Publications by authors named "Simon R Harris"

158 Publications

Globetrotting strangles: the unbridled national and international transmission of between horses.

Microb Genom 2021 Mar 8;7(3). Epub 2021 Mar 8.

Intervacc AB, Stockholm, Sweden.

The equine disease strangles, which is characterized by the formation of abscesses in the lymph nodes of the head and neck, is one of the most frequently diagnosed infectious diseases of horses around the world. The causal agent, subspecies , establishes a persistent infection in approximately 10 % of animals that recover from the acute disease. Such 'carrier' animals appear healthy and are rarely identified during routine veterinary examinations pre-purchase or transit, but can transmit to naïve animals initiating new episodes of disease. Here, we report the analysis and visualization of phylogenomic and epidemiological data for 670 isolates of recovered from 19 different countries using a new core-genome multilocus sequence typing (cgMLST) web bioresource. Genetic relationships among all 670 S. isolates were determined at high resolution, revealing national and international transmission events that drive this endemic disease in horse populations throughout the world. Our data argue for the recognition of the international importance of strangles by the Office International des Épizooties to highlight the health, welfare and economic cost of this disease. The Pathogenwatch cgMLST web bioresource described herein is available for tailored genomic analysis of populations of and its close relative subspecies that are recovered from horses and other animals, including humans, throughout the world. This article contains data hosted by Microreact.
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http://dx.doi.org/10.1099/mgen.0.000528DOI Listing
March 2021

Phylogenomics of reveals a new lineage and a complex evolutionary history.

Microb Genom 2021 02;7(2)

University of Basel, Basel, Switzerland.

Human tuberculosis (TB) is caused by members of the complex (MTBC). The MTBC comprises several human-adapted lineages known as , as well as two lineages (L5 and L6) traditionally referred to as . Strains of L5 and L6 are largely limited to West Africa for reasons unknown, and little is known of their genomic diversity, phylogeography and evolution. Here, we analysed the genomes of 350 L5 and 320 L6 strains, isolated from patients from 21 African countries, plus 5 related genomes that had not been classified into any of the known MTBC lineages. Our population genomic and phylogeographical analyses showed that the unclassified genomes belonged to a new group that we propose to name MTBC lineage 9 (L9). While the most likely ancestral distribution of L9 was predicted to be East Africa, the most likely ancestral distribution for both L5 and L6 was the Eastern part of West Africa. Moreover, we found important differences between L5 and L6 strains with respect to their phylogeographical substructure and genetic diversity. Finally, we could not confirm the previous association of drug-resistance markers with lineage and sublineages. Instead, our results indicate that the association of drug resistance with lineage is most likely driven by sample bias or geography. In conclusion, our study sheds new light onto the genomic diversity and evolutionary history of , and highlights the need to consider the particularities of each MTBC lineage for understanding the ecology and epidemiology of TB in Africa and globally.
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http://dx.doi.org/10.1099/mgen.0.000477DOI Listing
February 2021

The distribution and spread of susceptible and resistant Neisseria gonorrhoeae across demographic groups in a major metropolitan center.

Clin Infect Dis 2020 Aug 23. Epub 2020 Aug 23.

Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, United States of America.

Background: Genomic epidemiology studies of gonorrhea in the United States have primarily focused on national surveillance for antibiotic resistance, and patterns of local transmission between demographic groups of resistant and susceptible strains are unknown.

Methods: We analyzed a convenience sample of genome sequences, antibiotic susceptibility, and patient data from 897 gonococcal isolates cultured at the NYC Public Health Laboratory from NYC Department of Health and Mental Hygiene (DOHMH) Sexual Health Clinic (SHC) patients, primarily in 2012-13. We reconstructed the gonococcal phylogeny, defined transmission clusters using a 10 non-recombinant single nucleotide polymorphism threshold, tested for clustering of demographic groups, and placed NYC isolates in a global phylogenetic context.

Results: The NYC gonococcal phylogeny reflected global diversity with isolates from 22/23 of the prevalent global lineages (96%). Isolates clustered on the phylogeny by patient sexual behavior (p&0.001) and race/ethnicity (p&0.001). Minimum inhibitory concentrations were higher across antibiotics in isolates from men who have sex with men compared to heterosexuals (p&0.001) and white heterosexuals compared to black heterosexuals (p&0.01). In our dataset, all large transmission clusters (≥10 samples) of N. gonorrhoeae were susceptible to ciprofloxacin, ceftriaxone, and azithromycin and comprised isolates from patients across demographic groups.

Conclusions: All large transmission clusters were susceptible to gonorrhea therapies, suggesting that resistance to empiric therapy was not a main driver of spread, even as risk for resistance varied across demographic groups. Further study of local transmission networks is needed to identify drivers of transmission.
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http://dx.doi.org/10.1093/cid/ciaa1229DOI Listing
August 2020

Adaptation to the cervical environment is associated with increased antibiotic susceptibility in Neisseria gonorrhoeae.

Nat Commun 2020 08 17;11(1):4126. Epub 2020 Aug 17.

Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Neisseria gonorrhoeae is an urgent public health threat due to rapidly increasing incidence and antibiotic resistance. In contrast with the trend of increasing resistance, clinical isolates that have reverted to susceptibility regularly appear, prompting questions about which pressures compete with antibiotics to shape gonococcal evolution. Here, we used genome-wide association to identify loss-of-function (LOF) mutations in the efflux pump mtrCDE operon as a mechanism of increased antibiotic susceptibility and demonstrate that these mutations are overrepresented in cervical relative to urethral isolates. This enrichment holds true for LOF mutations in another efflux pump, farAB, and in urogenitally-adapted versus typical N. meningitidis, providing evidence for a model in which expression of these pumps in the female urogenital tract incurs a fitness cost for pathogenic Neisseria. Overall, our findings highlight the impact of integrating microbial population genomics with host metadata and demonstrate how host environmental pressures can lead to increased antibiotic susceptibility.
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http://dx.doi.org/10.1038/s41467-020-17980-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7431566PMC
August 2020

Genomic evolution of Neisseria gonorrhoeae since the preantibiotic era (1928-2013): antimicrobial use/misuse selects for resistance and drives evolution.

BMC Genomics 2020 Feb 3;21(1):116. Epub 2020 Feb 3.

WHO Collaborating Centre for Gonorrhoea and other Sexually Transmitted Infections, Department of Laboratory Medicine, Microbiology, Faculty of Medicine and Health, Örebro University, SE-710 85, Örebro, Sweden.

Background: Multidrug-resistant Neisseria gonorrhoeae strains are prevalent, threatening gonorrhoea treatment globally, and understanding of emergence, evolution, and spread of antimicrobial resistance (AMR) in gonococci remains limited. We describe the genomic evolution of gonococci and their AMR, related to the introduction of antimicrobial therapies, examining isolates from 1928 (preantibiotic era) to 2013 in Denmark. This is, to our knowledge, the oldest gonococcal collection globally.

Methods: Lyophilised isolates were revived and examined using Etest (18 antimicrobials) and whole-genome sequencing (WGS). Quality-assured genome sequences were obtained for 191 viable and 40 non-viable isolates and analysed with multiple phylogenomic approaches.

Results: Gonococcal AMR, including an accumulation of multiple AMR determinants, started to emerge particularly in the 1950s-1970s. By the twenty-first century, resistance to most antimicrobials was common. Despite that some AMR determinants affect many physiological functions and fitness, AMR determinants were mainly selected by the use/misuse of gonorrhoea therapeutic antimicrobials. Most AMR developed in strains belonging to one multidrug-resistant (MDR) clade with close to three times higher genomic mutation rate. Modern N. gonorrhoeae was inferred to have emerged in the late-1500s and its genome became increasingly conserved over time.

Conclusions: WGS of gonococci from 1928 to 2013 showed that no AMR determinants, except penB, were in detectable frequency before the introduction of gonorrhoea therapeutic antimicrobials. The modern gonococcus is substantially younger than previously hypothesized and has been evolving into a more clonal species, driven by the use/misuse of antimicrobials. The MDR gonococcal clade should be further investigated for early detection of strains with predispositions to develop and maintain MDR and for initiation of public health interventions.
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http://dx.doi.org/10.1186/s12864-020-6511-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6998845PMC
February 2020

Phylogenomic analysis of Neisseria gonorrhoeae transmission to assess sexual mixing and HIV transmission risk in England: a cross-sectional, observational, whole-genome sequencing study.

Lancet Infect Dis 2020 04 21;20(4):478-486. Epub 2020 Jan 21.

National Institute for Health Research Health Protection Research Unit in Blood Borne and Sexually Transmitted Infections, University College London, London, UK; National Infection Service, Public Health England, London, UK.

Background: Characterising sexual networks with transmission of sexually transmitted infections might allow identification of individuals at increased risk of infection. We aimed to investigate sexual mixing in Neisseria gonorrhoeae transmission networks between women, heterosexual men, and men who report sex with men (MSM), and between people with and without HIV.

Methods: In this cross-sectional observational study, we whole-genome sequenced N gonorrhoeae isolates from the archive of the Gonococcal Resistance to Antimicrobials Surveillance Programme (GRASP).w Isolates that varied by five single nucleotide polymorphisms or fewer were grouped into clusters that represented sexual networks with N gonorrhoeae transmission. Clusters were described by gender, sexual risk group, and HIV status.

Findings: We sequenced 1277 N gonorrhoeae isolates with linked clinical and sociodemographic data that were collected in five clinics in England during 2013-16 (July 1 to Sept 30 in 2013-15; July 1 to Sept 9 in 2016). The isolates grouped into 213 clusters. 30 (14%) clusters contained isolates from heterosexual men and MSM but no women and three (1%) clusters contained isolates from only women and MSM. 146 (69%) clusters comprised solely people with negative or unknown HIV status and seven (3%) comprised only HIV-positive people. 60 (28%) clusters comprised MSM with positive and negative or unknown HIV status.

Interpretation: N gonorrhoeae molecular data can provide information indicating risk of HIV or other sexually transmitted infections for some individuals for whom such risk might not be known from clinical history. These findings have implications for sexual health care, including offering testing, prevention advice, and preventive treatment, such as HIV pre-exposure prophylaxis.

Funding: National Institute for Health Research Health Protection Research Unit; Wellcome; Public Health England.
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http://dx.doi.org/10.1016/S1473-3099(19)30610-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099395PMC
April 2020

Genetic variation associated with infection and the environment in the accidental pathogen .

Commun Biol 2019 22;2:428. Epub 2019 Nov 22.

4Department of Medicine, University of Cambridge, Cambridge, CB2 0QQ UK.

