Milk metabolome relates enteric methane emission to milk synthesis and energy metabolism pathways

Microbiome and metabolome analyses of milk and feces from dairy cows with healthy, subclinical, and clinical mastitis

Mastitis is commonly recognized as a localized inflammatory udder disease induced by the infiltration of exogenous pathogens. In the present study, our objective was to discern fecal and milk variations in both microbiota composition and metabolite profiles among three distinct groups of cows: healthy cows, cows with subclinical mastitis and cows with clinical mastitis. The fecal microbial community of cows with clinical mastitis was significantly less rich and diverse than the one harbored by healthy cows. In parallel, mastitis caused a strong disturbance in milk microbiota. Metabolomic profiles showed that eleven and twenty-eight molecules exhibited significant differences among the three groups in feces and milk, respectively. Similarly, to microbiota profile, milk metabolome was affected by mastitis more extensively than fecal metabolome, with particular reference to amino acids and sugars. Pathway analysis revealed that amino acids metabolism and energy metabolism could be considered as the main pathways altered by mastitis. These findings underscore the notable distinctions of fecal and milk samples among groups, from microbiome and metabolomic points of view. This observation stands to enhance our comprehension of mastitis in dairy cows.

Proteomics and metabolomics analyses of Streptococcus agalactiae isolates from human and animal sources

Streptococcus agalactiae (S. agalactiae), group B Streptococcus (GBS), a major cause of infection in a wide variety of diseases, have been compared in different human and animal sources. We aimed to compare the bacterial proteome and metabolome profiles of human and animal S. agalactiae strains to delineate biological interactions relevant to infection. With the innovative advancement in mass spectrometry, a comparative result between both strains provided a solid impression of different responses to the host. For instance, stress-related proteins (Asp23/Gls24 family envelope stress response protein and heat shock protein 70), which play a role in the survival of GBS under extreme environmental conditions or during treatment, are highly expressed in human and animal strains. One human strain contains ꞵ-lactamase (serine hydrolase) and biofilm regulatory protein (lytR), which are important virulence regulators and potential targets for the design of novel antimicrobials. Another human strain contains the aminoglycosides-resistance bifunctional AAC/APH (A0A0U2QMQ5) protein, which confers resistance to almost all clinically used aminoglycosides. Fifteen different metabolites were annotated between the two groups. L-aspartic acid, ureidopropionic acid, adenosine monophosphate, L-tryptophan, and guanosine monophosphate were annotated at higher levels in human strains. Butyric acid, fumaric acid, isoleucine, leucine, and hippuric acid have been found in both human and animal strains. Certain metabolites were uniquely expressed in animal strains, with fold changes greater than 2. For example, putrescine modulates biofilm formation. Overall, this study provides biological insights into the substantial possible bacterial response reflected in its macromolecular production, either at the proteomic or metabolomic level.

Metabolomic Analysis of Multiple Biological Specimens (Feces, Serum, and Urine) by 1H-NMR Spectroscopy from Dairy Cows with Clinical Mastitis

Due to huge economic losses to the dairy industry worldwide, mastitis can be considered as one of the most common diseases in dairy cows. This work aimed to study this disease by comparing multiple biological specimens (feces, serum, and urine) from individuals with or without clinical mastitis. This was performed by a single analytical platform, namely ¹H-NMR, through a multi-matrix strategy. Thanks to the high reproducibility of ¹H-NMR, we could characterize 120 molecules across dairy cow feces, serum, and urine. Among them, 23 molecules were in common across the three biofluids. By integrating the results of multi-matrix metabolomics, several pathways pertaining to energy metabolism and amino acid metabolism appeared to be affected by clinical mastitis. The present work wished to deepen the understanding of dairy cow mastitis in its clinical form. Simultaneous analysis of metabolome changes across several key biofluids could facilitate knowledge discovery and the reliable identification of potential biomarkers, which could be, in turn, used to shed light on the early diagnosis of dairy cow mastitis in its subclinical form.

