Publications

Antibiotic resistance determination using Enterococcus faecium whole-genome sequences: a diagnostic accuracy study using genotypic and phenotypic data

Published in The Lancet Microbe, 2024

This work represents the largest evaluation to date on the accuracy of antibiotic resistance predictions from E. faecium genomes, using a dataset of 4,382 genomes with available culture-based AST phenotypes. I curated a catalogue of 228 genetic markers involved in resistance to 12 different antibiotics in E. faecium, and developed a bioinformatics pipeline to predict antibiotic resistance from E. faecium genomes, with important improvements in the accuracy of predictions. Given the mortality burden of antibiotic-resistant E. faecium and the increasingly routine use of WGS in clinical microbiology labs, these results and resources will facilitate the adoption of WGS as a tool for the diagnosis and surveillance of AMR in E. faecium.

Recommended citation: Coll F, Gouliouris T, Blane B, et al. Antibiotic resistance determination using Enterococcus faecium whole-genome sequences: a diagnostic accuracy study using genotypic and phenotypic data. January 11, 2024. The Lancet Microbe. DOI: 10.1016/S2666-5247(23)00297-5 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4345808

The mutational landscape of Staphylococcus aureus during colonisation

Published in bioRxiv, 2023

This study provides the most comprehensive picture to date on the heterogeneity of adaptive genetic changes that occur in S. aureus during colonisation, revealing the importance of specific nitrogen metabolic adaption, loss of quorum sensing and antibiotic resistance for successful human colonisation. Here I analysed a dataset of 7,150 S. aureus colonisation isolates from 1,593 subjects and identified novel adaptive variation that warrant further characterisation.

Recommended citation: Coll F, Blane B, Bellis K, et al. The mutational landscape of Staphylococcus aureus during colonisation. bioRxiv. 2023 https://www.biorxiv.org/content/10.1101/2023.12.08.570284v1

PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies

Published in Communications Biology, 2022

Genome-wide association studies (GWAS) have been used to investigate the genetic basis of bacterial traits but approaches to perform power calculations for bacterial GWAS are limited. Here I implemented two alternative approaches to conduct power calculations using existing collections of bacterial genomes. I designed the analytical approach, implemented the computational pipeline (including code in Python, Docker and Nextflow) and run all in silico experiments.

Recommended citation: Coll F, Gouliouris T, Bruchmann S, et al. PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies. Communications Biology. 2022;5(1):266. doi:10.1038/s42003-022-03194-2 https://www.nature.com/articles/s42003-022-03194-2

Key variables affecting genetic distance calculations in genomic epidemiology

Published in The Lancet Microbe, 2021

Here I was invited by to The Lancet Microbe comment on the approaches available to determine genetic distances from bacterial genomic data in the context of genomic surveillance studies.

Recommended citation: Coll F. Key variables affecting genetic distance calculations in genomic epidemiology. The Lancet Microbe. 2021;5247(21):6-7. doi:10.1016/S2666-5247(21)00183-X https://www.thelancet.com/journals/lanmic/article/PIIS2666-5247(21)00183-X/fulltext

Quantifying acquisition and transmission of Enterococcus faecium using genomic surveillance

Published in Nature Microbiology, 2021

This was a prospective surveillance study in haematology patients admitted to a hospital in England. We showed that carriage and environmental contamination by antibiotic resistant E. faecium was hyperendemic in this population and showed high hospital acquisition rates. We also showed that invasive E. faecium infections originated from patients’ own gut-colonizing strain. I conducted the genomic and epidemiological analyses and led the interpretation and writing of the results. The bioinformatics approaches developed could inform the future translation of E. faecium sequencing into routine outbreak detection and investigation.

Recommended citation: Gouliouris T, Coll F, Ludden C, et al. Quantifying acquisition and transmission of Enterococcus faecium using genomic surveillance. Nature Microbiology. 2020;6(1):103-111. doi:10.1038/s41564-020-00806-7 https://www.nature.com/articles/s41564-020-00806-7

Definition of a genetic relatedness cutoff to exclude recent transmission of meticillin-resistant Staphylococcus aureus: a genomic epidemiology analysis

Published in The Lancet Microbe, 2020

Here I proposed a genetic relatedness cut-off above which transmission of methicillin-resistant Staphylococcus aureus (MRSA) can be ruled out, in the context of prospective genomic surveillance. The methodological approaches proposed here could be applied to calculate equivalent relatedness cut-offs for other bacterial pathogens.

Recommended citation: Coll F, Raven KE, Knight GM, et al. Definition of a genetic relatedness cutoff to exclude recent transmission of meticillin-resistant Staphylococcus aureus: a genomic epidemiology analysis. The Lancet Microbe. 2020;1(8):e328-e335. doi:10.1016/S2666-5247(20)30149-X https://www.thelancet.com/journals/lanmic/article/PIIS2666-5247(20)30149-X/fulltext

Feasibility of informing syndrome-level empiric antibiotic recommendations using publicly available antibiotic resistance datasets

Published in Wellcome Open Research, 2020

We developed an interactive web app that uses public AMR surveillance data to inform the design of antibiotic empiric therapies.

