Paola Scano

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 1H-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 1H 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.

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.

Chemical composition and effect on intestinal Caco-2 cell viability and lipid profile of fixed oil from Cynomorium coccineum L.

Cynomorium coccineum L. is a non-photosynthetic plant, spread over Mediterranean countries, amply used in traditional medicine. We investigated the composition and effect on intestinal Caco-2 cell viability and lipid profile of fixed oil obtained from dried stems of the plant. Oil isolation has been performed by supercritical fractioned extraction with CO2. 13C NMR spectroscopy has been used to study the molecular composition of oil lipids; fatty acid composition was identified using GC and HPLC techniques. The fixed oil was composed mainly by triacylglycerols and derivates. The main fatty acids were 18:1 n-9 (38%), 18:2 n-6 (20%), 16:0 (15%), and 18:3 n-3 (10.8%). The oil showed a significant in vitro inhibitory effect on the growth of colon cancer undifferentiated Caco-2 cells. Moreover, cell viability, lipid composition, and lipid peroxidation were measured in intestinal epithelial cells (differentiated Caco-2 cells) after 24 h incubation with fixed oil. The oil did not show a toxic effect on colon epithelial cell viability but induced a significant change in fatty acid composition, with a significant accumulation of the essential fatty acids 18:3 n-3 and 18:2 n-6. The results showed remarkable biological activity of Maltese mushroom oil, and qualify it as a potential resource for food/pharmaceutical applications.

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.

Recognition and quantitation of cis-vaccenic and eicosenoic fatty acids in olive oils by 13C nuclear magnetic resonance spectroscopy.

The presence of 11-cis monoenoic fatty acids was detected in olive oil samples by means of 13C nuclear magnetic resonance spectroscopy, and the positional isomery on the glycerol backbone was derived. The 11-cis vaccenic and eicosenoic fatty acid resonances were recognized and the amounts of the fatty acids quantified. For comparison purposes, a quantitative analysis was also made by gas chromatography.

A Metabolomic Approach to Animal Vitreous Humor Topographical Composition: A Pilot Study

The purpose of this study was to evaluate the feasibility of a 1H-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. 1H-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. 1H-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.

1H NMR metabolite fingerprint and pattern recognition of mullet (Mugil cephalus) bottarga.

Nuclear magnetic resonance (NMR) spectroscopy combined with multivariate data analysis (MVA) was used to investigate the molecular components of the aqueous extract of samples of bottarga, that is, salted and dried mullet (Mugil cephalus) roe, manufactured in Sardinia (Italy) from mullets of known and unknown geographical provenience. Principal component analysis (PCA) applied to the processed (1)H NMR spectra indicated that samples tend to cluster according to their geographical origin and also on the basis of storage and manufacturing procedures. The most important metabolites that characterized grouping of samples are the free amino acids methionine (Met), glutamate (Glu), histidine (His), phenylalanine (Phe), tyrosine (Tyr), and isoleucine (Ile); trimethylamine (TMA) and dimethylamine (DMA), both biomarkers of degradation; nucleotides and derivatives; choline (Cho) and phosphorylcholine (P-cho); and lactate (Lac).

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.

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, 1H 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. 1H 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 analysts 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. Copyright