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

Characterization of feed efficiency-related key signatures molecular in different cattle breeds

Feed efficiency is a major constraint in the beef industry and has a significant negative correlation with residual feed intake (RFI). RFI is widely used as a measure of feed efficiency in beef cattle and is independent of economic traits such as body weight and average daily gain. However, key traits with commonality or specificity among beef cattle breeds at the same level of RFI have not been reported. Accordingly, the present study hypothesized that signatures associated with feed efficiency would have commonality or specificity in the liver of cattle breeds at the same RFI level. By comparing and integrating liver transcriptome data, we investigated the critical signatures closely associated with RFI in beef cattle using weighted co-expression network analysis, consensus module analysis, functional enrichment analysis and protein network interaction analysis. The results showed that the consensus modules in Angus and Charolais cattle were negatively correlated, and four (turquoise, red, tan, yellow) were significantly positively correlated in Angus liver, while (turquoise, red) were significantly negatively correlated in Charolais liver. These consensus modules were found to be primarily involved in biological processes such as substance metabolism, energy metabolism and gene transcription, which may be one of the possible explanations for the difference in feed efficiency between the two beef breeds. This research also identified five key candidate genes, PLA2G12B, LCAT, MTTP, LCAT, ABCA1 and FADS1, which are closely associated with hepatic lipid metabolism. The present study has identified some modules, genes and pathways that may be the major contributors to the variation in feed efficiency among different cattle breeds, providing a new perspective on the molecular mechanisms of feed efficiency in beef cattle and a research basis for investigating molecular markers associated with feed efficiency in beef cattle.

Plasma metabolomic profiling in two rabbit lines divergently selected for intramuscular fat content

This study provides a thorough comparison of the plasma metabolome of two rabbit lines divergently selected for intramuscular fat content (IMF). The divergent selection led to a correlated response in the overall adiposity, turning these lines into a valuable animal material to study also the genetics of obesity. Over 900 metabolites were detected, and the adjustment of multivariate models, both discriminant and linear, allowed to identify 322 with differential abundances between lines, which also adjusted linearly to the IMF content. The most affected pathways were those of lipids and amino acids, with differences between lines ranging from 0.23 to 6.04 standard deviations, revealing a limited capacity of the low-IMF line to obtain energy from lipids, and a greater branched-chain amino acids catabolism in the high-IMF line related to its increased IMF content. Additionally, changes in metabolites derived from microbial activity supported its relevant role in the lipid deposition. Future research will focus on the analysis of the metabolomic profile of the cecum content, and on the integration of the several -omics datasets available for these lines, to help disentangle the host and microbiome biological mechanisms involved in the IMF deposition.

Effect of Rumen-Protected Methionine on Metabolic Profile of Liver, Muscle and Blood Serum Samples of Growing German Simmental Bulls Fed Protein-Reduced Diets

This study aimed to determine the metabolic response of growing German Simmental bulls fed rations low in crude protein (CP) supplemented with rumen-protected methionine (RPMET). In total, 69 bulls (on average 238 ± 11 days of age at start and 367 ± 25 kg of bodyweight) were assigned to three dietary treatments (n = 23/group): Positive control (CON; 13.7% CP; 2.11 g methionine/kg DM), negative control deficient in CP (RED; 9.04% CP; 1.56 g methionine/kg DM) and crude protein-deficient ration supplemented with RPMET (RED+RPMET; 9.04% CP; 2.54 g methionine/kg DM). At slaughter, samples of liver, muscle and blood serum were taken and underwent subsequent metabolomics profiling using a UHPLC-QTOF-MS system. A total of 6540 features could be detected. Twenty metabolites in the liver, five metabolites in muscle and thirty metabolites in blood serum were affected (p < 0.05) due to dietary treatments. In total, six metabolites could be reliably annotated and were thus subjected to subsequent univariate analysis. Reduction in dietary CP had minimal effect on metabolite abundance in target tissues of both RED and RED+RPMET bulls as compared to CON bulls. The addition of RPMET altered the hepatic anti-oxidant status in RED+RPMET bulls compared to both RED and CON bulls. Results exemplify nutrient partitioning in growing German Simmental bulls: bulls set maintenance as the prevailing metabolic priority (homeostasis) and nutrient trafficking as the second priority, which was directed toward special metabolic functions, such as anti-oxidant pathways.

The time elapsed between assessments of blood metabolome and live weight affects associations between the abundance of metabolites and growth rate in beef cattle

INTRODUCTION

This study aimed to assess the associations between the relative abundance (RA) of blood metabolites and growth rate (i.e., live weight change, LWC) calculated using different intervals of time between live weight (LW) measurements from the metabolome assessment.

METHODS

Grazing beef cattle were raised for 56 days and blood samples from each animal were taken on day 57. Live weight was continuously measured using an automatic in-paddock weighing scale. The RA of plasma metabolites were determined using proton nuclear magnetic resonance (NMR). Live weight data were filtered for outliers and one LW record was selected every 1, 7, 14, 21, 28, 35, 42, 49 and 56 days before the metabolome assessment (LWC1 to LWC56, respectively). Live weight change was then re-calculated for each interval between LW data selected.

