Literature DB >> 35597888

Ecological dynamics of the gut microbiome in response to dietary fiber.

Hongbin Liu1, Chen Liao2, Lu Wu1, Jinhui Tang3, Junyu Chen1, Chaobi Lei1, Linggang Zheng1, Chenhong Zhang4, Yang-Yu Liu5, Joao Xavier2, Lei Dai6.   

Abstract

Dietary fibers are generally thought to benefit intestinal health. Their impacts on the composition and metabolic function of the gut microbiome, however, vary greatly across individuals. Previous research showed that each individual's response to fibers depends on their baseline gut microbiome, but the ecology driving microbiota remodeling during fiber intake remained unclear. Here, we studied the long-term dynamics of the gut microbiome and short-chain fatty acids (SCFAs) in isogenic mice with distinct microbiota baselines fed with the fermentable fiber inulin and resistant starch compared to the non-fermentable fiber cellulose. We found that inulin produced a generally rapid response followed by gradual stabilization to new equilibria, and those dynamics were baseline-dependent. We parameterized an ecology model from the time-series data, which revealed a group of bacteria whose growth significantly increased in response to inulin and whose baseline abundance and interspecies competition explained the baseline dependence of microbiome density and community composition dynamics. Fecal levels of SCFAs, such as propionate, were associated with the abundance of inulin responders, yet inter-individual variation of gut microbiome impeded the prediction of SCFAs by machine learning models. We showed that our methods and major findings were generalizable to dietary resistant starch. Finally, we analyzed time-series data of synthetic and natural human gut microbiome in response to dietary fiber and validated the inferred interspecies interactions in vitro. This study emphasizes the importance of ecological modeling to understand microbiome responses to dietary changes and the need for personalized interventions.
© 2022. The Author(s), under exclusive licence to International Society for Microbial Ecology.

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Year:  2022        PMID: 35597888      PMCID: PMC9296629          DOI: 10.1038/s41396-022-01253-4

Source DB:  PubMed          Journal:  ISME J        ISSN: 1751-7362            Impact factor:   11.217


  91 in total

1.  Interspecies Competition Impacts Targeted Manipulation of Human Gut Bacteria by Fiber-Derived Glycans.

Authors:  Michael L Patnode; Zachary W Beller; Nathan D Han; Jiye Cheng; Samantha L Peters; Nicolas Terrapon; Bernard Henrissat; Sophie Le Gall; Luc Saulnier; David K Hayashi; Alexandra Meynier; Sophie Vinoy; Richard J Giannone; Robert L Hettich; Jeffrey I Gordon
Journal:  Cell       Date:  2019-09-19       Impact factor: 41.582

2.  Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies.

Authors:  Daryl M Gohl; Pajau Vangay; John Garbe; Allison MacLean; Adam Hauge; Aaron Becker; Trevor J Gould; Jonathan B Clayton; Timothy J Johnson; Ryan Hunter; Dan Knights; Kenneth B Beckman
Journal:  Nat Biotechnol       Date:  2016-07-25       Impact factor: 54.908

Review 3.  The microbiome beyond the horizon of ecological and evolutionary theory.

Authors:  Britt Koskella; Lindsay J Hall; C Jessica E Metcalf
Journal:  Nat Ecol Evol       Date:  2017-10-16       Impact factor: 15.460

4.  Linking long-term dietary patterns with gut microbial enterotypes.

Authors:  Gary D Wu; Jun Chen; Christian Hoffmann; Kyle Bittinger; Ying-Yu Chen; Sue A Keilbaugh; Meenakshi Bewtra; Dan Knights; William A Walters; Rob Knight; Rohini Sinha; Erin Gilroy; Kernika Gupta; Robert Baldassano; Lisa Nessel; Hongzhe Li; Frederic D Bushman; James D Lewis
Journal:  Science       Date:  2011-09-01       Impact factor: 47.728

5.  Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies.

Authors:  Anna Klindworth; Elmar Pruesse; Timmy Schweer; Jörg Peplies; Christian Quast; Matthias Horn; Frank Oliver Glöckner
Journal:  Nucleic Acids Res       Date:  2012-08-28       Impact factor: 16.971

6.  metaSPAdes: a new versatile metagenomic assembler.

Authors:  Sergey Nurk; Dmitry Meleshko; Anton Korobeynikov; Pavel A Pevzner
Journal:  Genome Res       Date:  2017-03-15       Impact factor: 9.043

7.  Identifying and Overcoming Threats to Reproducibility, Replicability, Robustness, and Generalizability in Microbiome Research.

Authors:  Patrick D Schloss
Journal:  mBio       Date:  2018-06-05       Impact factor: 7.867

Review 8.  A Guide to Diet-Microbiome Study Design.

Authors:  Abigail J Johnson; Jack Jingyuan Zheng; Jea Woo Kang; Anna Saboe; Dan Knights; Angela M Zivkovic
Journal:  Front Nutr       Date:  2020-06-12

9.  CD-HIT: accelerated for clustering the next-generation sequencing data.

Authors:  Limin Fu; Beifang Niu; Zhengwei Zhu; Sitao Wu; Weizhong Li
Journal:  Bioinformatics       Date:  2012-10-11       Impact factor: 6.937

10.  Guild-based analysis for understanding gut microbiome in human health and diseases.

Authors:  Guojun Wu; Naisi Zhao; Chenhong Zhang; Yan Y Lam; Liping Zhao
Journal:  Genome Med       Date:  2021-02-09       Impact factor: 11.117

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  2 in total

1.  Ecological memory of prior nutrient exposure in the human gut microbiome.

Authors:  Jeffrey Letourneau; Zachary C Holmes; Eric P Dallow; Heather K Durand; Sharon Jiang; Verónica M Carrion; Savita K Gupta; Adam C Mincey; Michael J Muehlbauer; James R Bain; Lawrence A David
Journal:  ISME J       Date:  2022-07-23       Impact factor: 11.217

Review 2.  Dietary regulation in health and disease.

Authors:  Qi Wu; Zhi-Jie Gao; Xin Yu; Ping Wang
Journal:  Signal Transduct Target Ther       Date:  2022-07-23
  2 in total

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