Milk Metabolome Research Articles

Coordinated response of milk bacterial and metabolic profiles to subacute ruminal acidosis in lactating dairy cows

BackgroundBovine milk is an important source of nutrition for human consumption, and its quality is closely associated with the microbiota and metabolites in it. But there is limited knowledge about the milk microbiome and metabolome in cows with subacute ruminal acidosis.MethodsEight ruminally cannulated Holstein cows in mid lactation were selected for a 3-week experiment. The cows were randomly allocated into 2 groups, fed either a conventional diet (CON; 40% concentrate; dry matter basis) or a high-concentrate diet (HC; 60% concentrate; dry matter basis).ResultsThe results showed that there was a decreased milk fat percentage in the HC group compared to the CON group. The amplicon sequencing results indicated that the alpha diversity indices were not affected by the HC feeding. At the phylum level, the milk bacteria were dominated by Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes both in the CON and HC groups. At the genus level, the HC cows displayed an improved proportion of Labrys (P = 0.015) compared with the CON cows. Results of both the principal components analysis and partial least squares of discriminant analysis of milk metabolome revealed that samples of the CON and HC groups clustered separately. A total of 31 differential metabolites were identified between the two groups. Of these, the levels of 11 metabolites decreased (α-linolenic acid, prostaglandin E2, L-lactic acid, L-malic acid, 3-hydroxysebacic acid, succinyladenosine, guanosine, pyridoxal, L-glutamic acid, hippuric acid, and trigonelline), whereas the levels of the other 20 metabolites increased in the HC group with respect to the CON group (P < 0.05).ConclusionThese results suggested that subacute ruminal acidosis less impacted the diversity and composition of milk microbiota, but altered the milk metabolic profiles, which led to the decline of the milk quality.

Donkey Colostrum and Milk: How Dietary Probiotics Can Affect Metabolomic Profile, Alkaline Sphingomyelinase and Alkaline Phosphatase Activity

Positive results on animal health, feed efficiency, and milk’s nutritional content have been obtained after oral administration of probiotics. The aim of the present study was therefore to evaluate the effect of dietary supplementation with high numbers of multispecies probiotic formulations on the milk metabolomic profiles of alkaline sphingomyelinase (alk-SMase) and alkaline phosphatase (ALP) in donkeys. Twenty animals were randomly allocated to receive either a normal diet (group B) or a supplemented diet (group A). Colostrum and milk samples were obtained within 48 h, at 15 days (supplementation start), and at 45 days after parturition. Different metabolomic profiles were observed between colostrum and milk, as were the concentrations of 12 metabolites that changed following 30 days of probiotic supplementation. Alk-SMase activity was found to be higher in donkey colostrum (vs. milk at 15 days); this enzyme, together with ALP, increased in milk after 30 days of probiotic supplementation. The results of the present study provide new insight into the complex changes in donkey colostrum and milk composition in the first 45 days of lactation and how the milk metabolome can be modulated by probiotic supplementation.

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.

Milk metabolomics analyses of lactating dairy cows with divergent residual feed intake reveals physiological underpinnings and novel biomarkers.