The environmental bacterium causes melioidosis, an important endemic human disease in tropical and sub-tropical countries. This bacterium occupies broad ecological niches including soil, contaminated water, single-cell microbes, plants and infection in a range of animal species. Here, we performed genome-wide association studies for genetic determinants of environmental and human adaptation using a combined dataset of 1,010 whole genome sequences of from Northeast Thailand and Australia, representing two major disease hotspots. With these data, we identified 47 genes from 26 distinct loci associated with clinical or environmental isolates from Thailand and replicated 12 genes in an independent Australian cohort. We next outlined the selective pressures on the genetic loci (dN/dS) and the frequency at which they had been gained or lost throughout their evolutionary history, reflecting the bacterial adaptability to a wide range of ecological niches. Finally, we highlighted loci likely implicated in human disease.
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http://dx.doi.org/10.1038/s42003-019-0678-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874650PMC
May 2020

Genetic variation regulates the activation and specificity of Restriction-Modification systems in Neisseria gonorrhoeae.

Sci Rep 2019 10 11;9(1):14685. Epub 2019 Oct 11.

Microbiotica Ltd, Biodata Innovation Centre, Wellcome Genome Campus, Hinxton, Cambridge, UK.

Restriction-Modification systems (RMS) are one of the main mechanisms of defence against foreign DNA invasion and can have an important role in the regulation of gene expression. The obligate human pathogen Neisseria gonorrhoeae carries one of the highest loads of RMS in its genome; between 13 to 15 of the three main types. Previous work has described their organization in the reference genome FA1090 and has inferred the associated methylated motifs. Here, we studied the structure of RMS and target methylated motifs in 25 gonococcal strains sequenced with Single Molecule Real-Time (SMRT) technology, which provides data on DNA modification. The results showed a variable picture of active RMS in different strains, with phase variation switching the activity of Type III RMS, and both the activity and specificity of a Type I RMS. Interestingly, the Dam methylase was found in place of the NgoAXI endonuclease in two of the strains, despite being previously thought to be absent in the gonococcus. We also identified the real methylation target of NgoAXII as 5'-GCAGA-3', different from that previously described. Results from this work give further insights into the diversity and dynamics of RMS and methylation patterns in N. gonorrhoeae.
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http://dx.doi.org/10.1038/s41598-019-51102-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789123PMC
October 2019

Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data.

PLoS Comput Biol 2019 09 3;15(9):e1007349. Epub 2019 Sep 3.

Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.

Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation of factors that may influence performance of such models, how they might apply to and vary across clinical populations, and what the implications might be in the clinical setting. Here, we performed a meta-analysis of seven large Neisseria gonorrhoeae datasets, as well as Klebsiella pneumoniae and Acinetobacter baumannii datasets, with whole genome sequence data and antibiotic susceptibility phenotypes using set covering machine classification, random forest classification, and random forest regression models to predict resistance phenotypes from genotype. We demonstrate how model performance varies by drug, dataset, resistance metric, and species, reflecting the complexities of generating clinically relevant conclusions from machine learning-derived models. Our findings underscore the importance of incorporating relevant biological and epidemiological knowledge into model design and assessment and suggest that doing so can inform tailored modeling for individual drugs, pathogens, and clinical populations. We further suggest that continued comprehensive sampling and incorporation of up-to-date whole genome sequence data, resistance phenotypes, and treatment outcome data into model training will be crucial to the clinical utility and sustainability of machine learning-based molecular diagnostics.
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http://dx.doi.org/10.1371/journal.pcbi.1007349DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743791PMC
September 2019

Genome-wide epistasis and co-selection study using mutual information.

Nucleic Acids Res 2019 10;47(18):e112

Department of Mathematics and Statistics, Helsinki Institute for Information Technology (HIIT), Faculty of Science, University of Helsinki, FI-00014 Helsinki, Finland.

Covariance-based discovery of polymorphisms under co-selective pressure or epistasis has received considerable recent attention in population genomics. Both statistical modeling of the population level covariation of alleles across the chromosome and model-free testing of dependencies between pairs of polymorphisms have been shown to successfully uncover patterns of selection in bacterial populations. Here we introduce a model-free method, SpydrPick, whose computational efficiency enables analysis at the scale of pan-genomes of many bacteria. SpydrPick incorporates an efficient correction for population structure, which adjusts for the phylogenetic signal in the data without requiring an explicit phylogenetic tree. We also introduce a new type of visualization of the results similar to the Manhattan plots used in genome-wide association studies, which enables rapid exploration of the identified signals of co-evolution. Simulations demonstrate the usefulness of our method and give some insight to when this type of analysis is most likely to be successful. Application of the method to large population genomic datasets of two major human pathogens, Streptococcus pneumoniae and Neisseria meningitidis, revealed both previously identified and novel putative targets of co-selection related to virulence and antibiotic resistance, highlighting the potential of this approach to drive molecular discoveries, even in the absence of phenotypic data.
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http://dx.doi.org/10.1093/nar/gkz656DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6765119PMC
October 2019

Epidemic of carbapenem-resistant Klebsiella pneumoniae in Europe is driven by nosocomial spread.

Nat Microbiol 2019 11 29;4(11):1919-1929. Epub 2019 Jul 29.

