Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls
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...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759889/ https://www.ncbi.nlm.nih.gov/pubmed/33266049 http://dx.doi.org/10.3390/metabo10120491 |
_version_ | 1783627203503718400 |
---|---|
author | Foroutan, Aidin Fitzsimmons, Carolyn Mandal, Rupasri Berjanskii, Mark V. Wishart, David S. |
author_facet | Foroutan, Aidin Fitzsimmons, Carolyn Mandal, Rupasri Berjanskii, Mark V. Wishart, David S. |
author_sort | Foroutan, Aidin |
collection | PubMed |
description | 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 > 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. |
format | Online Article Text |
id | pubmed-7759889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77598892020-12-26 Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls Foroutan, Aidin Fitzsimmons, Carolyn Mandal, Rupasri Berjanskii, Mark V. Wishart, David S. Metabolites Article 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 > 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. MDPI 2020-11-30 /pmc/articles/PMC7759889/ /pubmed/33266049 http://dx.doi.org/10.3390/metabo10120491 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Foroutan, Aidin Fitzsimmons, Carolyn Mandal, Rupasri Berjanskii, Mark V. Wishart, David S. Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls |
title | Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls |
title_full | Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls |
title_fullStr | Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls |
title_full_unstemmed | Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls |
title_short | Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls |
title_sort | serum metabolite biomarkers for predicting residual feed intake (rfi) of young angus bulls |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759889/ https://www.ncbi.nlm.nih.gov/pubmed/33266049 http://dx.doi.org/10.3390/metabo10120491 |
work_keys_str_mv | AT foroutanaidin serummetabolitebiomarkersforpredictingresidualfeedintakerfiofyoungangusbulls AT fitzsimmonscarolyn serummetabolitebiomarkersforpredictingresidualfeedintakerfiofyoungangusbulls AT mandalrupasri serummetabolitebiomarkersforpredictingresidualfeedintakerfiofyoungangusbulls AT berjanskiimarkv serummetabolitebiomarkersforpredictingresidualfeedintakerfiofyoungangusbulls AT wishartdavids serummetabolitebiomarkersforpredictingresidualfeedintakerfiofyoungangusbulls |