Plasma metabolites associated with residual feed intake and other productivity performance traits in beef cattle

A comprehensive study of liver-gut microbiota and antioxidant enzyme activity mediated regulation of late-laying hens by high and low residual feed intake

Residual feed intake (RFI) is a better indicator of feed efficiency than feed conversion ratio (FCR). It is frequently used to evaluate the efficacy of poultry and livestock feed consumption. Generally, Low RFI (LRFI) is associated with better feed conversion efficiency, whereas high RFI (HRFI) suggests poorer feed conversion efficiency. The study examined the association between microorganisms, tissue and organ functions. The results demonstrated that in contrast to the HRFI group, the LRFI group revealed higher length measurements, the digestive organs' mass, and chest width. The antioxidant indices revealed that the enzymatic activities (catalase and glutathione peroxidase) in the LRFI group were significantly higher than those in the HRFI group. The serum levels of HDLC, AST, and ACTH were identified as potential markers that could affect RFI. The variations between high and low RFI and the function of the liver and cecum microbiota of hens during late laying period were systematically investigated by multiple omics techniques. Through 16S, the most common beneficial microbial population in the gut of LRFI groups, such as Oscillospirales, Ruminococcaceae, and Butyricicoccaceae, has been detected via a microbiome-metabolome association analysis. Through multi-omics analysis, we found that FABP1 and ACSS2 are important regulatory genes affecting RFI. These findings will provide a basis for comprehending the role of gut microbiota in regulating RFI and the molecular mechanism behind the phenotypic changes observed in late-laying hens.

Circulating serum metabolites as biomarkers and predictors of residual feed intake in lactating dairy cows

This study explored the potential of circulatory serum metabolite profiles to increase understanding of the physiology of feed efficiency and identify biomarkers to predict residual feed intake (RFI) in lactating Holsteins. Serum metabolite profiles were compared in high (n = 20) and low RFI (n = 20) cows at early, mid, and late lactation stages. The low RFI cows had decreased (P < 0.05) concentrations of dodecanoylcarnitine, dodecenoylcarnitine, dodecanedioylcarnitine, tetradecanoylcarnitine, succinic acid, trimethylamine N-oxide, betaine, and increased concentrations of p-Hydroxyhippuric acid, hydroxysphingomyeline C16:1, phosphatidylcholine diacyl C40:6, and glutarylcarnitine at early lactation. A similar comparison at mid lactation stage showed altered serum concentrations of 26 metabolites that fall into the categories of acyl carnitines, glycerophospholipids, biogenic amines, amino acids, and organic acids. At late lactation, fewer sets of metabolites were significantly affected by RFI grouping. Receiver operator curve analyses identified p-Hydroxyhippuric acid as the top biomarker at early lactation and acetylornithine at mid and late lactation. Models based on sets of serum metabolites in early, mid, and late lactation stages predicted RFI with a validation coefficient of determination of 0.54, 0.68, and 0.64, respectively. This study demonstrated the potential of circulatory serum metabolites as biomarkers and predictors of RFI in lactating dairy cows.

Protracted maternal malnutrition induces aberrant changes in maternal uterine artery hemodynamics and the metabolic profiles of the dam and neonate

Malnutritional stress during gestation is a well-established driver of metabolic disfunction in offspring. Extended exposure to malnutrition requires metabolic plasticity as the animal shifts toward a catabolic state. In this paper we demonstrate the influence of malnutrition throughout gestation on uterine artery hemodynamics and the metabolism of the dam and neonate. We hypothesized that gestational malnutrition reduces blood flow of the maternal uterine artery and regulates the metabolic profile of the dam and offspring. Further, the combination of these factors consequently influences the concentration of metabolites in the cerebrospinal fluid of the neonate at birth. To test our hypotheses, pregnant cows caring a single female fetus were assigned to treatments by age and body condition score to one of three individually-fed dietary treatments: Underfed, Control, or Overfed throughout gestation. Uterine blood flow was measured via transrectal Doppler ultrasonography in late gestation. Blood samples were collected from dams throughout gestation, and blood and cerebrospinal fluid were collected from neonates at birth to analyze concentration of metabolites. In the current report, we reveal that maternal malnutrition regulates uterine artery hemodynamics and the maternal metabolic profile throughout gestation. This is the first report to demonstrate that maternal undernutrition leads to an increase in the concentration of urea nitrogen in neonates. Finally, a concentration gradient of metabolites from the dam to neonatal cerebrospinal fluid was observed, which may have potential implications for central nervous system development. These findings not only illustrate the complexity of the maternal-to-fetal interaction required to support the growth of the fetus and homeostasis of the dam but also reveals a novel avenue for investigating the influence of protracted maternal malnutrition on metabolic pathway preferences in offspring. Moreover, these findings are of paramount importance in the development of intervention strategies for morbid neonates.

Unraveling Ruminant Feed Efficiency Through Metabolomics: A Systematic Review

BACKGROUND

Advancements in metabolomic technologies have revolutionized our understanding of feed efficiency (FE) in livestock, offering new pathways to enhance both profitability and sustainability in ruminant production.

METHODS

This review offers a critical and systematic evaluation of the metabolomics methods used to measure and assess FE in ruminants. We conducted a comprehensive search of PubMed, Web of Science, and Scopus databases, covering publications from 1971 to 2023. This review synthesizes findings from 71 studies that applied metabolomic approaches to uncover the biological mechanisms driving interindividual variations in FE across cattle, sheep, goats, and buffaloes.

RESULTS

Most studies focused on cattle and employed targeted metabolomics to identify key biomarkers, including amino acids, fatty acids, and other metabolites linked to critical pathways such as energy metabolism, nitrogen utilization, and muscle development. Despite promising insights, challenges remain, including small sample sizes, methodological inconsistencies, and a lack of validation studies, particularly for non-cattle species.

CONCLUSIONS

By leveraging state-of-the-art metabolomic methods, this review highlights the potential of metabolomics to provide cost-effective, non-invasive molecular markers for FE evaluation, paving the way for more efficient and sustainable livestock management. Future research should prioritize larger, species-specific studies with standardized methods to validate identified biomarkers and enhance practical applications in livestock production systems.

Development and validation of a model for early prediction of residual feed intake in beef cattle using plasma biomarkers

Identification of plasma biomarkers for feed efficiency in growing beef cattle offers a promising opportunity for developing prediction models to improve precision feeding strategies. However, these models must accurately predict feed efficiency at early stages of fattening. Our study aimed to evaluate the reliability of candidate biomarkers previously identified in late-fattening cattle when analysed during early fattening stages and to develop diet-specific prediction equations for residual feed intake (RFI). From a total of 364 Charolais bulls across seven cohorts, we selected 64 animals with extreme RFI values. The animals were fed either a corn‑ or grass-silage diets. These animals were chosen from four out of the available seven cohorts. Animals from three cohorts (24 high-RFI and 24 low-RFI, having a mean RFI difference of 1.48 kg/d) were used for biomarker confirmation and prediction model training. Animals from a fourth cohort (8 high-RFI and 8 low-RFI, having a mean RFI difference of 0.98 kg/d) were used for model external validation. Blood samples were collected at the beginning of the feed efficiency test (333 ± 20 days), and plasma underwent targeted metabolomic for 630 metabolites, natural abundance of 15N (δ15N), insulin, and IGF-1 analysis. Seven previously identified plasma biomarkers for RFI in late-fattening beef cattle still kept their capability for discriminating low and high RFI animals when analysed during early fattening stages (P < 0.05). Among these confirmed biomarkers, five were common for both grass- and corn-fed animals (creatinine, β-alanine, triglyceride TG18:0_34:2, symmetric dimethyl-arginine and phosphatidylcholine PC aa C30:2) while two were diet-specific (IGF-1 for grass silage-based diet, and isoleucine for corn silage-based diet. No new plasma biomarkers of RFI were identified at early-fattening stages (false discovery rate  > 0.05). Prediction models were developed based on seven confirmed RFI biomarkers analysed during early-fattening. Two logistic regression models incorporating creatinine and either IGF-1 (for grass silage-based diet) or PC aa C30:2 (for corn silage-based diet) effectively distinguished between high- and low-RFI animals with high sensitivity and specificity (area under the curve > 0.80). The biomarkers used in the models showed moderate to high repeatability between early and late fattening stages (0.45 < r < 0.65). The models were successfully externally validated, with more than 85% of animals from the fourth cohort correctly classified. Once validated in larger cohorts and utilising cost-effective and rapid analytical methods, these models could support precision feeding and breeding programmes, aiming to reduce the cost of raising beef cattle.

