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bioRxiv2018

rPinecone: Define sub-lineages of a clonal expansion via a phylogenetic tree

The ability to distinguish between pathogens is a fundamental requirement to understand the epidemiology of infectious diseases. Phylogenetic analysis of genomic data can provide a powerful platform to identify lineages within bacterial populations, and thus inform outbreak investigation and transmission dynamics. However, resolving differences between pathogens associated with low variant (LV) populations carrying low median pairwise single nucleotide variant (SNV) distances, remains a major challenge. Here we present rPinecone, an R package designed to define sub-lineages within closely related LV populations. rPinecone uses a root-to-tip directional approach to define sub-lineages within a phylogenetic tree according to SNV distance from the ancestral node. The utility of this program was demonstrated using genomic data of two LV populations: a hospital outbreak of methicillin-resistant Staphylococcus aureus and endemic Salmonella Typhi from rural Cambodia. rPinecone identified the transmission branches of the hospital outbreak and geographically-confined lineages in Cambodia. Sub-lineages identified by rPinecone in both analyses were phylogenetically robust. It is anticipated that rPinecone can be used to discriminate between lineages of bacteria from LV populations where other methods fail, enabling a deeper understanding of infectious disease epidemiology for public health purposes.\n\nDATA SUMMARYO_LISource code for rPinecone is available on GitHub under the open source licence GNU GPL 3; (url: https://github.com/alexwailan/rpinecone).\nC_LIO_LINewick format files for both phylogenetic trees have been deposited in Figshare; (url: https://doi.org/10.6084/m9.figshare.7022558)\nC_LIO_LIGeographical analysis of the S. Typhi Dataset using Microreact is available at https://microreact.org/project/r1IqkrN1X.\nC_LIO_LIAccession numbers, meta data and sample lineage results of both datasets used in this paper are listed in the supplementary tables.\nC_LI\n\nI/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. {boxtimes}\n\nIMPACT STATEMENTWhole genome sequence data from bacterial pathogens is increasingly used in the epidemiological investigation of infectious disease, both in outbreak and endemic situations. However, distinguishing bacterial species which are both very similar and which are likely to come from a small geographical and temporal range presents a major technical challenge for epidemiologists. rPinecone was designed to address this challenge and utilises phylogenetic data to define lineages within bacterial populations that have limited variation. This approach is therefore of great interest to epidemiologists as it adds a further level of clarity above and beyond that which is offered by existing approaches which have not been designed to consider bacterial isolates containing variation that only transiently exist, but which is epidemiologically informative. rPinecone has the flexibility to be applied to multiple pathogens and has direct application for investigations of clinical outbreaks and endemic disease to understand transmission dynamics or geographical hotspots of disease.

genomics↗

bioRxiv2016

Inference of direction, diversity, and frequency of HIV-1 transmission using approximate Bayesian computation

Diversity of the founding population of Human Immunodeficiency Virus Type 1 (HIV-1) transmissions raises many important biological, clinical, and epidemiological issues. In up to 40% of sexual infections there is clear evidence for multiple founding variants, which can influence the efficacy of putative prevention methods and the reconstruction of epidemiologic histories. To measure the diversity of the founding population and to compute the probability of alternative transmission scenarios, while explicitly taking phylogenetic uncertainty into account, we created an Approximate Bayesian Computation (ABC) method based on a set of statistics measuring phylogenetic topology, branch lengths, and genetic diversity. We applied our method to a heterosexual transmission pair showing a complex paraphyletic-polyphyletic donor-recipient phylogenetic topology. We found evidence identifying the donor that was consistent with the known facts of the case (Bayes factor >20). We also found that while the evidence for ongoing transmission between the pair was as good or better than the singular transmission event model, it was only viable when the rate of ongoing transmission was implausibly high (~1/day). We concluded that the singular transmission model, which was able to estimate the diversity of the founding population (mean 7% substitutions/site), was more biologically plausible. Our study provides a formal inference framework to investigate HIV-1 direction, diversity, and frequency of transmission. The ability to measure the diversity of founding populations in both simple and complex transmission situations is essential to understanding the relationship between the phylogeny and epidemiology of HIV-1 as well as in efforts developing new prevention technologies.

Epidemiology↗

bioRxiv2017

Reactive and pre-emptive vaccination strategies to control hepatitis E infection in emergency and refugee settings: a modelling study.