Institute for Infection Prevention and Hospital Epidemiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

Public health interventions to control the current epidemic of carbapenem-resistant Klebsiella pneumoniae rely on a comprehensive understanding of its emergence and spread over a wide range of geographical scales. We analysed the genome sequences and epidemiological data of >1,700 K. pneumoniae samples isolated from patients in 244 hospitals in 32 countries during the European Survey of Carbapenemase-Producing Enterobacteriaceae. We demonstrate that carbapenemase acquisition is the main cause of carbapenem resistance and that it occurred across diverse phylogenetic backgrounds. However, 477 of 682 (69.9%) carbapenemase-positive isolates are concentrated in four clonal lineages, sequence types 11, 15, 101, 258/512 and their derivatives. Combined analysis of the genetic and geographic distances between isolates with different β-lactam resistance determinants suggests that the propensity of K. pneumoniae to spread in hospital environments correlates with the degree of resistance and that carbapenemase-positive isolates have the highest transmissibility. Indeed, we found that over half of the hospitals that contributed carbapenemase-positive isolates probably experienced within-hospital transmission, and interhospital spread is far more frequent within, rather than between, countries. Finally, we propose a value of 21 for the number of single nucleotide polymorphisms that optimizes the discrimination of hospital clusters and detail the international spread of the successful epidemic lineage, ST258/512.
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http://dx.doi.org/10.1038/s41564-019-0492-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244338PMC
November 2019

The impact of antimicrobials on gonococcal evolution.

Nat Microbiol 2019 11 29;4(11):1941-1950. Epub 2019 Jul 29.

Pathogen Genomics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.

The sexually transmitted pathogen Neisseria gonorrhoeae is regarded as being on the way to becoming an untreatable superbug. Despite its clinical importance, little is known about its emergence and evolution, and how this corresponds with the introduction of antimicrobials. We present a genome-based phylogeographical analysis of 419 gonococcal isolates from across the globe. Results indicate that modern gonococci originated in Europe or Africa, possibly as late as the sixteenth century and subsequently disseminated globally. We provide evidence that the modern gonococcal population has been shaped by antimicrobial treatment of sexually transmitted infections as well as other infections, leading to the emergence of two major lineages with different evolutionary strategies. The well-described multidrug-resistant lineage is associated with high rates of homologous recombination and infection in high-risk sexual networks. A second, multisusceptible lineage is more associated with heterosexual networks, with potential implications for infection control.
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http://dx.doi.org/10.1038/s41564-019-0501-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817357PMC
November 2019

Atlas of group A streptococcal vaccine candidates compiled using large-scale comparative genomics.

Nat Genet 2019 06 27;51(6):1035-1043. Epub 2019 May 27.

School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia.

Group A Streptococcus (GAS; Streptococcus pyogenes) is a bacterial pathogen for which a commercial vaccine for humans is not available. Employing the advantages of high-throughput DNA sequencing technology to vaccine design, we have analyzed 2,083 globally sampled GAS genomes. The global GAS population structure reveals extensive genomic heterogeneity driven by homologous recombination and overlaid with high levels of accessory gene plasticity. We identified the existence of more than 290 clinically associated genomic phylogroups across 22 countries, highlighting challenges in designing vaccines of global utility. To determine vaccine candidate coverage, we investigated all of the previously described GAS candidate antigens for gene carriage and gene sequence heterogeneity. Only 15 of 28 vaccine antigen candidates were found to have both low naturally occurring sequence variation and high (>99%) coverage across this diverse GAS population. This technological platform for vaccine coverage determination is equally applicable to prospective GAS vaccine antigens identified in future studies.
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http://dx.doi.org/10.1038/s41588-019-0417-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650292PMC
June 2019

Molecular epidemiology and whole genome sequencing analysis of clinical Mycobacterium bovis from Ghana.

PLoS One 2019 4;14(3):e0209395. Epub 2019 Mar 4.

Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana, Legon, Accra, Ghana.

Background: Bovine tuberculosis (bTB) caused by Mycobacterium bovis is a re-emerging problem in both livestock and humans. The association of some M. bovis strains with hyper-virulence, MDR-TB and disseminated disease makes it imperative to understand the biology of the pathogen.

Methods: Mycobacterium bovis (15) among 1755 M. tuberculosis complex (MTBC) isolated between 2012 and 2014 were characterized and analyzed for associated patient demography and other risk factors. Five of the M. bovis isolates were whole-genome sequenced and comparatively analyzed against a global collection of published M. bovis genomes.

Results: Mycobacterium bovis was isolated from 3/560(0.5%) females and 12/1195(1.0%) males with pulmonary TB. The average age of M. bovis infected cases was 46.8 years (7-72years). TB patients from the Northern region of Ghana (1.9%;4/212) had a higher rate of infection with M. bovis (OR = 2.7,p = 0.0968) compared to those from the Greater Accra region (0.7%;11/1543). Among TB patients with available HIV status, the odds of isolating M. bovis from HIV patients (2/119) was 3.3 higher relative to non-HIV patients (4/774). Direct contact with livestock or their unpasteurized products was significantly associated with bTB (p<0.0001, OR = 124.4,95% CI = 30.1-508.3). Two (13.3%) of the M. bovis isolates were INH resistant due to the S315T mutation in katG whereas one (6.7%) was RIF resistant with Q432P and I1491S mutations in rpoB. M. bovis from Ghana resolved as mono-phyletic branch among mostly M. bovis from Africa irrespective of the host and were closest to the root of the global M. bovis phylogeny. M. bovis-specific amino acid mutations were detected among MTBC core genes such as mce1A, mmpL1, pks6, phoT, pstB, glgP and Rv2955c. Additional mutations P6T in chaA, G187E in mgtC, T35A in Rv1979c, S387A in narK1, L400F in fas and A563T in eccA1 were restricted to the 5 clinical M. bovis from Ghana.

