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Deusch S, Camarinha-Silva A, Conrad J, et al. A Structural and Functional Elucidation of the Rumen Microbiome Influenced by Various Diets and Microenvironments. Front Microbiol. 2017;8:1605doi: 10.3389/fmicb.2017.01605.
Deusch, S., Camarinha-Silva, A., Conrad, J., Beifuss, U., Rodehutscord, M., & Seifert, J. (2017). A Structural and Functional Elucidation of the Rumen Microbiome Influenced by Various Diets and Microenvironments. Frontiers in microbiology, 81605. https://doi.org/10.3389/fmicb.2017.01605
Deusch, Simon, et al. "A Structural and Functional Elucidation of the Rumen Microbiome Influenced by Various Diets and Microenvironments." Frontiers in microbiology vol. 8 (2017): 1605. doi: https://doi.org/10.3389/fmicb.2017.01605
Deusch S, Camarinha-Silva A, Conrad J, Beifuss U, Rodehutscord M, Seifert J. A Structural and Functional Elucidation of the Rumen Microbiome Influenced by Various Diets and Microenvironments. Front Microbiol. 2017 Aug 24;8:1605. doi: 10.3389/fmicb.2017.01605. eCollection 2017. PMID: 28883813; PMCID: PMC5573736.
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Front Microbiol. 2017 Aug 24;8:1605. doi: 10.3389/fmicb.2017.01605. eCollection 2017.

A Structural and Functional Elucidation of the Rumen Microbiome Influenced by Various Diets and Microenvironments.

Frontiers in microbiology

Simon Deusch, Amélia Camarinha-Silva, Jürgen Conrad, Uwe Beifuss, Markus Rodehutscord, Jana Seifert

Affiliations

  1. Department of Feed-Gut Microbiota Interaction, Institute of Animal Science, University of HohenheimStuttgart, Germany.
  2. Department of Bioorganic Chemistry, Institute of Chemistry, University of HohenheimStuttgart, Germany.

PMID: 28883813 PMCID: PMC5573736 DOI: 10.3389/fmicb.2017.01605

Abstract

The structure and function of the microbiome inhabiting the rumen are, amongst other factors, mainly shaped by the animal's feed intake. Describing the influence of different diets on the inherent community arrangement and associated metabolic activities of the most active ruminal fractions (bacteria and archaea) is of great interest for animal nutrition, biotechnology, and climatology. Samples were obtained from three fistulated Jersey cows rotationally fed with corn silage, grass silage or grass hay, each supplemented with a concentrate mixture. Samples were fractionated into ruminal fluid, particle-associated rumen liquid, and solid matter. DNA, proteins and metabolites were analyzed subsequently. DNA extracts were used for Illumina sequencing of the 16S rRNA gene and the metabolomes of rumen fluids were determined by 500 MHz-NMR spectroscopy. Tryptic peptides derived from protein extracts were measured by LC-ESI-MS/MS and spectra were processed by a two-step database search for quantitative metaproteome characterization. Data are available via ProteomeXchange with the identifier PXD006070. Protein- and DNA-based datasets revealed significant differences between sample fractions and diets and affirmed similar trends concerning shifts in phylogenetic composition. Ribosomal genes and proteins belonging to the phylum of Proteobacteria, particularly Succinivibrionaceae, exhibited a higher abundance in corn silage-based samples while fiber-degraders of the Lachnospiraceae family emerged in great quantities throughout the solid phase fractions. The analysis of 8163 quantified bacterial proteins revealed the presence of 166 carbohydrate active enzymes in varying abundance. Cellulosome affiliated proteins were less expressed in the grass silage, glycoside hydrolases appeared in slightest numbers in the corn silage. Most expressed glycoside hydrolases belonged to families 57 and 2. Enzymes analogous to ABC transporters for amino acids and monosaccharides were more abundant in the corn silage whereas oligosaccharide transporters showed a higher abundance in the fiber-rich diets. Proteins involved in carbon metabolism were detected in high numbers and identification of metabolites like short-chain fatty acids, methylamines and phenylpropionate by NMR enabled linkage between producers and products. This study forms a solid basis to retrieve deeper insight into the complex network of microbial adaptation in the rumen.

Keywords: 16S rRNA gene; CAZy; LC-ESI-MS/MS; NMR; dietary impact; metaproteomics; rumen microbiome

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