BackgroundHepatitis E Virus (HEV) is an important cause of morbidity and mortality in emergency and refugee camp settings. Symptomatic infection is associated with case fatality rates of ~20% in pregnant women. However, its epidemiology is poorly understood and the potential impact of immunisation in outbreak settings uncertain. We aimed to estimate key epidemiological parameters for HEV and to evaluate the potential impact of both reactive vaccination (initiated in response to an epidemic) and pre-emptive vaccination.\n\nMethodsWe analysed data from one of the worlds largest recorded HEV epidemics, which occurred in refugee camps in Uganda (2007-2009), using transmission dynamic models to estimate epidemiological parameters and assess the potential impact of reactive and pre-emptive vaccination strategies.\n\nResultsUnder baseline assumptions we estimated the basic reproduction number of HEV to range from 3.9 (95% CrI 2.8, 5.4) to 8.9 (5.4, 14.2). Mean latent and infectious periods were estimated to be 34 (28, 39) and 40 (23, 71) days respectively.\n\nReactive two-dose vaccination of those aged 16-65 years excluding pregnant women (for whom vaccine is not licensed), if initiated after 50 reported cases, led to mean camp-specific reductions in mortality of 10 to 29%. Pre-emptive vaccination with two doses reduced mortality by 35 to 65%. Both strategies were more effective if coverage was extended to groups for whom the vaccine is not currently licensed. For example, two dose pre-emptive vaccination, if extended to include pregnant women, led to mean reductions in mortality of 66 to 82%.\n\nConclusionsHEV has a high transmission potential in refugee camp settings. Substantial reductions in mortality through vaccination are expected, even if used reactively. There is potential for greater impact if vaccine safety and effectiveness can be established in pregnant women.\n\nFundingWellcome Trust (106491/Z/14/Z and 089275/Z/09/Z). BC: MRC/DfID (MR/K006924/1).

epidemiology↗

bioRxiv2018

Guiding Vaccine Efficacy Trial Design During Public Health Emergencies: An interactive web-based decision support tool

The design and execution of rigorous, fast, and ethical vaccine efficacy trials can be challenging during epidemics of emerging pathogens, such as the 2014-2016 Ebola virus and 2015-2016 Zika virus epidemics. Response to an urgent public health crisis requires accelerated research even as emerging epidemics themselves change rapidly and are inherently less well understood than well-established diseases. As part of the World Health Organization Research and Development Blueprint, we designed a web-based interactive decision support system (InterVax-Tool) to help diverse stakeholders navigate the epidemiological, logistical, and ethical decisions involved in designing a vaccine efficacy trial during a public health emergency. In contrast to existing literature on trial design, InterVax-Tool offers high-level visual and interactive assistance through a set of four decision trees, guiding users through selection of 1) the Primary Endpoint, (2) the Target Population, (3) Randomization, and (4) the Comparator. Guidance is provided on how each of fourteen key considerations-grouped as Epidemiological, Vaccine-related, Infrastructural, or Sociocultural-should be used to inform each decision in the trial design process. The tool is not intended to provide a black box decision framework for identifying an optimal trial design, but rather to facilitate transparent, collaborative and comprehensive discussion of the relevant decisions, while recording the decision process. The tool can also assist capacity building by providing a cross-disciplinary picture of trial design using concepts from epidemiology, study design, vaccinology, biostatistics, mathematical modeling and clinical research ethics. Here, we describe the goals and features of InterVax-Tool as well as its application to the design of a Zika vaccine efficacy trial.\n\nOne Sentence SummaryAn interactive web-based decision support tool was developed to assist in the design of vaccine efficacy trials during emerging outbreaks.

epidemiology↗

bioRxiv2018

Modelling coinfections to detect within-host interactions from genotype combination prevalences

Parasite genetic diversity can provide information on disease transmission dynamics but most methods ignore the exact combinations of genotypes in infections. We introduce and validate a new method that combines explicit epidemiological modelling of coinfections and regression Approximate Bayesian Computing (ABC) to detect within-host interactions. Using genital infections by different types of Human Papillomaviruses (HPVs) as a test case, we show that, if sufficiently strong, within-host parasite interactions can be detected from epidemiological data and that this detection is robust even in the face of host heterogeneity in behaviour. These results suggest that the combination of mathematical modelling and sophisticated inference techniques is promising to extract additional epidemiological information from existing datasets.

