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.

Mass spectrometry-based techniques for identification of compounds in milk and meat matrix

Food including milk and meat is often viewed as the mixture of different components such as fat, protein, carbohydrates, moisture and ash, which are estimated using well-established protocols and techniques. However, with the advent of metabolomics, low-molecular weight substances, also known as metabolites, have been recognized as one of the major factors influencing the production, quality and processing. Therefore, different separation and detection techniques have been developed for the rapid, robust and reproducible separation and identification of compounds for efficient control in milk and meat production and supply chain. Mass-spectrometry based techniques such as GC-MS and LC-MS and nuclear magnetic resonance spectroscopy techniques have been proven successful in the detailed food component analysis owing to their associated benefits. Different metabolites extraction protocols, derivatization, spectra generated, data processing followed by data interpretation are the major sequential steps for these analytical techniques. This chapter deals with not only the detailed discussion of these analytical techniques but also sheds light on various applications of these analytical techniques in milk and meat products.

Phenotypic and genetic characterization of the occurrence of noncoagulating milk in dairy sheep

Milk coagulation ability is of central importance for the sheep dairy industry because almost all sheep milk is destined for cheese processing. The occurrence of milk with impaired coagulation properties is an obstacle to cheese processing and, in turn, to the profitability of the dairy companies. In this work, we investigated the causes of noncoagulation of sheep milk; specifically, we studied the effect of milk physicochemical properties on milk coagulation status [coagulating and noncoagulating (NC) milk samples, which do or do not coagulate within 30 min, respectively], and whether mid-infrared spectroscopy (MIR) could be used to assess variability in coagulation status. We also investigated the genetic background of milk coagulation ability. Individual milk samples were collected from 996 Sarda ewes farmed in 47 flocks located in Sardinia (Italy). Considered traits were daily milk yield, milk composition traits, and milk coagulation properties (rennet coagulation time, curd firming time, and curd firmness), and MIR spectra were acquired. About 9% of samples did not coagulate within 30 min. A logistic regression approach was used to test the effect of milk-related traits on milk coagulation status. A principal component (PC) analysis was carried out on the milk MIR spectra, and PC scores were then used as covariates in a logistic regression model to assess their relationship with milk coagulation status. Results of the present work demonstrated that the probability of having NC samples increases as milk contents of proteins and chlorides and somatic cell score increase. The analysis of PC extracted from milk spectra that influenced coagulation status highlighted key regions associated with lactose and protein concentrations, and others not associated with routinely collected milk composition traits. These results suggest that the occurrence of NC is mostly related to damage of the epithelium secretory mammary cells, which occurs with the advancement of a lactation or due to unhealthy mammary gland status. Genetic analysis of milk coagulation status and of the extracted PC confirmed the genetic background of the milk coagulability of sheep milk.

Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed

Milk coagulation ability is crucial for the dairy sheep industry since the whole amount of milk is processed into cheese. Non-coagulating milk (NCM) is defined as milk not forming a curd within the testing time. In sheep milk, it has been reported in literature that up to 20% of milk is NCM. Although the clotting properties of individual milk have been widely studied, little attention has been given to NCM and genomic dissection of this trait. Mid-infrared (MIR) spectra can be exploited both to predict cheese-making aptitude and to discriminate between coagulating milk and NCM. The main goals of this work were (i) to assess the predictivity of MIR spectra for NCM classification and (ii) to conduct a genome-wide association study on coagulation ability. Milk samples from 949 Sarda ewes genotyped and phenotyped for milk coagulation properties (MCPs) served as the training dataset. The validation dataset included 662 ewes. Three classical MCPs were measured: rennet coagulation time (RCT), curd firmness (a30), and curd firming time (k20). Moreover, MIR spectra were acquired and stored in the region between 925.92 and 5,011.54 cm−1. The probability of a sample to be NCM was modeled by step-wise logistic regression on milk spectral information (LR-W), logistic regression on principal component (LR-PC), and canonical discriminant analysis of spectral wave number (DA-W). About 9% of the samples did not coagulate at 30 min. The use of LR-W gave a poorer classification of NCM. The use of LR-PC improved the percentage of correct assignment (45 ± 9%). The DA-W method allows us to reach 75.1 ± 10.3 and 76.5 ± 18.4% of correct assignments of the inner and external validation datasets, respectively. As far as GWA of NCM, 458 SNP associations and 45 candidate genes were detected. The genes retrieved from public databases were mostly linked to mammary gland metabolism, udder health status, and a milk compound also known to affect the ability of milk to coagulate. In particular, the potential involvement of CAPNs deserves further investigation.

The Impact of Seasonality in Pasture-Based Production Systems on Milk Composition and Functionality

Seasonal calving, pasture-based dairy systems are widely practiced in countries with a temperate climate and plentiful rainfall such as Ireland and New Zealand. This approach maximizes milk production from pasture and, consequently, is a low-cost, low-input dairy production system. On the other hand, the majority of global milk supply is derived from high input indoor total mixed ration systems where seasonal calving is not practiced due to the dependence on ensiled silages, grains and concentrated feeds, which are available year-round. Synchronous changes in the macro and micronutrients in milk are much more noticeable as lactation progresses through early, mid and late stages in seasonal systems compared to non-seasonal systems-which can have implications on the processability and functionality of milk.

