135 results found
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
<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
Didelot X, Pouwels KB, 2019, Machine-learning-assisted selection of antibiotic prescription, NATURE MEDICINE, Vol: 25, Pages: 1033-1034, ISSN: 1078-8956
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
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.
Challagundla L, Luo X, Tickler IA, et al., 2018, Range Expansion and the Origin of USA300 North American Epidemic Methicillin-Resistant Staphylococcus aureus., mBio, Vol: 9, ISSN: 2150-7511
The USA300 North American epidemic (USA300-NAE) clone of methicillin-resistant Staphylococcus aureus has caused a wave of severe skin and soft tissue infections in the United States since it emerged in the early 2000s, but its geographic origin is obscure. Here we use the population genomic signatures expected from the serial founder effects of a geographic range expansion to infer the origin of USA300-NAE and identify polymorphisms associated with its spread. Genome sequences from 357 isolates from 22 U.S. states and territories and seven other countries are compared. We observe two significant signatures of range expansion, including decreases in genetic diversity and increases in derived allele frequency with geographic distance from the Pennsylvania region. These signatures account for approximately half of the core nucleotide variation of this clone, occur genome wide, and are robust to heterogeneity in temporal sampling of isolates, human population density, and recombination detection methods. The potential for positive selection of a gyrA fluoroquinolone resistance allele and several intergenic regions, along with a 2.4 times higher recombination rate in a resistant subclade, is noted. These results are the first to show a pattern of genetic variation that is consistent with a range expansion of an epidemic bacterial clone, and they highlight a rarely considered but potentially common mechanism by which genetic drift may profoundly influence bacterial genetic variation.IMPORTANCE The process of geographic spread of an origin population by a series of smaller populations can result in distinctive patterns of genetic variation. We detect these patterns for the first time with an epidemic bacterial clone and use them to uncover the clone's geographic origin and variants associated with its spread. We study the USA300 clone of methicillin-resistant Staphylococcus aureus, which was first noticed in the early 2000s and subsequently became the leading cause of skin
Whittles L, White PJ, Didelot X, 2017, Estimating the fitness cost and benefit of cefixime resistance in Neisseria gonorrhoeae to inform prescription policy: a modelling study, PLoS Medicine, Vol: 14, ISSN: 1549-1277
BackgroundGonorrhoea is one of the most common bacterial sexually transmitted infections in England. Over 41,000 cases were recorded in 2015, more than half of which occurred in men who have sex with men (MSM). As the bacterium has developed resistance to each first-line antibiotic in turn, we need an improved understanding of fitness benefits and costs of antibiotic resistance to inform control policy and planning. Cefixime was recommended as a single-dose treatment for gonorrhoea from 2005 to 2010, during which time resistance increased, and subsequently declined.Methods and findingsWe developed a stochastic compartmental model representing the natural history and transmission of cefixime-sensitive and cefixime-resistant strains of Neisseria gonorrhoeae in MSM in England, which was applied to data on diagnoses and prescriptions between 2008 and 2015. We estimated that asymptomatic carriers play a crucial role in overall transmission dynamics, with 37% (95% credible interval CrI 24%–52%) of infections remaining asymptomatic and untreated, accounting for 89% (95% CrI 82%–93%) of onward transmission. The fitness cost of cefixime resistance in the absence of cefixime usage was estimated to be such that the number of secondary infections caused by resistant strains is only about half as much as for the susceptible strains, which is insufficient to maintain persistence. However, we estimated that treatment of cefixime-resistant strains with cefixime was unsuccessful in 83% (95% CrI 53%–99%) of cases, representing a fitness benefit of resistance. This benefit was large enough to counterbalance the fitness cost when 31% (95% CrI 26%–36%) of cases were treated with cefixime, and when more than 55% (95% CrI 44%–66%) of cases were treated with cefixime, the resistant strain had a net fitness advantage over the susceptible strain. Limitations include sparse data leading to large intervals on key model parameters and necessary assumptions in the m
Pandey AK, Cleary DW, Laver JR, et al., 2017, Neisseria lactamica Y92-1009 complete genome sequence, STANDARDS IN GENOMIC SCIENCES, Vol: 12, ISSN: 1944-3277
We present the high quality, complete genome assembly of Neisseria lactamica Y92–1009 used to manufacture an outer membrane vesicle (OMV)-based vaccine, and a member of the Neisseria genus. The strain is available on request from the Public Health England Meningococcal Reference Unit. This Gram negative, dipplococcoid bacterium is an organism of worldwide clinical interest because human nasopharyngeal carriage is related inversely to the incidence of meningococcal disease, caused by Neisseria meningitidis. The organism sequenced was isolated during a school carriage survey in Northern Ireland in 1992 and has been the subject of a variety of laboratory and clinical studies. Four SMRT cells on a RSII machine by Pacific Biosystems were used to produce a complete, closed genome assembly. Sequence data were obtained for a total of 30,180,391 bases from 2621 reads and assembled using the HGAP algorithm. The assembly was corrected using short reads obtained from an Illumina HiSeq 2000instrument. This resulted in a 2,146,723 bp assembly with approximately 460 fold mean coverage depth and a GC ratio of 52.3%.