epidemiology↗

bioRxiv2018

Real-time fine aerosol exposures in taconite mining operations

Respiratory health effects such as mesothelioma, silicosis, and lung cancer have been shown to be associated with working in the taconite mining industry. Taconite workers may also have elevated risks from cardiovascular disease (CVD), although the relationship of CVD to dust exposures at these mines has not been well-studied. Motivated by evidence from environmental epidemiological studies and occupational cohorts that have implicated the effects of fine particulates with increased risk of cardiovascular diseases, we conducted an air monitoring campaign to characterize fine aerosol concentrations at 91 locations across six taconite mines using an array of direct-reading instruments to obtain measurements of mass concentrations (PM2.5 or particles with aerodynamic diameter less than 2.5 m, and respirable particulate matter or RPM), alveolar-deposited surface area concentrations (ADSA), particle number concentrations (PN), and particle size distributions. To analyze these data, we fit a Bayesian hierarchical model with an AR(1) correlation structure to estimate exposure while accounting for temporal correlation. The highest estimated geometric means (GMs) were observed in the pelletizing and concentrating departments (pelletizing maintenance, balling drum operator, and concentrator operator) for PM2.5 and RPM. ADSA and PN generally had highest GMs in the pelletizing department, which processed large amounts of powder-like particles into iron pellets. The within-location variability (GSD_WL) generally ranged from 1 to 3 for all exposure metrics, except for a few locations which indicated changes of activities that caused the exposures to change. Between-location variability (GSD_BL) estimates were generally higher than GSD_WL, indicating larger differences in exposure levels at different locations between mines than at individual locations over the course of several hours. Ranking between PM2.5 and RPM generally agree with each other, whereas ADSA and PN were more consistent with each other, with some overlap with PM2.5 and RPM. Differences in ranking these groups may have potential implication for occupational epidemiological studies that rely on exposure information to detect an exposure-response relationship for various job groups. Future epidemiological studies investigating fine aerosol exposures and health risks in occupational settings are encouraged to use multiple metrics to see how they influence health outcomes risk.

epidemiology↗

bioRxiv2018

Experimentally infection of Cattle with wild types of Peste-des-petits-ruminants Virus -- Role in its maintenance and spread

PPR is a common and dreadful disease of sheep and goats in tropical regions caused by PPRV which can infect also cattle without any clinical signs but show a seroconversion. However the epidemiological role of cattle in the maintenance and spread of the disease is not known. For the purpose of the present study, cattle were infected with a wild candidate from each of the four lineages of PPRV and placed in separate boxes. Then naive goats were introduced in each specific box for the 30 days duration of the experiment. The results showed that no clinical signs of PPR were recorded from these infected cattle along with the in-contact goats. The nasal and oral swabs remainend negative. However, animals infected with wild types of PPRV from lineages 1, 3, 4 seroconverted with high percentage inhibition (PI %= values. Only two animals out of three with the Nigeria 75/3 strain of lineage 2 (mild strain) did elicit a production of specific anti-PPR antibodies in those cattle but with PI% values around the threshold of the test. Our findings confirm that cattle are dead end hosts for PPRV and do not play an epidemiological role in the maintenance and spread of PPRV. In a PPR surveillance programme, cattle can serve as indicators of PPRV infection.\n\nImportancePeste-ds-ptetis-ruminants (PPR) is a major Transboundary Animal disease (TADs) in the tropical regions which is spreading extensively nowadays to southern and northern of Africa, Turkey in Europ and southwest Asia. PPR virus is very close related to Rinderpest virus (RPV) which has been eradicated from the world. Today FAO, WOAH / OIE and the scientific community have elected PPR to be the second animal disease to be eradicated through The PPR Global Eradication Programme (GEP-PPR). Since PPR infects cattle without any clinical signs but they seroconvert, it is important to explore the role of cattle in the maintenance and spread of PPRV to better understand the epidemiology of the disease which wll help in the the GEP-PPR.

epidemiology↗

bioRxiv2018

Game theory of vaccination and depopulation for managing avian influenza on poultry farms

