Literature DB >> 29454699

Interrelations between the rumen microbiota and production, behavioral, rumen fermentation, metabolic, and immunological attributes of dairy cows.

M Schären1, J Frahm2, S Kersten2, U Meyer3, J Hummel4, G Breves5, S Dänicke2.   

Abstract

Different studies have shown a strong correlation between the rumen microbiome and a range of production traits (e.g., feed efficiency, milk yield and components) in dairy cows. Underlying dynamics concerning cause and effect are, however, still widely unknown and warrant further investigation. The aim of the current study was to describe possible functional interrelations and pathways using a large set of variables describing the production, the metabolic and immunological state, as well as the rumen microbiome and fermentation characteristics of dairy cows in early lactation (n = 36, 56 ± 3 d in milk). It was further hypothesized that the feed intake-associated behavior may influence the ruminal fermentation pattern, and a set of variables describing these individual animal attributes was included. Principal component analysis as well as Spearman's rank correlations were conducted including a total of 265 variables. The attained plots describe several well-known associations between metabolic, immunological, and production traits. Main drivers of variance within the data set included milk production and efficiency as well as rumen fermentation and microbiome diversity attributes, whereas behavioral, metabolic, and immunological variables did not exhibit any strong interrelations with the other variables. The previously well-documented strong correlation of production traits with distinct prokaryote groups was confirmed. This mainly included a negative correlation of operational taxonomic units ascribed to the Prevotella genus with milk and fat yield and feed efficiency. A central role of the animals' feed intake behavior in this context could not be affirmed. Furthermore, different methodological and interpretability aspects concerning the microbiome analysis by 16S rRNA gene sequencing, such as the discrepancy between taxonomic classification and functional communality, as well as the comparability with other studies, are discussed. We concluded that, to further investigate the driving force that causes the difference between efficient and inefficient animals, studies including more sophisticated methods to describe phenotypical traits of the host (e.g., rumen physiology, metabolic and genetic aspects) as well as the rumen microbiome (e.g., metagenome, metatranscriptome, metaproteome, and metabolome analysis) are needed. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Entities:  

Keywords:  PCA; behavior; feed efficiency; rumen microbiota

Mesh:

Year:  2018        PMID: 29454699     DOI: 10.3168/jds.2017-13736

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  16 in total

1.  Metagenomic analysis exploring taxonomic diversity of rumen microbial communities in Vechur and crossbred cattle of Kerala state, India.

Authors:  Tina Sadan; T V Aravindakshan; G Radhika; Lali F Anand; K Ally
Journal:  J Appl Genet       Date:  2020-01-31       Impact factor: 3.240

2.  Predicting residual feed intake status using rumen microbial profiles in ewe lambs1.

Authors:  Melinda J Ellison; Gavin C Conant; William R Lamberson; Kathleen J Austin; Edward van Kirk; Hannah C Cunningham; Daniel C Rule; Kristi M Cammack
Journal:  J Anim Sci       Date:  2019-07-02       Impact factor: 3.159

3.  Combined signature of rumen microbiome and metabolome in dairy cows with different feed intake levels.

Authors:  Yeqing Q Li; Yumeng M Xi; Zedong D Wang; Hanfang F Zeng; Zhaoyu Han
Journal:  J Anim Sci       Date:  2020-03-01       Impact factor: 3.159

4.  Chronic Effects of Fusarium Mycotoxins in Rations with or without Increased Concentrate Proportion on the Insulin Sensitivity in Lactating Dairy Cows.

Authors:  Asako Kinoshita; Christina Keese; Ulrich Meyer; Alexander Starke; Christine Wrenzycki; Sven Dänicke; Jürgen Rehage
Journal:  Toxins (Basel)       Date:  2018-05-08       Impact factor: 4.546

5.  Illumina sequencing analysis of the ruminal microbiota in high-yield and low-yield lactating dairy cows.

Authors:  Jinjin Tong; Hua Zhang; Delian Yang; Yonghong Zhang; Benhai Xiong; Linshu Jiang
Journal:  PLoS One       Date:  2018-11-13       Impact factor: 3.240

6.  Dynamic Alterations in Yak Rumen Bacteria Community and Metabolome Characteristics in Response to Feed Type.

Authors:  Chang Liu; Hao Wu; Shujie Liu; Shatuo Chai; Qingxiang Meng; Zhenming Zhou
Journal:  Front Microbiol       Date:  2019-05-22       Impact factor: 6.064

7.  Colonization of the human gut by bovine bacteria present in Parmesan cheese.

Authors:  Christian Milani; Sabrina Duranti; Stefania Napoli; Giulia Alessandri; Leonardo Mancabelli; Rosaria Anzalone; Giulia Longhi; Alice Viappiani; Marta Mangifesta; Gabriele Andrea Lugli; Sergio Bernasconi; Maria Cristina Ossiprandi; Douwe van Sinderen; Marco Ventura; Francesca Turroni
Journal:  Nat Commun       Date:  2019-03-20       Impact factor: 14.919

8.  A novel modelling approach to quantify the response of dairy goats to a high-concentrate diet.

Authors:  Masoomeh Taghipoor; Maud Delattre; Sylvie Giger-Reverdin
Journal:  Sci Rep       Date:  2020-11-23       Impact factor: 4.379

9.  Dynamics of rumen bacterial composition of yak (Bos grunniens) in response to dietary supplements during the cold season.

Authors:  Anum Ali Ahmad; Jian Bo Zhang; Zeyi Liang; Chao Yang; Qudratullah Kalwar; Tariq Shah; Mei Du; Ishaq Muhammad; Juanshan Zheng; Ping Yan; Xue-Zhi Ding; Ruijun Long
Journal:  PeerJ       Date:  2021-06-18       Impact factor: 2.984

10.  Characterization of variations within the rumen metaproteome of Holstein dairy cattle relative to morning feed offering.

Authors:  Mallory C Honan; Sabrina L Greenwood
Journal:  Sci Rep       Date:  2020-02-21       Impact factor: 4.379

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