141 results found
Rodriguez Manzano J, Moser N, Malpartida Cardenas K, et al., 2020, Rapid detection of mobilized colistin resistance using a nucleic acid based lab-on-a-chip diagnostic system, Scientific Reports, Vol: 10, ISSN: 2045-2322
The increasing prevalence of antimicrobial resistance is a serious threat to global public health. One of the most concerning trends is the rapid spread of Carbapenemase-Producing Organisms (CPO), where colistin has become the last-resort antibiotic treatment. The emergence of colistin resistance, including the spread of mobilized colistin resistance (mcr) genes, raises the possibility of untreatable bacterial infections and motivates the development of improved diagnostics for the detection of colistin-resistant organisms. This work demonstrates a rapid response for detecting the most recently reported mcr gene, mcr−9, using a portable and affordable lab-on-a-chip (LoC) platform, offering a promising alternative to conventional laboratory-based instruments such as real-time PCR (qPCR). The platform combines semiconductor technology, for non-optical real-time DNA sensing, with a smartphone application for data acquisition, visualization and cloud connectivity. This technology is enabled by using loop-mediated isothermal amplification (LAMP) as the chemistry for targeted DNA detection, by virtue of its high sensitivity, specificity, yield, and manageable temperature requirements. Here, we have developed the first LAMP assay for mcr−9 - showing high sensitivity (down to 100 genomic copies/reaction) and high specificity (no cross-reactivity with other mcr variants). This assay is demonstrated through supporting a hospital investigation where we analyzed nucleic acids extracted from 128 carbapenemase-producing bacteria isolated from clinical and screening samples and found that 41 carried mcr−9 (validated using whole genome sequencing). Average positive detection times were 6.58 ± 0.42 min when performing the experiments on a conventional qPCR instrument (n = 41). For validating the translation of the LAMP assay onto a LoC platform, a subset of the samples were tested (n = 20), showing average detection times o
Volz E, Wiuf C, Grad YH, et al., 2020, Identification of hidden population structure in time-scaled phylogenies, Systematic Biology, ISSN: 1063-5157
Abstract Population structure influences genealogical patterns, however data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealised genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial pol sequences. This revealed the presence of clades which had grown rapidly in the recent past, and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome Neisseria gonorrhoeae sequences. We find that population structure detected using these methods closely overlaps with th
Wang H, Yang C, Sun Z, et al., 2020, Genomic epidemiology of Vibrio cholerae reveals the regional and global spread of two epidemic non-toxigenic lineages, PLOS NEGLECTED TROPICAL DISEASES, Vol: 14, ISSN: 1935-2735
Wang H, Yang C, Sun Z, et al., 2020, Genomic epidemiology of Vibrio cholerae reveals the regional and global spread of two epidemic non-toxigenic lineages., PLoS Negl Trop Dis, Vol: 14
Non-toxigenic Vibrio cholerae isolates have been found associated with diarrheal disease globally, however, the global picture of non-toxigenic infections is largely unknown. Among non-toxigenic V. cholerae, ctxAB negative, tcpA positive (CNTP) isolates have the highest risk of disease. From 2001 to 2012, 71 infectious diarrhea cases were reported in Hangzhou, China, caused by CNTP serogroup O1 isolates. We sequenced 119 V. cholerae genomes isolated from patients, carriers and the environment in Hangzhou between 2001 and 2012, and compared them with 850 publicly available global isolates. We found that CNTP isolates from Hangzhou belonged to two distinctive lineages, named L3b and L9. Both lineages caused disease over a long time period with usually mild or moderate clinical symptoms. Within Hangzhou, the spread route of the L3b lineage was apparently from rural to urban areas, with aquatic food products being the most likely medium. Both lineages had been previously reported as causing local endemic disease in Latin America, but here we show that global spread of them has occurred, with the most likely origin of L3b lineage being in Central Asia. The L3b lineage has spread to China on at least three occasions. Other spread events, including from China to Thailand and to Latin America were also observed. We fill the missing links in the global spread of the two non-toxigenic serogroup O1 V. cholerae lineages that can cause human infection. The results are important for the design of future disease control strategies: surveillance of V. cholerae should not be limited to ctxAB positive strains.