Study of Plasma Biochemistry and Plasma Metabolomics Differences in Montbéliard and Holstein Backcross and Holstein Heifers

Holstein cattle are the main breed of dairy cattle in China. However, given the high degree of purebred selection of Holstein cattle, Chinese dairy cattle are increasingly being characterized by poor disease resistance, poor quality, and declining fertility. In this study, using Montbéliard × Holstein cattle as females and Montbéliard bulls as males for backcross breeding, we sought to provide a reference for improving the quality and performance of Holstein cattle and enhancing the efficiency of dairy farming. On the basis of similar physiological status and age, we selected 24 Montbéliard and Holstein backcross heifers and 11 Holstein heifers fed the same formula for comparative analyses. Plasma samples collected for plasma biochemical index analyses revealed that the content of ALB and BUN in the Montbéliard and Holstein backcross heifers was 20.83% (31.62 g/L to 26.17 g/L) and 42.36% (6.89 mmol/L to 4.84 mmol/L) higher than in the Holsteins (p < 0.01). The ALB/GLB (0.90 to 0.60, p < 0.05) was significantly higher in Montbéliard and Holstein backcross heifers than in Holstein heifers. Similarly, the activity of CAT in the backcross heifers was 61.28% (4.29 U/mL to 2.66 U/mL) higher than that in the Holstein heifers (p < 0.05). Although the activity of GSH-Px in the backcross heifers also showed an increasing trend, the difference did not reach the level of statistical significance (p = 0.052). Compared with Holstein heifers, the concentrations of IgA, IgG, and IL-4 were elevated by 32.52% (24.90 μg/mL to 18.79 μg/mL, p < 0.01), 13.46% (234.32 μg/mL to 206.53 μg/mL, p < 0.01), and 14.59% (306.27 pg/mL to 267.28 pg/mL, p < 0.05), and the contents of IL-6 and TNF-α were decreased by 15.92% (215.71 pg/mL to 256.55 pg/mL, p < 0.01) and 32.17% (7.17 ng/mL to 10.57 ng/mL, p < 0.01) in the plasma of Montbéliard and Holstein backcross heifers. Among the experimental heifers, five animals from each of the two groups were selected for plasma metabolomic analysis based on untargeted liquid chromatography-mass spectrometry. A comparison of the differential metabolites between the two heifer breeds revealed an up-regulation of d-glucuronic acid, s-glutathionyl-l-cysteine, and oleic acid levels in the backcross cattle compared with those in the Holstein heifers. We speculate that changes in the levels of these metabolites may be associated with an enhancement of the anti-inflammatory, antioxidant, and immune systems in these backcross heifers. Collectively, our findings in this study indicate that compared with 12-month-old purebred Holstein heifers, Montbéliard and Holstein backcross heifers of the same age are characterized by higher antioxidant capacity and immunity.

Unravelling the Genetic Architecture of Serum Biochemical Indicators in Sheep

Serum biochemical indicators serve as vital proxies that reflect the physiological state and functions of different organs. The genetic parameters and molecular mechanisms underlying serum biochemical indicators of sheep (Ovis aries) have not been well understood. Therefore, the aim of the present study was to identify the genetic architecture and genomic loci underlying ten serum biochemical indicators in sheep, including alanine transaminase, aspartate transferase, lactate dehydrogenase, cholesterol, glucose, phosphorus, calcium, creatinine, urea and total protein levels. We implemented genetic parameter estimations and GWASs for each trait in 422 Akkaraman lambs. Overall, low to moderate heritability estimates were found in the range of 0.14-0.55. Additionally, low to high genetic correlations were observed among traits. In total, 23 SNP loci were associated with serum biochemical indicators leading to 19 genes. These were SPTA1, MGST2, CACUL1, IGFBP7, PARD3, PHB1, SLC15A5, TRIM35, RGS6, NUP93, CNTNAP2, SLC7A11, B3GALT5, DPP10, HST2ST1, NRP1, LRP1B, MAP3K9 and ENSOARG00020040484.1, as well as LOC101103187, LOC101117162, LOC105611309 and LOC101118029. To our knowledge, these data provide the first associations between SPTA1 and serum cholesterol and between ENSOARG00020040484.1 and serum glucose. The current findings provide a comprehensive inventory of the relationships between serum biochemical parameters, genetic variants and disease-relevant characteristics. This information may facilitate the identification of therapeutic targets and fluid biomarkers and establish a strong framework for comprehending the pathobiology of complex diseases as well as providing targets for sheep genetic improvement programs.

Assessment of milk metabolites as biomarkers for predicting feed efficiency in dairy sheep

Estimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine learning (ML) algorithms and a multivariate regression method. The orthogonal partial least squares algorithm outperformed other ML algorithms for FCR prediction in the scenarios using the complete milk metabolite signature (R2 = 0.62 ± 0.06) and the 26 selected features (R2 = 0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the multilayer feedforward artificial neural network (R2 = 0.18 ± 0.14) and extreme gradient boosting (R2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.

Some plasma biomarkers of residual feed intake in beef cattle remain consistent regardless of intake level

This study investigated whether plasma biomarkers of residual feed intake (RFI), identified under ad libitum feeding conditions in beef cattle, remained consistent during feed restriction. Sixty Charolais crossbred young bulls were divided into two groups for a crossover study. Group A was initially fed ad libitum (first test) and then restricted (second test) on the same diet, while Group B experienced the opposite sequence. Blood samples were collected from the 12 most divergent RFI animals in each group at the end of the first test and again after the second test. 12 plasma variables consistently increased, while three consistently decreased during feed restriction (FDR < 0.05). Only two metabolites, α-aminoadipic acid for Group A and 5-aminovaleric acid for Group B, were associated with RFI independent of feed intake level (FDR < 0.05), demonstrating moderate-to-high repeatability across feeding levels (intraclass correlation coefficient ≥ 0.59). Notably, both metabolites belong to the same metabolic pathway: lysine degradation. These metabolites consistently correlated with RFI, irrespective of fluctuations in feed intake, indicating a connection to individual metabolic processes influencing feed efficiency. These findings suggest that a portion of RFI phenotypic variance is inherent to an individual's metabolic efficiency beyond variations in feed intake.

Analyses of plasma metabolites using a high performance four-channel CIL LC-MS method and identification of metabolites associated with enteric methane emissions in beef cattle

Reducing enteric methane (one greenhouse gas) emissions from beef cattle not only can be beneficial in reducing global warming, but also improve efficiency of nutrient utilization in the production system. However, direct measurement of enteric methane emissions on individual cattle is difficult and expensive. The objective of this study was to detect plasma metabolites that are associated with enteric methane emissions in beef cattle. Average enteric methane emissions (CH4) per day (AVG_DAILYCH4) for each individual cattle were measured using the GreenFeed emission monitoring (GEM) unit system, and beef cattle with divergent AVG_DAILYCH4 from Angus (n = 10 for the low CH4 group and 9 for the high CH4 group), Charolais (n = 10 for low and 10 for = high), and Kinsella Composite (n = 10 for low and 10 for high) populations were used for plasma metabolite quantification and metabolite-CH4 association analyses. Blood samples of these cattle were collected near the end of the GEM system tests and a high performance four-channel chemical isotope labeling (CIL) liquid chromatography (LC) mass spectrometer (MS) method was applied to identify and quantify concentrations of metabolites. The four-channel CIL LC-MS method detected 4235 metabolites, of which 1105 were found to be significantly associated with AVG_DAILYCH4 by a t-test, while 1305 were significantly associated with AVG_DAILYCH4 by a regression analysis at p<0.05. Both the results of the t-test and regression analysis revealed that metabolites that were associated with enteric methane emissions in beef cattle were largely breed-specific whereas 4.29% to 6.39% CH4 associated metabolites were common across the three breed populations and 11.07% to 19.08% were common between two breed populations. Pathway analyses of the CH4 associated metabolites identified top enriched molecular processes for each breed population, including arginine and proline metabolism, arginine biosynthesis, butanoate metabolism, and glutathione metabolism for Angus; beta-alanine metabolism, pyruvate metabolism, glycolysis / gluconeogenesis, and citrate cycle (TCA cycle) for Charolais; phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arginine biosynthesis, and arginine and proline metabolism for Kinsella Composite. The detected CH4 associated metabolites and enriched molecular processes will help understand biological mechanisms of enteric methane emissions in beef cattle. The detected CH4 associated plasma metabolites will also provide valuable resources to further characterize the metabolites and verify their utility as biomarkers for selection of cattle with reduced methane emissions.

Revealing the developmental characterization of rumen microbiome and its host in newly received cattle during receiving period contributes to formulating precise nutritional strategies

BACKGROUND

Minimizing mortality losses due to multiple stress and obtaining maximum performance are the production goals for newly received cattle. In recent years, vaccination and metaphylaxis treatment significantly decreased the mortality rate of newly received cattle, while the growth block induced by treatment is still obvious. Assessment of blood metabolites and behavior monitoring offer potential for early identification of morbid animals. Moreover, the ruminal microorganisms' homeostasis is a guarantee of beef steers' growth and health. The most critical period for newly received cattle is the first-month post-transport. Therefore, analyzing rumen metagenomics, rumen metabolomics, host metabolomics, and their interaction during receiving period (1 day before transport and at days 1/4, 16, and 30 after transport) is key to revealing the mechanism of growth retardation, and then to formulating management and nutritional practices for newly received cattle.

RESULTS

The levels of serum hormones (COR and ACTH), and pro-inflammatory factors (IL-1β, TNF-α, and IL-6) were highest at day 16, and lowest at day 30 after arrival. Meanwhile, the antioxidant capacity (SOD, GSH-Px, and T-AOC) was significantly decreased at day 16 and increased at day 30 after arrival. Metagenomics analysis revealed that rumen microbes, bacteria, archaea, and eukaryota had different trends among the four different time points. At day 16 post-transport, cattle had a higher abundance of ruminal bacteria and archaea than those before transport, but the eukaryote abundance was highest at day 30 post-transport. Before transport, most bacteria were mainly involved in polysaccharides digestion. At day 4 post-transport, the most significantly enriched KEGG pathways were nucleotide metabolism (pyrimidine metabolism and purine metabolism). At day 16 post-transport, the energy metabolism (glycolysis/gluconeogenesis, pyruvate metabolism) and ruminal contents of MCP and VFAs were significantly increased, but at the same time, energy loss induced by methane yields (Methanobrevibacter) together with pathogenic bacteria (Saccharopolyspora rectivirgula) were also significantly increased. At this time, the most upregulated ruminal L-ornithine produces more catabolite polyamines, which cause oxidative stress to rumen microbes and their host; the most downregulated ruminal 2',3'-cAMP provided favorable growth conditions for pathogenic bacteria, and the downregulated ruminal vitamin B6 metabolism and serum PC/LysoPC disrupt immune function and inflammation reaction. At day 30 post-transport, the ruminal L-ornithine and its catabolites (mainly spermidine and 1,3-propanediamine) were decreased, and the serum PC/LysoPC and 2',3'-cNMPs pools were increased. This is also consistent with the changes in redox, inflammation, and immune status of the host.

