Plasma biomarkers for residual feed intake prediction in beef bulls

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Authors: Mauro Venturini, Daniella C Heredia, Maria Camila López Duarte, Kamryn Joyce, Martin Ruiz‐Moreno, Federico Tarnonsky, Wilmer A. Cuervo, Nadia Ashrafi, Stewart Graham, William Thatcher, J.H.J. Bittar, José Carlos Batista Dubeux
+3 more Ricardo Chebel, Nicolás DiLorenzo, Angela Gonella
Cited by: 1
References: 58

Abstract

Abstract Residual feed intake (RFI) is a measure of feed efficiency (FE) independent of growth and body weight (BW), calculated as the difference between actual and expected feed intake (FI) based on mean metabolic weight (MW) and weight gain. We hypothesized that bulls with contrasting RFI differ in plasma concentration of different compounds. RFI was evaluated in 302 bulls from 3 different ranches. After adaptation, bulls consumed the same diet for 56 d, individual FI was daily recorded, BW was measured every 2 weeks, and blood samples were taken at d 0 and 56. The bulls were ranked as low RFI (LRFI) and high RFI (HRFI), and the top and bottom 30 were used for metabolomic, hormone, and isotope analysis. Multivariate and pathway analysis were conducted with MetaboAnalyst, and univariate analysis was conducted with SAS using Mixed procedures. Additionally, for Biomarker analysis, Receiver Operating Characteristic (ROC) curves were constructed with MetaboAnalyst. Sparse Partial Least Squares–Discriminant Analysis (sPLSDA) showed partial cluster separation evidenced by acceptable R2 values. The model showed poor predictive power, reflected by low Q2 values. For LRFI animals (more feed efficient), the most abundant metabolites (P = 0.05) at d 0 were Cer(d18:1/24:1), TG(20:2_32:1), SM (OH) C22:1, SM (OH) C22:2, SM C24:0, TG(20:2_34:3), GCA, Choline, TG(20:2_34:4), and Hex2Cer(d18:1/14:0), while at d 56 were Cer(d18:1/18:0), Cer(d18:1/23:0), TG(14:0_34:2), C16:2, HexCer(d18:1/20:0), C16:1, lysoPCaC16:0, TG(18:3_38:5), C9, SM C24:1, SM C16:0, Carnosine, Cer(d18:2/12:0), SM C18:0, and Cer(d18:1/24:0). Primary bile acid biosynthesis pathway was enriched at d 0 (P = 0.008) and sphingomyelin metabolism at d 56 in LRFI (P = 0.041). Compounds that were identified as variable importance of projection (VIP) and were also statistically different in the univariate analysis, were used to construct ROC curves to identify their potential as biomarker for RFI. With an Area Under the Curve (AUC) value > 0.7 and p-value < 0.05 as the criteria for diagnostic potential, choline was identified as biomarker of RFI at d 0, and Cer(d18:1/23:0) and TG(18:1_30:0) were identified as biomarkers of RFI at d 56. Although multivariate model showed a poor predictive value, further exploration of individual metabolites could provide insights into the mechanisms contributing to FE differences.

Fields of Study & Subjects

Ruminant Nutrition and Digestive Physiology Genetic and phenotypic traits in livestock Animal Nutrition and Physiology

Publication details

Journal / source
Translational Animal Science
Publisher
Oxford University Press (OUP)
Volume
10
Pages
txag020–txag020
Publication date
1 January 2026
Language
EN