High-resolution temporal profiling of the human gut microbiome reveals consistent and cascading alterations in response to dietary glycans
| Autor: | Ruth Thieroff-Ekerdt, Georg K. Gerber, Jonathan W. Leff, Michael A. Mahowald, Richard Creswell, Brandon Brooks, Jie Tan |
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| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Glycans Gastrointestinal Glycan lcsh:QH426-470 Systems biology lcsh:Medicine Computational biology Feces 03 medical and health sciences chemistry.chemical_compound 0302 clinical medicine Metabolomics Polysaccharides Genetics Humans Microbiome Molecular Biology Genetics (clinical) biology Polydextrose Research lcsh:R Human microbiome Computational Biology Bayes Theorem Biodiversity Models Theoretical Healthy Volunteers Human genetics Diet Gastrointestinal Microbiome Dynamics lcsh:Genetics 030104 developmental biology chemistry Metagenomics biology.protein Metagenome Molecular Medicine Time-series Algorithms Software 030217 neurology & neurosurgery Human |
| Zdroj: | Genome Medicine, Vol 12, Iss 1, Pp 1-16 (2020) Genome Medicine |
| ISSN: | 1756-994X |
| Popis: | Background Dietary glycans, widely used as food ingredients and not directly digested by humans, are of intense interest for their beneficial roles in human health through shaping the microbiome. Characterizing the consistency and temporal responses of the gut microbiome to glycans is critical for rationally developing and deploying these compounds as therapeutics. Methods We investigated the effect of two chemically distinct glycans (fructooligosaccharides and polydextrose) through three clinical studies conducted with 80 healthy volunteers. Stool samples, collected at dense temporal resolution (~ 4 times per week over 10 weeks) and analyzed using shotgun metagenomic sequencing, enabled detailed characterization of participants’ microbiomes. For analyzing the microbiome time-series data, we developed MC-TIMME2 (Microbial Counts Trajectories Infinite Mixture Model Engine 2.0), a purpose-built computational tool based on nonparametric Bayesian methods that infer temporal patterns induced by perturbations and groups of microbes sharing these patterns. Results Overall microbiome structure as well as individual taxa showed rapid, consistent, and durable alterations across participants, regardless of compound dose or the order in which glycans were consumed. Significant changes also occurred in the abundances of microbial carbohydrate utilization genes in response to polydextrose, but not in response to fructooligosaccharides. Using MC-TIMME2, we produced detailed, high-resolution temporal maps of the microbiota in response to glycans within and across microbiomes. Conclusions Our findings indicate that dietary glycans cause reproducible, dynamic, and differential alterations to the community structure of the human microbiome. |
| Databáze: | OpenAIRE |
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