Metabolomics for Exposure to Chemical or Radiological Risks

- T. Pourcher -
 
Developing new metabolomics methods to detect and measure toxicological contamination in a human population.

Single Photon Emission Computed Tomography (SPECT) imaging of live mouse using Iodide-123 for analysis of thyroid disruptor effects
Single Photon Emission Computed Tomography (SPECT) imaging of live mouse using Iodide-123 for analysis of thyroid disruptor effects Single Photon Emission Computed Tomography (SPECT) imaging of live mouse using Iodide-123 for analysis of thyroid disruptor effects

Academy 3 highlight

Metarisk brings together chemists, biologists, physicians, mathematicians, and risk management professionals to develop a new method to measure toxicological risks in a population and to help manage crisis situations.

The project

Metarisk aims to develop new metabolomics methods to assess a population’s exposure to chemical or radiotoxicological contaminations. Our strategy does not aim to identify exposure sources (such as toxic chemical agents) but, rather, to identify metabolomics biomarkers of exposure. Metabolomics yields qualitative and quantitative information on the nature and abundance of specific small organic molecules in biological samples that can attest to their contamination. The identification of these specific molecules should then enable discrimination between exposed and non-exposed individuals in a given population. The Metarisk project was launched recently: Our objective is to identify and characterize urinary metabolomic signatures of specific biological effects following exposure to different chemical sources. To best benefit from the combined expertise of the Metarisk team, we are initially focusing on chemical compounds that induce thyroid disruptor effects, radioactive iodine from nuclear industry accidents, and low-dose natural uranium. Meanwhile, we are developing methods for metabolomic analyses (LC-MS/MS) and for post-processing of metabolomics data (machine and deep learning). The work is in progress. We expect that the new metabolomics methods will become a useful tool for contamination tracking in a human population. As such, they would be helpful for population treatment, crisis management, and legal determination of individual exposure. The new metabolomics methods should also be useful for fundamental research in biology, toxicology and clinical research.

Chromatogram of a metabolite in samples of cultured cells exposed to pollutants
Chromatogram of a metabolite in samples of cultured cells exposed to pollutants Chromatogram of a metabolite in samples of cultured cells exposed to pollutants

    Non-invasive live cell cycle monitoring using quantitative phase imaging for innovative in vitro toxicological studies
Non-invasive live cell cycle monitoring using quantitative phase imaging for innovative in vitro toxicological studies Non-invasive live cell cycle monitoring using quantitative phase imaging for innovative in vitro toxicological studies

The +

If successful, this project should allow for the rapid identification of individuals who have been exposed to chemical or radiological contamination. These individuals could therefore be treated by health care professionals using appropriate crisis management procedures.

What’s next?

The capacity to detect and monitor biological effects of contamination using metabolomics should prove useful to optimize the management of related risks by crisis managers. To generalize and expand the scope of our results, we will build on the data obtained within the frame if this project to apply for additional funding from the European Union.

Project information

Scientific domain

Toxicology

Theme
Exposure metrology
Key words
Metabolomics
Spectrometry
Big data
Machine learning
Total budget
177.1 k€ including :
172.1 k€ from Académie 3 ;
5 k€ from Académie 4
Students inolved

Benjamin Reeves, PhD ICN
Xuchun Zhang, M2
Chenchen He, M1
Justine Bruna, M1
David Chardin, M2

Partner laboratories
ICN
IPMC
ESPACE
INRIA
CAL
Géoazur
GREDEG
Project members
Pourcher Thierry, 
Guigonis Jean-Marie,
Lindenthal Sabine,
Guglielmi Julien,
Darcourt Jacques, 
Benisvy Danielle, 
Carle Georges, 
Santucci Sabine ,
Pierrefitte-Carle Valérie, 
Glaichenhaus Nicolas,
Davidovic Laetitia, 
Suissa Laurent, 
Den Auwer Christophe,
Beccia Maria Rosa, 
Creff Gaëlle, 
Perez Sandra, 
Ayache Nicholas, 
Bouveyron Charles, 
Delingette Hervé, 
Gal Jocelyn, 
Provitolo Damienne,
Steichen Pascale.

portrait Thierry Pourcher
portrait Thierry Pourcher

Thierry Pourcher

TIRO MATOs, Université Côte d’Azur, CEA

Project valorization

Publication :

  • Primal-Dual for Classification with Rejection (PD-CR): A novel method for classification and feature selection. An application in Omics studies. Submitted to Computational and Structural Biotechnology Journal
logos partenaires METARISK 1
logos partenaires METARISK 1
logos partenaires METARISK 2
logos partenaires METARISK 2