Section: New Results

Growth control in bacteria and biotechnological applications

A bacterial cell adapts its growth rate and the level of gene expression required to sustain growth to the environment, notably to the availability of nutrients providing the molecular building blocks and the energy required for growth. This adaptive response involves the global physiological state of the cell, in particular the activity of the gene expression machinery, and DNA-binding transcription factors and other specific regulators. While many studies have focused on networks of transcription factors, the analysis of the relative contributions of both transcription factors and global effects of the physiological state has received relatively little attention thus far. There is a huge literature on the molecular mechanisms coupling the activity of the gene expression machinery to changes in the nutritional quality of the environment, but a quantitative and dynamic picture of this very complicated regulatory system is still missing. Delphine Ropers and Edith Grac as well as Nils Giordano are developing models to achieve this, from bottom-up and top-down perspectives, respectively.

The quantitative models adopting the bottom-up pespective describe the molecular mechanisms controlling the activity of the gene expression machinery. The calibration and analysis of these models is made difficult by their complexity, the nonidentifiability of many parameter values, and the heterogeneity of experimental data sources. To overcome these difficulties, Delphine Ropers and Edith Grac are developing model ensembles with the same structure but different parameter values that are consistent with the experimental data. In collaboration with Jean-Luc Gouzé and Ismail Belgacem from the BIOCORE project-team at Inria Sophia-Antipolis-Méditerranée, they have analysed the dynamical behavior of a central module of these models, which controls the cellular concentration of the RNA polymerase, the key player of the transcriptional machinery. By means of model reduction approaches and monotone system theory, they have analyzed the equilibria of the system and their stability, which they could relate to biological observations on E. coli. This work has been published in the proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems (MTNS 2014) [9] and the 53rd IEEE Conference on Decision and Control (CDC 2014) [10] . A journal article is in preparation.

In the context of the PhD thesis of former IBIS member Jérôme Izard, we have studied the relation between the gene expression machinery, the global physiology of the cell, and the growth rate from a different perspective. Our aim was to change the mechanisms regulating the activity of the gene expression machinery in such a way so as to be able to externally control the growth rate of the cell. More precisely, we have engineered an E. coli strain in which the transcription of an essential component of the global gene expression machinery is under the tight control of an inducible promoter. By adjusting the inducer concentration in the medium we can adjust the activity of the gene expression machinery and thereby reversibly switch the growth rate of the bacterium between zero and the maximal growth rate. Our modified E. coli strain, described in a paper prepared for submission, opens new perspectives for studying the mechanisms of growth control as well as for developing biotechnological applications, the subject of the post-doctoral fellowship of Cindy Gomez Balderas-Barillot. We have submitted a patent proposing such applications, which underlies the technology transfer activities undertaken in the recently-started Reset project (Section  8.1 ).