
Yr Athro Thomas Connor
Senior Lecturer
- connortr@cardiff.ac.uk
- +44 (0)29 2087 4147
- Cardiff School of Biosciences, Sir Martin Evans Building, Museum Avenue, Cardiff CF10 3AX, Adeilad Syr Martin Evans, Rhodfa'r Amgueddfa, Caerdydd, CF10 3AX
- Sylwebydd y cyfryngau
- Ar gael fel goruchwyliwr ôl-raddedig
Trosolwg
Research overview
Throughout my career to date I have worked on projects featuring a wide array of organisms. This is principally because rather than being focused on examining a particular organism, my research is based in the first instance around the fundamental narratives of pathogen evolution. The processes that underpin the diversity we see in the microbial world are often the same whatever species we look at; although the results they produce can be markedly different.
My research is made possible by a combination of technologies that enable us to explore organisms at a resolution that has never before been possible. Firstly, whole genome sequencing, combined with high quality metatdata provides the datasets that we can use to derive the answers to the questions that we seek. Secondly, using computational and mathematical approaches, we are able to make sense of the "Big Data" challenge that is posed by the large, rich datasets that we produce.
Research within my group is therefore characterised by developing and applying population genomics, comparative genomics, and phylogenetics to elucidate the natural histories of microbial pathogens. In a number of cases we have developed tools or approaches to analyse our data. However, in all cases we start first with the biological questions, and then develop the approaches to answer our question. So it could be said that while what we do is broadly Bioinformatics, the research focus is on the Biology first, and the informatics provides the tools to unlock the data that we produce.
Cyhoeddiadau
2021
- Volz, E.et al. 2021. Evaluating the effects of SARS-CoV-2 Spike mutation D614G on transmissibility and pathogenicity. Cell 184(1), pp. 64-75.e11. (10.1016/j.cell.2020.11.020)
- Jones, C.et al. 2021. Kill and cure: genomic phylogeny and bioactivity of Burkholderia gladioli bacteria capable of pathogenic and beneficial lifestyles. Microbial Genomics 17(1), article number: 515. (10.1099/mgen.0.000515)
2020
- Lyons, J.et al. 2020. Understanding and responding to COVID-19 in Wales: protocol for a privacy protecting data platform for enhanced epidemiology and evaluation of interventions. BMJ Open 10(10), article number: e043010. (10.1136/bmjopen-2020-043010)
- Mullins, A. J.et al. 2020. Genomic assemblies of members of Burkholderia and related genera as a resource for natural product discovery. Microbiology Resource Announcements 9, article number: e00485-20. (10.1128/MRA.00485-20)
- Crickmore, N.et al. 2020. A structure-based nomenclature for Bacillus thuringiensis and other bacteria-derived pesticidal proteins. Journal of Invertebrate Pathology, article number: 107438. (10.1016/j.jip.2020.107438)
- Millar, J. R.et al. 2020. High-frequency failure of combination antiretroviral therapy in paediatric HIV infection is associated with unmet maternal needs causing maternal non-adherence. EClinicalMedicine 22, article number: 100344. (10.1016/j.eclinm.2020.100344)
- Southgate, J.et al. 2020. Influenza classification from short reads with VAPOR facilitates robust mapping pipelines and zoonotic strain detection for routine surveillance applications. Bioinformatics 36(6), pp. 1681-1688. (10.1093/bioinformatics/btz814)
- Cunningham-Oakes, E.et al. 2020. Genome sequence of pluralibacter gergoviae ECO77, a unique multireplicon isolate of industrial origin. Microbiology Resource Announcements 9(9), article number: e01561-19. (10.1128/MRA.01561-19)
- Bush, S. J.et al. 2020. Evaluation of methods for detecting human reads in microbial sequencing datasets. Microbial Genomics 6(7), pp. 5-18. (10.1099/mgen.0.000393)
2019
- Webster, G.et al. 2019. Genome sequences of three Paraburkholderia spp. strains isolated from Wood-decay fungi reveals them as novel taxa with antimicrobial biosynthetic potential. Microbiology Resource Announcements 8(34), article number: e00778-19. (10.1128/MRA.00778-19)
- Mullins, A. J.et al. 2019. Genome mining identifies cepacin as a plant-protective metabolite of the biopesticidal bacterium Burkholderia ambifaria. Nature Microbiology 4, pp. 996-1005. (10.1038/s41564-019-0383-z)