Rosner BM, Schielke A, Didelot X, et al., 2017, A combined case-control and molecular source attribution study of human Campylobacter infections in Germany, 2011-2014, SCIENTIFIC REPORTS, Vol: 7, ISSN: 2045-2322
Campylobacter infection is the most commonly notified bacterial enteritis in Germany. We performed a large combined case-control and source attribution study (Nov 2011-Feb 2014) to identify risk factors for sporadic intestinal Campylobacter infections and to determine the relative importance of various animal sources for human infections in Germany. We conducted multivariable logistic regression analysis to identify risk factors. Source attribution analysis was performed using the asymmetric island model based on MLST data of human and animal/food isolates. As animal sources we considered chicken, pig, pet dog or cat, cattle, and poultry other than chicken. Consumption of chicken meat and eating out were the most important risk factors for Campylobacter infections. Additional risk factors were preparation of poultry meat in the household; preparation of uncooked food and raw meat at the same time; contact with poultry animals; and the use of gastric acid inhibitors. The mean probability of human C. jejuni isolates to originate from chickens was highest (74%), whereas pigs were a negligible source for C. jejuni infections. Human C. coli isolates were likely to originate from chickens (56%) or from pigs (32%). Efforts need to be intensified along the food chain to reduce Campylobacter load, especially on chicken meat.
Didelot X, Whittles L, Hall I, 2017, Model-based analysis of an outbreak of bubonic plague in Cairo in 1801, Interface, Vol: 14, ISSN: 0303-3902
Bubonic plague has caused three deadly pandemics in human history: from the mid-sixth to mid-eighth century, from the mid-fourteenth to the mid-eighteenth century and from the end of the nineteenth until the mid-twentieth century. Between the second and the third pandemics, plague was causing sporadic outbreaks in only a few countries in the Middle East, including Egypt. Little is known about this historical phase of plague, even though it represents the temporal, geographical and phylogenetic transition between the second and third pandemics. Here we analysed in detail an outbreak of plague that took place in Cairo in 1801, and for which epidemiological data are uniquely available thanks to the presence of medical officers accompanying the Napoleonic expedition into Egypt at that time. We propose a new stochastic model describing how bubonic plague outbreaks unfold in both rat and human populations, and perform Bayesian inference under this model using a particle Markov chain Monte Carlo. Rat carcasses were estimated to be infectious for approximately 4 days after death, which is in good agreement with local observations on the survival of infectious rat fleas. The estimated transmission rate between rats implies a basic reproduction number R0 of approximately 3, causing the collapse of the rat population in approximately 100 days. Simultaneously, the force of infection exerted by each infected rat carcass onto the human population increases progressively by more than an order of magnitude. We also considered human-to-human transmission via pneumonic plague or human specific vectors, but found this route to account for only a small fraction of cases and to be significantly below the threshold required to sustain an outbreak.
Mostowy RJ, Croucher NJ, De Maio N, et al., 2017, Pneumococcal capsule synthesis locus cps as evolutionary hotspot with potential to generate novel serotypes by recombination, Molecular Biology and Evolution, Vol: 34, Pages: 2537-2554, ISSN: 1537-1719
Diversity of the polysaccharide capsule in Streptococcus pneumoniae -- main surface antigen and the target of the currently used pneumococcal vaccines -- constitutes a major obstacle in eliminating pneumococcal disease. Such diversity is genetically encoded by almost 100 variants of the capsule biosynthesis locus, cps. However, the evolutionary dynamics of the capsule remains not fully understood. Here, using genetic data from 4,519 bacterial isolates, we found cps to be an evolutionary hotspot with elevated substitution and recombination rates. These rates were a consequence of relaxed purifying selection and positive, diversifying selection acting at this locus, supporting the hypothesis that the capsule has an increased potential to generate novel diversity compared to the rest of the genome. Diversifying selection was particularly evident in the region of wzd/wze genes, which are known to regulate capsule expression and hence the bacterium's ability to cause disease. Using a novel, capsule-centred approach, we analysed the evolutionary history of twelve major serogroups. Such analysis revealed their complex diversification scenarios, which were principally driven by recombination with other serogroups and other streptococci. Patterns of recombinational exchanges between serogroups could not be explained by serotype frequency alone, thus pointing to non-random associations between co-colonising serotypes. Finally, we discovered a previously unobserved mosaic serotype 39X, which was confirmed to carry a viable and structurally novel capsule. Adding to previous discoveries of other mosaic capsules in densely sampled collections, these results emphasise the strong adaptive potential of the bacterium by its ability to generate novel antigenic diversity by recombination.
Klinkenberg D, Backer JA, Didelot X, et al., 2017, Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks, Plos Computational Biology, Vol: 13, ISSN: 1553-7358
Whole-genome sequencing of pathogens from host samples becomes more and more routine during infectious disease outbreaks. These data provide information on possible transmission events which can be used for further epidemiologic analyses, such as identification of risk factors for infectivity and transmission. However, the relationship between transmission events and sequence data is obscured by uncertainty arising from four largely unobserved processes: transmission, case observation, within-host pathogen dynamics and mutation. To properly resolve transmission events, these processes need to be taken into account. Recent years have seen much progress in theory and method development, but existing applications make simplifying assumptions that often break up the dependency between the four processes, or are tailored to specific datasets with matching model assumptions and code. To obtain a method with wider applicability, we have developed a novel approach to reconstruct transmission trees with sequence data. Our approach combines elementary models for transmission, case observation, within-host pathogen dynamics, and mutation, under the assumption that the outbreak is over and all cases have been observed. We use Bayesian inference with MCMC for which we have designed novel proposal steps to efficiently traverse the posterior distribution, taking account of all unobserved processes at once. This allows for efficient sampling of transmission trees from the posterior distribution, and robust estimation of consensus transmission trees. We implemented the proposed method in a new R package phybreak. The method performs well in tests of both new and published simulated data. We apply the model to five datasets on densely sampled infectious disease outbreaks, covering a wide range of epidemiological settings. Using only sampling times and sequences as data, our analyses confirmed the original results or improved on them: the more realistic infection times place more conf
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