Whittles LK, White PJ, Didelot X, 2020, Assessment of the potential of vaccination to combat antibiotic resistance in gonorrhea: a modeling analysis to determine preferred product characteristics, Clinical Infectious Diseases, ISSN: 1058-4838
BACKGROUND: Gonorrhea incidence is increasing rapidly in many countries, whilst antibiotic resistance is making treatment more difficult. Combined with evidence that MeNZB and Bexsero meningococcal vaccines are likely partially-protective against gonorrhea, this has renewed interest in a gonococcal vaccine, and several candidates are in development. Key questions are how protective a vaccine needs to be, how long protection needs to last, and how should it be targeted. We assessed vaccination's potential impact, and the feasibility of achieving WHO's target 90% reduction in gonorrhea incidence 2016-2030, by comparing realistic vaccination strategies under a range of scenarios of vaccine efficacy and duration of protection, and emergence of extensively-resistant gonorrhea. METHODS: We developed a stochastic transmission-dynamic model, incorporating asymptomatic and symptomatic infection and heterogeneous sexual behavior in men-who-have-sex-with-men (MSM). We used data from England, which has a comprehensive, consistent nationwide surveillance system. Using particle Markov Chain Monte Carlo methods we fitted the model to gonorrhea incidence in 2008-17, and then used Bayesian forecasting to examine an extensive range of scenarios. RESULTS: Even in the worst-case scenario of untreatable infection emerging, the WHO target is achievable if all MSM attending sexual health clinics receive a vaccine offering ≥52% protection for ≥6 years. A vaccine conferring 31% protection (as estimated for MeNZB) for 2-4 years, could reduce incidence in 2030 by 45% in the worst-case scenario, and by 75% if >70% of resistant gonorrhea remains treatable. CONCLUSIONS: Even a partially-protective vaccine, delivered through a realistic targeting strategy, could substantially reduce gonorrhea incidence, despite antibiotic resistance.
Lassalle F, Dastgheib SMM, Zhao F-J, et al., 2019, Phylogenomic analysis reveals the basis of adaptation of Pseudorhizobium species to extreme environments
<jats:title>Abstract</jats:title><jats:p>The family <jats:italic>Rhizobiaceae</jats:italic> includes many genera of soil bacteria, often isolated for their association with plants. Herein, we investigate the genomic diversity of a group of <jats:italic>Rhizobium</jats:italic> species and unclassified strains isolated from atypical environments, including seawater, rock matrix or polluted soil. Based on whole-genome similarity and core genome phylogeny, we show that this group corresponds to the genus <jats:italic>Pseudorhizobium.</jats:italic> We thus reclassify <jats:italic>Rhizobium halotolerans, R. marinum, R. flavum</jats:italic> and <jats:italic>R. endolithicum</jats:italic> as <jats:italic>P. halotolerans</jats:italic> comb. nov., <jats:italic>P. marinum</jats:italic> comb. nov.<jats:italic>, P. flavum</jats:italic> comb. nov. and <jats:italic>R. endolithicum</jats:italic> comb. nov., respectively, and show that <jats:italic>P. pelagicum</jats:italic> is a synonym of <jats:italic>P. marinum</jats:italic>. We also delineate a new chemolithoautotroph species, <jats:italic>P. banfieldiae</jats:italic> sp. nov., whose type strain is NT-26<jats:sup>T</jats:sup> (= DSM 106348<jats:sup>T</jats:sup> = CFBP 8663<jats:sup>T</jats:sup>). This genome-based classification was supported by a chemotaxonomic comparison, with gradual taxonomic resolution provided by fatty acid, protein and metabolic profiles. In addition, we used a phylogenetic approach to infer scenarios of duplication, horizontal transfer and loss for all genes in the <jats:italic>Pseudorhizobium</jats:italic> pangenome. We thus identify the key functions associated with the diversification of each species and higher clades, shedding light on the mechanisms of adaptation to their respective ecological
Lassalle F, Veber P, Jauneikaite E, et al., 2019, Automated reconstruction of all gene histories in large bacterial pangenome datasets and search for co-evolved gene modules with Pantagruel
