Understanding the coordination of DNA mismatch repair using live-cell single-molecule imaging

All organisms from bacteria to humans rely on molecular machines to ensure accurate replication of their genomes. The DNA mismatch repair pathway (MMR) spots and reverts errors during DNA synthesis. The proteins that perform MMR in cells solve a remarkable problem, detecting single misincorporated DNA bases amongst millions of correctly matched bases in the genome. Without MMR, mutation rates in cells increase 100 to 1000-fold. Loss of MMR is thus a driver of diseases, with accelerated genetic change leading to cancer development in humans and acquisition of drug resistance mutations in pathogens. Investigating the molecular mechanisms of MMR is therefore paramount for understanding its fundamental role in evolution, health and disease. MMR also plays an important role in the efficiency of genome engineering techniques that are currently revolutionising biological research, biotechnology, and medicine.

The mismatch repair mechanism must be both fast and accurate. This is achieved via the sequential action of different proteins (called MutS, MutL, MutH), whose recruitment and enzymatic activities on DNA are tightly controlled. Much has been learnt about the mechanism of MMR based on experiments with purified proteins, but it remains uncertain how the repair process works inside a living cell. Our proposal addresses this large gap in the understanding of MMR.

My lab specialises in the development of single-molecule microscopy methods to directly observe the unperturbed function of proteins in cells. Via high-speed fluorescence imaging, we can track the movement of individual proteins and detect when and where they bind to DNA. This allows us to obtain the exact information needed to address how MMR proteins search for repair sites and how the sequential steps in the pathway are coordinated. We will perform these experiments in E. coli bacteria - the organism in which MMR has been characterised in most detail. E. coli cells are also ideally suited for our imaging methods.

Visualising repair events in living cells will allow us to explore why MMR sometimes goes wrong. Although this happens rarely, each repair failure leads to a permanent mutation in a cell. One failure of the MMR pathway can be the moment when a human cell turns cancerous, or a pathogenic bacterium becomes drug resistant. We will extract quantitative information about the speed and location of repair events from our microscopy data, and feed this into a mathematical model to identify which factors determine repair success and failure.

Overall, this project will establish how MMR proteins work together in a pathway, providing direct insight into a central process that preserves the genetic information in cells.

Conserved DNA mismatch repair (MMR) proteins act in a coordinated pathway to correct base incorporation errors during DNA replication. MutS and MutL detect rare DNA mismatches in a vast excess of correctly paired DNA, and subsequently coordinate the incision, degradation, and resynthesis of the DNA daughter strand that contains the mispaired base. The ability of MMR to discriminate between the parental and daughter strands is crucial to prevent mismatches from becoming fixed mutations. The E. coli MMR pathway uses DNA methylation at GATC sequences as the strand discrimination signal, targeting incision by MutH to the unmethylated daughter strand. A central unanswered question is how mismatch recognition is signalled to incision at a GATC site that can be several thousand nucleotides distant and on either the 5'- or 3'-side of a mismatch. This process has to be accurately completed before the transient strand-discrimination signal is lost.

Detailed genetic analysis and high-resolution structures of MutS, MutL, and MutH suggest mechanisms for how mismatch recognition and signalling are achieved. Our vision is to translate these mechanistic insights into the context of the living cell. The aim of this proposal is to use new single-molecule imaging methods with microfluidic technology to observe and perturb MMR in E. coli cells. We will track the intracellular motion of MMR proteins to monitor how they search for mismatches and form multi-protein assemblies at repair sites. By measuring protein recruitment and turnover kinetics, we will test alternative models for the coordination of sequential pathway steps in vivo. We apply microfluidic chips to monitor thousands of cells over tens of generations, providing substantial statistical power to characterise rare events in MMR. Using imaging, mathematical modelling, and machine learning approaches, we will determine how the timing and location of repair affects the success rate of the pathway in reverting mismatches.