group had higher RLU than those of the low bleeders. After treatment with Crest® Pro-Health Clinical Gum Protection Toothpaste (0.454% stannous fluoride) and Oral-B® Indicator Soft Manual Toothbrush for four weeks, the virulence was reduced at week 4 in the bleeding sites in both high and lower bleeders groups.

Example 12

THP1 dual reporter cells also express TLR2, TLR1 and TLR6 receptors. Bacterial cell wall and some membrane components are recognized by TLR2, TLR1 and TLR6. TLR2 recognizes the microbial motifs PGN (peptidoglycan)/lipoproteins/dectin and LPS. To determine whether LTA from different bacteria have different effects on stimulating NFkB-SEAP reporter gene expression in the THP1 dual reporter cells, the cells were prepared and treated in the same procedures as described in EXAMPLE 11. As shown in FIG. 13, LTA from both B. subtilis and S. aureus had similar potency in promoting reporter gene expression in the THP1 dual reporter cells.

Example 14

A randomized, two-group clinical study was conducted with 69 panelists (35 in the negative control group and 34 in the test regimen group). Panelists were 39 years old on average, ranging from 20 to 69, and 46% of the panelists were female. Treatment groups were well balanced, since there were no statistically significant (p>0.395) differences for demographic characteristics (age, ethnicity, gender) or starting measurements for Gingival Bleeding Index (GBI); mean=29.957 with at least 20 bleeding sites, and Modified Gingival Index (MGI); mean=2.086. All sixty-nine panelists attended each visit and completed the treatment process. The following treatment groups were compared over a 6-week period:

Test regimen: Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse. Control regimen: Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush.

Dental plaques were collected from the same panelists in the test regimen in the clinical study as described in EXAMPLE 2. A supragingival sample was taken from each panelist with a sterile curette at the tooth/gum interface, using care to avoid contact with the oral soft tissue. Plaques were sampled from all available natural teeth (upper arch only) until no plaque was visible. Following sampling, the plaque samples were placed into a pre-labeled (panelist ID, sample initials, visit, and date) Eppendorf tube with 1 ml of PBS/Glycerol buffer and about 50 of sterile 1 mm glass beads, stored on ice until all samples were collected. The samples were then transferred to a −70° C. freezer for storage until further processing. Genomic DNA was isolated from supragingival plaque samples using QIAamp® genomic DNA kits (Qiagen, Germany) following manufacturer's instruction. Metasequencing was carried out at BGI Americas Corporation (Cambridge, Mass.). All data were analyzed at Global Biotech of Procter & Gamble Company in Mason, Ohio.

Clinical measurements: Bleeding sites (GBI) were decreased in the test regimen significantly on week 1, 3 and 6 in comparison to the control regimen (FIG. 14). Similarly, Inflammation (MGI) grades also decreased in the test regimen (FIG. 14).

Genomic DNA of the supragingival plaques in the test regimen was sequenced. As shown in FIG. 15, abundance of certain bacteria in the supragingival plaques changed in the six week treatments. Certain bacteria, such as Porphyromonas sp oral taxon 279 and Prevotella pallens, were decreased in weeks 1 and 3 (FIG. 15). The amount of each bacterial species was plotted over the four time periods of the treatment. The amount of certain bacteria, such as Peptostreptococcus stomatis and Prevotella intermedia, was reduced during the six week of treatment as shown in FIG. 15.

Example 15

In the same clinical study as described in EXAMPLE 14, gingival-brush samples were collected from the same panelists as in EXAMPLE 14. Before sampling, panelists rinsed their mouths for 30 seconds with water. A dental hygienist then sampled the area just above the gumline using a buccal swab brush (Epicentre Biotechnologies cat.# MB 100SP). The swab was immediately placed into 1 ml extraction buffer [PBS, 0.25M NaCl, 1× Halt™ Protease Inhibitor Single-Use Cocktail (Lifetechnologies, Grand Island, N.Y.)] in a 1.5 ml Eppendorf tube vortexed for 30 seconds, and immediately frozen on dry ice and stored in a −80 C freezer until analysis. The samples were taken out of freezer, thawed and extracted by placing the samples on a tube shaker for 30 minutes at 4° C. The tubes were centrifuged at 15000 RPM for 10 min in Eppendorf Centrifuge 5417R (Eppendorf, Ontario, Canada) to pellet any debris. The extract (800 μl) was analyzed for protein concentrations using the Bio-Rad protein assay (BioRad, Hercules, Calif.).

