Biomarker and pathway analyses of urine metabolomics in dairy cows when corn stover replaces alfalfa hay

Multi-omics analysis of the lipid-regulating effects of metformin in a glucose concentration-dependent manner in macrophage-derived foam cells

Metformin has a long history of clinical application and has been shown to have outstanding ability in lowering glucose. Recent advances have further revealed its broad modulatory ability beyond glucose-lowering, expanding the scope of metformin applications. Metformin has now been applied as a viable lipid-lowering strategy in non-hyperglycemic obese patients. However, the benefits and underlying pharmacological mechanisms of metformin administration in non-hyperglycemic populations remain to be explained. Our study aimed to systematically investigate the differences in the lipid-lowering function and pharmacological mechanisms of metformin in high- and low-sugar conditions to facilitate the development of individualized metformin use regimens for different clinical patients. We constructed macrophage-derived foam cell models in vitro for subsequent analysis. ORO results showed that metformin significantly reduced lipid accumulation in macrophages in both high and low glucose environments, but the lipid decline was higher in the high glucose environment. By mutual validation and joint analysis of transcriptomics and metabolomics, significant differences in metformin transcriptional and metabolic patterns existed among high and normal glucose environments. The significant alterations of genes such as DGKA, LPL, DGAT2 and lipid metabolites such as LysPA and LysPC partially explained the glucose-dependent pharmacological function of metformin. In conclusion, our study confirmed that the lipid-lowering effect of metformin depends on the extracellular glucose concentration, and systematically studied the molecular mechanism of metformin in different glycemic environments, which provides a certain reference value for the subsequent in-depth study and clinical application.

Metabolic Changes in Serum and Milk of Holstein Cows in Their First to Fourth Parity Revealed by Biochemical Analysis and Untargeted Metabolomics

The performance of dairy cows is closely tied to the metabolic state, and this performance varies depending on the number of times the cows have given birth. However, there is still a lack of research on the relationship between the metabolic state of Holstein cows and the performance of lactation across multiple parities. In this study, biochemical analyses and metabolomics studies were performed on the serum and milk from Holstein cows of parities 1-4 (H1, N = 10; H2, N = 7; H3, N = 9; H4, N = 9) in mid-lactation (DIM of 141 ± 4 days) to investigate the link between performance and metabolic changes. The results of the milk quality analysis showed that the lactose levels were highest in H1 (p = 0.036). The total protein content in the serum increased with increasing parity (p = 0.013). Additionally, the lipase activity was found to be lowest in H1 (p = 0.022). There was no difference in the composition of the hydrolyzed amino acids in the milk among H1 to H4. However, the free amino acids histidine and glutamate in the serum were lowest in H1 and highest in H3 (p < 0.001), while glycine was higher in H4 (p = 0.031). The metabolomics analysis revealed that 53 and 118 differential metabolites were identified in the milk and serum, respectively. The differential metabolites in the cows' milk were classified into seven categories based on KEGG. Most of the differential metabolites in the cows' milk were found to be more abundant in H1, and these metabolites were enriched in two impact pathways. The differential metabolites in the serum could be classified into nine categories and enriched in six metabolic pathways. A total of six shared metabolites were identified in the serum and milk, among which cholesterol and citric acid were closely related to amino acid metabolism in the serum. These findings indicate a significant influence of blood metabolites on the energy and amino acid metabolism during the milk production process in the Holstein cows across 1-4 lactations, and that an in-depth understanding of the metabolic changes that occur in Holstein cows during different lactations is essential for precision farming, and that it is worthwhile to further investigate these key metabolites that have an impact through controlled experiments.

Untargeted metabolomics and lipidomics to assess plasma metabolite changes in dairy goats with subclinical hyperketonemia

