Selection for Growth and Precocity Alters Muscle Metabolism in Nellore Cattle

Performance, Meat Quality and Meat Metabolomics Outcomes: Efficacy of 3-Nitrooxypropanol in Feedlot Beef Cattle Diets

30 Nellore animals with an average weight of 407.25 ± 2.04 kg, were distributed in a completely randomized design across the following treatments: 1-Control (without inclusion of 3-NOP); 2-BV75 (inclusion of 3-NOP at 75 mg/kg DM); 3-BV100 (inclusion of 3-NOP at 100 mg/kg DM). No significant effects were observed between treatments on ingestive behavior. However, the notable effect on the BWfinal and ADG of animals supplemented with 3-NOP compared to the control group was measurable. Cattle beef receiving 3-NOP exhibited reduced methane emissions (p < 0.0001) for all variables analyzed, resulting in an average decrease of 38.2% in methane emissions compared to the control, along with increased hydrogen emissions (g/day) (p < 0.0001). While supplementation with BV100 demonstrated lower methane emission, the performance was lower than BV75 in DMI, BWfinal, ADG, and ADG carcasses. Partial separation of metabolomics observed between groups indicated changes in meat metabolism when comparing the control group with the 3-NOP group, identifying metabolites with a variable importance projection (VIP) score > 1. In conclusion, supplementation with 3-NOP effectively reduced methane emissions and did not negatively influence animal performance.

Reproductive system morphometry and productive parameters of beef heifers according to morphological classification

The aim of the present study was to analyze the effects of visual morphological classification based on body structure, maturity, and musculosity on the morphometry of the reproduction system and productive parameters of beef heifers. The study was conducted for 84 days, during winter season in Brazil. Thirty non-pregnant Nellore heifers, with an average body weight 338 kg and average age 18 months, were used for the study. The heifers were housed in collective pens and fed corn silage (70%) and concentrate (30%) twice a day. All heifers were weighed weekly without prior fasting. Morphological evaluation of body structure, maturity, and musculosity was conducted in the third-middle of the experimental period by a trained evaluator, adopting a comparative methodology of visual evaluation on a scale from 1 to 6, and the heifers were classified according to the visual assessment. The effects of visual classification, time, and interactions were analyzed, considering significant effects was detected (p < 0.05). The significant (p < 0.05) results obtained were compared using Tukey test. Morphological classification did not influence the morphometry of the reproductive system or implied on time interactions. Body structure, maturity, and musculosity had no effect on dry matter intake, body weight gain, feed efficiency, and carcass dressing. However, body weight and feed efficiency were influenced by the experimental time. For both variables, significant variations were detected after 63 days of finishing in the feedlot (p < 0.001), indicating that maximum productive efficiency of feedlot-finished Nellore beef heifers was achieved at a mean body weight of 424 kg.

A multi-block data approach to assessing beef quality: ComDim analysis of hyperspectral imaging, 1H NMR, electronic nose and quality parameters data

Several factors affect the quality of beef. In the field of chemometrics, multi-block data analysis methods are useful for examining multiple sources of information from a sample. This study focuses on the application of ComDim, a multi-block data analysis method, to evaluate beef from different parts of hyperspectral spectrum and image texture information, ¹H NMR fingerprints, quality parameters and electronic nose. Compared to principal component analysis (PCA) methods based on low-level data fusion, ComDim is more efficient and powerful, because it reveals the relationships between the methods and techniques studied, as well as the variability of beef quality across multiple metrics. The quality and metabolite composition of beef tenderloin and hindquarters were differentiated, with low L* value and high shear tenderloin distinguished from hindquarters with opposite characteristics. The proposed strategy demonstrates that ComDim approach can be used to characterize samples when different techniques describe the same set of samples.

