The Systems Chemical Biology of Infection and Resistance Lab studies how pathogenic bacteria survive and infect, using chemical biology and genetic tools to define essential gene functions and gene-gene interdependencies. Ultimately, we aim to enable antimicrobial therapies which exploit key weaknesses in the ability of pathogenic bacteria to evolve resistance to antibiotics. Working at the interface of genetics, chemistry, and machine learning, we discover and use small molecules to systematically and precisely disrupt the cellular machinery of pathogenic bacteria and study the consequences of this disruption on their ability to survive, infect, and resiliently evolve resistance.
We primarily study Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), a top-10 cause of death globally which kills around 1.5 million people each year. Small molecules complement genetics because they are easily applied to disparate cell types and species, precisely perturb specific functions of multifunctional gene products, and directly bridge the gap between implication of genes in disease and new therapeutics.
The Systems Chemical Biology of Infection and Resistance Lab opened in January 2021 and is supported by Crick core funding and works with cutting edge Scientific Technology Platforms including Advanced Sequencing, Proteomics, and High-Throughput Screening. Over the next two years, we expect to expand to six people with a balanced mix of postdocs, PhD students, and Laboratory Research Scientists.
The lab focuses on the intersection of systems biology and chemical biology approaches to the problem of antimicrobial resistance in tuberculosis. As soon as new antimicrobial drugs are discovered and used in the clinic, pathogenic bacteria inevitably evolve resistance, driving an unsustainable cycle threatening the twentieth century’s improvements to public health. Antibiotics revolutionized modern medicine, but once again millions of lives are threatened by pathogenic bacteria like M. tuberculosis.
This is a BBSRC-funded postdoctoral position as part of a collaborative grant with Prof Johnjoe McFadden and Dr Matteo Barberis at the University of Surrey. The successful candidate will develop computational techniques for rapidly identifying the mechanisms of action of new antituberculosis compounds, especially inhibitors of nitrogen metabolism in the context of the host, using data from high-content phenotypic assays. The details of the project will be adapted through discussions between the successful applicant and the Group Leader.
Almost all projects in the lab require a combination of wet lab and computational work. The successful candidate will not necessarily have a background in both, but will be provided training in necessary skills allowing them to bridge the wet and dry labs.
In this project, some of the specific aims could include but not be limited to:
• Developing experimental and computational methods to rapidly assign mechanism of action to new small molecule inhibitors of M. tuberculosis growth
• Developing high-content phenotyping assays and analysis pipelines to refine our understanding of M. tuberculosis biology
• Screening for small molecule inhibitors of new targets in M. tuberculosis and experimentally validating their mechanisms of action
Postdoctoral Training Fellows are expected to lead their own projects, contribute to other projects on a collaborative basis (both in the lab and with external collaborators) and guide PhD students in their research. The ability to work in a team is essential.
Key experience and competencies
The post holder should embody and demonstrate our core Crick values: bold, imaginative, open, dynamic and collegial, in addition to the following:
- PhD (or in the final stages of PhD submission) in chemistry, chemical biology, molecular biology, microbiology, systems biology or related field
- Deep knowledge of microbial genetics, microbiology, and host-pathogen interactions
- Experience of working with intracellular bacterial pathogens
- Familiarity with cell-based high-throughput screening assays
- Enthusiasm to work with large high-content phenotypic datasets
- Eagerness to develop computational skills to analyse large datasets
- Ability to work independently and as part of a small team
- Strong oral and written communication skills
- Enthusiasm and initiative to develop new skills and to take interdisciplinary and quantitative approaches to scientific questions
- Understanding of next-generation sequencing platforms
- Experience with image processing
- Familiarity with flow cytometry