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Lipoproteins

Lipoproteins are complex macromolecular assemblies of lipids and proteins that function as transporters of lipids in the body.
They play a crucial role in the metabolism and distribution of cholesterol, triglycerides, and other lipids.
Lipoproteins are classified based on their density and composition, including chylomicrons, very low-density lipoproteins (VLDL), low-density lipoproteins (LDL), and high-density lipoproteins (HDL).
Imbalancs in lipoprotein levels are associated with various cardiovascular and metabolic disorders, making them an important target for clinical research and therapeutic interventions.

Most cited protocols related to «Lipoproteins»

1
Deconvolution of Mass Spectrometry Data for Protein Complexes
We describe here application of the UniDec approach to problems of increasing complexity: membrane protein AqpZ; small heat shock proteins HSP17.7, HSP16.5, and αB-crystallin; and lipoprotein Nanodiscs.
MS and IM-MS data of aquaporin Z (AqpZ) with bound 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) obtained at 100 V accelerating potential into a dedicated collision cell was analyzed using UniDec by limiting the mass range to between 95 and 105 kDa.27 (link) An example of how the algorithm performs without mass limitations is shown in Figure S-2. Data was smoothed in MassLynx 4.1 software (Waters Corp.) before analysis with Transform and MaxEnt, which used the same mass limitation.
Deconvolution of subunit exchange data from HSP17.7 was performed by limiting the allowed mass range to between 211 kDa and 222 kDa. Tandem MS spectra of the isolated +47 charge state of HSP16.5 24-mers were summed across multiple collision voltages to compile an aggregate spectrum.28 (link) Deconvolution was performed by limiting the charge state between 10 and 49 and manually defining the +47 charge state, which was necessary because only one charge state was isolated in the MS/MS experiment. Collision induced dissociation (CID) spectra of αB-crystallin were obtained similarly. Masses were limited to within 3000 Da of a wide range of potential oligomer complexes ranging from 1 to 74 subunits of a 20085 Da monomer. Charge was limited to between 5 and 84. In addition to the charge-smooth filter, a mass-smooth filter was applied to smooth the distribution of dimer units.
Nanodiscs with 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and POPC were analyzed with a linear drift cell Waters Synapt G1 ion mobility-mass spectrometer.29 (link) Data was deconvolved without a charge filter but by using a mass filter to smooth the distribution of lipids. Masses were limited to between 100 kDa and 175 kDa. Conversion from arrival time to collision cross section (CCS) was performed using the Mason-Schamp equation as described previously,27 (link),29 (link) using t0 values calibrated from alcohol dehydrogenase analyzed under the same instrumental conditions.
Marty M.T., Baldwin A.J., Marklund E.G., Hochberg G.K., Benesch J.L, & Robinson C.V. (2015). Bayesian Deconvolution of Mass and Ion Mobility Spectra: From Binary Interactions to Polydisperse Ensembles. Analytical chemistry, 87(8), 4370-4376.
Publication 2015
Cells Crystallins Dehydrogenase, Alcohol Dimyristoylphosphatidylcholine Glycerylphosphorylcholine GPER protein, human Heat-Shock Proteins, Small Lipids Lipoproteins Phosphorylcholine plasma protein Z Protein Subunits Range of Motion, Articular Tandem Mass Spectrometry Tissue, Membrane Water Channel
2
Evaluating LDL-c in Metabolic Syndrome
We selected patients with known metabolic syndrome that fulfilled the criteria outlined in the National Cholesterol Education Program Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report [6 (link), 12 (link)]; three or more of the following components were present: increased waist circumference (≥102 cm for men and ≥88 cm  for women); triglycerides ≥ 150 mg/dL or drug treatment for elevated TG; low HDL-c (<40 mg/dL for men and <50 mg/dL for women) or drug treatment for low HDL-c; systolic blood pressure ≥ 130 mmHg, diastolic blood pressure ≥ 85 mmHg, or treatment with antihypertensive in patients with a history of hypertension; fasting glucose ≥ 100 mg/dL or treatment for high blood glucose.
Patients who fulfilled the MS criteria, consented to provide a blood sample, and signed the informed consent form were included in the study. Patients who did not fulfill the MS criteria, did not sign the informed consent form, and had TG ≥ 400 mg/dL were excluded.
All participants underwent a 12-hour fast. The following tests were performed (using a Selectra II analyzer with reagents and calibrators from ELITech): direct assays for TC, HDL-c, LDL-c, and TG. The results were applied in the FF, and then the LDL-c estimation could be performed. LDL-c was determined by a homogenous direct assay (i.e., colorimetry) using an ELITech kit. Colorimetry is a third generation method (a homogeneous assay with some reagents that can solubilize or specifically block these lipoproteins, dosing LDL-c alone in the same bucket with an enzymatic reaction) [17 ]. Thus, we could compare both LDL-c values (using the FF and by direct assay) and evaluate the reliability of the FF in the MS patients.
