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

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

Lineage specific recombination rates and microevolution in Listeria monocytogenes

Background: The bacterium Listeria monocytogenes is a saprotroph as well as an opportunistic human foodborne pathogen, which has previously been shown to consist of at least two widespread lineages (termed lineages I and II) and an uncommon lineage (lineage III). While some L. monocytogenes strains show evidence for considerable diversification by homologous recombination, our understanding of the contribution of recombination to L. monocytogenes evolution is still limited. We therefore used STRUCTURE and ClonalFrame, two programs that model the effect of recombination, to make inferences about the population structure and different aspects of the recombination process in L. monocytogenes. Analyses were performed using sequences for seven loci (including the house-keeping genes gap, prs, purM and ribC, the stress response gene sigB, and the virulence genes actA and inlA) for 195 L. monocytogenes isolates. Results: Sequence analyses with ClonalFrame and the Sawyer's test showed that recombination is more prevalent in lineage II than lineage I and is most frequent in two house-keeping genes (ribC and purM) and the two virulence genes (actA and inlA). The relative occurrence of recombination versus point mutation is about six times higher in lineage II than in lineage I, which causes a higher genetic variability in lineage II. Unlike lineage I, lineage II represents a genetically heterogeneous population with a relatively high proportion (30% average) of genetic material imported from external sources. Phylograms, constructed with correcting for recombination, as well as Tajima's D data suggest that both lineages I and II have suffered a population bottleneck. Conclusion: Our study shows that evolutionary lineages within a single bacterial species can differ considerably in the relative contributions of recombination to genetic diversification. Accounting for recombination in phylogenetic studies is critical, and new evolutionary models that account for the possibility of changes in the rate of recombination would be required. While previous studies suggested that only L. monocytogenes lineage I has experienced a recent bottleneck, our analyses clearly show that lineage II experienced a bottleneck at about the same time, which was subsequently obscured by abundant homologous recombination after the lineage II bottleneck. While lineage I and lineage II should be considered separate species from an evolutionary viewpoint, maintaining single species name may be warranted since both lineages cause the same type of human disease

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

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

Additive uncorrelated relaxed clock models for the dating of genomic epidemiology phylogenies

Phylogenetic dating is one of the most powerful and commonly used methods of drawing epidemiological interpretations from pathogen genomic data. Building such trees requires considering a molecular clock model which represents the rate at which substitutions accumulate on genomes. When the molecular clock rate is constant throughout the tree then the clock is said to be strict, but this is often not an acceptable assumption. Alternatively, relaxed clock models consider variations in the clock rate, often based on a distribution of rates for each branch. However, we show here that the distributions of rates across branches in commonly used relaxed clock models are incompatible with the biological expectation that the sum of the numbers of substitutions on two neighbouring branches should be distributed as the substitution number on a single branch of equivalent length. We call this expectation the additivity property. We further show how assumptions of commonly used relaxed clock models can lead to estimates of evolutionary rates and dates with low precision and biased confidence intervals. We therefore propose a new additive relaxed clock model where the additivity property is satisfied. We illustrate the use of our new additive relaxed clock model on a range of simulated and real datasets, and we show that using this new model leads to more accurate estimates of mean evolutionary rates and ancestral dates

Genomic epidemiology of Vibrio cholerae reveals the regional and global spread of two epidemic non-toxigenic lineages

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

Can ABC be Used for Model Selection?

Over the past ten years, Approximate Bayesian Computation (ABC) has become hugely popular to estimate the parameters of a model when the likelihood function cannot be computed in a reasonable amount of time. ABC can in principle be used also to perform Bayesian model comparison, but this raises the question of which summary statistic should be used for such applications. Here we present a general method for constructing a summary statistic that is sufficient for the model choice problem. We apply this construction to models from the exponential family. Unfortunately, in more complex models, our construct often results in statistics with too high dimensionality to use in ABC. We therefore discuss the possibility of applying ABC with non-sufficient statistics

Phantom of the Paradise de Brian de Palma, un témoignage

« J’ai écrit un opéra... » Je ne sais avec exactitude quelle en est la raison, mais chaque fois que je pense au film Phantom of the Paradise, je me rappelle cette tirade désespérée de l’artiste maudit Francis Lalanne à l’occasion d’une émission de télévision. Au-delà du ridicule de la situation, le chanteur incompris accusant les mystérieux « ronds-de-cuir » de l’empêcher de réaliser son projet touche bien aux grands thèmes de la création abordés dans le film : l’authenticité, la concession, ..