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Multidisciplinary collaborations are a critical feature of bioscience research enabling integration of data collection with computational and/or mathematical modelling. This project provides an exciting opportunity for an individual to participate in a project spanning research into a foodborne pathogen, high frequency mutation, population biology, mathematical modelling and biostatistical analysis of data sets.
Campylobacter jejuni is a commensal of chickens that is responsible for many cases of gastroenteritis in humans due to consumption of contaminated, undercooked chicken meat. Many surface structures of these bacterial pathogens are subject to stochastic, reversible ON and OFF switches in gene expression mediated by changes in the numbers of tandem DNA repeats (also termed microsatellites). Changes in repeat number cause switches in gene expression by altering the reading frame of genes encoding surface determinants. The genomes of this bacterial species contain 14-27 genes, which are subject to phase variation due to mutations in repeat tracts. This modular behaviour can be coded as a 0-to-1 or 1-to-0 switch, produces a vast range of genotypes and is amenable to mathematical treatment. We are currently performing biological experiments to analyse the frequency with which switches occur in particular environments and the selective/population factors driving these changes.
The specific aims of this project are:- (i) to analyse experimental data sets for statistically-significant changes in population structure; (ii) to develop appropriate biostatistical tools to examine the statistical significance of data sets with regard to genotype quantification, combinatorial switching of genes and independence of switching events; (iii) to compare observed populations with output populations from stochastic models of populations behaviour; (iv) to provide statistical methods for estimation of sample sizes for further data collection.
We require an enthusiastic graduate with a Mathematics or Biostatistics 1st class degree (in exceptional circumstances a 2(i) class degree could be considered), preferably of the MSc level. A candidate with working knowledge of biological systems, particularly microbial replication and DNA replication, or/and of Applied Statistics will have an advantage.
Training in the development of mathematical approaches to data analysis and theoretical modelling of data will be provided by Profs. Alexander Gorban and Michael Tretyakov. Dr. Christopher Bayliss will provide training in analysis of biological data sets and in the specifics of measuring phase variation in different bacterial species. The student will have a supervisory committee of appropriately qualified individuals and access to the graduate programs in both the Departments of Genetics and Mathematics ensuring access to a variety of appropriate training courses.
References:
Bayliss CD, Bidmos FA, Anjum A, Manchev VT, Richards RL, Grossier JP, Wooldridge KG, Ketley JM, Barrow PA, Jones MA, Tretyakov MV (2012). Phase variable genes of Campylobacter jejuni exhibit high mutation rates and specific mutational patterns but mutability is not the major determinant of population structure during host colonization. Nucleic Acids Res. PMID: 22434884
Moxon ER, Bayliss CD and Hood DW (2007). Bacterial contingency loci: the role of simple sequence DNA repeats in bacterial adaptation. Annual Review of Genetics. 40:307-333.
Bayliss CD (2009). Determinants of phase variation rate and the fitness implications of differing rates for bacterial pathogens and commensals. FEMS Microbiological Reviews 33: 504-520.
De Bolle X, Bayliss CD, Field D, van de Ven T, Saunders NJ, Hood DW, and Moxon ER (2000). The length of a tetranucleotide repeat tract in Haemophilus influenzae determines the phase variation rate of a gene with homology to type III DNA methyltransferases. Molecular Microbiology, 35:211-222.