Subclinical hyperketonemia (SCHK) is the major metabolic disease observed during the transition period in dairy goats, and is characterized by high plasma levels of nonesterified fatty acids (NEFA) and β-hydroxybutyrate (BHB). However, no prior study has comprehensively assessed metabolomic profiles of dairy goats with SCHK. Plasma samples were collected within 1 h after kidding from SCHK goats (BHB concentration >0.8 mM, n = 7) and clinically healthy goats (BHB concentration <0.8 mM, n = 7) with similar body condition score (2.75 ± 0.15, mean ± standard error of the mean) and parity (primiparous). A combination of targeted and untargeted mass spectrometric approaches was employed for analyzing the various changes in the plasma lipidome and metabolome. Statistical analyses were performed using the GraphPad Prism 8.0, SIMCA-P software (version 14.1), and R packages (version 4.1.3). Plasma aminotransferase, nonesterified fatty acids, and BHB concentrations were greater in the SCHK group, but plasma glucose concentrations were lower. A total of 156 metabolites and 466 lipids were identified. The analysis of untargeted metabolomics data by principal component analysis and orthogonal partial least squares discriminant analysis revealed a separation between SCHK and clinically healthy goats. According to the screening criteria (unpaired t-test, P < 0.05), 30 differentially altered metabolites and 115 differentially altered lipids were detected. Pathway enrichment analysis identified citrate cycle, alanine, aspartate and glutamate metabolism, glyoxylate and dicarboxylate metabolism, and phenylalanine metabolism as significantly altered pathways. A greater concentration of plasma isocitric acid and cis-aconitic acid levels was observed in SCHK goats. In addition, AA such as lysine and isoleucine were greater, whereas alanine and phenylacetylglycine were lower in SCHK dairy goats. Dairy goats with SCHK also exhibited greater oleic acid, acylcarnitine, and phosphatidylcholine and lower choline and sphingomyelins. Acylcarnitines, oleic acid, and tridecanoic acid displayed positive correlations with several lipid species. Alanine, hippuric acid, and histidinyl-phenylalanine were negatively correlated with several lipids. Overall, altered metabolites in SCHK dairy goats indicated a more severe degree of negative energy balance. Data also indicated an imbalance in the tricarboxylic acid (TCA) cycle, lipid metabolism, and AA metabolism. The findings provide a more comprehensive understanding of the pathogenesis of SCHK in dairy goats.

Multi-omics analysis identifies potential mechanisms by which high glucose accelerates macrophage foaming

Atherosclerotic morbidity is significantly higher in the diabetic population. Hyperglycemia, a typical feature of diabetes, has been proven to accelerate foam cell formation. However, the molecular mechanisms behind this process remain unclear. In this study, LPS and IFN-γ were used to convert THP-1-derived macrophages into M1 macrophages, which were then activated with ox-LDL in either high glucose or normal condition. We identified lipids within macrophages by Oil red O staining and total cholesterol detection. The genes involved in lipid absorption, efflux, inflammation, and metabolism were analyzed using qRT-PCR. The mechanisms of high glucose-induced foam cell formation were further investigated through metabolomics and transcriptomics analysis. We discovered that high glucose speed up lipid accumulation in macrophages (both lipid droplets and total cholesterol increased), diminished lipid efflux (ABCG1 down-regulation), and aggravated inflammation (IL1B and TNF up-regulation). Following multi-omics analysis, it was determined that glucose altered the metabolic and transcriptional profiles of macrophages, identifying 392 differently expressed metabolites and 293 differentially expressed genes, respectively. Joint pathway analysis suggested that glucose predominantly disrupted the glycerolipid, glycerophospholipid, and arachidonic acid metabolic pathways in macrophages. High glucose in the glyceride metabolic pathway, for instance, suppressed the transcription of triglyceride hydrolase (LIPG and LPL), causing cells to deposit excess triglycerides into lipid droplets and encouraging foam cell formation. More importantly, high glucose triggered the accumulation of pro-atherosclerotic lipids (7-ketocholesterol, lysophosphatidylcholine, and glycerophosphatidylcholine). In conclusion, this work elucidated mechanisms of glucose-induced foam cell formation via a multi-omics approach.

Multi-Channel Metabolomics Analysis Identifies Novel Metabolite Biomarkers for the Early Detection of Fatty Liver Disease in Dairy Cows

Fatty liver disease, a type of metabolic disorder, frequently occurs in dairy cows during the parturition period, causing a high culling rate and, therefore, considerable economic losses in the dairy industry owing to the lack of effective diagnostic methods. Here, metabolite biomarkers were identified and validated for the diagnosis of metabolic disorders. A total of 58 participant cows, including severe fatty liver disease and normal control groups, in the discovery set (liver biopsy tested, n = 18), test set (suspected, n = 20) and verification set (liver biopsy tested, n = 20), were strictly recruited and a sample collected for their feces, urine, and serum. Non-targeted GC-MS-based metabolomics methods were used to characterize the metabolite profiles and to screen in the discovery set. Eventually, ten novel biomarkers involved in bile acid, amino acid, and fatty acid were identified and validated in the test set. Each of them had a higher diagnostic ability than the traditional serum biochemical indicators, with an average area under the receiver operating characteristic curve of 0.830 ± 0.0439 (n = 10) versus 0.377 ± 0.182 (n = 9). Especially, combined biomarker panels via different metabolic pipelines had much better diagnostic sensitivity and specificity than every single biomarker, suggesting their powerful utilization potentiality for the early detection of fatty liver disease. Intriguingly, the serum biomarkers were confirmed perfectly in the verification set. Moreover, common biological pathways were found to be underlying the pathogenesis of fatty liver syndrome in cattle via different metabolic pipelines. These newly-discovered and non-invasive metabolic biomarkers are meaningful in reducing the high culling rate of cows and, therefore, benefit the sustainable development of the dairy industry.

