Evolution of intermediate latency strategies in seasonal parasites.

Traditional mechanistic trade-offs between transmission and parasite latency period length are foundational for nearly all theories on the evolution of parasite life-history strategies. Prior theoretical studies demonstrate that seasonal host activity can generate a trade-off for obligate-host killer parasites that selects for intermediate latency periods in the absence of a mechanistic trade-off between transmission and latency period lengths. Extensions of these studies predict that host seasonal patterns can lead to evolutionary bistability for obligate-host killer parasites in which two evolutionarily stable strategies, a shorter and longer latency period, are possible. Here we demonstrate that these conclusions from previously published studies hold for non-obligate host killer parasites. That is, seasonal host activity can select for intermediate parasite latency periods for non-obligate killer parasites in the absence of a trade-off between transmission and latency period length and can maintain multiple evolutionarily stable parasite life-history strategies. These results reinforce the hypothesis that host seasonal activity can act as a major selective force on parasite life-history evolution by extending the narrower prior theory to encompass a greater range of disease systems.

Assessing the impact of areal unit selection and the modifiable areal unit problem on associative statistics between cases of tick-borne disease and entomological indices.

The modifiable areal unit problem (MAUP) is a cause of statistical and visual bias when aggregating data according to spatial units, particularly when spatial units may be changed arbitrarily. The MAUP is a concern in vector-borne disease research when entomological metrics gathered from point-level sampling data are related to epidemiological data aggregated to administrative units like counties or ZIP Codes. Here, we assess the statistical impact of the MAUP when calculating correlations between randomly aggregated cases of anaplasmosis in New York State during 2017 and a geostatistical layer of an entomological risk index for Anaplasma phagocytophilum in blacklegged ticks (Ixodes scapularis Say, Acari: Ixodidae) collected during the fall of 2017. Correlations were also calculated using various administrative boundaries for comparison. We also demonstrate the impact of the MAUP on data visualization using choropleth maps and offer pycnophylactic interpolation as an alternative. Polygon simulations indicate that increasing the number of polygons decreases correlation coefficients and their variability. Correlation coefficients calculated using ZIP Code tabulation area and Census tract polygons were beyond 4 standard deviations from the mean of the simulated correlation coefficients. These results indicate that using smaller polygons may not best incorporate the geographical context of the tick-borne disease system, despite the tendency of researchers to strive for more granular spatial data and associations.

Differential Resistance of Borrelia burgdorferi Clones to Human Serum-Mediated Killing Does Not Correspond to Their Predicted Invasiveness.

Reservoir host associations have been observed among and within Borrelia genospecies, and host complement-mediated killing is a major determinant in these interactions. In North America, only a subset of Borrelia burgdorferi lineages cause the majority of disseminated infections in humans. We hypothesize that differential resistance to human complement-mediated killing may be a major phenotypic determinant of whether a lineage can establish systemic infection. As a corollary, we hypothesize that borreliacidal action may differ among human subjects. To test these hypotheses, we isolated primary B. burgdorferi clones from field-collected ticks and determined whether the killing effects of human serum differed among those clones in vitro and/or whether these effects were consistent among human sera. Clones associated with human invasiveness did not show higher survival in human serum compared to noninvasive clones. These results indicate that differential complement-mediated killing of B. burgdorferi lineages is not a determinant of invasiveness in humans. Only one significant difference in the survivorship of individual clones incubated in different human sera was detected, suggesting that complement-mediated killing of B. burgdorferi is usually similar among humans. Mechanisms other than differential human complement-mediated killing of B. burgdorferi lineages likely explain why only certain lineages cause the majority of disseminated human infections.

Development of an mRNA-lipid nanoparticle vaccine against Lyme disease.

