Publications
We maintain an update list of our publications below.
Members of the group have their name in bold.
Preprints under review
- Parker MJ, Hopkins KMV, Chau KK, Cregan J, Oakley S, Barrett L, Jeffery K, Butcher L, Paulus S, Young BC, Eyre DW, Fowler PW, Stoesser N, Sanderson ND, Bejon P (2026).
Genomic epidemiology of multi-modal ESBL gene transmission among Enterobacterales in a neonatal unit.
medRxiv preprint doi:10.64898/2026.07.03.26357218
- Colpus M, Baker CS, Roghi E, Hong HN, Trieu PP, Thub DDA, Hall A, Fowler PW, Walker TM, Spies R, Webster H, Westhead J, Thai H, Turner RD, Peto TEA, Quang NL, Thuong NTT, Omar SV, Crook DW (2026).
Long-read sequencing of Mycobacterial tuberculosis is comparable to short-read sequencing for antimicrobial resistance prediction and epidemiological studies.
bioRxiv preprint doi:10.64898/2026.04.08.717216
- Constantinides B, Webster H, Gentry J, Bastable J, Dunn L, Oakley S, Swann J, Sanderson N, Fowler PW, Peto TEA, Stoesser N, Street T, Crook DW (2021).
Rapid turnaround multiplex sequencing of SARS-CoV-2: comparing tiling amplicon protocol performance.
medRxiv preprint doi:10.1101/2021.12.28.21268461
2026
- Adlard D, Malone KM, Westhead J, Hunt M, Thai H, Colpus M, Turner RD, Omar SV, Eyre DW, Ismail N, Walker TM, Peto TEA, Crook DW, Iqbal Z, Fowler PW (2026).
Rapidly and reproducibly building a comprehensive catalogue of resistance-associated variants for M. tuberculosis.
accepted for publication in Lancet Microbe
bioRxiv preprint doi:10.1101/2025.10.02.679941
- Holt KE, Berends MS, Chindelevitch L, Couto N, Duncan DB, Dyson ZA, Foster-Nyarko E, Hawkey J, Lees JA, Maguire F, Prasad AB, Baines SL, ESGEM-AMR Working Group (2026).
A call for sharing phenotypic antimicrobial susceptibility data alongside bacterial genome sequence data in public archives.
npj Antimicrob Resist doi:10.1038/s44259-026-00278-5
Zenodo preprint doi:10.1038/s44259-026-00278-5
- Baker CS, Colpus M, Gentry J, Hall A, Roghi E, Webster H, Drummond B, Cooper R, Thai H, Westhead J, Turner R, Peto TEA, Fowler PW, Morgan M, Crook DW (2026).
Validation of an optimized Oxford Nanopore sequencing workflow versus Illumina for mycobacteria from primary MGIT culture.
Microbiology Spectrum doi:10.1128/spectrum.01402-26
bioRxiv preprint doi:10.64898/2026.02.04.703726
- Baranowski C, Cortade DL, Adler B, Bayliss S, Fowler PW, Greenberg D, Hawkey J, Holt K, Huseby D, Muwonge K, Knight-Connoni V, Mistretta M, Reider Apel A, Tobin M, Wonderly Trainor B, Zgurskaya H (2026).
Predicting Quantitative MIC from Whole Genome Sequencing.
Zenodo preprint doi:10.5281/zenodo.21456141
- Dissanayake D, Brunner VM, Adlard D, Morrone J, Fowler PW (2026).
Predicting pyrazinamide resistance in M. tuberculosis using a graph convolutional network.
BMC Microbiology doi:10.1186/s12866-026-04876-1
bioRxiv preprint doi:10.1101/2025.10.28.685176
- Hunt M, Hinrichs A S, Anderson D, Karim L, Dearlove B L, Knaggs J, Constantinides B, Fowler P W, Rodger G, Street T, Lumley S, Webster H, Sanderson T, Ruis C, Kotzen B, de Maio N, Amenga-Etego L N, Amuzu D S Y, Avaro M, Awandare G A, Ayivor-Djanie R, Barkham T, Bashton M, Batty E M, Bediako Y, De Belder D, Benedetti E, Bergthaler A, Boers S A, Campos J, Carr R A A, Chen Y Y C, Cuba F, Dattero M E, Dejnirattisai W, Dilthey A, Duedu K O, Endler L, Engelmann I, Francisco N M, Fuchs J, Gnimpieba E Z, Groc S, Gyamfi J, Heemskerk D, Houwaart T, Hsiao N y, Huska M, Hölzer M, Iranzadeh A, Jarva H, Jeewandara C, Jolly B, Joseph R, Kant R, Ki K K K, Kurkela S, Lappalainen M, Lataretu M, Lemieux J, Liu C, Malavige G N, Mashe T, Mongkolsapaya J, Montes B, Mora J A M, Morang’a C M, Mvula B, Nagarajan N, Nelson A, Ngoi J M, da Paixão J P, Panning M, Poklepovich T, Quashie P K, Ranasinghe D, Russo M, San J E, Sanderson N D, Scaria V, Screaton G, Sessions O M, Sironen T, Sisay A, Smith D, Smura T, Supasa P, Suphavilai C, Swann J, Tegally H, Tegomoh B, Vapalahti O, Walker A, Wilkinson R J, Williamson C, Zair X, IMSSC Laboratory Network Consortium, Biere B, Dürrwald R, Mache C, Oh D Y, Schulze J, Wedde M, Wolff T, Fuchs S, Semmler T, Paraskevopoulou S, Kerber R, Kröger S, Haas W, Bode K, Corman V, Erren M, Finzer P, Grosser R, Haffner M, Hermann B, Kiel C, Krumbholz A, Lorentz T, Meinck K, Nitsche A, Petzold M, Schwanz T, Szabados F, Tewald F, Tiemann C, de Oliveira T, Peto T E, Crook D, Corbett-Detig R, Iqbal Z (2026).
Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny.
Nature Methods doi:10.1038/s41592-025-02947-1
bioRxiv preprint doi:10.1101/2024.04.29.591666
2025
- Westhead J, Baker CS, Brouard M, Colpus M, Constantinides B, Hall A, Knaggs J, Lopes Alves M, Spies R, Thai H, Surrall S, Govender K, Peto TEA, Crook DW, Omar SV, Turner R, Fowler PW (2025).
Characterising the performance of an antibiotic resistance prediction tool, gnomonicus, using a diverse testset of 2,663 Mycobacterium tuberculosis samples.
Microbial Genomics 11:001592 doi:10.1099/mgen.0.001592
bioRxiv preprint doi:10.1101/2024.11.08.622466
- Spies R, Crook DW, Peto TEA, Fowler PW, Turner R, Thai H, Watson J, Walker TM (2025).
Evaluating 12 automated, whole-genome sequencing analysis pipelines for Mycobacterium tuberculosis complex: a comparative study.
Lancet Microbe doi:10.1016/j.lanmic.2025.101210
Lancet SSRN preprint doi:10.2139/ssrn.5064085
- Brunner VM, Fowler PW (2025).
Subpopulations in clinical samples of M. tuberculosis can give rise to rifampicin resistance and shed light on how resistance is acquired.
JAC-Antimicrobial Resistance 7:dlaf175 doi:10.1093/jacamr/dlaf175
bioRxiv preprint doi:10.1101/2025.04.09.647945
- Zhang X, Wan S, Bhati AP, Fowler PW, Coveney PV (2025).
Rapid, accurate and reproducible de novo prediction of resistance to antituberculars.
mSphere e00571 doi:10.1128/msphere.00571-25
Lancet SSRN preprint doi:10.2139/ssrn.5166252
- Vo HAT, Nguyen S, Tran AQT, Nguyen H, Bich HH, Fowler PW, Walker TM, Nguyen TT (2025).
Deep learning-based framework for Mycobacterium tuberculosis bacterial growth detection for antimicrobial susceptibility testing.
Computational and Structural Biotechnology Journal 27:2208 doi:10.1016/j.csbj.2025.05.030
bioRxiv preprint doi:10.1101/2025.02.14.638231
- Adlard D, Joseph L, Webster H, O’Reilly A, Knaggs J, Peto TEA, Crook DW, Omar SV, Fowler PW (2025).
An improved catalogue for whole-genome sequencing prediction of bedaquiline resistance in M. tuberculosis using a reproducible algorithmic approach.
Microbial Genomics 11:001429 doi:10.1099/mgen.0.001429
bioRxiv preprint doi:10.1101/2025.01.30.635633
- Lynch CI, Adlard D, Fowler PW (2025).
Predicting rifampicin resistance in M. tuberculosis using machine learning informed by protein structural and chemical features.
ERJ Open Research 00952 doi:10.1183/23120541.00952-2024
bioRxiv preprint doi:10.1101/2024.08.15.608097
2024
- Farrar A, Feehily C, Turner P, Zagajewski A, Chatzimichail S, Crook D, Andersson M, Oakley S, Barrett L, El Sayyed H, Fowler PW, Nellåker C, Kapanidis AN, Stoesser N (2024).
Infection Inspection: Using the power of citizen science to help with image-based prediction of antibiotic resistance in Escherichia coli treated with ciprofloxacin.
Sci Rep 14:19543 doi:10.1038/s41598-024-69341-3
medRxiv preprint doi:10.1101/2023.12.11.23299807
- The CRyPTIC Consortium (2024).
Quantitative drug susceptibility testing for Mycobacterium tuberculosis using unassembled sequencing data and machine learning.
PLoS Comp Biol doi:10.1371/journal.pcbi.1012260
bioRxiv preprint doi:10.1101/2021.09.14.458035
- Carter JJ, Walker TM, Waker AS, Whitfield M, Morlock GP, Lynch CI, Adlard D, Peto TEA, Posey JE, Crook DW, Fowler PW (2024).
Prediction of pyrazinamide resistance in Mycobacterium tuberculosis using structure-based machine learning approaches.
JAC-Antimicrobial Resistance 6:dlae037 doi:10.1093/jacamr/dlae037
bioRxiv preprint doi:10.1101/518142
- Brunner V, Fowler PW (2024).
Compensatory mutations are associated with increased in vitro growth in resistant clinical samples of Mycobacterium tuberculosis.
mGen 10:001187 doi:10.1099/mgen.0.001187
bioRxiv preprint doi:10.1101/2023.06.21.545231
- The CRyPTIC Consortium (2024).
Quantitative measurement of antibiotic resistance in M. tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach.