Identification of Potential Biomarkers and Metabolic Pathways of Different Levels of Heat Stress in Beef Calves

Heat stress (HS) damages the global beef industry by reducing growth performance causing high economic losses each year. However, understanding the physiological mechanisms of HS in Hanwoo calves remains elusive. The objective of this study was to identify the potential biomarkers and metabolic pathways involving different levels of heat stress in Hanwoo calves. Data were collected from sixteen Hanwoo bull calves (169.6 ± 4.6 days old, BW of 136.9 ± 6.2 kg), which were maintained at four designated ranges of HS according to the temperature−humidity index (THI) including: threshold (22 to 24 °C, 60%; THI = 70 to 73), mild (26 to 28 °C, 60%; THI = 74 to 76), moderate (29 to 31 °C, 80%; THI = 81 to 83), and severe (32 to 34 °C, 80%; THI = 89 to 91) using climate-controlled chambers. Blood was collected once every three days to analyze metabolomics. Metabolic changes in the serum of calves were measured using GC-TOF-MS, and the obtained data were calculated by multivariate statistical analysis. Five metabolic parameters were upregulated and seven metabolic parameters were downregulated in the high THI level compared with the threshold (p < 0.05). Among the parameters, carbohydrates (ribose, myo-inositol, galactose, and lactose), organic compounds (acetic acid, urea, and butenedioic acid), fatty acid (oleic acid), and amino acids (asparagine and lysine) were remarkably influenced by HS. These novel findings support further in-depth research to elucidate the blood-based changes in metabolic pathways in heat-stressed Hanwoo beef calves at different levels of THI. In conclusion, these results indicate that metabolic parameters may act as biomarkers to explain the HS effects in Hanwoo calves.

Feedomics provides bidirectional omics strategies between genetics and nutrition for improved production in cattle

Increasing the efficiency and sustainability of cattle production is an effective way to produce valuable animal proteins for a growing human population. Genetics and nutrition are the 2 major research topics in selecting cattle with beneficial phenotypes and developing genetic potentials for improved performance. There is an inextricable link between genetics and nutrition, which urgently requires researchers to uncover the underlying molecular mechanisms to optimize cattle production. Feedomics integrates a range of omic techniques to reveal the mechanisms at different molecular levels related to animal production and health, which can provide novel insights into the relationships of genes and nutrition/nutrients. In this review, we summarized the applications of feedomics techniques to reveal the effect of genetic elements on the response to nutrition and investigate how nutrients affect the functional genome of cattle from the perspective of both nutrigenetics and nutrigenomics. We highlighted the roles of rumen microbiome in the interactions between host genes and nutrition. Herein, we discuss the importance of feedomics in cattle nutrition research, with a view to ensure that cattle exhibit the best production traits for human consumption from both genetic and nutritional aspects.

Metabolomics Analysis Across Multiple Biofluids Reveals the Metabolic Responses of Lactating Holstein Dairy Cows to Fermented Soybean Meal Replacement

This experiment was performed to reveal the metabolic responses of dairy cows to the replacement of soybean meal (SBM) with fermented soybean meal (FSBM). Twenty-four lactating Chinese Holstein dairy cattle were assigned to either the SBM group [the basal total mixed ration (TMR) diet containing 5.77% SBM] or the FSBM group (the experimental TMR diet containing 5.55% FSBM), in a completely randomized design. The entire period of this trial consisted of 14 days for the adjustment and 40 days for data and sample collection, and sampling for rumen liquid, blood, milk, and urine was conducted on the 34th and 54th day, respectively. When SBM was completely replaced by FSBM, the levels of several medium-chain FA in milk (i.e., C13:0, C14:1, and C16:0) rose significantly (p < 0.05), while the concentrations of a few milk long-chain FA (i.e., C17:0, C18:0, C18:1n9c, and C20:0) declined significantly (p < 0.05). Besides, the densities of urea nitrogen and lactic acid were significantly (p < 0.05) higher, while the glucose concentration was significantly (p < 0.05) lower in the blood of the FSBM-fed cows than in the SBM-fed cows. Based on the metabolomics analysis simultaneously targeting the rumen liquid, plasma, milk, and urine, it was noticed that substituting FSBM for SBM altered the metabolic profiles of all the four biofluids. According to the identified significantly different metabolites, 3 and 2 amino acid-relevant metabolic pathways were identified as the significantly different pathways between the two treatments in the rumen fluid and urine, respectively. Furthermore, glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, and cysteine and methionine metabolism were the three key integrated different pathways identified in this study. Results mainly implied that the FSBM replacement could enhance nitrogen utilization and possibly influence the inflammatory reactions and antioxidative functions of dairy cattle. The differential metabolites and relevant pathways discovered in this experiment could serve as biomarkers for the alterations in protein feed and nitrogen utilization efficiency of dairy cows, and further investigations are needed to elucidate the definite roles and correlations of the differential metabolites and pathways.