Conclusion: Our data indicate potential zoonotic transmission of bTB in Ghana and hence calls for intensified public education on bTB, especially among risk groups.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0209395PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6398925PMC
November 2019

Mycobacterium ulcerans Population Genomics To Inform on the Spread of Buruli Ulcer across Central Africa.

mSphere 2019 02 6;4(1). Epub 2019 Feb 6.

Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.

Buruli ulcer is a neglected tropical disease of skin and subcutaneous tissue caused by infection with the pathogen Many critical issues for disease control, such as understanding the mode of transmission and identifying source reservoirs of , are still largely unknown. Here, we used genomics to reconstruct in detail the evolutionary trajectory and dynamics of populations at a central African scale and at smaller geographical village scales. Whole-genome sequencing (WGS) data were analyzed from 179 strains isolated from all Buruli ulcer foci in the Democratic Republic of the Congo, The Republic of Congo, and Angola that have ever yielded positive cultures. We used both temporal associations and the study of the mycobacterial demographic history to estimate the contribution of humans as a reservoir in Buruli ulcer transmission. Our phylogeographic analysis revealed one almost exclusively predominant sublineage of that arose in Central Africa and proliferated in its different regions of endemicity during the Age of Discovery. We observed how the best sampled endemic hot spot, the Songololo territory, became an area of endemicity while the region was being colonized by Belgium (1880s). We furthermore identified temporal parallels between the observed past population fluxes of from the Songololo territory and the timing of health policy changes toward control of the Buruli ulcer epidemic in that region. These findings suggest that an intervention based on detecting and treating human cases in an area of endemicity might be sufficient to break disease transmission chains, irrespective of other reservoirs of the bacterium. Buruli ulcer is a destructive skin and soft tissue infection caused by The disease is characterized by progressive skin ulceration, which can lead to permanent disfigurement and long-term disability. Currently, the major hurdles facing disease control are incomplete understandings of both the mode of transmission and environmental reservoirs of As decades of spasmodic environmental sampling surveys have not brought us much closer to overcoming these hurdles, the Buruli ulcer research community has recently switched to using comparative genomics. The significance of our research is in how we used both temporal associations and the study of the mycobacterial demographic history to estimate the contribution of humans as a reservoir in Buruli ulcer transmission. Our approach shows that it might be possible to use bacterial population genomics to assess the impact of health interventions, providing valuable feedback for managers of disease control programs in areas where health surveillance infrastructure is poor.
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http://dx.doi.org/10.1128/mSphere.00472-18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6365612PMC
February 2019

Using genomics to understand antimicrobial resistance and transmission in Neisseria gonorrhoeae.

Microb Genom 2019 02 30;5(2). Epub 2019 Jan 30.

Infection Genomics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK.

Gonorrhoea infections are on the increase and strains that are resistant to all antimicrobials used to treat the disease have been found worldwide. These observations encouraged the World Health Organization to include Neisseria gonorrhoeae on their list of high-priority organisms in need of new treatments. Fortunately, concurrent resistance to both antimicrobials used in dual therapy is still rare. The fight against antimicrobial resistance (AMR) must begin from an understanding of how it evolves and spreads in sexual networks. Genome-based analyses have allowed the study of the gonococcal population dynamics and transmission, giving a novel perspective on AMR gonorrhoea. Here, we will review past, present and future treatment options for gonorrhoea and explain how genomics is helping to increase our understanding of the changing AMR and transmission landscape. This article contains data hosted by Microreact.
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http://dx.doi.org/10.1099/mgen.0.000239DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421347PMC
February 2019

Fast and flexible bacterial genomic epidemiology with PopPUNK.

Genome Res 2019 02 24;29(2):304-316. Epub 2019 Jan 24.

MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, United Kingdom.

The routine use of genomics for disease surveillance provides the opportunity for high-resolution bacterial epidemiology. Current whole-genome clustering and multilocus typing approaches do not fully exploit core and accessory genomic variation, and they cannot both automatically identify, and subsequently expand, clusters of significantly similar isolates in large data sets spanning entire species. Here, we describe PopPUNK (ulation artitioning sing ucleotide -mers), a software implementing scalable and expandable annotation- and alignment-free methods for population analysis and clustering. Variable-length -mer comparisons are used to distinguish isolates' divergence in shared sequence and gene content, which we demonstrate to be accurate over multiple orders of magnitude using data from both simulations and genomic collections representing 10 taxonomically widespread species. Connections between closely related isolates of the same strain are robustly identified, despite interspecies variation in the pairwise distance distributions that reflects species' diverse evolutionary patterns. PopPUNK can process 10-10 genomes in a single batch, with minimal memory use and runtimes up to 200-fold faster than existing model-based methods. Clusters of strains remain consistent as new batches of genomes are added, which is achieved without needing to reanalyze all genomes de novo. This facilitates real-time surveillance with consistent cluster naming between studies and allows for outbreak detection using hundreds of genomes in minutes. Interactive visualization and online publication is streamlined through the automatic output of results to multiple platforms. PopPUNK has been designed as a flexible platform that addresses important issues with currently used whole-genome clustering and typing methods, and has potential uses across bacterial genetics and public health research.
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http://dx.doi.org/10.1101/gr.241455.118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360808PMC
February 2019

Bayesian inference of ancestral dates on bacterial phylogenetic trees.

