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Hemophilus

Hemophilius: A genus of gram-negative, rod-shaped bacteria found in the upper respiratory tract of humans and animals.
These bacteria can cause serious infections like pneumonia, meningitis, and septicemia, particularly in young children.
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Most cited protocols related to «Hemophilus»

1
Benchmarking Bacterial Genome Polishing Methods
The six bacterial isolates used in the real-read tests each belong to a different species: Acinetobacter baumannii, Citrobacter koseri, Enterobacter kobei, an unnamed Haemophilus species (given the placeholder name Haemophilus sp002998595 in GTDB R202 [28 , 29 ]), Klebsiella oxytoca and Klebsiella variicola. Sequencing was previously described in Wick et al. (2021) [19 ]. Briefly, isolates were cultured overnight at 37°C in Luria-Bertani broth and DNA was extracted using GenFind v3 according to the manufacturer’s instructions (Beckman Coulter). The same DNA extract was used to sequence each isolate using three different approaches: ONT ligation, ONT rapid and Illumina (S11(A) Fig). For ONT ligation, we followed the protocol for the SQK-LSK109 ligation sequencing kit and EXP-NBD104 native barcoding expansion (Oxford Nanopore Technologies). For ONT rapid, we followed the protocol for the SQK-RBK004 rapid barcoding kit (Oxford Nanopore Technologies). All ONT libraries were sequenced on MinION R9.4.1 flow cells. ONT read sets were basecalled and demultiplexed with Guppy v5.0.7, using the super-accuracy model. For Illumina, we followed a modified Illumina DNA Prep protocol (catalogue number 20018705), whereby the reaction volumes were quartered to conserve reagents. Illumina libraries were sequenced on the NovaSeq 6000 using SP reagent kits v1.0 (300 cycles, Illumina Inc.), producing 150 bp paired-end reads with a mean insert size of 331 bp. The resulting Illumina read pairs were shuffled and evenly split into two separate read sets, which were combined with the ONT read sets to produce two independent hybrid read sets (S11(B) Fig). We repeated this process (from culture to sequencing) to generate another two hybrid read sets for a total of four hybrid read sets per isolate. All reads are available in the manuscript’s data repository (bridges.monash.edu/articles/dataset/Polypolish_paper_dataset/16727680).
For each hybrid read set, we performed a long-read-only assembly using Trycycler v0.5.0 [3 ] and Medaka v1.4.3 [8 ], following the instructions in Trycycler’s documentation (S11(C) Fig and S6 Table). One of the ONT read sets for K. oxytoca MSB1_2C had very low depth (10×) and was therefore not able to yield a high-quality long-read-only assembly, leaving only three assemblies for this genome. We were able to produce four complete (circularised) long-read-only assemblies for the other five genomes, giving a total of 23 assemblies which served as the ‘unpolished’ assemblies in our real-read tests.
Polished genome sequences were generated by running the short-read polishers as described above (S11(D) Fig). For the single-tool tests, each polisher was run consecutively three times on each assembly. For the greedy combination tests, each polisher (excluding the hybrid polishers and wtpoa which performed poorly in the single-tool tests) was run once on each genome, and the best-performing polisher was defined as the one with the smallest total pairwise distance in its output assemblies. The best-performing polisher’s output was then used as input for another round of polishing until there were no more improvements. The greedy combination tests were then performed again with Polypolish excluded.
To assess the quality of real-read assemblies, we used the edlib [26 ] library to perform a global alignment of the chromosome sequences for all pairwise combinations within each genome (S11(E) Fig). The total distance was used as a metric of assembly quality, with lower values being better and a value of zero indicating that all assemblies for the genome were identical. We also ran ALE [18 ] on each real-read assembly using short-read alignments from BWA-MEM [16 ].
Wick R.R, & Holt K.E. (2022). Polypolish: Short-read polishing of long-read bacterial genome assemblies. PLoS Computational Biology, 18(1), e1009802.
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Publication 2022
Acinetobacter calcoaceticus Bacteria Cells Chromosomes Citrobacter koseri DNA Library Enterobacter kobei Genome Hemophilus Hybrids Klebsiella oxytoca Klebsiella variicola Lebistes Ligation Oryziinae
2
COPD Acute Exacerbation and Quality of Life Study
The primary outcome was the time to the first acute exacerbation of COPD, with acute exacerbation of COPD defined as “a complex of respiratory symptoms (increased or new onset) of more than one of the following: cough, sputum, wheezing, dyspnea, or chest tightness with a duration of at least 3 days requiring treatment with antibiotics or systemic steroids.”19 (link) At each clinic visit and telephone contact, study personnel determined whether an acute exacerbation of COPD had occurred in the previous month. The date of each acute exacerbation was taken as the date treatment was prescribed.