CONCLUSIONS

This study provides new ideas for regulating the health and performance of newly received cattle during the receiving period. The key point is to manage the newly received cattle about day 16 post-transport, specifically to inhibit the production of methane and polyamines, and the reproduction of harmful bacteria in the rumen, therefore improving the immunity and performance of newly received cattle. Video Abstract.

Combined transcriptome and metabolome analysis reveal key regulatory genes and pathways of feed conversion efficiency of oriental river prawn Macrobrachium nipponense

BACKGROUND

Oriental river prawn Macrobrachium nipponense is an economically important aquaculture species in China, Japan, and Vietnam. In commercial prawn farming, feed cost constitutes about 50 to 65% of the actual variable cost. Improving feed conversion efficiency in prawn culture will not only increase economic benefit, but also save food and protect the environment. The common indicators used for feed conversion efficiency include feed conversion ratio (FCR), feed efficiency ratio (FER), and residual feed intake (RFI). Among these, RFI is much more suitable than FCR and FER during the genetic improvement of feed conversion efficiency for aquaculture species.

RESULTS

In this study, the transcriptome and metabolome of hepatopancreas and muscle of M. nipponense from high RFI low RFI groups, which identified after culture for 75 days, were characterized using combined transcriptomic and metabolomic analysis. A total of 4540 differentially expressed genes (DEGs) in hepatopancreas, and 3894 DEGs in muscle were identified, respectively. The DEGs in hepatopancreas were mainly enriched in KEGG pathways including the metabolism of xenobiotics by cytochrome P450 (down-regulated), fat digestion and absorption (down-regulated) and aminoacyl-tRNA biosynthesis (up-regulated), etc. The DEGs in muscle were mainly enriched in KEGG pathways including the protein digestion and absorption (down-regulated), glycolysis/gluconeogenesis (down-regulated), and glutathione metabolism (up-regulated), etc. At the transcriptome level, the RFI of M. nipponense was mainly controlled in biological pathways such as the high immune expression and the reduction of nutrients absorption capacity. A total of 445 and 247 differently expressed metabolites (DEMs) were identified in the hepatopancreas and muscle, respectively. At the metabolome level, the RFI of M. nipponense was affected considerably by amino acid and lipid metabolism.

CONCLUSIONS

M. nipponense from higher and lower RFI groups have various physiological and metabolic capability processes. The down-regulated genes, such as carboxypeptidase A1, 6-phosphofructokinase, long-chain-acyl-CoA dehydrogenase, et. al., in digestion and absorption of nutrients, and the up-regulated metabolites, such as aspirin, lysine, et. al., in response to immunity could be potential candidate factors contributed to RFI variation for M. nipponense. Overall, these results would provide new insights into the molecular mechanism of feed conversion efficiency and assist in selective breeding to improve feed conversion efficiency in M. nipponense.

Serum metabolic profile and metabolome genome-wide association study in chicken

BACKGROUND

Chickens provide globally important livestock products. Understanding the genetic and molecular mechanisms underpinning chicken economic traits is crucial for improving their selective breeding. Influenced by a combination of genetic and environmental factors, metabolites are the ultimate expression of physiological processes and can provide key insights into livestock economic traits. However, the serum metabolite profile and genetic architecture of the metabolome in chickens have not been well studied.

RESULTS

Here, comprehensive metabolome detection was performed using non-targeted LC-MS/MS on serum from a chicken advanced intercross line (AIL). In total, 7,191 metabolites were used to construct a chicken serum metabolomics dataset and to comprehensively characterize the serum metabolism of the chicken AIL population. Regulatory loci affecting metabolites were identified in a metabolome genome-wide association study (mGWAS). There were 10,061 significant SNPs associated with 253 metabolites that were widely distributed across the entire chicken genome. Many functional genes affect metabolite synthesis, metabolism, and regulation. We highlight the key roles of TDH and AASS in amino acids, and ABCB1 and CD36 in lipids.

CONCLUSIONS

We constructed a chicken serum metabolite dataset containing 7,191 metabolites to provide a reference for future chicken metabolome characterization work. Meanwhile, we used mGWAS to analyze the genetic basis of chicken metabolic traits and metabolites and to improve chicken breeding.

Plasma and milk metabolomics in lactating sheep divergent for feed efficiency

Enhancing the ability of animals to convert feed into meat or milk by optimizing feed efficiency (FE) has become a priority in livestock research. Although untargeted metabolomics is increasingly used in this field and may improve our understanding of FE, no information in this regard is available in dairy ewes. This study was conducted to (1) discriminate sheep divergent for FE and (2) provide insights into the physiological mechanisms contributing to FE through high-throughput metabolomics. The ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS) technique was applied to easily accessible animal fluids (plasma and milk) to assess whether their metabolome differs between high- and low-feed efficient lactating ewes (H-FE and L-FE groups, respectively; 8 animals/group). Blood and milk samples were collected on the last day of the 3-wk period used for FE estimation. A total of 793 features were detected in plasma and 334 in milk, with 100 and 38 of them, respectively, showing differences between H-FE and L-FE. The partial least-squares discriminant analysis separated both groups of animals regardless of the type of sample. Plasma allowed the detection of a greater number of differential features; however, results also supported the usefulness of milk, more easily accessible, to discriminate dairy sheep divergent for FE. Regarding pathway analysis, nitrogen metabolism (either anabolism or catabolism) seemed to play a central role in FE, with plasma and milk consistently indicating a great impact of AA metabolism. A potential influence of pathways related to energy/lipid metabolism on FE was also observed. The variable importance in the projection plot revealed 15 differential features in each matrix that contributed the most for the separation in H-FE and L-FE, such as l-proline and phosphatidylcholine 20:4e in plasma or l-pipecolic acid and phosphatidylethanolamine (18:2) in milk. Overall, untargeted metabolomics provided valuable information into metabolic pathways that may underlie FE in dairy ewes, with a special relevance of AA metabolism in determining this complex phenotype in the ovine. Further research is warranted to validate these findings.

GWAS and genetic and phenotypic correlations of plasma metabolites with complete blood count traits in healthy young pigs reveal implications for pig immune response

Introduction: In this study estimated genetic and phenotypic correlations between fifteen complete blood count (CBC) traits and thirty-three heritable plasma metabolites in young healthy nursery pigs. In addition, it provided an opportunity to identify candidate genes associated with variation in metabolite concentration and their potential association with immune response, disease resilience, and production traits.

Methods: The blood samples were collected from healthy young pigs and Nuclear Magnetic Resonance (NMR) was used to quantify plasma metabolites. CBC was determined using the ADVIA® 2120i Hematology System. Genetic correlations of metabolite with CBC traits and single step genome-wide association study (ssGWAS) were estimated using the BLUPF90 programs.

Results: Results showed low phenotypic correlation estimates between plasma metabolites and CBC traits. The highest phenotypic correlation was observed between lactic acid and plasma basophil concentration (0.36 ± 0.04; p &lt; 0.05). Several significant genetic correlations were found between metabolites and CBC traits. The plasma concentration of proline was genetically positively correlated with hemoglobin concentration (0.94 ± 0.03; p &lt; 0.05) and L-tyrosine was negatively correlated with mean corpuscular hemoglobin (MCH; −0.92 ± 0.74; p &lt; 0.05). The genomic regions identified in this study only explained a small percentage of the genetic variance of metabolites levels that were genetically correlated with CBC, resilience, and production traits.

Discussion: The results of this systems approach suggest that several plasma metabolite phenotypes are phenotypically and genetically correlated with CBC traits, suggesting that they may be potential genetic indicators of immune response following disease challenge. Genomic analysis revealed genes and pathways that might interact to modulate CBC, resilience, and production traits.

The Duck RXRA Gene Promotes Adipogenesis and Correlates with Feed Efficiency

BACKGROUND

The accumulation of fat in ducks is the main cause of low feed efficiency and metabolic diseases in ducks. Retinoic acid X receptor alpha (RXRA) is a member of the nuclear receptor superfamily involved in lipid, glucose, energy, and hormone metabolism. The effect of the RXRA gene on lipid metabolism in duck preadipocytes (DPACs) and the relationship between SNPs and the feed efficiency traits of ducks are unclear.

METHODS

qRT-PCR and Western blotting analyses were used to detect changes in mRNA and protein in cells. Intracellular triglycerides (TGs) were detected using an ELISA kit. A general linear model analysis was used to determine the association between RXRA SNPs and feed efficiency.

RESULTS

The duck RXRA gene was highly expressed on the fourth day of DPAC differentiation. The RXRA gene increased the content of fat and TG in DPACs and promoted the expression of cell differentiation genes; g.5,952,667 correlated with average daily feed intake (ADFI), residual feed intake (RFI), and feed conversion ratio (FCR).

CONCLUSIONS

Duck RXRA can accelerate fat accumulation, and the polymorphism of the RXRA gene is closely related to feed efficiency, which provides basic data for breeding high feed efficiency ducks.

Characteristics of growth, carcass and meat quality of sheep with different feed efficiency phenotypes

The objective was to evaluate the performance, carcass and meat quality of 40 lambs classified by RFI (residual feed intake) and RIG (residual intake and gain). Dry matter intake (DMI) was recorded to calculate the RFI and RIG, classified as efficient, moderately or inefficient. After the confinement period, they were slaughtered and the carcass and meat quality were determined. The efficient animals had DMI scores of 0.700 RFI and 0.400 kg/d RIG, lower than the inefficient ones with similar weight gain. The RFI efficient animals showed greater shear force, without effect in the RIG classification. In general, the variables analyzed were not influenced by RFI or RIG. Efficiency measures do not affect the carcass and meat quality of sheep, but they do have the advantage of identifying animals with lower feed consumption, making the system more efficient. However, as the dataset is limited to fully assess the effects, this manuscript can be used as preliminary results for future studies.