Nucleic Acids Res 2018 12;46(22):e134

Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

The sequencing and comparative analysis of a collection of bacterial genomes from a single species or lineage of interest can lead to key insights into its evolution, ecology or epidemiology. The tool of choice for such a study is often to build a phylogenetic tree, and more specifically when possible a dated phylogeny, in which the dates of all common ancestors are estimated. Here, we propose a new Bayesian methodology to construct dated phylogenies which is specifically designed for bacterial genomics. Unlike previous Bayesian methods aimed at building dated phylogenies, we consider that the phylogenetic relationships between the genomes have been previously evaluated using a standard phylogenetic method, which makes our methodology much faster and scalable. This two-step approach also allows us to directly exploit existing phylogenetic methods that detect bacterial recombination, and therefore to account for the effect of recombination in the construction of a dated phylogeny. We analysed many simulated datasets in order to benchmark the performance of our approach in a wide range of situations. Furthermore, we present applications to three different real datasets from recent bacterial genomic studies. Our methodology is implemented in a R package called BactDating which is freely available for download at https://github.com/xavierdidelot/BactDating.
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http://dx.doi.org/10.1093/nar/gky783DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6294524PMC
December 2018

Loss of Genomic Diversity in a Neisseria meningitidis Clone Through a Colonization Bottleneck.

Genome Biol Evol 2018 08 1;10(8):2102-2109. Epub 2018 Aug 1.

Swiss Tropical and Public Health Institute, Basel, Switzerland.

Neisseria meningitidis is the leading cause of epidemic meningitis in the "meningitis belt" of Africa, where clonal waves of colonization and disease are observed. Point mutations and horizontal gene exchange lead to constant diversification of meningococcal populations during clonal spread. Maintaining a high genomic diversity may be an evolutionary strategy of meningococci that increases chances of fixing occasionally new highly successful "fit genotypes". We have performed a longitudinal study of meningococcal carriage and disease in northern Ghana by analyzing cerebrospinal fluid samples from all suspected meningitis cases and monitoring carriage of meningococci by twice yearly colonization surveys. In the framework of this study, we observed complete replacement of an A: sequence types (ST)-2859 clone by a W: ST-2881 clone. However, after a gap of 1 year, A: ST-2859 meningococci re-emerged both as colonizer and meningitis causing agent. Our whole genome sequencing analyses compared the A population isolated prior to the W colonization and disease wave with the re-emerging A meningococci. This analysis revealed expansion of one clone differing in only one nonsynonymous SNP from several isolates already present in the original A: ST-2859 population. The colonization bottleneck caused by the competing W meningococci thus resulted in a profound reduction in genomic diversity of the A meningococcal population.
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http://dx.doi.org/10.1093/gbe/evy152DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6110524PMC
August 2018

Comparative genomics of Mycobacterium africanum Lineage 5 and Lineage 6 from Ghana suggests distinct ecological niches.

Sci Rep 2018 07 26;8(1):11269. Epub 2018 Jul 26.

Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Accra, Ghana.

Mycobacterium africanum (Maf) causes a substantial proportion of human tuberculosis in some countries of West Africa, but little is known on this pathogen. We compared the genomes of 253 Maf clinical isolates from Ghana, including N = 175 Lineage 5 (L5) and N = 78 Lineage 6 (L6). We found that the genomic diversity of L6 was higher than in L5 despite the smaller sample size. Regulatory proteins appeared to evolve neutrally in L5 but under purifying selection in L6. Even though over 90% of the human T cell epitopes were conserved in both lineages, L6 showed a higher ratio of non-synonymous to synonymous single nucleotide variation in these epitopes overall compared to L5. Of the 10% human T cell epitopes that were variable, most carried mutations that were lineage-specific. Our findings indicate that Maf L5 and L6 differ in some of their population genomic characteristics, possibly reflecting different selection pressures linked to distinct ecological niches.
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http://dx.doi.org/10.1038/s41598-018-29620-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6062541PMC
July 2018

Global Scale Dissemination of ST93: A Divergent Epidemic Lineage That Has Recently Emerged From Remote Northern Australia.

Front Microbiol 2018 9;9:1453. Epub 2018 Jul 9.

Global and Tropical Health Division, Menzies School of Health Research, Darwin, NT, Australia.

In Australia, community-associated methicillin-resistant (MRSA) lineage sequence type (ST) 93 has rapidly risen to dominance since being described in the early 1990s. We examined 459 ST93 genome sequences from Australia, New Zealand, Samoa, and Europe to investigate the evolutionary history of ST93, its emergence in Australia and subsequent spread overseas. Comparisons with other genomes indicate that ST93 is an early diverging and recombinant lineage, comprising of segments from the ST59/ST121 lineage and from a divergent but currently unsampled Staphylococcal population. However, within extant ST93 strains limited genetic diversity was apparent with the most recent common ancestor dated to 1977 (95% highest posterior density 1973-1981). An epidemic ST93 population arose from a methicillin-susceptible progenitor in remote Northern Australia, which has a proportionally large Indigenous population, with documented overcrowded housing and a high burden of skin infection. Methicillin-resistance was acquired three times in these regions, with a clade harboring a staphylococcal cassette chromosome (SCC) IVa expanding and spreading to Australia's east coast by 2000. We observed sporadic and non-sustained introductions of ST93-MRSA-IVa to the United Kingdom. In contrast, in New Zealand, ST93-MRSA-IVa was sustainably transmitted with clonal expansion within the Pacific Islander population, who experience similar disadvantages as Australian Indigenous populations. ST93 has a highly recombinant genome including portions derived from an early diverging population. Our findings highlight the need to understand host population factors in the emergence and spread of antimicrobial resistant community pathogens.
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http://dx.doi.org/10.3389/fmicb.2018.01453DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6047344PMC
July 2018

Public health surveillance of multidrug-resistant clones of Neisseria gonorrhoeae in Europe: a genomic survey.