Secondary outcomes included quality of life, nasopharyngeal colonization with selected respiratory pathogens (i.e., Staphylococcus aureus, Streptococcus pneumoniae, haemophilus species, and moraxella species), and adherence to taking the study drug as prescribed. The St. George’s Respiratory Questionnaire (SGRQ, in which scores range from 0 to 100, with lower scores indicating better functioning) and the Medical Outcomes Study 36-Item 691 Short-Form Health Survey (SF-36) were administered at the time of enrollment and at study months 6 and 12. The minimal clinically important difference in the SGRQ score was considered to be −4 units, and the percentage of patients with a change of at least 4 units from the time of enrollment was a prespecified end point.34 (link) Deep nasopharyngeal swabs were obtained at the time of enrollment and every 3 months thereafter, and selected respiratory pathogens were assessed for resistance to macrolides. Adherence to the study drug was assessed at each clinic visit by means of pill counts performed by the staff. Hearing was assessed by means of audiometry at the time of enrollment and at 3 and 12 months, or whenever a patient reported worsening hearing or tinnitus.
Albert R.K., Connett J., Bailey W.C., Casaburi R., Cooper JA J.r., Criner G.J., Curtis J.L., Dransfield M.T., Han M.K., Lazarus S.C., Make B., Marchetti N., Martinez F.J., Madinger N.E., McEvoy C., Niewoehner D.E., Porsasz J., Price C.S., Reilly J., Scanlon P.D., Sciurba F.C., Scharf S.M., Washko G.R., Woodruff P.G, & Anthonisen N.R. (2011). Azithromycin for Prevention of Exacerbations of COPD. The New England journal of medicine, 365(8), 689-698.
Publication 2011
Antibiotics Audiometry Chest Chronic Obstructive Airway Disease Clinic Visits Contraceptives, Oral Cough Dyspnea Hemophilus Macrolides Moraxella Nasopharynx pathogenesis Patients Respiratory Rate Signs and Symptoms, Respiratory Sputum Staphylococcus aureus Steroids Streptococcus pneumoniae Tinnitus
3
Analyzing Airway Microbiome in Cystic Fibrosis
DNA was prepared from frozen sputum and bacterial 16S ribosomal subunit (16S rRNA) genes were sequenced as part of a study we described previously [5 (link),8 (link)]. Details are available in [5 (link),8 (link)] and in the supporting information section [S1 Methods]. Original sff files with metadata are deposited in NCBI Sequence Read Archive (NCBI BioProject ID PRJNA423040).
For sequence analysis of the 631 samples included in the present study, the mothur (v.1.29) software package was used following the standard operating procedures (https://www.mothur.org/wiki/454_SOP). The total number of reads for each sample was rarefied (an average of 1000 subsampling iterations, rounded to the nearest whole number) to 547, the smallest number of reads obtained in the sample set, to control for differences in sequencing depth before alpha diversity measures were calculated. The dominant genus was defined as the most abundant genus observed in the sample. Prevalence was calculated as the number of samples with nonzero relative abundance divided by the total sample size. Non-parametric Shannon dissimilarity (Shannon diversity) was used to describe community richness and evenness [12 ].
OTUs representing Pseudomonas, Achromobacter, Burkholderia, Haemophilus, Staphylococcus, and Stenotrophomonas were categorized as “typical CF pathogens.” OTUs representing the obligate anaerobic genera Actinomyces, Fusobacterium, Porphyromonas, Prevotella, and Veillonella, and the facultative anaerobic genera Gemella, Granulicatella, Rothia, and Streptococcus were collectively referred to as “anaerobic genera.” Each of these nine anaerobic genera accounted for at least 1% mean relative abundance when present. Collectively, the six typical CF pathogen genera and nine anaerobic genera represented 94.3% of all sequencing reads (60.7% of reads represented typical CF pathogens; 33.6% represented anaerobic genera); the remaining 5.7% of DNA sequencing reads represented other genera.
To accommodate the longitudinal design of this study (89 subjects contributed more than one sample), generalized estimating equations (GEE) were used, with a gamma probability distribution, log link function, and unstructured working correlation matrix. Alpha was set at 0.05 (2-tailed) and analyses were conducted in SPSS (v24).