Lyme disease is the most common vector-borne infectious disease in the United States, in part because a vaccine against it is not currently available for humans. We propose utilizing the lipid nanoparticle-encapsulated nucleoside-modified mRNA (mRNA-LNP) platform to generate a Lyme disease vaccine like the successful clinical vaccines against SARS-CoV-2. Of the antigens expressed by Borrelia burgdorferi, the causative agent of Lyme disease, outer surface protein A (OspA) is the most promising candidate for vaccine development. We have designed and synthesized an OspA-encoding mRNA-LNP vaccine and compared its immunogenicity and protective efficacy to an alum-adjuvanted OspA protein subunit vaccine. OspA mRNA-LNP induced superior humoral and cell-mediated immune responses in mice after a single immunization. These potent immune responses resulted in protection against bacterial infection. Our study demonstrates that highly efficient mRNA vaccines can be developed against bacterial targets.

Variation among strains of Borrelia burgdorferi in host tissue abundance and lifetime transmission determine the population strain structure in nature.

Pathogen life history theory assumes a positive relationship between pathogen load in host tissues and pathogen transmission. Empirical evidence for this relationship is surprisingly rare due to the difficulty of measuring transmission for many pathogens. The comparative method, where a common host is experimentally infected with a set of pathogen strains, is a powerful approach for investigating the relationships between pathogen load and transmission. The validity of such experimental estimates of strain-specific transmission is greatly enhanced if they can predict the pathogen population strain structure in nature. Borrelia burgdorferi is a multi-strain, tick-borne spirochete that causes Lyme disease in North America. This study used 11 field-collected strains of B. burgdorferi, a rodent host (Mus musculus, C3H/HeJ) and its tick vector (Ixodes scapularis) to determine the relationship between pathogen load in host tissues and lifetime host-to-tick transmission (HTT). Mice were experimentally infected via tick bite with 1 of 11 strains. Lifetime HTT was measured by infesting mice with I. scapularis larval ticks on 3 separate occasions. The prevalence and abundance of the strains in the mouse tissues and the ticks were determined by qPCR. We used published databases to obtain estimates of the frequencies of these strains in wild I. scapularis tick populations. Spirochete loads in ticks and lifetime HTT varied significantly among the 11 strains of B. burgdorferi. Strains with higher spirochete loads in the host tissues were more likely to infect feeding larval ticks, which molted into nymphal ticks that had a higher probability of B. burgdorferi infection (i.e., higher HTT). Our laboratory-based estimates of lifetime HTT were predictive of the frequencies of these strains in wild I. scapularis populations. For B. burgdorferi, the strains that establish high abundance in host tissues and that have high lifetime transmission are the strains that are most common in nature.

Parasite-mediated selection on host phenology.

The timing of seasonal activity, or phenology, is an adaptive trait that maximizes individual fitness by timing key life events to coincide with favorable abiotic factors and biotic interactions. Studies on the biotic interactions that determine optimal phenology have focused on temporal overlaps among positively-interacting species such as mutualisms. Less well understood is the extent that negative interactions such as parasitism impact the evolution of host phenology. Here, we present a mathematical model demonstrating the evolution of host phenological patterns in response to sterilizing parasites. Environments with parasites favor hosts with shortened activity periods or greater distributions in emergence timing, both of which reduce the temporal overlap between hosts and parasites and thus reduce infection risk. Although host populations with these altered phenological patterns are less likely to mature and reproduce, the fitness advantage of parasite avoidance can be greater than the cost of reduced reproduction. These results illustrate the impact of parasitism on the evolution of host phenology and suggest that shifts in host phenology could serve as a strategy to mitigate the risk of infection.

A fast machine-learning-guided primer design pipeline for selective whole genome amplification.

Addressing many of the major outstanding questions in the fields of microbial evolution and pathogenesis will require analyses of populations of microbial genomes. Although population genomic studies provide the analytical resolution to investigate evolutionary and mechanistic processes at fine spatial and temporal scales-precisely the scales at which these processes occur-microbial population genomic research is currently hindered by the practicalities of obtaining sufficient quantities of the relatively pure microbial genomic DNA necessary for next-generation sequencing. Here we present swga2.0, an optimized and parallelized pipeline to design selective whole genome amplification (SWGA) primer sets. Unlike previous methods, swga2.0 incorporates active and machine learning methods to evaluate the amplification efficacy of individual primers and primer sets. Additionally, swga2.0 optimizes primer set search and evaluation strategies, including parallelization at each stage of the pipeline, to dramatically decrease program runtime. Here we describe the swga2.0 pipeline, including the empirical data used to identify primer and primer set characteristics, that improve amplification performance. Additionally, we evaluate the novel swga2.0 pipeline by designing primer sets that successfully amplify Prevotella melaninogenica, an important component of the lung microbiome in cystic fibrosis patients, from samples dominated by human DNA.

