Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance

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 of β -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

Model-based analysis of an outbreak of bubonic plague in Cairo in 1801

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

The Landscape of Realized Homologous Recombination in Pathogenic Bacteria

Recombination enhances the adaptive potential of organisms by allowing genetic variants to be tested on multiple genomic backgrounds. Its distribution in the genome can provide insight into the evolutionary forces that underlie traits, such as the emergence of pathogenicity. Here, we examined landscapes of realized homologous recombination of 500 genomes from ten bacterial species and found all species have “hot” regions with elevated rates relative to the genome average. We examined the size, gene content, and chromosomal features associated with these regions and the correlations between closely related species. The recombination landscape is variable and evolves rapidly. For example in Salmonella, only short regions of around 1 kb in length are hot whereas in the closely related species Escherichia coli, some hot regions exceed 100 kb, spanning many genes. Only Streptococcus pyogenes shows evidence for the positive correlation between GC content and recombination that has been reported for several eukaryotes. Genes with function related to the cell surface/membrane are often found in recombination hot regions but E. coli is the only species where genes annotated as “virulence associated” are consistently hotter. There is also evidence that some genes with “housekeeping” functions tend to be overrepresented in cold regions. For example, ribosomal proteins showed low recombination in all of the species. Among specific genes, transferrin-binding proteins are recombination hot in all three of the species in which they were found, and are subject to interspecies recombination

Bacterial microevolution and the Pangenome

The comparison of multiple genome sequences sampled from a bacterial population reveals considerable diversity in both the core and the accessory parts of the pangenome. This diversity can be analysed in terms of microevolutionary events that took place since the genomes shared a common ancestor, especially deletion, duplication, and recombination. We review the basic modelling ingredients used implicitly or explicitly when performing such a pangenome analysis. In particular, we describe a basic neutral phylogenetic framework of bacterial pangenome microevolution, which is not incompatible with evaluating the role of natural selection. We survey the different ways in which pangenome data is summarised in order to be included in microevolutionary models, as well as the main methodological approaches that have been proposed to reconstruct pangenome microevolutionary history

Tetracycline Selective Pressure and Homologous Recombination Shape the Evolution of Chlamydia suis: A Recently Identified Zoonotic Pathogen

Species closely related to the human pathogen Chlamydia trachomatis (Ct) have recently been found to cause zoonotic infections, posing a public health threat especially in the case of tetracycline resistant Chlamydia suis (Cs) strains. These strains acquired a tet(C)-containing cassette via horizontal gene transfer (HGT). Genomes of 11 Cs strains from various tissues were sequenced to reconstruct evolutionary pathway(s) for tet(C) HGT. Cs had the highest recombination rate of Chlamydia species studied to date. Admixture occurred among Cs strains and with Chlamydia muridarum but not with Ct. Although in vitro tet(C) cassette exchange with Ct has been documented, in vivo evidence may require examining human samples from Ct and Cs co-infected sites. Molecular-clock dating indicated that ancestral clades of resistant Cs strains predated the 1947 discovery of tetracycline, which was subsequently used in animal feed. The cassette likely spread throughout Cs strains by homologous recombination after acquisition from an external source, and our analysis suggests Betaproteobacteria as the origin. Selective pressure from tetracycline may be responsible for recent bottlenecks in Cs populations. Since tetracycline is an important antibiotic for treating Ct, zoonotic infections at mutual sites of infection indicate the possibility for cassette transfer and major public health repercussions

Identification of hidden population structure in time-scaled phylogenies

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 the appearance and expansion of mutations conferring antimicrobial resistance

PLoS Genet.

Our understanding of basic evolutionary processes in bacteria is still very limited. For example, multiple recent dating estimates are based on a universal inter-species molecular clock rate, but that rate was calibrated using estimates of geological dates that are no longer accepted. We therefore estimated the short-term rates of mutation and recombination in Helicobacter pylori by sequencing an average of 39,300 bp in 78 gene fragments from 97 isolates. These isolates included 34 pairs of sequential samples, which were sampled at intervals of 0.25 to 10.2 years. They also included single isolates from 29 individuals (average age: 45 years) from 10 families. The accumulation of sequence diversity increased with time of separation in a clock-like manner in the sequential isolates. We used Approximate Bayesian Computation to estimate the rates of mutation, recombination, mean length of recombination tracts, and average diversity in those tracts. The estimates indicate that the short-term mutation rate is 1.4x10(-6) (serial isolates) to 4.5x10(-6) (family isolates) per nucleotide per year and that three times as many substitutions are introduced by recombination as by mutation. The long-term mutation rate over millennia is 5-17-fold lower, partly due to the removal of non-synonymous mutations due to purifying selection. Comparisons with the recent literature show that short-term mutation rates vary dramatically in different bacterial species and can span a range of several orders of magnitude