Forty proteins were measured in the gingival samples using V-PLEX Human Biomarker 40-Plex Kit (Meso Scale Diagnostics Rockville, Md.). The assay was performed following the manufacturer's instruction.

Among the proteins measured in the gingival samples, most proteins in the Proinflammatory Panel 1 (human), Cytokine Panel 1 (human), Chemokine Panel 1 (human), Angiogenesis Panel 1 (human), and Vascular Injury Panel 2 (human) had significant changes in their abundance during the 6-week treatment (TABLE 6). Those include FN-γ, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, GM-CSF, IL-5, IL-16, IL-7, IL-12/IL-23p40, IL-1α, VEGF-A, IL-17A, IL-15, TNF-β, IL-8 (HA), MCP-1, MCP-4, Eotaxin, IP-10, MDC, Eotaxin-3, TARC, MIP-1α, MIP-1β, VEGF-C, VEGF-D, Tie-2, Flt-1/VEGFR1, PlGF, FGF (basic), SAA, CRP, VCAM-1, and ICAM-1.

TABLE 6
Changes in abundance of proteins in the gingival-brush samples
Meanα = 0.05
BaselineWeek 1Week 3Week 6BaselineWeek 1Week 3Week 6
ICAM-116.03512.20910.0909.767ABB, CC
IL-1α3.5542.3312.1811.891AA, BB, CC
IL-1β53.66635.57524.29524.440ABCC
TNF-β0.00130.00100.00080.0007ABCC
IL-12p700.1720.1480.1180.127AA, BCB, C
IL-130.8050.7620.6240.648AA, BCB, C
IL-40.1270.1150.0900.096AA, BCB, C
IL-50.0040.0030.0020.003ABCB, C
CRP15.63712.74312.3855.809AAAB
Eotaxin0.0770.0640.0590.059AA, BBB
GM-CSF0.0100.0080.0080.008ABBB
IFNγ0.5300.4460.3780.386AA, BBB
IL-100.8750.4900.4230.244AA, BBB
IL-150.0050.0030.0030.003ABBB
IL-160.4660.3450.3420.295ABBB
IL-60.1960.1920.1680.150AAA, BB
IL-70.0040.0030.0030.003ABBB
IL-8856.276652.066567.361572.602ABBB
MCP-10.0530.0470.0390.039AA, BBB
MDC0.3990.4070.3450.339AABB
SAA7.0396.9056.0925.162AAA, BB
Tie-20.2730.2390.2670.221AA, BAB
VCAM-14.9713.7063.1562.892ABBB
VEGF0.6250.5110.4780.480ABBB
VEGF 20.7720.6610.6200.582ABBB
VEGF-D0.0570.0520.0510.045AA, BA, BB
VEGF-C0.1450.1490.1250.137A, BABA, B
TARC0.0200.0290.0190.019ABAA
bFGF0.0200.0150.0120.013AAAA
Eotaxin-30.0950.1080.0910.094AAAA
Flt-10.3900.5180.4330.415ABA, BA
IL-12p400.0390.0310.0280.031AAAA
IL-20.1660.1990.2100.162AAAA
IL-8 (HA)47.50844.36241.26039.119AAAA
IP-100.5401.6880.7400.606AAAA
MCP-40.0230.0230.0200.022AAAA
MIP-1α0.0910.0910.0840.080AAAA
MIP-10.0910.1000.1100.094AAAA
TNFα2.0092.0672.0211.670AAAA

Example 16

The same gingival-brush samples as described in EXAMPLE 15 were used for metabonomic analyses. Fourteen panelists were selected randomly from each treatment group to determine if any metabolite concentrations were changed in gingival samples during the first 3 weeks of treatment. Both baseline and week 3 samples were sent to Metabolon, Inc. (Durham, N.C.) for metabonomic measurement. 170 metabolites were identified and quantified. As shown in TABLE 7, some metabolite concentrations were changed during the first 3 weeks of treatment. Citrulline concentrations in the gingival samples were reduced after three weeks of treatment in the treatment regimen group. Similarly, ornithine was also reduced in the treatment regimen group after three weeks of treatment. Reduction of citrulline and ornithine was likely associated with alleviation of gingivitis.