Modeling Tick Populations: An Ecological Test Case for Gradient Boosted Trees.

General linear models have been the foundational statistical framework used to discover the ecological processes that explain the distribution and abundance of natural populations. Analyses of the rapidly expanding cache of environmental and ecological data, however, require advanced statistical methods to contend with complexities inherent to extremely large natural data sets. Modern machine learning frameworks such as gradient boosted trees efficiently identify complex ecological relationships in massive data sets, which are expected to result in accurate predictions of the distribution and abundance of organisms in nature. However, rigorous assessments of the theoretical advantages of these methodologies on natural data sets are rare. Here we compare the abilities of gradient boosted and linear models to identify environmental features that explain observed variations in the distribution and abundance of blacklegged tick (Ixodes scapularis) populations in a data set collected across New York State over a ten-year period. The gradient boosted and linear models use similar environmental features to explain tick demography, although the gradient boosted models found non-linear relationships and interactions that are difficult to anticipate and often impractical to identify with a linear modeling framework. Further, the gradient boosted models predicted the distribution and abundance of ticks in years and areas beyond the training data with much greater accuracy than their linear model counterparts. The flexible gradient boosting framework also permitted additional model types that provide practical advantages for tick surveillance and public health. The results highlight the potential of gradient boosted models to discover novel ecological phenomena affecting pathogen demography and as a powerful public health tool to mitigate disease risks.

Selective whole-genome amplification reveals population genetics of Leishmania braziliensis directly from patient skin biopsies.

In Brazil, Leishmania braziliensis is the main causative agent of the neglected tropical disease, cutaneous leishmaniasis (CL). CL presents on a spectrum of disease severity with a high rate of treatment failure. Yet the parasite factors that contribute to disease presentation and treatment outcome are not well understood, in part because successfully isolating and culturing parasites from patient lesions remains a major technical challenge. Here we describe the development of selective whole genome amplification (SWGA) for Leishmania and show that this method enables culture-independent analysis of parasite genomes obtained directly from primary patient skin samples, allowing us to circumvent artifacts associated with adaptation to culture. We show that SWGA can be applied to multiple Leishmania species residing in different host species, suggesting that this method is broadly useful in both experimental infection models and clinical studies. SWGA carried out directly on skin biopsies collected from patients in Corte de Pedra, Bahia, Brazil, showed extensive genomic diversity. Finally, as a proof-of-concept, we demonstrated that SWGA data can be integrated with published whole genome data from cultured parasite isolates to identify variants unique to specific geographic regions in Brazil where treatment failure rates are known to be high. SWGA provides a relatively simple method to generate Leishmania genomes directly from patient samples, unlocking the potential to link parasite genetics with host clinical phenotypes.

Associations of Anaplasma phagocytophilum Bacteria Variants in Ixodes scapularis Ticks and Humans, New York, USA.

Anaplasmosis, caused by the tickborne bacterium Anaplasma phagocytophilum, is an emerging public health threat in the United States. In the northeastern United States, the blacklegged tick (Ixodes scapularis) transmits the human pathogenic genetic variant of A. phagocytophilum (Ap-ha) and a nonpathogenic variant (Ap-V1). New York has recently experienced a rapid and geographically focused increase in cases of anaplasmosis. We analyzed A. phagocytophilum-infected I. scapularis ticks collected across New York during 2008-2020 to differentiate between variants and calculate an entomological risk index (ERI) for each. Ap-ha ERI varied between regions and increased in all regions during the final years of the study. Space-time scan analyses detected expanding clusters of Ap-ha located within documented anaplasmosis hotspots. Ap-ha ERI was more positively correlated with anaplasmosis incidence than non-genotyped A. phagocytophilum ERI. Our findings help elucidate the relationship between the spatial ecology of A. phagocytophilum variants and anaplasmosis.

