Mots-Clés

bioinformatics, integrative systems biology, metabolomics, network science

Description

Metabolomics analysis of pollutant mixture released from grafted adipose tissue

Project Summary :

The proposed project will aim at analysing new data generated by untargeted metabolomics, and to generated a biological network in the context of mixture of chemicals and their potential effects on metabolic disorders such as obesity and diabetes. The results will be discussed with experimentalists in

the laboratory for validation.

Description :

Exposure to endocrine disrupting chemicals including persistent organic pollutants (POPs) represents one of the most critical public health threats nowadays. In addition to the human health hazard, the associated ecosystem toxicity and significant economic burden relied to disorders such as metabolic diseases constitute additional incentives for the development of innovative approaches (including computational models) to decipher putative linkages between health outcomes and environmental chemicals.

The project will take place in the SysTox group under the MetaTox team (Inserm Unit 1124), that is located on the Campus Saint Germain at Paris Descartes University. The group works in bioinformatics, and its specialized in the development of innovative and new methods and models with the aim to have a better understanding of the effect from the chemical exposure on human health.

The project is part of an ANR project (French National Agency for Research), named CREATIvE. The aim of CREATIvE is to develop a multi-disciplinary approach to understand the complex modes of action (MoA) of a chemical mixture when the exposure source is internal, i.e. from the adipose tissue itself.

The untargeted metabolomics data to be analyzed will be provided from news samples generated using a novel experimental approach developed recently in the laboratory. The candidate will identify metabolomics profiling in various organs (liver, AT) with bioinformatics technics (advanced statistical & bioinformatics tools via dedicated software e.g. Bioconductor in R), to identify novel biomarkers, which will be discussed with the experts in the MetaTox team and external collaborators. The candidate will use a technical pipeline already established in the group. As a next step, biological network representation and analysis (for ex. clustering) of the results will be done using the Cytoscape tool, and other data type will be integrated (disease annotations) in order to fully interpret the results.

The relevant findings will be experimentally validated in the laboratory (not by the candidate), before to be integrated into a cross-omics model (to be done by a postdoc in the lab).

A close collaboration with the other members of the SysTox group (engineer, PhD, postdoc) and the experimentalists is expected.

A documentation of the bioinformatics analysis (scripts and results) will be provided by the end of internship Project Summary : The proposed project will aim at analysing new data generated by untargeted metabolomics, and to generated a biological network in the context of mixture of chemicals and their potential effects on metabolic disorders such as obesity and diabetes. The results will be discussed with experimentalists in the laboratory for validation. Description : Exposure to endocrine disrupting chemicals including persistent organic pollutants (POPs) represents one of the most critical public health threats nowadays. In addition to the human health hazard, the associated ecosystem toxicity and significant economic burden relied to disorders such as metabolic diseases constitute additional incentives for the development of innovative approaches (including computational models) to decipher putative linkages between health outcomes and environmental chemicals. The project will take place in the SysTox group under the MetaTox team (Inserm Unit 1124), that is located on the Campus Saint Germain at Paris Descartes University. The group works in bioinformatics, and its specialized in the development of innovative and new methods and models with the aim to have a better understanding of the effect from the chemical exposure on human health. The project is part of an ANR project (French National Agency for Research), named CREATIvE. The aim of CREATIvE is to develop a multi-disciplinary approach to understand the complex modes of action (MoA) of a chemical mixture when the exposure source is internal, i.e. from the adipose tissue itself. The untargeted metabolomics data to be analyzed will be provided from news samples generated using a novel experimental approach developed recently in the laboratory. The candidate will identify metabolomics profiling in various organs (liver, AT) with bioinformatics technics (advanced statistical & bioinformatics tools via dedicated software e.g. Bioconductor in R), to identify novel biomarkers, which will be discussed with the experts in the MetaTox team and external collaborators. The candidate will use a technical pipeline already established in the group. As a next step, biological network representation and analysis (for ex. clustering) of the results will be done using the Cytoscape tool, and other data type will be integrated (disease annotations) in order to fully interpret the results. The relevant findings will be experimentally validated in the laboratory (not by the candidate), before to be integrated into a cross-omics model (to be done by a postdoc in the lab). A close collaboration with the other members of the SysTox group (engineer, PhD, postdoc) and the experimentalists is expected. A documentation of the bioinformatics analysis (scripts and results) will be provided by the end of internship.