Comparative Analysis of the Composition of Fatty Acids and Metabolites between Black Tibetan and Chaka Sheep on the Qinghai-Tibet Plateau

The objective of this study was to investigate and compare fatty acids and metabolites in the longissimus dorsi muscle between Black Tibetan and Chaka sheep grazing in a highly saline environment. A total of eight castrated sheep (14 months old) with similar body weights (25 ± 2.2 kg) were selected. The experimental treatments included Black Tibetan (BT) and Chaka sheep (CK) groups, and each group had four replications. The experiment lasted for 20 months. All sheep grazed in a highly saline environment for the whole experimental period and had free access to water. The results showed that the diameter (42.23 vs. 51.46 μm), perimeter (131.78 vs. 166.14 μm), and area of muscle fibers (1328.74 vs. 1998.64 μm2) were smaller in Chaka sheep than in Black Tibetan sheep. The ash content in the longissimus dorsi was lower in Chaka sheep than in Black Tibetan sheep (p = 0.010), and the contents of dry matter (DM), ether extract (EE), and crude protein (CP) in the longissimus dorsi showed no differences (p > 0.05). For fatty acids, the proportions of C10:0, C15:0, and tC18:1 in the longissimus dorsi were higher in Chaka sheep than in Black Tibetan sheep (p < 0.05). However, all other individual fatty acids were similar among treatments, including saturated fatty acids (SFAs), unsaturated fatty acids (UFAs), monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs), and the ratios of n-6 PUFAs to n-3 PUFAs and PUFAs to SFAs (p > 0.05). A total of 65 biomarkers were identified between the two breeds of sheep. Among these metabolites, 40 metabolic biomarkers were upregulated in the CK group compared to the BT group, and 25 metabolites were downregulated. The main metabolites include 30 organic acids, 9 amino acids, 5 peptides, 4 amides, 3 adenosines, 2 amines, and other compounds. Based on KEGG analysis, eight pathways, namely, fatty acid biosynthesis, purine metabolism, the biosynthesis of unsaturated fatty acids, renin secretion, the regulation of lipolysis in adipocytes, neuroactive ligand−receptor interaction, the cGMP-PKG signaling pathway, and the cAMP signaling pathway, were identified as significantly different pathways. According to the results on fatty acids and metabolites, upregulated organic acid and fatty acid biosynthesis increased the meat quality of Chaka sheep.

The successful use of -omic technologies to achieve the 'One Health' concept in meat producing animals

Human health and wellbeing are closely linked to healthy domestic animals, a vital wildlife, and an intact ecosystem. This holistic concept is referred to as 'One Health'. In this review, we provide an overview of the potential and the challenges for the use of modern -omics technologies, especially transcriptomics and proteomics, to implement the 'One Health' idea for food-producing animals. These high-throughput studies offer opportunities to find new potential molecular biomarkers to monitor animal health, detect pharmacological interventions and evaluate the wellbeing of farm animals in modern intensive livestock systems.

Evaluating Starter Feeding on Ruminal Function in Yak Calves: Combined 16S rRNA Sequencing and Metabolomics

For young ruminants, starter feeding can effectively facilitate the growth and development of rumen in ruminants, but the development of rumen is an important physiological challenge as it remains unclear for the mechanism of starter feeding stimulating. In this study, we performed an analysis of ruminal microbiota and their metabolites in yak calves to explore how the ruminal microbiota and their metabolites stimulate the ruminal function. This study associated 16S rRNA sequencing with liquid chromatography-mass spectrometry (LC-MS)-based metabolomics to evaluate the effects of starter feeding on ruminal microbiota diversity and metabolites in yak calves. We designed the experiment using 20 yak calves that were assigned equally into 2 groups, based on feeding milk replacer; the control (RA) group was fed with alfalfa hay while the treatment (RAS) group was fed with alfalfa hay and starter. After the experiment, we investigated the ruminal microbiota and metabolites through 16S rRNA sequencing and LC-MS-based metabolomics. During the preweaning period, the RAS group significantly promoted the growth performance and ruminal development in yak calves, including increases in body weight, chest girth, and development of rumen (P &lt; 0.05). The RAS group increased the relative abundance of Bacteroidota, Proteobacteria, Chloroflexi, Synergistota, and Spirochaetota and decreased the abundance of Firmicutes, Desulfobacterota, Actinobacteriota, and Actinobacteriota at the phylum level (P &lt; 0.05). At the genus level, the ruminal content of the RAS group was significantly enriched for Rikenellaceae_RC9_gut_group and Ruminococcus, while depleted for Prevotella, Christensenellaceae_R-7_group, and NK4A214_group (P &lt; 0.05). A total of 37 metabolites were identified between the RA group and the RAS group, of which 15 metabolites were upregulated and 22 metabolites were downregulated compared with the RA group. Metabolic pathway analyses indicated that upregulated the metabolites of the RAS group yak calves were related to carbohydrate metabolism, ubiquinone, and other terpenoid-quinone biosynthesis, while the downregulated metabolic pathway was relevant to xenobiotic biodegradation, metabolism, and nucleotide metabolism. In summary, starter feeding before weaning significantly increased the dry matter intake and body weight of yak calves, changed the diversity and abundance of ruminal microbiota, and positively regulated the good development of ruminal morphology and function, providing an important basis for high-quality cultivation and the nutritional level of nutrition of yak calves in the Qinghai Tibet plateau. This study is based on the availability of 16S rRNA sequencing and LC-MS-based metabolomics in clarifying the function of starter feeding in the yak calves.

Metabolomics Reveals the Effects of High Dietary Energy Density on the Metabolism of Transition Angus Cows

Simple Summary

The increase in the metabolic demand and the dramatically decreased feed intake of cows around parturition often cause a negative energy balance status in cows, which can cause metabolic disorders. Before parturition, dry matter intake of cows starts to decline, and this decline is practically unavoidable. Therefore, increasing the energy density of the diet is extremely important. We used untargeted metabolomics to reveal the effect of high dietary energy density on body metabolism and explore whether it can alleviate negative energy balance. Our research shows that feeding a high-energy diet could significantly improve antioxidant capacity, maintain phosphatidylcholine homeostasis and reduce the negative energy balance of cows by regulating lipid mobilization, muscle mobilization, and protein turnover.

Abstract

The diet energy level plays a vital role in the energy balance of transition cows. We investigated the effects of high dietary energy density on body metabolism. Twenty multiparous Angus cows were randomly assigned to two treatment groups (10 cows/treatment), one receiving a high-energy (HE) diet (NEm = 1.67 Mcal/kg of DM) and the other administered a control (CON) diet (NEm = 1.53 Mcal/kg of DM). The results indicated that feeding a high-energy diet resulted in higher plasma glucose concentration and lower concentrations of plasma NEFA and BHBA on d 14 relative to calving in the HE-fed cows compared to the CON-fed ones. The postpartum plasma levels of T-AOC were lower in cows that received the CON diet than in cows in the HE group, while the concentration of malondialdehyde (MDA) showed an opposite trend. Among the 51 significantly different metabolites, the concentrations of most identified fatty acids decreased in HE cows. The concentrations of inosine, glutamine, and citric acid were higher in HE-fed cows than in CON-fed cows. Enrichment analysis revealed that linoleic acid metabolism, valine, leucine as well as isoleucine biosynthesis, and glycerophospholipid metabolism were significantly enriched in the two groups.

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.

Evaluation of the Links between Lamb Feed Efficiency and Rumen and Plasma Metabolomic Data

Feed efficiency is one of the keystones that could help make animal production less costly and more environmentally friendly. Residual feed intake (RFI) is a widely used criterion to measure feed efficiency by regressing intake on the main energy sinks. We investigated rumen and plasma metabolomic data on Romane male lambs that had been genetically selected for either feed efficiency (line rfi−) or inefficiency (line rfi+). These investigations were conducted both during the growth phase under a 100% concentrate diet and later on under a mixed diet to identify differential metabolite expression and to link it to biological phenomena that could explain differences in feed efficiency. Nuclear magnetic resonance (NMR) data were analyzed using partial least squares discriminant analysis (PLS-DA), and correlations between metabolites’ relative concentrations were estimated to identify relationships between them. High levels of plasma citrate and malate were associated with genetically efficient animals, while high levels of amino acids such as L-threonine, L-serine, and L-leucine as well as beta-hydroxyisovalerate were associated with genetically inefficient animals under both diets. The two divergent lines could not be discriminated using rumen metabolites. Based on phenotypic residual feed intake (RFI), efficient and inefficient animals were discriminated using plasma metabolites determined under a 100% concentrate diet, but no discrimination was observed with plasma metabolites under a mixed diet or with rumen metabolites regardless of diet. Plasma amino acids, citrate, and malate were the most discriminant metabolites, suggesting that protein turnover and the mitochondrial production of energy could be the main phenomena that differ between efficient and inefficient Romane lambs.