The opportunity to select for feed efficient cows has been limited by inability to cost-effectively record individual feed efficiency on an appropriate scale. This study investigated the differences in milk metabolite profiles between high- and low residual feed intake (RFI) categories and identified biomarkers of residual feed intake and models that can be used to predict residual feed intake in lactating Holsteins. Milk metabolomics analyses were undertaken at early, mid and late lactation stages and residual feed intake was calculated in 72 lactating dairy cows. Cows were ranked and grouped into high residual feed intake (RFI >0.5 SD above the mean, n = 20) and low residual feed intake (RFI <0.5 SD below the mean, n = 20). Milk metabolite profiles were compared between high residual feed intake (least efficient) and low residual feed intake (most efficient) groups. Results indicated that early lactation was predominantly characterized by significantly elevated levels of medium chain acyl carnitines and glycerophospholipids in high residual feed intake cows. Citrate cycle and glycerophospholipid metabolism were the associated pathways enriched with the significantly different metabolites in early lactation. At mid lactation short and medium chain acyl carnitines, glycerophospholipids and amino acids were the main metabolite groups differing according to residual feed intake category. Late lactation was mainly characterized by increased levels of amino acids in high residual feed intake cows. Amino acid metabolism and biosynthesis pathways were enriched for metabolites that differed between residual feed intake groups at the mid and late lactation stages. Receiver operating characteristic curve analysis identified candidate biomarkers: decanoylcarnitine (area under the curve: AUC = 0.81), dodecenoylcarnitine (AUC = 0.81) and phenylalanine (AUC = 0.85) at early, mid and late stages of lactation, respectively. Furthermore, panels of metabolites predicted residual feed intake with validation coefficient of determination (R 2) of 0.65, 0.37 and 0.60 at early, mid and late lactation stages, respectively. The study sheds light on lactation stage specific metabolic differences between high-residual feed intake and low-residual feed intake lactating dairy cows. Candidate biomarkers that distinguished divergent residual feed intake groups and panels of metabolites that predict individual residual feed intake phenotypes were identified. This result supports the potential of milk metabolites to select for more efficient cows given that traditional residual feed intake phenotyping is costly and difficult to conduct in commercial farms.

The Human Milk Metabolome: A Scoping Literature Review.

Human milk is a complex source of nutrition and other bioactives that protects infants from disease, holding a lifetime of beneficial effects. The field of metabolomics provides a robust platform through which we can better understand human milk at a level rarely examined. To Identify, describe, synthesize, and critically analyze the literature within the past 5 years related to the human milk metabolome. We conducted a scoping literature review and quality analysis of the recent science reflecting untargeted metabolomic approaches to examining human milk. We searched six databases using the terms "breast milk," "metabolome," "metabolite," and "human milk," Out of more than 1,069 abstracts, we screened and identified 22 articles that met our inclusion criteria. We extracted data related to the study author, geographic location, research design, analyses, platform used, and results. We also extracted data related to human milk research activities, including collection protocol, infant/maternal considerations, and time. Selected studies focused on a variety of phenotypes, including maternal and infant disease. Investigators used varying approaches to evaluate the metabolome, and differing milk collection protocols were observed. The human milk metabolome is informed by many factors-which may contribute to infant health outcomes-that have resulted in disparate milk metabolomic profiles. Standardized milk collection and storage procedures should be implemented to minimize degradation. Investigators may use our findings to develop research questions that test a targeted metabolomic approach.

The metabolome of human milk is altered differentially by Holder pasteurization and high hydrostatic pressure processing.

The milk metabolome is composed of hundreds of molecules that can impact infant development. In preterm infants, sterilized donor milk (DM) is frequently used for their feeding. We aimed to identify differences in the metabolome of DM after two types of milk sterilization: the Holder pasteurization (HoP) and a high hydrostatic pressure (HP) processing. DM samples were sterilized by HoP (62.5°C for 30 min) or processed by HP (350 MPa at 38°C). 595 milk metabolites were analyzed using an untargeted metabolomic analysis. Both treatments differentially altered several classes of compounds. The major changes noted included decreased levels of free fatty acids, phospholipid metabolites, and sphingomyelins. Decreases were more strongly noted in HP samples rather than in HoP ones. Both HoP and HP treatments increased the levels of ceramides and nucleotide compounds. The sterilization of human milk altered its metabolome especially for lipids.

Milk metabolome reveals pyrimidine and its degradation products as the discriminant markers of different corn silage-based nutritional strategies.

