Nuclear magnetic resonance and mass spectrometry-based milk metabolomics in dairy cows during early and late lactation

From sound check to encore: A journey through high-resolution mass spectrometry-based food analyses and metabolomics

This manuscript presents a comprehensive review of high-resolution mass spectrometry in the field of food analysis and metabolomics. We have followed the historical evolution of metabolomics, its associated techniques and technologies, and its increasing role in food science and research. The review provides a critical comparison and synthesis of tentative identification guidelines proposed for over 15 years, offering a condensed resource for researchers in the field. We have also examined a wide range of recent metabolomics studies, showcasing various methodologies and highlighting key findings as a testimony of the versatility of the field and the possibilities it offers. In doing so, we have also carefully provided a compilation of the software tools that may be employed in this type of studies. The manuscript also explores the prospects of high-resolution mass spectrometry and metabolomics in food science. By covering the history, guidelines, applications, and tools of metabolomics, this review attempts to become a comprehensive guide for researchers in a rapidly evolving field.

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.

Ceramide on the road to insulin resistance and immunometabolic disorders in transition dairy cows: driver or passenger?

Dairy cows must undergo profound metabolic and endocrine adaptations during their transition period to meet the nutrient requirements of the developing fetus, parturition, and the onset of lactation. Insulin resistance in extrahepatic tissues is a critical component of homeorhetic adaptations in periparturient dairy cows. However, due to increased energy demands at calving that are not followed by a concomitant increase in dry matter intake, body stores are mobilized, and the risk of metabolic disorders dramatically increases. Sphingolipid ceramides involved in multiple vital biological processes, such as proliferation, differentiation, apoptosis, and inflammation. Three typical pathways generate ceramide, and many factors contribute to its production as part of the cell's stress response. Based on lipidomic profiling, there has generally been an association between increased ceramide content and various disease outcomes in rodents. Emerging evidence shows that ceramides might play crucial roles in the adaptive metabolic alterations accompanying the initiation of lactation in dairy cows. A series of studies also revealed a negative association between circulating ceramides and systemic insulin sensitivity in dairy cows experiencing severe negative energy balance. Whether ceramide acts as a driver or passenger in the metabolic stress of periparturient dairy cows is an unknown but exciting topic. In the present review, we discuss the potential roles of ceramides in various metabolic dysfunctions and the impacts of their perturbations. We also discuss how this novel class of bioactive sphingolipids has drawn interest in extrahepatic tissue insulin resistance and immunometabolic disorders in transition dairy cows. We also discuss the possible use of ceramide as a new biomarker for predicting metabolic diseases in cows and highlight the remaining problems.

Metabolomics-a powerful tool in livestock research

Advancements in the Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS) along with recent developments in omics sciences have resulted in a better understanding of molecular mechanisms and pathways associated with the physio-pathological state of the animal. Metabolomics is a post-genomics tool that deals with small molecular metabolites in a given set of time which provides clear information about the status of an organism. Recently many researchers mainly focus their research on metabolomics studies due to its valuable information in the various fields of livestock management and precision dairying. The main aim of the present review is to provide an insight into the current research output from different sources and application of metabolomics in various areas of livestock including nutri-metabolomics, disease diagnosis advancements, reproductive disorders, pharmaco-metabolomics, genomics studies, and dairy production studies. The present review would be helpful in understanding the metabolomics methodologies and use of livestock metabolomics in various areas in a brief way.

Tracing the identity of Parmigiano Reggiano "Prodotto di Montagna - Progetto Territorio" cheese using NMR spectroscopy and multivariate data analysis

BACKGROUND

Nuclear magnetic resonance (NMR) spectroscopy is one of the well-established tools for food metabolomic analysis, as it proved to be very effective in authenticity and quality control of dairy products, as well as to follow product evolution during processing and storage. The analytical assessment of the EU mountain denomination label, specifically for Parmigiano Reggiano "Prodotto di Montagna - Progetto Territorio" (Mountain-CQ) cheese, has received limited attention. Although it was established in 2012 the EU mountain denomination label has not been much studied from an analytical point of view. Nonetheless, tracing a specific profile for the mountain products is essential to support the value chain of this specialty.

RESULTS

The aim of the study was to produce an identity profile for Parmigiano Reggiano "Prodotto di Montagna - Progetto Territorio" (Mountain-CQ) cheese, and to differentiate it from Parmigiano Reggiano PDO samples (conventional-PDO) using 1H NMR spectroscopy coupled with multivariate data analysis. Three different approaches were applied and compared. First, the spectra-as-such were analysed after proper preprocessing. For the other two approaches, Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) was used for signals resolution and features extraction, either individually on manually-defined spectral intervals or by reapplying MCR-ALS on the whole spectra with selectivity constraints using the reconstructed "pure profiles" as initial estimates and targets. All approaches provided comparable information regarding the samples' distribution, as in all three cases the separation between the two product categories conventional-PDO and Mountain-CQ could be highlighted. Moreover, a novel MATLAB toolbox for features extraction via MCR-ALS was developed and used in synergy with the Chenomx library, allowing for a putative identification of the selected features.