RESULTS

Associations between LWC calculations and the RA of metabolites were greatly affected by the interval of time between LW data selected. Thus, the number of significant associations decreased from 9 for LWC1 to 5 for LWC35 whereas no significant associations were found for LWC56 (P > 0.05). There were 7 metabolites negatively associated with LWC1 including leucine, 2-hydroxybutyrate, valine, creatinine, creatine, phenylalanine and methylhistidine; however, correlations were positive for 2 lipids. The strength of the correlation coefficients decreased as the length of the interval between LW measures increased although this reduction was greater for some metabolites such as leucine compared to others such as lipids. Our findings suggest that the time frame in which a particular response variable, such as LWC, is measured and metabolomic samples are taken could largely impact associations and thus conclusions drawn.

CONCLUSIONS

Depending on the variable to be explored, rapid changes in cattle metabolome may not be reflected in correlations if they are not assessed close in time. Our findings suggest that LWC should be measured for a period shorter than 28 days before the metabolome assessment as the number of significant associations decreases when LWC is measured for longer periods.

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.

Comparative evolutionary and molecular genetics based study of Buffalo lysozyme gene family to elucidate their antibacterial function

Lysozyme is used as a food preservative, biological medicine, and infant food additive as a natural anti-infective chemical having bactericidal activity and abundantly secreted in mammals' milk, saliva, etc. We systematically analyzed the 16 coding LYZ genes (C and G-type) in buffalo and cattle to elucidate their evolutionary perspective thoroughly by evaluating an evolutionary relationship, motif patterning, physicochemical attributes, gene, and protein structure, as well as the functional role of the mammary gland-specific expressed buffalo and cattle LYZ genes precisely while considering expression levels difference and the interaction sites variation with bacteria envisaged the potential ability of buffalo LYZ protein with enhanced antibacterial effect. Thus, we speculated that the buffalo mammary glands expressed lysozyme has good antibacterial activity. This study on the buffalo lysozyme gene family not only provides comprehensive insights into the genetic architecture and their antibacterial effect but also offers a theoretical basis for the development of new veterinary drugs and animal health care for mastitis, as well as a new molecular genetic basis to study food or medical lysozyme.

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

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

Discovering novel clues of natural selection on four worldwide goat breeds

In goat breeds, the domestication followed by artificial selection for economically important traits have shaped genetic variation within populations, leading to the fixation of specific alleles for specific traits. This led to the formation and evolution of many different breeds specialised and raised for a particular purpose. However, and despite the intensity of artificial selection, natural selection continues acting, possibly leaving a more diluted contribution over time, whose traces may be more difficult to capture. In order to explore selection footprints as response of environmental adaptation, we analysed a total of 993 goats from four transboundary goats breeds (Angora, Boer, Nubian and Saanen) genotyped with the SNP chip 50 K using outlier detection, runs of homozygosity and haplotype-based detection methods. Our results showed that all methods identified footprints on chromosome 6 (from 30 to 49 Mb) for two specific populations of Nubian goats sampled in Egypt. In Angora and Saanen breeds, we detected two selective sweeps using HapFLK, on chromosome 21 (from 52 to 55 Mb) and chromosome 25 (from 1 to 5 Mb) respectively. The analysis of runs of homozygosity showed some hotspots in all breeds. The overall investigation of the selected regions detected combining the different approaches and the gene ontology exploration revealed both novel and well-known loci related to adaptation, especially for heat stress. Our findings can help to better understand the balance between the two selective pressures in commercial goat breeds providing new insights on the molecular mechanisms of adaptation.

Multi-transcriptomics reveals RLMF axis-mediated signaling molecules associated with bovine feed efficiency

The regulatory axis plays a vital role in interpreting the information exchange and interactions among mammal organs. In this study on feed efficiency, it was hypothesized that a rumen-liver-muscle-fat (RLMF) regulatory axis exists and scrutinized the flow of energy along the RLMF axis employing consensus network analysis from a spatial transcriptomic standpoint. Based on enrichment analysis and protein-protein interaction analysis of the consensus network and tissue-specific genes, it was discovered that carbohydrate metabolism, energy metabolism, immune and inflammatory responses were likely to be the biological processes that contribute most to feed efficiency variation on the RLMF regulatory axis. In addition, clusters of genes related to the electron respiratory chain, including ND (2,3,4,4L,5,6), NDUF (A13, A7, S6, B3, B6), COX (1,3), CYTB, UQCR11, ATP (6,8), clusters of genes related to fatty acid metabolism including APO (A1, A2, A4, B, C3), ALB, FG (A, G), as well as clusters of the ribosomal-related gene including RPL (8,18A,18,15,13, P1), the RPS (23,27A,3A,4X), and the PSM (A1-A7, B6, C1, C3, D2-D4, D8 D9, E1) could be the primary effector genes responsible for feed efficiency variation. The findings demonstrate that high feed efficiency cattle, through the synergistic action of the regulatory axis RLMF, may improve the efficiency of biological processes (carbohydrate metabolism, protein ubiquitination, and energy metabolism). Meanwhile, high feed efficiency cattle might enhance the ability to respond to immunity and inflammation, allowing nutrients to be efficiently distributed across these organs associated with digestion and absorption, energy-producing, and energy-storing organs. Elucidating the distribution of nutrients on the RLMF regulatory axis could facilitate an understanding of feed efficiency variation and achieve the study on its molecular regulation.

