PhD Thesis: Development, characterization and control of E. coli communities on an automated experimental platform

Expected start date: Fall 2019

Keywords: natural and synthetic control of bacterial populations; systems biology; control; synthetic biology; engineering

A PhD position funded by the Inria Project-Lab CoSy  is open in project-team IBIS, which includes members of the Laboratoire Interdisciplinaire de Physique (LIPhy) of the University Grenoble-Alpes. The project includes data analysis and modelling tasks to be carried out at Inria, as well as experimental biology tasks carried out at LIPhy. Our interdisciplinary group, composed of biologists, computer scientists, mathematicians and physicists, studies bacteria, in particular Escherichia coli, at the level of the population and at the single-cell level. Our main focus is fundamental research, but we also aim at applications in biotechnology and synthetic biology.
Different species in natural bacterial communities generally communicate in complicated ways. Here, we construct precisely defined bacterial communities consisting of engineered strains of E. coli. Using this synthetic system, we can analyze and control the interactions between different subpopulations. In particular, we engineer bacteria that communicate by metabolites that are released in the medium and control the temporal expression profile of particular genes in the two populations by optogenetics.
The PhD project consists in constructing some of the strains, analyzing their behavior by measuring gene expression and growth parameters, and controlling their temporal dynamics using an advanced platform of mini-bioreactors coupled to a cytometer. By this setup, our aim is to achieve feedback control not only of mean behavior, but also of variability of growth and gene expression between and within subpopulations.

Student requirements
Applicants may come from different disciplinary backgrounds – physics, biology, engineering, and computer science. We expect them to be strongly motivated by interdisciplinary research combining experimental work in the lab with modeling of biological systems and data analysis. Basic knowledge in microbiology is required and previous experience with some of the above-mentioned techniques would be appreciated. Good relational skills are important for the project, as it will be carried out in an interdisciplinary and international environment.

Contact:  Eugenio Cinquemani ( and Hans Geiselmann (


  • Widder S. et al., Challenges in microbial ecology: Building predictive understanding of community function and dynamics (2016). The ISME Journal 10:2557-68
  • Izard, J., Gomez Balderas, C.D., Ropers, D., Lacour, S., Song, X., Yang, Y., Lindner, A.B., Geiselmann, J., and de Jong, H. (2015). A synthetic growth switch based on controlled expression of RNA polymerase. Molecular Systems Biology 11:840.
  • Jong, S.Casagranda, N.Giordano, E.Cinquemani, D.Ropers, J.Geiselmann, J.-L.Gouzé
    (2017). Mathematical modelling of microbes: Metabolism, gene expression and growth. Journal
    of the Royal Society Interface 14:20170502
  • Llamosi A, Gonzalez-Vargas AM, Versari C, Cinquemani E, Ferrari-Trecate G, Hersen P, Batt G (2016) What population reveals about individual cell identity: Single-cell parameter estimation of models of gene expression in yeast. PLoS Computational Biology 12: e1004706.

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