Weaning age influences indicators of rumen function and development in female Holstein calves

Background

Prenatal and postnatal conditions are crucial for the development of calves. Primiparous cows are still maturing during pregnancy, thus competing with the nutritional needs of their offspring. Therefore, mature cows might provide a superior intrauterine condition. Furthermore, weaning calves at an older age might affect them positively as well by reducing stress and offering time for various organs and their functions to develop. We aimed to evaluate effects of mothers’ parity and calves’ weaning age on gastrointestinal development and corresponding acid–base balance. Fifty-nine female German Holstein calves (about 8 days old) were investigated in a 2 × 2 factorial experiment with factors weaning age (7 vs. 17 weeks) and parity of mother (primiparous vs. multiparous). Calves were randomly assigned to one of these four groups. Animal behavior that was observed included resting, chewing and active behavior.

Results

Behavioral patterns were interactively affected by time and weaning age. Rumen sounds per 2 min increased in early-weaned calves during their weaning period. In late-weaned calves a consistently increase in rumen sounds was already recorded before their weaning period. Urinary N-containing compounds (creatinine, hippuric acid, uric acid, urea, allantoin) were interactively affected by time and weaning age. Concentrations of all measured compounds except urea increased during early weaning. All except hippuric acid concentration decreased in early-weaned calves after weaning. In late-weaned calves allantoin and uric acid increased before weaning and did not change during weaning.

Conclusion

These results suggest that late-weaned calves developed adequate rumen functions and acid–base balance, whereas early-weaned calves might have suffered from ruminal acidosis and catabolism. Weaning calves at 7 weeks of age might be too early for an adequate rumen development.

Integration of Multiplied Omics, a Step Forward in Systematic Dairy Research

Due to their unique multi-gastric digestion system highly adapted for rumination, dairy livestock has complicated physiology different from monogastric animals. However, the microbiome-based mechanism of the digestion system is congenial for biology approaches. Different omics and their integration have been widely applied in the dairy sciences since the previous decade for investigating their physiology, pathology, and the development of feed and management protocols. The rumen microbiome can digest dietary components into utilizable sugars, proteins, and volatile fatty acids, contributing to the energy intake and feed efficiency of dairy animals, which has become one target of the basis for omics applications in dairy science. Rumen, liver, and mammary gland are also frequently targeted in omics because of their crucial impact on dairy animals’ energy metabolism, production performance, and health status. The application of omics has made outstanding contributions to a more profound understanding of the physiology, etiology, and optimizing the management strategy of dairy animals, while the multi-omics method could draw information of different levels and organs together, providing an unprecedented broad scope on traits of dairy animals. This article reviewed recent omics and multi-omics researches on physiology, feeding, and pathology on dairy animals and also performed the potential of multi-omics on systematic dairy research.

Preliminary demonstration of benchtop NMR metabolic profiling of feline urine: chronic kidney disease as a case study

Objective

The use of benchtop metabolic profiling technology based on nuclear magnetic resonance (NMR) was evaluated in a small cohort of cats with a view to applying this as a viable and rapid metabolic tool to support clinical decision making.

Results

Urinary metabolites were analysed from four subjects consisting of two healthy controls and two chronic kidney disease (CKD) IRIS stage 2 cases. The study identified 15 metabolites in cats with CKD that were different from the controls. Among them were acetate, creatinine, citrate, taurine, glycine, serine and threonine. Benchtop NMR technology is capable of distinguishing between chronic kidney disease case and control samples in a pilot feline cohort based on metabolic profile. We offer perspectives on the further development of this pilot work and the potential of the technology, when combined with sample databases and computational intelligence techniques to offer a clinical decision support tool not only for cases of renal disease but other metabolic conditions in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05888-y.

Hepatic transcriptome perturbations in dairy cows fed different forage resources

Background

Forage plays critical roles in milk performance of dairy. However, domestic high-quality forage such as alfalfa hay is far from being sufficient in China. Thus, more than 1 million tons of alfalfa hay were imported in China annually in recent years. At the same time, more than 10 million tons of corn stover are generated annually in China. Thus, taking full advantage of corn stover to meet the demand of forage and reduce dependence on imported alfalfa hay has been a strategic policy for the Chinese dairy industry. Changes in liver metabolism under different forage resources are not well known. Thus, the objective of the present study was to investigate the effect of different forage resources on liver metabolism using RNAseq and bioinformatics analyses.