Carmody L.A., Caverly L.J., Foster B.K., Rogers M.A., Kalikin L.M., Simon R.H., VanDevanter D.R, & LiPuma J.J. (2018). Fluctuations in airway bacterial communities associated with clinical states and disease stages in cystic fibrosis. PLoS ONE, 13(3), e0194060.
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Publication 2018
Achromobacter Actinomyces Bacteria Burkholderia Freezing Fusobacterium Gamma Rays Gemella Genes Hemophilus Pathogenicity Porphyromonas Prevotella Pseudomonas Ribosome Subunits RNA, Ribosomal, 16S Sputum Staphylococcus Stenotrophomonas Streptococcus Veillonella
4
Seasonal Nasopharyngeal Carriage Prevalence
We did a cross-sectional survey of nasopharyngeal carriage prevalence among healthy subjects of all ages during the dry season and repeated it three months later in the rainy season in the same individuals. The sampling frame for the study was the population register of the Kilifi Demographic Surveillance System (DSS). The DSS began in 2000 with a population census of all households within a predefined area of 891 km2 surrounding Kilifi District Hospital. Vital status was subsequently updated in the population register by questionnaires administered at household visits conducted approximately twice a year. In 2005 Kilifi DSS was admitted to the INDEPTH network (www.indepth-network.net) a network of DSS sites with common data reporting standards. In January 2003 the population register numbered 220 000 individuals and we used this register to generate lists of randomly selected individuals within 64 age-sex-location strata aiming to recruit 480 individuals, 7-8 from each stratum. The strata were composites of two sexes, 4 locations and 8 age groups (<1, 1-2, 3-4, 5-9, 10-19, 20-39, 40-49, ≥50 years.) For logistic reasons we restricted selection to two semi-urban locations from township settings (Kilifi, Roka) and two rural locations (Marere, Pinglikani). In Kilifi District Hib vaccine was introduced into the routine childhood immunization program in 2001. At 12 months of age 87% of children have received three doses of the vaccine [14 (link)]. Pneumococcal carriage prevalence is higher among HIV-infected than HIV-uninfected individuals [15 (link)], however, we chose not to test study subjects for HIV status because the prevalence of HIV in Coastal Kenya is low at 4.8% in men and 6.6% in women [16 ].
In Kilifi there is a long rainy season in May-July and a short rainy season in October-November. The climate between January and March is very dry. To select dates for our rainy and dry season surveys we aggregated daily rainfall data from a meteorologic recording station at Kilifi Agricultural Research Institute in Kilifi town into weekly rainfall means for the preceding 10 years, 1994-2003. The dates of sampling selected were 2-24 March 2004 and 2 June-3 July 2004. The survey in the rainy season took longer to conduct because the rains impeded transport throughout the study area.
A nasopharyngeal specimen was collected from each consenting individual by trained field workers according to the WHO guidelines [17 (link)]. A rayon-tipped flexible aluminium-shaft (Medical Wire and Equipment Company, Town, UK) was passed via the anterior nares to the posterior nasopharynx to a depth predefined by the external distance from the tip of the nose to the external auditory canal. It was left in place for approximately 2 seconds and rotated through 180 degrees before removal. Swabs were immediately placed in STGG transport medium and transported to the laboratory within 8 hours. Putative risk factors for nasopharyngeal colonization, including cigarette smoking, coryza in the last two weeks, use of antibiotics or folate synthesis inhibitors (sulfadoxine/pyrimethamine or sulfamethoxazole/trimethoprim) in the preceding two weeks and number of children aged <5 years resident in the house, were ascertained by questionnaire at the same time. Those who had taken medications were asked to remember the name, describe the package and, if possible, produce the package for verification.