The results were described as means, medians, minimum values, maximum values, and standard deviations (quantitative variables) or by frequency and percentiles (qualitative variables). For the assessment of the results of LDL-c using the FF and LDL-c by direct assay was used the Student's t-test for paired samples. To evaluate the correlation between both methods, Pearson's correlation coefficient was used. Scattergram data and a Bland-Altman diagram were used to evaluate the dispersion and differences between the results obtained using the FF and direct assay, and P values < 0.05 were considered to be statistically significant. Data were analyzed with the software Statistica v.8.0.
Knopfholz J., Disserol C.C., Pierin A.J., Schirr F.L., Streisky L., Takito L.L., Massucheto Ledesma P., Faria-Neto J.R., Olandoski M., da Cunha C.L, & Bandeira A.M. (2014). Validation of the Friedewald Formula in Patients with Metabolic Syndrome. Cholesterol, 2014, 261878.
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Publication 2014
Adult Antihypertensive Agents Biological Assay BLOOD Cardiac Arrest Cholesterol Colorimetry Enzymes Glucose High Blood Pressures Homozygote Hypercholesterolemia Hyperglycemia Lipoproteins Metabolic Syndrome X Patients Pharmaceutical Preparations Pressure, Diastolic Programmed Learning Systolic Pressure Triglycerides Waist Circumference Woman
3
Comprehensive Metabolomic Profiling for CVD
A high-throughput NMR metabolomics platform8 was used for the quantification of 68 lipid and abundant metabolite measures from baseline serum samples of the FINRISK, SABRE, and BWHHS cohorts. All metabolites were measured in a single experimental setup, which allows for the simultaneous quantification of both routine lipids, total lipid concentrations of 14 lipoprotein subclasses, fatty acid composition such as monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA), various glycolysis precursors, ketone bodies and amino acids in absolute concentration units (Supplemental Table 1).8 (link) The targeted metabolite profiling therefore includes both known metabolic risk factors and metabolites from multiple physiological pathways, which have not previously been examined in relation to CVD risk in large population studies. The 68 metabolite measures were assessed for association with incident CVD events using a hypothesis-generating biomarker discovery approach with subsequent replication in two independent cohorts. Spearman’s correlations of the metabolites are shown in Supplemental Figure 1. The NMR metabolomics platform has previously been used in various epidemiological studies9 ,10 (link),16 (link),17 (link),20 (link)–22 (link),31 (link),32 (link), details of the experimentation have been described9 ,24 (link), and the method has recently been reviewed.8 (link),19 (link)A subset of 679 serum samples from the FINRISK study were additionally profiled with liquid-chromatography mass spectrometry (LC-MS) using the Metabolon platform33 (link) in a case-cohort design for comparison of biomarker associations with incident CVD (expanded methods online). The biomarker associations were further compared with those obtained by LC-MS-based profiling of the Framingham Offspring Study (fifth examination cycle, n=2289 fasting plasma samples), as described in detail previously.13 (link),14 (link) Since several fatty acid biomarkers were not measured by LC-MS, the quantification was analytically confirmed by comparing NMR and gas chromatography in the Cardiovascular Risk in Young Finns Study (YFS, n=2193 fasting serum samples).34 (link) Metabolite profiling data collected at two-time points in YFS9 was further used to examine associations of dietary intake with the circulating biomarkers, and tracking of concentrations within the same individuals over 6 years.
Würtz P., Havulinna A.S., Soininen P., Tynkkynen T., Prieto-Merino D., Tillin T., Ghorbani A., Artati A., Wang Q., Tiainen M., Kangas A.J., Kettunen J., Kaikkonen J., Mikkilä V., Jula A., Kähönen M., Lehtimäki T., Lawlor D.A., Gaunt T.R., Hughes A.D., Sattar N., Illig T., Adamski J., Wang T.J., Perola M., Ripatti S., Vasan R.S., Raitakari O.T., Gerszten R.E., Casas J.P., Chaturvedi N., Ala-Korpela M, & Salomaa V. (2015). Metabolite Profiling and Cardiovascular Event Risk: A Prospective Study of Three Population-Based Cohorts. Circulation, 131(9), 774-785.
Publication 2015
Amino Acids Biological Markers DNA Replication Fatty Acids Fatty Acids, Monounsaturated Gas Chromatography Glycolysis Ketone Bodies Lipids Lipoproteins Liquid Chromatography Mass Spectrometry physiology Plasma Polyunsaturated Fatty Acids Serum
4
Multivariable Mendelian Randomization: Dissecting Lipid Traits