The purpose of this study was to evaluate the effect of 6 different feeding systems (based on corn silage as the main ingredient) on the chemical composition of milk and to highlight the potential of untargeted metabolomics to find discriminant marker compounds of different nutritional strategies. Interestingly, the multivariate statistical analysis discriminated milk samples mainly according to the high-moisture ear corn (HMC) included in the diet formulation. Overall, the most discriminant compounds, identified as a function of the HMC, belonged to AA (10 compounds), peptides (71 compounds), pyrimidines (38 compounds), purines (15 compounds), and pyridines (14 compounds). The discriminant milk metabolites were found to significantly explain the metabolic pathways of pyrimidines and vitamin B6. Interestingly, pathway analyses revealed that the inclusion of HMC in the diet formulation strongly affected the pyrimidine metabolism in milk, determining a significant up-accumulation of pyrimidine degradation products, such as 3-ureidopropionic acid, 3-ureidoisobutyric acid, and 3-aminoisobutyric acid. Also, some pyrimidine intermediates (such as l-aspartic acid, N-carbamoyl-l-aspartic acid, and orotic acid) were found to possess a high discrimination degree. Additionally, our findings suggested that the inclusion of alfalfa silage in the diet formulation was potentially correlated with the vitamin B6 metabolism in milk, being 4-pyridoxic acid (a pyridoxal phosphate degradation product) the most significant and up-accumulated compound. Taken together, the accumulation trends of different marker compounds revealed that both pyrimidine intermediates and degradation products are potential marker compounds of HMC-based diets, likely involving a complex metabolism of microbial nitrogen based on total splanchnic fluxes from the rumen to mammary gland in dairy cows. Also, our findings highlight the potential of untargeted metabolomics in both foodomics and foodomics-based studies involving dairy products.

Effects of dietary branched-chain amino acid supplementation on serum and milk metabolome profiles in dairy cows during early lactation.

The 3 branched-chain AA (BCAA), Val, Leu, and Ile, are essential AA used by tissues as substrates for protein synthesis and energy generation. In addition, BCAA are also involved in modulating cell signaling pathways, such as nutrient sensing and insulin signaling. In our previous study, dietary BCAA supplementation was shown to improve protein synthesis and glucose homeostasis in transition cows. However, a more detailed understanding of the changes in metabolic pathways associated with an increased BCAA availability is desired to fine-tune nutritional supplementation strategies. Multiparous Holstein cows (n = 20) were enrolled 28 d before expected calving and assigned to either the BCAA treatment (n = 10) or the control group (n = 10). Cows assigned to BCAA were fed 550 g/d of rumen-protected BCAA mixed with 200 g/d of dry molasses from calving until 35 DIM, whereas the cows assigned to the control were fed only 200 g/d of dry molasses. Serum samples were collected on d 10 before expected calving, as well as on d 4 and d 21 postpartum. Milk samples were collected on d 14 postpartum. From a larger cohort, we selected 20 BCAA-supplemented cows with the greatest plasma urea nitrogen concentration, as an indicator for greater BCAA availability, for the metabolomics analysis herein. Serum and milk samples were subjected to a liquid chromatography-mass spectrometry-based assay, detecting and measuring the abundance of 241 serum and 211 milk metabolic features, respectively. Multivariable statistical analyses revealed that BCAA supplementation altered the metabolome profiles of both serum and milk samples. Increased abundance of serum phosphocholine and glutathione and of milk Val, Ile, and Leu, and decreased abundance of milk acyl-carnitines were associated with BCAA supplementation. Altered phosphocholine and glutathione abundances point to altered hepatic choline metabolism and antioxidant balance, respectively. Altered milk acyl-carnitine abundances suggest changes in mammary fatty acid metabolism. Dietary BCAA supplementation was associated with a range of alterations in serum and milk metabolome profiles, adding to our understanding of the role of BCAA availability in modulating dairy cow protein, lipid, and energy metabolism on a whole-body level and how it affects milk composition.