Genome-Wide Association Analysis Reveals Novel Loci Related with Visual Score Traits in Nellore Cattle Raised in Pasture-Based Systems

Body conformation traits assessed based on visual scores are widely used in Zebu cattle breeding programs. The aim of this study was to identify genomic regions and biological pathways associated with body conformation (CONF), finishing precocity (PREC), and muscling (MUSC) in Nellore cattle. The measurements based on visual scores were collected in 20,807 animals raised in pasture-based systems in Brazil. In addition, 2775 animals were genotyped using a 35 K SNP chip, which contained 31,737 single nucleotide polymorphisms after quality control. Single-step GWAS was performed using the BLUPF90 software while candidate genes were identified based on the Ensembl Genes 69. PANTHER and REVIGO platforms were used to identify key biological pathways and STRING to create gene networks. Novel candidate genes were revealed associated with CONF, including ALDH9A1, RXRG, RAB2A, and CYP7A1, involved in lipid metabolism. The genes associated with PREC were ELOVL5, PID1, DNER, TRIP12, and PLCB4, which are related to the synthesis of long-chain fatty acids, lipid metabolism, and muscle differentiation. For MUSC, the most important genes associated with muscle development were SEMA6A, TIAM2, UNC5A, and UIMC1. The polymorphisms identified in this study can be incorporated in commercial genotyping panels to improve the accuracy of genomic evaluations for visual scores in beef cattle.

Exploratory lipidome and metabolome profiling contributes to understanding differences in high and normal ultimate pH beef

The aim of this work was to compare the lipidome and metabolome profiling in the Longissimus thoracis muscle early and late postmortem from high and normal ultimate pH (pHu) beef. Lipid profiling discriminated between high and normal pHu beef based on fatty acid metabolism and mitochondrial beta-oxidation of long chain saturated fatty acids at 30 min postmortem, and phospholipid biosynthesis at 44 h postmortem. Metabolite profiling also discriminated between high and normal pHu beef, mainly through glutathione, purine, arginine and proline, and glycine, serine and threonine metabolisms at 30 min postmortem, and glycolysis, TCA cycle, glutathione, tyrosine, and pyruvate metabolisms at 44 h postmortem. Lipid and metabolite profiles showed reduced glycolysis and increased use of alternative energy metabolic processes that were central to differentiating high and normal pHu beef. Phospholipid biosynthesis modification suggested high pHu beef experienced greater oxidative stress.

Identification of biomarkers associated with the feed efficiency by metabolomics profiling: results from the broiler lines divergent for high or low abdominal fat content

Background

Improving feed efficiency (FE) is one of the main objectives in broiler breeding. It is difficult to directly measure FE traits, and breeders hence have been trying to identify biomarkers for the indirect selection and improvement of FE traits. Metabolome is the "bridge" between genome and phenome. The metabolites may potentially account for more of the phenotypic variation and can suitably serve as biomarkers for selecting FE traits. This study aimed to identify plasma metabolite markers for selecting high-FE broilers. A total of 441 birds from Northeast Agricultural University broiler lines divergently selected for abdominal fat content were used to analyze plasma metabolome and estimate the genetic parameters of differentially expressed metabolites.

Results

The results identified 124 differentially expressed plasma metabolites (P < 0.05) between the lean line (high-FE birds) and the fat line (low-FE birds). Among these differentially expressed plasma metabolites, 44 were found to have higher positive or negative genetic correlations with FE traits (|r_g| ≥ 0.30). Of these 44 metabolites, 14 were found to display moderate to high heritability estimates (h² ≥ 0.20). However, among the 14 metabolites, 4 metabolites whose physiological functions have not been reported were excluded. Ultimately, 10 metabolites were suggested to serve as the potential biomarkers for breeding the high-FE broilers. Based on the physiological functions of these metabolites, reducing inflammatory and improving immunity were proposed to improve FE and increase production efficiency.

Conclusions

According to the pipeline for the selection of the metabolite markers established in this study, it was suggested that 10 metabolites including 7-ketocholesterol, dimethyl sulfone, epsilon-(gamma-glutamyl)-lysine, gamma-glutamyltyrosine, 2-oxoadipic acid, L-homoarginine, testosterone, adenosine 5'-monophosphate, adrenic acid, and calcitriol could be used as the potential biomarkers for breeding the "food-saving broilers".