The metabolomics profile of growth rate in grazing beef cattle

This study aimed to determine the relationship between the metabolome and changes in growth rate (i.e., liveweight change, LWC) and molasses-lick block supplement intake (MLB) of grazing cattle. Weaner beef cattle were fed for 220 days with a sequence of feed types and blood samples, growth rate, and supplement intake were taken on five points in time. The relative abundance (RA) of plasma metabolites were determined using proton nuclear magnetic resonance (NMR). Sixty-four per cent of the metabolites identified were associated with LWC but only 26% with MLB intake (P < 0.05). Periods with faster growth rate showed high availability of amino acids (i.e., valine, leucine, isoleucine, phenylalanine and tyrosine), acetate, and 3-hydroxybutyrate. Periods with lower growth rate were associated with high RA of lipids, choline and acetate. The metabolic profile of individual animals during a period of compensatory growth (after periods of poor performance) showed that high-performing animals were characterised by lower RA of amino acids (i.e., valine, leucine, isoleucine, methylhistidine), creatinine, creatine, pyruvate, 3-hydroxybutyrate, and acetyl groups. It is speculated that high-performing animals have faster uptake of these metabolites from the bloodstream. Cattle growth rate over time was associated with their metabolome which could be used to ensure that the availability of certain metabolites promoting growth is tailored in feed supplements to improve production.

Evaluation of Ingestive Behavior, Ruminal and Blood Parameters, Performance, and Thermography as a Phenotypic Divergence Markers of Residual Feed Intake in Rearing Dairy Heifers

Simple Summary

The selection of highly efficient animals will support meeting the world’s future demand for products and food of animal origin. Thus, the identification of efficient animals and an understanding of the mechanisms inherent to this efficiency is fundamental for the progress of breeding systems. In the present study, we identify highly efficient animals for residual feed intake in dairy heifers. This animal category is unexplored in relation to this index. We utilized the classical parameters evaluated in cattle of different ages to carry out the study on these animals.

Abstract

The objectives of this study were: (1) to identify and rank phenotypically divergent animals for residual feed intake (RFI) regarding their efficiency (high: HE or low: LE); (2) to evaluate their relationships with ingestive behavior, ruminal and blood parameters, performance, and infrared thermography; and (3) to determine if such measurements can be used as feed efficiency markers in rearing dairy heifers. Thirty-eight heifers, 143 d ± 4 (Mean ± SD) of age and 108.7 kg ± 17.9 of body weight were used. The animals were fed with a total mixed ration during the 91 d of the trial. A phenotypic divergence of DMI for RFI was observed between −0.358 and 0.337 kg/d for HE and LE, respectively. Dry matter intake (DMI) was lower in the HE (2.5 kg DMI/d vs. 3.1 kg DMI/d), as was the number of visits to the feed bin with consumption (59 vs. 71). Feed intake was the best predictor of said divergence. Water intake and number of visits to the feed bin were presented moderate correlations with RFI. The ruminal fermentation variables, blood metabolites, blood hormones (such as the other ingestive behavior variables), and infrared thermography were not able to accurately predict HE or LE animals.

Common and diet-specific metabolic pathways underlying residual feed intake in fattening Charolais yearling bulls

Residual feed intake (RFI) is one of the preferred traits for feed efficiency animal breeding. However, RFI measurement is expensive and time-consuming and animal ranking may depend on the nature of the diets. We aimed to explore RFI plasma biomarkers and to unravel the underlying metabolic pathways in yearling bulls fed either a corn-silage diet rich in starch (corn diet) or a grass-silage diet rich in fiber (grass diet). Forty-eight extreme RFI animals (Low-RFI, n = 24, versus High-RFI, n = 24, balanced per diet) were selected from a population of 364 Charolais bulls and their plasma was subjected to a targeted LC-MS metabolomic approach together with classical metabolite and hormonal plasma analyses. Greater lean body mass and nitrogen use efficiency, and lower protein turnover were identified as common mechanisms underlying RFI irrespective of the diet. On the other hand, greater adiposity and plasma concentrations of branched-chain amino acids (BCAA) together with lower insulin sensitivity in High-RFI animals were only observed with corn diet. Conversely, greater plasma concentrations of BCAA and total triglycerides, but similar insulin concentrations were noted in efficient RFI cattle with grass diet. Our data suggest that there are diet-specific mechanisms explaining RFI differences in fattening Charolais yearling bulls.

Identification of candidate genes and enriched biological functions for feed efficiency traits by integrating plasma metabolites and imputed whole genome sequence variants in beef cattle

BACKGROUND

Feed efficiency is one of the key determinants of beef industry profitability and sustainability. However, the cellular and molecular background behind feed efficiency is largely unknown. This study combines imputed whole genome DNA variants and 31 plasma metabolites to dissect genes and biological functions/processes that are associated with residual feed intake (RFI) and its component traits including daily dry matter intake (DMI), average daily gain (ADG), and metabolic body weight (MWT) in beef cattle.

RESULTS

Regression analyses between feed efficiency traits and plasma metabolites in a population of 493 crossbred beef cattle identified 5 (L-valine, lysine, L-tyrosine, L-isoleucine, and L-leucine), 4 (lysine, L-lactic acid, L-tyrosine, and choline), 1 (citric acid), and 4 (L-glutamine, glycine, citric acid, and dimethyl sulfone) plasma metabolites associated with RFI, DMI, ADG, and MWT (P-value < 0.1), respectively. Combining the results of metabolome-genome wide association studies using 10,488,742 imputed SNPs, 40, 66, 15, and 40 unique candidate genes were identified as associated with RFI, DMI, ADG, and MWT (P-value < 1 × 10-5), respectively. These candidate genes were found to be involved in some key metabolic processes including metabolism of lipids, molecular transportation, cellular function and maintenance, cell morphology and biochemistry of small molecules.

CONCLUSIONS

This study identified metabolites, candidate genes and enriched biological functions/processes associated with RFI and its component traits through the integrative analyses of metabolites with phenotypic traits and DNA variants. Our findings could enhance the understanding of biochemical mechanisms of feed efficiency traits and could lead to improvement of genomic prediction accuracy via incorporating metabolite data.

Exploring Biological Impacts of Prenatal Nutrition and Selection for Residual Feed Intake on Beef Cattle Using Omics Technologies: A Review

Approximately 70% of the cost of beef production is impacted by dietary intake. Maximizing production efficiency of beef cattle requires not only genetic selection to maximize feed efficiency (i.e., residual feed intake (RFI)), but also adequate nutrition throughout all stages of growth and development to maximize efficiency of growth and reproductive capacity, even during gestation. RFI as a measure of feed efficiency in cattle has been recently accepted and used in the beef industry, but the effect of selection for RFI upon the dynamics of gestation has not been extensively studied, especially in the context of fluctuating energy supply to the dam and fetus. Nutrient restriction during gestation has been shown to negatively affect postnatal growth and development as well as fertility of beef cattle offspring. This, when combined with the genetic potential for RFI, may significantly affect energy partitioning in the offspring and subsequently important performance traits. In this review, we discuss: 1) the importance of RFI as a measure of feed efficiency and how it can affect other economic traits in beef cattle; 2) the influence of prenatal nutrition on physiological phenotypes in calves; 3) the benefits of investigating the interaction of genetic selection for RFI and prenatal nutrition; 4) how metabolomics, transcriptomics, and epigenomics have been employed to investigate the underlying biology associated with prenatal nutrition, RFI, or their interactions in beef cattle; and 5) how the integration of omics information is adding a level of deeper understanding of the genetic architecture of phenotypic traits in cattle.

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.

Dietary Energy Level Impacts the Performance of Donkeys by Manipulating the Gut Microbiome and Metabolome

Considerable evidence suggests that dietary energy levels and gut microbiota are pivotal for animal health and productivity. However, little information exists about the correlations among dietary energy level, performance, and the gut microbiota and metabolome of donkeys. The objective of this study was to investigate the mechanisms by which dietary energy content dictates the growth performance by modulating the intestinal microbiome and metabolome of donkeys. Thirty-six nine-month-old male Dezhou donkeys with similar body weights were randomly assigned to two groups fed low- or high-energy diets (LE or HE). The results showed that donkeys fed HE had increased (p < 0.05) the average daily gain (ADG) and feed efficiency (G/F) compared with those that received LE diet. The gut microbiota in both groups was dominated by the phyla Firmicutes and Bacteroidetes regardless of the dietary energy level. However, feeding HE to donkeys significantly decreased (p < 0.05) the ratio of Firmicutes to Bacteroidetes (F/B). Compared to the LE group, feeding HE specifically increased the abundances of unidentified_Prevotellaceae (p = 0.02) while decreasing the richness of unidentified_Ruminococcaceae (p = 0.05). Compared to the LE group, feeding the HE diet significantly (p < 0.05) upregulated certain metabolic pathways involving the aspartate metabolism and the urea cycle. In addition, the increased bacteria and metabolites in the HE-fed group exhibited a positive correlation with improved growth performance of donkeys. Taken together, feeding the HE diet increased the richness of Prevotellaceae and upregulated growth-related metabolic pathways, which may have contributed to the ameliorated growth performance of donkeys. Thus, it is a recommendable dietary strategy to feed HE diets to fattening donkeys for superior product performance and feed efficiency.

Heritability and genetic correlations of plasma metabolites of pigs with production, resilience and carcass traits under natural polymicrobial disease challenge

Metabolites in plasma of healthy nursery pigs were quantified using nuclear magnetic resonance. Heritabilities of metabolite concentration were estimated along with their phenotypic and genetic correlations with performance, resilience, and carcass traits in growing pigs exposed to a natural polymicrobial disease challenge. Variance components were estimated by GBLUP. Heritability estimates were low to moderate (0.11 ± 0.08 to 0.19 ± 0.08) for 14 metabolites, moderate to high (0.22 ± 0.09 to 0.39 ± 0.08) for 17 metabolites, and highest for l-glutamic acid (0.41 ± 0.09) and hypoxanthine (0.42 ± 0.08). Phenotypic correlation estimates of plasma metabolites with performance and carcass traits were generally very low. Significant genetic correlation estimates with performance and carcass traits were found for several measures of growth and feed intake. Interestingly the plasma concentration of oxoglutarate was genetically negatively correlated with treatments received across the challenge nursery and finisher (− 0.49 ± 0.28; P < 0.05) and creatinine was positively correlated with mortality in the challenge nursery (0.85 ± 0.76; P < 0.05). These results suggest that some plasma metabolite phenotypes collected from healthy nursery pigs are moderately heritable and genetic correlations with measures of performance and resilience after disease challenge suggest they may be potential genetic indicators of disease resilience.