Metabolomic and exposomic biomarkers of risk of future neurodevelopmental delay in human milk

BackgroundThe chemical composition of human milk has long-lasting effects on brain development. We examined the prognostic value of the human milk metabolome and exposome in children with the risk of neurodevelopmental delay (NDD).MethodsThis retrospective cohort study included 82 mother–infant pairs (40 male and 42 female infants). A total of 59 milk samples were from mothers with typically developing children and 23 samples were from mothers of children at risk. Milk samples were collected before 9 months of age (4.6 ± 2.5 months, mean ± SD). Neurocognitive development was assessed by maternal report at 14.2 ± 3.1 months using the Ages and Stages Questionnaires-2.ResultsMetabolome and exposome profiling identified 453 metabolites and 61 environmental chemicals in milk. Machine learning tools identified changes in deoxysphingolipids, phospholipids, glycosphingolipids, plasmalogens, and acylcarnitines in the milk of mothers with children at risk for future delay. A predictive classifier had a diagnostic accuracy of 0.81 (95% CI: 0.66–0.96) for females and 0.79 (95% CI: 0.62–0.94) for males.ConclusionsOnce validated in larger studies, the chemical analysis of human milk might be added as an option in well-baby checks to help identify children at risk of NDD before the first symptoms appear.ImpactMaternal milk for infants sampled before 9 months of age contained sex-specific differences in deoxysphingolipids, sphingomyelins, plasmalogens, phospholipids, and acylcarnitines that predicted the risk of neurodevelopmental delay at 14.2 months of age.Once validated, this early biosignature in human milk might be incorporated into well-baby checks and help to identify infants at risk so early interventions might be instituted before the first symptoms appear.

Metabolomic changes in lactating multiparous naturally MAP-infected Holstein-Friesian dairy cows suggest changes in mitochondrial energy pathways

Mycobacterium avium subspecies paratuberculosis (MAP) is the causative organism of Johne's Disease, a chronic intestinal infection of ruminants. Infected cows begin shedding MAP within the asymptomatic, subclinical stage of infection before clinical signs, such as weight loss, diarrhoea and reduced milk yields develop within the clinical stages of disease. Herein, we examine the milk metabolomic profiles of naturally MAP-infected Holstein-Friesian cows. The study used biobanked milk samples which were collected 73.4 ± 3.79 (early lactation) and 143 ± 3.79 (mean ± SE) (mid-lactation) days post-calving from 5 MAP-infected and 5 control multiparous cows. The milk metabolome was assessed using flow infusion electrospray high-resolution mass spectrometry (FIE-HRMS) for sensitive, non-targeted metabolite fingerprinting. Metabolite fingerprinting assessments using partial least squares discriminate analyses (PLS-DA) indicated that lactation stage was a larger source of variation than MAP status. Examining each lactation stage separately for changes associated to MAP-infection status identified 45 metabolites, 33 in early lactation and 12 in mid-lactation, but only 6 metabolites were targeted in both stages of lactation. Pathway enrichment analysis suggested that MAP affected the malate-aspartate shuffle during early lactation. Pearson's correlation analysis indicated relationships between milk lactose concentrations in mid-lactation and 6 metabolites that were tentatively linked to MAP-infection status. The targeted metabolites were suggestive of wider changes in the bioenergetic metabolism that appear to be an acceleration of the effects of progressing lactation in healthy cows. Additionally, milk lactose concentrations suggest that MAP reduces the availability of lactose derivatives.

Alterations in the Milk Metabolome of Dairy Cows Supplemented with Different Levels of Calcium Propionate in Early Lactation

