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Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls

Authors :
Mark V. Berjanskii
Carolyn Fitzsimmons
David S. Wishart
Aidin Foroutan
Rupasri Mandal
Source :
Metabolites, Volume 10, Issue 12, Metabolites, Vol 10, Iss 491, p 491 (2020)
Publication Year :
2020
Publisher :
Multidisciplinary Digital Publishing Institute, 2020.

Abstract

Residual feed intake (RFI) is a feed efficiency measure commonly used in the livestock industry to identify animals that efficiently/inefficiently convert feed into meat or body mass. Selection for low-residual feed intake (LRFI), or feed efficient animals, is gaining popularity among beef producers due to the fact that LRFI cattle eat less and produce less methane per unit weight gain. RFI is a difficult and time-consuming measure to perform, and therefore a simple blood test that could distinguish high-RFI (HRFI) from LRFI animals (early on) would potentially benefit beef farmers in terms of optimizing production or selecting which animals to cull or breed. Using three different metabolomics platforms (nuclear magnetic resonance (NMR) spectrometry, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and inductively coupled plasma mass spectrometry (ICP-MS)) we successfully identified serum biomarkers for RFI that could potentially be translated to an RFI blood test. One set of predictive RFI biomarkers included formate and leucine (best for NMR), and another set included C4 (butyrylcarnitine) and LysoPC(28:0) (best for LC-MS/MS). These serum biomarkers have high sensitivity and specificity (AUROC &gt<br />0.85), for distinguishing HRFI from LRFI animals. These results suggest that serum metabolites could be used to inexpensively predict and categorize bovine RFI values. Further validation using a larger, more diverse cohort of cattle is required to confirm these findings.

Details

Language :
English
ISSN :
22181989
Database :
OpenAIRE
Journal :
Metabolites
Accession number :
edsair.doi.dedup.....fef76582459646e36f91954523b36484
Full Text :
https://doi.org/10.3390/metabo10120491