Highly pathogenic avian influenza is endemic in domestic poultry populations in East and South Asia and is a major threat to human health, animal health, and the poultry production industry. The behavioral response of farmers to the disease and its epidemiological effects are still poorly understood. We considered a symmetric game in a region with widespread smallholder poultry production, where the players are broiler poultry farmers and between-farm disease transmission is both environmental (local) and mediated by the trade of infected birds. Three types of farmer behaviors were modelled: vaccination, depopulation, and cessation of poultry farming. We found that the transmission level of avian influenza through trade networks had strong qualitative effects on the systems epidemiological-economic equilibria. In the case of low trade-based transmission, when the monetary cost of infection is sufficiently high, depopulation behavior persists and maintains a disease-free equilibrium. In the case of high trade-based transmission, depopulation behavior has perverse epidemiological effects - as it accelerates the spread of disease via poultry traders - but has a high enough payoff to farmers that it persists at the systems game theoretic equilibrium. In this situation, state interventions should focus on making effective vaccination technologies available at a low price rather than penalizing infected farms. Our results emphasize the need in endemic countries to further investigate the commercial circuits through which birds from infected farms are traded.

epidemiology↗

bioRxiv2018

Descriptive analysis in time and space of recorded data for Buruli Ulcer occurrence in Victoria over 22 years

BackgroundBuruli ulcer (BU) is a subcutaneous necrotic infection of the skin caused by Mycobacterium ulcerans. There has been increasing BU incidence in Victoria, Australia. The aim of this study to provide an epidemiological update of BU cases in Victoria to understand the pattern of distribution over time and space and attempt to identify local risk factors.\n\nMethodsA comprehensive descriptive epidemiological analyses were performed on BU notification data from 1994 to 2016. In addition, retrospective temporal, spatial and spatio-temporal analyses were conducted to understand the distribution of cases. Quantum GIS was used to generate maps. Demographic, new housing settlements and historical rainfall data were analysed to assess their effects on BU incidence in Victoria.\n\nFindingsThere were a total of 902 patients notified from 1994-2016. The incidence rate was 0.8/100,000 persons in Victoria. Space and time analyses showed that the most likely disease cluster was the Bellarine and Mornington Peninsulas with incidence rate 50 times higher than the State of Victoria rate. Gender was not a risk factor, but age was, with increased susceptibility among the over 60 year old group. There was an unusual high risk in the 15-24 age group in Point Lonsdale. Correlation analyses indicated that increase in population and construction of new settlements might be some of the reasons contributing to the rise in cases in Victoria.\n\nInterpretationThe findings agreed with published works in Australia of the increase in BU cases in Victoria. However, our findings also highlights the endemic nature of cases. The identified spatial disease clusters could be relevant for future environmental sampling studies or screening tests for M. ulcerans exposure.\n\nAuthor SummaryBuruli ulcer (BU) has been reported in 33 countries, mainly from the Tropics and Sub-tropics. Tropical cases are mainly within the West African region. Australia is the only country outside Africa in the top six highest incidence countries for BU. The exact mode of transmission remains unclear. Disease cases are rising in Australia, especially in Victoria for reasons that remains unclear. We have provided a descriptive epidemiological analyses in space and time of 22 years of recorded data on BU cases in Victoria from 1994 to 2016. We have also discussed demographic and new settlement dynamics over the study period. There were a total of 902 PCR-confirmed BU cases from 245 suburbs. Five suburbs on the Bellarine and Mornington Peninsulas were identified as the most endemic locations in Victoria. Spatial analyses detected a wider disease cluster area on the Peninsulas. We propose environmental sampling for risk factors analyses should focus on the endemic regions and some secondary clusters.

epidemiology↗

bioRxiv2013

Bayesian inference of infectious disease transmission from whole genome sequence data

Genomics is increasingly being used to investigate disease outbreaks, but an important question remains unanswered - how well do genomic data capture known transmission events, particularly for pathogens with long carriage periods or large within-host population sizes? Here we present a novel Bayesian approach to reconstruct densely-sampled outbreaks from genomic data whilst considering within-host diversity. We infer a time-labelled phylogeny using BEAST, then infer a transmission network via a Monte-Carlo Markov Chain. We find that under a realistic model of within-host evolution, reconstructions of simulated outbreaks contain substantial uncertainty even when genomic data reflect a high substitution rate. Reconstruction of a real-world tuberculosis outbreak displayed similar uncertainty, although the correct source case and several clusters of epidemiologically linked cases were identified. We conclude that genomics cannot wholly replace traditional epidemiology, but that Bayesian reconstructions derived from sequence data may form a useful starting point for a genomic epidemiology investigation.

