Mots-Clés

Biologie des systèmes, modélisation métabolique, Constraint-Based Reconstruction and Analysis

Description

Expansion and application of an integrated human model of epigenetic regulation and metabolism

Human metabolic pathways are regulated by the epigenetic machinery through the maintenance of the methylation and acetylation status of downstream targets. The epigenetic machinery includes enzymes such as DNA methylases and demethylases, and histone acetylases and deacetylases. Epigenetic regulation plays an important role for early-life reprogramming of metabolism due to exposures such as diet, chemicals, and the microbiome, so-called fetal programming. This reprogramming of metabolism may predispose children to lifestyle-associated diseases later in life such as obesity and metabolic syndrome.

Our group is interested in modeling the mechanisms behind epigenetic regulation of fetal programming. We use a mechanic systems biology approach, Constraint-Based Reconstruction and Analysis (COBRA). COBRA relies on manually curated genome-scale reconstructions of metabolism that allow the prediction of metabolic fluxes. However, in their basic form, the genome-scale reconstructions do not account for regulatory mechanisms such as epigenetics. We have recently developed an integrated model of the regulatory network of the histone deacetylase SIRT1, and the human genome-scale metabolic reconstruction Recon3D.  The integrated model allows us to predict the effects of SIRT1 activity on downstream metabolic pathways, and to analyze the mechanisms through which SIRT1 is protective against metabolic syndrome.

In this M2 project, the regulatory model will be further expanded with other enzymes in the epigenetic machinery (e.g., SIRT3, SIRT5) and their downstream regulatory targets. This will involve constructing networks from databases and information from literature. The network will be constructed and joint with the human reconstruction using a previously developed Python tool. Afterwards, the impact of regulation on metabolic fluxes under different conditions (e.g., dietary regimes) may be simulated. Finally, tissue-specific models will be constructed from published transcriptomic and methylation data to model tissue-specific regulation of metabolism.

The ideal candidate has good knowledge of Python or other programming languages, and a solid background in biochemistry and metabolism. Good knowledge of omics analyses is also of advantage. The thesis work will take place at Campus Brabois, Nancy from January-June 2025. The workplace is NGERE U1256 NGERE, Université de Lorraine.