Review: Markers and proxies to monitor ruminal function and feed efficiency in young ruminants

Developing the rumen's capacity to utilise recalcitrant and low-value feed resources is important for ruminant production systems. Early-life nutrition and management practices have been shown to influence development of the rumen in young animals with long-term consequences on their performance. Therefore, there has been increasing interest to understand ruminal development and function in young ruminants to improve feed efficiency, health, welfare, and performance of both young and adult ruminants. However, due to the small size, rapid morphological changes and low initial microbial populations of the rumen, it is difficult to study ruminal function in young ruminants without major invasive approaches or slaughter studies. In this review, we discuss the usefulness of a range of proxies and markers to monitor ruminal function and nitrogen use efficiency (a major part of feed efficiency) in young ruminants. Breath sulphide and methane emissions showed the greatest potential as simple markers of a developing microbiota in young ruminants. However, there is only limited evidence for robust indicators of feed efficiency at this stage. The use of nitrogen isotopic discrimination based on plasma samples appeared to be the most promising proxy for feed efficiency in young ruminants. More research is needed to explore and refine potential proxies and markers to indicate ruminal function and feed efficiency in young ruminants, particularly for neonatal ruminants.

Candidate serum metabolite biomarkers of residual feed intake and carcass merit in sheep

Mutton and lamb sales continue to grow globally at a rate of 5% per year. However, sheep farming struggles with low profit margins due to high feed costs and modest carcass yields. Selecting those sheep expected to convert feed efficiently and have high carcass merit, as early as possible in their life cycle, could significantly improve the profitability of sheep farming. Unfortunately, direct measurement of feed conversion efficiency (via residual feed intake [RFI]) and carcass merit is a labor-intensive and expensive procedure. Thus, indirect, marker-assisted evaluation of these traits has been explored as a means of reducing the cost of its direct measurement. One promising and potentially inexpensive route to discover biomarkers of RFI and/or carcass merit is metabolomics. Using quantitative metabolomics, we profiled the blood serum metabolome (i.e., the sum of all measurable metabolites) associated with sheep RFI and carcass merit and identified candidate biomarkers of these traits. The study included 165 crossbred ram-lambs that underwent direct measurement of feed consumption to determine their RFI classification (i.e., low vs. high) using the GrowSafe System over a period 40 d. Carcass merit was evaluated after slaughter using standardized methods. Prior to being sent to slaughter, one blood sample was drawn from each animal, and serum prepared and frozen at -80 °C to limit metabolite degradation. A subset of the serum samples was selected based on divergent RFI and carcass quality for further metabolomic analyses. The analyses were conducted using three analytical methods (nuclear magnetic resonance spectroscopy, liquid chromatography mass spectrometry, and inductively coupled mass spectrometry), which permitted the identification and quantification of 161 unique metabolites. Biomarker analyses identified three significant (P < 0.05) candidate biomarkers of sheep RFI (AUC = 0.80), seven candidate biomarkers of carcass yield grade (AUC = 0.77), and one candidate biomarker of carcass muscle-to-bone ratio (AUC = 0.74). The identified biomarkers appear to have roles in regulating energy metabolism and protein synthesis. These results suggest that serum metabolites could be used to categorize and predict sheep for their RFI and carcass merit. Further validation using a larger (3×) and more diverse cohort of sheep is required to confirm these findings.

Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls

Residual feed intake (RFI) is a feed efficiency measure commonly used in the livestock industry to identify animals that efficiently/inefficiently convert feed into meat or body mass. Selection for low-residual feed intake (LRFI), or feed efficient animals, is gaining popularity among beef producers due to the fact that LRFI cattle eat less and produce less methane per unit weight gain. RFI is a difficult and time-consuming measure to perform, and therefore a simple blood test that could distinguish high-RFI (HRFI) from LRFI animals (early on) would potentially benefit beef farmers in terms of optimizing production or selecting which animals to cull or breed. Using three different metabolomics platforms (nuclear magnetic resonance (NMR) spectrometry, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and inductively coupled plasma mass spectrometry (ICP-MS)) we successfully identified serum biomarkers for RFI that could potentially be translated to an RFI blood test. One set of predictive RFI biomarkers included formate and leucine (best for NMR), and another set included C4 (butyrylcarnitine) and LysoPC(28:0) (best for LC-MS/MS). These serum biomarkers have high sensitivity and specificity (AUROC > 0.85), for distinguishing HRFI from LRFI animals. These results suggest that serum metabolites could be used to inexpensively predict and categorize bovine RFI values. Further validation using a larger, more diverse cohort of cattle is required to confirm these findings.

Genomic Heritability and Genome-Wide Association Studies of Plasma Metabolites in Crossbred Beef Cattle

Metabolites, substrates or products of metabolic processes, are involved in many biological functions, such as energy metabolism, signaling, stimulatory and inhibitory effects on enzymes and immunological defense. Metabolomic phenotypes are influenced by combination of genetic and environmental effects allowing for metabolome-genome-wide association studies (mGWAS) as a powerful tool to investigate the relationship between these phenotypes and genetic variants. The objectives of this study were to estimate genomic heritability and perform mGWAS and in silico functional enrichment analyses for a set of plasma metabolites in Canadian crossbred beef cattle. Thirty-three plasma metabolites and 45,266 single nucleotide polymorphisms (SNPs) were available for 475 animals. Genomic heritability for all metabolites was estimated using genomic best linear unbiased prediction (GBLUP) including genomic breed composition as covariates in the model. A single-step GBLUP implemented in BLUPF90 programs was used to determine SNP P values and the proportion of genetic variance explained by SNP windows containing 10 consecutive SNPs. The top 10 SNP windows that explained the largest genetic variation for each metabolite were identified and mapped to detect corresponding candidate genes. Functional enrichment analyses were performed on metabolites and their candidate genes using the Ingenuity Pathway Analysis software. Eleven metabolites showed low to moderate heritability that ranged from 0.09 ± 0.15 to 0.36 ± 0.15, while heritability estimates for 22 metabolites were zero or negligible. This result indicates that while variations in 11 metabolites were due to genetic variants, the majority are largely influenced by environment. Three significant SNP associations were detected for betaine (rs109862186), L-alanine (rs81117935), and L-lactic acid (rs42009425) based on Bonferroni correction for multiple testing (family wise error rate <0.05). The SNP rs81117935 was found to be located within the Catenin Alpha 2 gene (CTNNA2) showing a possible association with the regulation of L-alanine concentration. Other candidate genes were identified based on additive genetic variance explained by SNP windows of 10 consecutive SNPs. The observed heritability estimates and the candidate genes and networks identified in this study will serve as baseline information for research into the utilization of plasma metabolites for genetic improvement of crossbred beef cattle.

Changes in the blood metabolome of Wagyu crossbred steers with time in the feedlot and relationships with marbling

Wagyu crossbred steers (n = 167) were used to (1) compare the metabolome of individual animals at two distant time-points (days 196 and 432) in a feedlot (this corresponded to 272 and 36 days before slaughter); and (2) determine relationships between the metabolome and marbling, and the effect of days in the feedlot (time-points) on these relationships. ¹H NMR spectroscopy followed by standard recoupling of variables analysis produced 290 features or 'peaks' from which 38 metabolites were identified. There was a positive correlation between the relative concentration (RC) at days 196 and 432 for 35 of 38 metabolites (P > 0.05). The RC of 21 metabolites mostly involved in muscle energy and glucose metabolism increased (P < 0.05) from day 196 to 432, and the RC of 13 metabolites mostly involved in lipid metabolism decreased (P < 0.05). There were 14 metabolites correlated with marbling including metabolites involved in energy and fat metabolism (glucose, propionate, 3-hydroxybutyrate, lipids). The relationship between marbling and the RC of metabolites was affected by time-point, being positive for 3-hydroxybutyrate and acetate (P < 0.05) at day 432 but not at day 196. The findings indicate that the blood metabolome in Wagyu crossbred steers changes with time in a feedlot. Notwithstanding, the metabolome has potential to predict marbling in Wagyu. The ability to predict marbling from the blood metabolome appears to be influenced by days in a feedlot and presumably the stage of development towards a mature body conformation.

Profile of serum lipid metabolites of one-week-old goat kids depending on the type of rearing

Background

Weaning of goat kids immediately after birth and feeding them on bovine or heat-treated caprine colostrum, referred to as snatching, is considered an effective control measure in some infectious diseases. The study was carried out in one-week-old goat kids to gain insight into the profile of lipid metabolites and to investigate the influence of snatching on kids’ metabolism. Fifty-two goat kids born to 23 female goats were included in the study – 22 kids were weaned immediately after birth and kept isolated from their mothers; 30 remaining kids were left with their mothers for next 3 weeks so that they could nurse on dams’ milk at will. Blood was collected at the age of 1 week and serum was obtained by centrifugation. The concentration of lipid metabolites was determined with mass spectrometry using a commercial MxP® Quant 500 kit (Biocrates Life Sciences AG, Innsbruck, Austria).

Results

Concentration of 240 lipid metabolites belonging to 10 lipid classes was above the limit of detection of the assay. These lipid metabolites were quantified and included in the analysis. Concentration of 2 lipid classes (acyl-alkyl-phosphatidylcholines and ceramides) and 31 lipid metabolites (14 triacylglycerols, 5 acyl-alkyl-phosphatidylcholines, 2 diacylphosphatidylcholines, 1 lyso-phosphatidylcholine, 5 ceramides, 2 sphingomyelins, and 2 cholesterol esters) differed significantly between the two groups of kids.

