Exploring the phasevariome and contributions of phasotypes to the disease-causing attributes of Campylobacter jejuni.
This project will test the broad hypothesis that “Phase variation enables Campylobacter jejuni to adapt to a variety of different niches contributing to the virulence and spread of this pathogen”.
Phase variation refers to high frequency, reversible ON and OFF switching of specific phenotypes mediated by hypermutable DNA sequences or epigenetic modifications (ref 1-3). Phase variation enables adaptation to fluctuating environments and a range of strong selection pressures. Hence this phenomenon is widespread in bacterial pathogens.
Campylobacter jejuni is the major causative agent of foodborne gastroenteritis across Europe. Contaminated chicken meat is the major source of infections and hence control of this pathogen is critical to food security in the poultry industry. An unusual feature of this pathogen is that multiple genes are subject to polyG repeat-mediated phase variation causing ON/OFF switches in gene expression2. Four phase variable genes can produce 16 combinations of different expression states (e.g. ON-ON-ON-ON, OFF-ON-ON-ON, OFF-OFF-ON-ON) termed ‘phasotypes’. The number of phasotypes rises exponentially such that 12 genes have 4,096 combinations - the ‘phasevariome’. High mutation rates of polyG repeats permits rapid exploration of this ‘phasevariome’ enabling rapid adaptation to environmental selection and, as many of these genes modify known virulence factors (flagella, lipooligosaccharide, capsule), may contribute to disease.
We have recently developed rapid approaches for analysing the phasevariome of one C. jejuni strain (i.e. NCTC11168) containing 27 phase variable genes (ref 4). Exploration of the ‘phasevariome’ of other strains and of the contributions of phasotypes to pathogenesis is critical for understanding whether phase variation is an important component of the disease-causing attributes of C. jejuni. A critical aspect of this project will be a systems biology approach for exploration of the protein expression states, specific structures of virulence factors (many of the genes mediate biosynthesis of specific glycans) and of the phenotypes associated with different phasotypes. Progress will therefore require a unique combination of experimental, statistical, -omics and systems approaches.
Objective 1. Discover important adaptive phasotypes for different niches/hosts
Year 1. Explore Campylobacter genomic databases and sequences for associations between phasotype and:- (i) infection type (mild - severe diarrhoea); (ii) infection source (environment - poultry); and (iii) survival in the food chain (e.g. abattoir - farm; ref 7). Set-up of phasotype detection systems for various C. jejuni strains. Compare predominant phasotypes in human gastrointestinal samples versus poultry sample (ref 6)s.
Year 2. Develop phasotype/phenotype database for systems-based interrogation of data sets.
Objective 2. Test specific phasotypes for contributions to infection.
Year 2. Test for selection of specific phasotypes during experimental infections of chickens (ref 4), Galleria larvae (ref 5) and mice (ref 6).
Year 3. Generate non-switching mutants. Test mutants in infection models. Structural analysis of capsule and lipooligosaccharide polysaccharides.
We are an equal opportunities employer and particularly welcome applications for Ph.D. places from women, minority ethnic and other under-represented groups.
1. E.R. Moxon, C.D. Bayliss and D.W. Hood (2007). Bacterial contingency loci: the role of simple sequence DNA repeats in bacterial adaptation. Annual Review of Genetics. 40:307-333.
2. C.D. Bayliss (2009). Determinants of phase variation rate and the fitness implications of differing rates for bacterial pathogens and commensals. FEMS Microbiological Reviews 33: 504-520.
3. Bayliss (2009). Determinants of phase variation rate and the fitness implications of differing rates for bacterial pathogens and commensals. FEMS Microbiological Reviews 33: 504-520.
4. Bayliss et al. (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 colonisation. Nucl. Acids Res. 40: 5876-5889.
5. Champion et al. (2010). Insect infection model for Campylobacter jejuni reveals that O-methyl phosporamidate has insecticidal activity. J. Infect. Dis. 201: 776-782.
6. Kim et al. (2012). Passage of Campylobacter jejuni through the chicken reservoir or mice promotes phase variation in contingency genes Cj0045 and Cj0170 that strongly associates with colonization and disease in a mouse model. Microbiology 158: 1304-1316.
7. Sheppard et al. (2013). PNAS 110: 11,923-7.
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