Genomics↗

bioRxiv2015

Simple genetic models for autism spectrum disorder

To explore the interplay between new mutation, transmission, and gender bias in genetic disease requires formal quantitative modeling. Autism spectrum disorders offer an ideal case: they are genetic in origin, complex, and show a gender bias. The high reproductive costs of autism ensure that most strongly associated genetic mutations are short-lived, and indeed the disease exhibits both transmitted and de novo components. There is a large body of both epidemiologic and genomic data that greatly constrain the genetic mechanisms that may contribute to the disorder. We develop a computational framework that assumes classes of additive variants, each member of a class having equal effect. We restrict our initial exploration to single class models, each having three parameters. Only one model matches epidemiological data. It also independently matches the incidence of de novo mutation in simplex families, the gender bias in unaffected siblings in simplex populations, and rates of mutation in target genes. This model makes strong and as yet not fully tested predictions, namely that females are the primary carriers in cases of genetic transmission, and that the incidence of de novo mutation in target genes for families at high risk for autism are not especially elevated. In its simplicity, this model does not account for MZ twin concordance or the distorted gender bias of high functioning children with ASD, and does not accommodate all the known mechanisms contributing to ASD. We point to the next steps in applying the same computational framework to explore more complex models.\n\nAuthor summaryFor understanding complex genetic diseases one needs both data and molecular/genetic models. In the absence of any model, it is impossible to do more than summarize observations. A good model will be consistent with much or all of the existing data and puts the data in the context of known genetic principles. Ideally the model will make testable predictions. Where the good models fail often shows the directions that require more thought about mechanisms. In this paper we describe a new computational framework that we use to explore a complex genetic disorder with many gene targets, with both de novo and transmitted variants, and with gender bias. The disorder we consider is autism spectrum disorder (ASD), and our framework rules out some previous models that make unsustainable predictions. We identify a formal model that satisfies diverse epidemiologic and genomic observations. This model makes strong and untested predictions and thereby suggests new studies that would resolve outstanding aspects of autism genetics.

Genetics↗

bioRxiv2016

Identification of Klebsiella capsule synthesis loci from whole genome data

BackgroundKlebsiella pneumoniae and close relatives are a growing cause of healthcare-associated infections for which increasing rates of multi-drug resistance are a major concern. The Klebsiella polysaccharide capsule is a major virulence determinant and epidemiological marker. However, little is known about capsule epidemiology since serological typing is not widely accessible, and many isolates are serologically non-typeable. Molecular methods for capsular typing are needed, but existing methods lack sensitivity and specificity and fail to take advantage of the information available in whole-genome sequence data, which is increasingly being generated for surveillance and investigation of Klebsiella.\n\nMethodsWe investigated the diversity of capsule synthesis loci (K loci) among a large, diverse collection of 2503 genome sequences of K. pneumoniae and closely related species. We incorporated analyses of both full-length K locus DNA sequences and clustered protein coding sequences to identify, annotate and compare K locus structures, and we propose a novel method for identifying K loci based on full locus information extracted from whole genome sequences.\n\nResultsA total of 134 distinct K loci were identified, including 31 novel types. Comparative analysis of K locus gene content detected 508 unique protein coding gene clusters that appear to reassort via homologous recombination, generating novel K locus types. Extensive nucleotide diversity was detected among the wzi and wzc genes, both within and between K loci, indicating that current typing schemes based on these genes are inadequate. As a solution, we introduce Kaptive, a novel software tool that automates the process of identifying K loci from large sets of Klebsiella genomes based on full locus information.\n\nConclusionsThis work highlights the extensive diversity of Klebsiella K loci and the proteins that they encode. We propose a standardised K locus nomenclature for Klebsiella, present a curated reference database of all known K loci, and introduce a tool for identifying K loci from genome data (https://github.com/katholt/Kaptive). These developments constitute important new resources for the Klebsiella community for use in genomic surveillance and epidemiology.

