Literature DB >> 26244934

Quantifying Diet-Induced Metabolic Changes of the Human Gut Microbiome.

Saeed Shoaie1, Pouyan Ghaffari1, Petia Kovatcheva-Datchary2, Adil Mardinoglu1, Partho Sen1, Estelle Pujos-Guillot3, Tomas de Wouters4, Catherine Juste4, Salwa Rizkalla5, Julien Chilloux6, Lesley Hoyles6, Jeremy K Nicholson6, Joel Dore4, Marc E Dumas6, Karine Clement7, Fredrik Bäckhed8, Jens Nielsen9.   

Abstract

The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community And Systems-level INteractive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in vitro. Focusing on metabolic interactions between the diet, gut microbiota, and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention.
Copyright © 2015 Elsevier Inc. All rights reserved.

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Mesh:

Year:  2015        PMID: 26244934     DOI: 10.1016/j.cmet.2015.07.001

Source DB:  PubMed          Journal:  Cell Metab        ISSN: 1550-4131            Impact factor:   27.287


  146 in total

Review 1.  The Role of the Gut Microbiome in Predicting Response to Diet and the Development of Precision Nutrition Models-Part I: Overview of Current Methods.

Authors:  Riley L Hughes; Maria L Marco; James P Hughes; Nancy L Keim; Mary E Kable
Journal:  Adv Nutr       Date:  2019-11-01       Impact factor: 8.701

Review 2.  Manipulating Bacterial Communities by in situ Microbiome Engineering.

Authors:  Ravi U Sheth; Vitor Cabral; Sway P Chen; Harris H Wang
Journal:  Trends Genet       Date:  2016-02-22       Impact factor: 11.639

Review 3.  Effective models and the search for quantitative principles in microbial evolution.

Authors:  Benjamin H Good; Oskar Hallatschek
Journal:  Curr Opin Microbiol       Date:  2018-12-06       Impact factor: 7.934

Review 4.  The Role of the Gut Microbiome in Predicting Response to Diet and the Development of Precision Nutrition Models. Part II: Results.

Authors:  Riley L Hughes; Mary E Kable; Maria Marco; Nancy L Keim
Journal:  Adv Nutr       Date:  2019-11-01       Impact factor: 8.701

5.  Challenges in modeling the human gut microbiome.

Authors:  Parizad Babaei; Saeed Shoaie; Boyang Ji; Jens Nielsen
Journal:  Nat Biotechnol       Date:  2018-08-06       Impact factor: 54.908

Review 6.  Understanding the physiology of the ageing individual: computational modelling of changes in metabolism and endurance.

Authors:  Johannes H G M van Beek; Thomas B L Kirkwood; James B Bassingthwaighte
Journal:  Interface Focus       Date:  2016-04-06       Impact factor: 3.906

Review 7.  Metagenome-wide association studies: fine-mining the microbiome.

Authors:  Jun Wang; Huijue Jia
Journal:  Nat Rev Microbiol       Date:  2016-07-11       Impact factor: 60.633

8.  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

Review 9.  Understanding and Engineering Distributed Biochemical Pathways in Microbial Communities.

Authors:  Xinyun Cao; Joshua J Hamilton; Ophelia S Venturelli
Journal:  Biochemistry       Date:  2018-11-20       Impact factor: 3.162

Review 10.  The gut microbiome, diet, and links to cardiometabolic and chronic disorders.

Authors:  Judith Aron-Wisnewsky; Karine Clément
Journal:  Nat Rev Nephrol       Date:  2015-11-30       Impact factor: 28.314

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