Metagenomic insights into the modulatory effects of kelp powder (Thallus laminariae)-Treated dairy milk on growth performances and physiological lipometabolic processes of kunming mice

Kelp powder, supplemented with a dairy cow diet, effectively improved the milk polyunsaturated fatty acids (PUFAs) content. However, little information exists on the downstream effects of the kelp-treated milk on body health, gut microbiota, and nutrient metabolism. For this purpose, 48 3-week old Kunming (KM) male mice with an average body weight of 16.1 g ± 0.2 g were randomly divided into the control treatment (CON, fed with standard chow), the common milk supplement treatment (Milk), and the kelp powder-treated milk supplement treatment (KPM). The experiment lasted for 35 days, with a 7-day long adaptive period and a 28-day long main trial. Phenotypic parameters including growth performances and serum lipids-related parameters were first measured, and results indicated that Milk and KPM supplement significantly promoted the total body weight gain (P < 0.05), while significantly decreasing the feed conversion ratio compared with CON (P < 0.05). No significant differences were observed in the blood lipids content among all three treatments, however, the triglyceride content showed a decreasing trend after KPM supplement treatment. Further, activities of liver lipometabolic-related enzymes were investigated to determine the underlying factors that impacted physiological lipid metabolism. KPM treatment showed a significant reductive effect on the activity of lipogenesis-related enzymes, such as FAS and ACC, while a significant stimulative effect on the activity of lipolysis-related enzymes included the ATGL and CPT1 compared with CON (P < 0.05). Finally, gastrointestinal tract development and cecal microbiota community that correlated with body lipid degradation and absorption were measured to determine the underlying mechanism of KPM supplementation on physiological lipid metabolism. Results indicated that supplementation with KPM significantly enhanced cecal bacteria diversity which was reflected in the significant increase of Chao1 and ACE indexes. Besides, starch-degraded bacteria such as Faecalibacterium, Ruminococcaceae, and Streptococcus are significant decreased (P < 0.05), while cellulose-degraded bacteria including Parabacteroides, Prevotella, Lactobacillus, Clostridium, and Bifidobacterium are significantly increased (P < 0.05) after KPM supplement, which may further restrict the energy generation and therefore reduce the lipid deposition. In summary, kelp supplement helped increase the milk PUFAs content, enhance the bacterial diversity and relative abundances of probiotics, which finally modulated physiological lipid metabolism, and promote growth performances.

Microbial and metabolomic insights into the bovine lipometabolic responses of rumen and mammary gland to zymolytic small peptide supplementation

Small peptides provide the easily utilized nitrogen for rumen microbial and promote acetate generation for milk fat synthesis. However, the impacts of peptide supplements on lipometabolic processes were still unclear. Therefore, a total of 800 multiparous dairy herds (with an average live weight of 667.6 ± 39.4 kg, an average lactation of 89.3 ± 18.8 days, and an average calving parity of 2.76 ± 0.47) were randomly allocated to the control (CON) and the small peptide (SP) supplement (100 g/day for each cow) treatments, respectively. A 35-day-long feeding procedure that includes a 7-day-long pretreatment test and a 28-day-long treatment test was followed for all cows. Dry matter intake (DMI) was recorded every day and calculated by the deviation between the supply and residue, while the daily milk production was automatically recorded through the rotary milking facilities. Milk samples were collected from each replicate on the last day, followed by the milk quality and milk lipid composition measurement. Rumen fluid samples were collected on the last day through esophageal tubing 3 h after morning feeding for the determination of the underlying mechanism of the small peptide on lipid metabolism through the measurement of rumen lipometabolic-related metabolites and rumen bacterial communities. Results indicated that dry matter intake showed an increasing trend, while milk production and the milk fat content remarkably increased after SP supplement (P < 0.05). Further detailed detection showed the mainly increased milk composition focused on monounsaturated fatty acid (MUFA) and polyunsaturated fatty acid (PUFA). Acetate-producing microbes, such as Acetitomaculum, Bifidobacterium, Succiniclasticum, and Succinivibrio, and butyrate-producing microbes, such as Shuttleworthia and Saccharofermentans, significantly proliferated, which causatively brought the increased ruminal content of acetate, isobutyrate, and butyrate after SP supplement (P < 0.05) compared with CON. Lipometabolic metabolites such as phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylserine (PS), triacylglycerol (TG), and Acetyl-CoA also significantly increased after SP supplement. In summary, SP supplements help to increase milk fat content through the proliferation of rumen bacterial communities, which provided more acetate and butyrate for milk fat synthesis combined with the promotion of ruminal lipometabolism.