Nature Comms 15:488 doi:10.1038/s41467-023-44325-5
bioRxiv preprint doi:10.1101/2021.09.14.460353
2023
- Amoako D, Anh NT, Bastable J, Brouard M, Campano Romero C, Castillo Ramirez A, Constantinides B, Crook DW, Cuong PM, Diagne MM, Diallo A, Dung NT, Dunn L, Duyet LV, Everatt J, Fletcher K, Fowler PW, Gail M, Gentry J, Gharbia S, Hospital for Tropical Diseases SARS-CoV-2 testing team, Hong NTT, Hunt M, Iqbal Z, Jeffery K, Kekana D, Kesteman T, Knaggs J, Lopes Alves M, Man DNH, Mathers AJ, Ngoc MN, Oakley S, Parikh H, Peto TEA, Quan P, Rojas Herrera M, Sanderson N, Sintchenko V, Swann J, Takata J, Tam NT, Tan LV, Thach PN, Top NM, Trang NT, Trang VD, Turner R, van Doorn HR, von Gottberg A, Westhead J, Wolter N, Young BC (2023).
A validated cloud-based genomic platform for co-ordinated, expedient global analysis of SARS-CoV-2 genomic epidemiology.
medRxiv preprint doi:10.1101/2023.11.27.23298986
- Davies TJ, Swann J, Sheppard AE, Pickford H, Lipworth S, AbuOun M, Ellington M, Fowler PW, Hopkins S, Hopkins KL, Crook DW, Peto TEA, Anjum MF, Walker AS, Stoesser N (2023).
Discordance between different bioinformatic methods for identifying resistance genes from short-read genomic data, with a focus on Escherichia coli.
mGen 9:001151 doi:10.1099/mgen.0.001151
bioRxiv preprint doi:10.1101/2021.11.03.467004
- The CRyPTIC Consortium (2023).
Reply: “Epidemiological cut-off values for a 96-well broth microdilution plate for high-throughput research antibiotic susceptibility testing of M. tuberculosis.”.
Eur Resp J 61:2300426 doi:10.1183/13993003.00426-2023
- Brankin AE, Fowler PW (2023).
Inclusion of minor alleles improves catalogue-based prediction of fluoroquinolone resistance in M. tuberculosis.
JAC-Antimicrobial Resistance 5:dlad039 doi:10.1093/jacamr/dlad039
bioRxiv preprint doi:10.1101/2022.11.09.515757
- Dreyer V, Mandal A, Dev P, Merker M, Barilar I, Utpatel C, Nilgiriwala K, Rodrigues K, Crook DW, The CRyPTIC Consortium, Rasigade JP, Wirth T, Mistry N, Niemann S (2023).
High fluoroquinolone resistance proportions among multidrug-resistant tuberculosis driven by dominant L2 Mycobacterium tuberculosis clones in the Mumbai Metropolitan Region.
Genome Med 22:14 doi:10.1186/s13073-022-01076-0
- Sonnenkalb L, Carter JJ, Spitaleri A, Iqbal Z, Hunt M, Malone K, Utpatel C, Cirrillo DM, Rodrigues C, Nilgiriwala KS, the CRyPTIC Consortium, Fowler PW, Merker M, Niemann S (2023).
Deciphering Bedaquiline and Clofazimine Resistance in Tuberculosis: An Evolutionary Medicine Approach.
Lancet Microbe 54:e358 00002 doi:10.1016/S2666-5247(23)00002-2
bioRxiv preprint doi:10.1101/2021.03.19.436148
2022
- Hunt M, Letcher B, Malone KM, Nguyen G, Hall MB, Colquhoun RM, Lima L, Schatz M, Ramakrishnan S, The CRyPTIC Consortium, Iqbal Z (2022).
Minos: variant adjudication and joint genotyping of cohorts of bacterial genomes.
Genome Biology 23:147 doi:10.1186/s13059-022-02714-x
bioRxiv preprint: doi:10.1101/2021.09.15.460475
- The CRyPTIC Consortium (2022).
A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics.
PLoS Biology 20:e3001721 doi:10.1371/journal.pbio.3001721
bioRxiv preprint doi:10.1101/2021.09.14.460274
- The CRyPTIC Consortium (2022).
Genome-wide association studies of global Mycobacterium tuberculosis resistance to thirteen antimicrobials in 10,228 genomes.
PLoS Biology 20:e3001755 doi:10.1371/journal.pbio.3001755
bioRxiv preprint doi:10.1101/2021.09.14.460272
- Brankin AE, Fowler PW (2022).
Predicting antibiotic resistance in complex protein targets using alchemical free energy methods.
J Comp Chem 43:1771 doi:10.1002/jcc.26979
chemRxiv preprint doi:10.26434/chemrxiv-2021-shfgp
- Fowler PW, Wright C, Spiers H, Zhu T, Baeten EML, Hoosdally SW, Gibertoni Cruz AL, Roohi A, Kouchaki S, Walker TM, Peto TEA, Miller G, Lintott C, Clifton D, Crook DW, Walker AS, The CRyPTIC Consortium (2022).
BashTheBug: a crowd of volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates.
eLife 11:e75046 doi:10.7554/eLife.75046
bioRxiv preprint doi:10.1101/2021.07.20.453060
- Hunt M, Swann J, Constantinides B, Fowler PW, Iqbal Z (2022).