STGG swab specimens were processed at the Wellcome Trust/Kenya Medical Research Institute microbiology laboratories according to the WHO guidelines [17 (link)] either immediately (fresh) or after a period of freezing at -80°C for up to two months. Fresh or thoroughly thawed specimens were vortexed for 10 seconds and 10μl was inoculated directly onto 7% horse blood agar with gentamicin 2.5 μg/ml and 7% chocolate agar. Media were incubated overnight at 37°C in 5% CO2. S. pneumoniae was identified by colony morphology, α-haemolysis, optochin susceptibility, bile solubility and serotyping. Four morphologically distinct colonies were sub-cultured for typing from each primary plate. Pneumococci were serogrouped by latex agglutination and serotyped by the Quellung reaction using polyclonal rabbit antisera (Statens Serum Institute, Copenhagen, Denmark). Haemophilus species were identified by growth on chocolate agar alone, colony morphology, X and V factor dependency and serotype. Swabs from children aged <5 years were also cultured on media containing Hib antiserum to increase the sensitivity of detection of Hib carriage by identification of precipitation haloes [18 (link)]. Serotype results for H. influenzae isolates were confirmed in England by polymerase chain reaction-based capsular genotyping using primers designed to amplify the type-specific regions of the cap loci in each of the 6 (a-f) capsular types [Falla 1994]. [19 ]
STATA (version 8.2) was used for statistical analyses. The prevalence of nasopharyngeal carriage of S. pneumoniae and H. influenzae was presented as proportions of individuals in different age, sex and location strata. The effect of season on carriage was calculated as a matched odds ratio and tested with McNemar’s χ2 tests. Logistic regression was used to analyze risk factors for carriage entering subject identity as a random effect to take account of the correlation of response variables from the same individual in the two surveys. The contribution of each variable to the model was determined by Likelihood Ratio Tests and only those with a p value <0.05 were retained in the final model except for age, in 8 strata, which was retained as an a priori confounder.
The study was approved by the Kenya Medical Research Institute/National Ethical Review Committee and The Oxford Tropical Research Ethics Committee and written informed consent was obtained for all participants.
Abdullahi O., Nyiro J., Lewa P., Slack M, & Scott J.A. (2008). The descriptive epidemiology of Streptococcus pneumoniae and Haemophilus influenzae nasopharyngeal carriage in children and adults in Kilifi District, Kenya. The Pediatric infectious disease journal, 27(1), 59-64.
Publication 2008
Agar Age Groups Aluminum Anabolism Antibiotics Bile BLOOD Cacao Capsule Child Climate Common Cold Culture Media Equus caballus Ethical Review Ethics Committees, Research External Auditory Canals Folic Acid Antagonists Gentamicin Haemophilus influenzae Haemophilus influenzae type b polysaccharide vaccine Healthy Volunteers Hemolysis Hemophilus Households Hypersensitivity Immune Sera Immunization Programs Latex Fixation Tests Nasopharynx Neoplasm Metastasis Nose Oligonucleotide Primers Optoquine Pharmaceutical Preparations Polymerase Chain Reaction Pulmonal S Rabbits Rain rayon Reading Frames Serum Streptococcus pneumoniae sulphadoxine-pyrimethamine Susceptibility, Disease Trimethoprim-Sulfamethoxazole Combination Vaccine, Pneumococcal Polysaccharide Vaccines Woman Workers
5
Quantifying Bacterial 16S rDNA by Real-time PCR
Quantification of bacterial 16S rDNA was performed by real-time PCR utilizing TaqMan hydrolysis probes on a Roche 480 LightCycler. Degenerate bacterial 16S rDNA specific primers were targeted to the V1-V2 regions of the 16S rDNA gene using the following sequences: 5′-AGAGTTTGATCCTGGCTCAG-3′ (forward); 5′-CTGCTGCCTYCCGTA-3′ (reverse); (5′-FAM-TA+ACA+CATG+CA+AGTC+GA- BHQ1-3′ (probe). [20] (link)–[22] (link). The probe was developed for the primer BSR65/17 landing site using the following sequence: 5′-TCGACTTGCATGTRTTA-3′. 16S clones derived from a Haemophilus species were used for generation of a standard curve. After an initial denaturation of five minutes at 95°C, 40 cycles of amplification were performed: 30 seconds at 94°C, 30 seconds at 50°C and 30 seconds at 72°C. A final elongation step was performed at 72°C.
Dickson R.P., Erb-Downward J.R., Freeman C.M., Walker N., Scales B.S., Beck J.M., Martinez F.J., Curtis J.L., Lama V.N, & Huffnagle G.B. (2014). Changes in the Lung Microbiome following Lung Transplantation Include the Emergence of Two Distinct Pseudomonas Species with Distinct Clinical Associations. PLoS ONE, 9(5), e97214.