The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies

Ruminant supply chains contribute 5.7 gigatons of CO_2-eq per annum, which represents approximately 80% of the livestock sector emissions. One of the largest sources of emission in the ruminant sector is methane (CH₄), accounting for approximately 40% of the sectors total emissions. With climate change being a growing concern, emphasis is being put on reducing greenhouse gas emissions, including those from ruminant production. Various genetic and environmental factors influence cattle CH₄ production, such as breed, genetic makeup, diet, management practices, and physiological status of the host. The influence of genetic variability on CH₄ yield in ruminants indicates that genomic selection for reduced CH₄ emissions is possible. Although the microbiology of CH₄ production has been studied, further research is needed to identify key differences in the host and microbiome genomes and how they interact with one another. The advancement of “-omics” technologies, such as metabolomics and metagenomics, may provide valuable information in this regard. Improved understanding of genetic mechanisms associated with CH₄ production and the interaction between the microbiome profile and host genetics will increase the rate of genetic progress for reduced CH₄ emissions. Through a systems biology approach, various “-omics” technologies can be combined to unravel genomic regions and genetic markers associated with CH₄ production, which can then be used in selective breeding programs. This comprehensive review discusses current challenges in applying genomic selection for reduced CH₄ emissions, and the potential for “-omics” technologies, especially metabolomics and metagenomics, to minimize such challenges. The integration and evaluation of different levels of biological information using a systems biology approach is also discussed, which can assist in understanding the underlying genetic mechanisms and biology of CH₄ production traits in ruminants and aid in reducing agriculture’s overall environmental footprint.

Milk metabolome reveals variations on enteric methane emissions from dairy cows fed a specific inhibitor of the methanogenesis pathway

Metabolome profiling in biological fluids is an interesting approach for exploring markers of methane emissions in ruminants. In this study, a multiplatform metabolomics approach was used for investigating changes in milk metabolic profiles related to methanogenesis in dairy cows. For this purpose, 25 primiparous Holstein cows at similar lactation stage were fed the same diet supplemented with (treated, n = 12) or without (control, n = 13) a specific antimethanogenic additive that reduced enteric methane production by 23% with no changes in intake, milk production, and health status. The study lasted 6 wk, with sampling and measures performed in wk 5 and 6. Milk samples were analyzed using 4 complementary analytical methods, including 2 untargeted (nuclear magnetic resonance and liquid chromatography coupled to a quadrupole-time-of-flight mass spectrometer) and 2 targeted (liquid chromatography-tandem mass spectrometry and gas chromatography coupled to a flame ionization detector) approaches. After filtration, variable selection and normalization data from each analytical platform were then analyzed using multivariate orthogonal partial least square discriminant analysis. All 4 analytical methods were able to differentiate cows from treated and control groups. Overall, 38 discriminant metabolites were identified, which affected 10 metabolic pathways including methane metabolism. Some of these metabolites such as dimethylsulfoxide, dimethylsulfone, and citramalic acid, detected by nuclear magnetic resonance or liquid chromatography-mass spectrometry methods, originated from the rumen microbiota or had a microbial-host animal co-metabolism that could be associated with methanogenesis. Also, discriminant milk fatty acids detected by targeted gas chromatography were mostly of ruminal microbial origin. Other metabolites and metabolic pathways significantly affected were associated with AA metabolism. These findings provide new insight on the potential role of milk metabolites as indicators of enteric methane modifications in dairy cows.

Dandelion (Taraxacum mongolicum Hand.-Mazz.) Supplementation-Enhanced Rumen Fermentation through the Interaction between Ruminal Microbiome and Metabolome

This study investigated the effects of dandelion on the ruminal metabolome and microbiome in lactating dairy cows. A total of 12 mid-lactation dairy cows were selected and randomly classified into two groups, supplementing dandelion with 0 (CON) and 200 g/d per cow (DAN) above basal diet, respectively. Rumen fluid samples were collected in the last week of the trial for microbiome and metabolome analysis. The results showed that supplementation of DAN increased the concentrations of ammonia nitrogen, acetate, and butyrate significantly. The rumen bacterial community was significantly changed in the DAN group, with Bacterioidetes, Firmicutes, and Proteobacteria being the main ruminal bacterial phyla. The abundance of Ruminococcaceae_NK4A214_group, UCG_005, and Christensenellaceae_R_7_group were relatively higher, whereas that of Erysipelotrichaceae_UCG_002 and Dialister were lower in the DAN than those in the CON. Metabolomics analysis showed that the content of d-glucose, serotonin, ribulose-5-phosphate, and d-glycerate were higher in the DAN group. These metabolites were enriched in the starch and sucrose metabolism, pentose phosphate pathway, tryptophan metabolism, and glycerolipid metabolism. The ribulose-5-phosphate and d-glycerate were correlated with Ruminococcaceae_NK4A214_group, UCG_005, and Christensenellaceae_R-7_group positively. This study demonstrated that the supplementation of dandelion impacts the ruminal microorganisms and metabolites in a way that rumen fermentation was enhanced in lactating dairy cows.