<jats:title>Abstract</jats:title><jats:p>The availability of bacterial pangenome data grows exponentially, requiring efficient new methods of analysis. Currently popular approaches for the fast comparison of genomes have the drawback of not being based on explicit evolutionary models of diversification. Making sense of bacterial genome evolution, and notably in the accessory genome, requires however to take into account the complex processes by which the genomes evolve. Here we present the <jats:italic>Pantagruel</jats:italic> bioinformatic software pipeline, which enables the construction of a complete bacterial pangenome database geared towards the inference of gene evolution scenarios using gene tree/species tree reconciliation. <jats:italic>Pantagruel</jats:italic> is a modular pipeline that combines state-of-the-art external software with unique new methods. It can be executed with no supervision to perform a standard pangenome analysis, or be configured by advanced users to integrate methods of choice. A relational database underlies its data structure, allowing efficient retrieval of the large-scale data generated by integrative analyses of pangenome evolutionary history. From the reconstructed gene evolution scenarios, two main outputs are derived: firstly the gene tree-aware assignation of orthology, allowing the fine analysis of gene gain and loss history over the species phylogeny, and secondly a network of gene-to-gene association based on correlated events in scenarios of gene evolution, leading to the definition of co-evolved gene modules. <jats:italic>Pantagruel</jats:italic> is available as an open source software package at <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/flass/pantagruel">https://github.com/flass/pantagruel</jats:ext-link>.</jats:p>
Zhao L, Chen H, Didelot X, et al., 2019, Co-existence of multiple distinct lineages in Vibrio parahaemolyticus serotype O4:K12., Microb Genom
Criscuolo A, Issenhuth-Jeanjean S, Didelot X, et al., 2019, The speciation and hybridization history of the genus Salmonella, MICROBIAL GENOMICS, Vol: 5, ISSN: 2057-5858
Volz EM, Wiuf C, Grad YH, et al., 2019, Identification of hidden population structure in time-scaled phylogenies, Publisher: Cold Spring Harbor Laboratory
<jats:title>Abstract</jats:title><jats:p>Population structure influences genealogical patterns, however data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealised genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial <jats:italic>pol</jats:italic> sequences. This revealed the presence of clades which had grown rapidly in the recent past, and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome <jats:italic>Neisseria go
Ozer EA, Nnah E, Didelot X, et al., 2019, The Population Structure of Pseudomonas aeruginosa Is Characterized by Genetic Isolation of exoU plus and exoS plus Lineages, GENOME BIOLOGY AND EVOLUTION, Vol: 11, Pages: 1780-1796, ISSN: 1759-6653
Didelot X, Pouwels KB, 2019, Machine-learning-assisted selection of antibiotic prescription, NATURE MEDICINE, Vol: 25, Pages: 1033-1034, ISSN: 1078-8956
Ailloud F, Didelot X, Woltemate S, et al., 2019, Within-host evolution of Helicobacter pylori shaped by niche-specific adaptation, intragastric migrations and selective sweeps, NATURE COMMUNICATIONS, Vol: 10, ISSN: 2041-1723
Moniri A, Rodriguez-Manzano J, Malpartida-Cardenas K, et al., 2019, Framework for DNA quantification and outlier detection using multidimensional standard curves, Analytical Chemistry, Vol: 91, Pages: 7426-7434, ISSN: 0003-2700
Real-time PCR is a highly sensitive and powerful technology for the quantification of DNA and has become the method of choice in microbiology, bioengineering, and molecular biology. Currently, the analysis of real-time PCR data is hampered by only considering a single feature of the amplification profile to generate a standard curve. The current “gold standard” is the cycle-threshold (Ct) method which is known to provide poor quantification under inconsistent reaction efficiencies. Multiple single-feature methods have been developed to overcome the limitations of the Ct method; however, there is an unexplored area of combining multiple features in order to benefit from their joint information. Here, we propose a novel framework that combines existing standard curve methods into a multidimensional standard curve. This is achieved by considering multiple features together such that each amplification curve is viewed as a point in a multidimensional space. Contrary to only considering a single-feature, in the multidimensional space, data points do not fall exactly on the standard curve, which enables a similarity measure between amplification curves based on distances between data points. We show that this framework expands the capabilities of standard curves in order to optimize quantification performance, provide a measure of how suitable an amplification curve is for a standard, and thus automatically detect outliers and increase the reliability of quantification. Our aim is to provide an affordable solution to enhance existing diagnostic settings through maximizing the amount of information extracted from conventional instruments.