Results

The results of this study showed that the cows fed a diet with corn stover (CS) as the main forage had lower milk yield, DMI, milk protein content and yield, milk fat yield, and lactose yield than cows fed a mixed forage (MF) diet (P <  0.01). KEGG analysis for differently expressed genes (DEG) in liver (81 up-regulated and 423 down-DEG, Padj ≤0.05) showed that pathways associated with glycan biosynthesis and metabolism and amino acid metabolism was inhibited by the CS diet. In addition, results from DAVID and ClueGO indicated that biological processes related to cell-cell adhesion, multicellular organism growth, and amino acid and protein metabolism also were downregulated by feeding CS. Co-expression network analysis indicated that FAM210A, SLC26A6, FBXW5, EIF6, ZSCAN10, FPGS, and ARMCX2 played critical roles in the network. Bioinformatics analysis showed that genes within the co-expression network were enriched to “pyruvate metabolic process”, “complement activation, classical pathway”, and “retrograde transport, endosome to Golgi”.

Conclusions

Results of the present study indicated that feeding a low-quality forage diet inhibits important biological functions of the liver at least in part due to a reduction in DMI. In addition, the results of the present study provide an insight into the metabolic response in the liver to different-quality forage resources. As such, the data can help develop favorable strategies to improve the utilization of corn stover in China.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07332-0.

A Serum Metabolic Profiling Analysis During the Formation of Fatty Liver in Landes Geese via GC-TOF/MS

During the process of fatty liver production by overfeeding, the levels of endogenous metabolites in the serum of geese would change dramatically. This study investigated the effects of overfeeding on serum metabolism of Landes geese and the underlying mechanisms using a metabolomics approach. Sixty Landes geese of the same age were randomly divided into the following three groups with 20 replicates in each group: D0 group (free from gavage); D7 group (overfeeding for 7 days); D25 group (overfeeding for 25 days). At the end of the experiment, 10 geese of similar weight from each group were selected for slaughter and sampling. The results showed that overfeeding significantly increased the body weight and the liver weight of geese. Serum enzymatic activities and serum lipid levels were significantly enhanced following overfeeding. Gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS) was employed to explore the serum metabolic patterns, and to identify potential contributors to the formation of fatty liver and the correlated metabolic pathways. Relative to overfeeding for 7 days, a large number of endogenous molecules in serum of geese overfed for 25 days were altered. Continuous elevated levels of pyruvic acid, alanine, proline and beta-glycerophosphoric acid and reduced lactic acid level were observed in the serum of overfed geese. Pathway exploration found that the most of significantly different metabolites were involved in amino acids, carbohydrate and lipid metabolism. The present study exhibited the efficient capability of Landes geese to produce fatty liver, identified potential biomarkers and disturbed metabolic pathways in liver steatosis. These findings might reveal the underlying mechanisms of fatty liver formation and provide some theoretical basis for the diagnosis and treatment of liver diseases.

Nuclear magnetic resonance (NMR)-based metabolome profile evaluation in dairy cows with and without displaced abomasum

Background

Displaced abomasum (DA) is a condition of dairy cows that severely impacts animal welfare and causes huge economic losses.

Objective

To assess the metabolic status of the disease using metabolomics in serum, urine and liver samples aimed at both water soluble and lipid soluble fractions.

Methods

Fifty Holstein multiparous cows with DA (42 left, 8 right) and 20 clinically healthy Holstein multiparous cows were used. Left DA was associated with concomitant ketosis in 19 animals and right in two. NMR-based metabolomics approach and hematological and biochemical analyses were performed. Statistical analysis was carried out on ¹H-NMR data after they have been normalized using PQN method.

Results

Contrary to generated PCA score plots the OPLS-supervised method revealed differences between healthy animals and diseased ones based on serum water-soluble samples. While water and lipid soluble metabolites decreased in serum samples, fatty acid fractions and cholesterol were increased in liver samples in DA affected cows. The metabolomic and chemical profiles clearly revealed that cows with DA (especially with LDA) were at risk of ketosis and fatty liver. Serum hippuric acid concentration was significantly higher in healthy cows in comparison with LDA, whereas serum glycine concentration was reported higher for healthy when compared to RDA affected animals.

Conclusion

A biochemical network and pathway mapping revealed ‘valine, leucine and isoleucine biosynthesis’ and ‘phenylalanine, tyrosine and tryptophan biosynthesis’ as the most probable altered metabolic pathway in DA condition. Serum was advocated as the optimal biological matrix for the ¹H-NMR analysis.