TABLE 7
Comparison of metabolites in gingival brush samples between baseline and week 3 during gingivitis treatment
Baseline3 week 3 week/
Biochemical Namemeanmeanbaselinep-value q-valueMass
13-HODE + 9-HODE1.08770.70880.650.06010.1338295.2
1-arachidonoylglycero-1.22940.82740.670.0380.1035500.3
phosphoethanolamine
1-oleoylglycero-0.73781.07471.460.07670.1548478.3
phosphoethanolamine
2-methylbutyrylcarnitine1.77690.69970.390.00340.0546246.1
(C5)
adenosine 5′-monophosphate1.40920.84510.60.02950.0956348.1
(AMP)
alanine0.87211.1021.260.03180.0973115.9
arginylleucine1.44470.68190.470.00840.0777288.3
arginylphenylalanine0.96160.33350.350.01190.0777322.2
asparagylleucine0.92950.61220.660.06980.1465246.2
citrulline1.01470.710.70.01040.0777176.1
deoxycarnitine3.23810.60880.190.00030.0168146.1
EDTA1.59850.83840.520.01380.0777291.1
erythritol1.6250.80850.50.05820.1325217
fructose1.99331.11060.560.08470.1605217
glutamine1.24590.83660.670.03740.1035147.2
glutathione, oxidized (GSSG)1.01611.46691.440.0870.1605613.1
glycerol1.37830.83080.60.03910.1035205
lauryl sulfate1.6850.86230.510.03970.1035265.2
leucine1.21580.93590.770.06130.1338132.2
leucylleucine0.95050.43930.460.02510.0877245.1
lysylleucine1.20090.52750.440.00360.0546260.2
lysylphenylalanine1.16820.45630.390.00950.0777294.3
maltose0.87271.44811.660.0220.0877204.1
maltotriose1.04561.83471.750.08580.1605204
mannitol1.30040.79820.610.0420.107319.1
ornithine1.29160.70690.550.03670.1035141.9
palatinitol1.43950.82720.570.07820.1549204
phosphate1.40080.83760.60.02080.0877298.9
proline1.4050.990.70.00330.0546116.1
propionylcarnitine1.25650.76880.610.02010.0877218.2
pyroglutamine1.34240.78730.590.01360.0777129.2
serylisoleucine1.17530.71690.610.08140.1583219.2
spermidine1.16130.86780.750.06870.1465146.2
succinate1.29290.81130.630.07540.1548247
threonylleucine1.15130.49310.430.00440.0594231.2
threonylphenylalanine1.76930.9180.520.02330.0877267.2
trehalose2.35630.90840.390.00540.0647361.2
tryptophan1.15180.90890.790.04870.1185205.1
tyrosine1.3831.02990.740.01610.0787182.1
valine1.15980.92710.80.03040.0956118.1
valylvaline0.93470.82310.880.05080.1207215.2
X-136710.50350.9181.820.05450.1267315.3
X-145881.36470.83780.610.0240.0877151
X-161031.36430.84610.620.02970.095699.3
X-172661.31580.5760.440.00030.0168530.4
X-173751.47850.83870.570.01890.0877357.1
X-184720.61381.14411.860.00110.0405827.1
X-187791.37560.80350.580.01620.0787209.1
X-196071.52370.71670.470.0020.0537366.1
X-196091.32840.77210.580.0160.0787204
X-196121.38960.78430.560.010.0777427.2
X-196131.34120.75350.560.00990.0777429.3
X-196141.33780.73430.550.04540.113570.1
X-198071.34780.84110.620.02440.087793
X-198081.33480.83680.630.02540.087795
X-198501.35760.75190.550.0110.0777334.2
X-198571.33570.80320.60.0380.1035230
X-200001.27840.75360.590.01330.077781.2