Eyre DW, Didelot X, Buckley AM, et al., 2019, Clostridium difficile trehalose metabolism variants are common and not associated with adverse patient outcomes when variably present in the same lineage, EBIOMEDICINE, Vol: 43, Pages: 347-355, ISSN: 2352-3964
van Dorp L, Wang Q, Shaw LP, et al., 2019, Rapid phenotypic evolution in multidrug-resistant Klebsiella pneumoniae hospital outbreak strains, MICROBIAL GENOMICS, Vol: 5, ISSN: 2057-5858
Whittles L, White P, Didelot X, 2019, A dynamic power-law sexual network model of gonorrhoea outbreaks, PLoS Computational Biology, Vol: 15, ISSN: 1553-734X
Human networks of sexual contacts are dynamic by nature, with partnerships forming and breaking continuously over time. Sexual behaviours are also highly heterogeneous, so that the number of partners reported by individuals over a given period of time is typically distributed as a power-law. Both the dynamism and heterogeneity of sexual partnerships are likely to have an effect in the patterns of spread of sexually transmitted diseases. To represent these two fundamental properties of sexual networks, we developed a stochastic process of dynamic partnership formation and dissolution, which results in power-law numbers of partners over time. Model parameters can be set to produce realistic conditions in terms of the exponent of the power-law distribution, of the number of individuals without relationships and of the average duration of relationships. Using an outbreak of antibiotic resistant gonorrhoea amongst men have sex with men as a case study, we show that our realistic dynamic network exhibits different properties compared to the frequently used static networks or homogeneous mixing models. We also consider an approximation to our dynamic network model in terms of a much simpler branching process. We estimate the parameters of the generation time distribution and offspring distribution which can be used for example in the context of outbreak reconstruction based on genomic data. Finally, weinvestigate the impact of a range of interventions against gonorrhoea, including increased condom use, more frequent screening and immunisation, concluding that the latter shows great promise to reduce the burden of gonorrhoea, even if the vaccine was only partially effective or applied to only a random subset of the population.
Dingle KE, Didelot X, Quan TP, et al., 2019, A Role for Tetracycline Selection in Recent Evolution of Agriculture-Associated Clostridium difficile PCR Ribotype 078, MBIO, Vol: 10, ISSN: 2150-7511
Didelot X, Croucher NJ, Bentley SD, et al., 2018, Bayesian inference of ancestral dates on bacterial phylogenetic trees, Nucleic Acids Research, Vol: 46, Pages: 1-11, ISSN: 0305-1048
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.
Meric G, Mageiros L, Pensar J, et al., 2018, Disease-associated genotypes of the commensal skin bacterium Staphylococcus epidermidis, NATURE COMMUNICATIONS, Vol: 9, ISSN: 2041-1723
Pandey A, Cleary DW, Laver JR, et al., 2018, Microevolution of Neisseria lactamica during nasopharyngeal colonisation induced by controlled human infection, NATURE COMMUNICATIONS, Vol: 9, ISSN: 2041-1723
Séraphin MN, Didelot X, Nolan DJ, et al., 2018, Genomic investigation of a mycobacterium tuberculosis outbreak involving prison and community cases in Florida, United States, American Journal of Tropical Medicine and Hygiene, Vol: 99, Pages: 867-874, ISSN: 0002-9637
We used whole-genome sequencing to investigate a tuberculosis outbreak involving U.S.-born persons in the prison system and both U.S.- and foreign-born persons in the community in Florida over a 7-year period (2009-2015). Genotyping by spacer oligonucleotide typing and 24-locus mycobacterial interspersed repetitive unit-variable number tandem repeat suggested that the outbreak might be clonal in origin. However, contact tracing could not link the two populations. Through a multidisciplinary approach, we showed that the cluster involved distinct bacterial transmission networks segregated by country of birth. The source strain is of foreign origin and circulated in the local Florida community for more than 20 years before introduction into the prison system. We also identified novel transmission links involving foreign and U.S.-born cases not discovered during contact investigation. Our data highlight the potential for spread of strains originating from outside the United States into U.S. "high-risk" populations (such as prisoners), with subsequent movement back to the general community.