ReadItAndKeep: rapid decontamination of SARS-CoV-2 sequencing reads.
Bioinformatics 38:3291 doi:10.1093/bioinformatics/btac311
bioRxiv preprint doi:10.1101/2022.01.21.477194
- World Health Organization (2022).
Optimized broth microdilution plate methodology for drug susceptibility testing of Mycobacterium tuberculosis complex.
- The CRyPTIC Consortium (2022).
Epidemiological cutoff values for a 96-well broth microdilution plate for high-throughput research antibiotic susceptibility testing of M. tuberculosis.
Eur Resp J 60:2200239 doi:10.1183/13993003.00239-2022
medRxiv preprint doi:10.1101/2021.02.24.21252386
- Walker TM, Miotto P, Köser CU, Fowler PW, Knaggs J, Iqbal Z, Hunt M, Chindelevitch L, Farhat M, Cirillo DM, Comas I, Posey JE, Omar SV, Peto TEA, Suresh A, Uplekar S, Laurent S, Colman R, Nathanson CM, Zignol M, Walker AS, the CRyPTIC Consortium, the Seq&Treat Consortium, Crook DW, Ismail N, Rodwell TC (2022).
The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: A new global standard for molecular diagnostics.
Lancet Microbe 3:E265 doi:10.1016/S2666-5247(21)00301-3
Lancet SSRN preprint doi:10.2139/ssrn.3923444
- Yang Y, Walker TM, Kouchaki S, Wang C, Peto TEA, Crook DW, CRYPTIC Consortium, Clifton DA (2022).
An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction.
Briefings in Bioinformatics 22:bbab299 doi:10.1093/bib/bbab299
2021
- Adams O, Deme JC, Parker JL, the CRyPTIC Consortium, Fowler PW, Lea SM, Newstead S (2021).
Cryo-EM Structure and Resistance Landscape of M. tuberculosis MmpL3: An Emergent Therapeutic Target.
Structure 29:1182 doi:10.1016/j.str.2021.06.013
- Ismail NA, Nathanson CM, Korobitsyn A, Zignol M, Kasaeva T, Rodwell T, Miotto P, Walker TM, 2021 66 Fowler PW, Knaggs J, Iqbal Z, Hunt M, Chindelevitch L, Farhat M, Cirillo D, Crook DW, Comas I, Posey J, Vally Omar S, Peto TEA, Walker AS, Suresh A, Uplekar S, Laurent S, Colman R (2021).
Catalogue of mutations in M. tuberculosis complex and their association with drug resistance.
- Lumley SF, Rodger G, Constantinides B, Sanderson N, Chau KK, Street TL, O’Donnell D, Howarth A, Hatch SB, Marsden BD, Cox S, James T, Warren F, Peck LJ, Ritter TG, de Toledo Z, Warren L, Axten D, Cornall RJ, Jones EY, Stuart DI, Screaton G, Ebner D, Hoosdally S, Chand M, Oxford University Hospitals Staff Testing Group, Crook DW, O’Donnell A, Conlon CP, Pouwels KB, Walker AS, Peto TEA, Hopkins S, Walker TM, Stoesser NE, Matthews PC, Jeffery K, Eyre DW (2021).
An observational cohort study on the incidence of SARS-CoV-2 infection and B.1.1.7 variant infection in healthcare workers by antibody and vaccination status.
Clin Infec Dis 74:1208 doi:10.1093/cid/ciab608
medRxiv preprint doi:10.1101/2021.03.09.21253218
- Lumley S F, O’Donnell D, Stoesser N E, Matthews P C, Howarth A, Hatch S B, Marsden B D, Cox S, James T, Warren F, Peck L J, Ritter T G, de Toledo Z, Warren L, Axten D, Cornall R J, Jones E Y, Stuart D I, Screaton G, Ebner D, Hoosdally S, Chand M, Crook D W, O’Donnell A M, Conlon C P, Pouwels K B, Walker A S, Peto T E, Hopkins S, Walker T M, Jeffery K, Eyre D W (2021).
Antibody Status and Incidence of SARS-CoV-2 Infection in Health Care Workers.