We first conducted univariable MR analyses for each lipid-related trait. For this, we harmonised SNPs identified from our GWASs of lipoprotein lipid traits in the UKBB to those SNPs available in CARDIoGRAMplusC4D by either matching the SNP directly or by selecting proxy SNPs in high LD (r2 > 0.8). This led to a small drop in the number of SNPs being available for MR, with a median of 93% SNPs identified in GWASs available for MR (the numbers available for each trait are provided in Table 1). We used the inverse variance weighted approach, which, in brief, takes the form of a linear regression of the SNP–outcome association regressed on the SNP–exposure association weighted by the inverse of the square of the standard error of the SNP–outcome association, with the intercept constrained at the origin.
We next conducted multivariable MR, which is a statistical approach that allows for the association of SNPs with multiple phenotypes to be incorporated into the analysis, permitting an estimation of the direct effect of each phenotype on the outcome (i.e., an effect that is not mediated by any other factor in the model [28 (link)]); see S1 Fig for further details. In this manuscript, we use the term ‘adjusted’ in the context of multivariable MR to mean ‘direct’ effects, i.e., the effect of a lipid trait on CHD whilst accounting for either mediation or confounding by another trait included in the model. For the multivariable MR analyses, we fitted a model with apolipoprotein B, LDL cholesterol, and triglycerides to identify which one or more traits appeared to be responsible for the effect of ‘atherogenic’ lipid-related traits on risk of CHD. We then took the atherogenic trait(s) that retained an effect on CHD in the multivariable MR model forward and further adjusted for apolipoprotein A-I and HDL cholesterol to assess the potential causal roles of HDL-related phenotypes in the development of CHD. In the setting of multivariable MR, we included all GWAS-associated SNPs for all traits in the model. This meant that there were differing numbers of SNPs in the 2 multivariable models tested.
We characterised instrument strengths in both the univariable and multivariable MR settings as follows: for the univariable estimates, we generated the mean F-statistic, using the approximation described by Bowden and colleagues [44 (link)]. For the multivariable estimate, we generated the conditional F-statistic [28 (link),45 ]. Further details are provided in S1 Text.
Richardson T.G., Sanderson E., Palmer T.M., Ala-Korpela M., Ference B.A., Davey Smith G, & Holmes M.V. (2020). Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis. PLoS Medicine, 17(3), e1003062.
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Publication 2020
Apolipoprotein A-I Apolipoproteins B Atherogenesis Cholesterol, beta-Lipoprotein Genome-Wide Association Study High Density Lipoprotein Cholesterol Lipid A Lipids Lipoproteins Phenotype Single Nucleotide Polymorphism Triglycerides
5
Optimized Serum Metabolite Profiling by NMR
Serum samples contain a substantial portion of large molecular weight proteins and lipoproteins, which affects the identification and quantification of small molecule metabolites by NMR spectroscopy. Consequently, we introduced a step in the protocol to remove serum proteins (deproteinization). There are several routes to serum deproteinization, including organic solvent (acetonitrile, methanol, isopropanol) precipitation, ultrafiltration [28] (link), [44] (link) as well as spectral manipulation methods such as diffusion editing [45] (link). While other researchers have found that ultrafiltration yields poor signal-to-noise ratios, we found that by using an ultrafiltration protocol similar to that described by Tiziani [46] (link) and Weljie et al [47] (link), we could obtain excellent spectra that yielded metabolite concentrations that closely matched known values measured using standard clinical chemistry techniques. Ultrafiltration also has other advantages: it is relatively quick, very reproducible, does not introduce unwanted solvent peaks and is “safe” in terms of avoiding unwanted side-reactions with biofluid metabolites. All 1H-NMR spectra were collected on a either a 500 MHz or 800 MHz Inova (Varian Inc., Palo Alto, CA) spectrometer using the first transient of the tnnoesy-presaturation pulse sequence. The resulting 1H-NMR spectra were processed and analyzed using the Chenomx NMR Suite Professional software package version 6.0 (Chenomx Inc., Edmonton, AB), as previously described [15] . Further details on the NMR sample preparation and NMR data acquisition are provided in File S1.
Psychogios N., Hau D.D., Peng J., Guo A.C., Mandal R., Bouatra S., Sinelnikov I., Krishnamurthy R., Eisner R., Gautam B., Young N., Xia J., Knox C., Dong E., Huang P., Hollander Z., Pedersen T.L., Smith S.R., Bamforth F., Greiner R., McManus B., Newman J.W., Goodfriend T, & Wishart D.S. (2011). The Human Serum Metabolome. PLoS ONE, 6(2), e16957.
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Publication 2011
1H NMR acetonitrile Diffusion Isopropyl Alcohol Lipoproteins Methanol Proteins Pulse Rate Serum Serum Proteins Solvents Spectroscopy, Nuclear Magnetic Resonance Staphylococcal Protein A Transients Ultrafiltration

