Dr Francesc Coll
BSc MSc PhD
Francesc joined the School in July 2016 as a Postdoctoral Fellow in Prof. Sharon Peacock's group funded by a Sir Henry Wellcome Postdoctoral Fellowship. He was previously a Postdoctoral Research Associate in Prof. Peacock's group at the Department of Medicine, University of Cambridge (2014 to 2016) where he worked on the epidemiology of Methicillin-Resistant Staphylococcus aureus using whole-genome sequencing. In October 2014, he completed his Ph.D. at the School under the supervision of Prof. Taane Clark, which focused on strain genotyping and drug resistance in Mycobacterium tuberculosis using whole genome sequencing.
Francesc has taught in multiple short courses on bioinformatics and microbial genomics including:
- Kenya-United Kingdom Staphylococcus aureus training collaboration (KUK-SATC) workshop in Nairobi, Kenya (February 2017)
- Genomic Epidemiology in Infectious Diseases (GEID2016) in Bangkok, Thailand (March 2016)
- Pathogen genomics and genomic epidemiology of infectious diseases in London, UK (September 2012, 2013 and 2014)
- High throughput sequencing in disease studies in London, UK (September 2012, 2013 and 2014)
The introduction of genome-wide association studies (GWAS) in microbial genetics has recently become possible as a result of falling DNA sequencing costs. GWAS in pathogenic bacteria have the potential to shed light on the genes that make bacterial strains resistant to antibiotics, able to cause infection and colonise and transmit within and beyond their host population. Despite the potential of GWAS to characterise the genetic determinants of bacterial phenotypes, its wider adoption is hindered by limited expertise and lack of methodologies suitable to bacterial genomes.
Francesc wants to develop robust GWAS designs suitable for bacterial genomes and provide practical guidelines for future studies. He will evaluate the performance of different GWAS designs using large bacterial collections with available whole-genome sequences (WGS) and antimicrobial resistance phenotypes. He will also develop and release software tools implementing the GWAS methods.
In broad terms, his research interests focus on integrating whole-genome sequences from bacterial strains with other types of data - epidemiological, clinical and phenotypic - to glean biological insights in the area of clinical bacteriology.