Recommended citation: Leclerc QJ, Naylor NR, Aiken AM, Coll F#, Knight GM#. Feasibility of informing syndrome-level empiric antibiotic recommendations using publicly available antibiotic resistance datasets. Wellcome Open Research. 2020;4:140. doi:10.12688/wellcomeopenres.15477.2 https://wellcomeopenresearch.org/articles/4-140

Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis

Published in Nature Genetics, 2018

This was one of the largest bacterial GWAS published at the time, where a GWAS approach was applied to a diverse collection of 6,450 M. tuberculosis clinical isolates, from 30 different countries and varying degrees of drug resistances, to uncover novel mutations and epistatic interactions associated with drug resistance

Recommended citation: Coll F, Phelan J, Hill-Cawthorne GA, et al. Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis. Nature Genetics. 2018;50(2):307-316. doi:10.1038/s41588-017-0029-0 https://www.nature.com/articles/s41588-017-0029-0

Longitudinal genomic surveillance of MRSA in the UK reveals transmission patterns in hospitals and the community

Published in Science Translational Medicine , 2017

This was a large prospective surveillance study of all MRSA-positive patients in an entire healthcare network. A total of 2282 MRSA isolates were sequenced from 1465 individuals admitted to three hospitals and multiple primary care practices. The study captured a more typical view of MRSA transmission, attributable to small and multiple clinically unrecognized outbreaks, and had important implications for infection control policy and practice. I designed the analytical approach and conducted all the genomic and epidemiological analyses to reconstructed MRSA outbreaks.

Recommended citation: Coll F, Harrison EM, Toleman MS, et al. Longitudinal genomic surveillance of MRSA in the UK reveals transmission patterns in hospitals and the community. Science Translational Medicine. 2017;9(413):eaak9745. doi:10.1126/scitranslmed.aak9745 https://www.science.org/doi/10.1126/scitranslmed.aak9745

Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences

Published in Genome Medicine, 2015

The goal of this study was to assess the diagnostic accuracy of genomic sequencing to predict antibiotic resistance in Mycobacterium tuberculosis. We developed a software tool called TB-Profiler to determine antibiotic resistance directly from raw genomic sequences, which has been widely adopted and used in the field

Recommended citation: Coll F, McNerney R, Preston MD, et al. Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences. Genome Medicine. 2015;7(1):51. doi:10.1186/s13073-015-0164-0 https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-015-0164-0

A robust SNP barcode for typing Mycobacterium tuberculosis complex strains

Published in Nature Communications, 2014

Here I proposed the use of single nucleotide polymorphisms (SNPs) to accurately genotype and discriminate all lineages and sub-lineages of the Mycobacterium tuberculosis complex (MTBC), applying phylogenetic and population genetics methods to a collection of more than 1,500 genomes. This new system has become the preferred, most adopted and cited system in the field for MTBC genotyping.

Recommended citation: Coll F, McNerney R, Guerra-Assunção JA, et al. A robust SNP barcode for typing Mycobacterium tuberculosis complex strains. Nature Communications. 2014;5(1):4812. doi:10.1038/ncomms5812 https://www.nature.com/articles/ncomms5812

PolyTB: A genomic variation map for Mycobacterium tuberculosis

Published in Tuberculosis, 2014

We have developed the PolyTB web-based tool to visualise the resulting variation and important meta-data (e.g. in silico inferred strain-types, location) within geographical map and phylogenetic views.

Recommended citation: Coll F, Preston M, Guerra-Assunção JA, et al. PolyTB: A genomic variation map for Mycobacterium tuberculosis. Tuberculosis. 2014;94(3):346-354. doi:10.1016/j.tube.2014.02.005 https://www.sciencedirect.com/science/article/pii/S1472979214203428

SpolPred: rapid and accurate prediction of Mycobacterium tuberculosis spoligotypes from short genomic sequences

Published in Bioinformatics, 2012

In silico genotyping approaches are required to bridge the gap between experimental and high-throughput sequencing, leading to the development of SpolPred, a software tool to predict the spoligotype from Mycobacterium tuberculosis raw sequence reads.

Recommended citation: Coll F, Mallard K, Preston MD, et al. SpolPred: rapid and accurate prediction of Mycobacterium tuberculosis spoligotypes from short genomic sequences. Bioinformatics. 2012;28(22):2991-2993. doi:10.1093/bioinformatics/bts544 https://academic.oup.com/bioinformatics/article/28/22/2991/240583?login=false

Francesc Coll

Publications