Predictive ability of host genetics and rumen microbiome for subclinical ketosis

Subclinical metabolic disorders such as ketosis cause substantial economic losses for dairy farmers in addition to the serious welfare issues they pose for dairy cows. Major hurdles in genetic improvement against metabolic disorders such as ketosis include difficulties in large-scale phenotype recording and low heritability of traits. Milk concentrations of ketone bodies, such as acetone and β-hydroxybutyric acid (BHB), might be useful indicators to select cows for low susceptibility to ketosis. However, heritability estimates reported for milk BHB and acetone in several dairy cattle breeds were low. The rumen microbial community has been reported to play a significant role in host energy homeostasis and metabolic and physiologic adaptations. The current study aims at investigating the effects of cows' genome and rumen microbial composition on concentrations of acetone and BHB in milk, and identifying specific rumen microbial taxa associated with variation in milk acetone and BHB concentrations. We determined the concentrations of acetone and BHB in milk using nuclear magnetic resonance spectroscopy on morning milk samples collected from 277 Danish Holstein cows. Imputed high-density genotype data were available for these cows. Using genomic and microbial prediction models with a 10-fold resampling strategy, we found that rumen microbial composition explains a larger proportion of the variation in milk concentrations of acetone and BHB than do host genetics. Moreover, we identified associations between milk acetone and BHB with some specific bacterial and archaeal operational taxonomic units previously reported to have low to moderate heritability, presenting an opportunity for genetic improvement. However, higher covariation between specific microbial taxa and milk acetone and BHB concentrations might not necessarily indicate a causal relationship; therefore further validation is needed before considering implementation in selection programs.

Probiotic, Bacillus subtilis E20 alters the immunity of white shrimp, Litopenaeus vannamei via glutamine metabolism and hexosamine biosynthetic pathway

The purpose of this study was to profile the mechanisms of action of probiotic, Bacillus subtilis E20 in activating the immunity of white shrimp, Litopenaeus vannamei. Two groups of shrimp were studied. One group was fed a control diet without probiotic supplementation and the other was fed a probiotic-containing diet at a level of 10⁹ cfu kg diet^-1. After the 8-week feeding regimen, the metabolite composition in the hepatopancreas of shrimp were investigated using ¹H nuclear magnetic resonance (¹H NMR) based metabolomic analysis. Results from the ¹H NMR analysis revealed that 16 hepatopancreatic metabolites were matched and identified among groups, of which 2 metabolites, creatinine and glutamine were significantly higher in probiotic group than in the control group. This result was confirmed by the reverse-phase high-performance liquid chromatography (RP-HPLC) and spectrophotometric analysis. Transcriptome analysis indicated the expressions of 10 genes associated with antioxidant enzymes, pattern recognition proteins and antimicrobial molecules, more active expression in the shrimp fed a diet supplemented with probiotic as compared to that of shrimp in control. In addition, the expressions of 4 genes involved with hexosamine biosynthesis pathway (HBP) and UDP-N-acetylglucosamine-peptide N-acetylglucosaminyltransferase for protein O-glycosylation were also higher in hepatopancreas of probiotic-treated shrimp than in shrimp fed a control diet. Western blot and enzyme-linked immunosorbent assay showed that heat shock factor 1, heat shock protein 70, and protein O-glycosylation in hepatopancreas were higher in probiotic group than the control group. These findings suggest that probiotic, B. subtilis E20 promotes the digestibility of glutamine in the diet, and that the increased glutamine in shrimp can be used as fuel for immune cells or may be used to regulate immune molecule expressions and protein O-glycosylation via the HBP to increase protein O-glycosylation, thereby improving the health of shrimp.