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Publication 2014
Bacteria Clone Cells DNA, Ribosomal Genes Hemophilus Hydrolysis N-(4-azidobenzoylglycyl)-S-(2-thiopyridyl)cysteine Neoplasm Metastasis Oligonucleotide Primers Real-Time Polymerase Chain Reaction tetrahydroaldosterone 3 beta-glucosiduronic acid

Most recents protocols related to «Hemophilus»

1
Microbial Identification and Drug Susceptibility
The sputum and sterile samples were placed on chocolate, blood, and MacConkey agar plates and incubated in the culture media, in a 5% CO2 at 35°C for 48–72 hours, depending on the specimens. The growth of the medium was manually checked daily. Blood samples were inoculated into blood culture bottles and were incubated in the BD BACTEC FX system (Becton, Dickinson, and Company) at 37°C for 5 days. MicroScan WalkAway 40 automatic microbial identification instrument and drug susceptibility system (Beckman Coulter, Brea, California, USA) were used for simultaneous strain identification and drug susceptibility testing via negative Combo Panel Type 61 and positive Combo Panel Type 11. A microdilution method was used to evaluate the drug sensitivity and establish the minimum inhibitory concentration (MIC). This method uses a small volume of broth to disperse into a round or pointed bottom sterile plastic micro-dilution plate, called micro-dilution. Each hole should contain 0.1mL broth. The bacterial solution was diluted to 0.5 mc, before diluting 1000 times. After sealing, the bacterial solution was placed into a 35 °C ordinary air incubator and incubated for 16~20h, before reading the results. Haemophilus and Streptococcus were detected via incubation for 20–24 hours. Drug sensitivity of Staphylococcus and Enterococcus to oxacillin and vancomycin was evaluated by incubation for 24 hours. The MIC is the minimum drug concentration that can completely suppress bacterial growth in the small hole. It is only meaningful when the bacterial growth test is significant in the positive control hole (without antimicrobial). The maximum drug concentration that inhibits bacterial growth should be recorded when a single hole jumping occurs. The outcomes should not be reported and the test should be repeated in case of multiple hole jumps. The positive and negative drug-sensitive composite plates contain 16 and 20 antibacterial drugs respectively (Reach Surgical (Beijing), Inc.). Results were reported consistent with the Clinical Laboratory Standards Institute Criteria (CLSI) 2021.16 (link)
Wei X.L., Zeng Q.L., Xie M, & Bao Y. (2023). Pathogen Distribution, Drug Resistance Risk Factors, and Construction of Risk Prediction Model for Drug-Resistant Bacterial Infection in Hospitalized Patients at the Respiratory Department During the COVID-19 Pandemic. Infection and Drug Resistance, 16, 1107-1121.
Publication 2023
Agar Anti-Bacterial Agents Bacteria BLOOD Blood Culture Cacao Cardiac Arrest Clinical Laboratory Services Culture Media Enterococcus Hemophilus Hypersensitivity Microbicides Minimum Inhibitory Concentration Operative Surgical Procedures Oxacillin Pharmaceutical Preparations Sputum Staphylococcus Sterility, Reproductive Strains Streptococcus Susceptibility, Disease Technique, Dilution Vancomycin
2
Profiling Microbial and Host Transcripts in Infant Saliva
RNA was extracted from each sample using the miRNeasy Kit (Qiagen, Inc., Germantown, MD, USA), and RNA quality was assessed with an Agilent Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA). Downstream RNA processing was performed as we have previously described [50 (link)]. Briefly, RNA sequencing was completed at the SUNY Molecular Analysis Core using the Illumina TruSeq Small RNA Prep protocol and a NextSeq500 instrument (Illumina; San Diego, CA, USA) at a targeted depth of ten million, 50 base, paired-end reads per sample. Reads were aligned to the hg38 build of the human genome using Partek Flow (Partek; St. Louis, MO, USA) and the Bowtie2 aligner. Quantification of messenger RNAs (mRNAs) was performed using Ensembl annotation, and quantification of mature microRNAs was performed using miRBase 22 annotation. RNA reads that were unaligned to the human genome were aligned to the NCBI RefSeq genome using Kraken. Bacteria were aligned at the phylum level and viral phages were aligned at the species level. We chose to measure microbial RNA in order to streamline the nucleic acid extraction and analyses steps. Quality of RNA sequencing results was verified through read quality score and total read count. The RNA features with consistent detection (raw read counts ≥10 in ≥100% of samples) in each category (mRNAs, miRNAs, bacteria, virus) were quantile normalized and scaled prior to statistical analysis. Downstream analysis involved 8 transcripts (TMPRSS2, IL1RN, IL6ST, CCL2, TNFAIP3, TLR4, TAB2, NFKBIA), 8 miRNAs (miR-140-3p, miR-22-5p, miR-29c-5p, miR-34c-5p, miR-125a-5p, miR-27b-3p, miR-203a-3p, miR-155-5p), 8 viral phages (Streptococcus phage SpSL1, Pseudomonas phage PPpW-3, Proteus virus PM135, Streptococcus phage phiARI0131-1, Mycobacterium virus Cooper, Bacillus virus Mater, Haemophilus virus HP1, Klebsiella phage vB_KpV477), and 8 microbial phyla (Actinobacteria, Bacteroidetes, Candidatus Saccharibacteria, Firmicutes, Fusobacteria, Proteobacteria, Verrucomicrobia), plus a measure of microbial diversity (Simpson alpha index). These features were selected based on their biologic relevance to viral upper respiratory infections and their abundance in infant saliva [25 (link),26 (link),51 (link),52 (link),53 (link),54 (link)]. A maximum of 8 features were permitted in each category based on an a priori power analysis demonstrating that the sample size (n = 146) provided > 95% power to detect an effect size ≥ 2.0 for 8 predictors, with alpha set at 0.05 (assuming a non-central distribution).