This study aimed to investigate the effects of dietary supplementation with different levels of calcium propionate on the lactation performance, blood energy metabolite parameters, and milk metabolites of dairy cows in early lactation. Thirty-two multiparous Holstein cows were randomly divided into 4 groups, which were orally drenched with 0, 200, 350, and 500 g/d calcium propionate per cow supplemented to a basal diet for 5 weeks from calving. The milk and blood of the dairy cows were sampled and measured every week. The milk samples from the last week were used for the metabolomic analysis via liquid chromatography–mass spectrometry (LC-MS). The results showed that the calcium propionate supplementation quadratically increased the dry matter intake, energy-corrected milk yield, and 4% fat-corrected milk yield; linearly reduced the milk protein and milk lactose concentrations; and quadratically decreased the somatic cell count in the milk. With the increase in calcium propionate, the serum glucose content showed a linear increase, while the serum insulin content showed a quadratic increase. The diets supplemented with calcium propionate quadratically decreased the β-hydroxybutyric acid and linearly decreased the non-esterified fatty acid content in the serum. The metabolomic analysis revealed that eighteen different metabolites were identified in the milk samples of the dairy cows supplemented with calcium propionate at 350 g/d, which decreased the abundance of genistein and uridine 5-monophosphate and increased the abundance of adenosine, uracil, protoporphyrin IX, and sphingomyelin (d 18:1/18:0) compared with the control group. The milk metabolic analysis indicated that the calcium propionate effectively improved the milk synthesis and alleviated the mobilization of adipose tissue and bone calcium. In summary, the calcium propionate could improve the lactation performance and energy status and promote the milk metabolic profile of dairy cows in early lactation. Calcium propionate (350 g/d) is a well-recommended supplement for dairy cows for alleviating negative energy balance and hypocalcemia in early lactation.

Dynamic Changes in the Human Milk Metabolome Over 25 Weeks of Lactation.

Human milk (HM) provides essential nutrition for ensuring optimal infant growth and development postpartum. Metabolomics offers insight into the dynamic composition of HM. Studies have reported the impact of lactation stage, maternal genotype, and gestational age on HM metabolome. However, the majority of the studies have considered changes within the first month of lactation or sampled with large intervals. This leaves a gap in the knowledge of progressing variation in HM composition beyond the first month of lactation. The objective of this study was to investigate whether the HM metabolome from mothers with term deliveries varies beyond 1 month of lactation, during the period in which HM is considered fully mature. Human milk samples (n = 101) from 59 mothers were collected at weeks 1–2, 3–5, 7–9, and 20–25 postpartum and analyzed using 1H nuclear magnetic resonance spectroscopy. Several metabolites varied over lactation and exhibited dynamic changes between multiple time points. Higher levels of HM oligosaccharides, cis-aconitate, O-phosphocholine, O-acetylcarnitine, gluconate, and citric acid were observed in early lactation, whereas later in lactation, levels of lactose, 3-fucosyllactose, glutamine, glutamate, and short- and medium-chain fatty acids were increased. Notably, we demonstrate that the HM metabolome is dynamic during the period of maturity.

Human milk metabolome: Impact of gestational age, lactational stage and maternal diet.

Human breast milk due to its unique composition and the ability to adapt to the needs of the infant, is referred to as the "gold standard". Exclusive breastfeeding is recommended for the first 6 months of a inflant's life. The composition of breast milk and its metabolites is not constant and varies depending on the influence of various factors. Its analysis allows for rational management of infant nutrition. Intermediate and final metabolites of human milk are formed as a result of various metabolic processes in the mammary gland, and their role and the influence of various factors on them are not fully determined in the context of the proper development of infants. Metabolomic studies can be used to identify intermediate and terminal metabolites in breast milk. The aim of the study was to review the current literature on the variability of human milk metabolome depending on factors such as gestational age, lactation stage and mother's diet. A review of current research shows that the composition of human milk metabolome varies depending on various factors. Better understanding of metabolome of breast milk could be crucial in the future programming of metabolic processes in infants, which is crucial in preventing many diseases and maintaining health.

Human Milk Metabolomics Are Related to Maternal Adiposity, Infant Growth Rate and Allergies: The Chinese Human Milk Project.

The metabolomic profiles of Chinese human milk have been poorly documented. The objective of the study was to explore associations between human milk metabotypes, maternal adiposity, infant growth patterns, and risk of allergies. Two hundred mother–infant dyads from seven cities were randomly selected from the Chinese Human Milk Project (CHMP). Untargeted human milk metabolomic profiles were determined using HPLC-MS/MS. Two human milk metabotypes were identified using principal component analysis. Principal component (PC) 1 was characterized by high linoleic acid metabolites with low purine nucleosides and metabolites of glutamate and glutathione metabolism. PC 2 was characterized by high glycerophospholipids and sphingomyelins content. Higher PC1 scores were associated with slower infant growth rate and higher ambient temperature (p < 0.05). Higher PC 2 scores were related to higher maternal BMI and increased risk of infant allergies (p < 0.05). Future work is needed to understand the biologic mechanisms of these human milk metabotypes.