A blood metabolomics study of metabolic variations in Inner Mongolia white cashmere goats under shortened and natural photoperiod conditions

This study investigated metabolic variations by using gas chromatography – mass spectrometry (GC–MS)-based metabolomics in the blood of Inner Mongolia white cashmere goats under shortened and natural photoperiod conditions. Twenty-four female (non-pregnant) Inner Mongolia white cashmere goats aged 1–1.5 yr with similar live weights (mean, 20.36 ± 2.63 kg) were randomly allocated into two groups: a natural daily photoperiod group (NDPP group: 10–16 h light, n = 12) and a short daily photoperiod group (SDPP group: 7 h light:17 h dark, n = 12). In this study, we found that a SDPP promoted the blood metabolic perturbations based on the GC–MS-based metabolomics investigation, and nine metabolites were related to a SDPP. Compared with the NDPP group, the contents of serine, oxaloacetic acid, xylose, l-3,4-dihydroxyphenylalanine, and xanthosine significantly were up-regulated, whereas the contents of carnitine, 1,3-diaminopropane, indole-3-acetic acid, and l-kynurenine were significantly down-regulated in the SDPP group. The different metabolites could contribute to the regulation mechanisms of promoting cashmere growth of goats in the SDPP group.

Effect of Chilled Ageing Conditioning at 4°C in Lamb Longissimus Dorsi Muscles on Water-Soluble Flavour Precursors as Revealed by a Metabolomic Approach

The objective of this study was to investigate, by a metabolomic approach, the effects of chilled ageing conditioning at 4°C in lamb longissimus dorsi (LD) muscles on water-soluble flavour precursors. The results showed that the content of nucleotide degradation products significantly increased (P<0.05) due to the adjusted biosynthesis of alkaloids derived from histidine and purine from day 0 to day 4. Additionally, the content of glycolytic compounds significantly increased (P<0.05) due to enhanced glycolysis, and the content of organic acid increased (P<0.05) because of the altered tricarboxylic acid cycle (TCA) from day 0 to day 4. In addition, the content of total free amino acids significantly increased (P<0.05), owing to the altered biosynthesis of amino acids from day 4 to day 8. These results are significant proof that there were quantitative changes observed in lamb flavour precursors during chilled ageing.

Metabolomics reveals potential biomarkers in the rumen fluid of dairy cows with different levels of milk production

Objective

In the present study, an liquid chromatography/mass spectrometry (LC/MS) metabolomics approach was performed to investigate potential biomarkers of milk production in high- and low-milk-yield dairy cows and to establish correlations among rumen fluid metabolites.

Methods

Sixteen lactating dairy cows with similar parity and days in milk were divided into high-yield (HY) and low-yield (LY) groups based on milk yield. On day 21, rumen fluid metabolites were quantified applying LC/MS.

Results

The principal component analysis and orthogonal correction partial least squares discriminant analysis showed significantly separated clusters of the ruminal metabolite profiles of HY and LY groups. Compared with HY group, a total of 24 ruminal metabolites were significantly greater in LY group, such as 3-hydroxyanthranilic acid, carboxylic acids, carboxylic acid derivatives (L-isoleucine, L-valine, L-tyrosine, etc.), diazines (uracil, thymine, cytosine), and palmitic acid, while the concentrations of 30 metabolites were dramatically decreased in LY group compared to HY group, included gentisic acid, caprylic acid, and myristic acid. The metabolite enrichment analysis indicated that protein digestion and absorption, ABC transporters and unsaturated fatty acid biosynthesis were significantly different between the two groups. Correlation analysis between the ruminal microbiome and metabolites revealed that certain typical metabolites were exceedingly associated with definite ruminal bacteria; Firmicutes, Actinobacteria, and Synergistetes phyla were highly correlated with most metabolites.

Conclusion

These findings revealed that the ruminal metabolite profiles were significantly different between HY and LY groups, and these results may provide novel insights to evaluate biomarkers for a better feed digestion and may reveal the potential mechanism underlying the difference in milk yield in dairy cows.

Integrating a generalized data analysis workflow with the Single-probe mass spectrometry experiment for single cell metabolomics

We conducted single cell metabolomics studies of live cancer cells through online single cell mass spectrometry (SCMS) experiments combined with a generalized comprehensive data analysis workflow. The SCMS experiments were carried out using the Single-probe device coupled with a mass spectrometer to measure molecular profiles of cells in response to two mitotic inhibitors, taxol and vinblastine, under a series of treatment conditions. SCMS metabolomic data were analyzed using a comprehensive approach, including data pre-treatment, visualization, statistical analysis, machine learning, and pathway enrichment analysis. For comparative studies, traditional liquid chromatography-MS (LC-MS) experiments were conducted using lysates prepared from bulk cell samples. Metabolomic profiles of single cells were visualized through Partial Least Square-Discriminant Analysis (PLS-DA), and the phenotypic biomarkers associated with emerging phenotypes induced by drug treatment were discovered and compared through a series of rigorous statistical analysis. Species of interest were further identified at both the single cell and population levels. In addition, four biological pathways potentially involved in the drug treatment were determined through pathway enrichment analysis. Our work demonstrated the capability of comprehensive pipeline studies of single cell metabolomics. This method can be potentially applied to broader types of SCMS datasets for future pharmaceutical and chemotherapeutic research.

