Variation and transmission of the human gut microbiota across generations - 16S data
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PROVIDER: EGAC00001002344 | EGA |
REPOSITORIES: EGA
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Project description:Data Access Committee EGAC00001002355
| EGAC00001002355 | EGA
Project description:Although composition and functional potential of the human gut microbiota evolve over lifespan, kinship has been identified as a key covariate of microbial community diversification. To date, sharing of microbiota features within families has however mostly been assessed between parents and their direct offspring. Here, we investigate potential transmission and persistence of familial microbiome patterns and microbial genotypes in a family cohort (N=102) spanning three to five generations over the same female bloodline. We observe microbiome community composition to be associated with kinship, with seven (low-abundant) genera displaying familial distribution patterns. While kinship and current cohabitation emerged as closely entangled variables, our explorative analyses of microbial genotype distribution and transmission estimates point at the latter as a key covariate of strain dissemination. Highest potential transmission rates are estimated between sisters and mother-daughter pairs, decreasing with increasing daughter’s age, and being higher among cohabiting pairs than those living apart. Although rare, we do detect potential transmission events spanning three and four generations, primarily involving species of the genera Alistipes and Bacteroides. Overall, while our analyses confirm the existence of family-bound microbiome community profiles, transmission or co-acquisition of bacterial strains appears to be strongly linked to cohabitation.
| EGAS00001005651 | EGA
Project description:Although the composition and functional potential of the human gut microbiota evolve over the lifespan, kinship has been identified as a key covariate of microbial community diversification. However, to date, sharing of microbiota features within families has mostly been assessed between parents and their direct offspring. Here we investigate the potential transmission and persistence of familial microbiome patterns and microbial genotypes in a family cohort (n = 102) spanning 3 to 5 generations over the same female bloodline. We observe microbiome community composition associated with kinship, with seven low abundant genera displaying familial distribution patterns. While kinship and current cohabitation emerge as closely entangled variables, our explorative analyses of microbial genotype distribution and transmission estimates point at the latter as a key covariate of strain dissemination. Highest potential transmission rates are estimated between sisters and mother-daughter pairs, decreasing with increasing daughter's age and being higher among cohabiting pairs than those living apart. Although rare, we detect potential transmission events spanning three and four generations, primarily involving species of the genera Alistipes and Bacteroides. Overall, while our analyses confirm the existence of family-bound microbiome community profiles, transmission or co-acquisition of bacterial strains appears to be strongly linked to cohabitation.
| S-EPMC8727295 | biostudies-literature
Project description:Although composition and functional potential of the human gut microbiota evolve over lifespan, kinship has been identified as a key covariate of microbial community diversification. To date, sharing of microbiota features within families has however mostly been assessed between parents and their direct offspring. Here, we investigate potential transmission and persistence of familial microbiome patterns and microbial genotypes in a family cohort (N=102) spanning three to five generations over the same female bloodline. We observe microbiome community composition to be associated with kinship, with seven (low-abundant) genera displaying familial distribution patterns. While kinship and current cohabitation emerged as closely entangled variables, our explorative analyses of microbial genotype distribution and transmission estimates point at the latter as a key covariate of strain dissemination. Highest potential transmission rates are estimated between sisters and mother-daughter pairs, decreasing with increasing daughter’s age, and being higher among cohabiting pairs than those living apart. Although rare, we do detect potential transmission events spanning three and four generations, primarily involving species of the genera Alistipes and Bacteroides. Overall, while our analyses confirm the existence of family-bound microbiome community profiles, transmission or co-acquisition of bacterial strains appears to be strongly linked to cohabitation.
| EGAS00001005649 | EGA
Project description:To explore the effects of gut microbiota of young (8 weeks) or old mice (18～20 months) on stroke, feces of young (Y1-Y9) and old mice (O6-O16) were collected and analyzed by 16s rRNA sequencing. Then stroke model was established on young mouse receive feces from old mouse (DOT1-15) and young mouse receive feces from young mouse (DYT1-15). 16s rRNA sequencing were also performed for those young mice received feces from young and old mice.
2021-10-15 | E-MTAB-10837 | biostudies-arrayexpress
Project description:Tamoxifen is the most prescribed drug used to prevent breast cancer recurrence, but patients show variable responses to tamoxifen. Such differential inter-individual response has a significant socioeconomic impact as one in eight women will develop breast cancer and nearly half a million people in the United States are treated with tamoxifen annually. Tamoxifen is orally delivered and must be activated by metabolizing enzymes in the liver; however, clinical studies show that neither genotype nor hepatic metabolic enzymes are sufficient to predict why some patients have sub-therapeutic levels of the drug. Here, using gnotobiotic- and antibiotics-treated mice, we show that tamoxifen pharmacokinetics are heavily influenced by gut bacteria and prolonged exposure to tamoxifen. Interestingly, 16S rRNA gene sequencing shows tamoxifen does not affect overall microbiota composition and abundance. Metabolomics, however, reveals differential metabolic profiles across the microbiomes of different donors cultured with tamoxifen, suggesting an enzymatic diversity within the gut microbiome that influences response to tamoxifen. Consistent with this notion, we found that β-glucuronidase (GUS) enzymes vary in their hydrolysis activity of glucuronidated tamoxifen metabolites across the gut microbiomes of people. Together, these findings highlight the importance of the gut microbiome in tamoxifen's pharmacokinetics.IMPORTANCEOne in eight women will develop breast cancer in their lifetime, and tamoxifen is used to suppress breast cancer recurrence, but nearly 50% of patients are not effectively treated with this drug. Given that tamoxifen is orally administered and, thus, reaches the intestine, this variable patient response to the drug is likely related to the gut microbiota composed of trillions of bacteria, which are remarkably different among individuals. This study aims to understand the impact of the gut microbiome on tamoxifen absorption, metabolism, and recycling. The significance of our research is in defining the role that gut microbes play in tamoxifen pharmacokinetics, thus paving the way for more tailored and effective therapeutic interventions in the prevention of breast cancer recurrence.