Beheshti R., Halstead E.S., Cusack B, & Hicks S.D. (2023). Multi-Omic Factors Associated with Frequency of Upper Respiratory Infections in Developing Infants. International Journal of Molecular Sciences, 24(2), 934.
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Publication 2023
Actinomycetes Bacillus Bacteria Bacteriophages Bacteroidetes Biopharmaceuticals CCL2 protein, human Common Cold Firmicutes Fusobacterium Genome Genome, Human Hemophilus IL1RN protein, human IL6ST protein, human Infant Klebsiella MicroRNAs Mothers Mycobacterium NFKBIA protein, human Nucleic Acids Proteobacteria Proteus Pseudomonas Phages RNA, Messenger Saliva Streptococcus Phages TMPRSS2 protein, human TNFAIP3 protein, human Verrucomicrobia Virus
3
Gut Microbiota Analysis of Postprandial Glycemic Response
During pre- and post-intervention study days, participants were asked to collect fecal samples using a stool sampling collection kit. Samples were taken using an EasySampler Stool Collector and a sample tube with a spoon lid. The sample was protected by being placed in yet another tube and stored immediately in the freezer (−20 °C). The samples were transported in a cooling box with an ice pack to the clinic within 72 h after the sample was collected. At the clinic, the sample is transferred to −80 °C within 24 h. The samples were analyzed with the 16S rRNA gene amplicon sequencing method, where DNA was extracted and purified from fecal samples using the QIAamp FAST DNA Stool mini kit from Qiagen, Venlo, The Netherlands. The DNA extraction followed the protocol from the manufacturer with one exception, where lysis of the bacterial cell walls used a mechanical lysis step (bead beating 2 × 1 min in a Precellys Evolution using 0.1 mm zirconium/silica beads). Once the DNA was extracted and purified from the sample, polymerase chain reaction (PCR) was used to amplify the V3-V4 region of the gene encoding 16S rRNA. This gene exists in all bacteria and is normally used for the taxonomic classification of bacteria since parts of the 16S gene vary in sequence composition between different bacteria. Sample-specific barcodes and Illumina adapters were then attached to the PCR amplicons to enable the pooling of samples. The library of PCR amplicons was then sequenced on the Illumina NovaSeq 6000 platform at Novogene, Singapore. The bioinformatics analysis to handle the generated sequence data used QIIME2 via the dada2 pipeline. The sequences were first demultiplexed, i.e., separated according to the sample-specific barcode in the specific sample. Then, quality control and filtration of the sequence data was performed to remove sequences with poor quality. Finally, a taxonomic classification of the sequences was performed. The gut microbiota analysis and subsequent data processing and analysis were described in detail by Iversen and Dicksved [15 (link)]. The gut microbiota was analyzed to investigate if it could explain inter-individual differences in glycemic postprandial response and provide some mechanistic insights into potential differential response profiles between subjects. The microbiota was aggregated to the genus level prior to downstream analysis.
Species that were known from the literature to associate with glucose regulation were selected to assess association with response clusters. The selected species were “Bifidobacterium”, “Bacteroides”, “Faecalibacterium”, “Akkermansia”, “Roseburia”, “Fusobacterium”, “Blautia”, “Haemophilus”, “Ruminococcus”, “Clostridium”, and “Dorea” [16 (link),17 (link),18 (link),19 (link),20 (link),21 (link),22 (link)].