Example 17

Quantitation of citrulline and ornithine from the extracts of the Gingival-brush samples was conducted using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Gingival-brush samples were obtained from the same human panelists in the clinical study as described in EXAMPLE 14, and were placed into extraction buffer as described in EXAMPLE 15. The supernatants were subject to both HILIC/MS/MS and BCA analysis. For free citrulline and ornithine analysis, the extracts of the Gingival-brush samples were analyzed either directly (50 μl undiluted sample solution) in 50/50 acetonitrile/ultra-pure water with 0.754% formic acid or diluted fivefold. For total citrulline and ornithine analysis, the extracts of the Gingival-brush samples were first hydrolyzed using 6 N HCl (50 μL of extract with 450 μL of 6N HCl), no shaking, and placed on a hot plate at 110° C. for 16 hours. The hydrolyzed samples were then dried down under vacuum at room temperature (Savant speedvac of Lifetechnology, Grand Island, N.Y.) and then reconstituted in 1 ml of dilution solution (50/50 acetonitrile/ultra-pure water with 0.754% formic acid) for analysis. The standards and the samples were analyzed using gradient hydrophilic interaction liquid chromatography with tandem mass spectrometry (HILIC/MS/MS). Analytes and the corresponding ISTDs (stable isotope labeled internal standard) were monitored by electrospray ionization (ESI) in positive mode using the selected-reaction-monitoring schemes shown in TABLE 8. A standard curve was constructed by plotting the signal, defined here as the peak area ratio (peak area analyte/peak area ISTD), for each standard versus the mass of each analyte for the corresponding standard. The mass of each analyte in the calibration standards and Gingival-brush extract samples were then back-calculated using the generated regression equation. The concentration of protein bound citrulline or ornithine was calculated as the result of subtracting the concentration of free citrulline or ornithine from the concentration of total citrulline or ornithine, respectively. The result was reported as the concentration of citrulline or ornithine or the result was standardized by dividing by the amount of citrulline or ornithine by the amount of the total proteins that were found in the extract.

TABLE 8
Multiple Reaction Monitoring (MRM) transitions for analytes and
their corresponding stable isotope labeled internal standards
AnalytesMRMInternal StandardsMRM
Citrulline176 → 159d7-Citrulline181 → 164
Ornithine133 → 70 d6-Ornithine139 → 76 

All samples from all panelists of the Test regimen [Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse] were analyzed. As shown in FIG. 16, citrulline levels reduced rapidly in the first week of treatment, and then continued to decline gradually in weeks 3 and 6 of treatment. These results are consistent with clinical observations, where gingival bleeding sites (GBI) and the gingival inflammation (MGI) were reduced over the 6-week treatment period.

Example 18

The same samples as described in EXAMPLE 17 were analyzed using procedures as described in EXAMPLE 17. Gingivitis was treated for 6 weeks. Baseline (BL) represents diseased status. Symptoms of gingivitis were alleviated from week 1 to week 6 treatments. Protein bound ornithine (the difference between total and the free ornithine) was higher in gingivitis as shown in FIG. 17. Protein bound ornithine was reduced gradually as gingivitis was decreased in severity.

Example 19

Gingival samples were collected as described in EXAMPLES 15, from the same panelists as in EXAMPLE 15, and were used to examine the expression of genes during 6 weeks of treatments with Test regimen [Crest® Pro-Health Clinical Plaque Control (0.454% stannous fluoride) dentifrice, Oral-B® Professional Care 1000 with Precision Clean brush head and Crest® Pro-Health Refreshing Clean Mint (0.07% CPC) mouth rinse] and Control regimen [Crest® Cavity Protection (0.243% sodium fluoride) dentifrice and Oral-B® Indicator Soft Manual toothbrush].

After harvesting the samples, the brush was completely immersed in the RNAlater solution (1 ml in in a 1.5 ml Eppendorf tube) for keeping RNA from degrading during transport and storage (Qiagen, Valencia, Calif.). The microcentrifuge tubes were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. RNA isolation and microarray analysis were performed as described previously in a publication (Offenbacher S, Barros S P, Paquette D W, Winston J L, Biesbrock A R, Thomason R G, Gibb R D, Fulmer A W, Tiesman J P, Juhlin K D, Wang S L, Reichling T D, Chen K S, Ho B. J Periodontol. 2009 December; 80(12): 1963-82. doi: 10.1902/jop.2009.080645. Gingival transcriptome patterns during induction and resolution of experimental gingivitis in humans).

The ornithine-citrulline-arginine cycle consists of four enzymes (FIG. 18). The main feature of the cycle is that three amino acids (arginine, ornithine, and citrulline) can be converted to each other. The first enzyme is ornithine transcarbamoylase, which transfers a carbamoyl group from carbamoyl phosphate to ornithine to generate citrulline. This reaction occurs in the matrix of the mitochondria. Expression of ornithine transcarbamoylase was reduced in the treatment (FIG. 19). The second enzyme is argininosuccinate synthetase. This enzyme uses ATP to activate citrulline by forming a citrullyl-AMP intermediate, which is attacked by the amino group of an aspartate residue to generate argininosuccinate. This and subsequent two reactions occur in the cytosol. Again, expression of argininosuccinate synthetase decreased during the treatment. The third enzyme is argininosuccinate lyase, which catalyzes cleavage of argininosuccinate into fumarate and arginine. The last enzyme is argininase. Argininases cleave arginine to produce urea and ornithine. In a contrast to the decreased expression of ornithine transcarbamoylase and argininosuccinate synthetase genes, argininase I and II increased (FIG. 19).