| S-EPMC11708054 | biostudies-literature
Project description:The aim of study is to evaluate whether salidroside (S), tyrosol (T) and hydroxytyrosol (H) which are dietary phenylethanoids of natural origins have an influence on reversing gut dysbiosis induced by metabolic syndrome (MetS) mice. C57 BL/6J female mice induced by high fructose diet were established. All mice were adapted to the environment for 7 days with normal diet and sterile drinking water (DW), and randomly divided into 6 groups. Mice in the ND group are fed with ND and treated with normal saline. Other groups were fed with high fructose (HFru) by administration of normal saline, salidroside (S), tyrosol (T) or hydroxytyrosol (H) for 12 weeks by intragastric gavage. Fresh feces from each mouse were collected one days before the end of the experiment and temporarily placed in sterile tubules, and then snap-frozen in liquid nitrogen. Total DNA from stool bacteria was extracted using QIAamp DNA stool mini kit from Qiagen (Germantown, MD, USA) according to the manufacturer’s instructions. Illumina HiSeq sequencing analysis of the DNA samples.16S rRNA gene sequence data further revealed that S, T and H could enhance the diversity of gut microbiota. In general, the abundance of Shigella, Acinetobacter, Lactobacillus, Staphylococcus and Sporosarcina had changed significantly. These findings suggest that S, T and H probably suppress lipid accumulation and to hepatoprotective effect and improve intestinal microflora disorders to attenuate metabolic syndromes.
2022-01-24 | GSE194127 | GEO
Project description:Human gut microbiota 16S Raw sequence reads from Koreans recovering from COVID-19
| PRJNA950198 | ENA
Project description:Motivation16S rRNA gene sequencing is the most frequent approach for the characterization of the human gut microbiota. Despite different efforts in the literature, the inference of functional and metabolic interpretations from 16S rRNA gene sequencing data is still a challenging task. High-quality metabolic reconstructions of the human gut microbiota, such as AGORA and AGREDA, constitute a curated resource to improve functional inference from 16S rRNA data, but they are not typically integrated into standard bioinformatics tools.ResultsHere, we present q2-metnet, a QIIME2 plugin that enables the contextualization of 16S rRNA gene sequencing data into AGORA and AGREDA. In particular, based on relative abundances of taxa, q2-metnet determines normalized activity scores for the reactions and subsystems involved in the selected metabolic reconstruction. Using these scores, q2-metnet allows the user to conduct differential activity analysis for reactions and subsystems, as well as exploratory analysis using PCA and hierarchical clustering. We apply q2-metnet to a dataset from our group that involves 16S rRNA data from stool samples from lean, allergic to cow's milk, obese and celiac children, and the Belgian Flemish Gut Flora Project cohort, which includes faecal 16S rRNA data from obese and normal-weight adult individuals. In the first case, q2-metnet outperforms existing algorithms in separating different clinical conditions based on predicted pathway abundances and subsystem scores. In the second case, q2-metnet complements competing approaches in predicting functional alterations in the gut microbiota of obese individuals. Overall, q2-metnet constitutes a powerful bioinformatics tool to provide metabolic context to 16S rRNA data from the human gut microbiota.Availability and implementationPython code of q2-metnet is available in https://github.com/PlanesLab/q2-metnet and https://figshare.com/articles/dataset/q2-metnet_package/26180446.
| S-EPMC11561042 | biostudies-literature
Project description:The gut microbiota residing in the distal ileum and colon is the most complex, diverse, and densest microbial ecosystem in the human body. Despite its known role in human health and disease, gut microbiome diversity and function are rarely explored in vulnerable populations such as refugees. The current study aimed to explore gut microbiota diversity and sources of variation among adolescent Afghan refugees residing in Peshawar, Pakistan. Stool samples were collected from 10 - 18 years old, healthy adolescents (n=205) for 16S rRNA gene sequence (V4-V5 hypervariable region) analysis on isolated faecal DNA. Bioinformatics analyses were performed using Kraken2, Bracken and Phyloseq. The data presented here will allow researchers to profile the gut microbiota of this rarely explored, vulnerable population who are at high risk of food insecurity and malnutrition. The data can be used to provide insight on the impact of demographic characteristics, dietary intake, nutritional status, and health on gut microbiome diversity, and enables a comparative analysis with similar data sets from other population groups of relevance. The amplicon sequencing data are deposited in the NCBI Sequence Read Archive as BioProject PRJNA1105775.
| S-EPMC11372392 | biostudies-literature