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

Background

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

Results

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

Conclusions

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

Multi-omic data integration for the study of production, carcass, and meat quality traits in Nellore cattle

Data integration using hierarchical analysis based on the central dogma or common pathway enrichment analysis may not reveal non-obvious relationships among omic data. Here, we applied factor analysis (FA) and Bayesian network (BN) modeling to integrate different omic data and complex traits by latent variables (production, carcass, and meat quality traits). A total of 14 latent variables were identified: five for phenotype, three for miRNA, four for protein, and two for mRNA data. Pearson correlation coefficients showed negative correlations between latent variables miRNA 1 (mirna1) and miRNA 2 (mirna2) (−0.47), ribeye area (REA) and protein 4 (prot4) (−0.33), REA and protein 2 (prot2) (−0.3), carcass and prot4 (−0.31), carcass and prot2 (−0.28), and backfat thickness (BFT) and miRNA 3 (mirna3) (−0.25). Positive correlations were observed among the four protein factors (0.45–0.83): between meat quality and fat content (0.71), fat content and carcass (0.74), fat content and REA (0.76), and REA and carcass (0.99). BN presented arcs from the carcass, meat quality, prot2, and prot4 latent variables to REA; from meat quality, REA, mirna2, and gene expression mRNA1 to fat content; from protein 1 (prot1) and mirna2 to protein 5 (prot5); and from prot5 and carcass to prot2. The relations of protein latent variables suggest new hypotheses about the impact of these proteins on REA. The network also showed relationships among miRNAs and nebulin proteins. REA seems to be the central node in the network, influencing carcass, prot2, prot4, mRNA1, and meat quality, suggesting that REA is a good indicator of meat quality. The connection among miRNA latent variables, BFT, and fat content relates to the influence of miRNAs on lipid metabolism. The relationship between mirna1 and prot5 composed of isoforms of nebulin needs further investigation. The FA identified latent variables, decreasing the dimensionality and complexity of the data. The BN was capable of generating interrelationships among latent variables from different types of data, allowing the integration of omics and complex traits and identifying conditional independencies. Our framework based on FA and BN is capable of generating new hypotheses for molecular research, by integrating different types of data and exploring non-obvious relationships.

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

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

Identification of key genes and functional enrichment pathways involved in fat deposition in Xinyang buffalo by WGCNA

The Xinyang buffalo is a valuable and endangered domestic heritage resource in the Dabie Mountain region in China. With the increasing mechanization of agriculture, the Xinyang buffalo, mainly used for labor, faces unprecedented challenges. One of the feasible approaches to conserve and expand the species is to transfer Xinyang buffalo from service-use to meat-use, but the main hindrance to this transformation is the inferior meat quality of Xinyang buffalo, which is not popular with consumers. Based on the above, this study was conducted to evaluate the growth performance (n = 120) and slaughter performance (n = 3) of Xinyang buffalo and to measure the amino acid levels of the eye muscle (EM), and assess the meat quality. Later, transcriptome sequencing was performed on the subcutaneous fat of the back at six (n = 3) and 30 months of age (n = 3), together with the excavation of candidate genes associated with fat deposition using the weighted co-expression network analysis (WGCNA) method. The results showed that the slaughter rate of Xinyang buffalo was 43.09%, net meat percentage was 33.04%, the ocular area was 59.16 ± 7.58, the backfat thickness was 1.03 ± 0.16, and meat bone ratio was 3.29. The total amino acid contents were 0.63 g per gram of beef, which contained 0.05 g of essential amino acids, and the three most abundant amino acids were Ser (447.17 mg/g), Asp (29.8 mg/g), and Pro (27.24 mg/g). The WGCNA results showed that six phenotypes measured were significantly correlated with the turquoise module (r > 0.97, P < 0.001), and the genes in these modules were significantly enriched in the pathways related to substance metabolism and energy metabolisms, such as metabolic pathways, citrate cycle, and fatty acid metabolism. Meanwhile, six key candidate genes (FH, MECR, GPI, PANK3, ATP6V1A, PHYH) were identified, which were associated with growth and development, fat deposition, and intra-muscular amino acid levels (P < 0.05). In short, this study provides another feasible way to preserve buffalo and enriches the theory of its molecular genetic breeding.

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.

Comparisons of carcass traits, meat quality, and serum metabolome between Shaziling and Yorkshire pigs

This study aims to compare the meat quality of Shaziling and Yorkshire pigs and to find the potential indicator in serum for superior meat quality. Six Shaziling and Yorkshire pigs at 30, 60, 90, 150, 210, and 300 d of age were selected to examine carcass traits, meat quality, and serum metabolome. The results showed that the body weight, carcass length, and loin eye area of Shaziling pigs at 150, 210, and 300 d of age were significantly lower than those of Yorkshire pigs (P < 0.05). Shaziling pigs at 150 and 300 d of age had significantly lower backfat thickness than Yorkshire pigs (P < 0.05). Compared with Yorkshire pigs, Shaziling pigs at all 6 ages had a lower lean percentage and a higher fat percentage (P < 0.05). At 60, 90, and 150 d of age, the post-mortem pH-decline, b∗ value (yellowness), and drip loss of Shaziling pigs were significantly lower than those of Yorkshire pigs (P < 0.05). Moreover, at 150 d of age, Shaziling pigs had significantly higher a∗ value (redness) and intramuscular fat (IMF) content than Yorkshire pigs (P < 0.05). Correlation analysis between the top 40 metabolites and phenotypes indicated that L-carnitine had positive correlations with fat percentage, pH_24h, and IMF content, but had negative correlations with lean percentage, L∗ value (lightness), and b∗ value (P < 0.05). Serum L-carnitine content, fat percentage, pH_24h, and IMF content all decreased first and then increased as the pigs grew, which verified the positive correlations between L-carnitine and these phenotypes. In conclusion, Shaziling pigs have a slower growth rate but a better meat quality than Yorkshire pigs. The meat quality of Shaziling pigs is the best from 150 to 210 d of age. This study suggests that a higher serum L-carnitine content is a promising indicator for better meat quality.

