AUTHOR=Hailemariam Dagnachew , Hashemiranjbar Mohsen , Manafiazar Ghader , Stothard Paul , Plastow Graham 

TITLE=Milk metabolomics analyses of lactating dairy cows with divergent residual feed intake reveals physiological underpinnings and novel biomarkers

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2023.1146069

DOI=10.3389/fmolb.2023.1146069

ISSN=2296-889X

ABSTRACT=The opportunity to select for feed efficient cows has been limited by inability to cost-effectively record individual feed efficiency on an appropriate scale. This study investigated the differences in milk metabolite profiles between high- and low residual feed intake (RFI) categories and identified biomarkers of RFI and models that can be used to predict RFI in lactating Holsteins. Milk metabolomics analyses were undertaken at early, mid and late lactation stages and RFI was calculated in 72 lactating dairy cows. Cows were ranked and grouped into high RFI (RFI > 0.5 SD above the mean, n = 20) and low RFI (RFI < 0.5 SD below the mean, n = 20). Milk metabolite profiles were compared between high RFI (least efficient) and low RFI (most efficient) groups. Results indicated that early lactation was predominantly characterized by significantly elevated levels of medium chain acyl carnitines and glycerophospholipids in high RFI cows. Citrate cycle and glycerophospholipid metabolism were the associated pathways enriched with the significantly different metabolites in early lactation. At mid lactation short and medium chain acyl carnitines, glycerophospholipids and amino acids were the main metabolite groups differing according to RFI category. Late lactation was mainly characterized by increased levels of amino acids in high RFI cows. Amino acid metabolism and biosynthesis pathways were enriched for metabolites that differed between RFI groups at the mid and late lactation stages. Receiver operating characteristic curve analysis identified candidate biomarkers: decanoylcarnitine (area under the curve: AUC = 0.81), dodecenoylcarnitine (AUC = 0.81) and phenylalanine (AUC = 0.85) at early, mid and late stages of lactation, respectively. Furthermore, panels of metabolites predicted RFI with validation coefficient of determination (R2) of 0.65, 0.37 and 0.60 at early, mid and late lactation stages, respectively. The study sheds light on lactation stage specific metabolic differences between high-RFI and low-RFI lactating dairy cows. Candidate biomarkers that distinguished divergent RFI groups and panels of metabolites that predict individual RFI phenotypes were identified. This result supports the potential of milk metabolites to select for more efficient cows given that traditional RFI phenotyping is costly and difficult to conduct in commercial farms.