- Weiser, R.et al. 2019. Not all Pseudomonas aeruginosa are equal: strains from industrial sources possess uniquely large multireplicon genomes. Microbial Genomics, article number: 276. (10.1099/mgen.0.000276)
2018
- Green, A.et al. 2018. The consistent differential expression of genetic pathways following exposure of an industrial Pseudomonas aeruginosa strain to preservatives and a laundry detergent formulation. FEMS Microbiology Letters 365(9), article number: fny062. (10.1093/femsle/fny062)
- Rius, C.et al. 2018. Peptide-MHC class 1 tetramers can fail to detect relevant functional T cell clonotypes and underestimate antigen-reactive T cell populations. Journal of Immunology 200(7), pp. 2263-2279. (10.4049/jimmunol.1700242)
- Knetsch, C. W.et al. 2018. Zoonotic transfer of clostridium difficile harboring antimicrobial resistance between farm animals and humans. Journal of Clinical Microbiology 56(3), article number: e01384-17. (10.1128/JCM.01384-17)
2017
- Baker, K.et al. 2017. Whole genome sequencing of Shigella sonnei through PulseNet Latin America and Caribbean: advancing global surveillance of foodborne illnesses. Clinical Microbiology and Infection 23(11), pp. 845-853. (10.1016/j.cmi.2017.03.021)
2016
- Pollard, D. J.et al. 2016. The Type III secretion system effector SeoC of salmonella enterica subsp. salamae and S. enterica subsp. arizonae ADP-Ribosylates Src and Inhibits Opsonophagocytosis. Infection and Immunity 84(12), pp. 3618-3628. (10.1128/IAI.00704-16)
- Connor, T. R.et al. 2016. CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community. Microbial Genomics 2(9), article number: 86. (10.1099/mgen.0.000086)
- Ryan, E. T.et al. 2016. Retrospective analysis of serotype switching of Vibrio cholerae O1 in a cholera endemic region Shows it is a non-random process. PLOS Neglected Tropical Diseases 10(10), article number: e0005044. (10.1371/journal.pntd.0005044)
- Wong, V. K.et al. 2016. An extended genotyping framework for Salmonella enterica serovar Typhi, the cause of human typhoid. Nature Communications 7, pp. -., article number: 12827. (10.1038/ncomms12827)
- International Typhoid Consortium, .et al. 2016. Molecular surveillance identifies multiple transmissions of typhoid in West Africa. PLOS Neglected Tropical Diseases 10(9), article number: e0004781. (10.1371/journal.pntd.0004781)
- Baker, K. S.et al. 2016. Travel- and community-based transmission of multidrug-resistant Shigella sonnei lineage among international Orthodox Jewish communities. Emerging Infectious Diseases 22(9), pp. 1545. (10.3201/eid2209.151953)
- Connor, T.et al. 2016. What's in a name? Species wide whole genome sequencing resolves invasive and non-invasive Salmonella Paratyphi B. mBio 7(4), article number: e00527-16. (10.1128/mBio.00527-16)
- Laugel, B.et al. 2016. Engineering of isogenic cells deficient for MR1 with a CRISPR/Cas9 lentiviral system: tools to study microbial antigen processing and presentation to human MR1-restricted T cells. Journal of Immunology 197(3), pp. 971-982. (10.4049/jimmunol.1501402)
- Petrovska, L.et al. 2016. Microevolution of Monophasic Salmonella Typhimurium during epidemic, United Kingdom, 2005-2010. Emerging infectious diseases 22(4), article number: 617. (10.3201/eid2204.150531)
2015
- Connor, T. R.et al. 2015. Species-wide whole genome sequencing reveals historical global spread and recent local persistence in Shigella flexneri. eLife 4, article number: e07335. (10.7554/eLife.07335)
- Baker, K. S.et al. 2015. Intercontinental dissemination of azithromycin-resistant shigellosis through sexual transmission: a cross-sectional study. The Lancet Infectious Diseases 15(8), pp. 913-921. (10.1016/S1473-3099(15)00002-X)
- Holt, K. E.et al. 2015. Genomic analysis of diversity, population structure, virulence, and antimicrobial resistance inKlebsiella pneumoniae, an urgent threat to public health. Proceedings of the National Academy of Sciences of the United States of America 112(27), pp. E3574-E3581. (10.1073/pnas.1501049112)
- Okoro, C. K.et al. 2015. Correction: Signatures of adaptation in human invasive Salmonella Typhimurium ST313 populations from Sub-Saharan Africa. PLOS Neglected Tropical Diseases 9(6), article number: e0003848. (10.1371/journal.pntd.0003848)
- Okoro, C. K.et al. 2015. Signatures of adaptation in human invasive Salmonella Typhimurium ST313 populations from Sub-Saharan Africa. PLOS Neglected Tropical Diseases 9(3), article number: e0003611. (10.1371/journal.pntd.0003611)