Healthcare-associated outbreak of meticillin-resistant Staphylococcus aureus bacteraemia: role of a cryptic variant of an epidemic clone

BACKGROUND New strains of meticillin-resistant Staphylococcus aureus (MRSA) may be associated with changes in rates of disease or clinical presentation. Conventional typing techniques may not detect new clonal variants that underlie changes in epidemiology or clinical phenotype. AIM To investigate the role of clonal variants of MRSA in an outbreak of MRSA bacteraemia at a hospital in England. METHODS Bacteraemia isolates of the major UK lineages (EMRSA-15 and -16) from before and after the outbreak were analysed by whole-genome sequencing in the context of epidemiological and clinical data. For comparison, EMRSA-15 and -16 isolates from another hospital in England were sequenced. A clonal variant of EMRSA-16 was identified at the outbreak hospital and a molecular signature test designed to distinguish variant isolates among further EMRSA-16 strains. FINDINGS By whole-genome sequencing, EMRSA-16 isolates during the outbreak showed strikingly low genetic diversity (P < 1 × 10(-6), Monte Carlo test), compared with EMRSA-15 and EMRSA-16 isolates from before the outbreak or the comparator hospital, demonstrating the emergence of a clonal variant. The variant was indistinguishable from the ancestral strain by conventional typing. This clonal variant accounted for 64/72 (89%) of EMRSA-16 bacteraemia isolates at the outbreak hospital from 2006. CONCLUSIONS Evolutionary changes in epidemic MRSA strains not detected by conventional typing may be associated with changes in disease epidemiology. Rapid and affordable technologies for whole-genome sequencing are becoming available with the potential to identify and track the emergence of variants of highly clonal organisms

Genomic signatures of pre-resistance in Mycobacterium tuberculosis

Recent advances in bacterial whole-genome sequencing have resulted in a comprehensive catalog of antibiotic resistance genomic signatures in Mycobacterium tuberculosis. With a view to pre-empt the emergence of resistance, we hypothesized that pre-existing polymorphisms in susceptible genotypes (pre-resistance mutations) could increase the risk of becoming resistant in the future. We sequenced whole genomes from 3135 isolates sampled over a 17-year period. After reconstructing ancestral genomes on time-calibrated phylogenetic trees, we developed and applied a genome-wide survival analysis to determine the hazard of resistance acquisition. We demonstrate that M. tuberculosis lineage 2 has a higher risk of acquiring resistance than lineage 4, and estimate a higher hazard of rifampicin resistance evolution following isoniazid mono-resistance. Furthermore, we describe loci and genomic polymorphisms associated with a higher risk of resistance acquisition. Identifying markers of future antibiotic resistance could enable targeted therapy to prevent resistance emergence in M. tuberculosis and other pathogens

Genomic analysis and comparison of two gonorrhoea outbreaks

© 2016 Didelot et al.Gonorrhea is a sexually transmitted disease causing growing concern, with a substantial increase in reported incidence over the past few years in the United Kingdom and rising levels of resistance to a wide range of antibiotics. Understanding its epidemiology is therefore of major biomedical importance, not only on a population scale but also at the level of direct transmission. However, the molecular typing techniques traditionally used for gonorrhea infections do not provide sufficient resolution to investigate such fine-scale patterns. Here we sequenced the genomes of 237 isolates from two local collections of isolates from Sheffield and London, each of which was resolved into a single type using traditional methods. The two data sets were selected to have different epidemiological properties: the Sheffield data were collected over 6 years from a predominantly heterosexual population, whereas the London data were gathered within half a year and strongly associated with men who have sex with men. Based on contact tracing information between individuals in Sheffield, we found that transmission is associated with a median time to most recent common ancestor of 3.4 months, with an upper bound of 8 months, which we used as a criterion to identify likely transmission links in both data sets. In London, we found that transmission happened predominantly between individuals of similar age, sexual orientation, and location and also with the same HIV serostatus, which may reflect serosorting and associated risk behaviors. Comparison of the two data sets suggests that the London epidemic involved about ten times more cases than the Sheffield outbreak. IMPORTANCE: The recent increases in gonorrhea incidence and antibiotic resistance are cause for public health concern. Successful intervention requires a better understanding of transmission patterns, which is not uncovered by traditional molecular epidemiology techniques. Here we studied two outbreaks that took place in Sheffield and London, United Kingdom. We show that whole-genome sequencing provides the resolution to investigate direct gonorrhea transmission between infected individuals. Combining genome sequencing with rich epidemiological information about infected individuals reveals the importance of several transmission routes and risk factors, which can be used to design better control measures