Literature DB >> 29058420

Exploration of Biological Markers of Feed Efficiency in Young Bulls.

Sarah J Meale1, Diego P Morgavi1, Isabelle Cassar-Malek1, Donato Andueza1, Isabelle Ortigues-Marty1, Richard J Robins2, Anne-Marie Schiphorst2, Carole Migné, Mélanie Pétéra, Sophie Laverroux1, Benoit Graulet1, Hamid Boudra1, Gonzalo Cantalapiedra-Hijar1.   

Abstract

The efficiency with which ruminants convert feed to desirable products is difficult to measure under normal commercial settings. We explored the use of potential biological markers from easily obtainable samples, that is, blood, hair, and feces, to characterize potential causes of divergent efficiency when considered as residual feed intake (RFI) or feed conversion efficiency (FCE). A total of 54 Charolais bulls, 20 in period 1 and 34 in period 2, were examined for individual dry matter intake (DMI) and growth. Bulls were offered a diet of 70:30 wrapped grass silage to concentrate for 99 d. At the conclusion of the test period, blood samples were collected for the determination of vitamins B2 and B6, and plasma used for the determination of metabolites, natural isotopic 15N abundance (15N NIA, expressed as δ15N ‰) and fractionation (Δ15Nplasma proteins-diet and Δ13Cplasma proteins-diet) and near-infrared spectroscopy (NIRS). Feces were analyzed by NIRS. Bulls were slaughtered at 15-17 months of age and carcass characteristics determined. Bulls were ranked according to RFI with extremes (SD ± 0.5; n = 31) classified as either efficient (Neg-RFI) or inefficient (Pos-RFI). Extreme bulls were then classified for FCE (high vs low FCE), changing the groups. Pos-RFI bulls consumed 14% more feed than Neg-RFI bulls for the same level of weight gain. Low FCE bulls tended to eat more, but had lower weight gains than high FCE bulls. No differences were detected in carcass conformation, fat scores, hot carcass weight, or dressing percentage. Yet, heart and bladder weights were heavier in Pos-RFI, and rumen weight tended to be heavier in Pos-RFI bulls. RFI did not affect bulk 15N or 13C fractionation. A negative correlation was observed between FCE and Δ15Nplasma proteins-diet. Inefficient bulls (Pos-RFI) had higher δ15N in glycine compared to Neg-RFI bulls. Similarly, metabolomic analysis showed a tendency for concentrations of glycine and sarcosine to be elevated in Pos-RFI bulls, whereas aspartic acid and carnosine tended to be elevated, and serine tended to be lower in High FCE. Among vitamins, only flavin adenine dinucleotide concentration was higher in the blood of bulls with High FCE. These results suggest that the two feed efficiency metrics differ in the underlying mechanisms of metabolism, where RFI is driven by differences in the energetic requirements of visceral organs and the extent of AA catabolism.

Entities:  

Keywords:  amino acid catabolism; energetic efficiency; metabolomics; nitrogen fractionation; vitamin B

Mesh:

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Year:  2017        PMID: 29058420     DOI: 10.1021/acs.jafc.7b03503

Source DB:  PubMed          Journal:  J Agric Food Chem        ISSN: 0021-8561            Impact factor:   5.279


  7 in total

1.  Relationship between feed efficiency and slaughter traits of French Charolais bulls.

Authors:  Sébastien Taussat; Romain Saintilan; Daniel Krauss; David Maupetit; Marie-Noëlle Fouilloux; Gilles Renand
Journal:  J Anim Sci       Date:  2019-05-30       Impact factor: 3.159

2.  Evaluation of the Links between Lamb Feed Efficiency and Rumen and Plasma Metabolomic Data.

Authors:  Florian Touitou; Flavie Tortereau; Lydie Bret; Nathalie Marty-Gasset; Didier Marcon; Annabelle Meynadier
Journal:  Metabolites       Date:  2022-03-29

3.  Identification of key genes and pathways associated with feed efficiency of native chickens based on transcriptome data via bioinformatics analysis.

Authors:  Lei Yang; Tingting He; Fengliang Xiong; Xianzhen Chen; Xinfeng Fan; Sihua Jin; Zhaoyu Geng
Journal:  BMC Genomics       Date:  2020-04-09       Impact factor: 3.969

4.  Individual Feed Efficiency Monitoring of Charolaise Candidate Young Bulls in Relation to Feeding Behavior and Self-Performance Test Results.

Authors:  Gabriella Holló; Henrietta Nagy-Kiszlinger; János Tossenberger; Márton Török; Balázs Húth
Journal:  Animals (Basel)       Date:  2021-12-24       Impact factor: 2.752

5.  Transcriptome analysis reveals the potential roles of long non-coding RNAs in feed efficiency of chicken.

Authors:  Parastoo Karimi; Mohammad Reza Bakhtiarizadeh; Abdolreza Salehi; Hamid Reza Izadnia
Journal:  Sci Rep       Date:  2022-02-15       Impact factor: 4.379

6.  Common and diet-specific metabolic pathways underlying residual feed intake in fattening Charolais yearling bulls.

Authors:  Ezequiel Jorge-Smeding; Muriel Bonnet; Gilles Renand; Sébastien Taussat; Benoit Graulet; Isabelle Ortigues-Marty; Gonzalo Cantalapiedra-Hijar
Journal:  Sci Rep       Date:  2021-12-21       Impact factor: 4.379

7.  Microbiome-metabolomics analysis of the effects of decreasing dietary crude protein content on goat rumen mictobiota and metabolites.

Authors:  Wen Zhu; Tianwei Liu; Jian Deng; Cong Cong Wei; Zi Jun Zhang; Di Ming Wang; Xing Yong Chen
Journal:  Anim Biosci       Date:  2022-03-03
  7 in total

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