Host Phenology Can Select for Multiple Stable Parasite Virulence Strategies in Obligate Killer Parasites.

AbstractThe timing of seasonal host activity, or host phenology, is an important driver of parasite transmission dynamics and evolution. Despite the vast diversity of parasites in seasonal environments, the impact of phenology on parasite diversity remains relatively understudied. For example, little is known about the selective pressures and environmental conditions that favor a monocyclic strategy (complete a single cycle of infection per season) or a polycyclic strategy (complete multiple cycles). Here, we present a mathematical model that demonstrates that seasonal host activity patterns can generate evolutionary bistability in which two evolutionarily stable strategies (ESSs) are possible. The ESS that a particular system reaches is a function of the virulence strategy initially introduced into the system. The results demonstrate that host phenology can, in theory, maintain diverse parasite strategies among isolated geographic locations.

Deployment of a Reservoir-Targeted Vaccine Against Borrelia burgdorferi Reduces the Prevalence of Babesia microti Coinfection in Ixodes scapularis Ticks.

In the Northeast and upper Midwest of the United States, Babesia microti and Borrelia burgdorferi use Ixodes scapularis ticks as vector and Peromyscus leucopus mice as major reservoir host. We previously established, in a 5-year field trial, that a reservoir-targeted outer surface protein A vaccine reduces the prevalence of B. burgdorferi-infected ticks. We accessed ticks and mouse blood samples collected during the trial, extracted total DNA, and amplified the B. microti 18S rRNA gene. Vaccine deployment reduced the prevalence of ticks coinfected with B. microti and that of mice infected with B. microti. Breaking the enzootic cycle of B. burgdorferi may reduce the incidence of babesiosis.

Borrelia burgdorferi strain and host sex influence pathogen prevalence and abundance in the tissues of a laboratory rodent host.

Experimental infections with different pathogen strains give insight into pathogen life history traits. The purpose of the present study was to compare variation in tissue infection prevalence and spirochete abundance among strains of Borrelia burgdorferi in a rodent host (Mus musculus, C3H/HeJ). Male and female mice were experimentally infected via tick bite with one of 12 strains. Ear tissue biopsies were taken at days 29, 59 and 89 postinfection, and seven tissues were collected at necropsy. The presence and abundance of spirochetes in the mouse tissues were measured by quantitative polymerase chain reaction. To determine the frequencies of our strains in nature, their multilocus sequence types were matched to published data sets. For the infected mice, 56.6% of the tissues were infected with B. burgdorferi. The mean spirochete load in the mouse necropsy tissues varied 4.8-fold between the strains. The mean spirochete load in the ear tissue biopsies decreased rapidly over time for some strains. The percentage of infected tissues in male mice (65.4%) was significantly higher compared to female mice (50.5%). The mean spirochete load in the seven tissues was 1.5× higher in male mice compared to female mice; this male bias was 15.3× higher in the ventral skin. Across the 11 strains, the mean spirochete loads in the infected mouse tissues were positively correlated with the strain-specific frequencies in their tick vector populations. The study suggests that laboratory-based estimates of pathogen abundance in host tissues can predict the strain composition of this important tick-borne pathogen in nature.

A Borrelia burgdorferi outer surface protein C (OspC) genotyping method using Luminex technology.

Borrelia burgdorferi is an important tickborne human pathogen comprising several strains based on nucleotide sequence of the outer surface protein C (ospC) gene. Detection and characterization of different ospC genotypes is vital for research on B. burgdorferi and the risk it poses to humans. Here we present a novel, multiplex assay based on Luminex xMAP technology for the detection of B. burgdorferi ospC genotypes. The assay has five major steps: amplification of the ospC gene, hydrolyzation of surplus primers and nucleotides, incorporation of biotinylated nucleotides into the template DNA, hybridization to Luminex microspheres, and detection of fluorescent signals corresponding to each ospC genotype. We validated the protocol by comparing results obtained from our method against results from an established ospC genotyping method. This protocol can be used for the characterization of ospC genotypes in B. burgdorferi infected ticks, reservoir hosts, and/or clinical samples.

