The production of FAHFA is enhanced when Haematococcus pluvialis is grown in CO2.

Microalgae are considered as a potential source of bioactive compounds to be used in different fields including food and pharmaceutical industry. In this context, fatty acid esters of hydroxy-fatty acids (FAHFA) are emerging as a new class of compounds with anti-inflammatory and anti-diabetic properties. An existing gap in the field of algal research is the limited knowledge regarding the production of these compounds. Our research questions aimed to determine whether the microalga H. pluvialis can synthesize FAHFA and whether the production levels of these compounds are increased when cultivated in a CO2-rich environment. To answer these questions, we used a LC-QTOF/MS method for the characterization of FAHFA produced by H. pluvialis while an LC-MS/MS method was used for their quantitation. The cultivation conditions of H. pluvialis, which include the utilization of CO2, can result in a 10-50-fold increase in FAHFA production.

Untargeted lipidomics of ovine milk to analyse the influence of different diet regimens.

In this work we report a lipidomics approach to study the effects of two diet systems on the composition of ovine milk. Milk from two groups of Sarda sheep grazing on 40% (P40) and 60% (P60) of pasture were analyzed by a UHPLC-QTOF-MS analytical platform and data submitted to multivariate statistical analysis. Pairwise partial least square discriminant analysis of the lipid profile of the data was carried out to classify samples and to find discriminant lipids. The two dietary groups were characterized by differences in triacylglycerols, phosphocholines and phosphatidylethanolamines levels. Discriminants of the P40 group were TG and PC containing in their backbone saturated medium chain FA thus suggesting greater de novo fatty synthesis in the mammary gland. On the other hand, the P60 group was characterized by TG and PC formed by unsaturated long chain FA originating from the diet or from lipid mobilization.

Metabolomics and lipid profile analysis of Coccomyxa melkonianii SCCA 048.

With an unsupervised GC-MS metabolomics approach, polar metabolite changes of the microalgae Coccomyxa melkonianii SCCA 048 grown under standard conditions for seven weeks were studied. C. melkonianii was sampled at the Rio Irvi River, in the mining site of Montevecchio-Ingurtosu (Sardinia, Italy), which is severely contaminated by heavy metals and shows high concentrations of sulfates. The partial-least-square (PLS) analysis of the GC-MS data indicated that growth of C. melkonianii was characterized by an increase of the levels of threonic acid, myo-inositol, malic acid, and fumaric acid. Furthermore, at the sixth week of exponential phase the lipid fingerprint of C. melkonianii was studied by LC-QTOF-MS. C. melkonianii lipid extract characterized through an iterative MS/MS analysis showed the following percent levels: 61.34 ± 0.60% for triacylglycerols (TAG); 11.55 ± 0.09% for diacylglyceryltrimethyl homoserines (DGTS), 11.34 ± 0.10% for sulfoquinovosyldiacylglycerols (SQDG) and, 5.29 ± 0.04% for lysodiacylglyceryltrimethyl homoserines (LDGTS). Noteworthy, we were able to annotate different fatty acid ester of hydroxyl fatty acid, such as FAHFA (18:1_20:3), FAHFA (18:2_20:4), FAHFA (18:0_20:2), and FAHFA (18:1_18:0), with relevant biological activity. These approaches can be useful to study the biochemistry of this extremophile algae in the view of its potential exploitation in the phycoremediation of polluted mining areas.

NMR Lipid Profile of Milk from Alpine Goats with Supplemented Hempseed and Linseed Diets.

The supplementation of goat diets with natural products to obtain milk with nutraceutical components is a common practice. In these last years, the influence of supplementation of specifically designed diets has been studied with different analytical tools in order to explore possible beneficial effects in human consumption of animal milk and milk-derived products. In this study, the lipid fraction of milk from Alpine goats undergoing different dietary regimens was studied by 1H-NMR spectroscopy. Alpine goats were fed with linseed or hempseed supplements, and after 14 weeks of treatment, milk was collected and analyzed. Results showed that feeding diets supplemented with seeds positively affected the fatty acid composition with a pronounced increase in unsaturated fatty acids for both diets compared to a control diet. Specifically, linolenic acid content was more than doubled for linseed diet compared with the hempseed and control groups, while linoleic acid greatly increased only upon hempseed supplementation. However, a number of conjugated linoleic acid (CLA) isomers and higher levels of fatty acids with trans configuration were found in supplemented diets, particularly in the linseed diet.