Conclusion

Snatching of kids results in reduction of serum concentration of lipid metabolites, however, the magnitude of this phenomenon does not seem to be sufficient to negatively affect kids’ health condition. This study is the first in which the broad set of lipid metabolites of young ruminants was quantified using the novel metabolomic assay MxP® Quant 500 kit.

Natural 15N abundance in specific amino acids indicates associations between transamination rates and residual feed intake in beef cattle

Improving the ability of animals to convert feed resources into food for humans is needed for more sustainable livestock systems. Genetic selection for animals eating less while maintaining their performance (i.e., low residual feed intake [RFI]) appears a smart strategy but its effectiveness relies on high-throughput animal phenotyping. Here, we explored plasma nitrogen (N) isotope ratios in an attempt to identify easily superior young bulls in terms of RFI. For this, 48 Charolais young bulls fed two contrasting diets (corn vs. grass silage diets) were selected from a larger population as extreme RFI animals (24 low-RFI vs. 24 high-RFI) and their plasma analyzed for natural ¹⁵N abundance (δ¹⁵N) in the whole protein (bulk protein) and in the individual protein-bound amino acids (PbAA). For the first time, we showed that the δ ¹⁵N in plasma bulk protein differed (P = 0.007) between efficient (low-RFI) and inefficient (high-RFI) cattle regardless of diet. Furthermore, most analyzed PbAA followed the same trend as the bulk protein, with lower (P < 0.05) δ ¹⁵N values in more efficient (low-RFI) compared with less efficient (high-RFI) cattle, again regardless of diet. The only three exceptions were Phe, Met, and Lys (P > 0.05) for which the first metabolic reaction before being catabolized does not involve transamination, a pathway known naturally to enrich AAs in ¹⁵N. The contrasted isotopic signatures across RFI groups only in those PbAA undergoing transamination are interpreted as differences in transamination rates and N-use efficiency between low- and high-RFI phenotypes. Natural isotopic N signatures in bulk proteins and specific PbAA can be proposed as biomarkers of RFI in growing beef cattle fed different diets. However, the current study cannot delineate whether this effect only occurs post-absorption or to some extent also in the rumen. Our data support the conclusion that most efficient cattle in terms of RFI upregulate N conservation mechanisms compared with less efficient cattle and justify future research on this topic.

Transforming the Adaptation Physiology of Farm Animals through Sensors

Despite recent scientific advancements, there is a gap in the use of technology to measure signals, behaviors, and processes of adaptation physiology of farm animals. Sensors present exciting opportunities for sustained, real-time, non-intrusive measurement of farm animal behavioral, mental, and physiological parameters with the integration of nanotechnology and instrumentation. This paper critically reviews the sensing technology and sensor data-based models used to explore biological systems such as animal behavior, energy metabolism, epidemiology, immunity, health, and animal reproduction. The use of sensor technology to assess physiological parameters can provide tremendous benefits and tools to overcome and minimize production losses while making positive contributions to animal welfare. Of course, sensor technology is not free from challenges; these devices are at times highly sensitive and prone to damage from dirt, dust, sunlight, color, fur, feathers, and environmental forces. Rural farmers unfamiliar with the technologies must be convinced and taught to use sensor-based technologies in farming and livestock management. While there is no doubt that demand will grow for non-invasive sensor-based technologies that require minimum contact with animals and can provide remote access to data, their true success lies in the acceptance of these technologies by the livestock industry.

Carbohydrate and amino acid metabolism and oxidative status in Holstein heifers precision-fed diets with different forage to concentrate ratios

Previous work led to the proposal that the precision feeding of a high-concentrate diet may represent a potential method with which to enhance feed efficiency (FE) when rearing dairy heifers. However, the physiological and metabolic mechanisms underlying this approach remain unclear. This study used metabolomics analysis to investigate the changes in plasma metabolites of heifers precision-fed diets containing a wide range of forage to concentrate ratios. Twenty-four half-sib Holstein heifers, with a similar body condition, were randomly assigned into four groups and precision fed with diets containing different proportions of concentrate (20%, 40%, 60% and 80% based on DM). After 28 days of feeding, blood samples were collected 6 h after morning feeding and gas chromatography time-of-flight/MS was used to analyze the plasma samples. Parameters of oxidative status were also determined in the plasma. The FE (after being corrected for gut fill) increased linearly (P < 0.01) with increasing level of dietary concentrate. Significant changes were identified for 38 different metabolites in the plasma of heifers fed different dietary forage to concentrate ratios. The main pathways showing alterations were clustered into those relating to carbohydrate and amino acid metabolism; all of which have been previously associated with FE changes in ruminants. Heifers fed with a high-concentrate diet had higher (P < 0.01) plasma total antioxidant capacity and superoxide dismutase but lower (P ≤ 0.02) hydroxyl radical and hydrogen peroxide than heifers fed with a low-concentrate diet, which might indicate a lower plasma oxidative status in the heifers fed a high-concentrate diet. Thus, heifers fed with a high-concentrate diet had higher FE and antioxidant capacity but a lower plasma oxidative status as well as changed carbohydrate and amino acid metabolism. Our findings provide a better understanding of how forage to concentrate ratios affect FE and metabolism in the precision-fed growing heifers.

Impact of feeding regimens on the composition of gut microbiota and metabolite profiles of plasma and feces from Mongolian sheep

Mongolian sheep are an indigenous ruminant raised for wool and meat production in China. The gut microbial community plays an important role in animal performance and metabolism. The objective of this study was to investigate the effects of two feeding regimens on the diversity and composition of gut microbiota and metabolite profiles of feces and plasma from Mongolian sheep. A total of 20 Mongolian sheep were assigned to one of two feeding regimens: free grazing (FG) and barn confinement (BC). When samples were collected, the average live weights of the sheep were 31.28 ± 1.56 kg and 34.18 ± 1.87 kg for the FG and BC groups, respectively. At the genus level, the FG group showed higher levels of Bacteroides, RC9_gut_group, Alistipes, Phocaeicola, Barnesiella, and Oscillibacter, and lower levels of Succinivibrio, Treponema, and Prevotella, compared to the BC group. The butyric acid content in feces was lower in the FG group (P > 0.05). Higher levels of palmitic acid, oleic acid, alpha-linolenic acid, L-carnitine, L-citrulline, and L-histidine, and lower levels of L-tyrosine, L-phenylalanine, and L-kynurenine were found in the plasma of the FG sheep. Moreover, there were substantial associations between several gut microbiota genera and alterations in feces and plasma metabolites especially those involved in the metabolism of butyric acid, linolenic acid, and L-tyrosine. Feeding regimens can not only influence the composition of gut microbiota, but also alter metabolic homeaostasis in sheep.

Blood Plasma Metabolomics Predicts Pregnancy in Holstein Cattle Transferred with Fresh and Vitrified/Warmed Embryos Produced in Vitro

Metabolomics may identify biomarkers in blood that differentiate pregnant from open embryo recipients. Fresh and vitrified/warmed, in vitro-produced embryos were transferred to Holstein recipients (discovery group). Recipient blood plasma collected on Day-0 (estrus) and Day-7 (before embryo transfer) were analyzed by nuclear magnetic resonance (N = 36 metabolites quantified). Metabolites whose concentrations differed between open and pregnant recipients were analyzed [(P < 0.05); false discovery rate (FDR) (P < 0.05)]. Biomarkers were identified in Day-7 plasma (receiver operator characteristic-area under curve (ROC-AUC) > 0.650; t-test P < 0.05; random forests, mean decrease accuracy) and cross-validated in independent Holstein, beef, and crossbred recipients (overall classification accuracy -OCA-; P < 0.05). Recipients with fresh embryos showed N = 6 biomarkers consistently on Day-40, Day-62, and at birth. Recipients with vitrified embryos showed N = 5 biomarkers on Day-40 and Day-62 but only one biomarker at birth. The most predictive biomarkers identified at birth within fresh embryos were oxoglutaric acid (ROC-AUC = 0.709; OCA = 0.812) and ornithine (ROC-AUC = 0.731; OCA = 0.727), while l-glycine was identified in vitrified embryos (ROC-AUC = 0.796; OCA = 0.667) together with other predictive biomarkers not identified at birth (Day-62: l-glutamine ROC-AUC = 0.757; OCA = 0.767) and l-lysine (Day-62: ROC-AUC = 0.680; OCA = 0.767). Pathway enrichment analysis distinguished between pregnant recipients for fresh (enriched energy oxidative metabolism from fat) and vitrified (lower lipid metabolism) embryos. Metabolomics can select individuals that will become pregnant in a defined cycle.

Diagnosis of Bovine Respiratory Disease in feedlot cattle using blood 1H NMR metabolomics

Current diagnosis methods for Bovine Respiratory Disease (BRD) in feedlots have a low diagnostic accuracy. The current study aimed to search for blood biomarkers of BRD using ¹H NMR metabolomics and determine their accuracy in diagnosing BRD. Animals with visual signs of BRD (n = 149) and visually healthy (non-BRD; n = 148) were sampled for blood metabolomics analysis. Lung lesions indicative of BRD were scored at slaughter. Non-targeted ¹H NMR metabolomics was used to develop predictive algorithms for disease classification using classification and regression trees. In the absence of a gold standard for BRD diagnosis, six reference diagnosis methods were used to define an animal as BRD or non-BRD. Sensitivity (Se) and specificity (Sp) were used to estimate diagnostic accuracy (Acc). Blood metabolomics demonstrated a high accuracy at diagnosing BRD when using visual signs of BRD (Acc = 0.85), however was less accurate at diagnosing BRD using rectal temperature (Acc = 0.65), lung auscultation score (Acc = 0.61) and lung lesions at slaughter as reference diagnosis methods (Acc = 0.71). Phenylalanine, lactate, hydroxybutyrate, tyrosine, citrate and leucine were identified as metabolites of importance in classifying animals as BRD or non-BRD. The blood metabolome classified BRD and non-BRD animals with high accuracy and shows potential for use as a BRD diagnosis tool.