Short communication: Effect of different kefir grains on the attributes of kefir produced with milk from Costa Rica

Kefir is an artisanal product that is gaining scientific attention due to its increase in consumption attributed to its potential health benefits. The effect on the quality attributes of kefir grains of different origin (household and commercial) and preserved with different methods (drying and freezing) was evaluated to standardize a domestic and semi-industrial process. Chemical (protein, lactose. lactic acid, ethanol, and acetic acid) as well as microbial properties (total plate count and total yeast count) were monitored during the experiment. Results show a statistical difference between the kefir grains in terms of acetic acid and ethanol percentages, which leads to the conclusion that there is a difference in the microbial populations that produce these products. Lactic acid, protein, and lactose parameters are statistically the same as well as the growth in biomass and the total population of yeast. Our results suggest that both types of kefir grains maintain a similar performance and that their metabolic capabilities are stable throughout time (taking into account that the household grains have been productive for years), meaning that domestic or semi-industrial processes could be easily standardized.

Microbiome and Metabolome Analyses of Milk From Dairy Cows With Subclinical Streptococcus agalactiae Mastitis-Potential Biomarkers

The microbial ecosystem in the udders of dairy cows directly influences the flavor and quality of milk. However, to our knowledge, no published research has analyzed the complex relationship between the udder microbiome and its associated metabolism in animals with subclinical mastitis. We identified the bacterial species and measured relative population numbers in the milk of cows with subclinical Streptococcus agalactiae mastitis (GBS) and compared this information to that from the milk of healthy cows. Metabolite profiles were determined to investigate correlations between the milk microbiota and metabolic factors in healthy vs. GBS dairy cows. Six milk samples from GBS cows and six from healthy cows were subjected to 16S rRNA gene sequencing to identify the microbial species using a MiSeq high-throughput sequencing apparatus. The metabolites present in the milk were identified by gas chromatography time-of-flight mass spectrometry. Both principal component analysis and orthogonal partial least squares discriminant analysis indicated that the metabolites were well-separated from each other in the milk samples from the two groups. GBS dramatically altered microbial diversity, and the GBS group had significantly fewer Proteobacteria, Actinobacteria, and Acidobacteria than the CON group, with greater relative abundance of Firmicutes (p < 0.01). Several bacterial genera, such as Streptococcus, were significantly more abundant in milk from the GBS group than in milk from the CON group, and there was a tendency for greater abundance of Turicibacter (p = 0.07) and Enterococcus spp. (p = 0.07) in the GBS group. The levels of five milk metabolites were significantly higher in the GBS group than in the CON group: phenylpyruvic acid, the homogentisic acid: 4-hydroxyphenylpyruvic acid ratio, the xanthine: guanine ratio, uridine and glycerol. Metabolic pathway analysis of the different metabolites revealed that the following were enriched in both groups: galactose metabolism; pentose and glucuronate interconversion; starch and sucrose metabolism; alanine, aspartate and glutamate metabolism; arginine biosynthesis; citrate cycle (TCA cycle); D-glutamine and D-glutamate metabolism; and the neomycin, kanamycin, and gentamicin biosynthesis pathways. Several typical metabolites were highly correlated with specific ruminal bacteria, such as Streptococcaceae, Lachnospiraceae, Lactobacillaceae and Corynebacteriaceae, demonstrating the functional correlations between the milk microbiome and associated metabolites. These findings revealed that the milk microbiota and metabolite profiles were significantly different between the two groups of cows, raising the question of whether the microbiota associated with the bovine mammary gland could be related to mammary gland health. There was also a relationship between milk quality and the presence of spoilage bacteria. Other bacterial taxa should be investigated, as related information may provide insights into how perturbations in milk metabolomics profiles relate to differences in milk synthesis between healthy cows and those with subclinical mastitis.

Metabolomic profiles in yak mammary gland tissue during the lactation cycle

The yak is one of the most important domestic animals in Tibetan life for providing basic resources such as milk, meat and transportation. Although yak milk production is not elevated, yak milk is superior to dairy cow milk in nutrient composition (protein and fat). However, the understanding of the metabolic mechanisms of yak mammary gland tissue during the lactation cycle remains elusive. In this study, GC-MS-based metabolomics was employed to study the metabolic variations in the yak mammary gland during the lactation cycle (pregnancy, lactation and dry period). Twenty-nine metabolites were up or downregulated during the lactation period. Compared to the dry period, during the lactation period the levels of oxalic acid were upregulated, while glycine and uridine were downregulated. Thirty-seven pathways were obtained when the 29 differential metabolites were imported into the KEGG pathway analysis. The most impacted pathways during the lactation cycle were glycine, serine and threonine metabolism; alanine, aspartate and glutamate metabolism; TCA cycle; glyoxylate and dicarboxylate metabolism; and pyrimidine metabolism. Our results provide important insights into the metabolic events involved in yak mammary gland development, lactogenesis and lactation, which can guide further research to improve milk yield and enhance the constituents of yak milk.

