Study of the Stability of Wine Samples for 1H-NMR Metabolomic Profile Analysis through Chemometrics Methods.

Wine is a temperature, light, and oxygen-sensitive product, so its physicochemical characteristics can be modified by variations in temperature and time when samples are either sampled, transported, and/or analyzed. These changes can alter its metabolomic fingerprinting, impacting further classification tasks and quality/quantitative analyses. For these reasons, the aim of this work is to compare and analyze the information obtained by different chemometric methods used in a complementary form (PCA, ASCA, and PARAFAC) to study 1H-NMR spectra variations of four red wine samples kept at different temperatures and time lapses. In conjunction, distinctive changes in the spectra are satisfactorily tracked with each chemometric method. The chemometric analyses reveal variations related to the wine sample, temperature, and time, as well as the interactions among these factors. Moreover, the magnitude and statistical significance of the effects are satisfactorily accounted for by ASCA, while the time-related effects variations are encountered by PARAFAC modeling. Acetaldehyde, formic acid, polyphenols, carbohydrates, lactic acid, ethyl lactate, methanol, choline, succinic acid, proline, acetoin, acetic acid, 1,3-propanediol, isopentanol, and some amino acids are identified as some of the metabolites which present the most important variations.

NMR-based metabolomics of human cerebrospinal fluid identifies signature of brain death.

INTRODUCTION: Brain death (BD) is the irreversible cessation of all functions of the entire brain, including the brainstem. Cerebrospinal fluid (CSF) is a biological liquid that circulates in brain and spine. Metabolomics is able to reveal the response of biological systems to diverse factors in a specific moment or condition. Therefore, the study of this neurological condition through metabolic profiling using high resolution Nuclear Magnetic Resonance (NMR) spectroscopy is important for understanding biochemical events. OBJECTIVES: The aim of the current study is to identify the metabolomics signature of BD using 1H-NMR spectroscopy in human CSF. METHODS: 1H-NMR spectroscopy has been employed for metabolomic untargeted analysis in 46 CSF samples: 22 control and 24 with BD. Spectral data were further subjected to multivariate analysis. RESULTS: Statistically significant multivariate models separated subject's samples with BD from controls and revealed twenty one discriminatory metabolites. The statistical analysis of control and BD subjects using Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) model resulted in R2X of 0.733 and Q2 of 0.635. An elevation in the concentration of statistically discriminant metabolites in BD was observed. CONCLUSION: This study identifies a metabolic signature associated with BD and the most relevant enriched selected metabolic pathways.

A Longitudinal 1H NMR-Based Metabolic Profile Analysis of Urine from Hospitalized Premature Newborns Receiving Enteral and Parenteral Nutrition.

Preterm newborns are extremely vulnerable to morbidities, complications, and death. Preterm birth is a global public health problem due to its socioeconomic burden. Nurturing preterm newborns is a critical medical issue because they have limited nutrient stores and it is difficult to establish enteral feeding, which leads to inadequate growth frequently associated with poor neurodevelopmental outcomes. Parenteral nutrition (PN) provides nutrients to preterm newborns, but its biochemical effects are not completely known. To study the effect of PN treatment on preterm newborns, an untargeted metabolomic 1H nuclear magnetic resonance (NMR) assay was performed on 107 urine samples from 34 hospitalized patients. Multivariate data (Principal Component Analysis, PCA, Orthogonal partial least squares discriminant analysis OPLS-DA, parallel factor analysis PARAFAC-2) and univariate analyses were used to identify the association of specific spectral data with different nutritional types (NTs) and gestational ages. Our results revealed changes in the metabolic profile related to the NT, with the tricarboxylic acid cycle and galactose metabolic pathways being the most impacted pathways. Low citrate and succinate levels, despite higher glucose relative urinary concentrations, seem to constitute the metabolic profile found in the studied critically ill preterm newborns who received PN, indicating an energetic dysfunction that must be taken into account for better nutritional management.

1H -NMR Metabolomics Study of the Effect of Cisplatin and Casiopeina IIgly on MDA-MB-231 Breast Tumor Cells.

The knowledge of the metabolic processes of designed metallodrugs for cancer treatment is an area that has been not profoundly studied. Casiopeina IIgly (CasIIgly), which belongs to the Casiopeínas® family, is a copper (II) coordination compound that has shown good biological activity against several cancer cells, low toxicity in normal cells, and antineoplastic activity in in vivo murine and xenografted models. In this work we employed a triple-negative highly metastatic breast carcinoma line (MDA-MB-231), which is one of the cancer types with a great mortality index, for 1H-NMR metabolomic analysis using cisplatin and CasIIgly, in order to quantify the effect of metallodrugs in the metabolic profile of this cell tumor line as a consequence of treatment at different times. Our findings indicate that cisplatin mainly contributes to phospholipid biosynthesis while CasIIgly affects processes such as carbohydrates and nucleotides metabolism. Also, we observed that CasIIgly treatment has an important and fast effect over MDA-MB-231 cell metabolism, which makes it a good alternative for treatment in this type of cancer.

1H NMR profiling and chemometric analysis as an approach to predict the leishmanicidal activity of dichloromethane extracts from Lantana camara (L.).

The application of 1H NMR spectroscopy and chemometrics for the analysis of extracts of Lantana camara is described. This approach allowed to predict the leishmanicidal activity of samples obtained at different harvest times from their 1H NMR spectra. The anti-leishmanial activity of dichloromethane extracts obtained from the aerial parts of L. camara was measured using an in vitro assay. As the extracts displayed differences in their activity according to a one-way ANOVA analysis, their 1H NMR spectra were subjected to multivariate analysis using exploratory (Principal Component Analysis (PCA) and Anova Simultaneous Component Analysis (ASCA)) and regression, (Partial Least Squares Regression to Latent Structures (PLS)) chemometrics methods. These analyses allowed to establish and characterize a predictive model capable of determining the anti-leishmanial activity of Lantana camara dichloromethane extracts from their 1H NMR spectra. Figures of merit of the developed method are given as well. The identified chemical signals responsible for the iPLS calibration model corresponded to the presence of eicosane, caryophyllene oxide, ß-ionone, tiglic acid, lantanilic acid, camaric acid, and lantadene B; the chemical markers. This study proposed a fast and simple method that avoids the need of using complex biological assays to predict the leishmanicidal activity of L. camara dichloromethane extracts.