Literature DB >> 29788417

Poor feed efficiency in sheep is associated with several structural abnormalities in the community metabolic network of their ruminal microbes.

Rocky D Patil1, Melinda J Ellison2, Sara M Wolff1, Courtney Shearer3, Anna M Wright4, Rebecca R Cockrum5, Kathy J Austin6, William R Lamberson1, Kristi M Cammack7, Gavin C Conant1,8,9,10.   

Abstract

Ruminant animals have a symbiotic relationship with the microorganisms in their rumens. In this relationship, rumen microbes efficiently degrade complex plant-derived compounds into smaller digestible compounds, a process that is very likely associated with host animal feed efficiency. The resulting simpler metabolites can then be absorbed by the host and converted into other compounds by host enzymes. We used a microbial community metabolic network inferred from shotgun metagenomics data to assess how this metabolic system differs between animals that are able to turn ingested feedstuffs into body mass with high efficiency and those that are not. We conducted shotgun sequencing of microbial DNA from the rumen contents of 16 sheep that differed in their residual feed intake (RFI), a measure of feed efficiency. Metagenomic reads from each sheep were mapped onto a database-derived microbial metabolic network, which was linked to the sheep metabolic network by interface metabolites (metabolites transferred from microbes to host). No single enzyme was identified as being significantly different in abundance between the low and high RFI animals (P > 0.05, Wilcoxon test). However, when we analyzed the metabolic network as a whole, we found several differences between efficient and inefficient animals. Microbes from low RFI (efficient) animals use a suite of enzymes closer in network space to the host's reactions than those of the high RFI (inefficient) animals. Similarly, low RFI animals have microbial metabolic networks that, on average, contain reactions using shorter carbon chains than do those of high RFI animals, potentially allowing the host animals to extract metabolites more efficiently. Finally, the efficient animals possess community networks with greater Shannon diversity among their enzymes than do inefficient ones. Thus, our system approach to the ruminal microbiome identified differences attributable to feed efficiency in the structure of the microbes' community metabolic network that were undetected at the level of individual microbial taxa or reactions.

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Year:  2018        PMID: 29788417      PMCID: PMC6095279          DOI: 10.1093/jas/sky096

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  43 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-24       Impact factor: 11.205

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Journal:  Diagn Microbiol Infect Dis       Date:  2012-12-28       Impact factor: 2.803

Review 4.  Contributions of microbes in vertebrate gastrointestinal tract to production and conservation of nutrients.

Authors:  C E Stevens; I D Hume
Journal:  Physiol Rev       Date:  1998-04       Impact factor: 37.312

5.  Relating the metatranscriptome and metagenome of the human gut.

Authors:  Eric A Franzosa; Xochitl C Morgan; Nicola Segata; Levi Waldron; Joshua Reyes; Ashlee M Earl; Georgia Giannoukos; Matthew R Boylan; Dawn Ciulla; Dirk Gevers; Jacques Izard; Wendy S Garrett; Andrew T Chan; Curtis Huttenhower
Journal:  Proc Natl Acad Sci U S A       Date:  2014-05-19       Impact factor: 11.205

6.  Copy number alterations among mammalian enzymes cluster in the metabolic network.

Authors:  Michaël Bekaert; Gavin C Conant
Journal:  Mol Biol Evol       Date:  2010-11-03       Impact factor: 16.240

7.  Structure, function and diversity of the healthy human microbiome.

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Journal:  Nature       Date:  2012-06-13       Impact factor: 49.962

8.  Ensembl 2014.

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Journal:  Nucleic Acids Res       Date:  2013-12-06       Impact factor: 16.971

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

Authors:  Sara M Wolff; Melinda J Ellison; Yue Hao; Rebecca R Cockrum; Kathy J Austin; Michael Baraboo; Katherine Burch; Hyuk Jin Lee; Taylor Maurer; Rocky Patil; Andrea Ravelo; Tasia M Taxis; Huan Truong; William R Lamberson; Kristi M Cammack; Gavin C Conant
Journal:  Microbiome       Date:  2017-06-08       Impact factor: 14.650

10.  Alterations in composition and diversity of the intestinal microbiota in patients with diarrhea-predominant irritable bowel syndrome.

Authors:  I M Carroll; T Ringel-Kulka; J P Siddle; Y Ringel
Journal:  Neurogastroenterol Motil       Date:  2012-02-20       Impact factor: 3.598

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Review 2.  Emerging Roles of Non-Coding RNAs in the Feed Efficiency of Livestock Species.

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