Literature DB >> 22156428

Impact of feed efficiency and diet on adaptive variations in the bacterial community in the rumen fluid of cattle.

Emma Hernandez-Sanabria1, Laksiri A Goonewardene, Zhiquan Wang, Obioha N Durunna, Stephen S Moore, Le Luo Guan.   

Abstract

Limited knowledge of the structure and activities of the ruminal bacterial community prevents the understanding of the effect of population dynamics on functional bacterial groups and on host productivity. This study aimed to identify particular bacteria associated with host feed efficiency in steers with differing diets and residual feed intake (RFI) using culture-independent methods: PCR-denaturing gradient gel electrophoresis (DGGE) and quantitative real-time PCR analysis. PCR-DGGE profiles were generated from the ruminal fluid of 55 steers fed a low-energy-density diet and then switched to a high-energy-density diet. Bacterial profile comparisons by multivariate statistical analysis showed a trend only for RFI-related clusters on the high-energy diet. When steers (n = 19) belonging to the same RFI group under both diets were used to identify specific bacterial phylotypes related to feed efficiency traits, correlations were detected between dry matter intake, average daily gain, and copy numbers of the 16S rRNA gene of Succinivibrio sp. in low-RFI (efficient) steers, whereas correlations between Robinsoniella sp. and RFI (P < 0.05) were observed for high-RFI (inefficient) animals. Eubacterium sp. differed significantly (P < 0.05) between RFI groups that were only on the high-energy diet. Our work provides a comprehensive framework to understand how particular bacterial phylotypes contribute to differences in feed efficiency and ultimately influence host productivity, which may either depend on or be independent from diet factors.

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Year:  2011        PMID: 22156428      PMCID: PMC3273029          DOI: 10.1128/AEM.05114-11

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  44 in total

1.  Effect of environmental factors and influence of rumen and hindgut biogeography on bacterial communities in steers.

Authors:  Gustavo A Romero-Pérez; Kim H Ominski; Tim A McAllister; Denis O Krause
Journal:  Appl Environ Microbiol       Date:  2010-11-12       Impact factor: 4.792

2.  Effect of rapid or gradual grain adaptation on subacute acidosis and feed intake by feedlot cattle.

Authors:  D W Bevans; K A Beauchemin; K S Schwartzkopf-Genswein; J J McKinnon; T A McAllister
Journal:  J Anim Sci       Date:  2005-05       Impact factor: 3.159

3.  Advantage of using inosine at the 3' termini of 16S rRNA gene universal primers for the study of microbial diversity.

Authors:  Eitan Ben-Dov; Orr H Shapiro; Nachshon Siboni; Ariel Kushmaro
Journal:  Appl Environ Microbiol       Date:  2006-09-01       Impact factor: 4.792

4.  Diversity of H2/CO2-utilizing acetogenic bacteria from feces of non-methane-producing humans.

Authors:  A Bernalier; V Rochet; M Leclerc; J Doré; P Pochart
Journal:  Curr Microbiol       Date:  1996-08       Impact factor: 2.188

5.  Dominance of Prevotella and low abundance of classical ruminal bacterial species in the bovine rumen revealed by relative quantification real-time PCR.

Authors:  David M Stevenson; Paul J Weimer
Journal:  Appl Microbiol Biotechnol       Date:  2007-01-18       Impact factor: 4.813

6.  Rapidly growing rumen methanogenic organism that synthesizes coenzyme M and has a high affinity for formate.

Authors:  D R Lovley; R C Greening; J G Ferry
Journal:  Appl Environ Microbiol       Date:  1984-07       Impact factor: 4.792

7.  Microbial ecology of the equine hindgut during oligofructose-induced laminitis.

Authors:  Gabriel J Milinovich; Paul C Burrell; Christopher C Pollitt; Athol V Klieve; Linda L Blackall; Diane Ouwerkerk; Erika Woodland; Darren J Trott
Journal:  ISME J       Date:  2008-06-26       Impact factor: 10.302

8.  Real-time polymerase chain reaction quantification of specific butyrate-producing bacteria, Desulfovibrio and Enterococcus faecalis in the feces of patients with colorectal cancer.