Genomics↗

bioRxiv2017

Consensus and conflict among ecological forecasts of Zika virus outbreaks in the United States

Ecologists are increasingly involved in the pandemic prediction process. In the course of the Zika outbreak in the Americas, several ecological models were developed to forecast the potential global distribution of the disease. Conflicting results produced by alternative methods are unresolved, hindering the development of appropriate public health forecasts. We compare ecological niche models and experimentally-driven mechanistic forecasts for Zika transmission in the continental United States, a region of high model conflict. We use generic and uninformed stochastic county-level simulations to demonstrate the downstream epidemiological consequences of conflict among ecological models, and show how assumptions and parameterization in the ecological and epidemiological models propagate uncertainty and produce downstream model conflict. We conclude by proposing a basic consensus method that could resolve conflicting models of potential outbreak geography and seasonality. Our results illustrate the unacceptable and often undocumented margin of uncertainty that could emerge from using any one of these predictions without reservation or qualification. In the short term, ecologists face the task of developing better post hoc consensus that accurately forecasts spatial patterns of Zika virus outbreaks. Ultimately, methods are needed that bridge the gap between ecological and epidemiological approaches to predicting transmission and realistically capture both outbreak size and geography.

ecology↗

bioRxiv2017

Macroecology suggests cancer-causing papillomaviruses form non-neutral communities

Chronic infection by oncogenic Human papillomaviruses (HPVs) leads to cancers. Public health interventions, such as cancer screening and mass vaccination, radically change the ecological conditions encountered by circulating viruses. It is currently unclear how HPVs communities may respond to these environmental changes, because little is known about their ecology. Predicting the impact on viral diversity by the introduction of HPV vaccines requires answering the unresolved question of how HPVs interact. Although it is commonly believed that they do not interact (neutral theory), there are suggestions that HPV types may compete for resources or via the immune response (niche-based or non-neutral theory). Here, we applied for the first time established biodiversity measures and methods to epidemiological data in order to assess whether niche-partitioning or neutral processes are shaping HPV diversity patterns at the population level. We find that as infections progress toward cancer, HPVs communities become more uneven and a few HPVs play a stronger dominance role. By fitting species abundance distributions, we found that neutral models were always out-performed by non-neutral distributions, both in asymptomatic infections and in cancers. Our results suggest that temporally moving from a more even to a less even community implies an increase in competition, probably due to environmental changes linked to infection progression. More ecological thinking will be required to understand present-day interactions and to anticipate the future of the long lasting interactions between HPVs and humans.\n\nSIGNIFICANCE STATEMENTHuman papillomaviruses (HPVs) are very diverse. Infections by HPVs are very common and chronic infections may lead to cancers. The more oncogenic HPVs are now targetted by effective vaccines, and this has raised the question of whether there may be a viral replacement if these dominant types were removed. This is a medical version of a classical ecological controversy, namely how much biodiversity distributions and community dynamics are explained by neutral theory plays out across ecosystems. For HPVs, epidemiologic studies before and after the vaccination have led to the widespread belief that these viruses do not interact. Here, we apply different methods developed in macroecology to the best available epidemiologic data to address this issue. Consistently, we find that HPVs form non-neutral communities. Instead, competitive niche-partitioning process and dominance explain best HPVs communities. We also find that the vaccine might not change such competitive niche processes. Beyond clinical implications, this garners support that niche processes often best explain biodiversity patterns, even in human viral communities.

ecology↗

bioRxiv2018

Anti-CRISPR phages cooperate to overcome CRISPR-Cas immunity

Some phages encode anti-CRISPR (acr) genes, which antagonize bacterial CRISPR-Cas immune systems by binding components of its machinery, but it is less clear how deployment of these acr genes impacts phage replication and epidemiology. Here we demonstrate that bacteria with CRISPR-Cas resistance are still partially immune to Acr-encoding phage. As a consequence, Acr-phages often need to cooperate in order to overcome CRISPR resistance, with a first phage taking down the host CRISPR-Cas immune system to allow a second Acr- phage to successfully replicate. This cooperation leads to epidemiological tipping points in which the initial density of Acr-phage tips the balance from phage extinction to a phage epidemic. Furthermore, both higher levels of CRISPR-Cas immunity and weaker Acr activities shift the tipping points towards higher phage densities. Collectively these data help to understand how interactions between phage-encoded immune suppressors and the CRISPR systems they target shape bacteria-phage population dynamics.\n\nHighlightsO_LIBacteria with CRISPR immunity remain partially resistant to Acr-phage\nC_LIO_LISequentially infecting Acr phages cooperate to overcome CRISPR resistance\nC_LIO_LIAcr-phage epidemiology depends on the initial phage density\nC_LIO_LICRISPR resistant bacteria can drive Acr phages extinct\nC_LI\n\neTOC blurbSome phages encode Acr proteins that block bacterial CRISPR-Cas immune systems. Although CRISPR-Cas can clear the first infection, this Acr-phage still suppresses the host immune system, which can be exploited by other Acr-phages. This is critical for Acr-phage amplification, but this \"cooperation\" only works beyond a critical Acr-phage density threshold.