Yahara K, Nakayama S-I, Shimuta K, et al., 2018, Genomic surveillance of Neisseria gonorrhoeae to investigate the distribution and evolution of antimicrobial-resistance determinants and lineages (vol 4, 000205, 2018), MICROBIAL GENOMICS, Vol: 4, ISSN: 2057-5858
Whittles L, White PJ, Paul J, et al., 2018, Epidemiological trends of antibiotic resistant gonorrhoea in the United Kingdom, Antibiotics, Vol: 7, ISSN: 2079-6382
Gonorrhoea is one of the most common sexually-transmitted bacterial infections, globally and in the United Kingdom. The levels of antibiotic resistance in gonorrhoea reported in recent years represent a critical public health issue. From penicillins to cefixime, the gonococcus has become resistant to all antibiotics that have been previously used against it, in each case only a matter of years after introduction as a first-line therapy. After each instance of resistance emergence, the treatment recommendations have required revision, to the point that only a few antibiotics can reliably be prescribed to treat infected individuals. Most countries, including the UK, now recommend that gonorrhoea be treated with a dual therapy combining ceftriaxone and azithromycin. While this treatment is still currently effective for the vast majority of cases, there are concerning signs that this will not always remain the case, and there is no readily apparent alternative. Here, we review the use of antibiotics and epidemiological trends of antibiotic resistance in gonorrhoea from surveillance data over the past 15 years in the UK and describe how surveillance could be improved.
Yahara K, Nakayama S-I, Shimuta K, et al., 2018, Genomic surveillance of Neisseria gonorrhoeae to investigate the distribution and evolution of antimicrobial-resistance determinants and lineages, Microbial Genomics, Vol: 4, ISSN: 2057-5858
The first extensively drug resistant (XDR) Neisseria gonorrhoeae strain with high resistance to the extended-spectrum cephalosporin ceftriaxone was identified in 2009 in Japan, but no other strain with this antimicrobial-resistance profile has been reported since. However, surveillance to date has been based on phenotypic methods and sequence typing, not genome sequencing. Therefore, little is known about the local population structure at the genomic level, and how resistance determinants and lineages are distributed and evolve. We analysed the whole-genome sequence data and the antimicrobial-susceptibility testing results of 204 strains sampled in a region where the first XDR ceftriaxone-resistant N. gonorrhoeae was isolated, complemented with 67 additional genomes from other time frames and locations within Japan. Strains resistant to ceftriaxone were not found, but we discovered a sequence type (ST)7363 sub-lineage susceptible to ceftriaxone and cefixime in which the mosaic penA allele responsible for reduced susceptibility had reverted to a susceptible allele by recombination. Approximately 85 % of isolates showed resistance to fluoroquinolones (ciprofloxacin) explained by linked amino acid substitutions at positions 91 and 95 of GyrA with 99 % sensitivity and 100 % specificity. Approximately 10 % showed resistance to macrolides (azithromycin), for which genetic determinants are less clear. Furthermore, we revealed different evolutionary paths of the two major lineages: single acquisition of penA X in the ST7363-associated lineage, followed by multiple independent acquisitions of the penA X and XXXIV in the ST1901-associated lineage. Our study provides a detailed picture of the distribution of resistance determinants and disentangles the evolution of the two major lineages spreading worldwide.
Volz E, Didelot X, 2018, Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance, Systematic Biology, Vol: 67, Pages: 719-728, ISSN: 1063-5157
Nonparametric population genetic modeling provides a simple and flexible approach for studying demographic history and epidemic dynamics using pathogen sequence data. Existing Bayesian approaches are premised on stochastic processes with stationary increments which may provide an unrealistic prior for epidemic histories which feature extended period of exponential growth or decline. We show that nonparametric models defined in terms of the growth rate of the effective population size can provide a more realistic prior for epidemic history. We propose a nonparametric autoregressive model on the growth rate as a prior for effective population size, which corresponds to the dynamics expected under many epidemic situations. We demonstrate the use of this model within a Bayesian phylodynamic inference framework. Our method correctly reconstructs trends of epidemic growth and decline from pathogen genealogies even when genealogical data are sparse and conventional skyline estimators erroneously predict stable population size. We also propose a regression approach for relating growth rates of pathogen effective population size and time-varying variables that may impact the replicative fitness of a pathogen. The model is applied to real data from rabies virus and Staphylococcus aureus epidemics. We find a close correspondence between the estimated growth rates of a lineage of methicillin-resistant S. aureus and population-level prescription rates ofβ-lactam antibiotics. The new models are implemented in an open source R package called skygrowth which is available at https://github.com/mrc-ide/skygrowth.
