Effects of multiple sources of genetic drift on pathogen variation within hosts

Effects of plant tissue permeability on invasion and population bottlenecks of a phytopathogen

Pathogen genetic diversity varies in response to environmental changes. However, it remains unclear whether plant barriers to invasion could be considered a genetic bottleneck for phytopathogen populations. Here, we implement a barcoding approach to generate a pool of 90 isogenic and individually barcoded Ralstonia solanacearum strains. We used 90 of these strains to inoculate tomato plants with different degrees of physical permeability to invasion (intact roots, wounded roots and xylem inoculation) and quantify the phytopathogen population dynamics during invasion. Our results reveal that the permeability of plant roots impacts the degree of population bottleneck, genetic diversity, and composition of Ralstonia populations. We also find that selection is the main driver structuring pathogen populations when barriers to infection are less permeable, i.e., intact roots, the removal of root physical and immune barriers results in the predominance of stochasticity in population assembly. Taken together, our study suggests that plant root permeability constitutes a bottleneck for phytopathogen invasion and genetic diversity.

Infectious Disease Diagnosis and Pathogen Identification Platform Based on Multiplex Recombinase Polymerase Amplification-Assisted CRISPR-Cas12a System

Controlling and mitigating infectious diseases caused by multiple pathogens or pathogens with several subtypes require multiplex nucleic acid detection platforms that can detect several target genes rapidly, specifically, sensitively, and simultaneously. Here, we develop a detection platform, termed Multiplex Assay of RPA and Collateral Effect of Cas12a-based System (MARPLES), based on multiplex nucleic acid amplification and Cas12a ssDNase activation to diagnose these diseases and identify their pathogens. We use the clinical specimens of hand, foot, and mouth disease (HFMD) and influenza A to evaluate the feasibility of MARPLES in diagnosing the disease and identifying the pathogen, respectively, and find that MARPLES can accurately diagnose the HFMD associated with enterovirus 71, coxsackievirus A16 (CVA16), CVA6, or CVA10 and identify the exact types of H1N1 and H3N2 in an hour, showing high sensitivity and specificity and 100% predictive agreement with qRT-PCR. Collectively, our findings demonstrate that MARPLES is a promising multiplex nucleic acid detection platform for disease diagnosis and pathogen identification.

The evolution of host specialization in an insect pathogen

Niche breadth coevolution between biotic partners underpins theories of diversity and co-existence and influences patterns of disease emergence and transmission in host-parasite systems. Despite these broad implications, we still do not fully understand how the breadth of parasites' infectivity evolves, the nature of any associated costs, or the genetic basis of specialization. Here, we serially passage a granulosis virus on multiple inbred populations of its Plodia interpunctella host to explore the dynamics and outcomes of specialization. In particular, we collect time series of phenotypic and genetic data to explore the dynamics of host genotype specialization throughout the course of experimental evolution and examine two fitness components. We find that the Plodia interpunctella granulosis virus consistently evolves and increases in overall specialization, but that our two fitness components evolve independently such that lines can specialize in productivity or infectivity. Furthermore, we find that specialization in our experiment is a highly polygenic trait best explained by a combination of evolutionary mechanisms. These results are important for understanding the evolution of specialization in host-parasite interactions and its broader implications for co-existence, diversification, and infectious disease management.

Empirical estimates of the mutation rate for an alphabaculovirus

Mutation rates are of key importance for understanding evolutionary processes and predicting their outcomes. Empirical mutation rate estimates are available for a number of RNA viruses, but few are available for DNA viruses, which tend to have larger genomes. Whilst some viruses have very high mutation rates, lower mutation rates are expected for viruses with large genomes to ensure genome integrity. Alphabaculoviruses are insect viruses with large genomes and often have high levels of polymorphism, suggesting high mutation rates despite evidence of proofreading activity by the replication machinery. Here, we report an empirical estimate of the mutation rate per base per strand copying (s/n/r) of Autographa californica multiple nucleopolyhedrovirus (AcMNPV). To avoid biases due to selection, we analyzed mutations that occurred in a stable, non-functional genomic insert after five serial passages in Spodoptera exigua larvae. Our results highlight that viral demography and the stringency of mutation calling affect mutation rate estimates, and that using a population genetic simulation model to make inferences can mitigate the impact of these processes on estimates of mutation rate. We estimated a mutation rate of μ = 1×10⁻⁷ s/n/r when applying the most stringent criteria for mutation calling, and estimates of up to μ = 5×10⁻⁷ s/n/r when relaxing these criteria. The rates at which different classes of mutations accumulate provide good evidence for neutrality of mutations occurring within the inserted region. We therefore present a robust approach for mutation rate estimation for viruses with stable genomes, and strong evidence of a much lower alphabaculovirus mutation rate than supposed based on the high levels of polymorphism observed.