SIGNIFICANCE

A first identity profile for Parmigiano Reggiano "Prodotto di Montagna - Progetto Territorio" obtained by interpreting the metabolites signals in NMR spectroscopy was obtained. Our workflow and toolbox for generating the features dataset allows a more straightforward interpretation of the results, to overcome the limitations due to dimensionality and to peaks overlapping, but also to include the signals assignment and matching since the early stages of the data processing and analysis.

Impact of Lactation Stage on the Metabolite Composition of Bovine Milk

Bovine milk is a nutrient-dense food and a major component of the human diet. Therefore, understanding the factors that impact its composition is of great importance. Applications of metabolomics provide in-depth analysis of the metabolite composition of milk. The objective of this research was to examine the impact of lactation stage on bovine milk metabolite levels. Metabolomic analysis of bovine milk powder samples across lactation (N = 18) was performed using nuclear magnetic resonance (1H-NMR) spectroscopy and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Forty-one metabolites were identified and quantified in the 1H-NMR spectra. Statistical analysis revealed that 17 metabolites were significantly different across lactation stages (FDR < 0.05), of which the majority had higher levels in early lactation. In total, 491 metabolites were measured using LC-MS/MS, of which 269 had significantly different levels across lactation (FDR < 0.05). Compound classes significantly affected by lactation stage included phosphatidylcholines (59%) and triglycerides (64%), of which 100% of phosphatidylcholines and 61% of triglycerides increased from early lactation onwards. Our study demonstrates significant differences in metabolites across the stages of lactation, with early-lactation milk having a distinct metabolomic profile. More research is warranted to further explore these compositional differences to inform animal feeding practice.

Mastitis: What It Is, Current Diagnostics, and the Potential of Metabolomics to Identify New Predictive Biomarkers

Periparturient diseases continue to be the greatest challenge to both farmers and dairy cows. They are associated with a decrease in productivity, lower profitability, and a negative impact on cows’ health as well as public health. This review article discusses the pathophysiology and diagnostic opportunities of mastitis, the most common disease of dairy cows. To better understand the disease, we dive deep into the causative agents, traditional paradigms, and the use of new technologies for diagnosis, treatment, and prevention of mastitis. This paper takes a systems biology approach by highlighting the relationship of mastitis with other diseases and introduces the use of omics sciences, specifically metabolomics and its analytical techniques. Concluding, this review is backed up by multiple studies that show how earlier identification of mastitis through predictive biomarkers can benefit the dairy industry and improve the overall animal health.

Triacylglycerol fingerprint of sow milks during different lactation stages and from different breeds

Sow milk fats not only provide energy but also essential nutrients for piglets. Thus, feeding strategies must be aligned with fat composition, especially triacylglycerols (TAGs) and their isomers. The triacylglycerol (TAG) profiles of sow milk fats from five typical breeds (Landrace × Large White, Landrace, Large White, Duroc, Pietrain) and two lactation stages (colostrum and milk) were systematically studied. A total of 45 major TAG species were identified using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. The most abundant TAG was oleic acid-palmitic acid-linoleic acid (O-P-L) (13.92% and 12.03% in colostrum and milk, respectively), which was not significantly different in colostrum among all breeds. TAG composition of sow milk was affected mainly by the lactation stage rather than sow breed. Furthermore, TAG compositions of sow milk fats were similar to those of human milk fats, but significant differences were observed between commercial piglet formulas and sow milk. Therefore, the results will contribute to the optimization of piglet formulas to improve the growth and wellness of piglets, as well as potentially providing a basis for food usage as a new source of nutrients for human infants in future.

NADES Compounds Identified in Hypoxis hemerocallidea Corms during Dormancy

Soaking Hypoxis hemerocallidea corms in distilled water improved the propagation and development of cormlets, suggesting the potential leaching-out of inhibitory chemical compounds. To investigate the presence of inhibitory compounds, nuclear magnetic resonance (NMR) spectral data of the leachate from dormant H. hemerocallidea corms were obtained using a 600 MHz ¹H-NMR spectrometer. The ¹H-NMR analysis led to the identification of choline, succinate, propylene glycol, and lactose, as inhibitory compounds. These four chemical compounds are part of the “Natural Deep Eutectic Solvents” (NADES) that protect plant cells during stress periods, each of which has the potential to inhibit bud growth and development. These compounds are supposedly leached out of the corms during the first rain under natural conditions, possibly accompanied by changes in the ratios of dormancy-breaking phytohormones and inhibitory compounds, to release bud dormancy. The identified chemical compounds heralded a novel frontier in the vegetative propagation of H. hemerocallidea as a medicinal plant, and for its enhanced sustainable uses.

