Metabolic Clustering Analysis as a Strategy for Compound Selection in the Drug Discovery Pipeline for Leishmaniasis.

A lack of viable hits, increasing resistance, and limited knowledge on mode of action is hindering drug discovery for many diseases. To optimize prioritization and accelerate the discovery process, a strategy to cluster compounds based on more than chemical structure is required. We show the power of metabolomics in comparing effects on metabolism of 28 different candidate treatments for Leishmaniasis (25 from the GSK Leishmania box, two analogues of Leishmania box series, and amphotericin B as a gold standard treatment), tested in the axenic amastigote form of Leishmania donovani. Capillary electrophoresis-mass spectrometry was applied to identify the metabolic profile of Leishmania donovani, and principal components analysis was used to cluster compounds on potential mode of action, offering a medium throughput screening approach in drug selection/prioritization. The comprehensive and sensitive nature of the data has also made detailed effects of each compound obtainable, providing a resource to assist in further mechanistic studies and prioritization of these compounds for the development of new antileishmanial drugs.

Metabolomic approach with LC-QTOF to study the effect of a nutraceutical treatment on urine of diabetic rats.

The rat treated with streptozotocin has been proposed as the most appropriate model of systemic oxidative stress for studying antioxidant therapies. In that sense, rosemary extracts have long been recognized as having antioxidant properties, and folic acid may be able to improve endothelial progenitor cell function. A mixture containing both has been tested as a possible nutraceutical to improve health complications in diabetes. We have developed the methodology to evaluate metabolic changes in the urine of streptozotocin-induced diabetic rats after supplementing their diet with rosemary extract obtained with supercritical fluids (SFE) containing 10% folic acid in an acute but short-term study. It has been done with a metabolomics approach using LC-QTOF as an analytical tool. About 20 endogenous metabolites have been identified by databases and MS/MS showing statistically significant changes. Among them, several amino acids and their metabolites point to changes due to the effect of the gut microbiota. In addition, the comparison between control and streptozotocin-diabetic rats has permitted the showing of some metabolic coincidences between type 1 diabetes and other (possible) autoimmune diseases such as autism and/or Crohn's disease, and the nutraceutical intervention has succeeded in inducing changes in such biomarkers.

Dunaliella salina extract effect on diabetic rats: metabolic fingerprinting and target metabolite analysis.

Antioxidant therapy has been proposed to improve the oxidative stress status of diabetic patients. Natural products are a source of substances such as carotenoids, with known antioxidant properties with possible benefits on diabetes. Among them, Dunaliella salina is a microalga with high content in carotenoids that can be extracted via an environmentally clean process such as supercritical fluid extraction with CO2. Five doses of D. salina extract with in vitro antioxidant properties were intragastrically administrated to adult male streptozotocin (STZ) diabetic rats. Urine fingerprints of control and diabetic rats, both with and without treatment, were obtained by capillary electrophoresis with two different modes (normal polarity and MEKC and reverse polarity and CZE). When the profiles were submitted together to pattern recognition techniques they showed the effects of D. salina extract on this acute and short-term treatment animal model in a rapid, simple and cost-effective way without identifying a single marker. In order to have a further biochemical knowledge of the effect, after treatment, rats were sacrificed and blood and liver glutathione, as well as plasma glucose, triglycerides, cholesterol, total protein, urea, acetoacetate, 3-hydroxybutyrate, lactate, pyruvate and urate, TBARS and urine 8-isoprostane were analysed. Vitamin E in plasma and liver was also measured. Twenty-seven parameters were individually assessed, and both univariate statistics (mean comparison after 1W-ANOVA) and multivariate data analysis were performed. D. salina extract induced changes showed up by the multivariate analysis. Results of the treatment from most of the parameters can be considered beneficial for diabetic animals; although an increase in hyperglycemia and 8-isoprostane excretion when STZ treated animals received the extract was observed.

Fingerprinting of human bile during liver transplantation by capillary electrophoresis.

Increasing rates of success in liver transplantation have increased the number of cases considered. However, liver post-transplant graft dysfunction of liver transplants (TXs) is not fully understood and by applying holistic approaches we can investigate metabolic change deriving from confounding factors such as liver fat content, ischaemia time, donor age, recipient's health, etc. Twenty-six hepatic bile samples taken from liver donors and recipients were retrieved from a total of six TXs, from these one recipient underwent post-graft dysfunction. CE was employed to fingerprint bile collected at 10 min increments in the donors and in the recipients. The electropherograms of these samples were aligned and normalised using correlation optimised warping algorithms and modelled with multivariate techniques. The resulting metabolic signatures were compared; in general donors and recipients showed distinct fingerprints and clustered separately. When a partial least square discriminant analysis (PLS-DA) model was constructed between donor and recipient's samples, a recipient of a 32 year old liver with normal steatosis, and shortest cold ischaemia time showed as the observation nearest to its donor observation, denoting minimal metabolic change. This study proposes CE fingerprinting of human bile as a promising technique to help unravel the complex metabolic pathways involved during transplantation.