Experimental evolution and genome sequencing reveal variation in levels of clonal interference in large populations of bacteriophage φX174

<p>Abstract</p> <p>Background</p> <p>In large asexual populations where beneficial mutations may co-occur and recombination is absent, the fate of beneficial mutations can be significantly affected by competition (i.e., clonal interference). Theoretical models predict that clonal interference (CI) can slow adaptation, alter the distribution of fixed beneficial mutations, and affect disease progression by impacting within-host evolution of pathogens. While phenotypic data support that CI is a significant determinant of adaptive outcome, genetic data are needed to verify the patterns and to inform evolutionary models. We adapted replicate populations of the bacteriophage φX174 under two levels of CaCl₂to create benign and harsh environments. Genomic sequences of multiple individuals from evolved populations were used to detect competing beneficial mutations.</p> <p>Results</p> <p>There were several competing genotypes in most of the populations where CaCl₂was abundant, but no evidence of CI where CaCl₂was scarce, even though rates of adaptation and population sizes among the treatments were similar. The sequence data revealed that observed mutations were limited to a single portion of one gene in the harsh treatment, but spanned a different and larger region of the genome under the benign treatments, suggesting that there were more adaptive solutions to the benign treatment.</p> <p>Conclusion</p> <p>Beneficial mutations with relatively large selection coefficients can be excluded by CI. CI may commonly determine the fate of beneficial mutations in large microbial populations, but its occurrence depends on selective conditions. CI was more frequent in benign selective conditions possibly due to a greater number of adaptive targets under this treatment. Additionally, the genomic sequence data showed that selection can target different types and numbers of phenotypes in environments that differ by only a single continuous variable.</p

BOARD INVITED REVIEW: Prospects for improving management of animal disease introductions using disease-dynamic models

Management and policy decisions are continually made to mitigate disease introductions in animal populations despite often limited surveillance data or knowledge of disease transmission processes. Science-based management is broadly recognized as leading to more effective decisions yet application of models to actively guide disease surveillance and mitigate risks remains limited. Disease-dynamic models are an efficient method of providing information for management decisions because of their ability to integrate and evaluate multiple, complex processes simultaneously while accounting for uncertainty common in animal diseases. Here we review disease introduction pathways and transmission processes crucial for informing disease management and models at the interface of domestic animals and wildlife. We describe how disease transmission models can improve disease management and present a conceptual framework for integrating disease models into the decision process using adaptive management principles. We apply our framework to a case study of African swine fever virus in wild and domestic swine to demonstrate how disease-dynamic models can improve mitigation of introduction risk. We also identify opportunities to improve the application of disease models to support decision-making to manage disease at the interface of domestic and wild animals. First, scientists must focus on objective-driven models providing practical predictions that are useful to those managing disease. In order for practical model predictions to be incorporated into disease management a recognition that modeling is a means to improve management and outcomes is important. This will be most successful when done in a cross-disciplinary environment that includes scientists and decisionmakers representing wildlife and domestic animal health. Lastly, including economic principles of value-of-information and cost-benefit analysis in disease-dynamic models can facilitate more efficient management decisions and improve communication of model forecasts. Integration of disease-dynamic models into management and decision-making processes is expected to improve surveillance systems, risk mitigations, outbreak preparedness, and outbreak response activities

Disease-emergence dynamics and control in a socially-structured wildlife species

Once a pathogen is introduced in a population, key factors governing rate of spread include contact structure, supply of susceptible individuals and pathogen life-history. We examined the interplay of these factors on emergence dynamics and efficacy of disease prevention and response. We contrasted transmission dynamics of livestock viruses with different life-histories in hypothetical populations of feral swine with different contact structures (homogenous, metapopulation, spatial and network). Persistence probability was near 0 for the FMDV-like case under a wide range of parameter values and contact structures, while persistence was probable for the CSFV-like case. There were no sets of conditions where the FMDV-like pathogen persisted in every stochastic simulation. Even when population growth rates were up to 300% annually, the FMDV-like pathogen persisted in \u3c25% of simulations regardless of transmission probabilities and contact structure. For networks and spatial contact structure, persistence probability of the FMDV-like pathogen was always \u3c10%. Because of its low persistence probability, even very early response to the FMDV-like pathogen in feral swine was unwarranted while response to the CSFV-like pathogen was generally effective. When pre-emergence culling of feral swine caused population declines, it was effective at decreasing outbreak size of both diseases by ≥80%

Evaluating wildlife-cattle contact rates to improve the understanding of dynamics of bovine tuberculosis transmission in Michigan, USA