- Vehkala, M.et al. 2015. Novel R pipeline for analyzing biolog phenotypic microarray data. PLoS ONE 10(3), article number: e0118392. (10.1371/journal.pone.0118392)
- Croucher, N. J.et al. 2015. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Research 43(3), article number: e15. (10.1093/nar/gku1196)
- Jones, L. S.et al. 2015. Characterization of plasmids in extensively drug-resistant acinetobacter strains isolated in India and Pakistan. Antimicrobial Agents and Chemotherapy 59(2), pp. 923-929. (10.1128/AAC.03242-14)
- Langridge, G. C.et al. 2015. Patterns of genome evolution that have accompanied host adaptation in Salmonella. Proceedings of the National Academy of Sciences 112(3), pp. 863-868. (10.1073/pnas.1416707112)
- Hall, M.et al. 2015. Use of whole-genus genome sequence data to develop a multilocus sequence typing tool that accurately identifies Yersinia isolates to the species and subspecies levels. Journal of Clinical Microbiology 53(1), pp. 35-42. (10.1128/JCM.02395-14)
- Connor, T. R. and Southgate, J. 2015. Automated cloud brokerage based upon continuous real-time benchmarking. Presented at: 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, Limassol, Cyprus, 7 - 0 December 2015.
2014
- von Mentzer, A.et al. 2014. Identification of enterotoxigenic Escherichia coli (ETEC) clades with long-term global distribution. Nature Genetics 46(12), pp. 1321-1326. (10.1038/ng.3145)
- Knetsch, C. W.et al. 2014. Whole genome sequencing reveals potential spread of Clostridium difficile between humans and farm animals in the Netherlands, 2002 to 2011. Eurosurveillance 19(45), article number: 20954.
- Lamelas, A.et al. 2014. Emergence of a new epidemic Neisseria meningitidis serogroup A clone in the African meningitis belt: high-resolution picture of genomic changes that mediate immune evasion. mBio 5(5), pp. e01974-14. (10.1128/mBio.01974-14)
- Reuter, S.et al. 2014. Parallel independent evolution of pathogenicity within the genus Yersinia. Proceedings of the National Academy of Sciences 111(18), pp. 6768-6773. (10.1073/pnas.1317161111)
- Sheppard, S. K.et al. 2014. Cryptic ecology among host generalist Campylobacter jejuniin domestic animals. Molecular Ecology 23(10), pp. 2442-2451. (10.1111/mec.12742)
2013
- Shepheard, M. A.et al. 2013. Historical zoonoses and other changes in host tropism of staphylococcus aureus, identified by phylogenetic analysis of a population dataset. PLoS ONE 8(5), article number: e62369. (10.1371/journal.pone.0062369)
- Cheng, L.et al. 2013. Hierarchical and spatially explicit clustering of DNA sequences with BAPS software. Molecular Biology and Evolution 30(5), pp. 1224-1228. (10.1093/molbev/mst028)
- Dziva, F.et al. 2013. Sequencing and functional annotation of avian pathogenic Escherichia coli serogroup O78 strains reveal the evolution of E. coli lineages pathogenic for poultry via distinct mechanisms. Infection and Immunity 81(3), pp. 838-849. (10.1128/IAI.00585-12)
- McDonnell, J.et al. 2013. Retrospective analysis of whole genome sequencing compared to prospective typing data in further informing the epidemiological investigation of an outbreak of Shigella sonnei in the UK. Epidemiology and Infection 141(12), pp. 2568-2575. (10.1017/S0950268813000137)
- Kingsley, R. A.et al. 2013. Genome and transcriptome adaptation accompanying emergence of the definitive type 2 host-restricted Salmonella enterica serovar Typhimurium pathovar. mBio 4(5), pp. e00565-13. (10.1128/mBio.00565-13)
- Mather, A. E.et al. 2013. Distinguishable epidemics of multidrug-resistant Salmonella Typhimurium DT104 in different hosts. Science 341(6153), pp. 1514-1517. (10.1126/science.1240578)
2012
- He, M.et al. 2012. Emergence and global spread of epidemic healthcare-associated Clostridium difficile [Letter]. Nature Genetics 45(1), pp. 109-113. (10.1038/ng.2478)
- Okoro, C. K.et al. 2012. Intracontinental spread of human invasive Salmonella Typhimurium pathovariants in sub-Saharan Africa. Nature Genetics 44(11), pp. 1215-1221. (10.1038/ng.2423)
- Lawley, T. D.et al. 2012. Targeted restoration of the intestinal microbiota with a simple, defined bacteriotherapy resolves relapsing clostridium difficile disease in mice. PLoS Pathogens 8(10), article number: e1002995. (10.1371/journal.ppat.1002995)
- Quail, M.et al. 2012. A tale of three next generation sequencing platforms: comparison of Ion torrent, pacific biosciences and illumina MiSeq sequencers. BMC Genomics 13(1), article number: 341. (10.1186/1471-2164-13-341)