Maternal consumption of a fermented diet protects offspring against intestinal inflammation by regulating the gut microbiota

ABSTRACT The neonatal intestinal tract is immature and can be easily infected by pathogens causing inflammation. Maternal diet manipulation is a promising nutritional strategy to enhance the gut health of offspring. A fermented diet is a gut microbiota targeting diet containing live probiotics and their metabolites, which benefit the gut and overall health host. However, it remains unclear how a maternal fermented diet (MFD) affects neonatal intestinal inflammation. Here, in vivo and in vitro models together with multi-omics analysis were applied to investigate the impacts and the underlying mechanism through which an MFD prevents from gut inflammation in neonates. An MFD remarkably improved the performance of both sows and piglets and significantly altered the gut microbiome and milk metabolome of sows. In addition, the MFD significantly accelerated the maturation of the gut microbiota of neonates and increased the abundance of gut Lactobacillus and the microbial functions of amino acid-related enzymes and glucose metabolism on the weaning day. Notably, the MFD reduced susceptibility to colonic inflammation in offspring. The fecal microbiota of sows was then transplanted into mouse dams and it was found that the mouse dams and pups in the MFD group alleviated the LPS-induced decrease in gut Lactobacillus abundance and barrier injury. Milk L-glutamine (GLN) and gut Lactobacillus reuteri (LR) were found as two of the main MFD-induced sow effectors that contributed to the gut health of piglets. The properties of LR and GLN in modulating gut microbiota and alleviating colonic inflammation by inhibiting the phosphorylation of p38 and JNK activation of Caspase 3 were further verified. These findings provide the first data revealing that an MFD drives neonate gut microbiota development and ameliorates the colonic inflammation by regulating the gut microbiota. This fundamental evidence might provide references for modulating maternal nutrition to enhance early-life gut health and prevent gut inflammation.

Nuclear magnetic resonance spectroscopy to investigate the association between milk metabolites and udder quarter health status in dairy cows

Nuclear magnetic resonance spectroscopy was applied to investigate the association between milk metabolome and udder quarter health status in dairy cows. Mammary gland health status was defined by combining information provided by traditional somatic cell count (SCC) and differential SCC (DSCC), which expresses the percentage of neutrophils and lymphocytes over total SCC. Quarter milk samples were collected in triplicate (d 1 to 3) from 10 Simmental cows, 5 defined as cases and 5 defined as controls according to SCC levels at d 0. A total of 120 samples were collected and analyzed for bacteriology, milk composition, SCC, DSCC, and milk metabolome. Bacteriological analysis revealed the presence of mostly coagulase-negative staphylococci in quarter milk samples of cows defined as cases. Nuclear magnetic resonance spectra of all quarter samples were first analyzed using the unsupervised multivariate approach principal component analysis, which revealed a specific metabolomic fingerprint of each cow. Then, the supervised cross-validated orthogonal projections to latent structures discriminant analysis unquestionably showed that each cow could be very well identified according to its milk metabolomic fingerprint (accuracy = 95.8%). The comparison of 12 different models, built on bucketed 1-dimensional NOESY spectra (noesygppr1d, Bruker BioSpin) using different SCC and DSCC thresholds, corroborated the assumption of improved udder health status classification ability by joining information provided by both SCC and DSCC. Univariate analysis performed on the 34 quantitated metabolites revealed lower levels of riboflavin, galactose, galactose-1-phosphate, dimethylsulfone, carnitine, hippurate, orotate, lecithin, succinate, glucose, and lactose, and greater levels of lactate, phenylalanine, choline, acetate, O-acetylcarnitine, 2-oxoglutarate, and valine, in milk samples with high somatic cells. In the 5 cases, results of the udder quarter with the highest SCC compared with its symmetrical relative were in line with quarter-level findings. Our study suggests that increased SCC is associated with changes in milk metabolite fingerprint and highlights the potential use of different metabolites as novel indicators of udder health status and milk quality.