Metabolic impact of infant formulas in young infants. An outlook from the urine metabolome

Introduction

Although breast milk is the ideal food source for newborns during the first six months of life, a high percentage of children receive infant formulas. There is evidence that specific diet habits may influence individual metabolic profile. Therefore, in newborns, such profile can be influenced by the use of infantile formulas given the composition differences that display compared to human milk. Up to now, there are no reports in the literature that address this issue.

Objectives

this work aims to compare the metabolic profile of full-term newborns that were feed with either breast milk (n = 32) or infantile formulas (n = 21). Methods: Metabolic profile was established based on urine analysis through gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance (H-NMR).

Results

our results evidenced a more gluconeogenic profile in breast-fed infants characterized by elevation of Kreb's cycle intermediaries like fumaric, succinic and ketoglutaric acids compared to infants receiving infant formula. In addition, infant formula fed infants presented urinary excretion of metabolites derived from specific compounds present in this type of diet that were not observed in breast-fed infants, for instance D-glucitol, and 4-deoxytetronic. Moreover, in infant formula fed infants there was excretion of basal levels of metabolites of clinical relevance like 3-hydroxy-3-methyl-glutaric, 2-methyl-3-keto-valeric and 3,4-dihydroxybutyric.

Conclusion

These results show the importance of understanding the metabolic impact of diet in newborn population in normal and pathological contexts.

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

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

Application of the Metabolomics Approach in Food Authentication

The authentication of food products is essential for food quality and safety. Authenticity assessments are important to ensure that the ingredients or contents of food products are legitimate and safe to consume. The metabolomics approach is an essential technique that can be utilized for authentication purposes. This study aimed to summarize food authentication through the metabolomics approach, to study the existing analytical methods, instruments, and statistical methods applied in food authentication, and to review some selected food commodities authenticated using metabolomics-based methods. Various databases, including Google Scholar, PubMed, Scopus, etc., were used to obtain previous research works relevant to the objectives. The review highlights the role of the metabolomics approach in food authenticity. The approach is technically implemented to ensure consumer protection through the strict inspection and enforcement of food labeling. Studies have shown that the study of metabolomics can ultimately detect adulterant(s) or ingredients that are added deliberately, thus compromising the authenticity or quality of food products. Overall, this review will provide information on the usefulness of metabolomics and the techniques associated with it in successful food authentication processes, which is currently a gap in research that can be further explored and improved.

Oxidative Quality of Dairy Powders: Influencing Factors and Analysis

Lipid oxidation (LO) is a primary cause of quality deterioration in fat-containing dairy powders and is often used as an estimation of a products shelf-life and consumer acceptability. The LO process produces numerous volatile organic compounds (VOC) including aldehydes, ketones and alcohols, which are known to contribute to the development of off-flavours in dairy powders. The main factors influencing the oxidative state of dairy powders and the various analytical techniques used to detect VOC as indicators of LO in dairy powders are outlined. As the ability to identify and quantify specific VOC associated with LO improves this review highlights how these techniques can be used in conjunction with olfactory and sensory analysis to better understand product specific LO processes with the aim of maximizing shelf-life without compromising quality.

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.

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.

Metabolomic Markers of Storage Temperature and Time in Pasteurized Milk

The current date labeling system for pasteurized milk is based on the predicted growth of spoilage microorganisms, but inherent inaccuracies and the inability to account for environmental factors (e.g., temperature fluctuations) contribute to household and retail food waste. Improved shelf-life estimation can be achieved by monitoring milk quality in real-time. In this study, we identify and quantify metabolites changing over storage temperature and time, the main factors affecting milk stability. Pasteurized 2% fat milk was stored at 4, 10, 15, and 20 °C. Metabolite change was analyzed using untargeted and targeted nuclear magnetic resonance (NMR) metabolomics approaches. Several metabolites correlated significantly to storage time and temperature. Citric acid decreased linearly over time at a temperature-dependent rate. Ethanol, formic acid, acetic acid, lactic acid, and succinic acid increased non-linearly after an initial period of minimal increase. Butyric acid exhibited strong inverse temperature dependencies. This study provides the first analysis of the effect of time and temperature on the concentration of key metabolites during milk storage. Candidate molecules for shelf-life monitoring have been identified, and the results improve our understanding of molecular changes during milk storage. These results will inform the development of real-time shelf-life indicators for milk, helping to reduce milk waste.

