Project description:Analysis of COVID-19 hospitalized patients, with different kind of symptoms, by human rectal swabs collection and 16S sequencing approach.
Project description:Analysis of breast cancer survivors' gut microbiota after lifestyle intervention, during the COVID-19 lockdown, by 16S sequencing of fecal samples.
Project description:In a prior report, we observed two distinct lung microbiomes in healthy subjects that we termed â??pneumotypesâ??: pneumotypeSPT, characterized by high bacterial load and supraglottic predominant taxa (SPT) such as the anaerobes Prevotella and Veillonella; and pneumotypeBPT, with low bacterial burden and background predominant taxa (BPT) found in the saline lavage and bronchoscope. Here, we determined the prevalence of these two contrasting lung microbiome types, in a multi-center study of healthy subjects. We confirmed that a lower airway microbiome enriched with upper airway microbes (pneumotypeSPT) was present in ~45% of healthy individuals. Cross-sectional Multicenter cohort. BAL of 49 healthy subjects from three cohort had their lower airway microbiome assessed by 16S rDNA sequencing and microbial gene content (metagenome) was computationally inferred from taxonomic assignments. The amplicons from total 100 samples are barcoded; the barcode and other clinical characteristics (e.g. inflammatory biomarkers and metabolome data) for each sample are provided in the 'Pneumotype.sep.Map.A1.txt' file.
Project description:The gut microbiome plays an important role in normal immune function and has been implicated in several autoimmune disorders. Here we use high-throughput 16S rRNA sequencing to investigate the gut microbiome in subjects with multiple sclerosis (MS, n=61) and healthy controls (n=43). Alterations in the gut microbiome in MS include increases in the genera Methanobrevibacter and Akkermansia and decreases in Butyricimonas, and correlate with variations in the expression of genes involved in dendritic cell maturation, interferon signaling and NF-kB signaling pathways in circulating T cells and monocytes. Patients on disease-modifying treatment show increased abundances of the genera Prevotella and Sutterella, and decreased Sarcina, compared to untreated patients. MS patients of a second cohort show elevated breath methane compared to controls, consistent with our observation of increased gut Methanobrevibacter in MS in the first cohort. Further study is required to assess whether the observed alterations in the gut microbiome play a role in, or are a consequence of, MS pathogenesis.
Project description:Gut microbiota were assessed in 540 colonoscopy-screened adults by 16S rRNA gene sequencing of stool samples. Investigators compared gut microbiota diversity, overall composition, and normalized taxon abundance among these groups.
Project description:Hundreds of microbial species were found to be transcriptionally active in the human gut microbiome based on the expression profiling of ca. 680.000 microbial genes As a part of the MetaHIT cohort 233 human stool samples were transcriptionally profiled using a custom made microarray that included probes for most prevalent microbial genes in the cohort as established by whole-genome sequencing of the same samples
Project description:Sub-Saharan Africa represents 69% of the total number of individuals living with HIV infection worldwide and 72% of AIDS deaths globally. Pulmonary infection is a common and frequently fatal complication, though little is known regarding the lower airway microbiome composition of this population. Our objectives were to characterize the lower airway microbiome of Ugandan HIV-infected patients with pneumonia, to determine relationships with demographic, clinical, immunological, and microbiological variables and to compare the composition and predicted metagenome of these communities to a comparable cohort of patients in the US (San Francisco). Bronchoalveolar lavage samples from a cohort of 60 Ugandan HIV-infected patients with acute pneumonia were collected. Amplified 16S ribosomal RNA was profiled and aforementioned relationships examined. Ugandan airway microbiome composition and predicted metagenomic function were compared to US HIV-infected pneumonia patients. Among the most common bacterial pulmonary pathogens, Pseudomonas aeruginosa was most prevalent in the Ugandan cohort. Patients with a richer and more diverse airway microbiome exhibited lower bacterial burden, enrichment of members of the Lachnospiraceae and sulfur-reducing bacteria and reduced expression of TNF-alpha and matrix metalloproteinase-9. Compared to San Franciscan patients, Ugandan airway microbiome were significantly richer, and compositionally distinct with predicted metagenomes that encoded a multitude of distinct pathogenic pathways e.g secretion systems. Ugandan pneumonia-associated airway microbiome is compositionally and functionally distinct from those detected in comparable patients in developed countries, a feature which may contribute to adverse outcomes in this population. Please note that the data from the comparable cohort of patients in the USUS data was published as supplemental material of PMID: 22760045 but not submitted to GEO The 'patient_info.txt' contains 12 clinical, 7 immunological and 3 microbiological variables for each patient. The G2 PhyloChip microarray platform (commercially available from Second Genome, Inc.) was used to profile bacteria in lower airway samples from 60 subjects
Project description:Quantitative metaproteomics is a relatively new research field by applying proteomics technique to study microbial proteins of microbiome, and holds the great potential to truly quantify the functional proteins actually expressed by microbes in the biological environment such as gastrointestinal tract. The significant association between arsenic exposure and gut microbiome perturbations has been reported; however, metaproteomics has not yet been applied to study arsenic induced proteome changes of microbiome. Most importantly, to our knowledge, isobaric-labeling based large-scale metaproteomics has not been reported using the advanced database search approaches such as MetaPro-IQ and matched metagenome database search strategies to provide high quantification accuracy and less missing quantification values. In the present study, a new experimental workflow coupled with isobaric labeling and MetaPro-IQ was demonstrated for metaproteomics study of arsenic induced gut microbiome perturbations. The advantages of this workflow were also discussed. For all 18 fecal samples analyzed, 7,611 protein groups were quantified without any missing values. The consistent results of expression profiles were observed between 16S rRNA gene sequencing and metaproteomics. This isobaric labeling based workflow demonstrated the significant improvement of quantitative metaproteomics for gut microbiome study.