Key areas of focus
- Antimicrobial resistance and therapy
- Pathogenic Mechanisms and Evolution
This new theme harnesses the considerable local expertise and comprehensive databases generated at Cambridge University Hospitals (CUH) over recent years to tackle the problem of antimicrobial resistance (AMR). Our theme coordinates strengths in genomics and informatics with studies on host/pathogen interactions. We link DNA/RNA sequencing, analysis of pathogen, the microbiota and human genotype directly to clinical decision-making. We explore how pathogens survive in the patient during antibiotic treatment using state-of-the-art technologies that work directly off clinical sample through a hub laboratory within CUH. We conduct studies in active clinical settings threatened by antibiotic resistant microorganisms and introduce pathogen transmission mapping based on whole genome sequencing (WGS) using software that integrates geo-spatial mapping linked to genomic databases.
We try to bring a holistic and translational approach to clinical investigations, considering the pathogen, the microbiota and genetics/immunology in individual patients and clinical cohorts. We also work with companies that are developing adjunct therapies with the potential to clear or modulate colonisation by AMRs. We also have an interest in linking our work with external groups, particularly those working in economically deprived areas of the world.
WGS has revolutionised our understanding of bacterial evolution and the emergence of AMR in different settings, facilitating phylogenetic mapping of emerging threats e.g. C. difficile O27 and identifying their source and spread. We and other UK scientists have sequenced more than 200,000 bacterial genomes available as archived global databases for monitoring emerging AMR threats and have developed open-access software for analysis. Significantly, more than 5,000 bacterial isolates originating from CUH have been sequenced, making it perhaps the most intensively investigated clinical site in the world.
A key to controlling AMR is to understand how resistance is evolving within the healthcare setting. To this end, we have generated infection transmission maps based on WGSs covering the movement of pathogens within and into hospitals and communities. These transmission maps cover common AMR pathogens including MRSA and C. difficile. The partnership is extending these databases, capturing the movement of AMR within and into CUH and local communities, trying to generate an in depth analysis of the holistic impact of antibiotic therapy directly in patients. Samples are collected by the theme hub laboratory in close collaboration with the CUH/Public Health England (PHE) diagnostic laboratory. We are trying to identify (a) outbreaks within the hospital at an early stage and direct interventions (b) novel AMR threats and (c) potential introductions from the community. This transmission intelligence will directly facilitate decision-making by clinicians and infection management teams working with and beyond the theme.
AMR is an enormous challenge to the clinical treatment of infectious diseases. AMR is emerging in part by the dissemination of resistance genes between bacteria but also by the accumulating mutations in bacterial genomes that generally help bacteria manage antibiotics and resist their actions. We know of some resistance determinants but know little about many others, including transporters, regulators, stress response systems etc.
Thus, using this capital investment, we will build a unique and contained state-of-the-art high throughput platform based on cutting edge microscopy and integrated genomic analysis. For the first time we will be able to carry out in real time a highly detailed analysis of growing bacteria as they respond to known antibiotics or to novel compounds with potential antibacterial activities.
We are establishing a novel high-throughput screening platform that will be able to observe small populations of bacteria as they grow in the presence of antibiotics or new compounds with potential antibiotic activity. We will exploit reporter bacteria (using fluorescent or luminescent reporters as well as panels of mutant bacteria (e.g. transposon libraries). Using this information, we will be able to accurately predict how different bacteria respond to distinct classes of antibiotics, including signatures shared by different species or how they acquire multiple resistance. The analysis will benefit from state-of-the-art data (RNA, metabolome, proteome) analysis platforms available through links with The Wellcome Trust Sanger Institute (WTSI). We will also have direct access to core funding support for sequencing from WTSI.