microbiology↗

bioRxiv2018

Global emergence and population dynamics of divergent serotype 3 CC180 pneumococci

Streptococcus pneumoniae serotype 3 remains a significant cause of morbidity and mortality worldwide, despite inclusion in the 13-valent pneumococcal conjugate vaccine (PCV13). Serotype 3 increased in carriage since the implementation of PCV13 in the United States, while invasive disease rates remain unchanged. We investigated the persistence of serotype 3 in carriage and disease, through genomic analyses of a global sample of 301 serotype 3 isolates of the Netherlands3-31 (PMEN31) clone CC180, combined with associated patient data and PCV utilization among countries of isolate collection. We assessed phenotypic variation between dominant clades in capsule charge (zeta potential), capsular polysaccharide shedding, and susceptibility to opsonophagocytic killing, which have previously been associated with carriage duration, invasiveness, and vaccine escape. We identify a recent shift in the CC180 population attributed to a lineage termed Clade II, which was estimated by Bayesian coalescent analysis to have first appeared in 1968 [95% HPD: 1939-1989] and increased in prevalence and effective population size thereafter. Clade II isolates are divergent from the pre-PCV13 serotype 3 population in non-capsular antigenic composition, competence, and antibiotic susceptibility, the last resulting from the acquisition of a Tn916-like conjugative transposon. Differences in recombination rates among clades correlated with variations in the ATP-binding subunit of Clp protease as well as amino acid substitutions in the comCDE operon. Opsonophagocytic killing assays elucidated the low observed efficacy of PCV13 against serotype 3. Variation in PCV13 use among sampled countries was not independently correlated with the CC180 population shift; therefore, genotypic and phenotypic differences in protein antigens and, in particular, antibiotic resistance may have contributed to the increase of Clade II. Our analysis emphasizes the need for routine, representative sampling of isolates from disperse geographic regions, including historically under-sampled areas. We also highlight the value of genomics in resolving antigenic and epidemiological variations within a serotype, which may have implications for future vaccine development.\n\nAuthor SummaryStreptococcus pneumoniae is a leading cause of bacterial pneumoniae, meningitis, and otitis media. Despite inclusion in the most recent pneumococcal conjugate vaccine, PCV13, serotype 3 remains epidemiologically important globally. We investigated the persistence of serotype 3 using whole-genome sequencing data form 301 isolates collected among 24 countries from 1993-2014. Through phylogenetic analysis, we identified three distinct lineages within a single clonal complex, CC180, and found one has recently emerged and grown in prevalence. We then compared genomic difference among lineages as well as variations in pneumococcal vaccine use among sampled countries. We found that the recently emerged lineage, termed Clade II, has a higher prevalence of antibiotic resistance compared to other lineages, diverse surface protein antigens, and a higher rate of recombination, a process by which bacteria can uptake and incorporate genetic material from its surroundings. Differences in vaccine use among sampled countries did not appear to be associated with the emergence of Clade II. We highlight the need to routine, representative sampling of bacterial isolates from diverse geographic areas and show the utility of genomic data in resolving epidemiological differences within a pathogen population.

evolutionary biology↗

bioRxiv2018

Contemporary circulating enterovirus D68 strains show differential viral entry and replication in human neuronal cells