Impact of Cattle Feeding Strategy on the Beef Metabolome

The present study explored changes in the meat metabolome of animals subjected to different finishing systems and growth rates. Thirty-six Angus × Nellore crossbred steers were used in a completely randomized design with four treatments: (1) feedlot system with high average daily gain (ADG; FH); (2) feedlot system with low ADG (FL); (3) pasture system with high ADG (PH); and (4) pasture system with low ADG (PL). After harvest and chilling, Longissimus thoracis (LT) muscle samples were taken for metabolite profile analysis using nuclear magnetic resonance. Spectrum was analyzed using chenomx software, and multi- and mega-variate data analyses were performed. The PLS-DA showed clear separation between FH and PL groups and overlap among treatments with different finishing systems but similar for matching ADG (FL and PH) treatments. Using a VIP cut-off of around 1.0, ATP and fumarate were shown to be greater in meat from PL cattle, while succinate, leucine, AMP, glutamate, carnosine, inosine, methionine, G1P, and choline were greater in meat from FH. Comparing FL and PH treatments, glutamine, carnosine, urea, NAD+, malonate, lactate, isoleucine, and alanine were greater in the meat of PH cattle, while G6P and betaine were elevated in that of FL cattle. Relevant pathways were also identified by differences in growth rate (FH versus PL) and finishing system were also noted. Growth rate caused a clear difference in meat metabolism that was highlighted by energy metabolism and associated pathways, while the feeding system tended to alter protein and lipid metabolism.

Applications of Omics Technology for Livestock Selection and Improvement

Conventional animal selection and breeding methods were based on the phenotypic performance of the animals. These methods have limitations, particularly for sex-limited traits and traits expressed later in the life cycle (e.g., carcass traits). Consequently, the genetic gain has been slow with high generation intervals. With the advent of high-throughput omics techniques and the availability of multi-omics technologies and sophisticated analytic packages, several promising tools and methods have been developed to estimate the actual genetic potential of the animals. It has now become possible to collect and access large and complex datasets comprising different genomics, transcriptomics, proteomics, metabolomics, and phonemics data as well as animal-level data (such as longevity, behavior, adaptation, etc.,), which provides new opportunities to better understand the mechanisms regulating animals’ actual performance. The cost of omics technology and expertise of several fields like biology, bioinformatics, statistics, and computational biology make these technology impediments to its use in some cases. The population size and accurate phenotypic data recordings are other significant constraints for appropriate selection and breeding strategies. Nevertheless, omics technologies can estimate more accurate breeding values (BVs) and increase the genetic gain by assisting the section of genetically superior, disease-free animals at an early stage of life for enhancing animal productivity and profitability. This manuscript provides an overview of various omics technologies and their limitations for animal genetic selection and breeding decisions.

Using TD-NMR relaxometry and 1D 1H NMR spectroscopy to evaluate aging of Nellore beef

The aim of this study was to explore the use of TD-NMR relaxometry and ¹H NMR spectroscopy-based for detecting differences in meat quality attributes. There was limited association between various TD-NMR signals and any physicochemical parameters of fresh and aged meat differing in tenderness ratings. Samples were then divided into three groups based on statistical changes in metabolite concentration. Group A samples possessed near linear increases in metabolite concentration over aging time; whereas samples assigned to Groups B and C were characterized by increases in metabolites that peaked between 7 and 14 days, and up to 14 days aging, respectively. ¹H NMR spectroscopy discriminated meat quality using changes in metabolites reflective of glycolysis, the citric acid cycle, protein degradation, amino acid generation and purine metabolisms. These data suggest segregation of meat quality is possible using both NMR technologies but additional work is necessary to understand fully their utility in a commercial industry setting.

