Quantitative tool for in vivo analysis of DNA-binding proteins using High Resolution Sequencing Data

DNA-binding proteins (DBPs) such as repair proteins, DNA polymerases, re- combinases, transcription factors, etc. manifest diverse stochastic behaviours dependent on physiological conditions inside the cell. Now that multiple independent in vitro studies have extensively characterised different aspects of the biochemistry of DBPs, computational and mathematical tools that would be able to integrate this information into a coherent framework are in huge demand, especially when attempting a transition to in vivo characterisation of these systems. ChIP-Seq is the method commonly used to study DBPs in vivo. This method generates high resolution sequencing data { population scale readout of the activity of DBPs on the DNA. The mathematical tools available for the analysis of this type of data are at the moment very restrictive in their ability to extract mechanistic and quantitative details on the activity of DBPs. The main trouble that researchers experience when analysing such population scale sequencing data is effectively disentangling complexity in these data, since the observed output often combines diverse outcomes of multiple unsynchronised processes reflecting biomolecular variability. Although being a static snapshot ChIP-Seq can be effectively utilised as a readout for the dynamics of DBPs in vivo. This thesis features a new approach to ChIP-Seq analysis { namely accessing the concealed details of the dynamic behaviour of DBPs on DNA using probabilistic modelling, statistical inference and numerical optimisation. In order to achieve this I propose to integrate previously acquired assumptions about the behaviour of DBPs into a Markov- Chain model which would allow to take into account their intrinsic stochasticity. By incorporating this model into a statistical model of data acquisition, the experimentally observed output can be simulated and then compared to in vivo data to reverse engineer the stochastic activity of DBPs on the DNA. Conventional tools normally employ simple empirical models where the parameters have no link with the mechanistic reality of the process under scrutiny. This thesis marks the transition from qualitative analysis to mechanistic modelling in an attempt to make the most of the high resolution sequencing data. It is also worth noting that from a computer science point of view DBPs are of great interest since they are able to perform stochastic computation on DNA by responding in a probabilistic manner to the patterns encoded in the DNA. The theoretical framework proposed here allows to quantitatively characterise complex responses of these molecular machines to the sequence features

Quantitative genomic analysis of RecA protein binding during DNA double-strand break repair reveals RecBCD action in vivo

International audienceUnderstanding molecular mechanisms in the context of living cells requires the development of new methods of in vivo biochemical analysis to complement established in vitro biochemistry. A critically important molecular mechanism is genetic recombination, required for the beneficial reassortment of genetic information and for DNA double-strand break repair (DSBR). Central to recom-bination is the RecA (Rad51) protein that assembles into a spiral filament on DNA and mediates genetic exchange. Here we have developed a method that combines chromatin immunoprecipita-tion with next-generation sequencing (ChIP-Seq) and mathematical modeling to quantify RecA protein binding during the active repair of a single DSB in the chromosome of Escherichia coli. We have used quantitative genomic analysis to infer the key in vivo molecular parameters governing RecA loading by the helicase/ nuclease RecBCD at recombination hot-spots, known as Chi. Our genomic analysis has also revealed that DSBR at the lacZ locus causes a second RecBCD-mediated DSBR event to occur in the terminus region of the chromosome, over 1 Mb away. homologous recombination | mechanistic modelling | DNA repair | RecA

RecG directs DNA synthesis during double-strand break repair

Homologous recombination provides a mechanism of DNA double-strand break repair (DSBR) that requires an intact, homologous template for DNA synthesis. When DNA synthesis associated with DSBR is convergent, the broken DNA strands are replaced and repair is accurate. However, if divergent DNA synthesis is established, over-replication of flanking DNA may occur with deleterious consequences. The RecG protein of Escherichia coli is a helicase and translocase that can re-model 3-way and 4-way DNA structures such as replication forks and Holliday junctions. However, the primary role of RecG in live cells has remained elusive. Here we show that, in the absence of RecG, attempted DSBR is accompanied by divergent DNA replication at the site of an induced chromosomal DNA double-strand break. Furthermore, DNA double-stand ends are generated in a recG mutant at sites known to block replication forks. These double-strand ends, also trigger DSBR and the divergent DNA replication characteristic of this mutant, which can explain over-replication of the terminus region of the chromosome. The loss of DNA associated with unwinding joint molecules previously observed in the absence of RuvAB and RecG, is suppressed by a helicase deficient PriA mutation (priA300), arguing that the action of RecG ensures that PriA is bound correctly on D-loops to direct DNA replication rather than to unwind joint molecules. This has led us to put forward a revised model of homologous recombination in which the re-modelling of branched intermediates by RecG plays a fundamental role in directing DNA synthesis and thus maintaining genomic stability