Arginine is also a substrate for nitric oxide synthase, which oxidizes arginine to produce citrulline and nitric oxide. Expression of nitric oxide synthase gene increased too (FIG. 19).

Example 20

Experimental Gingivitis:

Another clinical study was carried out to determine whether citrulline is increased in experimentally induced gingivitis in healthy human panelists. This was a case-control study enrolling 60 panelists. The study population included two groups as follows: Group 1 or high bleeders group, thirty (30) panelists with at least 20 bleeding sites, where bleeding is a GBI site score of 1 or 2 at baseline. Group 2 or low bleeders group, thirty (30) panelists with 2 or less bleeding sites, where bleeding is a GBI site score of 1 or 2.

The Study Consisted of Two Phases:

Health/Rigorous Hygiene Phase with dental prophylaxis, polishing and rigorous oral hygiene; and Induced Gingivitis Phase without oral hygiene. At the Screening visit, panelists underwent an oral soft tissue assessment and had a gingivitis evaluation (Modified Gingival Index (MGI) and Gingival Bleeding Index (GBI). At Visit 2 qualifying panelists received an oral soft tissue exam followed by a gingivitis evaluation and gingival plaques and gum swabs were collected for the qPCR, protein and RNA host biomarker analysis. Following that, all panelists received dental prophylaxis and entered the Health/Rigorous Hygiene Phase, lasting two weeks. After two weeks of rigorous hygiene, panelists entered the Induced Gingivitis Phase, lasting for three weeks. Oral soft tissue exams and gingivitis were re-evaluated and all samples (gum swabs) were collected at Baseline, WK0 and WK2.

Gingival Sample Collection—

A gum swab was collected from each side of the upper arch using the procedures as described in EXAMPLE 15. Gum swabs were collected close to the gum line from the buccal sites only (preferably from four adjacent teeth—preferably from premolar and molar areas). Panelists rinsed for 30 seconds with 15 ml of Listerine rinse to clean the surface of sampling area. After the Listerine rinse, panelists rinsed for 30 seconds with 20 ml of water. Following that, selected sites were isolated with a cotton roll and gently dried with an air syringe and two gum swabs were taken with collection brushes/swabs from the gingiva region close to the gumline of the selected teeth. The samples were placed in a pre-labeled (panelist ID, sample ID, visit, and date) 1.5 ml micro-centrifuge tube containing 800 ul DPBS (Dulbecco's phosphate-buffered saline) (Lifetechnologies, Grand Island, N.Y.) with protease inhibitors, including AEBSF (4-(2-Aminoethyl)benzenesulfonyl fluoride hydrochloride) 2 mM, aprotinin 0.3 μM, Bestatin 130 μM, EDTA (Ethylenediaminetetraacetic acid) 1 mM, E-64 1 μM, and leupeptin 1 μM. The vials were vortexed/mixed for 30 seconds, immediately frozen on dry ice, stored and transferred on dry ice to the lab for biomarker analysis. Samples from three visits were analyzed using the procedures described in EXAMPLE 17, and shown in FIG. 20. Those three visits were baseline, Week 0, (right after the Health/Rigorous Hygiene Phase and before the induced gingivitis phase) and week 2 (at the end of Induced Gingivitis Phase). Free citrulline levels were low in both the high and low bleeders groups at the baseline and week 0, but rose quickly in the induced gingivitis in both groups at week 2.

Example 21

The same procedures were used as described in EXAMPLE 17. The samples were the same as described in EXAMPLE 20. Protein bound citrulline was lower at the baseline than that at week 0 in both high and low bleeders groups as shown in FIG. 21 in gingival tissue. It was low in experimental gingivitis in both groups at week 2.

Example 22

The same clinical samples from experimental gingivitis (EXAMPLE 20) were analyzed using the procedures described in EXAMPLE 17. The bound ornithine was the lowest at week 0 (FIG. 22) in both groups. Its levels at the baseline were higher than those at week 0. The bound ornithine reached peaks when gingivitis was induced in both groups at week 2. Also it is worth noting the total ornithine (Free and protein bound ornithine) was increased in the induced gingivitis (FIG. 23) in both groups.

