Literature DB >> 33785185

Characterization of the rumen microbiota and its relationship with residual feed intake in sheep.

Y K Zhang1, X X Zhang2, F D Li3, C Li1, G Z Li1, D Y Zhang1, Q Z Song1, X L Li1, Y Zhao1, W M Wang4.   

Abstract

Feed efficiency is a highly important economic trait in sheep production and has a significant impact on the economic benefits of sheep farming. Microbial fermentation of the rumen has a vital role in the host's nutrition; the rumen microbiota might affect host feed efficiency. However, the relationship between the rumen microbiota and feed efficiency in sheep is unclear. In the present study, the microbiota of 195 Hu sheep was investigated and their residual feed intake (RFI), a commonly used measure of feed efficiency, was determined. From birth, all sheep were subjected to the same management practices. At slaughter, samples of liquid rumen contents were collected and subjected to amplicon sequencing for the 16S rDNA gene on the IonS5™XL platform. To identify the bacterial taxa differentially represented at the genus or higher taxonomy levels, we used linear discriminant analysis coupled with effect size and curve fitting. In the sheep rumen, the four most abundant phyla were Firmicutes, Bacteroidetes, Fibrobacteres, and Proteobacteria; and the dominant genera were unidentified Prevotellaceae, Fibrobacter, unidentified Lachnospiraceae, Saccharofermentans, and Succinivibrio. Pathway analysis of the 16S rDNA sequencing data from the rumen microbiota identified that carbohydrate metabolism was enriched. Using α-diversity analysis, we further identified that Observed species, ACE, Good's coverage, and Chao1 are more abundant (P < 0.01) in the low-RFI (L-RFI) group compared to the high-RFI (H-RFI) group. High-RFI sheep had a higher abundance of three bacterial taxa (Prevotellaceae, Negativicutes, and Selenomonadales), and one taxa was overrepresented in the L-RFI sheep (Succinivibrio), respectively. Furthermore, model fitting showed that Veillonellaceae, Sphaerochaeta, Negativibacillus, Saccharofermentans, and members of the Tenericutes, Kiritimatiellaeota, Deltaproteobacteria, and Campylobacterales were correlated with the sheep RFI classification and thus were indicative of a role in animal efficiency. Tax4Fun analysis revealed that metabolic pathways such as "energy metabolism," "metabolism of cofactors and vitamins," "poorly characterized," and "replication recombination and repair proteins" were enriched in the rumen from H-RFI sheep, and "genetic information processing" and "lipopolysaccharide biosynthesis" were overrepresented in L-RFI sheep rumen. In addition, six Kyoto Encyclopedia of Genes and Genomes orthology pathways were identified as different between H-RFI and L-RFI groups. In conclusion, the low RFI phenotype (efficient animals) consistently (or characteristically) exhibited a more abundant and diverse microbiome in sheep.
Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  16S rDNA; Microbial function; Microbiota; Residual feed intake; Rumen

Mesh:

Year:  2021        PMID: 33785185     DOI: 10.1016/j.animal.2020.100161

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  9 in total

1.  Fermented soybean meal modified the rumen microbiome to enhance the yield of milk components in Holstein cows.

Authors:  Abdulmumini Baba Amin; Lei Zhang; JiYou Zhang; Shengyong Mao
Journal:  Appl Microbiol Biotechnol       Date:  2022-10-20       Impact factor: 5.560

2.  Serum Biochemical Parameters, Rumen Fermentation, and Rumen Bacterial Communities Are Partly Driven by the Breed and Sex of Cattle When Fed High-Grain Diet.

Authors:  Xinjun Qiu; Xiaoli Qin; Liming Chen; Zhiming Chen; Rikang Hao; Siyu Zhang; Shunran Yang; Lina Wang; Yafang Cui; Yingqi Li; Yiheng Ma; Binghai Cao; Huawei Su
Journal:  Microorganisms       Date:  2022-01-30

3.  The value of gut microbiota to predict feed efficiency and growth of rabbits under different feeding regimes.

Authors:  María Velasco-Galilea; Miriam Piles; Yuliaxis Ramayo-Caldas; Juan P Sánchez
Journal:  Sci Rep       Date:  2021-09-30       Impact factor: 4.379

4.  The Effect of Dietary Supplementation with Resveratrol on Growth Performance, Carcass and Meat Quality, Blood Lipid Levels and Ruminal Microbiota in Fattening Goats.

Authors:  Yujian Shen; Yuhang Jiang; Sanbao Zhang; Juhong Zou; Xiaotong Gao; Ying Song; Yu Zhang; Yan Hu; Yanna Huang; Qinyang Jiang
Journal:  Foods       Date:  2022-02-18

5.  Residual Feed Intake and Rumen Metabolism in Growing Pelibuey Sheep.

Authors:  Carlos Arce-Recinos; Nadia Florencia Ojeda-Robertos; Ricardo Alfonso Garcia-Herrera; Jesús Alberto Ramos-Juarez; Ángel Trinidad Piñeiro-Vázquez; Jorge Rodolfo Canul-Solís; Luis Enrique Castillo-Sanchez; Fernando Casanova-Lugo; Einar Vargas-Bello-Pérez; Alfonso Juventino Chay-Canul
Journal:  Animals (Basel)       Date:  2022-02-24       Impact factor: 2.752

6.  Supplementation of Aspergillus oryzae Culture Improved the Feed Dry Matter Digestibility and the Energy Supply of Total Volatile Fatty Acid Concentrations in the Rumen of Hu Sheep.

Authors:  Long Guo; Duihong Zhang; Ruifang Du; Fadi Li; Fei Li; Tao Ran
Journal:  Front Nutr       Date:  2022-04-25

7.  Age-dependent variations in rumen bacterial community of Mongolian cattle from weaning to adulthood.

Authors:  Anum Ali Ahmad; Jianbo Zhang; Zeyi Liang; Mei Du; Yayuan Yang; Juanshan Zheng; Ping Yan; RuiJun Long; Bin Tong; Jianlin Han; Xuezhi Ding
Journal:  BMC Microbiol       Date:  2022-09-07       Impact factor: 4.465

8.  Association between rumen microbiota and marbling grade in Hu sheep.

Authors:  Jianghui Wang; Yukun Zhang; Xiaojuan Wang; Fadi Li; Deyin Zhang; Xiaolong Li; Yuan Zhao; Liming Zhao; Dan Xu; Jiangbo Cheng; Wenxin Li; Changchun Lin; Xiaobin Yang; Rui Zhai; Xiwen Zeng; Panpan Cui; Zongwu Ma; Jia Liu; Xiaoxue Zhang; Weimin Wang
Journal:  Front Microbiol       Date:  2022-09-21       Impact factor: 6.064

Review 9.  Essential Oils as a Dietary Additive for Small Ruminants: A Meta-Analysis on Performance, Rumen Parameters, Serum Metabolites, and Product Quality.

Authors:  Griselda Dorantes-Iturbide; José Felipe Orzuna-Orzuna; Alejandro Lara-Bueno; Germán David Mendoza-Martínez; Luis Alberto Miranda-Romero; Héctor Aarón Lee-Rangel
Journal:  Vet Sci       Date:  2022-09-02
  9 in total

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