Phylogeographic dynamics of the arthropod vector, the blacklegged tick (Ixodes scapularis).

BACKGROUND: The emergence of vector-borne pathogens in novel geographic areas is regulated by the migration of their arthropod vectors. Blacklegged ticks (Ixodes scapularis) and the pathogens they vector, including the causative agents of Lyme disease, babesiosis and anaplasmosis, continue to grow in their population sizes and to expand in geographic range. Migration of this vector over the previous decades has been implicated as the cause of the re-emergence of the most prevalent infectious diseases in North America. METHODS: We systematically collected ticks from across New York State (hereafter referred to as New York) from 2004 to 2017 as part of routine tick-borne pathogen surveillance in the state. This time frame corresponds with an increase in range and incidence of tick-borne diseases within New York. We randomly sampled ticks from this collection to explore the evolutionary history and population dynamics of I. scapularis. We sequenced the mitochondrial genomes of each tick to characterize their current and historical spatial genetic structure and population growth using phylogeographic methods. RESULTS: We sequenced whole mitochondrial genomes from 277 ticks collected across New York between 2004 and 2017. We found evidence of population genetic structure at a broad geographic scale due to differences in the relative abundance, but not the composition, of haplotypes among sampled ticks. Ticks were often most closely related to ticks from the same and nearby collection sites. The data indicate that both short- and long-range migration events shape the population dynamics of blacklegged ticks in New York. CONCLUSIONS: We detailed the population dynamics of the blacklegged tick (Ixodes scapularis) in New York during a time frame in which tick-borne diseases were increasing in range and incidence. Migration of ticks occurred at both coarse and fine scales in the recent past despite evidence of limits to gene flow. Past and current tick population dynamics have implications for further range expansion as habitat suitability for ticks changes due to global climate change. Analyses of mitochondrial genome sequencing data will expound upon previously identified drivers of tick presence and abundance as well as identify additional drivers. These data provide a foundation on which to generate testable hypotheses on the drivers of tick population dynamics occurring at finer scales.

Host phenology can drive the evolution of intermediate virulence strategies in some obligate-killer parasites.

Traditional mechanistic trade-offs between transmission and virulence are the foundation of nearly all theory on parasite virulence evolution. For obligate-host killer parasites, evolution toward intermediate virulence depends on a trade-off between virulence (time to death) and transmission (the number of progeny released upon death). Although several ecological factors impact optimal virulence strategies constrained by trade-offs, these factors have been insufficient to explain the intermediate virulence levels observed in nature. The timing of seasonal activity, or phenology, is a factor that commonly influences ecological interactions but is difficult to incorporate into virulence evolution studies. We present a mathematical model of a seasonal obligate-killer parasite to study the impact of host phenology on virulence evolution. The model demonstrates that host phenology can select for intermediate parasite virulence even when a traditional mechanistic trade-off between transmission and virulence is omitted. The optimal virulence strategy is impacted by both the host activity period duration and the host emergence timing variation. Parasites with lower virulence strategies are favored in environments with longer host activity periods and when hosts emerge synchronously. The results demonstrate that host phenology can be sufficient to select for intermediate virulence strategies, providing an alternative driver of virulence evolution in some natural systems.

Host phenology regulates parasite-host demographic cycles and eco-evolutionary feedbacks.