Whittles L, Didelot X, Grad Y, et al., 2018, Testing for gonorrhoea should routinely include the pharynx, Lancet Infectious Diseases, Vol: 18, Pages: 716-717, ISSN: 1473-3099
The profile of Kit Fairley by Tony Kirby1 highlighted his work on the potentially important role of kissing among men who have sex with men (MSM) in gonorrhoea transmission. The role of pharyngeal infection in gonorrhoea transmission, and in the emergence and spread of antimicrobial resistance, is poorly characterised, which represents an important knowledge gap.2 Intimate kissing is a risk factor for meningococcal carriage,3 indicating other Neisseria spp can transmit via this route. Pharyngeal gonococcal infection is predominantly asymptomatic, frequently undetected, and often exposed to suboptimal antibiotic concentrations in therapy;2,4 hence infection might be persistent.
Wang R, van Dorp L, Shaw LP, et al., 2018, The global distribution and spread of the mobilized colistin resistance gene mcr-1, NATURE COMMUNICATIONS, Vol: 9, ISSN: 2041-1723
Colistin represents one of the few available drugs for treating infections caused by carbapenem-resistant Enterobacteriaceae. As such, the recent plasmid-mediated spread of the colistin resistance gene mcr-1 poses a significant public health threat, requiring global monitoring and surveillance. Here, we characterize the global distribution of mcr-1 using a data set of 457 mcr-1-positive sequenced isolates. We find mcr-1 in various plasmid types but identify an immediate background common to all mcr-1 sequences. Our analyses establish that all mcr-1 elements in circulation descend from the same initial mobilization of mcr-1 by an ISApl1 transposon in the mid 2000s (2002–2008; 95% highest posterior density), followed by a marked demographic expansion, which led to its current global distribution. Our results provide the first systematic phylogenetic analysis of the origin and spread of mcr-1, and emphasize the importance of understanding the movement of antibiotic resistance genes across multiple levels of genomic organization.
Peters J, Cresswell F, Amor L, et al., 2018, Whole genome sequencing of Neisseria gonorrhoeae reveals transmission clusters involving patients of mixed HIV serostatus, SEXUALLY TRANSMITTED INFECTIONS, Vol: 94, Pages: 138-+, ISSN: 1368-4973
Collins C, Didelot X, 2018, A phylogenetic method to perform genome-wide association studies in microbes that accounts for population structure and recombination, PLoS Computational Biology, Vol: 14, ISSN: 1553-734X
Genome-Wide Association Studies (GWAS) in microbial organisms have the potential to vastly improve the way we understand, manage, and treat infectious diseases. Yet, microbial GWAS methods established thus far remain insufficiently able to capitalise on the growing wealth of bacterial and viral genetic sequence data. Facing clonal population structure and homologous recombination, existing GWAS methods struggle to achieve both the precision necessary to reject spurious findings and the power required to detect associations in microbes. In this paper, we introduce a novel phylogenetic approach that has been tailor-made for microbial GWAS, which is applicable to organisms ranging from purely clonal to frequently recombining, and to both binary and continuous phenotypes. Our approach is robust to the confounding effects of both population structure and recombination, while maintaining high statistical power to detect associations. Thorough testing via application to simulated data provides strong support for the power and specificity of our approach and demonstrates the advantages offered over alternative cluster-based and dimension-reduction methods. Two applications to Neisseria meningitidis illustrate the versatility and potential of our method, confirming previously-identified penicillin resistance loci and resulting in the identification of both well-characterised and novel drivers of invasive disease. Our method is implemented as an open-source R package called treeWAS which is freely available at https://github.com/caitiecollins/treeWAS.
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