|ARTEGOITIA, VIRGINIA - University Of Nebraska|
|LEWIS, RON - University Of Nebraska|
Submitted to: Journal of Animal Science Supplement
Publication Type: Abstract Only
Publication Acceptance Date: 4/21/2016
Publication Date: 7/11/2016
Citation: Artegoitia, V.M., Foote, A.P., Lewis, R.M., Freetly, H.C. 2016. Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers [abstract]. Journal of Animal Science. 94(E-Supplement 5):768.
Technical Abstract: The rumen plays a central role in the efficiency of digestion in ruminants. To identify potential differences in rumen function that lead to differences in feed efficiency, rumen metabolomic analysis by ultra-performance liquid chromatography/ time-of-flight mass spectrometry (MS) and multivariate/univariate statistical analysis were used to identify differences in rumen metabolites. Individual feed intake and BW gain was measured on 144 crossbred steers for 105 d on a high concentrate ration. Eight steers with the greatest ADG and 8 steers with the least ADG within 0.32 SD of the mean DMI were selected for the study. The DMI did not differ between ADG groups (10.10 ± 0.05 kg/d; P=0.41); however, ADG was greater (P<0.01) in the greatest ADG group (1.96 ± 0.02 kg/d) than the least ADG group (1.57 ± 0.02 kg/d). Rumen fluid was collected at slaughter. Metabolite identification was obtained through a mass-based bovine database search. Verification of the identities of selected metabolites was conducted by comparing MS/MS fragmentation patterns with those from authentic compounds. Principal component analysis and t-test on rumen fluid metabolic profile identified 90 metabolites (P<0.10) that segregated with ADG group. These metabolites were primarily involved in linoleic and alpha-linolenic metabolism (impact-value 1.0 and 0.75, respectively; P<0.05); both pathways were down-regulated in the greatest-ADG compared with least-ADG group. Ruminal levels of four metabolites associated with ADG group were screened by receiver operating curve analysis to test their efficacy as biomarkers for ADG. Subsequently, a partial least square discriminate analysis was used to develop a predictive model to verify and optimize the exclusive biomarkers. The combination of pentadecanoic acid, eicosanoic acid, linoleic acid and alpha-linolenic acid produced a good predictor of feed efficiency, AUC (95% CI) = 0.901 (0.67-1.0), representing 87.5% of sensitivity and 75% of specificity. All four metabolites level decreased in greatest-ADG vs. least-ADG animals in the rumen fluid. As well, higher fold levels of small molecules in the rumen fluid were found in greatest-ADG vs. least-ADG (P<0.05), such as folic acid (13%), malonyl-CoA (30%), pyroglutamic acid (57%), oleamide (13%) and alloxan (23%; glucose analog). This study indicates that metabolomics based on ruminal fluid can yield metabolites that can predict and classify feed efficiency. Furthermore, on the basis of the pathway analysis of biomarkers, ruminant fluid metabolomics profile give new insight into the physiology of feed efficiency.