Virus populations can evolve rapidly, driven by the large number of mutations that occur during virus replication. It is challenging to measure mutation rates because selection will affect which mutations are observed: beneficial mutations are overrepresented in virus populations, while deleterious mutations are selected against and therefore underrepresented. Few mutation rates have been estimated for viruses with large DNA genomes, and there are no estimates for any insect virus. Here, we estimate the mutation rate for an alphabaculovirus, a virus that infects caterpillars and has a large, 134 kilobase pair DNA genome. To ensure that selection did not bias our estimate of mutation rate, we studied which mutations occurred in a large artificial region inserted into the virus genome, where mutations did not affect viral fitness. We deep sequenced evolved virus populations, and compared the distribution of observed mutants to predictions from a simulation model to estimate mutation rate. We found evidence for a relatively low mutation rate, of one mutation in every 10 million bases replicated. This estimate is in line with expectations for a DNA virus with self-correcting replication machinery and a large genome.

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.

Long-read sequencing reveals the evolutionary drivers of intra-host diversity across natural RNA mycovirus infections

Intra-host dynamics are a core component of virus evolution but most intra-host data come from a narrow range of hosts or experimental infections. Gaining broader information on the intra-host diversity and dynamics of naturally occurring virus infections is essential to our understanding of evolution across the virosphere. Here we used PacBio long-read HiFi sequencing to characterize the intra-host populations of natural infections of the RNA mycovirus Cryphonectria hypovirus 1 (CHV1). CHV1 is a biocontrol agent for the chestnut blight fungus (Cryphonectria parasitica), which co-invaded Europe alongside the fungus. We characterized the mutational and haplotypic intra-host virus diversity of thirty-eight natural CHV1 infections spread across four locations in Croatia and Switzerland. Intra-host CHV1 diversity values were shaped by purifying selection and accumulation of mutations over time as well as epistatic interactions within the host genome at defense loci. Geographical landscape features impacted CHV1 inter-host relationships through restricting dispersal and causing founder effects. Interestingly, a small number of intra-host viral haplotypes showed high sequence similarity across large geographical distances unlikely to be linked by dispersal.

Generation of Variability in Chrysodeixis includens Nucleopolyhedrovirus (ChinNPV): The Role of a Single Variant

The mechanisms generating variability in viruses are diverse. Variability allows baculoviruses to evolve with their host and with changes in their environment. We examined the role of one genetic variant of Chrysodeixis includens nucleopolyhedrovirus (ChinNPV) and its contribution to the variability of the virus under laboratory conditions. A mixture of natural isolates (ChinNPV-Mex1) contained two genetic variants that dominated over other variants in individual larvae that consumed high (ChinNPV-K) and low (ChinNPV-E) concentrations of inoculum. Studies on the ChinNPV-K variant indicated that it was capable of generating novel variation in a concentration-dependent manner. In cell culture, cells inoculated with high concentrations of ChinNPV-K produced OBs with the ChinNPV-K REN profile, whereas a high diversity of ChinNPV variants was recovered following plaque purification of low concentrations of ChinNPV-K virion inoculum. Interestingly, the ChinNPV-K variant could not be recovered from plaques derived from low concentration inocula originating from budded virions or occlusion-derived virions of ChinNPV-K. Genome sequencing revealed marked differences between ChinNPV-K and ChinNPV-E, with high variation in the ChinNPV-K genome, mostly due to single nucleotide polymorphisms. We conclude that ChinNPV-K is an unstable genetic variant that is responsible for generating much of the detected variability in the natural ChinNPV isolates used in this study.