Comparative metabolomics analysis of milk components between Italian Mediterranean buffaloes and Chinese Holstein cows based on LC-MS/MS technology

Buffalo and cow milk have a very different composition in terms of fat, protein, and total solids. For a better knowledge of such a difference, the milk metabolic profiles and characteristics of metabolites was investigated in Italian Mediterranean buffaloes and Chinese Holstein cows were investigated by liquid chromatography tandem-mass spectrometry (LC-MS/MS) in this study. Totally, 23 differential metabolites were identified to be significantly different in the milk from the two species of which 15 were up-regulated and 8 down-regulated in Italian Mediterranean buffaloes. Metabolic pathway analysis revealed that 4 metabolites (choline, acetylcholine, nicotinamide and uric acid) were significantly enriched in glycerophospholipid metabolism, nicotinate and nicotinamide metabolism, glycine, serine and threonine metabolism, as well as purine metabolism. The results provided further insights for a deep understanding of the potential metabolic mechanisms responsible for the different performance of Italian Mediterranean buffaloes' and Chinese Holstein cows' milk. The findings will offer new tools for the improvement and novel directions for the development of dairy industry.

Integrated Analysis of mRNA and MicroRNA Co-expressed Network for the Differentiation of Bovine Skeletal Muscle Cells After Polyphenol Resveratrol Treatment

Resveratrol (RSV) has been confirmed to benefit human health. Resveratrol supplemented in the feeds of animals improved pork, chicken, and duck meat qualities. In this study, we identified differentially expressed (DE) messenger RNAs (mRNAs) (n = 3,856) and microRNAs (miRNAs) (n = 93) for the weighted gene co-expression network analysis (WGCNA) to investigate the co-expressed DE mRNAs and DE miRNAs in the primary bovine myoblasts after RSV treatment. The mRNA results indicated that RSV treatments had high correlations with turquoise module (0.91, P-value = 0.01) and blue module (0.93, P-value < 0.01), while only the turquoise module (0.96, P-value < 0.01) was highly correlated with the treatment status using miRNA data. After biological enrichment analysis, the 2,579 DE genes in the turquoise module were significantly enriched in the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The top two GO terms were actin filament-based process (GO:0030029) and actin cytoskeleton organization (GO:0030036). The top two KEGG pathways were regulation of actin cytoskeleton (bta04810) and tight junction (bta04530). Then, we constructed the DE mRNA co-expression and DE miRNA co-expression networks in the turquoise module and the mRNA–miRNA targeting networks based on their co-expressions in the key module. In summary, the RSV-induced miRNAs participated in the co-expression networks that could affect mRNA expressions to regulate the primary myoblast differentiation. Our study provided a better understanding of the roles of RSV in inducing miRNA and of the characteristics of DE miRNAs in the key co-expressed module in regulation of mRNAs and revealed new candidate regulatory miRNAs and genes for the beef quality traits.

Identifying the key genes and functional enrichment pathways associated with feed efficiency in cattle

Residual feed intake (RFI) is a measurement of feed efficiency, and is inversely correlated with feed efficiency. The differentially expressed genes (DEGs) associated with RFI vary substantially among studies, posing great challenges in finding the RFI-related marker genes. This study attempted to resolve this issue by integrating and comparing the multiple transcriptome sequencing data associated with RFI in the cattle liver, using differential, functional enrichment, protein-protein interaction (PPI) network, weighted co-expression network (WGCNA), and gene set enrichment analyses (GSEA) to identify the candidate genes and functional enrichment pathways that are closely associated with RFI. Four candidate genes namely SHC1, GPX4, ACADL, and IGF1 were identified and validated as the marker genes for RFI. Four functional enrichment pathways, namely the fatty acid metabolism, sugar metabolism, energy metabolism, and protein ubiquitination were also found to be closely related to RFI. This study identified several genes and signaling pathways with shared characteristics, which will provide new insights into the molecular mechanisms related to the regulation of feed efficiency, and provide basis for molecular markers related to feed efficiency in beef cattle.