- Corander, J.et al. 2012. Population structure in the Neisseria, and the biological significance of fuzzy species. Journal of The Royal Society Interface 9(71), pp. 1208-1215. (10.1098/rsif.2011.0601)
- Murchison, E.et al. 2012. Genome sequencing and analysis of the Tasmanian Devil and its transmissible cancer. Cell 148(4), pp. 780-791. (10.1016/j.cell.2011.11.065)
- Connor, T. R., Corander, J. and Hanage, W. P. 2012. Population subdivision and the detection of recombination in non-typable Haemophilus influenzae. Microbiology 158(12), pp. 2958-2964. (10.1099/mic.0.063073-0)
2011
- Marttinen, P.et al. 2011. Detection of recombination events in bacterial genomes from large population samples. Nucleic Acids Research 40(1), article number: e6. (10.1093/nar/gkr928)
- Mutreja, A.et al. 2011. Evidence for several waves of global transmission in the seventh cholera pandemic [Letter]. Nature 477(7365), pp. 462-465. (10.1038/nature10392)
- Fookes, M.et al. 2011. Salmonella bongori provides insights into the evolution of the Salmonellae. PLoS Pathogens 7(8), article number: e1002191. (10.1371/journal.ppat.1002191)
- Cheng, L.et al. 2011. Bayesian semi-supervised classification of bacterial samples using MLST databases. BioMed Central Bioinformatics 12(1), article number: 302. (10.1186/1471-2105-12-302)
2009
- Hanage, W. P.et al. 2009. Hyper-recombination, diversity, and antibiotic resistance in pneumococcus. Science 324(5933), pp. 1454-1457. (10.1126/science.1171908)
2007
- Turner, K. M. E.et al. 2007. Assessing the reliability of eBURST using simulated populations with known ancestry. BMC Microbiology 7(1), pp. 30-43. (10.1186/1471-2180-7-30)
Population and Comparative Genomics
Whole genome sequences provide us with the complete blueprint for the organisms that we are investigating. To understand our organisms of interest, we consider how their genomes vary between organisms (comparative genomics) and how they have changed/evolved over time (population genomics).
Unlike eukaryotic organisms, bacteria have highly variable genomes; they can gain and loose genes at a very high frequency, and members of the same named species may have fewer than half of their genes in common. This genomic plasticity is hugely important, as the genes that vary between strains are often the genes that are associated with characteristics of interest – such as virulence or antimicrobial resistance. Using whole genome sequence data we perform comparative genomics to:
- work out how pathogens are related, in terms of the gene content they share
- work out how they vary in their gene content
- work out how their genetic variation relates to differences in their phenotype (basically their behaviour – such as the seriousness of disease that they cause)
We complement comparative genomics with phylogenetics, which enables us to determine the relationships between isolates, and by integrating the results from these in silico analyses with phenotypic data produced from in vitro and in vivo experimental work, we are able to derive a better understanding of how, and why our organisms of interest cause disease.
While the comparative genomics work is focused on examining the similarities and differences between organisms, and how this relates to the phenotype of organisms, we supplement this by performing population genetic analyses to identify structure within the population, and to infer the recent evolutionary history of strains of interest. This work has been underpinned by a strong, longstanding collaboration with Professor Jukka Corander of the University of Helsinki, with whom I have developed a number of population genetic approaches to analyse bacterial genome-scale datasets (Cheng et al. 2011, Cheng et al. 2013, Marttinen et al. 2012).
I have developed considerable expertise using these approaches and to date I have applied these approaches to datasets including those comprising Vibrio cholerae (Mutreja et al. 2011), Salmonella Typhimurium (Mather et al. 2013, Okoro et al. 2012) and Clostridium difficile (He et al. 2013). In these cases, using a population genetic framework called BEAST, we reconstructed the evolutionary history of these organisms not in evolutionary time, but in human-understandable calendar units – years/days. Using this data I have been able to contribute significantly to answering key questions about how, and when outbreaks have begun, as well as being able to identify key events in the evolution of the pathogens of interest.
