systems biology; bioinformatics; biotechnology; biophysics; proteomics; microbiology; molecular biology; mathematical biology

Eteindre et rallumer la machinerie d'expression génique chez les bactéries: de modèles mathématiques aux applications biotechnologiques

Bio-informatique (BINF)


Informations générales

Référence projet : 11-BINF-0005
Etablissement Coordinateur : INRIA_Centre Saclay Ile-de-France
Région du projet : Auvergne-Rhône-Alpes
Discipline : 5 - Bio Med

Aide de l'ANR 1 500 000 euros
Investissement couvrant la période de septembre 2012 à septembre 2017

Résumé de soumission

One of the key issues in biotechnology is the redesign of microorganisms to optimize the yield of products of interest, such as biofuels, bulk and fine chemicals, or molecules of medical interest. The redesign modifies the metabolic flux distribution such that, ideally, the cells switch from growth, i.e., biomass production, to product synthesis. In order to redirect metabolic fluxes, classical approaches have focused on the genetic modification of specific components of metabolism, such as the overexpression of heterologous enzymes or enzymes involved in rate-limiting steps. Whether based on an empirical understanding of the system or on a mathematical model of metabolism, these approaches have met with only partial success, due to the robustness of the regulatory mechanisms of the cell that tend to maintain a flux distribution optimal for growth.

The aim of the RESET project has been to break with these classical approaches and propose a novel strategy for improving product yield and productivity. Instead of interfering with the functioning of specific pathways, we have focused on a global control system of the microbial cell, the gene expression machinery (GEM). The synthesis of all proteins and RNAs, and thus the production of biomass, is dependent on RNA polymerase, ribosome, and other components of the GEM. The basic idea of our approach is to arrest the GEM in a precise and controlled way, so as to create non-growing cells with a functioning metabolism that utilizes substrates for the synthesis of specific target compounds rather than for biomass. Conversely, when the degradation of enzymes and other proteins threatens the stability of metabolic fluxes, the GEM is switched on again, thus alternating phases of growth and product synthesis.

In order to meet this ambitious goal, several scientific and technological challenges were met in RESET. First, we needed to be able to arrest and restart the GEM in a quick and reversible way. A key element for achieving this has been the development of a genetic circuit for externally controlling the expression of RNA polymerase in the bacterium Escherichia coli. In order to assess physiological changes provoked by turning on or shutting off the GEM, we have used a combination of proteomics, metabolomics, and transcriptomics techniques. In parallel, we developed a second strategy for growth arrest, based on the external control of a key regulator of the replication machinery and an original induction system using transcription activation via the Uhp two-component system.

Second, in order to better understand and possibly optimize the effects of the externally controlled genetic circuits on the GEM, we developed coarse-grained, quantitative models of the GEM and the effect of the GEM on metabolic fluxes, calibrated by means of literature data and dedicated experiments. Several techniques for model reduction and analysis were developed, which when applied to the models, contributed to better understanding the mechanisms underlying some of the observed phenomena, such as the effect of the timing of growth arrest on the production yield and the ultrasensitive response of the growth rate to changes of the RNA polymerase concentration.

Third, we have ascertained the feasibility of our approach for improving the bioproduction of metabolites both in the academic laboratory and in a pre-industrial environment. We notably provided a proof-of-concept by means of engineered E. coli cells capable of producing glycerol from glucose by expressing two heterologous enzymes. We showed that the yield of glycerol production during growth arrest in a growth-arrested strain is higher than in a growing wild-type strain expressing the same enzyme, and that the obtained yield is close to the theoretical maximum. The industrial partner of the project has extended the test from the µL to the L scale, by confirming the results in a bioreactor operating in industrially relevant conditions. We have also made first steps to further increase the genetic stability of the strains, replace the chemical induction system by a more economical and better controllable optogenetic system, explore more complex process conditions, and start the construction of a strain capable of producing a second product of interest, 1,3 propanediol (1,3-PD).

These results summarized above demonstrate that the desired reallocation of resources from growth towards the production of a molecule of interest is indeed feasible by means of the approach of the RESET project. The results form the basis of a European patent, extended to the US, the main claims of which were accepted by the EPO and USPTO. In parallel, the project partners concerned have launched the valorization action Theo, supported by Linksium, the local agency for technology transfer and start-up incubation in Grenoble. More generally, the project efforts have resulted in 18 journal publications, 15 conference publications, and 3 PhD theses (completely or partially) funded by RESET. Several other publications are under review or in an advanced stage of submission. Moreover, two software programs developed within the RESET project, with additional support from other funding programs, have been deposited at the APP and are being distributed to the broader community, in one case through the cloud of the PIA-supported Institut Français de Bioinformatique (IFB).  A workshop presenting the RESET results was held as a satellite event of the annual meeting of the French special interest group in systems and synthetic bology (GDR BioSynsSys).

The RESET project spawned a broad range of research topics some of which will be continued after the end of the project, either by wrapping up the work in the form of journal publications or in the context of new projects. For example, work on self-replicator models of bacterial growth, in close relation with the modeling efforts undertaken in RESET, lie at the basis of the new ANR project Maximic, involving three RESET partners. Another ANR proposal has been submitted this year and we will actively explore funding possibilities for the maturation of biotechnological applications of the growth switch.

L'auteur de ce résumé est le coordinateur du projet, qui est responsable du contenu de ce résumé. L'ANR décline par conséquent toute responsabilité quant à son contenu.

Liens utiles