One of the most fundamental questions in biology is how cells replicate, repair and segregate chromosomes, and how failures in those processes result in mutations, genome rearrangements or cell death. In mammalian cells, this is directly linked to the appearance of cancerous cells. In bacteria, many clinically relevant antibiotics target DNA replication and repair which in turn often promotes mutagenesis and recombination leading to drug resistance. DNA maintenance pathways have therefore been extensively studied at the molecular level both in eukaryotes and prokaryotes. However, most experiments are done in bulk while all genetic circuits operate and fail at the single cell level. Single cell analyses are in fact be particularly important for understanding DNA maintenance, not just because the rare failures lead to genetic alterations, which are more permanent than fluctuations in gene expression, but also because several key enzymes of DNA repair pathways are are expressed at extremely low levels. The importance of single molecule events and ‘noise’ is then generally greater.
Our work aims to explore the contribution of molecular stochasticity to genetic variability in E. coli in the physiological context of the cell. Our work is divided in three main lines of research:
We quantify in single cells the mRNA and protein level of RecBCD, which controls the main repair pathway and is reported to be present in low levels. We use single molecule microscopy to count in live cells RecBCD subunit numbers and quantify their heterogeneity using a recently developed microfluidics device. We use single particle tracking methods to follow repair in real time and assess cell-to-cell variability in the dynamics of the process. We monitor the impact of RecBCD fluctuations on the triggering of the SOS response, a transient state activated to allow repair of DNA before resuming DNA replication and cell growth. This response increases mutation rates, therefore acting as a possible causal link between heterogeneity in DNA repair and generation of genetic variants.
We are interested in testing how bacterial response to DNA damage is dependent on their underlying physiological state. For example, we vary their growth rate using different sugar sources and measure their sensitivity to DNA damaging antibiotics and their capacity to induce SOS. The results are interpreted using a coarse grained mechanistic model of bacterial growth and NDA repair developed in collaboration with V. Danos (University of Edinburgh and ENS, Paris). Briefly, the model recapitulates in an abstract but tractable manner the main molecular processes controlling bacterial growth such as production of energy, transcription/translation and cell division. This will allow us to directly input our measurements in the predictions of the model and test seemingly counter-intuitive behaviors such as the antagonistic effects of certain antibiotics combination.
Bacteria have evolved a defence mechanism against bacteriophages and plasmids named CRISPRs (clustered regularly interspaced short palindromic repeats). The CRISPRs response induces double strand breaks to the incoming DNA, which becomes a target for degradation by RecBCD. We are explore how RecBCD interacts with this system. In particular, we are using the CRISPRs-cas9 system to target the conjugative plasmid R388 and measure in single cell conjugation rates in the presence of CRISPRs-cas9 (collaboration with F. de la Cruz, Satander, Spain). Preliminary results indicate that this system efficiently prevents conjugation but that some plasmids are able to escape either because of mis-targetting, too low levels of RecBCD or because of mutation. This raises the question of how evolutionary forces shape this process and we have recently started to explore how to model such processes with S. Méléard (Ecole Polytechnique).