Invited review: Advances and challenges in application of feedomics to improve dairy cow production and health

Dairy cattle science has evolved greatly over the past century, contributing significantly to the improvement in milk production achieved today. However, a new approach is needed to meet the increasing demand for milk production and address the increased concerns about animal health and welfare. It is now easy to collect and access large and complex data sets consisting of molecular, physiological, and metabolic data as well as animal-level data (such as behavior). This provides new opportunities to better understand the mechanisms regulating cow performance. The recently proposed concept of feedomics could help achieve this goal by increasing our understanding of interactions between the different components or levels and their impact on animal production. Feedomics is an emerging field that integrates a range of omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics, and metatranscriptomics) to provide these insights. In this way, we can identify the best strategies to improve overall animal productivity, product quality, welfare, and health. This approach can help research communities elucidate the complex interactions among nutrition, environment, management, animal genetics, metabolism, physiology, and the symbiotic microbiota. In this review, we summarize the outcomes of the most recent research on omics in dairy cows and highlight how an integrated feedomics approach could be applied in the future to improve dairy cow production and health. Specifically, we focus on 2 topics: (1) improving milk yield and milk quality, and (2) understanding metabolic physiology in transition dairy cows, which are 2 important challenges faced by the dairy industry worldwide.

Effect of different time intervals after feeding on plasma metabolites in growing pigs: an UPLC-MS-based metabolomics study

A diet consumed by pigs provides the nutrients for the production of a large number of metabolites that, after first-pass metabolism in the liver, circulate systemically where they may exert diverse physiologic influences on pigs. So far, little is known of how feeding elicits changes in metabolic profiles for growing pigs. This study investigated differences in plasma metabolites in growing pigs at several intervals after feeding using the technique of metabolomics. Ten barrows (22.5 ± 0.5 kg BW) were fed a corn-soybean meal basal diet and were kept in metabolism crates for a period of 11 days. An indwelling catheter was inserted into the jugular vein of each pig before the experimental period. Plasmas before and 1, 4, and 8 hr after feeding were collected at day 11 and differential metabolites were determined using a metabolomics approach. Direct comparison at several intervals after feeding revealed differences in 14 compounds. Identified signatures were enriched in metabolic pathways related to linoleic acid metabolism, arginine and proline metabolism, lysine degradation, glycine, serine and threonine metabolism, and lysine biosynthesis. These results suggest that plasma metabolites of growing pigs after feeding were modulated through changes in linoleic acid metabolism and amino acid metabolism.

Trichostatin A modulates cellular metabolism in renal cell carcinoma to enhance sunitinib sensitivity

Although sunitinib is the first-line drug for progressive renal cell carcinoma (RCC), most patients experience its tolerance. One possible way of overcoming drug resistance is combination therapy. Epigenetic modifier is one of the candidate drug group. A recent evidence suggests that cell metabolism is regulated by epigenetic mechanisms. Epigenetic abnormalities lead to changes in metabolism and may contribute to drug resistance and progression of RCC. Consequently, we investigated whether trichostatin A (TSA), a potent histone-deacetylase (HDAC) inhibitor, alters sunitinib-induced cytotoxicity and metabolism in RCC cells at epigenetic regulatory concentrations. Combined metabolome and transcriptome analysis suggested that TSA impacts on energy productive metabolic pathways, such as those involving TCA cycle and nucleotide metabolism especially for increase of hyperphosphorylated form. Combination of sunitinib and TSA increased cell death with PARP cleavage, an early marker of mitochondrial apoptosis, whereas receptor tyrosine kinase signaling, which is the target of sunitinib, was not altered by TSA. Finally, the established sunitinib resistant-RCC cell (786-O Res) was also exposed to sunitinib and TSA combination, resulting in significant growth inhibition. In summary, it was suggested that TSA reduces sunitinib resistance by triggering intracellular metabolome shifts regarding energy metabolism, that is the first recognized mechanism as an HDAC inhibitor.