Multi-platform metabolomic approach to discriminate ripening markers of black truffles (Tuber melanosporum).

Black truffle is characterized by a black ascocarp and white veins. This hypogeous fruit body is known for its aroma. Understanding metabolic variation during ripening can shed light on truffle biology. In this work, the comprehensive polar metabolome and the volatile organic compounds of T. melanosporum were studied at different ripening stages by means of a metabolomic approach using GC-MS. Multivariate statistical data analysis indicated that the metabolic profile changed during ripening and that the metabolites that mostly discriminated truffles in the early ripening stages belonged to the classes of carbohydrates, while free fatty acids and amino acids, among which precursors of VOCs, characterized the late stages of ripening. Principal component analysis of the volatilome indicated that dimethylsulfide and dimethyldisulfide characterized most of the samples collected in December-January, while 1-octen-3-ol samples collected in February-March.

Metabolomics profiling reveals different patterns in an animal model of asphyxial and dysrhythmic cardiac arrest.

Cardiac arrest (CA) is not a uniform condition and its pathophysiology strongly depends on its cause. In this work we have used a metabolomics approach to study the dynamic metabolic changes occurring in the plasma samples of a swine model following two different causes of CA, namely asphyxia (ACA) and ventricular fibrillation (VFCA). Plasma samples were collected at baseline and every minute during the experimental phases. In order to identify the metabolomics profiles characterizing the two pathological entities, all samples were analysed by 1H NMR spectroscopy and LC-MS/MS spectrometry.The metabolomics fingerprints of ACA and VFCA significantly differed during the peri-arrest period and the resuscitation phase. Major alterations were observed in plasma concentrations of metabolites related to tricarboxylic acid (TCA) cycle, urea cycle, and anaplerotic replenishing of TCA. ACA animals showed significant metabolic disturbances during the asphyxial and CA phases, while for VFCA animals this phenomenon resulted shifted at the resuscitation phase. Interestingly, starting from the asphyxial phase, the ACA animals were stratified in two groups based on their metabolomics profiles that resulted to be correlated with the clinical outcome. Succinate overproduction was observed in the animals with the worse outcome, suggesting a potential prognostic role for this metabolite.

Metabolomic patterns associated to QTc interval in shiftworkers: an explorative analysis.

OBJECTIVES: (1)H NMR-metabolomic approach was used to investigate QTc interval correlation with plasma metabolic profiles in shiftworkers. METHODS: Socio-demographic data, electrocardiographic QTc interval and plasma metabolic profiles from 32 male shiftworkers, were correlated by multivariate regression analysis. RESULTS: We found a positive correlation between QTc interval values, body mass index, glycemia and lactate level and a negative correlation between QTc interval and both pyroglutamate and 3-hydroxybutyrate plasma level. CONCLUSIONS: Our analysis provides evidence of the association between clinical, metabolic profiles and QTc interval values. This could be used to identify markers of early effects and/or susceptibility in shiftworkers.

Can Urine Metabolomics Be Helpful in Differentiating Neuropathic and Nociceptive Pain? A Proof-of-Concept Study.

