Muscle and liver metabolomic signatures associated with residual feed intake in Nellore cattle

Performance, nutrient utilization and meat quality traits in Bos indicus cattle: a meta-analysis examining the effect of residual feed intake

This meta-analysis aims to investigate the effects of residual feed intake (RFI) phenotype on performance, nutrient utilization and meat quality traits in Zebu (Bos indicus) cattle. Twenty-three peer-reviewed publications with 37 treatment means were included in the dataset. Weighted mean difference analysis compared animals categorized into low RFI (more efficient) versus medium or high RFI (less efficient) groups. Data heterogeneity via meta-regression and subgroup analysis, considering variables such as animal age, sex class, experimental duration, RFI group, dietary concentrate, and estimated metabolizable energy intake were also explored. The predominant genetic group of cattle in the dataset was Nellore (89.18%), followed by Brahman (10.81%). More efficient animals (low RFI phenotype) exhibited less dry matter intake (DMI; P < 0.010) than medium or high RFI animals (-0.95 kg vs. -0.42 kg/d). Cattle dietary crude protein and fiber digestibility were consistent across RFI groups (P > 0.05), while dietary ether extract digestibility tended to decrease (P = 0.050) in low RFI animals (-13.20 g/kg DM). Low RFI animals tended to increased (P = 0.065) ribeye area (REA) compared to the high/medium RFI groups, while carcass backfat thickness (BFT) decreased (P = 0.042) compared to high/medium RFI groups. Moreover, there was an increase (P < 0.001) of 0.22 kg in Warner-Bratzler shear force (WBSF) and a reduction (P < 0.001) in the myofibrillar fragmentation index (MFI) in low RFI animals. Meat color parameters (lightness [L*] and yellowness [b*]) and visual marbling scores were consistent (P > 0.05) across RFI groups. In conclusion, Zebu cattle classified as efficient (low RFI) exhibited reduced DMI, which improves their feed efficiency. However, BFT and meat quality parameters such as tenderness (WBSF and MFI) and redness [a*] were compromised by low RFI phenotype, highlighting the challenge of enhancing feed efficiency and meat quality traits in Zebu cattle.

Metabolomics Changes in Meat and Subcutaneous Fat of Male Cattle Submitted to Fetal Programming

This study investigated changes in meat and subcutaneous fat metabolomes and possible metabolic pathways related to prenatal nutrition in beef cattle. For this purpose, 18 Nellore bulls were used for meat sampling and 15 for fat sampling. The nutritional treatments during the gestation were: NP-not programmed or control, without protein-energy supplementation; PP-partially programmed, with protein-energy supplementation (0.3% of body weight (BW)) only in the final third of pregnancy; and FP-full programming, with protein-energy supplementation (0.3% of BW) during the entire pregnancy. The meat and fat samples were collected individually 24 h after slaughter, and the metabolites were extracted using a combination of chemical reagents and mechanical processes and subsequently quantified using liquid chromatography or flow injection coupled to mass spectrometry. The data obtained were submitted to principal component analysis (PCA), analysis of variance (ANOVA), and functional enrichment analysis, with a significance level of 5%. The PCA showed an overlap between the treatments for both meat and fat. In meat, 25 metabolites were statistically different between treatments (p ≤ 0.05), belonging to four classes (glycerophospholipids, amino acids, sphingolipids, and biogenic amine). In fat, 10 significant metabolites (p ≤ 0.05) were obtained in two classes (phosphatidylcholine and lysophosphatidylcholine). The functional enrichment analysis showed alterations in the aminoacyl-tRNA pathway in meat (p = 0.030); however, there was no pathway enriched for fat. Fetal programming influenced the meat and fat metabolomes and the aminoacyl-tRNA metabolic pathway, which is an important candidate for the biological process linked to meat quality and related to fetal programming in beef cattle.

Impacts of Different Prenatal Supplementation Strategies on the Plasma Metabolome of Bulls in the Rearing and Finishing Phase

This study investigated the effects of maternal nutrition on the plasma metabolome of Nellore bulls in the rearing and finishing phases, and metabolic differences between these phases. For this study, three nutritional approaches were used in 126 cows during pregnancy: NP-(control) mineral supplementation; PP-protein-energy supplementation in the final third; and FP-protein-energy supplementation during the entire pregnancy. We collected blood samples from male offspring in the rearing (450 ± 28 days old) and finishing phases (660 ± 28 days old). The blood was processed, and from plasma samples, we performed the targeted metabolome analysis (AbsoluteIDQ® p180 Kit). Multiple linear regression, principal component analysis (PCA), repeated measures analysis over time, and an enrichment analysis were performed. PCA showed an overlap of treatments and time clusters in the analyses. We identified significant metabolites among the treatments (rearing phase = six metabolites; finishing phase = three metabolites) and over time (21 metabolites). No significant metabolic pathways were found in the finishing phase, however, we found significant pathways in the rearing phase (Arginine biosynthesis and Histidine metabolism). Thus, prenatal nutrition impacted on plasma metabolome of bulls during the rearing and finishing phase and the different production stages showed an effect on the metabolic levels of bulls.