Example 23

The same procedures were used as described in EXAMPLE 17. The samples were the same as described in EXAMPLE 20. The protein bound arginine was the lowest in induced gingivitis (FIG. 24) in both groups. Its levels were higher in WK0 than at Baseline in both groups. The total arginine in the gingival brush samples displayed the same patterns as the protein bound one (FIG. 25).

Example 24

Citrulline was purchased from Sigma-Aldrich (St. Louis, Mo.). THP1-Dual™ cells were purchased from Invivogen (San Diego, Calif.). Cells were cultured following the manufacturer's instruction, as described in EXAMPLE 11. For treatment, 0.3 mM to 9 mM of citrulline were first added to the culture medium. Then, 300 ng/ml of P. gingivalis LPS 1690 were added 60 minutes later. After 24 hours of treatment, media was collected and analyzed for cytokine production using 9-plex kit (Meso Scale Diagnostics Rockville, Md.).

P. gingivalis LPS 1690 stimulated cytokine production, as shown in FIG. 26. Citrulline inhibited P. gingivalis LPS 1690 effects on proinflammatory cytokine production in a dose-dependent manner. Those cytokines include IL-6, TNF-α, IL-12p70, IL-10, IL-2, IFN-r and IL-1β.

Example 26

Growth of bacteria: Two bacteria, Bacterium A and Bacterium B, were cultured in Tryptic Soy Broth medium (Sigma-Aldrich, St. Louis, Mo.) at 37° C. with shaking at 200 rpm. The bacteria were harvested at 24 hours, and suspended in 0.5 ml of phosphate-buffered saline, labeled “live”. Half ml of “Live” bacteria was transferred to a 1.5 ml microtube, and heated to 80° C. for 30 min. The heat-treated bacteria were labeled “Heat-Inactivated”, or “Dead”.

Measurement of TLR responses in THP-1 gene reporter cells (NFkB-SEAP): The Live and Heat-Inactivated bacteria were applied to THP-1 cells as described in EXAMPLE 11. As shown in FIG. 31, EC50 of Bacterium A and B on activation of NFkB-SEAP reporter gene in THP-1 cells was determined. Both Live and Heat-inactivated (Dead) bacteria stimulated expression of the NFkB-SEAP reporter gene. Bacterium B had a lower EC50 than Bacterium A in activating expression of the NFkB-SEAP reporter gene.

Cytokine production and measurement: Human peripheral bleed mononuclear cells (hPBMC) were obtained from All Cells company (All Cells, Alameda, Calif.) as Leukapheresed blood. Leukapheresed blood was mixed with an equal part of DMEM+glutaGRO supplemented with 9.1% fetal bovine serum and 1% penicillin/streptomycin (Thermo Fisher, Waltham, Mass.). hPBMC were isolated from the 1:1 mixture of blood and culture medium by collecting the buffy coat of a centrifuged Histopaque®-1077 (Sigma-Aldrich, St. Louis, Mo.) buffer density gradient. The cells (200,000 cells) were cultured in 200 μl of DMEM+glutaGRO supplemented with 9.1% fetal bovine serum and 1% penicillin/streptomycin, and treated with Live and Heat-Inactive bacteria (6,250,000 colony-forming units). The medium was harvested at 24 hours after adding the bacteria, and analyzed for proinflammatory cytokines in a kit following manufacturer's instruction (Meso Scale Diagnostics, Rockville, Md.).

As shown in TABLE 9, both live bacterium A and B stimulated production of cytokines in hPBMC. Bacteriun B was far more potent than Bacterium A in promoting production of IFN-T, IL-10, IL-12p70, IL-1β, IL-6, IL-8 and TNF-α in hPBMC.

StatisticsCytokinesLive Bacterium ALive Bacterium
MeanIFN-γ867.1612734.36
MeanIL-1068.35412.51
MeanIL-12p7023.75253.47
MeanIL-1β2300.866969.31
MeanIL-244.2465.17
MeanIL-63431.059963.84
MeanIL-865742.9170357.25
MeanTNF-α3710.6613825.49
Std DevIFN-γ488.118200.13
Std DevIL-1033.56314.23
Std DevIL-12p7014.71283.33
Std DevIL-1β1569.727691.93
Std DevIL-232.9736.29
Std DevIL-62212.626552.12
Std DevIL-818689.2413669.28
Std DevTNF-α2503.258302.26

The dimensions and values disclosed herein are not to be understood as being strictly limited to the exact numerical values recited. Instead, unless otherwise specified, each such dimension is intended to mean both the recited value and a functionally equivalent range surrounding that value. For example, a dimension disclosed as “40 mm” is intended to mean “about 40 mm.”