Non-invasive metabolomics biomarkers of production efficiency and beef carcass quality traits

The inter-cattle growth variations stem from the interaction of many metabolic processes making animal selection difficult. We hypothesized that growth could be predicted using metabolomics. Urinary biomarkers of cattle feed efficiency were explored using mass spectrometry-based untargeted and targeted metabolomics. Feed intake and weight-gain was measured in steers (n = 75) on forage-based growing rations (stage-1, 84 days) followed by high-concentrate finishing rations (stage-2, 84 days). Urine from days 0, 21, 42, 63, and 83 in each stage were analyzed from steers with the greater (n = 14) and least (n = 14) average-daily-gain (ADG) and comparable dry-matter-intake (DMI; within 0.32 SD of the mean). Steers were slaughtered after stage-2. Adjusted fat-thickness and carcass-yield-grade increased in greater-ADG-cattle selected in stage-1, but carcass traits did not differ between ADG-selected in stage-2. Overall 85 untargeted metabolites segregated greater- and least-ADG animals, with overlap across diets (both stages) and breed type, despite sampling time effects. Total 18-bile acids (BAs) and 5-steroids were quantified and associated with performance and carcass quality across ADG-classification depending on the stage. Stepwise logistic regression of urinary BA and steroids had > 90% accuracy identifying efficient-ADG-steers. Urine metabolomics provides new insight into the physiological mechanisms and potential biomarkers for feed efficiency.

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.

Metabolomic signature of spermatozoa established during holding time is responsible for differences in boar sperm freezability

Holding at room temperature is the first step in most boar semen cryopreservation protocols. It is well accepted that a holding time (HT) of 24 h increases sperm cryotolerance. However, the effect of HT on ejaculates with different freezability is not entirely clear. The aim of this study was to understand how HT influences spermatic and seminal plasma metabolite profiles of boar ejaculates and how these possible changes affect freezability. Twenty-seven ejaculates were collected and extended to 1:1 (v: v) with BTS and split into two aliquots. The first aliquot was cryopreserved without holding time (0 h), and the second was held at 17°C for 24 h before cryopreservation. Spermatozoa and seminal plasma were collected by centrifugation at two times, before HT (0 h) and after HT (24 h), and subsequently frozen until metabolite extraction and UPLC-MS analysis. After thawing, the semen samples were evaluated for kinetics, membrane integrity, mitochondrial potential, membrane lipid peroxidation, and fluidity. The ejaculates were then allocated into two phenotypes (good ejaculate freezers [GEF] and poor ejaculate freezers [PEF]) based on the percent reduction in sperm quality (%RSQ) as determined by the difference in total motility and membrane integrity between raw and post-thaw samples cryopreserved after 24 h of HT. The metabolic profile of the seminal plasma did not seem to influence ejaculate freezability, but that of the spermatozoa were markedly different between GEF and PEF. We identified a number of metabolic markers in the sperm cells (including inosine, hypoxanthine, creatine, ADP, niacinamide, spermine, and 2-methylbutyrylcarnitine) that were directly related to the improvement of ejaculate freezability during HT; these were components of metabolic pathways associated with energy production. Furthermore, PEF showed an up-regulation in the arginine and proline as well as the glutathione metabolism pathways. These findings help to better understand the effect of holding time on boar sperm freezability and propose prospective metabolic markers that may predict freezability; this has implications in both basic and applied sciences.

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.

Chemical Gradients of Plant Substrates in an Atta texana Fungus Garden

Many ant species grow fungus gardens that predigest food as an essential step of the ants' nutrient uptake. These symbiotic fungus gardens have long been studied and feature a gradient of increasing substrate degradation from top to bottom. To further facilitate the study of fungus gardens and enable the understanding of the predigestion process in more detail than currently known, we applied recent mass spectrometry-based approaches and generated a three-dimensional (3D) molecular map of an Atta texana fungus garden to reveal chemical modifications as plant substrates pass through it. The metabolomics approach presented in this study can be applied to study similar processes in natural environments to compare with lab-maintained ecosystems. IMPORTANCE The study of complex ecosystems requires an understanding of the chemical processes involving molecules from several sources. Some of the molecules present in fungus-growing ants' symbiotic system originate from plants. To facilitate the study of fungus gardens from a chemical perspective, we provide a molecular map of an Atta texana fungus garden to reveal chemical modifications as plant substrates pass through it. The metabolomics approach presented in this study can be applied to study similar processes in natural environments.

Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency

Background

Improving feed efficiency is economically and environmentally beneficial in the pig industry. A deeper understanding of feed efficiency is essential on many levels for its highly complex nature. The aim of this project is to explore the relationship between fecal metabolites and feed efficiency-related traits, thereby identifying metabolites that may assist in the screening of the feed efficiency of pigs.

Results

We performed fecal metabolomics analysis on 50 individuals selected from 225 Duroc x (Landrace x Yorkshire) (DLY) commercial pigs, 25 with an extremely high feed efficiency and 25 with an extremely low feed efficiency. A total of 6749 and 5644 m/z features were detected in positive and negative ionization modes by liquid chromatography-mass spectrometry (LC/MS). Regrettably, the PCA could not classify the the samples accurately. To improve the classification, OPLS-DA was introduced. However, the predictive ability of the OPLS-DA model did not perform well. Then, through weighted coexpression network analysis (WGCNA), we found that one module in each positive and negative mode was related to residual feed intake (RFI), and six and three metabolites were further identified. The nine metabolites were found to be involved in multiple metabolic pathways, including lipid metabolism (primary bile acid synthesis, linoleic acid metabolism), vitamin D, glucose metabolism, and others. Then, Lasso regression analysis was used to evaluate the importance of nine metabolites obtained by the annotation process.

Conclusions

Altogether, this study provides new insights for the subsequent evaluation of commercial pig feed efficiency through small molecule metabolites, but also provide a reference for the development of new feed additives.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40813-021-00219-w.