Most recents protocols related to «Lipoproteins»

1
Translocation of Surface Lipoproteins in E. coli
Not available on PMC !

Example 6

TbpB and NMB0313 genes were amplified from the genome of Neisseria meningitidis serotype B strain B16B6. The LbpB gene was amplified from Neisseria meningitidis serotype B strain MC58. Full length TbpB was inserted into Multiple Cloning Site 2 of pETDuet using restriction free cloning ((F van den Ent, J. Löwe, Journal of Biochemical and Biophysical Methods (Jan. 1, 2006)).). NMB0313 was inserted into pET26, where the native signal peptide was replaced by that of pelB. Mutations and truncations were performed on these vectors using site directed mutagenesis and restriction free cloning, respectively. Pairs of vectors were transformed into E. coli C43 and were grown overnight in LB agar plates supplemented with kanamycin (50 μg/mL) and ampicillin (100 μg/mL).

tbpB genes were amplified from the genomes of M. catarrhalis strain 035E and H. influenzae strain 86-028NP and cloned into the pET52b plasmid by restriction free cloning as above. The corresponding SLAMs (M. catarrhalis SLAM 1, H. influenzae SLAM1) were inserted into pET26b also using restriction free cloning. A 6His-tag was inserted between the pelB and the mature SLAM sequences as above. Vectors were transformed into E. coli C43 as above.