Detection of bovine milk adulteration in caprine milk with N-acetyl carbohydrate biomarkers by using 1H nuclear magnetic resonance spectroscopy

In a return to tradition, the popularity of caprine milk is on the rise. However, particularly in countries with developed dairy industries based on bovine milk, there is the risk of adulteration with bovine milk, which is a cheaper alternative. Thus, a rapid, robust, and simple method for the detection of bovine milk added to caprine milk is necessary, and ¹H nuclear magnetic resonance spectroscopy appears to provide a solution. A matrix of 115 pure and artificially adulterated pasteurized milk samples was prepared and used to discover biomarkers of bovine milk that are independent of chemical and biological variation caused by factors such as genetics, diet, or seasonality. Principal component analysis and orthogonal projections to latent structures discriminant analysis of pure bovine milk and pure caprine milk revealed spectral features that were assigned to the resonances of 4 molecules. Of these, the peaks corresponding to protons in the N-acetylglucosamine and N-acetylgalactosamine acetyl moieties showed significant applicability for our method. Receiver operating characteristic curve analysis was used to evaluate the performance of the peak integrals as biomarkers of adulteration. This approach was able to distinguish caprine milk adulterated with 5% of bovine milk with 84.78% accuracy and with 10% of bovine milk an excellent 95.65% accuracy. This study demonstrates that N-acetyl carbohydrates could be used as biomarkers for the detection of bovine milk in caprine milk and could help in protecting caprine milk authenticity.

In vitro singlet state and zero-quantum encoded magnetic resonance spectroscopy: Illustration with N-acetyl-aspartate

Magnetic resonance spectroscopy (MRS) allows the analysis of biochemical processes non-invasively and in vivo. Still, its application in clinical diagnostics is rare. Routine MRS is limited to spatial, chemical and temporal resolutions of cubic centimetres, mM and minutes. In fact, the signal of many metabolites is strong enough for detection, but the resonances significantly overlap, exacerbating identification and quantification. Besides, the signals of water and lipids are much stronger and dominate the entire spectrum. To suppress the background and isolate selected signals, usually, relaxation times, J-coupling and chemical shifts are used. Here, we propose methods to isolate the signals of selected molecular groups within endogenous metabolites by using long-lived spin states (LLS). We exemplify the method by preparing the LLSs of coupled protons in the endogenous molecules N-acetyl-L-aspartic acid (NAA). First, we store polarization in long-lived, double spin states, followed by saturation pulses before the spin order is converted back to observable magnetization or double quantum filters to suppress background signals. We show that LLS and zero-quantum coherences can be used to selectively prepare and measure the signals of chosen metabolites or drugs in the presence of water, inhomogeneous field and highly concentrated fatty solutions. The strong suppression of unwanted signals achieved allowed us to measure pH as a function of chemical shift difference.

Use of Integrative Interactomics for Improvement of Farm Animal Health and Welfare: An Example with Fescue Toxicosis

Rapid scientific advances are increasing our understanding of the way complex biological interactions integrate to maintain homeostatic balance and how seemingly small, localized perturbations can lead to systemic effects. The ‘omics movement, alongside increased throughput resulting from statistical and computational advances, has transformed our understanding of disease mechanisms and the multi-dimensional interaction between environmental stressors and host physiology through data integration into multi-dimensional analyses, i.e., integrative interactomics. This review focuses on the use of high-throughput technologies in farm animal research, including health- and toxicology-related papers. Although limited, we highlight recent animal agriculture-centered reports from the integrative multi-‘omics movement. We provide an example with fescue toxicosis, an economically costly disease affecting grazing livestock, and describe how integrative interactomics can be applied to a disease with a complex pathophysiology in the pursuit of novel treatment and management approaches. We outline how ‘omics techniques have been used thus far to understand fescue toxicosis pathophysiology, lay out a framework for the fescue toxicosis integrome, identify some challenges we foresee, and offer possible means for addressing these challenges. Finally, we briefly discuss how the example with fescue toxicosis could be used for other agriculturally important animal health and welfare problems.

A volatolomic approach using cerumen as biofluid to diagnose bovine intoxication by Stryphnodendron rotundifolium

An innovative volatolomic approach employs the detection of biomarkers present in cerumen (earwax) to identify cattle intoxication by Stryphnodendron rotundifolium Mart., Fabaceae (popularly known as barbatimão). S. rotundifolium is a poisonous plant with the toxic compound undefined and widely distributed throughout the Brazilian territory. Cerumen samples from cattle of two local Brazilian breeds ('Curraleiro Pé-Duro' and 'Pantaneiro') were collected during an experimental intoxication protocol and analyzed using headspace (HS)/GC-MS followed by multivariate analysis (genetic algorithm for a partial least squares, cluster analysis, and classification and regression trees). A total of 106 volatile organic metabolites were identified in the cerumen samples of bovines. The intoxication by S. rotundifolium influenced the cerumen volatolomic profile of the bovines throughout the intoxication protocol. In this way, it was possible to detect biomarkers for cattle intoxication. Among the biomarkers, 2-octyldecanol and 9-tetradecen-1-ol were able to discriminate all samples between intoxicated and nonintoxicated bovines. The cattle intoxication diagnosis by S. rotundifolium was accomplished by applying the cerumen analysis using HS/GC-MS, in an easy, accurate, and noninvasive way. Thus, the proposed bioanalytical chromatography protocol is a useful tool in veterinary applications to determine this kind of intoxication.