Skantze V., Hjorth T., Wallman M., Brunius C., Dicksved J., Pelve E.A., Esberg A., Vitale M., Giacco R., Costabile G., Bergia R.E., Jirstrand M., Campbell W.W., Riccardi G, & Landberg R. (2023). Differential Responders to a Mixed Meal Tolerance Test Associated with Type 2 Diabetes Risk Factors and Gut Microbiota—Data from the MEDGI-Carb Randomized Controlled Trial. Nutrients, 15(20), 4369.
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Publication 2023
Akkermansia Bacteria Bacteroides Bifidobacterium Biological Evolution Cell Wall Clostridium DNA Library Faecalibacterium Feces Filtration Fusobacterium Gastrointestinal Microbiome Genes Glucose Hemophilus Microbial Community Polymerase Chain Reaction Ribosomal RNA Genes RNA, Ribosomal, 16S Ruminococcus Silicon Dioxide Specimen Collection Zirconium
4
Infective Endocarditis Etiology and Treatment
All patients admitted for the first episode of IE between 1 January 2010 and 31 December 2020 were identified using the following ICD-8/10 diagnosis codes for infective endocarditis: 421 (ICD-8), DI33.0, DI38.0, and DI39.8. To increase the accuracy of the IE diagnosis, only patients who were hospitalized for >14 days or died within the first 14 days of admission were included, as descried previously, with a positive predictive value of 90% in the Danish National Patient Registry [22 (link),23 (link)]. The study population was stratified according to treatment choice: (i) patients who underwent surgery during the initial admission (procedure codes are available in Supplementary Table S1) and (ii) patients who received medical therapy only. The microbiological etiology was identified as a positive blood culture collected within 30 days of the index date and until the discharge date of IE. We ranked the possible microbiological etiologies to identify the most likely primary microorganisms causing IE: (1) S. aureus, Streptococcus spp., HACEK (Haemophilus (not including Haemophilus influenzae), Aggregatibacter, Cardiobacterium, Eikenella, and Kingella), and Enterococcus spp.; (2) coagulase-negative Staphylococci (CoNS); (3) “other microbiological etiologies”; and (4) negative blood cultures. Subsequently, patients were categorized according to the following groups of microorganisms: (1) S. aureus, (2) Streptococcus spp., (3) Enterococcus spp., (4) CoNS, (5) “other microbiological etiologies” (including HACEK and fungi) referred to as “other IE”, and (6) blood-culture-negative IE, referred to as “Negative IE”. The specific bacteria assessed in the parent groups of microbiological etiologies are shown in Supplementary Table S2a–c. Patients without available blood cultures within 30 days of the index date were excluded (Figure 1).
Graversen P.L., Østergaard L., Voldstedlund M., Wandall-Holm M.F., Smerup M.H., Køber L, & Fosbøl E.L. (2023). Microbiological Etiology in Patients with IE Undergoing Surgery and for Patients with Medical Treatment Only: A Nationwide Study from 2010 to 2020. Microorganisms, 11(10), 2403.
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Publication 2023
Aggregatibacter Bacteria Blood Culture Cardiobacterium Coagulase Diagnosis Eikenella Enterococcus Fungi Haemophilus influenzae Hemophilus Infective Endocarditis Kingella Operative Surgical Procedures Parent Patient Discharge Patients Selection for Treatment Staphylococcus Staphylococcus aureus Streptococcus Therapeutics
5
Sputum Collection for Pneumonia Diagnosis
On the day of hospitalization, samples were collected using a sterile suction tube attached to a special suction device at one end and the other end inserted into the child’s nasal cavity, from the nasopharynx into the airway, using negative pressure suction to draw sputum out of the respiratory tract. Sputum would be sent to the examination room for screening and pre-treatment before inoculation for culture. The bacterial species mainly linked to community-acquired pneumonia in clinical practice were selected as the target bacterial species, which included Streptococcus pneumoniae, Staphylococcus aureus, Escherichia coli, Haemophilus infuenzae, Pseudomonas aeruginosa, Klebsiella sp, Acinetobacter sp, etc.
Tang M., Dong W., Yuan S., Chen J., Lin J., Wu J., Zhang J., Yin Y, & Zhang L. (2023). Comparison of respiratory pathogens in children with community-acquired pneumonia before and during the COVID-19 pandemic. BMC Pediatrics, 23, 535.