NMR-based metabolomics to evaluate the milk composition from Friesian and autochthonous cows of Northern Italy at different lactation times

It is well established that different factors affect milk composition in cows and that milk composition, in turn, affect both technological and nutritional qualities. In this respect the comprehension of the metabolic variability of milk composition in relation to the lactation time as well as to the genetic background may be of paramount importance for the agri-food industries. In the present study we investigated the variations of the metabolic profiles during lactation in milks obtained from Friesian and autochthonous races from Northern Italy by ¹H NMR metabolomics. Furthermore, the external factors influencing the milk composition were minimized: the cows were breeded in the same farm, were fed with the same diet and were paired for the lactation interval and lactation stage. Our results showed a difference in milk composition between races and in relation to late lactation. The PLS-DA analysis permitted to distinguish the Friesian and autochthonous cow milks at the investigated different lactation times. Interestingly, the metabolites significantly involved into the discrimination between races appeared to be also technological property parameters, highlighting the importance of maintaining the biodiversity of cow breeds. Therefore, NMR-based metabolomics of milk could represent an informative tool to identify metabolites involved in milk quality both from a nutritional and industrial perspective.

Comparison of commercially-available preservatives for maintaining the integrity of bacterial DNA in human milk

BACKGROUND

Inhibiting changes to bacteria in human milk between sample collection and analysis is necessary for unbiased characterization of the milk microbiome. Although cold storage is considered optimal, alternative preservation is sometimes necessary.

RESEARCH AIM/QUESTION

The objective of this study was to compare the effectiveness of several commercially-available preservatives with regard to maintaining bacterial DNA in human milk for delayed microbiome analysis. Specifically, we compared Life Technologies' RNAlater® stabilization solution, Biomatrica's DNAgard® Saliva, Advanced Instruments' Broad Spectrum Microtabs II™, and Norgen Biotek Corporation's Milk DNA Preservation and Isolation Kit.

METHODS

Aliquots of 8 pools of human milk were treated with each preservative. DNA was extracted immediately and at 1, 2, 4, and 6wk, during which time milk was held at 37°C. The V1-V3 region of the bacterial 16S rRNA gene was amplified and sequenced. Changes in bacterial community structure and diversity over time were evaluated.

RESULTS

Comparable to other studies, the most abundant genera were Streptococcus (33.3%), Staphylococcus (14.0%), Dyella (6.3%), Pseudomonas (3.0%), Veillonella (2.5%), Hafnia (2.0%), Prevotella (1.7%), Rhodococcus (1.6%), and Granulicatella (1.4%). Overall, use of Norgen's Milk DNA Preservation and Isolation Kit best maintained the consistency of the bacterial community structure. Total DNA, diversity, and evenness metrics were also highest in samples preserved with this method.

CONCLUSIONS

When collecting human milk for bacterial community analysis in field conditions where cold storage is not available, our results suggest that Norgen's Milk DNA Preservation and Isolation Kit may be a useful method, at least for a period of 2weeks.

Crude glycerol as glycogenic precursor in feed; effects on milk coagulation properties and metabolic profiles of dairy cows

As grain prices rise, the search for alternative glycogenic precursors in animal feed becomes increasingly important, and this study was conducted to determine if the replacement of starch with glycerol, as an alternative glycogenic precursor, affects the milk metabolic profile and milk coagulation ability, and therefore the quality of the milk. Eight primiparous mid-lactation Holstein cows were fed during a replicated 4 × 4 Latin square trial with four different isoenergetic rations: (1) control (T0) fed a total mixed ration (TMR) with barley meal; (2) group T1, decreased barley content, replaced isoenergetically with 1 kg crude glycerol; (3) group T2, the barley meal was replaced with 2 kg of crude glycerol; and (4) group T3 the barley meal was replaced with 3 kg of crude glycerol. Rumen, blood and milk samples were collected at the end of every 21-d treatment period. Rumen samples were analysed for proportion of total volatile fatty acid (VFA), blood samples for insulin and glucose, and milk for metabolites (e.g. citric-acid cycle compounds). The change in glycogenic precursors had a positive effect on rumen VFA proportions; the proportion of propionic acid increased (P < 0·001). Milk protein (P < 0·001) and curd firmness (P < 0·001) both increased. The increase in milk protein concentration may have been due to an increase in microbial protein. Regarding the milk metabolic profiles, different signals were positively associated with coagulation ability and change in the diet. Based on this study, changing the glycogenic precursor in animal diet in this way is possible, and may have no immediate deleterious consequences on milk quality or cow health. Indeed, there is evidence for benefits from this substitution.

Alterations in milk and blood metabolomes during the first months of lactation in dairy cows

The molecular composition of milk is influenced by various genetic and environmental factors. Time is one important factor, and the fact that certain milk components change over the course of lactation is widely accepted. Untargeted global metabolomics is an approach to study hundreds of low molecular weight compounds simultaneously. In this study, mass spectrometry-based global metabolomics was used to follow the course of changes in milk (n=133) and blood plasma (n=133) during the early stage of lactation. Little correlation was found between the molecular composition of blood plasma and milk. Blood showed a higher dependence on animal individuality than did milk, in which common evolutions in time resolved. Citrate and lactose had the greatest effect on these changes; however, the most significant changes in milk during the first months of lactation were associated with phosphorylated saccharide levels, whereas the most significant changes in blood plasma were associated with levels of polyunsaturated fatty acids containing phosphatidylcholine. In conclusion, a new systemic approach was used to search for minor metabolites whose concentrations were significantly altered in milk and blood during the first months of lactation.

Metabolomics in food science

Metabolomics, the newest member of the omics techniques, has become an important tool in agriculture, pharmacy, and environmental sciences. Advances in compound extraction, separation, detection, identification, and data analysis have allowed metabolomics applications in food sciences including food processing, quality, and safety. This chapter discusses recent advances and applications of metabolomics in food science.