Metabolomic signature of genetic potential for muscularity in beef cattle

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

Prediction of complex phenotypes using the Drosophila melanogaster metabolome

Understanding the genotype-phenotype map and how variation at different levels of biological organization is associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins and metabolites. This can facilitate our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use the Drosophila melanogaster Genetic Reference Panel and nuclear magnetic resonance (NMR) metabolomics to investigate the ability of the metabolome to predict organismal phenotypes. We performed NMR metabolomics on four replicate pools of male flies from each of 170 different isogenic lines. Our results show that metabolite profiles are variable among the investigated lines and that this variation is highly heritable. Second, we identify genes associated with metabolome variation. Third, using the metabolome gave better prediction accuracies than genomic information for four of five quantitative traits analyzed. Our comprehensive characterization of population-scale diversity of metabolomes and its genetic basis illustrates that metabolites have large potential as predictors of organismal phenotypes. This finding is of great importance, e.g., in human medicine, evolutionary biology and animal and plant breeding.

Altered metabolic pathways in a transgenic mouse model suggest mechanistic role of amyloid precursor protein overexpression in Alzheimer's disease

INTRODUCTION

The mechanistic role of amyloid precursor protein (APP) in Alzheimer's disease (AD) remains unclear.

OBJECTIVES

Here, we aimed to identify alterations in cerebral metabolites and metabolic pathways in cortex, hippocampus and serum samples from Tg2576 mice, a widely used mouse model of AD.

METHODS

Metabolomic profilings using liquid chromatography-mass spectrometry were performed and analysed with MetaboAnalyst and weighted correlation network analysis (WGCNA).

RESULTS

Expressions of 11 metabolites in cortex, including hydroxyphenyllactate-linked to oxidative stress-and phosphatidylserine-lipid metabolism-were significantly different between Tg2576 and WT mice (false discovery rate < 0.05). Four metabolic pathways from cortex, including glycerophospholipid metabolism and pyrimidine metabolism, and one pathway (sulphur metabolism) from hippocampus, were significantly enriched in Tg2576 mice. Network analysis identified five pathways, including alanine, aspartate and glutamate metabolism, and mitochondria electron transport chain, that were significantly correlated with AD genotype.

CONCLUSIONS

Changes in metabolite concentrations and metabolic pathways are present in the early stage of APP pathology, and may be important for AD development and progression.

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.

Genome-Wide Co-Expression Distributions as a Metric to Prioritize Genes of Functional Importance

Genome-wide gene expression analysis are routinely used to gain a systems-level understanding of complex processes, including network connectivity. Network connectivity tends to be built on a small subset of extremely high co-expression signals that are deemed significant, but this overlooks the vast majority of pairwise signals. Here, we developed a computational pipeline to assign to every gene its pair-wise genome-wide co-expression distribution to one of 8 template distributions shapes varying between unimodal, bimodal, skewed, or symmetrical, representing different proportions of positive and negative correlations. We then used a hypergeometric test to determine if specific genes (regulators versus non-regulators) and properties (differentially expressed or not) are associated with a particular distribution shape. We applied our methodology to five publicly available RNA sequencing (RNA-seq) datasets from four organisms in different physiological conditions and tissues. Our results suggest that genes can be assigned consistently to pre-defined distribution shapes, regarding the enrichment of differential expression and regulatory genes, in situations involving contrasting phenotypes, time-series, or physiological baseline data. There is indeed a striking additional biological signal present in the genome-wide distribution of co-expression values which would be overlooked by currently adopted approaches. Our method can be applied to extract further information from transcriptomic data and help uncover the molecular mechanisms involved in the regulation of complex biological process and phenotypes.

Metabolomic analysis of organic acids, amino acids, and fatty acids in plasma of Hanwoo beef on a high-protein diet

INTRODUCTION

Ketoacidosis of metabolic disease showed in beef cattle although body weight was increased by high-grain diets (HGDs). However, few studies have examined for health status related with metabolic disease of ketoacidosis following high-protein diet (HPD).

OBJECTIVES

Metabolomic analysis was performed for the monitoring of health status associated with metabolic disease of ketoacidosis in the plasma of Hanwoo heifers following a HPD.

METHODS

Hanwoo heifers of 24 months with 459 ± 42 kg weight were used under a 2 × 2 crossover design. The plasma was collected from control (n = 5) and HPD group (n = 5) on day 21 following diet adaptation for 20 days. Metabolic profiling analysis of organic acids (OAs), amino acids (AAs) and fatty acids (FAs) by gas chromatography-tandem mass spectrometry combined with star pattern analysis was performed in plasma. Levels of OAs, AAs and FAs were evaluated by Mann-Whitney test, PCA and PLS-DA.

RESULTS

In HPD group, ketoacidosis as metabolic disease was monitored by elevated acetoacetic acid and 3-hydroxybutyric acid. In addition, the elevation of ketogenic AAs, reduction of medium chain FAs and OAs with energy metabolism in TCA cycle were monitored in HPD group. Star graphic pattern was characteristic and readily distinguished between control and HPD groups. In PLS-DA, two groups were separated with VIP score of top-ranked 10 FAs as important metabolites for discrimination.

