High frequency phase variable epigenetic systems; a novel paradigm for transcriptional control in bacteria

Principal Supervisor: Marco R. Oggioni, Department of Genetics, University of Leicester
Co-supervisor: Alexander N. Gorban, Department of Mathematics, University of Leicester

We have identified, as part of a previous PhD thesis, a novel type of phase variable epigenetic control mechanism in bacteria with impact on gene expression and important phenotypes such as capacity to cause disease. Phase variable switching in the specificity of type I restriction modification (RM) systems result in a change in methylation of the bacterial genome. With recombination rates hundred times higher than other systems and four to six instead of two distinct epigenetic control options, this mechanism does not only represent a novelty in epigenetic control, but also presents a challenge to modellers. This system is not exclusively found in the model pathogen Streptococcus pneumoniae, but is widespread in bacteria including Gram-positive bacteria responsible for foodborne infection. The present PhD project is a unique opportunity to investigate this new mechanism in food borne pathogen Listeria monocytogenes, a sophisticated model organism for intracellular pathogenicity. In particular, work will focus on the intriguing temperature dependent control mechanism of the phase variable system (unpublished preliminary data) reminiscent of other virulence related mechanisms which are differentially regulated outside (cold) and inside (warm) host cells.

The work will be divided in phases. A first phase will involve mining of published genomic data in species of interest for type I RM systems having multiple specificity subunits and a recombinase. Based on previous methodology (Manso et al., Nature Communications 2014) a PCR-restriction-GeneScan protocol will be designed and validated for allele quantification on multiple RM systems positive clinical and food strains present in the lab. The wet bench part of the project will specifically focus on the aspects of temperature dependent control of the phase variable RM system. Bacterial populations expressing each one single variant of the specificity subunit will be analysed for their in vitro and in vivo phenotypes at different temperatures, including work in cell cultures and experimental infections. Quantitative analysis of methylation will be determined by PacBio sequencing and the associated gene expression patterns defined by RNAseq. Next generation sequencing data, including the PacBio data, will be analysed in-house on software suites running on our high performance computing cluster.

We plan to develop a hierarchy of kinetic models for phase variation and epigenetic transformations. The structure and parameters of these models have to be identified from the experimental data. In large dimensions, the problem of identification becomes ill-conditioned therefore we will use the concept of “optimal complexity” and apply the modern methods of systems’ identification. In the model of optimal complexity state and parameters can be estimated reliably, in the worst-case scenario. An alternative method will be used the combination of agent-based methodology with the equation-free technologies. Equation-free methodologies will be exploited to directly couple various timescales without explicitly constructing effective coarse-grained models out of the microscopic core models.

Training: Techniques will include standard bacterial culture techniques, construction of mutants, molecular methods as PCR and GeneScan analysis, bioinformatic database analysis and processing of next generation sequencing data as methylome analysis, SNP detection and RNAseq analysis. In addition of work in microbial genetics the candidate will receive training in mathematical modelling. This will include the applied mathematics modules “Mathematical Modelling”, “Data Mining” and “Scientific Computing” as well as the advanced reading module of mathematical methods in genomics and epigenomics. The PhD student on this project will in addition attend the courses on Linux, High Performance Computing to be able to analyse sequence data on bioinformatics software suites running on high performance computing clusters.
Training on for in vivo skills training in mammalian systems. Students will attend the Home Office Training Courses on Rodents modules 1-4 and then be trained in the Central Research Facility in Leicester equipped with excellent imaging and biosafety biosafety facilities for experimental infections.