Metabolomics of Milk Reflects a Negative Energy Balance in Cows

Dairy cows can experience a negative energy balance (NEB) in early lactation when feed intake is too low to meet the energy requirements for body maintenance and milk production. Metabolic changes occur in mammary gland cells of animals experiencing a negative energy balance. We studied these metabolic changes in milk samples from dairy cows in relation to energy balance status using liquid chromatography–mass spectrometry (QQQ-LC–MS) and nuclear magnetic resonance (¹H NMR). NMR and LC–MS techniques are complementary techniques that enabled a comprehensive overview of milk metabolites in our study. Energy balance and milk samples were obtained from 87 dairy cows. A total of 55 milk metabolites were reliably detected, of which 15 metabolites were positively correlated to energy balance and 20 were negatively correlated to energy balance. Cows in NEB produced more milk with increased milk fat yield and higher concentrations of citrate, cis-aconitate, creatinine, glycine, phosphocreatine, galactose-1-phosphate, glucose-1-phosphate, UDP-N-acetyl-galactosamine, UDP-N-acetyl-glucosamine, and phosphocholine but lower concentrations of choline, ethanolamine, fucose, N-acetyl-neuraminic acid, N-acetyl-glucosamine, and N-acetyl-galactosamine. During NEB, we observed an increased leakage of cellular content, increased synthesis of nucleic acids and cell membrane phospholipids, an increase in one-carbon metabolic processes, and an increase in lipid-triglyceride anabolism. Overall, both apoptosis combined with cellular renewal is paramount in the mammary gland in cows in NEB.

Nuclear Magnetic Resonance-Based Metabolomic Comparison of Breast Milk and Organic and Traditional Formula Milk Brands for Infants and Toddlers

In recent years, new formula milk (FM) products based on milk from farms that strictly adhere to the "organic farming" practices became available. However, little is known about the differences in nutritional profile of these organic formulae with respect to traditional ones. We comprehensively evaluated the metabolite profiles of FM with nuclear magnetic resonance (NMR)-based metabolomic analysis. Five commercial brands of organic and nonorganic formula liquid milk for infants (0-12 months) and toddlers (1-3 years) were analyzed, together with human milk (HM) samples. Proton NMR (¹H NMR) spectroscopy mapped molecular characteristics of FM linked to different production techniques, and identified differences between FM and HM samples. We performed a metabolic fingerprint analysis using multivariate and univariate statistical techniques. A clear distinction is found among different commercial brands of the FM samples. In addition, several differences in metabolomic profiles of FM have been found in comparison with HM for the first time. Notably, it was possible to identify, both in the formulations for toddlers and for infants, metabolites that vary in concentration between the formulae produced with milk obtained according to organic farming techniques, and those produced using nonorganic milk. In particular, organic and nonorganic formulations are differentiated by the levels of glucose, methionine, o-phosphocholine, butyrate, hippurate, creatine, and dimethyl sulfone. Importantly, the HM appeared to differ from both organic and nonorganic brands in a context of metabolites. These findings inform efforts to design FM in ways that closely mimic HM, and guide research to differentiate organic and traditional FM.

Ketosis an Old Story Under a New Approach

Ketosis, characterized by high concentrations of ketone bodies in the blood, urine, and milk, affects a considerable number of cows immediately after calving. Although much is known about ketosis, dairy cows continue to be affected in every herd world-wide. Cows affected by ketosis are treated with palliative treatments after the disease is diagnosed. This is a very expensive approach and costs the dairy industry extra expenses, contributing to lower profitability of dairy herds. In this review article, we summarize the mainstream view on ketosis, classification of ketosis into three types, current diagnostic approaches to ketosis, and the economic impact of ketosis on dairy farms. Additionally, we discuss the most recent applications of the new ‘omics’ science of metabolomics in studying the etiopathology of ketosis as well as its contribution in identification of novel screening or diagnostic biomarkers of ketosis.

