Literature DB >> 29556107

Nutritional preferences of human gut bacteria reveal their metabolic idiosyncrasies.

Melanie Tramontano1, Sergej Andrejev1, Mihaela Pruteanu1,2, Martina Klünemann1, Michael Kuhn1, Marco Galardini3, Paula Jouhten1, Aleksej Zelezniak1,4, Georg Zeller1, Peer Bork5,6,7,8, Athanasios Typas9, Kiran Raosaheb Patil10.   

Abstract

Bacterial metabolism plays a fundamental role in gut microbiota ecology and host-microbiome interactions. Yet the metabolic capabilities of most gut bacteria have remained unknown. Here we report growth characteristics of 96 phylogenetically diverse gut bacterial strains across 4 rich and 15 defined media. The vast majority of strains (76) grow in at least one defined medium, enabling accurate assessment of their biosynthetic capabilities. These do not necessarily match phylogenetic similarity, thus indicating a complex evolution of nutritional preferences. We identify mucin utilizers and species inhibited by amino acids and short-chain fatty acids. Our analysis also uncovers media for in vitro studies wherein growth capacity correlates well with in vivo abundance. Further value of the underlying resource is demonstrated by correcting pathway gaps in available genome-scale metabolic models of gut microorganisms. Together, the media resource and the extracted knowledge on growth abilities widen experimental and computational access to the gut microbiota.

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Year:  2018        PMID: 29556107     DOI: 10.1038/s41564-018-0123-9

Source DB:  PubMed          Journal:  Nat Microbiol        ISSN: 2058-5276            Impact factor:   17.745


  61 in total

1.  A Multireporter Bacterial 2-Hybrid Assay for the High-Throughput and Dynamic Assay of PDZ Domain-Peptide Interactions.

Authors:  David M Ichikawa; Carles Corbi-Verge; Michael J Shen; Jamie Snider; Victoria Wong; Igor Stagljar; Philip M Kim; Marcus B Noyes
Journal:  ACS Synth Biol       Date:  2019-04-18       Impact factor: 5.110

Review 2.  Thinking Outside the Cereal Box: Noncarbohydrate Routes for Dietary Manipulation of the Gut Microbiota.

Authors:  Aspen T Reese; Rachel N Carmody
Journal:  Appl Environ Microbiol       Date:  2019-05-02       Impact factor: 4.792

3.  Cutting the Gordian Knot of the Microbiota.

Authors:  Kimberly S Vasquez; Anthony L Shiver; Kerwyn Casey Huang
Journal:  Mol Cell       Date:  2018-06-07       Impact factor: 17.970

4.  Inferring Metabolic Mechanisms of Interaction within a Defined Gut Microbiota.

Authors:  Gregory L Medlock; Maureen A Carey; Dennis G McDuffie; Michael B Mundy; Natasa Giallourou; Jonathan R Swann; Glynis L Kolling; Jason A Papin
Journal:  Cell Syst       Date:  2018-09-05       Impact factor: 10.304

5.  Fast automated reconstruction of genome-scale metabolic models for microbial species and communities.

Authors:  Daniel Machado; Sergej Andrejev; Melanie Tramontano; Kiran Raosaheb Patil
Journal:  Nucleic Acids Res       Date:  2018-09-06       Impact factor: 16.971

6.  Evaluating the Impact of Four Major Nutrients on Gut Microbial Metabolism by a Targeted Metabolomics Approach.

Authors:  Kundi Yang; Mengyang Xu; Jiangjiang Zhu
Journal:  J Proteome Res       Date:  2020-04-23       Impact factor: 4.466

Review 7.  Microbiota-dependent and -independent effects of dietary fibre on human health.

Authors:  Yang Cai; Jelle Folkerts; Gert Folkerts; Marcus Maurer; Saskia Braber
Journal:  Br J Pharmacol       Date:  2019-12-12       Impact factor: 8.739

8.  Hypoglycemic mechanism of polysaccharide from Cyclocarya paliurus leaves in type 2 diabetic rats by gut microbiota and host metabolism alteration.

Authors:  Qiqiong Li; Jielun Hu; Qixing Nie; Xiao Chang; Qingying Fang; Junhua Xie; Haishan Li; Shaoping Nie
Journal:  Sci China Life Sci       Date:  2020-06-17       Impact factor: 6.038

9.  Orthogonal Dietary Niche Enables Reversible Engraftment of a Gut Bacterial Commensal.

Authors:  Sean M Kearney; Sean M Gibbons; Susan E Erdman; Eric J Alm
Journal:  Cell Rep       Date:  2018-08-14       Impact factor: 9.423

10.  Gut microbiota dysbiosis is associated with malnutrition and reduced plasma amino acid levels: Lessons from genome-scale metabolic modeling.

Authors:  Manish Kumar; Boyang Ji; Parizad Babaei; Promi Das; Dimitra Lappa; Girija Ramakrishnan; Todd E Fox; Rashidul Haque; William A Petri; Fredrik Bäckhed; Jens Nielsen
Journal:  Metab Eng       Date:  2018-07-31       Impact factor: 9.783

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