Metabolomic signature of genetic potential for muscularity in beef cattle

The aim of this study was to investigate the serum and meat metabolomic changes according to the genetic potential for muscularity of non-castrated Nellore males and its association with phenotypic traits. Forty-eight non-castrated Nellore males were separated into two groups based on their genetic potential for post-weaning muscularity: high (HM) and low (LM). Selection for muscularity did not cause noticeable differences in the traits evaluated during the finishing phase and after slaughter. However, several metabolites in meat and serum, have changed according to the muscularity group. HM animals presented an over-abundance of glycerol, glutamine, choline, methylhistidine, betaine, creatinine and methionine in serum, compared with their LM counterparts. Similarly, the meat samples of HM animals were rich in glucose-6-phosphate, lactate, pyruvate, creatinine, betaine, choline, glycerol and arginine relative to LM bulls. Inosine monophosphate was the only metabolite over-abundant in LM animals. In conclusion, the genetic potential for post-weaning muscularity did not affect performance during the finishing phase, carcass traits and meat quality. However, multivariate analysis shows that the genetic potential of muscularity can be correlated with serum lipid and protein metabolites, and with energy metabolism in meat, providing a footprint of cattle muscularity metabolism.

Meat Quality, Fatty Acid Content and NMR Metabolic Profile of Dorper Sheep Supplemented with Bypass Fats

The supplementation of rumen bypass fat (RBF) has remained one of the preferred approaches used to decrease undesirable saturated fatty acids (FA) and increase beneficial unsaturated FA in the meat. This study was planned to evaluate the influences of rumen bypass fats on meat quality, fatty acid and metabolic profiles in male Dorper sheep (n = 36) with 24.66 ± 0.76 kg (mean ± standard error) initial body weight. Treatment comprised a basal diet (30:70 rice straw to concentrate) with no added RBF as a control (CON), basal diet with prilled fat (PF), basal diet with prilled fat plus lecithin (PFL) and basal diet with calcium soap of palm fatty acids (CaS). The findings revealed that cooking loss, drip loss and shear force in longissimus dorsi (LD) muscle were not affected by RBF supplementation, while meat pH was significantly higher in the CaS on aging day 1. However, the diet supplemented with prilled fat and lecithin modified the meat's fatty acid profile significantly by increasing unsaturated fatty acids and decreasing saturated fats. The relative quantification of the major differentiating metabolites found in LD muscle of sheep showed that total cholesterol, esterified cholesterol, choline, glycerophosphocholine and glycerophospholipids were significantly lower in CaS and PFL diets, while glycerol and sphingomyelin were significantly higher in CaS and PFL diets. Most of the metabolites in the liver did not show any significant difference. Based on our results, the supplementation of protected fats did not have a negative influence on meat quality and the meat from Dorper sheep fed prilled fat with lecithin contained more healthy fatty acids compared to other diets.

Preliminary study on the characterization of Longissimus lumborum dark cutting meat in Angus × Nellore crossbreed cattle using NMR-based metabolomics

The aim of this preliminary study was to evaluate meat quality properties, muscle metabolite profile and metabolic pathways associated with the occurrence of dark cutting meat in Angus x Nellore crossbreed cattle. After 14 days' ageing, dark cutting meat presented a higher pH, lower cooking loss and colour parameters, and greater tenderness compared with normal meat. Dark cutting meat had a higher ATP level and lower concentrations of glucose-6-phosphate, lactate, glucose, serine, threonine, creatine phosphate, inosine, leucine, methionine, succinate and glucose-1-phosphate compared to normal meat. In dark cutting samples, the ultimate pH was positively correlated with carnitine and negatively correlated with glucose-6-phosphate. However, in normal meat, the ultimate pH presented a positive correlation with arginine, leucine, methionine, proline, threonine, tyrosine and valine. Pathway analysis showed that differentiation of the groups was linked to energetic pathways such as starch and sucrose metabolism, the pentose phosphate pathway, amino sugar, nucleotide sugar metabolism, and glycolysis or gluconeogenesis. In conclusion, the occurrence of dark cutting meat has a notable impact on meat quality attributes and concentrations of post-mortem glycolytic metabolites, appears to be correlated with mitochondrial activity and affects energetic metabolic pathways.