Lancet Infect Dis 2018 07 15;18(7):758-768. Epub 2018 May 15.

WHO Collaborating Centre for Gonorrhoea and Other Sexually Transmitted Infections, Department of Laboratory Medicine, Clinical Microbiology, Faculty of Medicine and Health, Örebro University Hospital, Örebro, Sweden. Electronic address:

Background: Traditional methods for molecular epidemiology of Neisseria gonorrhoeae are suboptimal. Whole-genome sequencing (WGS) offers ideal resolution to describe population dynamics and to predict and infer transmission of antimicrobial resistance, and can enhance infection control through linkage with epidemiological data. We used WGS, in conjunction with linked epidemiological and phenotypic data, to describe the gonococcal population in 20 European countries. We aimed to detail changes in phenotypic antimicrobial resistance levels (and the reasons for these changes) and strain distribution (with a focus on antimicrobial resistance strains in risk groups), and to predict antimicrobial resistance from WGS data.

Methods: We carried out an observational study, in which we sequenced isolates taken from patients with gonorrhoea from the European Gonococcal Antimicrobial Surveillance Programme in 20 countries from September to November, 2013. We also developed a web platform that we used for automated antimicrobial resistance prediction, molecular typing (N gonorrhoeae multi-antigen sequence typing [NG-MAST] and multilocus sequence typing), and phylogenetic clustering in conjunction with epidemiological and phenotypic data.

Findings: The multidrug-resistant NG-MAST genogroup G1407 was predominant and accounted for the most cephalosporin resistance, but the prevalence of this genogroup decreased from 248 (23%) of 1066 isolates in a previous study from 2009-10 to 174 (17%) of 1054 isolates in this survey in 2013. This genogroup previously showed an association with men who have sex with men, but changed to an association with heterosexual people (odds ratio=4·29). WGS provided substantially improved resolution and accuracy over NG-MAST and multilocus sequence typing, predicted antimicrobial resistance relatively well, and identified discrepant isolates, mixed infections or contaminants, and multidrug-resistant clades linked to risk groups.

Interpretation: To our knowledge, we provide the first use of joint analysis of WGS and epidemiological data in an international programme for regional surveillance of sexually transmitted infections. WGS provided enhanced understanding of the distribution of antimicrobial resistance clones, including replacement with clones that were more susceptible to antimicrobials, in several risk groups nationally and regionally. We provide a framework for genomic surveillance of gonococci through standardised sampling, use of WGS, and a shared information architecture for interpretation and dissemination by use of open access software.

Funding: The European Centre for Disease Prevention and Control, The Centre for Genomic Pathogen Surveillance, Örebro University Hospital, and Wellcome.
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http://dx.doi.org/10.1016/S1473-3099(18)30225-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010626PMC
July 2018

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study.

Wellcome Open Res 2018 23;3:33. Epub 2018 Mar 23.

Infection Genomics, Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.

: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made. : We simulated data from a defined "true tree" using a realistic evolutionary model. We built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from alignments to compare individual core gene trees to a core genome tree. : We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other. : We recommend three approaches, depending on requirements for accuracy and computational time. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology. We have publicly released our simulated data and code to enable further comparisons.
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http://dx.doi.org/10.12688/wellcomeopenres.14265.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5930550PMC
March 2018

Genomic evidence that the live Chlamydia abortus vaccine strain 1B is not attenuated and has the potential to cause disease.

Vaccine 2018 06;36(25):3593-3598

Infection Genomics, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, United Kingdom.

Background: The live, temperature-attenuated vaccine strain 1B of Chlamydia abortus, the aetiological agent of ovine enzootic abortion (OEA), has been implicated in cases of vaccine breakdown. The aim of this study was to understand the nature of this attenuation through sequencing of the vaccine parent strain (AB7) and the derived mutant strains 1B and 1H, as well as to clarify the role of the vaccine strain in causing disease through comparative whole genome analysis.

Methods: Whole genome sequencing was performed on: vaccine parent strain AB7; N-methyl-N'-nitro-N-nitrosoguanidine (NTG)-induced temperature attenuated mutant strain 1B grown from the commercial live vaccines Cevac Chlamydia and Enzovax; strain 1H a reverted NTG mutant; and 5 strains isolated from cases of OEA originating from animals from the original vaccine safety trial (2 strains) or from vaccinated ewes or ewes exposed to vaccinated animals (3 strains).

Results: We confirmed that AB7 is in a different lineage from the reference strain S26/3. The genome of vaccine strain 1B contains ten single nucleotide polymorphisms (SNPs) created by the NTG treatment, which are identical to those found in strain 1H. The strains from OEA cases also cluster phylogenetically very tightly with these vaccine strains.