N Eng J Med 384:533 doi:10.1056/NEJMoa2034545
- Lumley S F, Wei J, O’Donnell D, Stoesser N E, Matthews P C, Howarth A, Hatch S B, Marsden B D, Cox S, James T, Peck L J, Ritter T G, de Toledo Z, Cornall R J, Jones E Y, Stuart D I, Screaton G, Ebner D, Hoosdally S, Crook D W, Conlon C P, Pouwels K B, Walker A S, Peto T E A, Walker T M, Jeffery K, Eyre D W, Oxford University Hospitals Staff Testing Group, Abbott M, Abhari R, Abuelgasim H, Ahmed-Firani T, Alhussni A, Argles I, Ashworth R, Back F, Black S, Brennan I, Cansdale L, Chakravorty T, Choudhury Z, Clay H, Conway-Jones R, Curtis A, Cutteridge J, Danbury H, Davies H, Denly L, Dequaire J, Dimitrov S, Dunlop E, Dunn P, East C, Eastwood B, Edwardes C, Evans M, Fields C, Flaherty S, Foord T, Freer R, Fuchs H, Grassam-Rowe A, Greenan-Barrett L, Gunnell J, Harries C, Harris E, Hatton E, Hennessy C, Holland C, Holloway B, Howgego G, Barnham I J, Johnson S, Johnson T, Johnstone D, Jurdon R, Kelly G, Kerneis S, Khulusi B, Killen A, Kourdov S, Kumarendran M, Laurenson-Schafer H, Lawrence R, Lee C, Livingstone A, Lynch R, Madsen T, Manji A, Marsh J, Mason C, Mccance A, Mcgivern E, Mckinlay A, Mighiu A, Millar L, Mohamed Y, Motohashi K, Myat S, Nezhentsev A, O’Byrne K, Okuwoga T, Oliver M, Pattenden S, Perera V, Petit Y, Pickles F, Pikoula M, Randhawa G, Ravi K, Reed L, Rigler C, Robinson C, Rothwell E, Santos-Paulo S, Savva C, Scharmeli A, Scott S, Shabir Z, Sharma I, Sheehan R, Shibu A, Somanathan A, Sussmes S, Sweeney O, Swift E, Tadikamalla G, Tamblyn M, Taylor A, Naudé R T W, Thomas S, Thompson C, Till L, Toward R, Virgo C, Vorley I, Waite S, Ward H, Ward J, Watson A, Watson L, Wedlich M, Wilkins L, Wilson J, Wilson J, Wong W, Young R, Doherty G, Kavanagh J, Chau K K, Fowler P W, Swann J, Volk D, Yang-Turner F, Skelly D, Karpe F, Neville M J, Ferreira L M, Christott T, Rodger G, Pickford H, Cameron S, Tamblin-Hopper P, Amini A, Andersson M, Anson K, Aston L, Axten D, Barot S, Bellinger T, Bialek A, Bodo N, Brent A, Campbell M, Cox V, Cronin T, Davies T, Deales A, Downs L, Drennan P, Dudareva M, Gates L, Gates M, Georgiou D, Gergely B, Holland L, Jones N, Jones S, Kerr S, Lawson E, Looms S, Luciw M, Martins D, Mcknight M, Mentzer A, Millard R, Mitchell T, Morgan L, Morrow J, Mortimore E, Mullins H, Nevard H, O’Donnell A M, Patel K, Peto L, Philips J, Ponting J, Ray R, Robles M, Rughani S, Sande N, Shaw R, Simons E J, Sims E, Smit K, Smith L, Szczurkowska J, Thompson Z, Turford R, Vilca K, Vogt A, Warren F, Warren L, Wharton V, Whitty A, Woodley H, Wozniak B, Young B, Justice A, Jesuthasan G, Wareing S, Fadzillah N H M, Cann K, Kirton R, Sutton C, Salvagno C, D’Amato G, Pill G, Butcher L, Rylance-Knight L, Tabirao M, Moroney R, Wright S (2021).
The Duration, Dynamics, and Determinants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antibody Responses in Individual Healthcare Workers.
Clinical Infectious Diseases 73:e699 doi:10.1093/cid/ciab004
medRxiv preprint doi:10.1101/2020.11.02.20224824
2020
- Fowler PW (2020).
How quickly can we predict trimethoprim resistance using alchemical free energy methods?.
Interface Focus 10:20190141 doi:10.1098/rsfs.2019.0141
bioRxiv preprint doi:10.1098/rsfs.2019.0141
- Eyre D W, Lumley S F, O’Donnell D, Campbell M, Sims E, Lawson E, Warren F, James T, Cox S, Howarth A, Doherty G, Hatch S B, Kavanagh J, Chau K K, Fowler P W, Swann J, Volk D, Yang-Turner F, Stoesser N, Matthews P C, Dudareva M, Davies T, Shaw R H, Peto L, Downs L O, Vogt A, Amini A, Young B C, Drennan P G, Mentzer A J, Skelly D T, Karpe F, Neville M J, Andersson M, Brent A J, Jones N, Martins Ferreira L, Christott T, Marsden B D, Hoosdally S, Cornall R, Crook D W, Stuart D I, Screaton G, Oxford University Hospitals Staff Testing Group, Watson A J, Taylor A, Chetwynd A, Grassam-Rowe A, Mighiu A S, Livingstone A, Killen A, Rigler C, Harries C, East C, Lee C, Mason C J, Holland C, Thompson C, Hennesey C, Savva C, Kim D S, Harris E W, McGivern E J, Qian E, Rothwell E, Back F, Kelly G, Watson G, Howgego G, Chase H, Danbury H, Laurenson-Schafer H, Ward H L, Hendron H, Vorley I C, Tol I, Gunnell J, Ward J L, Drake J, Wilson J D, Morton J, Dequaire J, O’Byrne K, Motohashi K, Harper K, Ravi K, Millar L J, Peck L J, Oliver M, English M R, Kumarendran M, Wedlich M, Ambler O, Deal O T, Sweeney O, Cowie P, Naudé R t W, Young R, Freer R, Scott S, Sussmes S, Peters S, Pattenden S, Waite S, Johnson S A, Kourdov S, Santos-Paulo S, Dimitrov S, Kerneis S, Ahmed-Firani T, King T B, Ritter T G, Foord T H, De Toledo Z, Christie T, Gergely B, Axten D, Simons E J, Nevard H, Philips J, Szczurkowska J, Patel K, Smit K, Warren L, Morgan L, Smith L, Robles M, McKnight M, Luciw M, Gates M, Sande N, Turford R, Ray R, Rughani S, Mitchell T, Bellinger T, Wharton V, Justice A, Jesuthasan G, Wareing S, Huda Mohamad Fadzillah N, Cann K, Kirton R, Sutton C, Salvagno C, DAmato G, Pill G, Butcher L, Rylance-Knight L, Tabirao M, Moroney R, Wright S, Peto T E, Holthof B, O’Donnell A M, Ebner D, Conlon C P, Jeffery K, Walker T M (2020).