Performance, carcass traits and serum metabolomic profile of Nellore males with different genetic potential for post-weaning growth

The BW has been largely used as a selection criterion in genetic selection programmes; however, increases in BW can affect animal metabolism and metabolites. The knowledge of how genetic potential for growth affects the metabolites can give a footprint of growth metabolism. This research aimed to evaluate the effect of genetic potential for post-weaning growth (GG) on performance, carcass traits and serum metabolome of non-castrated Nellore males during the finishing phase. Forty-eight Nellore non-castrated males, with divergent potential for post-weaning growth, were selected and divided into two groups: high potential for post-weaning growth (HG; n = 24) and low potential for post-weaning growth (LG; n = 24). Animals were kept and fed for 90 days where performance and ultrasound carcass traits were evaluated. Blood samples were collected at the beginning and end of feeding period to analyse serum metabolites concentration. The hot carcass weight and dressing percentage were recorded at slaughter. The feedlot performance and carcass traits were not affected by genetic potential. The HG animals had a lower glucose (P = 0.039), glutamate (P = 0.038), glutamine (P = 0.004), greater betaine (P = 0.039) and pyruvate (P = 0.039) compared to the LG group at the beginning of feedlot. In addition, higher creatine phosphate concentrations were observed at the beginning of feeding period, compared to final, for both groups (P = 0.039). In conclusion, the genetic potential for post-weaning growth does not affect performance and carcass traits during the finishing period. Differences in metabolite concentrations can be better found at the beginning of feedlot, providing a footprint of growth metabolism, but similar metabolite concentration at the end of finishing period.

Relationship of the blood metabolome to subsequent carcass traits at slaughter in feedlot Wagyu crossbred steers

The aim of the present study was to determine the relationships between the blood metabolome and (1) carcass traits with a focus on intramuscular fat (marbling), and (2) the length of time cattle consumed a high-starch diet in feedlot cattle. Blood samples were obtained from 181 Wagyu-crossbred steers between 300-400 days before slaughter when carcass data was collected. ¹H NMR spectroscopy identified 35 metabolites with 7 positively associated with marbling (3-hydroxybutyrate, propionate, acetate, creatine, histidine, valine, and isoleucine; P ≤ 0.05). Subcutaneous rump fat thickness was positively associated with glucose, leucine and lipids (P ≤ 0.05) and negatively associated with anserine and arabinose (P ≤ 0.05). Carcass weight and growth rate were negatively associated with 3-hydroxybutyrate (P < 0.05), and growth rate was negatively associated with creatine (P < 0.05) and positively associated with aspartate (P < 0.05). Glucose and arginine showed a significant interaction between marbling and number of days animals consumed a high-starch diet (P < 0.05). Sire was the single variable with the largest effect on the relative concentration of metabolites and carcass and production traits. Blood metabolomics helps understand fat and muscle metabolism, and is associated with genotype, and carcass and production traits in cattle offering potential biomarkers suitable to select animals for management and genetic improvement.

Metabolomics Analyses in High-Low Feed Efficient Dairy Cows Reveal Novel Biochemical Mechanisms and Predictive Biomarkers

Residual feed intake (RFI) is designed to estimate net efficiency of feed use, so low RFI animals are considered for selection to reduce feeding costs. However, metabolic profiling of cows and availability of predictive metabolic biomarkers for RFI are scarce. Therefore, this study aims to generate a better understanding of metabolic mechanisms behind low and high RFI in Jerseys and Holsteins and identify potential predictive metabolic biomarkers. Each metabolite was analyzed to reveal their associations with two RFIs in two breeds by a linear regression model. An integrative analysis of metabolomics and transcriptomics was performed to explore interactions between functionally related metabolites and genes in the created metabolite networks. We found that three main clusters were detected in the heat map and all identified fatty acids (palmitoleic, hexadecanoic, octadecanoic, heptadecanoic, and tetradecanoic acid) were grouped in a cluster. The lower cluster were all from fatty acids, including palmitoleic acid, hexadecanoic acid, octadecanoic acid, heptadecanoic acid, and tetradecanoic acid. The first component of the partial least squares-discriminant analysis (PLS-DA) explained a majority (61.5%) of variations of all metabolites. A good division between two breeds was also observed. Significant differences between low and high RFIs existed in the fatty acid group (P < 0.001). Statistical results revealed clearly significant differences between breeds; however, the association of individual metabolites (leucine, ornithine, pentadecanoic acid, and valine) with the RFI status was only marginally significant or not significant due to a lower sample size. The integrated gene-metabolite pathway analysis showed that pathway impact values were higher than those of a single metabolic pathway. Both types of pathway analyses revealed three important pathways, which were aminoacyl-tRNA biosynthesis, alanine, aspartate, and glutamate metabolism, and the citrate cycle (TCA cycle). Finally, one gene (2-hydroxyacyl-CoA lyase 1 (+HACL1)) associated with two metabolites (-α-ketoglutarate and succinic acid) were identified in the gene-metabolite interaction network. This study provided novel metabolic pathways and integrated metabolic-gene expression networks in high and low RFI Holstein and Jersey cattle, thereby providing a better understanding of novel biochemical mechanisms underlying variation in feed efficiency.

Altering the Gut Microbiome of Cattle: Considerations of Host-Microbiome Interactions for Persistent Microbiome Manipulation

The beef cattle industry represents a significant portion of the USA's agricultural sect, with beef cattle accounting for the most red meat consumed in the USA. Feed represents the largest input cost in the beef industry, accounting for approximately 70% of total input cost. Given that, novel methods need to be employed to optimize feed efficiency in cattle to reduce monetary cost as well as environmental cost associated with livestock industries, such as methane production and nitrogen release into the environment. The rumen microbiome contributes to feed efficiency by breaking down low-quality feedstuffs into energy substrates that can subsequently be utilized by the host animal. Attempts to manipulate the rumen microbiome have been met with mixed success, though persistent changes have not yet been achieved beyond changing diet. Recent technological advances have made analyzing host-wide effects of the rumen microbiome possible, as well as provided finer resolution of those effects. This manuscript reviews contributing factors to the rumen microbiome establishment or re-establishment following rumen microbiome perturbation, as well as host-microbiome interactions that may be responsible for possible host specificity of the rumen microbiome. Understanding and accounting for the variety of factors contributing to rumen microbiome establishment or re-establishment in cattle will ultimately lead to identification of biomarkers of feed efficiency that will result in improved selection criteria, as well as aid to determine methods for persistent microbiome manipulation to optimize production phenotypes.

Integrating 16S rRNA Sequencing and LC⁻MS-Based Metabolomics to Evaluate the Effects of Live Yeast on Rumen Function in Beef Cattle

We evaluated the effects of live yeast on ruminal bacterial diversity and metabolome of beef steer. Eight rumen-cannulated Holstein steers were assigned randomly to one of two treatment sequences in a study with two 25-d experimental periods and a crossover design. The steers were housed in individual pens. The dietary treatments were control (CON) or yeast (YEA; CON plus 15 g/d of live yeast product). Bacterial diversity was examined by sequencing the V3-V4 region of 16S rRNA gene. The metabolome analysis was performed using a liquid chromatograph and a mass spectrometry system (LC⁻MS). Live yeast supplementation increased the relative abundance of eight cellulolytic bacterial genera as well as Anaerovorax and Lachnospiraceae. Proteiniclasticum, Salmonella, and Lactococcus were not detected in the YEA treatment. Live yeast supplementation increased the concentrations of 4-cyclohexanedione and glucopyranoside and decreased the concentrations of threonic acid, xanthosine, deoxycholic acid, lauroylcarnitine, methoxybenzoic acid, and pentadecylbenzoic acid. The bacteroidales BS11, Christensenellaceae R-7, and Candidatus saccharimonas showed positive correlations with the metabolites involved in amino acid biosynthesis and the metabolism of energy substrates; the functions of these bacteria are not fully understood in relation to the mode of action of yeast. This study confirms the usefulness of LC⁻MS-based metabolomics in deciphering the mode of action of live yeast in the rumen.

Identification of a metabolomic signature associated with feed efficiency in beef cattle

BACKGROUND

Ruminants play a great role in sustainable livestock since they transform pastures, silage, and crop residues into high-quality human food (i.e. milk and beef). Animals with better ability to convert food into animal protein, measured as a trait called feed efficiency (FE), also produce less manure and greenhouse gas per kilogram of produced meat. Thus, the identification of high feed efficiency cattle is important for sustainable nutritional management. Our aim was to evaluate the potential of serum metabolites to identify FE of beef cattle before they enter the feedlot.

RESULTS

A total of 3598 and 4210 m/z features was detected in negative and positive ionization modes via liquid chromatography-mass spectrometry. A single feature was different between high and low FE groups. Network analysis (WGCNA) yielded the detection of 19 and 20 network modules of highly correlated features in negative and positive mode respectively, and 1 module of each acquisition mode was associated with RFI (r = 0.55, P < 0.05). Pathway enrichment analysis (Mummichog) yielded the Retinol metabolism pathway associated with feed efficiency in beef cattle in our conditions.

CONCLUSION

Altogether, these findings demonstrate the existence of a serum-based metabolomic signature associated with feed efficiency in beef cattle before they enter the feedlot. We are now working to validate the use of metabolites for identification of feed efficient animals for sustainable nutritional management.