Cells were harvested by centrifugation at 4000 g and were twice washed with 1 mL PBS to remove any remaining growth media. Cells were then incubated with either 0.05-0.1 mg/mL biotinylated human transferrin (Sigma-aldrich T3915-5 MG), α-TbpB (1:200 dilution from rabbit serum for M. catarrhalis and H. influenzae; 1:10000 dilution from rabbit serum for N. meningitidis), or α-LbpB (1:10000 dilution from rabbit serum-obtained a gift from J. Lemieux) or α-fHbp (1:5000 dilution from mouse, a gift from D. Granoff) for 1.5 hours at 4° C., followed by two washes with 1 mL of PBS. The cells were then incubated with R-Phycoerythrin-conjugated Streptavidin (0.5 mg/ml Cedarlane) or R-phycoerythrin conjugated Anti-rabbit IgG (Stock 0.5 mg/ml Rockland) at 25 ug/mL for 1.5 hours at 4° C. The cells were then washed with 1 mL PBS and resuspended in 200 uL fixing solution (PBS+2% formaldehyde) and left for 20 minutes. Finally, cells were washed with 2×1 mL PBS and transferred to 5 mL polystyrene FACS tubes. The PE fluorescence of each sample was measured for PE fluorescence using a Becton Dickinson FACSCalibur. The results were analyzed using FLOWJO software and were presented as mean fluorescence intensity (MFI) for each sample. For N. meningtidis experiments, all samples were compared to wildtype strains by normalizing wildtype fluorescent signals to 100%. Errors bars represent the standard error of the mean (SEM) across three experiments. Results were plotted statistically analysed using GraphPad Prism 5 software. The results shown in FIG. 6 for the SLPs, TbpB (FIG. 6A), LbpB. (FIG. 6B) and fHbp (FIG. 6C) demonstrate that SLAM effects translocation of all three SLP polypeptides in E. coli. The results shown in FIG. 10 demonstrate that translocation of TbpB from M. catarrhalis (FIG. 10C) and in H. influenzae (FIG. 10D) in E. coli require the co-expression of the required SLAM protein (Slam is an outer membrane protein that is required for the surface display of lipidated virulence factors in Neisseria. Hooda Y, Lai C C, Judd A, Buckwalter C M, Shin H E, Gray-Owen S D, Moraes T F. Nat Microbiol. 2016 Feb. 29; 1:16009).

US11872275B2. SLAM polynucleotides and polypeptides and uses thereof (2024-01-16). ENGINEERED ANTIGENS INC. [CA]. Inventors: Trevor F. Moraes [CA], Christine Chieh-Lin Lai [CA], Yogesh Hooda [CA], Andrew Judd [CA], Anthony B. Schryvers [CA], Scott D. Gray-Owen [CA].
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Patent 2024
ADRB2 protein, human Agar Ampicillin anti-IgG Cells Centrifugation Cloning Vectors Culture Media Escherichia coli Fluorescence Formaldehyde Genes Genome Haemophilus influenzae Homo sapiens Kanamycin Lipoproteins Membrane Proteins Moraxella catarrhalis Mus Mutagenesis, Site-Directed Mutation Neisseria Neisseria meningitidis Phycoerythrin Plasmids Polypeptides Polystyrenes prisma Rabbits Serum Signaling Lymphocytic Activation Molecule Family Member 1 Signal Peptides Strains Streptavidin Technique, Dilution Transferrin Translocation, Chromosomal Virulence Factors
2
Identifying SLAM-Dependent Surface Lipoproteins
Not available on PMC !