Use of Large and Diverse Datasets for 1H NMR Serum Metabolic Profiling of Early Lactation Dairy Cows

Most livestock metabolomic studies involve relatively small, homogenous populations of animals. However, livestock farming systems are non-homogenous, and large and more diverse datasets are required to ensure that biomarkers are robust. The aims of this study were therefore to (1) investigate the feasibility of using a large and diverse dataset for untargeted proton nuclear magnetic resonance (¹H NMR) serum metabolomic profiling, and (2) investigate the impact of fixed effects (farm of origin, parity and stage of lactation) on the serum metabolome of early-lactation dairy cows. First, we used multiple linear regression to correct a large spectral dataset (707 cows from 13 farms) for fixed effects prior to multivariate statistical analysis with principal component analysis (PCA). Results showed that farm of origin accounted for up to 57% of overall spectral variation, and nearly 80% of variation for some individual metabolite concentrations. Parity and week of lactation had much smaller effects on both the spectra as a whole and individual metabolites (< 3% and < 20%, respectively). In order to assess the effect of fixed effects on prediction accuracy and biomarker discovery, we used orthogonal partial least squares (OPLS) regression to quantify the relationship between NMR spectra and concentrations of the current gold standard serum biomarker of energy balance, β-hydroxybutyrate (BHBA). Models constructed using data from multiple farms provided reasonably robust predictions of serum BHBA concentration (0.05 ≤ RMSE ≤ 0.18). Fixed effects influenced the results biomarker discovery; however, these impacts could be controlled using the proposed method of linear regression spectral correction.

Sex-dependent changes in the skin mucus metabolome of discus fish (Symphysodon haraldi) during biparental care

Discus fish Symphysodon spp. employs an unusual parental care where fry feed on parental skin mucus after hatching. Here, we investigated the mucus metabolites of parental and non-parental discus by using non-targeted metabolomics. Statistical analysis of the skin mucus metabolome revealed sex-dependent changes of mucus between parental and non-parental discus, as well as sex-specific differences between parental fish. Differential metabolites reflected that mucus of both parents was rich in prostaglandin A1, but only male contained more oligosaccharides (gentiobiose and D-melezitose) and nucleotides (guanine and cytosine), and only female detected more thymine. Moreover, differential metabolites revealed the metabolic status of parental discus, including the inhibition of biosynthesis of amino acids, e.g., L-phenylalanine (parents), L-aspartic acid (female) and taurine (male) and the activation of metabolism of these amino acids; the increase of metabolism of fatty acids such as α-Linolenic acid (female), arachidonic acid (female) and linoleic acid (male); the perturbation of metabolism of carbohydrate and energy including starch and sucrose metabolism (parents), ascorbate and aldarate metabolism (parents), amino sugar and nucleotide sugar metabolism (female), pentose and glucuronate interconversions (male) and glyoxylate and dicarboxylate metabolism (male). These results might suggest sex-specific metabolic changes in the skin mucus of discus fish during parental care. SIGNIFICANCE: We detected the low-molecular-weight compounds present in the parental mucus of discus fish evolving for offspring and revealed the possible metabolic changes associated with parental care. These results are helpful to gain further insights on the functional and regulatory aspects of skin mucus of discus during parental care.

Milk yield, milk composition, and milk metabolomics of dairy goats intramammary-challenged with lipopolysaccharide under heat stress conditions

Heat stress and mastitis are major economic issues in dairy production. The objective was to test whether goat’s mammary gland immune response to E. coli lipopolysaccharide (LPS) could be conditioned by heat stress (HS). Changes in milk composition and milk metabolomics were evaluated after the administration of LPS in mammary glands of dairy goats under thermal-neutral (TN; n = 4; 15 to 20 °C; 40 to 45% humidity) or HS (n = 4; 35 °C day, 28 °C night; 40% humidity) conditions. Milk metabolomics were evaluated using ¹H nuclear magnetic resonance spectroscopy, and multivariate analyses were carried out. Heat stress reduced feed intake and milk yield by 28 and 21%, respectively. Mammary treatment with LPS resulted in febrile response that was detectable in TN goats, but was masked by elevated body temperature due to heat load in HS goats. Additionally, LPS increased milk protein and decreased milk lactose, with more marked changes in HS goats. The recruitment of somatic cells in milk after LPS treatment was delayed by HS. Milk metabolomics revealed that citrate increased by HS, whereas choline, phosphocholine, N-acetylcarbohydrates, lactate, and ß-hydroxybutyrate could be considered as putative markers of inflammation with different pattern according to the ambient temperature (i.e. TN vs. HS). In conclusion, changes in milk somatic cells and milk metabolomics indicated that heat stress affected the mammary immune response to simulated infection, which could make dairy animals more vulnerable to mastitis.

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.

