Global metabolomic experiments indicate that the number of endogenous metabolites in biological systems is larger than anticipated and cannot be accounted for merely with canonical biochemical pathways. The challenge, though, is that most of these putative unanticipated (and unknown) metabolites are extremely difficult to characterize by the fact that both chemical structures of metabolites and annotated tandem MS spectra are largely unknown or incomplete in databases.
We are developing an integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry (LC/MS) and gas chromatography/mass spectrometry (GC/MS) data sets for global metabolomic experiments. We aim to develop integrating algorithms to extract compound spectra, annotate isotope and adduct peaks, and implement advanced statistical, chemometric, multivariate and artificial intelligence algorithms turning large measurement datasets into useful clinical information.
Identification of metabolic pathways in retinal neurodegeneration induced by hyperglycemia, and ischemia using a metabolomics and proteomics approach
The general aim of this project is to determine the mechanisms leading to neurodegeneration in diabetic retinopathy. To this end, we use a unique approach combining metabolomics and proteomics technologies based on mass spectrometry and nuclear magnetic resonance. The study of metabolic pathways leading to neurodegeneration of the retina is fundamental for the discovery of new biomarkers and therapeutic targets in early stages of diabetic retinopathy. Reference: SAF2011-30578. PI: Oscar Yanes. Funding Agency: Spanish Ministry of Science and Innovation.
Rethinking cellular metabolism through identification of unpredicted metabolites and biochemical transformations using a novel metabolomic approach
Global metabolomic experiments suggest that the number of endogenous metabolites in biological systems is larger than anticipated and cannot be accounted for merely with canonical biochemical pathways. The challenge, though, is that most of these putative unanticipated (and unknown) metabolites are extremely difficult to characterize by the fact that both chemical structures of metabolites and annotated tandem MS spectra are largely unknown or incomplete in databases. Here we want to implement "iMet", a conceptual and computational advance in de novo identification of unknown metabolites, which will experimentally demonstrate that ‘classical’ biochemistry and cellular metabolism (brought together in biochemistry books by Lehninger or Stryer) are far from being complete. Reference: BFU2014-57466. PI: Oscar Yanes. Funding Agency: Spanish Ministry of Economy and Competitiveness.
ChroMe: Chromatin–metabolism interactions as targets for healthy living
ChroMe’s research targets an important nexus between metabolism and chromatin. This holds great promise to develop novel metabolic disease therapeutics, predict disease risk and take new preventive measures that can correct the genetic and epigenetic predisposition to obesity and diabetes. The research goals of ChroMe are to understand how chromatin is steered by metabolism to sustain health or cause disease, and to exploit our new knowledge and expertise to develop new therapies. Reference: 675610. Principal investigator: Andreas Ladurner. Funding Agency: European Comission (H2020-MSCA-ITN-2015).
- Metabolomics (7)
Bioinformatics services offered
Metabolomics data processing
Metabolic network analysis