CONCLUSION

Elevation of ketone body including ketogenic AAs and reduced energy metabolism of FAs and OAs may useful for evaluation of health states associated with ketoacidosis from metabolic event by HPD in beef cattle.

Diet induced the change of mtDNA copy number and metabolism in Angus cattle

Background

Grass-fed and grain-fed Angus cattle differ in the diet regimes. However, the intricate mechanisms of different beef quality and other phenotypes induced by diet differences are still unclear. Diet affects mitochondrial function and dynamic behavior in response to changes in energy demand and supply. In this study, we examined the mtDNA copy number, mitochondria-related genes expression, and metabolic biomarkers in grass-fed and grain-fed Angus cattle.

Results

We found that the grass-fed group had a higher mtDNA copy number than the grain-fed group. Among different tissues, the mtDNA copy number was the highest in the liver than muscle, rumen, and spleen. Based on the transcriptome of the four tissues, a lower expression of mtDNA-encoded genes in the grass-fed group compared to the grain-fed group was discovered. For the mitochondria-related nuclear genes, however, most of them were significantly down-regulated in the muscle of the grass-fed group and up-regulated in the other three tissues. In which, COX6A2, POLG2, PPIF, DCN, and NDUFA12, involving in ATP synthesis, mitochondrial replication, transcription, and maintenance, might contribute to the alterations of mtDNA copy number and gene expression. Meanwhile, 40 and 23 metabolic biomarkers were identified in the blood and muscle of the grain-fed group compared to a grass-fed group, respectively. Integrated analysis of the altered metabolites and gene expression revealed the high expression level of MDH1 in the grain-fed group might contribute to the mitochondrial NADH oxidation and spermidine metabolism for adapting the deletion mtDNA copy number.

Conclusions

Overall, the study may provide further deep insight into the adaptive and regulatory modulations of the mitochondrial function in response to different feeding systems in Angus cattle.

Integrative Analysis of Metabolomic and Transcriptomic Profiles Uncovers Biological Pathways of Feed Efficiency in Pigs

Feed efficiency (FE) is an economically important trait. Thus, reliable predictors would help to reduce the production cost and provide sustainability to the pig industry. We carried out metabolome-transcriptome integration analysis on 40 purebred Duroc and Landrace uncastrated male pigs to identify potential gene-metabolite interactions and explore the molecular mechanisms underlying FE. To this end, we applied untargeted metabolomics and RNA-seq approaches to the same animals. After data quality control, we used a linear model approach to integrate the data and find significant differently correlated gene-metabolite pairs separately for the breeds (Duroc and Landrace) and FE groups (low and high FE) followed by a pathway over-representation analysis. We identified 21 and 12 significant gene-metabolite pairs for each group. The valine-leucine-isoleucine biosynthesis/degradation and arginine-proline metabolism pathways were associated with unique metabolites. The unique genes obtained from significant metabolite-gene pairs were associated with sphingolipid catabolism, multicellular organismal process, cGMP, and purine metabolic processes. While some of the genes and metabolites identified were known for their association with FE, others are novel and provide new avenues for further research. Further validation of genes, metabolites, and gene-metabolite interactions in larger cohorts will elucidate the regulatory mechanisms and pathways underlying FE.

Rumen fluid metabolomics of beef steers differing in feed efficiency

INTRODUCTION

Beef is the most consumed red meat in the United States, and the US is the largest producer and consumer of beef cattle globally. Feed is one of the largest input costs for the beef cattle industry, accounting for 40-60% of the total input costs. Identifying methods for improving feed efficiency in beef cattle herds could result in decreased cost to both producers and consumers, as well as increased animal protein available for global consumption.

METHODS

In this study, rumen fluid was collected from low- (n = 14) and high-RFI (n = 15) steers. Rumen fluid was filtered through a 0.22 µM syringe filter, extracted using 0.1% formic acid in acetonitrile:water:methanol (2:2:1) and injected into the Dionex UltiMate 3000 UHPLC system with an Exactive Plus Orbitrap MS. Peaks were identified using MAVEN and analyzed using MetaboAnalyst 4.0 and SAS. Significance was determined using an α ≤ 0.05.

RESULTS

Eight metabolites were greater in low-RFI steers compared to high-RFI steers, including 3,4-dihydroxyphenylacetate, 4-pyridoxate, citraconate, hypoxanthine, succinate/methylmalonate, thymine, uracil, and xylose (P ≤ 0.05). These metabolites were predominantly involved in amino acid and lipid metabolism.

CONCLUSIONS

Rumen fluid metabolomes differ in steers of varying feed efficiencies. These metabolites may be used as biomarkers of feed efficiency, and may provide insight as to factors contributing to differences in feed efficiency that may be exploited to improve feed efficiency in beef cattle herds.

Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs

Improving feed efficiency (FE) is a major goal of pig breeding, reducing production costs and providing sustainability to the pig industry. Reliable predictors for FE could assist pig producers. We carried out untargeted blood metabolite profiling in uncastrated males from Danbred Duroc (n = 59) and Danbred Landrace (n = 50) pigs at the beginning and end of a FE testing phase to identify biomarkers and biological processes underlying FE and related traits. By applying linear modeling and clustering analyses coupled with WGCNA framework, we identified 102 and 73 relevant metabolites in Duroc and Landrace based on two sampling time points. Among them, choline and pyridoxamine were hub metabolites in Duroc in early testing phase, while, acetoacetate, cholesterol sulfate, xanthine, and deoxyuridine were identified in the end of testing. In Landrace, cholesterol sulfate, thiamine, L-methionine, chenodeoxycholate were identified at early testing phase, while, D-glutamate, pyridoxamine, deoxycytidine, and L-2-aminoadipate were found at the end of testing. Validation of these results in larger populations could establish FE prediction using metabolomics biomarkers. We conclude that it is possible to identify a link between blood metabolite profiles and FE. These results could lead to improved nutrient utilization, reduced production costs, and increased FE.