Relationship between energy balance and metabolic profiles in plasma and milk of dairy cows in early lactation

Negative energy balance in dairy cows in early lactation is related to alteration of metabolic status. However, the relationships among energy balance, metabolic profile in plasma, and metabolic profile in milk have not been reported. In this study our aims were: (1) to reveal the metabolic profiles of plasma and milk by integrating results from nuclear magnetic resonance (NMR) with data from liquid chromatography triple quadrupole mass spectrometry (LC-MS); and (2) to investigate the relationship between energy balance and the metabolic profiles of plasma and milk. For this study 24 individual dairy cows (parity 2.5 ± 0.5; mean ± standard deviation) were studied in lactation wk 2. Body weight (mean ± standard deviation; 627.4 ± 56.4 kg) and milk yield (28.1 ± 6.7 kg/d; mean ± standard deviation) were monitored daily. Milk composition (fat, protein, and lactose) and net energy balance were calculated. Plasma and milk samples were collected and analyzed using LC-MS and NMR. From all plasma metabolites measured, 27 were correlated with energy balance. These plasma metabolites were related to body reserve mobilization from body fat, muscle, and bone; increased blood flow; and gluconeogenesis. From all milk metabolites measured, 30 were correlated with energy balance. These milk metabolites were related to cell apoptosis and cell proliferation. Nine metabolites detected in both plasma and milk were correlated with each other and with energy balance. These metabolites were mainly related to hyperketonemia; β-oxidation of fatty acids; and one-carbon metabolism. The metabolic profiles of plasma and milk provide an in-depth insight into the physiological pathways of dairy cows in negative energy balance in early lactation. In addition to the classical indicators for energy balance (e.g., β-hydroxybutyrate, acetone, and glucose), the current study presents some new metabolites (e.g., glycine in plasma and milk; kynurenine, panthothenate, or arginine in plasma) in lactating dairy cows that are related to energy balance and may be of interest as new indicators for energy balance.

Applications of metabolomics in assessing ecological effects of emerging contaminants and pollutants on plants

Metabolomics, the global profiling of metabolite composition, is a powerful technique that can be applied to answer a diverse set of research questions concerning effects of toxicants on organisms. It has recently emerged as a tool to understand complex environmental perturbations in biological systems, especially at sub-lethal concentrations. Organisms can be affected by different stressors such as xenobiotics or increase in concentration of natural compounds such as nitrogen, phosphorous, and sulfur. Metabolomics has facilitated a better understanding of the effects of these perturbations on organisms such as plants, animals, and humans providing phenotypic and biological information in a high throughput manner. In this review, we will discuss recent applications of metabolomics to study the ecological effects of different environmental perturbations, including nanoparticles, pharmaceuticals and personal care products, pesticides, as well as the changes in natural compounds found in the environment with a focus on plant systems.

Chemical Composition of Commercial Cow's Milk

Bovine milk is a nutritionally rich, chemically complex biofluid consisting of hundreds of different components. While the chemical composition of cow's milk has been studied for decades, much of this information is fragmentary and very dated. In an effort to consolidate and update this information, we have applied modern, quantitative metabolomics techniques along with computer-aided literature mining to obtain the most comprehensive and up-to-date characterization of the chemical constituents in commercial cow's milk. Using nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography-mass spectrometry (LC-MS), and inductively coupled plasma-mass spectrometry (ICP-MS), we were able to identify and quantify 296 bovine milk metabolites or metabolite species (corresponding to 1447 unique structures) from a variety of commercial milk samples. Through our literature analysis, we also found another 676 metabolites or metabolite species (corresponding to 908 unique structures). Detailed information regarding all 2355 of the identified chemicals in bovine milk have been made freely available through a Web-accessible database called the Milk Composition Database or MCDB ( http://www.mcdb.ca/ ).

NMR-Based Μetabolomics of the Lipid Fraction of Organic and Conventional Bovine Milk

Origin and quality identification in dairy products is an important issue and also an extremely challenging and complex experimental procedure. The objective of the present work was to compare the metabolite profile of the lipid fraction of organic and conventional bovine milk using NMR metabolomics analysis. ¹H-NMR and 1D TOCSY NMR methods of analysis were performed on extracted lipid fraction of lyophilized milk. For this purpose, 14 organic and 16 conventional retail milk samples were collected monthly, and 64 bulk-tank (58 conventional and 6 organics) milk samples were collected over a 14-month longitudinal study in Cyprus. Data were treated with multivariate methods (PCA, PLS-DA). Minor components were identified and quantified, and modification of the currently used equations is proposed. A significantly increased % content of conjugated (9-cis, 11-trans)18:2 linoleic acid (CLA), α-linolenic acid, linoleic acid, allylic protons and total unsaturated fatty acids (UFA) and decreased % content for caproleic acid were observed in the organic samples compared to the conventional ones. The present work confirms that lipid profile is affected by contrasting management system (organic vs. conventional), and supports the potential of NMR-based metabolomics for the rapid analysis and authentication of the milk from its lipid profile.

