My primary research goal is to elevate our ability to study infectious diseases caused by bacteria. I believe we should be constantly advancing (in terms of both rapidity and accuracy) in our ability to take any infectious disease, define its root causes, and devise strategies for prevention and treatment.
The overall strategy is to use a tractable model system of disease as a testing grounds for novel approaches. My lab uses a mouse model of urinary tract infection (UTI), which is caused by uropathogenic Escherichia coli (UPEC). This is an outstanding system for its correspondence with human disease and for the combination of mice (the best studied and most easily manipulated experimental animal) and E. coli (the most well studied organism of all). However, many other infectious diseases lack animal models and many bacteria are not tractable in the lab; thus, the only viable general approach to improving our study of infectious disease is genomics. My lab therefore has focused on applying new genomics tools to the study of UTI and infectious diseases in general.
From my initial work in the UTI system, my lab has now grown to encompass three themes of work, all of which share the common goal of developing new tools to elevate our study of UTI in the further service of studying other infectious diseases. These themes are functional genomics, genetics and synthetic biology, and computational sequence analysis.
In functional genomics, we are building on single cell genomics expertise in GIS to perform niche-specific, single cell, simultaneous host and pathogen expression profiling to understand intracellular stages of urinary tract infections. These are important because they may explain recurrent urinary tract infections, which can sometimes plague patients for many years or decades. We have also used novel sequencing-based approaches (with PacBio and Illumina sequencing) to derive a global understanding of the regulation of Type 1 pili, the most important virulence factor for E. coli to cause urinary tract infection.
For genetics and synthetic biology, my lab has spent 7 years developing techniques specifically for wild type, clinical isolates of E. coli. Decades of research have provided numerous genetic tools usable in lab-adapted, cloning strains of E. coli; we have essentially arbitrary control over making any change to the genome of this bacterium. However, lab-adapted strains do not typically cause infections; understanding disease-causing clinical isolates has been much more difficult, as much of the wealth of E. coli genetics techniques are less efficient or unusable in wild type E. coli isolates. We developed a stringent negative selection system usable in nearly all isolates of E. coli and other Enteric bacteria, which enables us to perform "perfect" genetics and achieve arbitrary control over the genomes of disease-causing E. coli isolates, just as we can with cloning strains.
For sequence analysis, I work with the GIS GERMS platform to collaborate with the local clinical community to understand the genomics of local Singaporean bacterial isolates. Microbiology is local; Singapore and Asia have different strains and sometimes different infections than elsewhere in the world. We use whole genome sequencing to do outbreak analysis, which helps to trace the extent and source of an infection. We also are exploring computational methods to use local genome sequences to understand the overall evolution of bacteria in Singapore and Asia. Two two highlights from this theme are the 2015 Streptococcus agalactiae (Group B Streptococcus, GBS) outbreak in Singapore and an analysis of Campylobacter-mediated abortion in livestock in the United States. The genomics work on GBS helped prove that GBS could indeed be transmitted by eating contaminated food, a new paradigm for GBS disease. The Campylobacter project, done in collaboration with Qijing Zhang at Iowa State University, found a single gene responsible for enabling one clone of C. jejuni to cause abortion in livestock. This was found using a new experimental technique we call sexual genetics (akin to using F1 hybrids in mice to map a phenotype). We also found a population genetics analysis could identify the same gene just from computational analysis of Campylobacter genome sequences.
These three themes are distinct yet related, all coming back to improving our ability to study infectious disease. As an example of the interplay between the three themes, the Campylobacter work (Theme 3) has launched new projects to develop sexual genetics techniques for E. coli (Theme 2) as well as using population genetics to understand the evolution of virulence in GBS and E. coli (Themes 1 and 3).