Differential occupational risks to healthcare workers from SARS-CoV-2 observed during a prospective observational study.
eLife 9:e60675 doi:10.7554/eLife.60675
medRxiv preprint doi:10.1101/2020.06.24.20135038
- Davies TJ, Stoesser N, Sheppard AE, Abuoun M, Fowler PW, Swann J, Quan P, Griffiths D, Vaughan A, Morgan M, Phan HTT, Jeffery KJM, Andersson M, Eillington M, Ekelund O, Mathers A, Bonomo R, Woodford N, Crook DW, Peto TEA, Anjum M, Walker AS (2020).
Reconciling the potentially irreconcilable? Genotypic and phenotypic amoxicillin-clavulanate resistance in E. coli.
Antimicrobial Agent Chemo 64:e02026 doi:10.1128/aac.02026-19
bioRxiv preprint doi:10.1101/511402
- Kouchaki S, Yang Y, Lachapelle A, Walker TM, Walker AS, CRyPTIC Consortium, Peto TEA, Crook DW, Clifton DA (2020).
Multi-label random forest model for tuberculosis drug resistance classification and mutation ranking.
Frontiers in Microbiology 11:667 doi:10.3389/fmicb.2020.00667
- Wilson DJ, CRyPTIC Consortium (2020).
GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes.
Mol Biol Evol 37:2450 doi:10.1093/molbev/msaa069
biorXiv preprint doi:10.1101/523316
- Merker M, Kohl TA, Barilar I, Andres S, Fowler PW, Chryssanthou E, Ängeby K, Jureen P, Moradigaravand D, Parkhill J, Peacock SJ, Schön T, Maurer F, Walker TM, Köser C, Niemann S (2020).
Phylogenetically informative mutations in genes implicated in antibiotic resistance in Mycobacterium tuberculosis complex.
Genome Medicine 12:27 doi:10.1186/s13073-020-00726-5
2019
- Hunt M, Bradley P, Lapierre SG, Heys S, Thomsit M, Hall MB, Malone KM, Wintringer P, Walker TM, Cirillo DM, Comas I, Farhat MR, Fowler PW, Gardy J, Ismail N, Kohl TA, Mathys V, Merker M, Niemann S, Omar SV, Sintchenko V, Smith G, van Soolingen D, Supply P, Tahseen S, Wilcox M, Arandjelovic I, Peto TEA, Crook DW, Iqbal Z (2019).
Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe.
Wellcome Open Research 4:191 doi:10.12688/wellcomeopenres.15603.1
- Brankin AE, Fowler PW (2019).
Predicting Resistance is (Not) Futile.
ACS Cent Sci 5:1312 doi:10.1021/acscentsci.9b00791
- Collins JJ, Brown E, Baym M, Wright GD, Dantas G, Burrows L, Liu GY, Fowler PW, Whitchurch CB, Skelly AN, Honda K, Strathdee SA, Patterson TL (2019).
Overcoming Antibiotic Resistance.
Cell Host Microbe 26:8 doi:10.1016/j.chom.2019.06.007
- Yang-Turner F, Volk D, Fowler PW, Hoosdally S, Peto TEA, Crook DW (2019).
Scalable Pathogen Pipeline Platform (SP3) Enabling Unified Genomic Data Analysis with Elastic Cloud Computing.
IEEE Cloud 2019 478 doi:10.1109/CLOUD.2019.00083
- Yang Y, Walker TM, Walker AS, Wilson DJ, Peto TEA, Crook DW, Shamout F, CRyPTIC Consortium, Zhu T, Clifton DA (2019).
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis.
Bioinformatics 35:3240 doi:10.1093/bioinformatics/btz067
- Kouchaki S, Yang Y, Walker TM, Walker AS, Wilson DJ, Peto TEA, Crook DW, CRyPTIC Consortium, Clifton DA (2019).
Application of machine learning techniques to tuberculosis drug resistance analysis.
Bioinformatics 35:2276 doi:10.1093/bioinformatics/bty949
2018
- Fowler PW, Gibertoni-Cruz AL, Hoosdally S, Jarrett L, Borroni E, Chiacchiaretta M, Rathod P, Lehmann S, Molodtsov N, Grazian C, Walker TM, Robinson E, Hoffmann H, Peto TEA, Cirillo DM, Smith EG, Crook DW (2018).
Automated detection of bacterial growth on 96-well plates for high-throughput drug susceptibility testing of Mycobacterium tuberculosis.
Microbiology 164:1522 doi:10.1099/mic.0.000733
biorXiv preprint doi:10.1101/229427
- The CRyPTIC Consortium, the 100, 000 Genomes Project (2018).
Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing.
N Eng J Med 379:1403 doi:10.1056/NEJMoa1800474
- Rancoita PMV, Cugnata F, Gibertoni-Cruz AL, Borroni E, Hoosdally SJ, Walker TM, Grazian C, Davies TJ, Peto TEA, Crook DW, Fowler PW, Cirillo DM, the CRyPTIC consortium (2018).
Validating a 14-Drug Microtiter Plate Containing Bedaquiline and Delamanid for Large-Scale Research Susceptibility Testing of Mycobacterium tuberculosis.
Antimicrob Agent Chemo 62:e00344 doi:10.1128/AAC.00344-18
biorXiv preprint doi:10.1101/244731
- Fowler PW, Coles K, Gordon NC, Kearns AM, Llewelyn MJ, Peto TEA, Crook DW, Walker AS (2018).
Robust prediction of resistance to trimethoprim in S. aureus.
Cell Chem Biol 25:339 doi:10.1016/j.chembiol.2017.12.009
2017
- Duncan A, Reddy T, Koldsø H, Helie J, Fowler PW, Chavent M, Sansom MSP (2017).
Protein crowding and lipid complexity influence the nanoscale dynamic organization of ion channels in cell membranes.
Sci. Rep. 7:16647 doi:10.1038/s41598-017-16865-6
- Fowler PW, Sansom MSP, Reithmeier RAF (2017).
Effect of the Southeast Asian Ovalocytosis Deletion on the Conformational Dynamics of the Signal-Anchor Transmembrane Segment 1 of the Red Cell Anion Exchanger 1 (AE1, Band 3).
Biochemistry 56:712 doi:10.1021/acs.biochem.6b00966
2016
- Fowler PW, Helie J, Duncan AL, Chavent M, Koldsø H, Sansom MSP (2016).
Membrane stiffness is modified by integral membrane proteins.
Soft Matter 12:7792 doi:10.1039/c6sm01186a
- Fowler PW, Williamson JJ, Sansom MSP, Olmsted PD (2016).
Roles of interleaflet coupling and hydrophobic mismatch in lipid membrane phase-separation kinetics.
J Am Chem Soc 138:11633 doi:10.1021/jacs.6b04880
- Koldsø H, Reddy T, Fowler PW, Duncan AL, Sansom MSP (2016).
Membrane compartmentalization reduces the mobility of lipids and proteins within a model plasma membrane.
J Phys Chem B 120:8873 doi:10.1021/acs.jpcb.6b05846
- Samsudin F, Parker JL, Sansom MSP, Newstead, Fowler PW (2016).
Accurate prediction of ligand affinities for a peptide transporter.
Cell Chem Biol 23:299 doi:10.1016/j.chembiol.2015.11.015
2015
- Beale JH, Parker JL, Samsudin F, Barret AL, Senan A, Bird LE, Scott D, Owens RJ, Sansom MSP, Tucker SJ, Meredith D, Fowler PW, Newstead S (2015).
Crystal structures of the extracellular domain from PepT1 and PepT2 provide novel insights into mammalian peptide transport.
Structure 23:1889 doi:10.1016/j.str.2015.07.016
- Jefferys E, Sands Z, Shi J, Sansom MSP, Fowler PW (2015).
Alchembed: A computational method for incorporating proteins into complex lipid geometries.
J Chem Theo Comp 11:2743 doi:10.1021/ct501111d
- Reddy T, Shorthouse D, Parton D, Jefferys E, Fowler PW, Chavent M, Baaden M, Sansom MSP (2015).
Nothing to sneeze at: a dynamic and integrative computational model of an influenza A virion.
Structure 23:584 doi:10.1016/j.str.2014.12.019
- Fowler PW, Orwick-Rydmark M, Radestock S, Solcan N, Dijkman P, Lyons JA, Kwok J, Caffery M, Watts A, Forrest LR, Newstead S (2015).
Gating topology of the proton coupled oligopeptide symporters.
Structure 23:290 doi:10.1016/j.str.2014.12.012
2014
- Fowler PW, Bollepalli MK, Rapedius M, Shang L, Nematian E, Sansom MSP, Tucker SJ, Baukrowitz T (2014).
Insights into the structural nature of the transition state in the Kir channel gating pathway.
Channels 8:551 doi:10.4161/19336950.2014.962371
- Bollepalli MK, Fowler PW, Rapedius M, Shang L, Sansom MSP, Tucker SJ, Baukrowitz T (2014).
State dependent network connectivity determines gating in a K+ channel.
Structure 22:1037 doi:10.1016/j.str.2014.04.018
- Jefferys E, Sansom MSP, Fowler PW (2014).
NRas slows the rate at which a model lipid bilayer phase separates.
RSC Faraday Discussion 169:209 doi:10.1039/c3fd00131h
- Stelzl L, Fowler PW, Sansom MSP, Beckstein O (2014).
Flexible gates generate occluded intermediates in the transport cycle of LacY.
J Mol Biol 426:735 doi:10.1016/j.jmb.2013.10.024
2013
- Fowler PW, Beckstein O, Abad E, Sansom MSP (2013).
Detailed examination of a single conduction event in a potassium channel.
