Postdoc in systems biology - microbial ecology - metabolic modelling of the gut microbiota
CDD · Postdoc · 24 mois Bac+8 / Doctorat, Grandes Écoles Inria Bordeaux Sud-Ouest · Talence (France)
Date de prise de poste : 1 octobre 2021
systems biology microbiota metabolic modelling dynamics logic programming
Context of the position
The position is funded by Inria and is part of the Inria Exploratory Action SLIMMEST: Statistical Learning of the Intestinal Microbiota MEtabolism in Space and Time. This project consists in two postdoc positions: one scientist with a systems biology background, and a second with an applied mathematical background. Both scientists will work in close collaboration on an exciting project aiming at building a spatio-temporal numerical model of the gut microbiota. This particular offer concerns the systems biology profile.
The main objective of the SLIMMEST project is to resolve a numerical bottleneck in spatio-temporal modeling of microbiota: the coupling between microbe-scale metabolic models with community-scale dynamics described with PDE models. The recruited person will provide expertise in system biology, microbial metabolism, and community-wide metabolic network modeling. Missions will include modelling and simplification of metabolic models in order to identify metabolic drivers of ecosystems. Such drivers will in turn be used by the second postdoc scientist of the project to develop machine learning techniques and build a partial differential equations (PDE) model of the gut microbiota.
The two recruited candidates will be members of the Pleiade team, a joint research group between Inria and INRAE, in the beautiful city of Bordeaux. Pleiade is an interdisciplinary group at the frontier of computer science, mathematics, bioinformatics and biology. One of our main research interests is to develop and validate new computational and numerical models for microbial ecology, that we dedicate to better understand the complex interactions occurring in complex communities of microorganisms known as microbiotas.
Description of the position
The recruited person will be taken to carry the metabolic-modelling related part of the SLIMMEST project.
The dynamics of a microbial community is driven by the metabolism of its microorganisms, the interactions between those microorganisms, and spatio-temporal interactions between them and the environment. Mathematical and computational models of such dynamics are crucial to build mechanistic hypotheses of the biological observations, as well as predict the evolution of the ecosystems, and actions to lead ecosystems in a desired state. SLIMMEST will combine logic programming and metamodelling of metabolism in a scalable framework applied to communities of the gut microbiota.
The mission of this postdoc position is to develop methods suitable to the reduction of metabolic models for a community. The purpose is to simplify the metabolism of an ecoystem by targeting crucial functions that are main drivers of the ecosystem. The results will be used in mathematical models by the second postdoc scientist of the project.
For that purpose, we must model the metabolism of bacteria from their genome, and connect metabolic networks to the available literature resources on pathways of interest such as short-chain fatty acid production. The simplification of the community metabolism will be performed by modelling constraints and solving combinatorial optimisation problems. In addition, the successful candidate will contextualise the results of community metamodelling back to metabolic networks. The first application of the project will be a model of the murine gut microbiota, with expectations to successfully scale up the size of the community during the project.
For a better knowledge of the proposed research subject:
- J. D. Orth, I. Thiele, and B. Ø. Palsson, « What is flux balance analysis? ». In : Nat Biotechnol, vol. 28, no. 3, pp. 245–248, 2010, doi: 10.1038/nbt.1614.
- Arnaud Belcour et al. « Metage2Metabo, microbiota-scale metabolic complementarity for the identication of key species ». In : eLife 9 (2020), e61968. doi : 10.7554/elife.61968.
- Seth R Bordenstein et Kevin R Theis. « Host biology in light of the microbiome : ten principles of holobionts and hologenomes ». In : PLoS Biol 13.8 (2015), e1002226.
- Oliver Ebenhöh, Thomas Handorf et Reinhart Heinrich. « Structural analysis of expanding metabolic networks. » In : Genome informatics. International Conference on Genome Informatics 15.1 (2004), p. 35-45. issn : 0919-9454.
- Clémence Frioux, Simon M Dittami et Anne Siegel. « Using automated reasoning to explore the metabolism of unconventional organisms : a first step to explore host–microbial interactions ». In : Biochemical Society Transactions 48.3 (2020), p. 901-913. issn : 0300-5127. doi : 10.1042/bst20190667.
- Simon Labarthe et al. « A mathematical model to investigate the key drivers of the biogeography of the colon microbiota ». In : Journal of theoretical biology 462 (2019), p. 552-581.
- Ilias Lagkouvardos et al. « The Mouse Intestinal Bacterial Collection (miBC) provides host-specific insight into cultured diversity and functional potential of the gut microbiota ». In : Nature microbiology 1.10 (2016), p. 1-15.
- Arun S Moorthy et al. « A spatially continuous model of carbohydrate digestion and transport processes in the colon ». In : PloS one 10.12 (2015), e0145309.
- Alberto Noronha et al. « The Virtual Metabolic Human database : integrating human and gut microbiome metabolism with nutrition and disease ». In : Nucleic Acids Research 47.D1 (2018), p. D614- D624. issn : 0305-1048. doi : 10.1093/nar/gky992.
- Clémence Frioux et al. « Scalable and exhaustive screening of metabolic functions carried out by microbial consortia ». In : Bioinformatics 34.17 (2018), p. i934-i943. issn : 1367-4803. doi : 10.1093/ bioinformatics/bty588.
- Build high quality metabolic models of a simplified model of murine gut microbiota using state-of-the-art methods. Model them using qualitative and quantitative (Flux Balance Analysis) techniques.
- Develop methods to simplify a community of metabolic models using logic constraints and combinatorial optimisation.
- Characterize the main functions and interactions that drive the community
- Analyse results of metamodelling by identifying and visualising metabolic functions provided by the simulations
- Share the results of the projects through scientific publications and code/documentation distribution
- Collaborate with the second post-doc of the project by providing expertise on community-scale metabolic modeling. This expertise will be crucial to build the community scale problem and to analyse the results to identify the metabolic significance of the results.
- Participate in supervising students in the team.
Technical skills and level required:
- Systems biology skills: metabolic network modelling or skills in a close area.
- Python programming
- Data analysis: Python or R
- Scientific writing
- English for scientific communition
- English or French for day to day work
- Ability to work in a collaborative environment
- Good communication skills (sharing results, supervising students)
Other valued appreciated: logic programming (e.g. Answer Set Programming) is a plus but is not mandatory.
- Subsidized meals
- Partial reimbursement of public transport costs
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage
2653€ / month (before taxs)
More information on: https://jobs.inria.fr/public/classic/fr/offres/2021-03628
Procédure : Online application via https://jobs.inria.fr/public/classic/fr/offres/2021-03628
Date limite : 30 août 2021
Offre publiée le 5 mai 2021, affichage jusqu'au 31 août 2021