Even healthy humans constantly interact with a vast diversity of bacterial species, which can normally be found growing over the skin, inside the nose, and throughout the gut. However, bacterial diseases are responsible for the loss of millions of lives every year. Some bacterial pathogens we study are usually harmless, but when given the opportunity, can cause life-threatening conditions such as pneumonia and meningitis (Streptococcus pneumoniae), bloodstream and wound infections common in hospitals (Staphylococcus aureus, Klebsiella pneumoniae and Clostridium difficile) and stomach ulcers (Helicobacter pylori). Other bacteria of interest to us are pathogens that depend on their ability to cause disease to spread between individuals, including bacteria causing sexually transmitted diseases (Chlamydia trachomatis and Neisseria gonorrhoeae), tuberculosis (Mycobacterium tuberculosis) and gastrointestinal infections (Escherichia coli and Campylobacter jejuni). The differences in these bacteria’s lifestyles, and the types of disease they cause, pose varied challenges to understanding how to best prevent them causing infections.
Our work aims to make best use of the recent explosion of bacterial genome data that has been made possible by advances in DNA sequencing technology. We are at the forefront of the development of new generally applicable statistical and computational tools to exploit genomic sequencing data in the fight against bacterial pathogens. This has required developing methods that can trace the transmission of bacteria between individuals (TransPhylo), identify rapidly evolving genes in the pathogens (ClonalFrameML, Gubbins), and collect (EpiCollect), analyse (WGSA) and visualise (Microreact) genetic and epidemiological information online. This allows us to discover how bacteria spread, evade the effects of the immune system and some vaccines, and become resistant to antibiotics. Achieving this necessitates that we run studies on a variety of scales, from single infections studied in detail, to multiple isolates from regional or national outbreaks, or worldwide collections to look at global populations.