Evaluation of sample preparation methods for NMR-based metabolomics of cow milk

The quality of milk metabolome analyzed by nuclear magnetic resonance (NMR) is greatly influenced by the way samples are prepared. Although this analytical method is increasingly used to study milk metabolites, a thorough examination of available sample preparation protocols for milk has not been reported yet. We evaluated the performance of eight milk preparation methods namely (1) raw milk without any processing; (2) skimmed milk; (3) ultrafiltered milk; (4) skimming followed by ultrafiltration; (5) ultracentrifuged milk; (6) methanol; (7) dichloromethane; and (8) methanol/dichloromethane, in terms of spectra quality, repeatability, signal-to-noise ratio, extraction efficiency and yield criteria. A pooled sample of milk was used for all protocols. Skimming, ultracentrifugation and unprocessed milk protocols showed poor NMR spectra quality. Protocols involving multiple steps, namely methanol/dichloromethane extraction, and skimming followed by ultrafiltration produced inadequate results for signal-to-noise ratio parameter. Methanol and skimming associated to ultrafiltration provided good repeatability results compared to the other protocols. Chemical-based sample preparation protocols, particularly methanol, showed more efficient metabolite extraction compared to physical preparation methods. When considering all evaluation parameters, the methanol extraction protocol proved to be the best method. As a proof of utility, methanol protocol was then applied to milk samples from dairy cows fed a diet with or without a feed additive, showing a clear separation between the two groups of cows.

The relationship between milk metabolome and methane emission of Holstein Friesian dairy cows: Metabolic interpretation and prediction potential

This study aimed to quantify the relationship between CH₄ emission and fatty acids, volatile metabolites, and nonvolatile metabolites in milk of dairy cows fed forage-based diets. Data from 6 studies were used, including 27 dietary treatments and 123 individual observations from lactating Holstein-Friesian cows. These dietary treatments covered a large range of forage-based diets, with different qualities and proportions of grass silage and corn silage. Methane emission was measured in climate respiration chambers and expressed as production (g per day), yield (g per kg of dry matter intake; DMI), and intensity (g per kg of fat- and protein-corrected milk; FPCM). Milk samples were analyzed for fatty acids by gas chromatography, for volatile metabolites by gas chromatography-mass spectrometry, and for nonvolatile metabolites by nuclear magnetic resonance. Dry matter intake was 15.9 ± 1.90 kg/d (mean ± SD), FPCM yield was 25.2 ± 4.57 kg/d, CH₄ production was 359 ± 51.1 g/d, CH₄ yield was 22.6 ± 2.31 g/kg of DMI, and CH₄ intensity was 14.5 ± 2.59 g/kg of FPCM. The results show that changes in individual milk metabolite concentrations can be related to the ruminal CH₄ production pathways. Several of these relationships were diet driven, whereas some were partly dependent on FPCM yield. Next, prediction models were developed and subsequently evaluated based on root mean square error of prediction (RMSEP), concordance correlation coefficient (CCC) analysis, and random 10-fold cross-validation. The best models with milk fatty acids (in g/100 g of fatty acids; MFA) alone predicted CH₄ production, yield, and intensity with a RMSEP of 34 g/d, 2.0 g/kg of DMI, and 1.7 g/kg of FPCM, and with a CCC of 0.67, 0.44, and 0.75, respectively. The CH₄ prediction potential of both volatile metabolites alone and nonvolatile metabolites alone was low, regardless of the unit of CH₄ emission, as evidenced by the low CCC values (<0.35). The best models combining the 3 types of metabolites as selection variables resulted in the inclusion of only MFA for CH₄ production and CH₄ yield. For CH₄ intensity, MFA, volatile metabolites, and nonvolatile metabolites were included in the prediction model. This resulted in a small improvement in prediction potential (CCC of 0.80; RMSEP of 1.5 g/kg of FPCM) relative to MFA alone. These results indicate that volatile and nonvolatile metabolites in milk contain some information to increase our understanding of enteric CH₄ production of dairy cows, but that it is not worthwhile to determine the volatile and nonvolatile metabolites in milk to estimate CH₄ emission of dairy cows. We conclude that MFA have moderate potential to predict CH₄ emission of dairy cattle fed forage-based diets, and that the models can aid in the effort to understand and mitigate CH₄ emissions of 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.