Parasite-host interactions can drive periodic population dynamics when parasites overexploit host populations. The timing of host seasonal activity, or host phenology, determines the frequency and demographic impact of parasite-host interactions, which may govern whether parasites sufficiently overexploit hosts to drive population cycles. We describe a mathematical model of a monocyclic, obligate-killer parasite system with seasonal host activity to investigate the consequences of host phenology on host-parasite dynamics. The results suggest that parasites can reach the densities necessary to destabilize host dynamics and drive cycling as they adapt, but only in some phenological scenarios such as environments with short seasons and synchronous host emergence. Furthermore, only parasite lineages that are sufficiently adapted to phenological scenarios with short seasons and synchronous host emergence can achieve the densities necessary to overexploit hosts and produce population cycles. Host-parasite cycles also generate an eco-evolutionary feedback that slows parasite adaptation to the phenological environment as rare advantageous phenotypes can be driven extinct due to a population bottleneck depending on when they are introduced in the cycle. The results demonstrate that seasonal environments can drive population cycling in a restricted set of phenological patterns and provide further evidence that the rate of adaptive evolution depends on underlying ecological dynamics.

Predicting spatio-temporal population patterns of Borrelia burgdorferi, the Lyme disease pathogen.

The causative bacterium of Lyme disease, Borrelia burgdorferi, expanded from an undetected human pathogen into the etiologic agent of the most common vector-borne disease in the United States over the last several decades. Systematic field collections of the tick vector reveal increases in the geographic range and prevalence of B. burgdorferi-infected ticks that coincided with increases in human Lyme disease incidence across New York State.We investigate the impact of environmental features on the population dynamics of B. burgdorferi. Analytical models developed using field collections of nearly 19,000 nymphal Ixodes scapularis and spatially and temporally explicit environmental features accurately explained the variation in the nymphal infection prevalence of B. burgdorferi across space and time.Importantly, the model identified environmental features reflecting landscape ecology, vertebrate hosts, climatic metrics, climate anomalies and surveillance efforts that can be used to predict the biogeographical patterns of B. burgdorferi-infected ticks into future years and in previously unsampled areas.Forecasting the distribution and prevalence of a pathogen at fine geographic scales offers a powerful strategy to mitigate a serious public health threat. Synthesis and applications. A decade of environmental and tick data was collected to create a model that accurately predicts the infection prevalence of Borrelia burgdorferi over space and time. This predictive model can be extrapolated to create a high-resolution risk map of the Lyme disease pathogen for future years that offers an inexpensive approach to improve both ecological management and public health strategies to mitigate disease risk.

Estimating disease vector population size from citizen science data.

Citizen science projects have the potential to address hypotheses requiring extremely large datasets that cannot be collected with the financial and labour constraints of most scientific projects. Data collection by the general public could expand the scope of scientific enquiry if these data accurately capture the system under study. However, data collection inconsistencies by the untrained public may result in biased datasets that do not accurately represent the natural world. In this paper, we harness the availability of scientific and public datasets of the Lyme disease tick vector to identify and account for biases in citizen science tick collections. Estimates of tick abundance from the citizen science dataset correspond moderately with estimates from direct surveillance but exhibit consistent biases. These biases can be mitigated by including factors that may impact collector participation or effort in statistical models, which, in turn, result in more accurate estimates of tick population sizes. Accounting for collection biases within large-scale, public participation datasets could update species abundance maps and facilitate using the wealth of citizen science data to answer scientific questions at scales that are not feasible with traditional datasets.

The role of host phenology for parasite transmission.

Phenology is a fundamental determinant of species distributions, abundances, and interactions. In host-parasite interactions, host phenology can affect parasite fitness due to the temporal constraints it imposes on host contact rates. However, it remains unclear how parasite transmission is shaped by the wide range of phenological patterns observed in nature. We develop a mathematical model of the Lyme disease system to study the consequences of differential tick developmental-stage phenology for the transmission of B. burgdorferi. Incorporating seasonal tick activity can increase B. burgdorferi fitness compared to continuous tick activity but can also prevent transmission completely. B. burgdorferi fitness is greatest when the activity period of the infectious nymphal stage slightly precedes the larval activity period. Surprisingly, B. burgdorferi is eradicated if the larval activity period begins long after the end of nymphal activity due to a feedback with mouse population dynamics. These results highlight the importance of phenology, a common driver of species interactions, for the fitness of a parasite.