Phylogeography
Bacteria do not respect borders; and local outbreaks can, and sadly sometimes do, lead to global epidemics. By combining population genomic approaches with excellent metadata, we are able to move beyond simple dated phylogenies towards a greater understanding of how bacteria move in time and space. I have worked extensively in projects that have examined the phylogeography of bacterial pathogens such as Vibrio cholerae, Salmonella Typhimurium and Clostridium difficile, deploying approaches to combine strain metadata and genomic information to derive insight into how and when pathogens of interest have spread around the world.
References
Cheng L, Connor T R, Aanensen D M, Spratt B G and Corander J (2011) Bayesian semi-supervised classification of bacterial samples using MLST databases. BMC Bioinformatics 12 302.
Cheng L, Connor T R, Siren J, Aanensen D M and Corander J (2013) Hierarchical and spatially explicit clustering of DNA sequences with BAPS software. Mol Biol Evol 30 (5) 1224-1228.
Dziva F, Hauser H*, Connor T R*, van Diemen P M, Prescott G, Langridge G C, Eckert S, Chaudhuri R R, Ewers C, Mellata M, Mukhopadhyay S, Curtiss R, 3rd, Dougan G, Wieler L H, Thomson N R, Pickard D J and Stevens M P (2013) Sequencing and functional annotation of avian pathogenic Escherichia coli serogroup O78 strains reveal the evolution of E. coli lineages pathogenic for poultry via distinct mechanisms. Infect Immun 81 (3) 838-849.
Fookes M, Schroeder G N, Langridge G C, Blondel C J, Mammina C, Connor T R, Seth-Smith H, Vernikos G S, Robinson K S, Sanders M, Petty N K, Kingsley R A, Baumler A J, Nuccio S P, Contreras I, Santiviago C A, Maskell D, Barrow P, Humphrey T, Nastasi A, Roberts M, Frankel G, Parkhill J, Dougan G and Thomson N R (2011) Salmonella bongori provides insights into the evolution of the Salmonellae. PLoS Pathog 7 (8) e1002191.
He M, Miyajima F, Roberts P, Ellison L, Pickard D J, Martin M J, Connor T R, Harris S R, Fairley D, Bamford K B, D'Arc S, Brazier J, Brown D, Coia J E, Douce G, Gerding D, Kim H J, Koh T H, Kato H, Senoh M, Louie T, Michell S, Butt E, Peacock S J, Brown N M, Riley T, Songer G, Wilcox M, Pirmohamed M, Kuijper E, Hawkey P, Wren B W, Dougan G, Parkhill J and Lawley T D (2013) Emergence and global spread of epidemic healthcare-associated Clostridium difficile. Nat Genet 45 (1) 109-113.
Marttinen P, Hanage W P, Croucher N J, Connor T R, Harris S R, Bentley S D and Corander J (2012) Detection of recombination events in bacterial genomes from large population samples. Nucleic Acids Res 40 (1) e6.
Mather A E, Reid S W, Maskell D J, Parkhill J, Fookes M C, Harris S R, Brown D J, Coia J E, Mulvey M R, Gilmour M W, Petrovska L, de Pinna E, Kuroda M, Akiba M, Izumiya H, Connor T R, Suchard M A, Lemey P, Mellor D J, Haydon D T and Thomson N R (2013) Distinguishable epidemics of multidrug-resistant Salmonella Typhimurium DT104 in different hosts. Science 341 (6153) 1514-1517.
Mutreja A, Kim D W, Thomson N R, Connor T R, Lee J H, Kariuki S, Croucher N J, Choi S Y, Harris S R, Lebens M, Niyogi S K, Kim E J, Ramamurthy T, Chun J, Wood J L, Clemens J D, Czerkinsky C, Nair G B, Holmgren J, Parkhill J and Dougan G (2011) Evidence for several waves of global transmission in the seventh cholera pandemic. Nature 477 (7365) 462-465.
Okoro C K, Kingsley R A, Connor T R, Harris S R, Parry C M, Al-Mashhadani M N, Kariuki S, Msefula C L, Gordon M A, de Pinna E, Wain J, Heyderman R S, Obaro S, Alonso P L, Mandomando I, MacLennan C A, Tapia M D, Levine M M, Tennant S M, Parkhill J and Dougan G (2012) Intracontinental spread of human invasive Salmonella Typhimurium pathovariants in sub-Saharan Africa. Nat Genet 44 (11) 1215-1221.