Every document cited herein, including any cross referenced or related patent or application and any patent application or patent to which this application claims priority or benefit thereof, is hereby incorporated herein by reference in its entirety unless expressly excluded or otherwise limited. The citation of any document is not an admission that it is prior art with respect to any invention disclosed or claimed herein or that it alone, or in any combination with any other reference or references, teaches, suggests or discloses any such invention. Further, to the extent that any meaning or definition of a term in this document conflicts with any meaning or definition of the same term in a document incorporated by reference, the meaning or definition assigned to that term in this document shall govern.

While particular embodiments of the present invention have been illustrated and described, it would be obvious to those skilled in the art that various other changes and modifications can be made without departing from the spirit and scope of the invention. It is therefore intended to cover in the appended claims all such changes and modifications that are within the scope of this invention.

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Patent 2018
Samples -A total of 48 T. cruzi stocks from T. infestans and three from Rhodnius pictipes captured in various Bolivian areas in domestic and peridomestic sites were isolated. The digestive tract of each insect was placed in NNN biphasic medium supplemented with 1.5 ml of LIT medium and incubated at 28 o C without shaking. Then subcultures of parasites were processed in small volumes of LIT medium (3 ml) until their adaptation. Mass cultures were obtained by subcultures in higher LIT medium volumes (10 to 50 ml) at 28 o C without shaking. Finally, the adequate quantity of parasites for isoenzyme electrophoresis (20-50 mg of parasite pellet) was obtained after 4 to 6 weeks. The genetic characterization of the stocks by isoenzyme and PCR/hybridization was done from the same collection of cultured parasites.
All fecal samples presented flagellates (direct microscopical observation) and before isolation of the stocks, a drop of feces from each insect was collected in appropriate PCR conditions and preserved at -20 o C for further determination of the clonal composition by PCR/hybridization.
Identification of clonet 20 and 39 by PCR/ hybridization -The procedures for feces collection, extraction and PCR were according to Brenière et al. (1992 Brenière et al. ( , 1995)) , using primers (Genset, Paris, France) chosen to amplify the hyper variable region of the kinetoplast minicircles (HVRm). After electrophoresis the PCR products were transferred on to membranes and successively hybridized with the specific clonet probes 20 and 39 (Veas et al. 1991 , Brenière et al. 1992 ). Total DNAs were purified by phenol/chloroform extraction from parasite pellets of each stock and similarly, the clonets were detected by hybridization of the PCR products amplified from total DNAs.
Isoenzyme characterization -The electrophoretic study was carried out on cellulose acetate plates, according to Ben Abderrazak et al. (1993) with slight modifications. Twelve enzymes systems were surveyed (13 enzymatic loci): glutamate oxaloacetate transaminase (GOT, EC 2.6.1.1), glucose-6-phosphate dehydrogenase (G6PD, EC 1.1.1.49), glucose phosphate isomerase (GPI, EC 5.3.1.9), glutamate dehydrogenase NAD+ (GDH NAD+, EC 1.4.1.2), glutamate dehydrogenase NADP+ (GDH NADP+, EC 1.4.1.4), isocitrate dehydrogenase (IDH, EC 1.1.1.42), malate dehydrogenase (MDH, EC 1.1.1.37), malic enzyme (ME, EC 1.1.1.40), peptidases (substrates: L-leucylleucine-leucine and L-leucyl-L-alanine) (PEP, EC 3.4.11 or 13.*), 6-phospho-gluconate dehydrogenase ( PGDH, EC 1.1.1.44), and phosphoglucomutase (PGM, EC 2.7.5.1). Jaccard's distances (Jaccard 1908) were used to estimate the phenetic divergence between the stocks. The UPGMA method [unweighted pair-group method with arithmetic averages, Sneath and Sokal (1973) ] was used to cluster the zymodemes according to their Jaccard's distances. The dendrogram was obtained using the Mac Dendro software computer program (Thioulouse 1989) .
Publication 2000

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