Historically, enterovirus D68 (EV-D68) has primarily been associated with respiratory illnesses. However, in the summers of 2014 and 2016 EV-D68 outbreaks coincided with a spike in polio-like acute flaccid myelitis/paralysis (AFM/AFP) cases. This raised concerns that the EV-D68 virus could be the causative agent of AFM during these recent outbreaks. To assess the neurotropic capacity of EV-D68, we explored the use of the neuroblastoma-derived neuronal cell line, SH-SY5Y, as a tissue culture model to determine if differential infection permissibility is observed for different EV-D68 strains. In contrast to HeLa and A549 cells, which support viral infection of all EV-D68 strains tested, SH-SY5Y cells only supported infection by a subset of contemporary EV-D68 strains, including members from the 2014 outbreak. Viral replication and infectivity in SH-SY5Y was assessed using four different assays - infectious virus production, cytopathic effects, cellular ATP release, and VP1 capsid protein production - with similar results. Similar differential neurotropism was also observed in differentiated SH-SY5Y cells, primary human neuron cultures, and a mouse paralysis model. Using the SH-SY5Y cell culture model, we determined that barriers to viral entry was at least partly responsible for the differential infectivity phenotype, since transfection of genomic RNA into SH-SY5Y generated virions for all EV-D68 isolates, but only a single round of replication was observed from strains which could not directly infect SH-SY5Y. In addition to supporting virus replication and other functional studies, this cell culture model may help confirm epidemiological associations between EV-D68 strains and AFM and allow for the rapid identification of emerging neurotropic strains.\n\nAuthor SummarySince the outbreak during the summer of 2014, EV-D68 has been linked to a type of limb paralysis referred to as acute flaccid myelitis (AFM), with evidence mounting for the causal link of EV-D68 to AFM. Among these AFM cases, concurrent EV-D68 infection was confirmed in several independent epidemiological clusters in four continents. In this report, we describe a neuronal cell culture model (SH-SY5Y cells) where only a subset of contemporary 2014 outbreak strains of EV-D68 show infectivity in neuronal cells, or neurotropism, based on four different assays of viral replication and infection. We further confirmed the observed difference in neurotropism in vitro using primary human neuron cell cultures and in vivo with a mouse paralysis model. Using the SH-SY5Y cell model, we determined that a barrier to viral entry is at least partly responsible for neurotropism. SH-SY5Y cells may be useful in determining if specific EV-D68 genetic determinants are associated with neuropathogenesis, and replication in this cell line could be used as rapid screening tool for identifying neurotropic EV-D68 strains. This may assist with better understanding of pathogenesis and epidemiology, and with the development of potential therapies.

microbiology↗

bioRxiv2018

Competition for hosts modulates vast antigenic diversity to generate persistent strain structure in Plasmodium falciparum

In their competition for hosts, parasites with antigens that are novel to host immunity will be at a competitive advantage. The resulting frequency-dependent selection can structure parasite populations into strains of limited genetic overlap. For Plasmodium falciparum-the causative agent of malaria-in endemic regions, the high recombination rates and associated vast diversity of its highly antigenic and multicopy var genes preclude such clear clustering; this undermines the definition of strains as specific, temporally-persisting gene variant combinations. We use temporal multilayer networks to analyze the genetic similarity of parasites in both simulated data and in an extensively and longitudinally sampled population in Ghana. When viewed over time, populations are structured into modules (i.e., groups) of parasite genomes whose var gene combinations are more similar within, than between, the modules, and whose persistence is much longer than that of the individual genomes that compose them. Comparison to neutral models that retain parasite population dynamics but lack competition reveals that the selection imposed by host immunity promotes the persistence of these modules. The modular structure is in turn associated with a slower acquisition of immunity by individual hosts. Modules thus represent dynamically generated niches in host immune space, which can be interpreted as strains. Negative frequency-dependent selection therefore shapes the organization of the var diversity into parasite genomes, leaving a persistence signature over ecological time scales. Multilayer networks extend the scope of phylodynamics analyses by allowing quantification of temporal genetic structure in organisms that generate variation via recombination or other non-bifurcating processes. A strain structure similar to the one described here should apply to other pathogens with large antigenic spaces that evolve via recombination. For malaria, the temporal modular structure should enable the formulation of tractable epidemiological models that account for parasite antigenic diversity and its influence on intervention outcomes.\n\nSignificanceMany pathogens, including the causative agent of malaria Plasmodium falciparum, use antigenic variation, obtained via recombination, as a strategy to evade the human immune system. The vast diversity and multiplicity of genes encoding antigenic variation in high transmission regions challenge the notion of the existence of distinct strains: temporally-persistent and specific combinations of genes relevant to epidemiology. We examine the role of human immune selection in generating such genetic population structure in the major blood-stage antigen of Plasmodium falciparum. We show, using simulated and empirical data, that immune selection generates and maintains modules of genomes with higher genetic similarity within, than between, these groups. Selection further promotes the persistence of these modules for much longer times than those of their constituent genomes. Simulations show that the temporal modular structure reduces the speed at which hosts acquire immunity to the parasite. We argue that in P. falciparum modules can be viewed as dynamic strains occupying different niches in human immune space; they are thus relevant to formulating transmission models that encompass the antigenic diversity of the parasite. Our analyses may prove useful to understand the interplay between temporal genetic structure and epidemiology in other pathogens of human and wildlife importance.

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