Example 8

In selecting genomes for a given bacterial species where a SLAM homolog was identified, preference was given to reference genomes that contained fully sequenced genomes. SLAM homologs were identified using iterative Blast searches into closely related species to Neisseria to more distantly related species. For each of the SLAM homologs identified in these species, the corresponding genomic record (NCBI genome) was used to identify genes upstream and downstream along with their corresponding functional annotations (NCBI protein database, Ensembl bacteria). In a few cases, no genes were predicted upstream or downstream of the SLAM gene as they were too close to the beginning or end of the contig, respectively, and thus these sequences were ignored.

Neighbouring genes were analyzed for 1) an N-terminal lipobox motif (predicted using LipoP, SignalP), and 2) a solute binding protein, Tbp-like (InterPro signature: IPR or IPR011250), or pagP-beta barrel (InterPro signature: IPR011250) fold. If they contained these elements, we identified the adjacent genes as potential SLAM-dependent surface lipoproteins.

A putative SLAM (PM1515, SEQ ID NO: 1087) was identified in Pasteurella multocida using the Neisseria SLAM as a search. The putative SLAM (PM1515, SEQ ID NO: 1087) was adjacent to a newly predicted lipoprotein gene with unknown function (PM1514, SEQ ID NO: 1083) (FIG. 11A). The putative SLAM displayed 32% identity to N. meningitidis SLAM1 while the SLP showed no sequence similarity to known SLAM-dependent neisserial SLPs.

The putative SLAM (PM1515, SEQ ID NO: 1087) and its adjacent lipoprotein (PM1514, SEQ ID NO: 1083) were cloned into pET26b and pET52b, respectively, as previously described and transformed into E. coli C43 and grown overnight on LB agar supplemented with kanamycin (50 ug/ml) and ampicillin (100 ug/ml).

Cells were grown in auto-induction media for 18 hours at 37 C and then harvested, washed twice in PBS containing 1 mM MgCl2, and labeled with α-Flag (1:200, Sigma) for 1 hr at 4 C. The cells were then washed twice with PBS containing 1 mM MgCl2 and then labeled with R-PE conjugated α-mouse IgG (25 ug/mL, Thermo Fisher Scientific) for 1 hr at 4 C. following straining, cells were fixed in 2% formaldehyde for 20 minutes and further washed with PBS containing 1 mM MgCl2. Flow Cytometry was performed with a Becton Dickinson FACSCalibur and the results were analyzed using FLOWJO software. Mean fluorescence intensity (MFI) was calculated using at least three replicates was used to compare surface exposure the lipoprotein in strains either containing or lacking the putative SLAM (PM1515) and are shown in FIG. 11C and FIG. 11D. PM1514 could be detected on the surface of E. coli illustrating i) that SLAM can be used to identify SLPs and ii) that SLAM is required to translocate these SLPs to the surface of the cell—thus identifying a class of proteins call “SLAM-dependent surface lipoproteins”. Antibodies were raised against purified PmSLP (PM1514) and the protein was shown to be on the surface of Pasteurella multocida via PK shaving assays.

US11872275B2. SLAM polynucleotides and polypeptides and uses thereof (2024-01-16). ENGINEERED ANTIGENS INC. [CA]. Inventors: Trevor F. Moraes [CA], Christine Chieh-Lin Lai [CA], Yogesh Hooda [CA], Andrew Judd [CA], Anthony B. Schryvers [CA], Scott D. Gray-Owen [CA].
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Patent 2024
Agar Ampicillin Antibodies Bacteria Binding Proteins Biological Assay Cells Escherichia coli Flow Cytometry Fluorescence Formaldehyde Genes Genome Kanamycin Lipoprotein (a-) Lipoproteins Magnesium Chloride Mus Neisseria Neisseria meningitidis Pasteurella multocida Proteins Staphylococcal Protein A Strains
3
Sustained Peptide Release for Targeted Therapy
Not available on PMC !

