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Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome

BACKGROUND: Grazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal’s diet, we inferred a microbiome-level metabolic network from shotgun metagenomic dat...

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Autores principales: Wolff, Sara M., Ellison, Melinda J., Hao, Yue, Cockrum, Rebecca R., Austin, Kathy J., Baraboo, Michael, Burch, Katherine, Lee, Hyuk Jin, Maurer, Taylor, Patil, Rocky, Ravelo, Andrea, Taxis, Tasia M., Truong, Huan, Lamberson, William R., Cammack, Kristi M., Conant, Gavin C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5465553/
https://www.ncbi.nlm.nih.gov/pubmed/28595639
http://dx.doi.org/10.1186/s40168-017-0274-6
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author Wolff, Sara M.
Ellison, Melinda J.
Hao, Yue
Cockrum, Rebecca R.
Austin, Kathy J.
Baraboo, Michael
Burch, Katherine
Lee, Hyuk Jin
Maurer, Taylor
Patil, Rocky
Ravelo, Andrea
Taxis, Tasia M.
Truong, Huan
Lamberson, William R.
Cammack, Kristi M.
Conant, Gavin C.
author_facet Wolff, Sara M.
Ellison, Melinda J.
Hao, Yue
Cockrum, Rebecca R.
Austin, Kathy J.
Baraboo, Michael
Burch, Katherine
Lee, Hyuk Jin
Maurer, Taylor
Patil, Rocky
Ravelo, Andrea
Taxis, Tasia M.
Truong, Huan
Lamberson, William R.
Cammack, Kristi M.
Conant, Gavin C.
author_sort Wolff, Sara M.
collection PubMed
description BACKGROUND: Grazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal’s diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data. RESULTS: Using comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When the host sheep were fed a grain-based diet, the induced microbial metabolic network showed several critical differences from those seen on the evolved forage-based diet. Grain-based (e.g., concentrate) diets tend to be dominated by a smaller set of reactions that employ metabolites that are nearer in network space to the host’s metabolism. In addition, these reactions are more central in the network and employ substrates with shorter carbon backbones. Despite this apparent lower complexity, the concentrate-associated metabolic networks are actually more dissimilar from each other than are those of forage-fed animals. Because both groups of animals were initially fed on a forage diet, we propose that the diet switch drove the appearance of a number of different microbial networks, including a degenerate network characterized by an inefficient use of dietary nutrients. We used network simulations to show that such disparate networks are not an unexpected result of a diet shift. CONCLUSION: We argue that network approaches, particularly those that link the microbial network with that of the host, illuminate aspects of the structure of the microbiome not seen from a strictly taxonomic perspective. In particular, different diets induce predictable and significant differences in the enzymes used by the microbiome. Nonetheless, there are clearly a number of microbiomes of differing structure that show similar functional properties. Changes such as a diet shift uncover more of this type of diversity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-017-0274-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-54655532017-06-09 Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome Wolff, Sara M. Ellison, Melinda J. Hao, Yue Cockrum, Rebecca R. Austin, Kathy J. Baraboo, Michael Burch, Katherine Lee, Hyuk Jin Maurer, Taylor Patil, Rocky Ravelo, Andrea Taxis, Tasia M. Truong, Huan Lamberson, William R. Cammack, Kristi M. Conant, Gavin C. Microbiome Research BACKGROUND: Grazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal’s diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data. RESULTS: Using comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When the host sheep were fed a grain-based diet, the induced microbial metabolic network showed several critical differences from those seen on the evolved forage-based diet. Grain-based (e.g., concentrate) diets tend to be dominated by a smaller set of reactions that employ metabolites that are nearer in network space to the host’s metabolism. In addition, these reactions are more central in the network and employ substrates with shorter carbon backbones. Despite this apparent lower complexity, the concentrate-associated metabolic networks are actually more dissimilar from each other than are those of forage-fed animals. Because both groups of animals were initially fed on a forage diet, we propose that the diet switch drove the appearance of a number of different microbial networks, including a degenerate network characterized by an inefficient use of dietary nutrients. We used network simulations to show that such disparate networks are not an unexpected result of a diet shift. CONCLUSION: We argue that network approaches, particularly those that link the microbial network with that of the host, illuminate aspects of the structure of the microbiome not seen from a strictly taxonomic perspective. In particular, different diets induce predictable and significant differences in the enzymes used by the microbiome. Nonetheless, there are clearly a number of microbiomes of differing structure that show similar functional properties. Changes such as a diet shift uncover more of this type of diversity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-017-0274-6) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-08 /pmc/articles/PMC5465553/ /pubmed/28595639 http://dx.doi.org/10.1186/s40168-017-0274-6 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Wolff, Sara M.
Ellison, Melinda J.
Hao, Yue
Cockrum, Rebecca R.
Austin, Kathy J.
Baraboo, Michael
Burch, Katherine
Lee, Hyuk Jin
Maurer, Taylor
Patil, Rocky
Ravelo, Andrea
Taxis, Tasia M.
Truong, Huan
Lamberson, William R.
Cammack, Kristi M.
Conant, Gavin C.
Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome
title Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome
title_full Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome
title_fullStr Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome
title_full_unstemmed Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome
title_short Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome
title_sort diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5465553/
https://www.ncbi.nlm.nih.gov/pubmed/28595639
http://dx.doi.org/10.1186/s40168-017-0274-6
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