The diagnosis of pain nature is a troublesome task and a wrong attribution often leads to an increase of costs and to avoidable pharmaceutical adverse reactions. An objective and specific approach to achieve this diagnosis is highly desirable. The aim of this work was to investigate urine samples collected from patients suffering from pain of different nature by a metabolomics approach based on (1)H NMR spectroscopy and multivariate statistical analysis. We performed a prospective study on 74 subjects: 37 suffering from pain (12 with nociceptive and 25 with neuropathic pain), and 37 controls not suffering from any kind of chronic pain. The application of discriminant analysis on the urine spectral profiles allowed us to classify these two types of pain with high sensibility and specificity. Although the classification relies on the global urine metabolic profile, the individual contribution in discriminating neuropathic pain patients of metabolites such as choline and phosphocholine, taurine and alanine, suggests potential lesions to the nervous system. To the best of our knowledge, this is the first time that a urine metabolomics profile is used to classify these two kinds of pain. This methodology, although based on a limited sample, may constitute the basis for a new helpful tool in the clinical diagnosis.

Exploring the Role of Different Neonatal Nutrition Regimens during the First Week of Life by Urinary GC-MS Metabolomics.

In this study, a gas-chromatography mass spectrometry (GC-MS) metabolomics study was applied to examine urine metabolite profiles of different classes of neonates under different nutrition regimens. The study population included 35 neonates, exclusively either breastfed or formula milk fed, in a seven-day timeframe. Urine samples were collected from intrauterine growth restriction (IUGR), large for gestational age (LGA), and appropriate gestational age (AGA) neonates. At birth, IUGR and LGA neonates showed similarities in their urine metabolite profiles that differed from AGA. When neonates started milk feeding, their metabolite excretion profile was strongly characterized by the different diet regimens. After three days of formula milk nutrition, urine had higher levels of glucose, galactose, glycine and myo-inositol, while up-regulated aconitic acid, aminomalonic acid and adipic acid were found in breast milk fed neonates. At seven days, neonates fed with formula milk shared higher levels of pseudouridine with IUGR and LGA at birth. Breastfed neonates shared up-regulated pyroglutamic acid, citric acid, and homoserine, with AGA at birth. The role of most important metabolites is herein discussed.

Metabolite profiles of formula milk compared to breast milk.

Breast milk (BM) feeding is the gold standard in neonate nutrition. When BM is not available it can be substituted or integrated with commercial formula milk (FM) usually sold under different brands and formulations. In this work, the low-molecular-weight hydrophilic compounds in milk were studied by gas chromatography electronic impact mass spectrometry (GC-MS), comparing eight different FM brands with BM samples. With the aid of multivariate statistical data analysis, a marked variability among FM brands, especially driven by the presence of prebiotics in their formulation, was highlighted. Quali-quantitative differences were found between FM and BM. Orotic acid and isomaltulose were found exclusively in FM, while phenylalanine and tyrosine levels were high in two FM brands. Moreover, higher levels of malic acid, sugars (glucose, fructose and galactose), and mannitol were detected in FM. On the other hand, BM showed a higher amino acid content. In conclusion, GC-MS proved to be a very sensitive analytical technique for the study of FM, highlighting metabolite differences among FM brands, and between FM and BM, that may have a possible strong impact on neonatal nutrition.

Metabolomics and microbiological profile of Italian mozzarella cheese produced with buffalo and cow milk.

Italian buffalo mozzarella (BM) cheese metabolite profile and microbial communities were characterised and compared to cow mozzarella (CM). Polar metabolite profiles were studied by gas-chromatography mass-spectrometry (GC-MS) and results elaborated by multivariate analysis (MVA). BM produced using natural whey starter cultures (NWS) exhibited a higher microbial diversity with less psychrotrophic bacteria. BM samples were higher in threonine, serine, valine, and lower in orotic acid and urea. CM produced with commercial starters (CMS) had the highest count of Streptococcus thermophilus and higher levels of galactose and phenylalanine. CM obtained by direct acidification (CMA) had lower microbial counts and higher levels of urea and sugars. Orotic acid was the only metabolite linked to milk animal origin. Results indicated that this metabolite pool well reflects the different production protocols and microbial complexity of these dairy products. This approach can help to protect the designation of origin of Italian buffalo mozzarella.

(1)H NMR brain metabonomics of scrapie exposed sheep.