GC-MS-based identification and statistical analysis of liposoluble components in the rhizosphere soils of Panax notoginseng

Continuous cropping obstacle, mainly caused by microorganisms and organic components in soil, has become a serious problem for the plantation of Panax notoginseng (Araliaceae) due to the rapidly increased demands of this famous herbal medicine in recent decades. The rhizosphere soils cultivated with 3-year-old healthy and ill notoginseng were chemically investigated by gas chromatography-mass spectrometry (GC-MS) and compared with the corresponding soils without the plantation of notoginseng. Totally 47 liposoluble components were identified. Furthermore, the multiple statistical analysis showed that these constituents were qualitatively and quantitatively associated with the differences between the cultivated soil with P. notoginseng and the uncultivated soil. Among them, neophytadiene (4), d-α-tocopherol (38), (3β,22E,24S)-ergosta-5,22-dien-3-ol (39), (3β,24R)-ergost-5-en-3-ol (40), stigmasta-5,22-dien-3-ol (41), stigmast-4-en-3-one (44) and (5α)-stigmastane-3,6-dione (47) contributed most to the significant differences between the cultivated and uncultivated soils, whereas cyclopentadecane (3), octadecanoic acid methyl ester (16), docosanoic acid ethyl ester (31), nonacosane (34), 38 and 39 were found in much higher amount in the soils with ill P. notoginseng as compared to the case of those with the healthy P. notoginseng. On the other hand, liposoluble components in different cultivation areas were of great diversity; however, they were able to remain relatively consistent across the overall trend of differential substances.

Liposoluble components in the rhizosphere soils of Panax notoginseng were found as potential allelochemicals by GC-MS identification and statistical analysis.

Metabolomics and pathway analyses to characterize metabolic alterations in pregnant dairy cows on D 17 and D 45 after AI

Nutrient flow to the embryo and placenta is crucial for proper development and growth during pregnancy. In this study, a metabonomic analysis was undertaken to better understand global changes in pregnant dairy cows on D 17 and D 45 after timed artificial insemination (AI). Metabolic changes in the blood plasma of pregnant dairy cows were investigated using HPLC-MS and a multivariate statistical analysis. Changes in metabolic networks were established using the MetPA method. Alterations in six metabolic pathways were found on D 17 and D 45, including variations in the level of alpha-linolenic acid metabolism, glycerophospholipid metabolism, pentose and glucuronate interconversions, glycerolipid metabolism, folate biosynthesis, and tyrosine metabolism. In addition to these pathways, 9 metabolic pathways were markedly altered on D 45. These pathways included changes in the one-carbon pool caused by folate; phenylalanine, tyrosine and tryptophan biosynthesis; thiamine metabolism; pantothenate and CoA biosynthesis; purine metabolism; inositol phosphate metabolism; amino sugar and nucleotide sugar metabolism; pentose phosphate; and the TCA pathway. The combination of metabonomics and network methods used in this study generated rich biochemical insight into possible biological modules related to early pregnancy in dairy cows.

Lactation-related metabolic mechanism investigated based on mammary gland metabolomics and 4 biofluids' metabolomics relationships in dairy cows

Background

Lactation is extremely important for dairy cows; however, the understanding of the underlying metabolic mechanisms is very limited. This study was conducted to investigate the inherent metabolic patterns during lactation using the overall biofluid metabolomics and the metabolic differences from non-lactation periods, as determined using partial tissue-metabolomics. We analyzed the metabolomic profiles of four biofluids (rumen fluid, serum, milk and urine) and their relationships in six mid-lactation Holstein cows and compared their mammary gland (MG) metabolomic profiles with those of six non-lactating cows by using gas chromatography-time of flight/mass spectrometry.

Results

In total, 33 metabolites were shared among the four biofluids, and 274 metabolites were identified in the MG tissues. The sub-clusters of the hierarchical clustering analysis revealed that the rumen fluid and serum metabolomics profiles were grouped together and highly correlated but were separate from those for milk. Urine had the most different profile compared to the other three biofluids. Creatine was identified as the most different metabolite among the four biofluids (VIP = 1.537). Five metabolic pathways, including gluconeogenesis, pyruvate metabolism, the tricarboxylic acid cycle (TCA cycle), glycerolipid metabolism, and aspartate metabolism, showed the most functional enrichment among the four biofluids (false discovery rate < 0.05, fold enrichment >2). Clear discriminations were observed in the MG metabolomics profiles between the lactating and non-lactating cows, with 54 metabolites having a significantly higher abundance (P < 0.05, VIP > 1) in the lactation group. Lactobionic acid, citric acid, orotic acid and oxamide were extracted by the S-plot as potential biomarkers of the metabolic difference between lactation and non-lactation. The TCA cycle, glyoxylate and dicarboxylate metabolism, glutamate metabolism and glycine metabolism were determined to be pathways that were significantly impacted (P < 0.01, impact value >0.1) in the lactation group. Among them, the TCA cycle was the most up-regulated pathway (P < 0.0001), with 7 of the 10 related metabolites increased in the MG tissues of the lactating cows.

Conclusions

The overall biofluid and MG tissue metabolic mechanisms in the lactating cows were interpreted in this study. Our findings are the first to provide an integrated insight and a better understanding of the metabolic mechanism of lactation, which is beneficial for developing regulated strategies to improve the metabolic status of lactating dairy cows.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4314-1) contains supplementary material, which is available to authorized users.