Enhancing in silico serotyping for bacterial vaccine development

Surface polysaccharides are common antigens in priority bacterial pathogens and therefore attractive targets for novel control strategies such as vaccines, monoclonal antibody and phage therapies. Distinct serotypes correspond to diverse polysaccharide structures that are encoded by distinct biosynthesis gene clusters; e.g. the Klebsiella pneumoniae species complex (KpSC) K- and O-loci encode the synthesis machinery for the capsule (K) and outer-lipopolysaccharides (O), respectively. Understanding the sero-epidemiology of these antigens can not only inform vaccine design, but improve/maintain vaccine efficacy after immunisation. Our team develops Kaptive, a bioinformatic tool to predict these serotypes directly from bacterial genomes, enabling rapid and large-scale sero-epidemiology. However, much of the information we have about these serotypes is inferred from genomic data, limiting our predict the resulting antigen and serological reaction from a genome. Much of the known information about antigens and their serotypes was confirmed in laboratories before the age of next-generation sequencing, resulting in a disconnect between genotype and phenotype. In this project, we are looking to consolidate as much as this information as possible to not only better predict bacterial antigen structures for vaccine design, but changes at the genetic level that influence vaccine efficacy. Outcomes for you as a student: • Experience in large scale genomic sequence analysis including bioinformatic workflows and high-performance computing- key skills in the modern microbiology research tool-box • Contribution to research that will support vaccine design Resources you will be supported by: • World-leading bacterial genomics research team • Access to a large collection of high-quality bacterial genome sequences • Remote-access, high-performance compute cluster What you will bring: • A passion for microbiology research to reduce the global burden of antimicrobial resistance and/or inform novel vaccines and other control strategies • A background in biology, including microbiology and/or molecular biology • An interest in learning genomic analyses, including command-line computing i.e. telling the computer what to do by typing a series of words rather than using a mouse to point and click. You don’t need prior experience in this, just a keen interest and demonstrated capacity to learn! The project can be tailored to suit individual research interests and degree levels.