Page 27 - CIBERDEM2016-ENG

Metabolomics Platform
Director: Xavier Correig · Coordinator: Òscar Yanes http://www.metabolomicsplatform.com/
The Metabolomics Platform is a mixed CIBERDEM - Universitat Rovira i Virgili (URV) platform for giving technology services in the field of omic sciences. The main aim of the Metabolomics Platform is to work as an integrated laboratory for CIBERDEM groups, defining objectives, dimensions and characteristics of both the set of samples and of experimental designs. The equipment currently available in the NMR and LC/gC-MS field allows large-scale analyses of body fluids (for example, serum or urine) as well as tissues or biopsies of patients and/or animal models. The use of advanced statistics, chemometrics and multivariate algorithms enables a large set of data to be turned into metabolic profiles and ultimately into clinical information. The experimental data is processed by the platform team, facilitating the interpretation of results and providing sound and relevant clinical conclusions of use for different research groups.
The Metabolomics Platform particularly addresses to the needs of research groups from the CIBERDEM and the URV; however its services as well as potential scientific cooperation are available for other CIBER groups. In 2016 seven colaborations were carried out with CIBERDEM groups and four collaborations with groups from other thematic areas of the CIBER.
The platform’s scientific activity in 2016 can be summed up as follows:
• Publications in indexed journals: 16
• Average impact factor: 8.27
• Participation in international conferences: 7
• Projects active in 2016: 3 national projects (BFU2014-57466-P, EUIN2015-62503 AND TEC2015- 69076-P) and 3 European projects (EU660034-MSCA-IF-ES-FT, 645758-TROPSENSE AND H2020-MSCA- ITN-2015).
Research lines active in 2016:
• Characterisation of lipoproteins by NMR for studying dyslipidaemias.
• Procedure for profiling serum for studying resistance to insulin and diabetes in population studies.
• Development and study of statistic algorithms, statistics, chemometrics, multivariates and artificial intelligence to enable the analysis of large sets of data.
• Non-radioactive isotopomers for studying metabolic profiles and their flow in cell cultures and animal models.
• Study of diabetic retinopathy.
• Study of molecular images of tissues and profiling of body fluid by means of nanostructured surfaces.
• Metabolomics study on the exposure to third-hand smoke (THS).
Relevant results in 2016:
• Development of a method for profiling glycoproteins in the blood by means of 1HRMn.
• Identification of metabolic markers in the vitreous humour of patients with diabetic retinopathy.
• Programming algorithms for flowomic experiments with mass spectrometry (LC-MS) and NMR.
• Creation and validation of a new algorithm for identifying unknown metabolites by means of mass spectrometry (gC-MS).
• Development of a methodology for obtaining and analysing metabolic images of mass spectrometry by cathodic spraying of metal nanoparticles (nP-LDI-MSI) on tissues of animal models.
platforms 27
• Development of a new computational approach based on the metabolic network of human metabolism to predict alterations in the abundance of metabolites based on quantitative proteomic data.
DEM