While neurochemical metabolite modifications, determined by different techniques, have been diffusely reported in human and mice brains affected by transmissible spongiform encephalopathies (TSEs), this aspect has been little studied in the natural animal hosts with the same pathological conditions so far. Herein, we investigated, by high resolution (1)H NMR spectroscopy and multivariate statistical data analysis, the brain metabolite profile of sheep exposed to a scrapie agent in a naturally affected flock. On the basis of clinical examinations and western blotting analysis for the pathological prion protein (PrP(Sc)) in brain tissues, sheep were catalogued as not infected (H), infected with clinical signs (S), and infected without clinical signs (A). By discriminant analysis of spectral data, comparing S vs. H, we found a different metabolite distribution, with inosine, cytosine, creatine, and lactate being higher in S than in H brains, while the branched chain amino acids (leucine, isoleucine, and valine), phenylalanine, uracil, tyrosine, gamma-amino butyric acid, total aspartate (aspartate + N-acetyl aspartate) being lower in S. By a soft independent modelling of class analogy approach, 1 out of 3 A samples was assigned to class H. Furthermore, A brains were found to be higher in choline and choline-containing compounds. By means of partial least squares regression, an excellent correlation was found between the PrP(Sc) amount and the (1)H NMR metabolite profile of infected (S and A) sheep, and the metabolite mostly correlated with PrP(Sc) was alanine. The overall results, obtained using different chemometric tools, were able to describe a brain metabolite profile of infected sheep with and without clinical signs, compared to healthy ones, and indicated alanine as a biomarker for PrP(Sc) amounts in scrapie brains.

Monitoring the modifications of the vitreous humor metabolite profile after death: an animal model.

We applied a metabolomic approach to monitor the modifications occurring in goat vitreous humor (VH) metabolite composition at different times (0, 6, 12, 18, and 24 hours) after death. The (1)H-NMR analysis of the VH samples was performed for the simultaneous determination of several metabolites (i.e., the metabolite profile) representative of the VH status at different times. Spectral data were analyzed by Principal Component Analysis (PCA) and by Orthogonal Projection to Latent Structures (OPLS) regression technique. PCA and OPLS suggested that different spectral regions were involved in time-related changes. The major time-related compositional changes, here detected, were the increase of lactate, hypoxanthine, alanine, total glutathione, choline/phosphocholine, creatine, and myo-inositol and the decrease of glucose and 3-hydroxybutyrate. We attempted a speculative interpretation of the biological mechanisms underlying these changes. These results show that multivariate statistical approach, based on (1)H NMR metabolite profiling, is a powerful tool for detecting ongoing differences in VH composition and may be applied to investigate several physiological and pathological conditions.

A gas chromatography-mass spectrometry-based metabolomic approach for the characterization of goat milk compared with cow milk.

In this work, the polar metabolite pool of commercial caprine milk was studied by gas chromatography-mass spectrometry and multivariate statistical data analysis. Experimental data were compared with those of cow milk and the discriminant analysis correctly classified milk. By the same means, differences due to heat treatments (UHT or pasteurization) on milk samples were also investigated. Results of the 2 discriminant analyses were combined, with the aim of finding the discriminant metabolites unique for each class and shared by 2 classes. Valine and glycine were specific to goat milk, talose and malic acid to cow milk, and hydroxyglutaric acid to pasteurized samples. Glucose and fructose were shared by cow milk and UHT-treated samples, whereas ribose was shared by pasteurized and goat milk. Other discriminant variables were not attributed to specific metabolites. Furthermore, with the aim to reduce food fraud, the issue of adulteration of caprine milk by addition of cheaper bovine milk has been also addressed. To this goal, mixtures of goat and cow milk were prepared by adding the latter in a range from 0 to 100% (vol/vol) and studied by multivariate regression analysis. The error in the level of cow milk detectable was approximately 5%. These overall results demonstrated that, through the combined approach of gas chromatography-mass spectrometry and multivariate statistical data analysis, we were able to discriminate between milk typologies on the basis of their polar metabolite profiles and to propose a new analytical method to easily discover food fraud and to protect goat milk uniqueness. The use of appropriate visualization tools improved the interpretation of multivariate model results.