Direct and indirect contacts among individuals drive transmission of infectious disease. When multiple interacting species are susceptible to the same pathogen, risk assessment must include all potential host species. Bovine tuberculosis (bTB) is an example of a disease that can be transmitted among several wildlife species and to cattle, although the potential role of several wildlife species in spillback to cattle remains unclear. To better understand the complex network of contacts and factors driving disease transmission, we fitted proximity logger collars to beef and dairy cattle (n = 37), white-tailed deer (Odocoileus virginianus; n=29), raccoon (Procyon lotor; n=53), and Virginia opossum (Didelphis virginiana; n=79) for 16 months in Michigan\u27s Lower Peninsula, USA. We determined inter- and intra-species direct and indirect contact rates. Data on indirect contact was calculated when collared animals visited stationary proximity loggers placed at cattle feed and water resources. Most contact between wildlife species and cattle was indirect, with the highest contact rates occurring between raccoons and cattle during summer and fall. Nearly all visits (\u3e99%) to cattle feed and water sources were by cattle, whereas visitation to stored cattle feed was dominated by deer and raccoon (46% and 38%, respectively). Our results suggest that indirect contact resulting from wildlife species visiting cattle-related resources could pose a risk of disease transmission to cattle and deserves continued attention with active mitigation

Optimal bait density for delivery of acute toxicants to vertebrate pests

Oral baiting is a fundamental method for delivering toxicants to pest species. Planning baiting strategies is challenging because bait-consumption rates depend on dynamic processes including space use and demographics of the target species. To determine cost-effective strategies for optimizing baiting, we developed a spatially explicit model of population dynamics using field-based measures of wild-pig (Sus scrofa) space use, bait consumption, and mortality probabilities. The most cost-effective baiting strategy depended strongly on the population reduction objective and initial density. A wide range of baiting strategies were cost-effective when the objective was 80% population reduction. In contrast, only a narrow range of baiting strategies allowed for a 99% reduction. Cost-effectiveness was lower for low densities of wild pigs because of the increased effort for locating target animals. Bait avoidance due to aversive conditioning from sub-lethal dosing had only minor effects on cost-effectiveness when the objective was an 80% reduction, whereas the effect was much stronger when the objective was 99% population reduction. Our results showed that a bait-based toxicant could be cost-effective for substantially reducing populations of wild pigs, but for elimination it may be most cost-effective to integrate additional management techniques following initial toxicant deployment. The nonlinear interaction of cost-effectiveness, initial population size, and reduction objective also emphasized the importance of considering the dynamics of space use and bait consumption for predicting effective baiting strategies. Although we used data for an acute toxicant and wild-pig consumption rates, our framework can be readily adapted to other vertebrate pest species and toxicant characteristics

Efficiency of different spatial and temporal strategies for reducing vertebrate pest populations

Understanding effectiveness of control strategies of pest species is fundamental for planning efficient and cost-effective management programs. In addition to culling rates, there are many potential factors that can determine efficiency of different management strategies, including demographic processes such as immigration rates, birth dynamics, and spatial ecology. We developed a stochastic, data-based simulation model of feral swine population dynamics which accounted for social dynamics in space. We tested the impacts of different spatio-temporal management strategies (i.e., culling rates, timing of culling during the year, spatial pattern of culling and strength of a barrier to immigration) on population response and efficiency. The spatial culling strategy dramatically impacted efficiency of control – using zonation required removal of fewer pigs (up to 46% less) to achieve similar reductions compared with other spatial strategies. Also, our spatially-explicit model predicted that lower culling intensities could be used to achieve population reductions when zonation was applied relative to predictions from harvesting theory based on simple logistic models. As culling intensity increased (≥50% of target population annually) and the target population reached low density (\u3c5% of original density), effects of spatial strategy became less pronounced relative to immigration barrier effects. Lastly, for the same level of moderate culling effort, prioritization of culling during the low-birthing period generally resulted in faster population reduction to near zero abundance relative to prioritization during the high-birthing period, or spreading the work over a year period, but the significance of this effect depended on the spatial culling strategy and culling intensity. Our results imply that continually updating knowledge of current abundance during management may not only be important for determining culling quotas, but also for updating and optimizing management strategies. When the management goal is maximum population control, consideration of birth and spatial dynamics can increase return on management effort and bring to light management inefficiencies

Evaluating wildlife-cattle contact rates to improve the understanding of dynamics of bovine tuberculosis transmission in Michigan, USA