Methods and basic concepts for microbiota assessment

There has been a marked increase in interest regarding complex microbial populations in recent years. The methodology used for microbial assessment has drastically changed over the last two decades and continues to advance at a rapid pace. Culture-based studies have been superseded by those based upon molecular methods, which have been largely used to discover new species and to better characterize complex communities, mainly driven by the advances in DNA sequencing, termed 'next generation sequencing'. These methodologies have allowed for a better understanding of the relationship between hosts and their microbiotas, which have important roles in health maintenance and in the pathophysiology of wide ranging conditions such as obesity, diabetes, allergic diseases and even behavioural changes. While most widely used in humans, these approaches are now commonly used in veterinary research, with increasing interest in direct clinical applications. As these methods provide novel insights that will constitute the basis for the development of new therapeutic and prevention strategies, and as commercial efforts to offer microbiota assessment as a clinical tool expand, it is essential for researchers and clinical veterinarians to understand and have the tools to be able to interpret research performed in this new fascinating field. The objective of this review is to describe some of the most common methods for characterization of microbial communities and to provide an overview of the basic concepts necessary for good interpretation of the research performed in this field.

Omics-based analyses revealed metabolic responses of Clostridium acetobutylicum to lignocellulose-derived inhibitors furfural, formic acid and phenol stress for butanol fermentation

BACKGROUND

Clostridium acetobutylicum is a model fermentative anaerobe for consolidated bioprocessing of lignocellulose hydrolysates into acetone-butanol-ethanol (ABE). However, the main inhibitors (acids, furans and phenols) ubiquitous in lignocellulose hydrolysates strictly limit the conversion efficiency. Thus, it is essential to understand the underlying mechanisms of lignocellulose hydrolysate inhibitors to identify key industrial bottlenecks that undermine efficient biofuel production. The recently developed omics strategy for intracellular metabolites and protein quantification now allow for the in-depth mapping of strain metabolism and thereby enable the resolution of the underlying mechanisms.

RESULTS

The toxicity of the main inhibitors in lignocellulose hydrolysates against C. acetobutylicum and ABE production was systematically investigated, and the changes in intracellular metabolism were analyzed by metabolomics and proteomics. The toxicity of the main lignocellulose hydrolysate inhibitors at the same dose was ranked as follows: formic acid > phenol > furfural. Metabolomic analysis based on weighted gene coexpression network analysis (WGCNA) revealed that the three inhibitors triggered the stringent response of C. acetobutylicum. Proteomic analysis based on peptide mass spectrometry (MS) supported the above results and provided more comprehensive conclusions. Under the stress of three inhibitors, the metabolites and key enzymes/proteins involved in glycolysis, reductive tricarboxylic acid (TCA) cycle, acetone-butanol synthesis and redox metabolism were lower than those in the control group. Moreover, proteins involved in gluconeogenesis, the oxidative TCA cycle, thiol peroxidase (TPX) for oxidative stress were significantly upregulated, indicating that inhibitor stress induced the stress response and metabolic regulation. In addition, the three inhibitors also showed stress specificity related to fatty acid synthesis, ATP synthesis, nucleic acid metabolism, nicotinic acid metabolism, cell wall synthesis, spore synthesis and flagellum synthesis and so on.

CONCLUSIONS

Integrated omics platforms provide insight into the cellular responses of C. acetobutylicum to cytotoxic inhibitors released during the deconstruction of lignocellulose. This insight allows us to fully improve the strain to adapt to a challenging culture environment, which will prove critical to the industrial efficacy of C. acetobutylicum.

Systems Biology Reveals NR2F6 and TGFB1 as Key Regulators of Feed Efficiency in Beef Cattle

Systems biology approaches are used as strategy to uncover tissue-specific perturbations and regulatory genes related to complex phenotypes. We applied this approach to study feed efficiency (FE) in beef cattle, an important trait both economically and environmentally. Poly-A selected RNA of five tissues (adrenal gland, hypothalamus, liver, skeletal muscle and pituitary) of eighteen young bulls, selected for high and low FE, were sequenced (Illumina HiSeq 2500, 100 bp, pared-end). From the 17,354 expressed genes considering all tissues, 1,335 were prioritized by five selection categories (differentially expressed, harboring SNPs associated with FE, tissue-specific, secreted in plasma and key regulators) and used for network construction. NR2F6 and TGFB1 were identified and validated by motif discovery as key regulators of hepatic inflammatory response and muscle tissue development, respectively, two biological processes demonstrated to be associated with FE. Moreover, we indicated potential biomarkers of FE, which are related to hormonal control of metabolism and sexual maturity. By using robust methodologies and validation strategies, we confirmed the main biological processes related to FE in Bos indicus and indicated candidate genes as regulators or biomarkers of superior animals.