Authors:  Ramadass Balamurugan; Ethendhar Rajendiran; Sarah George; G Vijay Samuel; Balakrishnan S Ramakrishna
Journal:  J Gastroenterol Hepatol       Date:  2008-07-08       Impact factor: 4.029

9.  Molecular studies of fecal anaerobic commensal bacteria in acute diarrhea in children.

Authors:  Ramadass Balamurugan; Harish P Janardhan; Sarah George; M Venkata Raghava; Jayaprakash Muliyil; Balakrishnan S Ramakrishna
Journal:  J Pediatr Gastroenterol Nutr       Date:  2008-05       Impact factor: 2.839

10.  Effect of divergence in residual feed intake on feeding behavior, blood metabolic variables, and body composition traits in growing beef heifers.

Authors:  A K Kelly; M McGee; D H Crews; A G Fahey; A R Wylie; D A Kenny
Journal:  J Anim Sci       Date:  2009-10-09       Impact factor: 3.159

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  66 in total

1.  Buccal swabbing as a noninvasive method to determine bacterial, archaeal, and eukaryotic microbial community structures in the rumen.

Authors:  Sandra Kittelmann; Michelle R Kirk; Arjan Jonker; Alan McCulloch; Peter H Janssen
Journal:  Appl Environ Microbiol       Date:  2015-08-14       Impact factor: 4.792

2.  Zinc AA supplementation alters yearling ram rumen bacterial communities but zinc sulfate supplementation does not.

Authors:  Suzanne L Ishaq; Chad M Page; Carl J Yeoman; Thomas W Murphy; Megan L Van Emon; Whit C Stewart
Journal:  J Anim Sci       Date:  2019-02-01       Impact factor: 3.159

3.  Ruminal Bacterial Community Composition in Dairy Cows Is Dynamic over the Course of Two Lactations and Correlates with Feed Efficiency.

Authors:  Kelsea A Jewell; Caroline A McCormick; Christine L Odt; Paul J Weimer; Garret Suen
Journal:  Appl Environ Microbiol       Date:  2015-05-01       Impact factor: 4.792

4.  Genetic parameters and genome-wide association study regarding feed efficiency and slaughter traits in Charolais cows.

Authors:  Pauline Martin; Sébastien Taussat; Aurélie Vinet; Daniel Krauss; David Maupetit; Gilles Renand
Journal:  J Anim Sci       Date:  2019-09-03       Impact factor: 3.159

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

Authors:  Rocky D Patil; Melinda J Ellison; Sara M Wolff; Courtney Shearer; Anna M Wright; Rebecca R Cockrum; Kathy J Austin; William R Lamberson; Kristi M Cammack; Gavin C Conant
Journal:  J Anim Sci       Date:  2018-06-04       Impact factor: 3.159

6.  Bacterial community composition and fermentation patterns in the rumen of sika deer (Cervus nippon) fed three different diets.

Authors:  Zhipeng Li; André-Denis G Wright; Hanlu Liu; Kun Bao; Tietao Zhang; Kaiying Wang; Xuezhe Cui; Fuhe Yang; Zhigang Zhang; Guangyu Li
Journal:  Microb Ecol       Date:  2014-09-25       Impact factor: 4.552

7.  The impact of feed efficiency selection on the ruminal, cecal, and fecal microbiomes of Angus steers from a commercial feedlot.

Authors:  Christina B Welch; Jeferson M Lourenco; Dylan B Davis; Taylor R Krause; Mia N Carmichael; Michael J Rothrock; T Dean Pringle; Todd R Callaway
Journal:  J Anim Sci       Date:  2020-07-01       Impact factor: 3.159

8.  RUMINANT NUTRITION SYMPOSIUM: Tiny but mighty: the role of the rumen microbes in livestock production.

Authors:  Kristi M Cammack; Kathleen J Austin; William R Lamberson; Gavin C Conant; Hannah C Cunningham
Journal:  J Anim Sci       Date:  2018-03-06       Impact factor: 3.159

9.  Digestive tract microbiota of beef cattle that differed in feed efficiency.

Authors:  Harvey C Freetly; Aaron Dickey; Amanda K Lindholm-Perry; Richard M Thallman; John W Keele; Andrew P Foote; James E Wells
Journal:  J Anim Sci       Date:  2020-02-01       Impact factor: 3.159

10.  Metagenomic characterisation of ruminal bacterial diversity in buffaloes from birth to adulthood using 16S rRNA gene amplicon sequencing.

Authors:  Prakash G Koringa; Jalpa R Thakkar; Ramesh J Pandit; Ankit T Hinsu; Mithil J Parekh; Ravi K Shah; Subhash J Jakhesara; Chaitanya G Joshi
Journal:  Funct Integr Genomics       Date:  2018-10-24       Impact factor: 3.410

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