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Publication 2023
Acinetobacter Bacteria Child Escherichia coli Hemophilus Hospitalization Klebsiella Medical Devices Nasal Cavity Nasopharynx Pneumonia Pressure Pseudomonas aeruginosa Respiratory System Sputum Staphylococcus aureus Sterility, Reproductive Streptococcus pneumoniae Suction Drainage Vaccination

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Trizma base by Merck Group
Sourced in United States, Germany, Spain, Italy, France, Switzerland, United Kingdom, Sao Tome and Principe, Japan, India, Czechia, China, Ireland, Poland
Trizma base is a buffer compound used in various laboratory applications. It is a stable, water-soluble chemical that can be used to maintain a consistent pH in aqueous solutions. Trizma base is commonly employed in biochemical and molecular biology experiments to create buffer systems with a desired pH range.
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C25 incubator shaker by Eppendorf
Sourced in United States
The Eppendorf C25 Incubator Shaker is a laboratory instrument designed for the incubation and agitation of samples. It provides controlled temperature and shaking conditions to facilitate the growth and cultivation of microbial cultures or other biological samples.
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Polyvitex plates by bioMérieux
Sourced in France, Spain
PolyViteX plates are a type of microbiological culture medium used for the isolation and enumeration of microorganisms. The plates are designed to support the growth of a wide range of bacterial and fungal species. They provide a standardized and consistent platform for microbial cultivation and analysis.
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Lightcycler 480 by Roche
Sourced in Switzerland, Germany, United States, China, Japan, United Kingdom, France, Belgium, Canada, Australia, Sweden, Austria, Denmark, Italy, Norway, Estonia, Spain, Morocco, New Zealand, Netherlands, Czechia
The LightCycler 480 is a real-time PCR instrument designed for quantitative nucleic acid analysis. It features a 96-well format and uses high-performance optics and detection technology to provide accurate and reliable results. The core function of the LightCycler 480 is to facilitate real-time PCR experiments through thermal cycling, fluorescence detection, and data analysis.
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Haemophilus test medium supplement by Thermo Fisher Scientific
Sourced in Poland, Canada, United Kingdom
Haemophilus test medium supplement is a culture medium used for the isolation and identification of Haemophilus species. It provides the necessary growth factors and nutrients required for the cultivation of these bacteria.
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Haemophilus test media by Thermo Fisher Scientific
Sourced in United Kingdom
Haemophilus test media is a type of culture medium used for the growth and identification of Haemophilus species bacteria in a laboratory setting. It provides the necessary nutrients and growth factors required for the cultivation of these microorganisms.

More about "Hemophilus"

Hemophilus, also known as Haemophilus, is a genus of gram-negative, rod-shaped bacteria commonly found in the upper respiratory tract of humans and animals.
These bacteria are responsible for causing serious infections like pneumonia, meningitis, and septicemia, particularly in young children.
To study Hemophilus effectively, researchers can leverage the advanced AI-driven protocols offered by PubCompare.ai.
These protocols enable researchers to identify the most reproducible and accurate findings from scientific literature, preprints, and patents, helping them optimize their Hemophilus research.
When conducting Hemophilus studies, researchers may utilize various techniques and tools, such as: - Ampicillin: An antibiotic commonly used to treat Hemophilus infections. - Chocolate agar: A specialized growth medium that supports the cultivation of Hemophilus species. - MALDI Biotyper 3.0 software: A tool used for the rapid identification of Hemophilus isolates using MALDI-TOF MS technology. - MALDI-TOF MS: Mass spectrometry technique that can be used to identify Hemophilus species. - Trizma base: A buffer solution used in the cultivation and analysis of Hemophilus bacteria. - C25 Incubator Shaker: An instrument that provides controlled temperature and agitation for Hemophilus cultures. - PolyViteX plates: A specialized growth medium that supports the growth of Hemophilus species. - LightCycler 480: A real-time PCR instrument that can be used to detect and quantify Hemophilus DNA. - Haemophilus test medium supplement: A nutrient supplement that enhances the growth of Hemophilus bacteria. - Haemophilus test media: Specialized growth media designed for the cultivation and identification of Hemophilus species.
By leveraging the insights and tools available for Hemophilus research, researchers can take their studies to the next level and contribute to the understanding and management of these important bacterial pathogens.