Effects of Different Prenatal Nutrition Strategies on the Liver Metabolome of Bulls and Its Correlation with Body and Liver Weight

This study investigated the effect of prenatal nutrition on liver metabolome and on body (BW) and liver weight (LW) of Nellore bulls at slaughter. Three treatments were applied in 126 cows during pregnancy: NP—control (mineral supplementation); PP—protein-energy supplementation in the third trimester; and FP—protein-energy supplementation during the entire pregnancy. Offspring BW and LW were evaluated, and a targeted metabolomics analysis was performed on their livers (n = 18, 22.5 ± 1 months of age). Data were submitted to principal component analysis (PCA), analysis of variance (ANOVA), enrichment analysis, and Pearson’s correlation analysis. The phenotypes did not show differences between treatments (p > 0.05). Metabolites PCA showed an overlap of treatment clusters in the analysis. We found significant metabolites in ANOVA (p ≤ 0.05; Glycine, Hydroxytetradecadienylcarnitine, Aminoadipic acid and Carnosine). Enrichment analysis revealed some biological processes (Histidine metabolism, beta-Alanine metabolism, and Lysine degradation). Pearson’s correlation analysis showed 29 significant correlated metabolites with BW and 1 metabolite correlated with LW. In summary, prenatal nutrition did not show effects on the phenotypes evaluated, but affected some metabolites and biological pathways, mainly related to oxidative metabolism. In addition, BW seems to influence the hepatic metabolome more than LW, due to the amount and magnitude of correlations found.

Prenatal Supplementation in Beef Cattle and Its Effects on Plasma Metabolome of Dams and Calves

This study investigated the effect of different prenatal nutrition on the plasma metabolome of Nellore dams and their offspring. For that purpose, three nutritional treatments were used in 126 cows during pregnancy: NP—(control) only mineral supplementation; PP—protein-energy supplementation in the final third; and FP—protein-energy supplementation during the entire pregnancy. Targeted metabolomics were analyzed in plasma at the beginning of pregnancy and in pre-delivery of cows (n = 27) as well as in calves (n = 27, 30 ± 9.6 days of age). Data were analyzed by the analysis of variance, partial least squares discriminant analysis, and the principal component analysis (PCA). The PCA showed a clear clustering in the periods investigated only in cows (early gestation and pre-delivery). We found significant metabolites in both supervised analyses (p < 0.05 and VIP score > 1) for cows (Taurine, Glutamic acid, Histidine, and PC aa C42:2) and for calves (Carnosine, Alanine, and PC aa C26:0). The enrichment analysis revealed biological processes (p < 0.1) common among cows and calves (histidine metabolism and beta-alanine metabolism), which may be indicative of transgenerational epigenetic changes. In general, fetal programming affected mainly the metabolism of amino acids.

Individual Feed Efficiency Monitoring of Charolaise Candidate Young Bulls in Relation to Feeding Behavior and Self-Performance Test Results

This study evaluated the effect of differences in residual feed intake (RFI) of Charolaise candidate young bulls on feeding behavior and self-performance test results. Bulls were classified into high and low RFI (H-RFI, L-RFI) groups. Bulls were fed in a HOKOFARM system to measure individual animal intake and behavior. L-RFI bulls had significantly lower feed intakes (p = 0.002) and higher gain to feed ratio (p = 0.001), lower intake per day/kg DM (dry matter) (p = 0.002) and lower intake g/body weight/day (p < 0.001). L-RFI animals had lower visits number per day (p = 0.02), but spent longer time per visit (p = 0.02), and tended to have higher intake g/visit (p = 0.06) on feeders. The correlation between RFI and DMI (dry matter intake)/bodyweight/day as well as intake per day/kg were large and positive. Back-loin length and rump length, and moreover muzzle width and frame, showed negative correlations with RFI value. However, bulls with better RFI values associated with lower legs score. Results reveal that RFI was shown beneficial correlations with economically relevant self-performance traits. Further investigations are needed to seek additional indicator traits that are predictive for RFI.

Overview of Metabolomic Analysis and the Integration with Multi-Omics for Economic Traits in Cattle

Metabolomics has been applied to measure the dynamic metabolic responses, to understand the systematic biological networks, to reveal the potential genetic architecture, etc., for human diseases and livestock traits. For example, the current published results include the detected relevant candidate metabolites, identified metabolic pathways, potential systematic networks, etc., for different cattle traits that can be applied for further metabolomic and integrated omics studies. Therefore, summarizing the applications of metabolomics for economic traits is required in cattle. We here provide a comprehensive review about metabolomic analysis and its integration with other omics in five aspects: (1) characterization of the metabolomic profile of cattle; (2) metabolomic applications in cattle; (3) integrated metabolomic analysis with other omics; (4) methods and tools in metabolomic analysis; and (5) further potentialities. The review aims to investigate the existing metabolomic studies by highlighting the results in cattle, integrated with other omics studies, to understand the metabolic mechanisms underlying the economic traits and to provide useful information for further research and practical breeding programs in cattle.