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Filangi, O.

Publications and source records attributed to Filangi, O..

2 recordsLinked to original sources

Validation of carbon isotopologue distribution measurements by GC-MS and application to 13C-metabolic flux analysis of plant tricarboxylic acid cycle

The estimation of metabolic fluxes in photosynthetic organisms represents an important challenge that has gained interest over the last decade with the development of 13C-Metabolic Flux Analysis at isotopically non-stationary steady-state. This approach requires a high level of accuracy for the measurement of Carbon Isotopologue Distribution in plant metabolites. But this accuracy has still not been evaluated at the isotopologue level for GC-MS, leading to uncertainties for the metabolic fluxes calculated based on these fragments. Here, we developed a workflow to validate the measurements of CIDs from plant metabolites with GC-MS by producing tailor-made E. coli standard extracts harboring a predictable binomial CID for some organic and amino acids. Overall, most of our TMS-derivatives mass fragments were validated with these standards and at natural isotope abundance in plant matrices. Then, we applied this validated MS method to investigate the light/dark regulation of plant TCA cycle by incorporating U-13C-pyruvate to Brassica napus leaf discs. We took advantage of pathway-specific isotopologues/isotopomers observed between two and six hours of labeling to show that the TCA cycle can operate in a cyclic manner under both light and dark conditions. Interestingly, this forward cyclic flux mode has a nearly four-fold higher contribution for pyruvate-to-citrate and pyruvate-to-malate fluxes than the phosphoenolpyruvate carboxylase (PEPc) flux reassimilating carbon derived from some mitochondrial enzymes. The contribution of stored citrate to the mitochondrial TCA cycle activity was also questioned based on dynamics of 13C-enrichment in citrate, glutamate and succinate and variations of citrate total amounts under light and dark conditions. Interestingly, there was a light-dependent 13C-incorporation into glycine and serine showing that decarboxylations from pyruvate dehydrogenase complex and TCA cycle enzymes were actively reassimilated and could represent up to 5% to net photosynthesis.

plant biology↗

FORUM: Building a Knowledge Graph from public databases and scientific literature to extract associations between chemicals and diseases

Metabolomics studies aim at reporting a metabolic signature (list of metabolites) related to a particular experimental condition. These signatures are instrumental in the identification of biomarkers or classification of individuals, however their biological and physiological interpretation remains a challenge. Overcoming this challenge is critical when aiming to associate metabolic signatures with potential pathological outcomes. To support this task, we introduce FORUM: a Knowledge Graph (KG) providing a semantic representation of relations between chemicals and biomedical concepts, built from a federation of life science databases and scientific literature repositories. An important number of scientific articles discuss relations between chemical compounds and biomedical concepts in various contexts, from biomarkers to therapeutic uses. The extraction of these statements and their interconnection in a graph structure can thus allow us to identify and explore relations strongly supported in the scientific literature. The use of a Semantic Web framework on biological data allows us to apply ontological based reasoning to infer new relations between entities. We show that these new relations provide different levels of abstraction and could open the path to new hypotheses. We estimate the statistical relevance of each extracted relation, explicit or inferred, using an enrichment analysis, and instantiate them as new knowledge in the KG to support results interpretation/further inquiries. Beyond this result, FORUM can also provide insights into complex biological questions and the extracted information could then be used for further developments. Containing more than 8 billion triples and providing more than 8 million relations, FORUM leverages the increasing availability of linked datasets in life science and is built in agreement with FAIR principles. A web interface to browse and download the extracted relations, as well as a SPARQL endpoint to directly probe the whole FORUM knowledge graph, are available at https://forum-webapp.semantic-metabolomics.fr. The code needed to reproduce the triplestore is available at https://github.com/eMetaboHUB/Forum-DiseasesChem.

bioinformatics↗