Contexte et atouts du poste
The postdoctoral project will be carried out in the project-team MICROCOSME at Inria Grenoble - Rhône-Alpes under the joint supervision of Aline Marguet, Eugenio Cinquemani and Hidde de Jong within the framework of the ARBOREAL ANR project.
MICROCOSME is an interdisciplinary team that includes applied mathematicians, engineers, computer scientists, biologists as well as experimentalists from the biology/physics team BIOP of the Université Grenoble-Alpes.
Mission confiée
Gaining an understanding of the cellular processes underlying bacterial growth is crucial for fundamental research in biology as well as for applications in biotechnology, health, and environmental technology.
New experimental technologies have been developed
to monitor growth and gene expression at the single-cell level, opening the path to the exploration of the origins of variability in growth phenotypes within a population of bacterial cells.
So far, the data obtained from these technological breakthroughs have been exploited only in part.
In particular, appropriate mathematical models and methods to relate single-cell gene expression data with the emergence of growth variabilityin a population are rare [1].
The ARBOREAL ANR project aims at developing a new mathematical framework for the analysis of growth variability from single-cell data, by combining structured branching processes [2, 3] with models of bacterial growth [4] at the single-cell level.
We will obtain a
new class of stochastic individual-based models, called Branching Resource allocation Processes (BRP), that will enable investigation of the variability of growth phenotypes in a proliferating microbial population in terms of the variability of physiological and cell division processes.
The development of the BRP framework will entail modelling, analysis, and inference, and will exploit microfluidics experiments comprising single-cell measurements of growth and expression levels of ribosomes and enzymes in the model organism Escherichia coli [5].
The proposed postdoc position involves the numerical simulation, analysis and inference of branching resource allocation processes and the application of this new framework to existing single-cell datasets in the team to study the onset of growth variability in bacterial
populations.
Principales activités
Using a variety of mathematical tools and algorithmic approaches (Continuous-Time Markov chains, Mixed-Effects modelling, Branching processes, stochastic simulation) as well as single-cell gene expression datasets, we will address several of the following points:
Bibliography.
[1] Thomas, P., G.
Terradot, V.
Danos, and A.
Y.
Wei e, Sources, propagation and consequences of stochasticity in cellular growth.
Nat Commun 9:4528, 2018.
[2] A.
Marguet, Uniform sampling in a structured branching population,Bernoulli, 25, pp.
2649–2695, 2019.
[3] S.
Méléard and V.
Bansaye, Stochastic Models for Structured Populations: Scaling Limits and Long Time Behavior, Springer Cham, 2015.
[4] N.
Giordano, F.
Mairet, J.-L.
Gouzé, J.
Geiselmann, and H.
de Jong, Dynamical allocation of cellular resources as an optimal control problem: Novel insights into microbial growth strategies, PLoS Comput Biol, 12, p.
e1004802, 2016.
[5] A.
Pavlou, E.
Cinquemani, C.
Pinel, N.
Giordano, M.
Van Melle-Gateau, I.
Mihalcescu, J.
Geiselmann and H.
de Jong.
Single-cell data reveal heterogeneity of investment in ribosomes across a bacterial population.
Nat Commun 16, 285 .
Compétences
Interested candidates are expected to have a solid preparation in dynamical system / stochastic process modelling and analysis and some familiarity with scientific programming, and to be interested in biological applications and data processing.
Avantages
Rémunération
2788 € gross salary / month