APPLIED MICROBIAL GENOMICS

Description

At the Applied Microbial Genomics Unit, we work on the applications of whole-genome sequencing as a research, surveillance, and diagnostics tool for bacterial infections. We employ advanced population-genomics approaches to characterise the genetic basis of bacterial phenotypes and adaptation, with a particular focus on antibiotic resistance, and use genomic surveillance approaches to study the epidemiology of bacterial pathogens. We also work in the development of bioinformatics pipelines and standards for the analysis and interpretation of bacterial genomic data, and in the identification of genetic markers for surveillance and diagnosis of bacterial pathogens and antibiotic resistance. We work collaboratively with molecular bacteriologists, laboratory scientists, infectious diseases clinicians, public health labs and other microbial genomics groups to deliver our research projects.

We have expertise and work on the following methodological and research areas:

1. Application of Genome-Wide Association Studies (GWAS) to bacterial populations.
2. Evolution and adaptation of bacterial pathogens and commensals.
3. Prediction of antibiotic resistance from bacterial genome sequences.
4. Acquisition, evolution, and transmission of antibiotic resistance.
5. Bioinformatics pipelines and standards for analysis and interpretation of bacterial genomic data.
6. Genomic epidemiology of bacterial pathogens.

Personal

Last publications

Coll F, Blane B, Bellis K, Matuszewska M, Toleman M, Geoghegan JA, Parkhill J, Massey RC, Peacock SJ, Harrison EM.
The mutational landscape of Staphylococcus aureus during colonisation.
bioRxiv. 2023.

Coll F, Gouliouris T, Blane B, Yeats CA, Raven KE, Ludden C, Khokhar FA, Wilson HJ, Roberts LW, Harrison EM, Horner CS, Le TH, Nguyen TH, Nguyen VT, Brown NM, Holmes MA, Parkhill J, Estee Török M, Peacock SJ.
Antibiotc resistance determination using Enterococcus faecium whole-genome sequences: a diagnostic accuracy study using genotypic and phenotypic data.
Lancet Microbe. 2024 Feb;5(2):e151-e163. doi: 10.1016/S2666-5247(23)00297-5. Epub 2024 Jan 11. PMID: 38219758.

Coll F.
Key variables affecting genetic distance calculations in genomic epidemiology. Lancet Microbe.
2021 Oct;2(10):e486-e487. doi: 10.1016/S2666-5247(21)00183-X. Epub 2021 Aug 6. PMID: 35544172.

Coll F, Gouliouris T, Bruchmann S, Phelan J, Raven KE, Clark TG, Parkhill J, Peacock SJ.
PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies.
Commun Biol. 2022 Mar 25;5(1):266. doi: 10.1038/s42003-022-03194-2. PMID: 35338232; PMCID: PMC8956664.

Coll F, Raven KE, Knight GM, Blane B, Harrison EM, Leek D, Enoch DA, Brown NM, Parkhill J, Peacock SJ.
Definition of a genetic relatedness cutoff to exclude recent transmission of meticillin-resistant <i>Staphylococcus aureus</i>: a genomic epidemiology analysis.
Lancet Microbe. 2020 Dec;1(8):e328-e335. doi: 10.1016/S2666-5247(20)30149-X. PMID: 33313577; PMCID: PMC7721685.

Gouliouris T, Coll F, Ludden C, Blane B, Raven KE, Naydenova P, Crawley C, Török ME, Enoch DA, Brown NM, Harrison EM, Parkhill J, Peacock S
Quantifying acquisition and transmission of Enterococcus faecium using genomic surveillance.
Nat Microbiol. 2021 Jan;6(1):103-111. doi: 10.1038/s41564-020-00806-7. Epub 2020 Oct 26. PMID: 33106672; PMCID: PMC7610418.

Coll F, Phelan J, Hill-Cawthorne GA, Nair MB, Mallard K, Ali S, Abdallah AM, Alghamdi S, Alsomali M, Ahmed AO, Portelli S, Oppong Y, Alves A, Bessa TB, Campino S, Caws M, Chatterjee A, Crampin AC, Dheda K, Furnham N, Glynn JR, Grandjean L, Minh Ha D, Hasan R, Hasan Z, Hibberd ML, Joloba M, Jones-Lópe EC, Matsumoto T, Miranda A, Moore DJ, Mocillo N, Panaiotov S, Parkhill J, Penha C, Perdigão J, Portugal I, Rchiad Z, Robledo J, Sheen P, Shesha NT Sirgel FA, Sola C, Oliveira Sousa E, Streicher EM, Helden PV, Viveiros M, Warren RM, McNerney R, Pain A, Clark TG.
Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis.
Nat Genet. 2018 Feb;50(2):307-316. doi: 10.1038/s41588-017-0029-0. Epub 2018 Jan 22. Erratum in: Nat Genet. 2018 Apr 19;: PMID: 29358649.

Coll F, Harrison EM, Toleman MS, Reuter S, Raven KE, Blane B, Palmer B, Kappeler ARM, Brown NM, Török ME, Parkhill J, Peacock SJ.
Longitudin l genomic surveillance of MRSA in the UK reveals transmission patterns in hospitals and the community.
Sci Transl Med. 2017 Oct 25;9(413):eaak9745. doi: 10.1126/scitranslmed.aak9745. Epub 2017 Oct 25. PMID: 29070701; PMCID: PMC5683347.