Example 5

According to the teachings herein, one or more peptides comprising a lipoprotein targeting domain and a protease inhibitor domain, optionally further including therebetween a linker, can be placed in a suitable container, such as a tissue microcapsule implant, and placed within a subject to allow continuous, slow release of one or more of the disclosed peptides. Such peptides can either be provided in the free state or after complexation with lipid (e.g., in the form of a loaded or enriched nHDL or rHDL).

US11872261B2. Lipoprotein targeting protease inhibitors and uses (2024-01-16). The United States of America, as represented by the Secretary, Dept. of Health and Human Services [US]. Inventors: Alan T. Remaley [US], Scott M. Gordon [US].
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Patent 2024
Lipids Lipoprotein (a) Lipoproteins Microcapsules Peptides Protease Inhibitors SERPINB5 protein, human Teaching Tissues
4
SLAM C-terminal Rescues SLP Translocation
Not available on PMC !

Example 5

Neisseria meningitidis SLAM knockout strain Δmnb0313 was used to evaluate translocation of surface lipoproteins (SLPs). Full-length SLAM polypeptides and N-terminal and C-terminal portions of the SLAM polypeptide were used. The N-terminal and C-terminal portions are shown in FIG. 5 A. Flow cytometry (FIG. 5B) and proteinase K digestion (FIG. 5C) experiments reveal that the SLP translocation defect observed in the SLAM knockout strain can be rescued with only the C-terminal β-barrel domain (amino acids 204-488). The N-terminal domain (Ntd) (amino acids 32-203) of SLAM does not provide any SLP translocation activity. The mean fluorescent intensity was measured for each sample and the signal obtained from wildtype cells was set to 100% for comparison with signals from knockout and single domain complemented cells. Error bars represent the standard error of the mean (SEM) from three experiments. A * indicates results are significantly different at p<0.05.

US11872275B2. SLAM polynucleotides and polypeptides and uses thereof (2024-01-16). ENGINEERED ANTIGENS INC. [CA]. Inventors: Trevor F. Moraes [CA], Christine Chieh-Lin Lai [CA], Yogesh Hooda [CA], Andrew Judd [CA], Anthony B. Schryvers [CA], Scott D. Gray-Owen [CA].
Full text: Click here
Patent 2024
Amino Acids Cells Digestion Endopeptidase K Flow Cytometry Lipoproteins Neisseria meningitidis polypeptide C Polypeptides Strains Translocation, Chromosomal
5
Untargeted NMR Metabolomics of Serum
Metabolic biomarkers were quantified from serum samples using untargeted high-throughput proton nuclear magnetic resonance (NMR) spectroscopy metabolomics platform (Nightingale Health Plc, Helsinki, Finland). The details of the methodology used have been described previously (Soininen et al., 2015 (link)). The samples were barcoded for sample identification and kept frozen at −80°C for analysis. Metabolites were measured by a quantitative high-throughput NMR experimental set up for the simultaneous quantification of lipids and lipoprotein subclass profiling in 350 µL of serum. All liquid handling procedures were completed prior to the NMR studies, and the SampleJet robotic sample charger was set up at a cooled temperature to prevent sample deterioration. Every single metabolic measurement was subjected to a number of statistical quality control procedures and cross-referenced with a sizable collection of quantitative molecular data.
Alfadda A.A., Almaghamsi A.M., Sherbeeni S.M., Alqutub A.N., Aldosary A.S., Isnani A.C., Al-Daghri N., Taylor-Robinson S.D, & Gul R. (2023). Alterations in circulating lipidomic profile in patients with type 2 diabetes with or without non-alcoholic fatty liver disease. Frontiers in Molecular Biosciences, 10, 1030661.
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Publication 2023
Biological Markers Freezing Lipids Lipoproteins Magnetic Resonance Imaging Proton Magnetic Resonance Spectroscopy Serum

Top products related to «Lipoproteins»