A metabolomic approach to animal vitreous humor topographical composition: a pilot study.

The purpose of this study was to evaluate the feasibility of a (1)H-NMR-based metabolomic approach to explore the metabolomic signature of different topographical areas of vitreous humor (VH) in an animal model. Five ocular globes were enucleated from five goats and immediately frozen at -80 °C. Once frozen, three of them were sectioned, and four samples corresponding to four different VH areas were collected: the cortical, core, and basal, which was further divided into a superior and an inferior fraction. An additional two samples were collected that were representative of the whole vitreous body. (1)H-NMR spectra were acquired for twenty-three goat vitreous samples with the aim of characterizing the metabolomic signature of this biofluid and identifying whether any site-specific patterns were present. Multivariate statistical analysis (MVA) of the spectral data were carried out, including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Partial Least Squares Discriminant Analysis (PLS-DA). A unique metabolomic signature belonging to each area was observed. The cortical area was characterized by lactate, glutamine, choline, and its derivatives, N-acetyl groups, creatine, and glycerol; the core area was characterized by glucose, acetate, and scyllo-inositol; and the basal area was characterized by branched-chain amino acids (BCAA), betaine, alanine, ascorbate, lysine, and myo-inositol. We propose a speculative approach on the topographic role of these molecules that are mainly responsible for metabolic differences among the as-identified areas. (1)H-NMR-based metabolomic analysis has shown to be an important tool for investigating the VH. In particular, this approach was able to assess in the samples here analyzed the presence of different functional areas on the basis of a different metabolite distribution.

Analysing the effects of frozen storage and processing on the metabolite profile of raw mullet roes using ¹H NMR spectroscopy.

(1)H NMR spectroscopy was used to investigate changes in the low molecular weight metabolic profile of raw mullet (Mugil spp.) roes during frozen storage and upon processing. NMR data were analysed by Principal Component Analyses (PCA). In the model constructed using frozen roes, no statistical significant metabolic modifications were observed in the first six months of storage, while choline derivatives, dimethylamine, lactate, and most of the free amino acids were identified as changing with statistical significance (p<0.05) in response to frozen storage time of twelve months. The PCA model comparing the metabolic profiles of roes before and after processing showed that the major modifications occurring upon manufacturing were the increase of the choline derivative compounds, uracil, and free amino acids, and a large decrease of taurine, glucose, lactate, and creatine/phosphocreatine. All of the above mentioned modifications reflect the occurrence of chemical/biochemical reactions arising from degradation processes such as lipolysis and proteolysis.

Lipid profiles in brains from sheep with natural scrapie.

Prion diseases are fatal neurodegenerative disorders affecting many mammals, ovine scrapie being the archetypal prion disease. Several independent studies in murine and cell-based models of scrapie have highlighted the presence of a link between prion generation and lipid alterations; yet, no data on natural disease are available. In this study we investigated levels of total lipids and cholesterol as well as profiles of fatty acids in brain homogenates from symptomatic and asymptomatic scrapie-infected sheep vs. healthy sheep, all belonging to the same flock. Lipid extracts were analyzed by means of gas chromatography and high performance liquid chromatography. Data of fatty acids were submitted to multivariate statistical analysis to give a picture of the brain lipid profiles of sheep. Interestingly, results revealed abnormalities in the brain fatty acid unsaturation of infected/symptomatic animals. Significant reduction of monoene 18:1 n-9 was detected in brain lipids from infected/symptomatic sheep, as compared to healthy and infected/asymptomatic animals, and this alteration occurred in combination with a significant increase in 18:0 level. The unsupervised Principal Component Analysis showed that infected/symptomatic and healthy sheep samples lie in two different regions of the plot, infected/asymptomatic lie mostly next to healthy. The increase of cerebral saturated fatty acids provides a rough indication of presumed alterations in lipid raft domains of nervous cells during scrapie, suggesting that they may exist in a notable viscous liquid-ordered state. Such physicochemical alteration would have a profound impact on the raft thermodynamic properties, its spatial organization, and signal transduction, all potentially relevant for prion generation.