Direct and indirect contacts among individuals drive transmission of infectious disease. When multiple interacting species are susceptible to the same pathogen, risk assessment must include all potential host species. Bovine tuberculosis (bTB) is an example of a disease that can be transmitted among several wildlife species and to cattle, although the potential role of several wildlife species in spillback to cattle remains unclear. To better understand the complex network of contacts and factors driving disease transmission, we fitted proximity logger collars to beef and dairy cattle (n = 37), white-tailed deer (Odocoileus virginianus; n=29), raccoon (Procyon lotor; n=53), and Virginia opossum (Didelphis virginiana; n=79) for 16 months in Michigan\u27s Lower Peninsula, USA. We determined inter- and intra-species direct and indirect contact rates. Data on indirect contact was calculated when collared animals visited stationary proximity loggers placed at cattle feed and water resources. Most contact between wildlife species and cattle was indirect, with the highest contact rates occurring between raccoons and cattle during summer and fall. Nearly all visits (\u3e99%) to cattle feed and water sources were by cattle, whereas visitation to stored cattle feed was dominated by deer and raccoon (46% and 38%, respectively). Our results suggest that indirect contact resulting from wildlife species visiting cattle-related resources could pose a risk of disease transmission to cattle and deserves continued attention with active mitigation

Predicting spatial spread of rabies in skunk populations using surveillance data reported by the public

Background: Prevention and control of wildlife disease invasions relies on the ability to predict spatio-temporal dynamics and understand the role of factors driving spread rates, such as seasonality and transmission distance. Passive disease surveillance (i.e., case reports by public) is a common method of monitoring emergence of wildlife diseases, but can be challenging to interpret due to spatial biases and limitations in data quantity and quality. Methodology/Principal findings: We obtained passive rabies surveillance data from dead striped skunks (Mephitis mephitis) in an epizootic in northern Colorado, USA. We developed a dynamic patch-occupancy model which predicts spatio-temporal spreading while accounting for heterogeneous sampling. We estimated the distance travelled per transmission event, direction of invasion, rate of spatial spread, and effects of infection density and season. We also estimated mean transmission distance and rates of spatial spread using a phylogeographic approach on a subsample of viral sequences from the same epizootic. Both the occupancy and phylogeographic approaches predicted similar rates of spatio-temporal spread. Estimated mean transmission distances were 2.3 km (95% Highest Posterior Density (HPD95): 0.02, 11.9; phylogeographic) and 3.9 km (95% credible intervals (CI95): 1.4, 11.3; occupancy). Estimated rates of spatial spread in km/year were: 29.8 (HPD95: 20.8, 39.8; phylogeographic, branch velocity, homogenous model), 22.6 (HPD95: 15.3, 29.7; phylogeographic, diffusion rate, homogenous model) and 21.1 (CI95: 16.7, 25.5; occupancy). Initial colonization probability was twice as high in spring relative to fall. Conclusions/Significance: Skunk-to-skunk transmission was primarily local (&lt; 4 km) suggesting that if interventions were needed, they could be applied at the wave front. Slower viral invasions of skunk rabies in western USA compared to a similar epizootic in raccoons in the eastern USA implies host species or landscape factors underlie the dynamics of rabies invasions. Our framework provides a straightforward method for estimating rates of spatial spread of wildlife diseases

Rabies Surveillance Identifies Potential Risk Corridors and Enables Management Evaluation

Intensive efforts are being made to eliminate the raccoon variant of rabies virus (RABV) from the eastern United States and Canada. The United States Department of Agriculture (USDA) Wildlife Services National Rabies Management Program has implemented enhanced rabies surveillance (ERS) to improve case detection across the extent of the raccoon oral rabies vaccination (ORV) management area. We evaluated ERS and public health surveillance data from 2006 to 2017 in three northeastern USA states using a dynamic occupancy modeling approach. Our objectives were to examine potential risk corridors for RABV incursion from the U.S. into Canada, evaluate the effectiveness of ORV management strategies, and identify surveillance gaps. ORV management has resulted in a decrease in RABV cases over time within vaccination zones (from occupancy (ψ) of 0.60 standard error (SE) = 0.03 in the spring of 2006 to ψ of 0.33 SE = 0.10 in the spring 2017). RABV cases also reduced in the enzootic area (from ψ of 0.60 SE = 0.03 in the spring of 2006 to ψ of 0.45 SE = 0.05 in the spring 2017). Although RABV occurrence was related to habitat type, greater impacts were associated with ORV and trap–vaccinate–release (TVR) campaigns, in addition to seasonal and yearly trends. Reductions in RABV occupancy were more pronounced in areas treated with Ontario Rabies Vaccine Bait (ONRAB) compared to RABORAL V-RG®. Our approach tracked changes in RABV occurrence across space and time, identified risk corridors for potential incursions into Canada, and highlighted surveillance gaps, while evaluating the impacts of management actions. Using this approach, we are able to provide guidance for future RABV management