Dietary supplementation of Scutellaria baicalensis extract during early lactation decreases milk somatic cells and increases whole lactation milk yield in dairy cattle

Systemic inflammation is common in early lactation dairy cows and is associated with decreased milk production. The Scutellaria baicalensis plant contains flavonoids with anti-inflammatory and anti-oxidative properties, which may counteract the inflammatory state in early lactation dairy cows. The objective of this experiment was to determine whether Scutellaria baicalensis extract (SBE), a source of bioactive flavonoids, would alter the adaptation to lactation. Multiparous Holstein cows (n = 122) were used in a randomized block design to determine the effect of short-term and long-term postpartum administration of SBE on 305-d milk yield, 120-d milk component yield, and early lactation milk markers of inflammation and metabolic function. Treatments were 1) control, 2) short term (5-d) administration of the SBE (SBE5), and 3) long term (60-d) administration of the SBE (SBE60). Treatments were included in a treatment pellet that was identical to a control pellet in ingredient source and composition except for the extract (10 g/d SBE providing 3.3 g/d of the flavonoid baicalin), both provided via an automated milking system beginning on d 1 of lactation. Milk samples were collected on d 1, 3, and once during d 5–12 of lactation, followed by weekly sampling until 120 days in milk (DIM). Milk samples collected in the first 2 wk were used for biomarker analysis (haptoglobin, β-hydroxybutyrate [BHB], and glucose-6-phosphate [G6P]), and all samples were used for composition analysis. Cows were body condition scored every 2 wk prepartum and postpartum. Milk production, programmed pellet allocation, and actual provision of both pelleted feeds were recorded daily. Treatment effects were evaluated by contrasts between control and SBE5 and control and SBE60 for both the treatment (TP; wk 1–9) and carryover periods (CP; wk 10–37). Total pellet offered was greater for SBE60 in both the TP (P < 0.01) and CP (P = 0.02) but was not different for SBE5 during either period (P ≥ 0.13). No treatment effects were observed for body condition score (BCS), milk haptoglobin, BHB, or G6P. SBE5 did not alter milk yield or milk components. SBE60 increased whole-lactation milk yield by 1,419 kg (13%; P = 0.03). SBE60 increased milk lactose and fat yields (P ≤ 0.04) and tended to increase milk protein yield (P = 0.09) during TP, and each increased during CP (P ≤ 0.04). Somatic cell count decreased by 10% in SBE60 during TP (P = 0.02) but not CP (P = 0.13). Mastitis incidence tended to differ by treatment, being lesser for both SBE5 and SBE60 vs. control (14 and 15% vs. 33%). SBE supplementation did not impact time to pregnancy or hazard of leaving the herd. In conclusion, despite no detected treatment effects on BCS or milk biomarkers of inflammation and metabolic status, supplementation of postpartum dairy cows with Scutellaria baicalensis extract for 60 d was effective at increasing whole lactation milk yield.

Mesenchymal Stem Cells Shift Mitochondrial Dynamics and Enhance Oxidative Phosphorylation in Recipient Cells

Mesenchymal stem cells (MSCs) are the most commonly used cells in tissue engineering and regenerative medicine. MSCs can promote host tissue repair through several different mechanisms including donor cell engraftment, release of cell signaling factors, and the transfer of healthy organelles to the host. In the present study, we examine the specific impacts of MSCs on mitochondrial morphology and function in host tissues. Employing in vitro cell culture of inherited mitochondrial disease and an in vivo animal experimental model of low-grade inflammation (high fat feeding), we show human-derived MSCs to alter mitochondrial function. MSC co-culture with skin fibroblasts from mitochondrial disease patients rescued aberrant mitochondrial morphology from a fission state to a more fused appearance indicating an effect of MSC co-culture on host cell mitochondrial network formation. In vivo experiments confirmed mitochondrial abundance and mitochondrial oxygen consumption rates were elevated in host tissues following MSC treatment. Furthermore, microarray profiling identified 226 genes with differential expression in the liver of animals treated with MSC, with cellular signaling, and actin cytoskeleton regulation as key upregulated processes. Collectively, our data indicate that MSC therapy rescues impaired mitochondrial morphology, enhances host metabolic capacity, and induces widespread host gene shifting. These results highlight the potential of MSCs to modulate mitochondria in both inherited and pathological disease states.

A metabolomics comparison between sheep's and goat's milk

Despite the worldwide consumption of bovine milk, dairy products from small ruminants, such as goat's and sheep's milk, are gaining a large interest especially in the Mediterranean area. The aim of this work was to study the metabolite profiles of 30 sheep's and 28 goat's milk using an untargeted metabolomics approach by a gas chromatography coupled with mass spectrometry (GC-MS) analysis. Results showed several differences in the metabolite profiles: arabitol, citric acid, α-ketoglutaric acid, glyceric acid, myo-inositol, and glycine were more abundant in sheep's milk, while goat's milk had higher levels of mannose-6-phosphate, isomaltulose, valine, pyroglutamic acid, leucine, and fucose. Associations between metabolite profile and milk compositional traits were also found. Predictive capabilities of statistical models indicated a good correlation between the metabolite profile and the protein content in sheep's milk, and with the fat content in goat's milk. This work leads to a better understanding of milk metabolites in small ruminants and their role in the evaluation of milk properties.