Potential anti-tumor effects of Mugil cephalus processed roe extracts on colon cancer cells.

The salted-semidried mullet ovary product, bottarga, is a Mediterranean food rich in n-3 PUFA EPA and DHA. We studied and compared the effects on cell viability, sensitivity to the anti-tumor drug 5-fluorouracil, and lipid composition, in colon cancer Caco-2 cells after 24 h incubation with oils and hydrophilic extracts obtained from two bottarga samples stored at different conditions. The cellular absorption of bottarga lipids was assessed in cancer cells by the evaluation of lipid accumulation in cytoplasmic lipid droplets by fluorescence microscopy. Bottarga oil showed a significant in vitro inhibitory effect on the growth of cancer Caco-2 cells and the ability to potentiate, at non-toxic concentration, the growth inhibitory effect of 5-fluorouracil. Moreover, bottarga oil induced in cancer Caco-2 cells marked changes in fatty acid composition, with a significant accumulation of the n-3 PUFA EPA and DHA, and cytoplasmic lipid droplet formation. Also bottarga hydrophilic extract, characterized by means of ¹H NMR spectroscopy, exhibited a reduction in cancer cell viability, without affecting cell lipid profile. Cell cholesterol levels were unmodified by all treatments. The results showed interesting anti-tumor properties of bottarga lipids, and qualify this fish product as a food with nutraceutical properties and potential benefits in colon cancer prevention.

1H NMR metabolite fingerprinting as a new tool for body fluid identification in forensic science.

In this feasibility study, we propose, for the first time, (1)H NMR spectroscopy coupled with mathematical strategies as a valid tool for body fluid (BF) trace identification in forensic science. In order to assess the ability of this approach to identify traces composed either by a single or by two different BFs, samples of blood, urine, saliva, and semen were collected from different donors, and binary mixtures were prepared. (1)H NMR analyses were carried out for all samples. Spectral data of the whole set were firstly submitted to unsupervised principal component analysis (PCA); it showed that samples of the same BF cluster well on the basis of their characterizing molecular components and that mixtures exhibit intermediate characteristics among BF typologies. Furthermore, samples were divided into a training set and a test set. An average NMR spectral profile for each typology of BF was obtained from the training set and validated as representative of each BF class. Finally, a fitting procedure, based on a system of linear equations with the four obtained average spectral profiles, was applied to the test set and the mixture samples; it showed that BFs can be unambiguously identified, even as components of a mixture. The successful use of this mathematical procedure has the advantage, in forensics, of overcoming bias due to the analyst's personal judgment. We therefore propose this combined approach as a valid, fast, and non-destructive tool for addressing the challenges in the identification of composite traces in forensics.

Prediction of physical-chemical properties of crude oils by 1H NMR analysis of neat samples and chemometrics.

In this work, we report the feasibility study to predict the properties of neat crude oil samples from 300-MHz NMR spectral data and partial least squares (PLS) regression models. The study was carried out on 64 crude oil samples obtained from 28 different extraction fields and aims at developing a rapid and reliable method for characterizing the crude oil in a fast and cost-effective way. The main properties generally employed for evaluating crudes' quality and behavior during refining were measured and used for calibration and testing of the PLS models. Among these, the UOP characterization factor K (K(UOP)) used to classify crude oils in terms of composition, density (D), total acidity number (TAN), sulfur content (S), and true boiling point (TBP) distillation yields were investigated. Test set validation with an independent set of data was used to evaluate model performance on the basis of standard error of prediction (SEP) statistics. Model performances are particularly good for K(UOP) factor, TAN, and TPB distillation yields, whose standard error of calibration and SEP values match the analytical method precision, while the results obtained for D and S are less accurate but still useful for predictions. Furthermore, a strategy that reduces spectral data preprocessing and sample preparation procedures has been adopted. The models developed with such an ample crude oil set demonstrate that this methodology can be applied with success to modern refining process requirements.