1
Superose 6 column by GE Healthcare
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The Superose 6 column is a size exclusion chromatography (SEC) column designed for the separation and purification of biomolecules such as proteins, peptides, and oligonucleotides. The column is packed with a cross-linked agarose matrix that provides high chemical and physical stability. It is suitable for a wide range of molecular weight separations and can be used with a variety of common buffer systems.
2
Fetal bovine serum (fbs) by Thermo Fisher Scientific
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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
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Superose 6 10 300 gl column by GE Healthcare
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Dulbecco modified eagle medium (dmem) by Thermo Fisher Scientific
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Pam3csk4 by InvivoGen
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Pam3CSK4 is a synthetic triacylated lipopeptide that mimics the structure of the acylated amino terminus of bacterial lipoproteins. It acts as a potent agonist of Toll-like receptor 2 (TLR2) and can be used in cell-based assays to study TLR2-mediated cellular responses.
6
Amplex red cholesterol assay kit by Thermo Fisher Scientific
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The Amplex Red Cholesterol Assay Kit is a fluorometric assay used to measure total cholesterol levels in biological samples. The kit utilizes the Amplex Red reagent, which produces a fluorescent product upon reaction with hydrogen peroxide generated from the cholesterol oxidase-catalyzed oxidation of cholesterol.
7
Superose 6 column by Cytiva
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8
Infinity reagent by Thermo Fisher Scientific
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Infinity reagents are a line of high-quality laboratory reagents designed for use in a variety of scientific applications. These reagents are manufactured to meet the stringent quality standards of Thermo Fisher Scientific, ensuring consistent performance and reliability. The core function of Infinity reagents is to provide essential chemical compounds and solutions required for various experimental and analytical procedures in life science research and clinical laboratories.
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Mevalonate by Merck Group
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Mevalonate is a chemical compound used in laboratory settings for research and analysis purposes. It serves as a key intermediate in the biosynthesis of various molecules, including sterols, terpenes, and isoprenoids. Mevalonate plays a critical role in cellular metabolism and is essential for the proper functioning of various biological processes.
10
Lipoprotein deficient serum by Merck Group
Sourced in United States
Lipoprotein-deficient serum is a laboratory reagent used in biochemical and cell culture research. It is a type of serum that has been processed to remove lipoproteins, such as cholesterol, triglycerides, and other lipid-containing molecules. This specialized serum is used as a cell culture supplement to study the effects of lipoproteins on cellular processes and metabolism.

More about "Lipoproteins"

Lipoproteins are complex macromolecular assemblies composed of lipids and proteins that serve as crucial transporters of lipids throughout the body.
These biomolecular complexes play a pivotal role in the metabolism and distribution of cholesterol, triglycerides, and other essential lipids.
Lipoproteins are classified based on their density and composition, including chylomicrons, very low-density lipoproteins (VLDL), low-density lipoproteins (LDL), and high-density lipoproteins (HDL).
Imbalances in lipoprotein levels are associated with a variety of cardiovascular and metabolic disorders, making them a vital target for clinical research and therapeutic interventions.
Researchers and clinicians often utilize techniques such as Superose 6 column chromatography, fetal bovine serum (FBS), and the Superose 6 10/300 GL column to study and analyze these complex biomolecular structures.
Additionally, cell culture media like DMEM (Dulbecco's Modified Eagle Medium) and compounds like Pam3CSK4 (a synthetic triacylated lipopeptide) are commonly employed in lipoprotein research.
The Amplex Red Cholesterol Assay Kit and Infinity reagents are also valuable tools for measuring and quantifying cholesterol and other lipid components within lipoprotein particles.
Furthermore, the understanding of lipoprotein metabolism and regulation often involves the study of molecules like mevalonate, a key intermediate in the cholesterol biosynthesis pathway, as well as the use of lipoprotein-deficient serum to create specialized experimental conditions.
By leveraging the power of PubCompare.ai, an AI-driven platform, researchers can enhance the reproducibility and accuracy of their lipoprotein studies.
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