Exploring the Regulatory Potential of Long Non-Coding RNA in Feed Efficiency of Indicine Cattle

Long non-coding RNA (lncRNA) can regulate several aspects of gene expression, being associated with complex phenotypes in humans and livestock species. In taurine beef cattle, recent evidence points to the involvement of lncRNA in feed efficiency (FE), a proxy for increased productivity and sustainability. Here, we hypothesized specific regulatory roles of lncRNA in FE of indicine cattle. Using RNA-Seq data from the liver, muscle, hypothalamus, pituitary gland and adrenal gland from Nellore bulls with divergent FE, we submitted new transcripts to a series of filters to confidently predict lncRNA. Then, we identified lncRNA that were differentially expressed (DE) and/or key regulators of FE. Finally, we explored lncRNA genomic location and interactions with miRNA and mRNA to infer potential function. We were able to identify 126 relevant lncRNA for FE in Bos indicus, some with high homology to previously identified lncRNA in Bos taurus and some possible specific regulators of FE in indicine cattle. Moreover, lncRNA identified here were linked to previously described mechanisms related to FE in hypothalamus-pituitary-adrenal axis and are expected to help elucidate this complex phenotype. This study contributes to expanding the catalogue of lncRNA, particularly in indicine cattle, and identifies candidates for further studies in animal selection and management.

Metabolites and Metabolic Pathways Correlated With Beef Tenderness

Metabolite profile has been used to understand the causes of variability in beef tenderness, but still little is known about how metabolites contribute to beef quality. Therefore, this study was carried out to evaluate how meat metabolites and their metabolic pathways correlate to variability in beef tenderness. Carcasses from 60 noncastrated male cattle were selected, and three 2.5-cm-thick longissimus thoracis steaks were obtained and aged (0°C to 4°C) for 7d. Warner-Bratzler shear force (WBSF) was performed (steak 1). Based on WBSF data, 2 tenderness classes (n = 30; 15 per class [tender and tough]) were created to perform sarcomere length (steak 2) and metabolom ic analysis (steak 3). Meat ultimate pH did not differ between tenderness classes. However, steaks classified as tender had greater sarcomere length (P = 0.019) than those classified as tough. Acetyl-carnitine (P = 0.026), adenine (P = 0.026), beta-alanine (P = 0.005), fumarate (P = 0.022), glutamine (P = 0.043), and valine (P = 0.030) concentration were higher in tender beef compared with tough beef. The 4 most important compounds differing between tender and tough beef were lactate, glucose, creatine, and glutamine, which may indicate that metabolic pathways such as D-glutamine and D-glutamate metabolism, beta-alanine metabolism, purine metabolism, and tricarboxylic acid cycle affected the tenderness classes. Beta-alanine (r = − 0.45), acetyl-carnitine (r = − 0.40), fumarate (r = − 0.38), valine (r = − 0.34), glucose (r = − 0.32), glutamine (r = − 0.31), and adenine (r = −0.31) were negatively correlated with WBSF values. Metabolite profile in tender beef indicated a greater oxidative metabolism, which promoted modifications in the muscle structure and proteolysis, favoring its tenderization.

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

In the past decades, metabolomics has been used to comprehensively understand a variety of food materials for improvement and assessment of food quality. Farm animal skeletal muscles and meat are one of the major targets of metabolomics for the characterization of meat and the exploration of biomarkers in the production system. For identification of potential biomarkers to control meat quality, studies of animal muscles and meat with metabolomics (MEATabolomics) has been conducted in combination with analyses of meat quality traits, focusing on specific factors associated with animal genetic background and sensory scores, or conditions in feeding system and treatments of meat in the processes such as postmortem storage, processing, and hygiene control. Currently, most of MEATabolomics approaches combine separation techniques (gas or liquid chromatography, and capillary electrophoresis)-mass spectrometry (MS) or nuclear magnetic resonance (NMR) approaches with the downstream multivariate analyses, depending on the polarity and/or hydrophobicity of the targeted metabolites. Studies employing these approaches provide useful information to monitor meat quality traits efficiently and to understand the genetic background and production system of animals behind the meat quality. MEATabolomics is expected to improve the knowledge and methodologies in animal breeding and feeding, meat storage and processing, and prediction of meat quality.