Untargeted Metabolomic Analysis of Human Milk from Mothers of Preterm Infants.

The application of metabolomics in neonatology offers an approach to investigate the complex relationship between nutrition and infant health. Characterization of the metabolome of human milk enables an investigation into nutrients that affect the neonatal metabolism and identification of dietary interventions for infants at risk of diseases such as necrotizing enterocolitis (NEC). In this study, we aimed to identify differences in the metabolome of breast milk of 48 mothers with preterm infants with NEC and non-NEC healthy controls. A minimum significant difference was observed in the human milk metabolome between the mothers of infants with NEC and mothers of healthy control infants. However, significant differences in the metabolome related to fatty acid metabolism, oligosaccharides, amino sugars, amino acids, vitamins and oxidative stress-related metabolites were observed when comparing milk from mothers with control infants of ≤1.0 kg birth weight and >1.5 kg birth weight. Understanding the functional biological features of mothers’ milk that may modulate infant health is important in the future of tailored nutrition and care of the preterm newborn.

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.

Increased plasma and milk short-chain acylcarnitine concentrations reflect systemic LPS response in mid-lactation dairy cows.

Lipopolysaccharides (LPS) challenge the metabolic integrity of high-yielding dairy cows, activating the immune system and altering energy metabolism. Fatty acid oxidation, a major energy-gaining pathway, can be improved by supplementary carnitine, facilitating the transport of fatty acids into mitochondria. The metabolic response to the LPS challenge could alter both the plasma and the milk metabolome. Plasma and milk samples collected from cows treated with (n = 27) or without (n = 27) dietary carnitine, before and after intravenous administration of LPS, were subjected to a targeted metabolomics analysis. Multivariate statistical analyses revealed that both plasma and milk metabolome changed in response to the LPS challenge in both the carnitine-supplemented and the control cows. Short-chain acylcarnitines (carbon chain length C2, C3, C4, and C5) and long-chain acylcarnitines (C14, C16, and C18) had the highest performance to indicate LPS response when testing the predictive power of single metabolites using receiver-operator characteristics (ROC) analysis. The maximum area under a ROC curve (AUC) was 0.93. Biogenic amines, including sarcosine, and amino acids such as glutamine and isoleucine had AUC > 0.80 indicating metabolic changes due to the LPS challenge. In summary, the metabolites involved in the LPS response were acylcarnitines C2 and C5, sarcosine, glutamine, and isoleucine in plasma, and acylcarnitines C4 and C5 in milk. The interrelationship of plasma and milk metabolome included correlation of acylcarnitines C2, C4, and C5 between plasma and milk.

An Untargeted Metabolomics Investigation of Milk from Dairy Cows with Clinical Mastitis by 1H-NMR.

Mastitis is one of the diseases with the highest incidence in dairy cows, causing huge economic losses to the dairy industry all over the world. The aim of the study was to characterize mastitic milk metabolome through untargeted nuclear magnetic resonance spectroscopy (1H-NMR). Taking advantage of the high reproducibility of 1H-NMR, we had the opportunity to provide quantitative information for all the metabolites identified. Fifty-four molecules were characterized, sorted mainly into the chemical groups, namely amino acids, peptides and analogues, carbohydrates and derivates, organic acids and derivates, nucleosides, nucleotides and analogues. Combined with serum metabolomic investigations, several pathways were addressed to explain the mechanisms of milk metabolome variation affected by clinical mastitis, such as tricarboxylic acid cycle (TCA cycle) and phenylalanine, tyrosine and tryptophan biosynthesis. These results provide a further understanding of milk metabolome altered by clinical mastitis, which can be used as a reference for the further milk metabolome investigations.