Conclusions: The results show that C. abortus vaccine strain 1B has an identical genome sequence to the non-attenuated "reverted mutant" strain 1H. Thus, the protection of the 1B vaccine is unlikely to be due to the NTG induced SNPs and is more likely caused by the administration of high doses of C. abortus elementary bodies that stimulate protective immunity. Vaccine-identical strains were also isolated from cases of disease, as well as strains which had acquired 1-3 SNPs, including an animal that had not been vaccinated with either of the commercial live OEA vaccines, indicating that the 1B vaccine strain may be circulating and causing disease.
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http://dx.doi.org/10.1016/j.vaccine.2018.05.042DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005232PMC
June 2018

ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads.

Microb Genom 2017 10 4;3(10):e000131. Epub 2017 Sep 4.

1​Infection Genomics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK.

Antimicrobial resistance (AMR) is one of the major threats to human and animal health worldwide, yet few high-throughput tools exist to analyse and predict the resistance of a bacterial isolate from sequencing data. Here we present a new tool, ARIBA, that identifies AMR-associated genes and single nucleotide polymorphisms directly from short reads, and generates detailed and customizable output. The accuracy and advantages of ARIBA over other tools are demonstrated on three datasets from Gram-positive and Gram-negative bacteria, with ARIBA outperforming existing methods.
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http://dx.doi.org/10.1099/mgen.0.000131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695208PMC
October 2017

Phandango: an interactive viewer for bacterial population genomics.

Bioinformatics 2018 Jan;34(2):292-293

Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK.

Summary: Fully exploiting the wealth of data in current bacterial population genomics datasets requires synthesizing and integrating different types of analysis across millions of base pairs in hundreds or thousands of isolates. Current approaches often use static representations of phylogenetic, epidemiological, statistical and evolutionary analysis results that are difficult to relate to one another. Phandango is an interactive application running in a web browser allowing fast exploration of large-scale population genomics datasets combining the output from multiple genomic analysis methods in an intuitive and interactive manner.

Availability And Implementation: Phandango is a web application freely available for use at www.phandango.net and includes a diverse collection of datasets as examples. Source code together with a detailed wiki page is available on GitHub at https://github.com/jameshadfield/phandango.
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http://dx.doi.org/10.1093/bioinformatics/btx610DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860215PMC
January 2018

Emergence and genomic diversification of a virulent serogroup W:ST-2881(CC175) clone in the African meningitis belt.

Microb Genom 2017 08 21;3(8):e000120. Epub 2017 Jun 21.

1​Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051 Basel, Switzerland.

Countries of the African 'meningitis belt' are susceptible to meningococcal meningitis outbreaks. While in the past major epidemics have been primarily caused by serogroup A meningococci, W strains are currently responsible for most of the cases. After an epidemic in Mecca in 2000, W:ST-11 strains have caused many outbreaks worldwide. An unrelated W:ST-2881 clone was described for the first time in 2002, with the first meningitis cases caused by these bacteria reported in 2003. Here we describe results of a comparative whole-genome analysis of 74 W:ST-2881 strains isolated within the framework of two longitudinal colonization and disease studies conducted in Ghana and Burkina Faso. Genomic data indicate that the W:ST-2881 clone has emerged from Y:ST-175(CC175) bacteria by capsule switching. The circulating W:ST-2881 populations were composed of a variety of closely related but distinct genomic variants with no systematic differences between colonization and disease isolates. Two distinct and geographically clustered phylogenetic clonal variants were identified in Burkina Faso and a third in Ghana. On the basis of the presence or absence of 17 recombination fragments, the Ghanaian variant could be differentiated into five clusters. All 25 Ghanaian disease isolates clustered together with 23 out of 40 Ghanaian isolates associated with carriage within one cluster, indicating that W:ST-2881 clusters differ in virulence. More than half of the genes affected by horizontal gene transfer encoded proteins of the 'cell envelope' and the 'transport/binding protein' categories, which indicates that exchange of non-capsular antigens plays an important role in immune evasion.
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http://dx.doi.org/10.1099/mgen.0.000120DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5610715PMC
August 2017

Genomic epidemiology of a national outbreak of post-surgical wound infections in Brazil.

Microb Genom 2017 05 3;3(5):e000111. Epub 2017 May 3.

1​Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.

An epidemic of post-surgical wound infections, caused by a non-tuberculous mycobacterium, has been on-going in Brazil. It has been unclear whether one or multiple lineages are responsible and whether their wide geographical distribution across Brazil is due to spread from a single point source or is the result of human-mediated transmission. 188 isolates, collected from nine Brazilian states, were whole genome sequenced and analysed using phylogenetic and comparative genomic approaches. The isolates from Brazil formed a single clade, which was estimated to have emerged in 2003. We observed temporal and geographic structure within the lineage that enabled us to infer the movement of sub-lineages across Brazil. The genome size of the Brazilian lineage was reduced relative to most strains in the three subspecies of and contained a novel plasmid, pMAB02, in addition to the previously described pMAB01 plasmid. One lineage, which emerged just prior to the initial outbreak, is responsible for the epidemic of post-surgical wound infections in Brazil. Phylogenetic analysis indicates that multiple transmission events led to its spread. The presence of a novel plasmid and the reduced genome size suggest that the lineage has undergone adaptation to the surgical niche.
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http://dx.doi.org/10.1099/mgen.0.000111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562415PMC
May 2017