28 Models Later: Model Competition and the Zombie Apocalypse

Between Fall 2011 and Fall 2012 students at Utah State University played several rounds of Humans versus Zombies (HvZ), a role-playing variant of tag popular on college campuses. The goal of the game is for the zombies to tag humans, converting them into more zombies. Based on portrayals of 'zombieism' in popular culture, one might treat HvZ as a disease system. However, a traditional SIR model with mass-action dynamics does a poor job of modeling HvZ, leading to the natural question: What mechanisms drive the dynamics of the HvZ system? We use model competition, with Bayesian Information Criterion as arbiter, to answer this question. First, we develop a suite of models with a variety of transmission mechanisms and fit to data from fall 2011. We use model competition to determine which model(s) have the most support from the data, thereby offering insight into driving mechanisms for HvZ. Bootstrapping is used to both assess the significance of individual mechanisms and to determine confidence in the performance of our models. Finally, we test predictions of the best models with data from fall 2012. Results indicate that through both years of the game humans tend to cluster defensively, zombies tend to hunt in groups, some zombies are more proficient hunters, and some humans leave the game.

Current scenario of COVID-19 in pediatric age group and physiology of immune and thymus response

COVID-19 pandemic caused by SARS-CoV-2, continues to manifest with severe acute respiratory syndrome among the adults, however, it offers a convincing indication of less severity and fatality in pediatric age group (0-18 years). The current trend suggests that children may get infected but are less symptomatic with less fatality, which is concordant to earlier epidemic outbreaks of SARS-CoV and MERS-CoV, in 2002 and 2012, respectively. According to the available data, children appear to be at lower risk for COVID-19, as adults constitute for maximum number of the confirmed cases (308,592) and deaths (13,069) as on 22nd March (https://www.worldometers.info/coronavirus). However, rapid publications and information of the adult patients with COVID-19 is in progress and published, on the contrary, almost no comprehensive data or discussion about the COVID-19 in children is available. Therefore, in this review, we outline the epidemiology, clinical symptoms, diagnosis, treatment, prevention, possible immune response and role of thymus in children to combat the COVID-19 outbreak.

Resource quality determines the evolution of resistance and its genetic basis

Parasites impose strong selection on their hosts, but the level of any evolved resistance may be constrained by the availability of resources. However, studies identifying the genomic basis of such resource-mediated selection are rare, particularly in nonmodel organisms. Here, we investigated the role of nutrition in the evolution of resistance to a DNA virus (PiGV), and any associated trade-offs in a lepidopteran pest species (Plodia interpunctella). Through selection experiments and whole-genome resequencing, we identify genetic markers of resistance that vary between the nutritional environments during selection. We do not find consistent evolution of resistance in the presence of virus but rather see substantial variation among replicate populations. Resistance in a low-nutrition environment is negatively correlated with growth rate, consistent with an established trade-off between immunity and development, but this relationship is highly context dependent. Whole-genome resequencing of the host shows that resistance mechanisms are likely to be highly polygenic and although the underlying genetic architecture may differ between high and low-nutrition environments, similar mechanisms are commonly used. As a whole, our results emphasize the importance of the resource environment on influencing the evolution of resistance.

Molecular phylogeny of sturgeon mimiviruses and Bayesian hierarchical modeling of their effect on wild Lake Sturgeon (Acipenser fulvescens) in Central Canada

Sturgeon mimiviruses can cause a lethal disease of the integumentary systems of sturgeon (Acipenseridae). Here we provide phylogeographic evidence that sturgeon mimivirus is endemic in endangered populations of wild Lake Sturgeon within Canada's Hudson Bay drainage basin. Namao virus (NV) variants were diagnosed in 24% of Lake Sturgeon samples (n = 1329) collected between 2010-2015. Lake Sturgeon populations with the highest virus prevalence were from the Nelson River (58%) in 2015, Saskatchewan River (41%) in 2010 and South Saskatchewan River (36%) in 2011. Bayesian phylogenetic reconstructions suggested that four NV variants, designated HBDB I-IV, co-circulate temporally and spatially within and between the genetically and biogeographically distinct Lake Sturgeon populations. Evidence from recapture studies suggested that Lake Sturgeon across the basin are persistently infected with NV at prevalence and titer (10^3.6 equivalent plasmid copies per μg DNA) levels consistent with the hypothesis that wild Lake Sturgeon populations serve as a maintenance population and reservoir for sturgeon mimiviruses. Bayesian hierarchical modeling of NV in the Landing River population of Lake Sturgeon suggested that host weight and age were the best predictors of sturgeon mimivirus presence and titer, respectively, whereas water flow rate, level and temperature, and number of previous captures did not significantly improve model fit. A negative relationship was estimated between sturgeon mimivirus presence and Lake Sturgeon weight and between virus titer and Lake Sturgeon age.