J Phys Chem Lett 4:3104 doi:10.1021/jz4014079
- Fowler PW, Abad E, Beckstein O, Sansom MSP (2013).
Energetics of multi-ion conduction pathways in potassium ion channels.
J Chem Theo Comp 9:5176 doi:10.1021/ct4005933
- Fowler PW, Sansom MSP (2013).
The pore of voltage-gated potassium ion channels is strained when closed.
Nature Communications 4:1872 doi:10.1038/ncomms2858
2012
- Solcan N, Kwok J, Fowler PW, Cameron AD, Drew D, Iwata S, Newstead S (2012).
Alternating access mechanism in the POT family of oligopeptide transporters.
EMBO J 31:3411 doi:10.1038/emboj.2012.157
2011
- Newstead S, Drew D, Cameron AD, Postis VLG, Xia X, Fowler PW, Carpenter EP, Sansom MSP, McPheron MJ, Baldwin SA, Iwata S (2011).
Crystal structure of a prokaryotic homologue of the mammalian oligopeptide-proton symporters, PepT1 and PepT2.
EMBO J 30:417 doi:10.1038/emboj.2010.309
2010
- Paynter JJ, Andres-Enguix I, Fowler PW, Tottey S, Cheng W, Enkvetchakul D, Bavro VN, Kusakabe Y, Sansom MSP, Robinson NJ, Nichols CG, Tucker SJ (2010).
Functional complementation and genetic deletion studies of KirBac channels.
J Biol Chem 285:40754 doi:10.1074/jbc.M110.175687
2009
- Newstead S, Fowler PW, Bilton P, Carpenter E, Sadler P, Campopiano D, Sansom M, Iwata S (2009).
Insights into how nucleotide-binding domains power ABC transport.
Structure 17:1213 doi:10.1016/j.str.2009.07.009
- Abad E, Reingruber J, Fowler PW, Sansom MSP (2009).
A novel rate theory approach to transport in ion channels.
TACC 1102:236 doi:10.1063/1.3108380
2008
- Tai K, Fowler PW, Mokrab Y, Stansfield P, Sansom MSP (2008).
Molecular modeling and simulation studies of ion channel structures, dynamics & mechanisms.
Methods Nano Cell Biol 90:233 doi:10.1016/S0091-679X(08)00812-100812-1
- Psachoulia E, Fowler PW, Bond PJ, Sansom MSP (2008).
Helix-helix interactions in membrane proteins: Coarse grained simulations of Glycophorin helix dimerization.
Biochemistry 47:10503 doi:10.1021/bi800678t
- Fowler PW, Tai K, Sansom MSP (2008).
The selectivity of K+ ion channels: testing the hypotheses.
Biophys J 95:5062 doi:10.1529/biophysj.108.132035
2007
- Rapedius M, Paynter J, Fowler PW, Shang L, Sansom MSP, Tucker SJ, Baukrowitz T (2007).
Control of pH and PIP2 gating in heteromeric Kir4.1/Kir5.1 channels by H-bonding at the helix bundle crossing.
Channels 1:327 doi:10.4161/chan.5176
- Rapedius M, Fowler PW, Shang L, Sansom MSP, Tucker SJ, Baukrowitz T (2007).
H-Bonding at the helix-bundle crossing controls gating in Kir potassium channels.
Neuron 55:602 doi:10.1016/j.neuron.2007.07.026
- Fowler PW, Geroult S, Jha S, Waksman G, Coveney PV (2007).
Rapid, accurate and precise calculation of relative binding affinities for the SH2 domain using a computational grid.
J Comp Theo Chem 3:1193 doi:10.1021/ct6003017
- Fowler PW, Balali-Mood K, Deol SS, Coveney PV, Sansom MSP (2007).
Monotopic proteins and lipid bilayers: a comparative study.
Biochemistry 46:3108 doi:10.1021/bi602455n
2006
- Fowler PW, Coveney PV (2006).
A computational protocol for the integration of the monotopic protein PGHS into a bilayer. Biophys J 91:401.
doi:10.1529/biophysj.105.077784
2005
- Coveney PV, Fowler PW (2005).
Modelling biological complexity: a physical scientist’s perspective.
J R Soc Interface 2:267 doi:10.1098/rsif.2005.0045
- Fowler PW, Jha S, Coveney PV (2005).
Grid-based steered thermodynamic integration accelerates the calculation of binding affinities. Phil Trans R Soc Lond A 363(1833):1999.
doi:10.1098/rsta.2005.1625
- Giordanetto F, Fowler PW, Saqi M, and Coveney PV (2005).
Large scale molecular dynamics simulation of native and mutant DHPS complexes suggests the molecular basis for dihydropteroate synthase drug resistance.
Phil Trans R Soc Lond A 363:(1833):2055 doi:10.1098/rsta.2005.1629
2004
- Fowler PW, Coveney PV, Jha S, Wan S (2004).
Exact calculation of peptide-protein binding energies by steered thermodynamic integration using high performance computing grids.
Proceedings of the UK e-Science All Hands Meeting
1998
- Al-Mushadani O, Boghosian BM, Coveney PV, Fowler PW, Maillet JB, Wilson JL (1998).
Lattice-Gas Simulations of Ternary Amphiphilic Fluid Flow in Porous Media.
Int J Mod Phys C 9:1479 doi:10.1142/S0129183198001345