Within-Host Viral Diversity: A Window into Viral Evolution

The evolutionary dynamics of a virus can differ within hosts and across populations. Studies of within-host evolution provide an important link between experimental studies of virus evolution and large-scale phylodynamic analyses. They can determine the extent to which global processes are recapitulated on local scales and how accurately experimental infections model natural ones. They may also inform epidemiologic models of disease spread and reveal how host-level dynamics contribute to a virus's evolution at a larger scale. Over the last decade, advances in viral sequencing have enabled detailed studies of viral genetic diversity within hosts. I review how within-host diversity is sampled, measured, and expressed, and how comparative studies of viral diversity can be leveraged to elucidate a virus's evolutionary dynamics. These concepts are illustrated with detailed reviews of recent research on the within-host evolution of influenza virus, dengue virus, and cytomegalovirus.

Understanding the Evolutionary Ecology of host--pathogen Interactions Provides Insights into the Outcomes of Insect Pest Biocontrol

The use of viral pathogens to control thepopulation size of pest insects has produced both successful and unsuccessful outcomes. Here, we investigate whether those biocontrol successes and failures can be explained by key ecological and evolutionary processes between hosts and pathogens. Specifically, we examine how heterogeneity inpathogen transmission, ecological and evolutionary tradeoffs, andpathogen diversity affect insect population density and thus successful control. Wefirst review theexisting literature and then use numerical simulations of mathematical models to further explore these processes. Our results show that thecontrol of insect densities using viruses depends strongly on theheterogeneity of virus transmission among insects. Overall, increased heterogeneity of transmission reduces theeffect of viruses on insect densities and increases thelong-term stability of insect populations. Lower equilibrium insect densities occur when transmission is heritable and when there is atradeoff between mean transmission and insect fecundity compared to when theheterogeneity of transmission arises from non-genetic sources. Thus, theheterogeneity of transmission is akey parameter that regulates thelong-term population dynamics of insects and their pathogens. Wealso show that both heterogeneity of transmission and life-history tradeoffs modulate characteristics of population dynamics such as thefrequency and intensity of ``boom--bust" population cycles. Furthermore, we show that because of life-history tradeoffs affecting thetransmission rate, theuse of multiple pathogen strains is more effective than theuse of asingle strain to control insect densities only when thepathogen strains differ considerably intheir transmission characteristics. By quantifying theeffects of ecology and evolution on population densities, we are able to offer recommendations to assess thelong-term effects of classical biocontrol.

Linked within-host and between-host models and data for infectious diseases: a systematic review

The observed dynamics of infectious diseases are driven by processes across multiple scales. Here we focus on two: within-host, that is, how an infection progresses inside a single individual (for instance viral and immune dynamics), and between-host, that is, how the infection is transmitted between multiple individuals of a host population. The dynamics of each of these may be influenced by the other, particularly across evolutionary time. Thus understanding each of these scales, and the links between them, is necessary for a holistic understanding of the spread of infectious diseases. One approach to combining these scales is through mathematical modeling. We conducted a systematic review of the published literature on multi-scale mathematical models of disease transmission (as defined by combining within-host and between-host scales) to determine the extent to which mathematical models are being used to understand across-scale transmission, and the extent to which these models are being confronted with data. Following the PRISMA guidelines for systematic reviews, we identified 24 of 197 qualifying papers across 30 years that include both linked models at the within and between host scales and that used data to parameterize/calibrate models. We find that the approach that incorporates both modeling with data is under-utilized, if increasing. This highlights the need for better communication and collaboration between modelers and empiricists to build well-calibrated models that both improve understanding and may be used for prediction.

Evaluating the Within-Host Dynamics of Ranavirus Infection with Mechanistic Disease Models and Experimental Data

Mechanistic models are critical for our understanding of both within-host dynamics (i.e., pathogen replication and immune system processes) and among-host dynamics (i.e., transmission). Within-host models, however, are not often fit to experimental data, which can serve as a robust method of hypothesis testing and hypothesis generation. In this study, we use mechanistic models and empirical, time-series data of viral titer to better understand the replication of ranaviruses within their amphibian hosts and the immune dynamics that limit viral replication. Specifically, we fit a suite of potential models to our data, where each model represents a hypothesis about the interactions between viral replication and immune defense. Through formal model comparison, we find a parsimonious model that captures key features of our time-series data: The viral titer rises and falls through time, likely due to an immune system response, and that the initial viral dosage affects both the peak viral titer and the timing of the peak. Importantly, our model makes several predictions, including the existence of long-term viral infections, which can be validated in future studies.