A stochastic analysis of the interplay between antibiotic dose, mode of action, and bacterial competition in the evolution of antibiotic resistance.

The use of an antibiotic may lead to the emergence and spread of bacterial strains resistant to this antibiotic. Experimental and theoretical studies have investigated the drug dose that minimizes the risk of resistance evolution over the course of treatment of an individual, showing that the optimal dose will either be the highest or the lowest drug concentration possible to administer; however, no analytical results exist that help decide between these two extremes. To address this gap, we develop a stochastic mathematical model of bacterial dynamics under antibiotic treatment. We explore various scenarios of density regulation (bacterial density affects cell birth or death rates), and antibiotic modes of action (biostatic or biocidal). We derive analytical results for the survival probability of the resistant subpopulation until the end of treatment, the size of the resistant subpopulation at the end of treatment, the carriage time of the resistant subpopulation until it is replaced by a sensitive one after treatment, and we verify these results with stochastic simulations. We find that the scenario of density regulation and the drug mode of action are important determinants of the survival of a resistant subpopulation. Resistant cells survive best when bacterial competition reduces cell birth and under biocidal antibiotics. Compared to an analogous deterministic model, the population size reached by the resistant type is larger and carriage time is slightly reduced by stochastic loss of resistant cells. Moreover, we obtain an analytical prediction of the antibiotic concentration that maximizes the survival of resistant cells, which may help to decide which drug dosage (not) to administer. Our results are amenable to experimental tests and help link the within and between host scales in epidemiological models.

The impact of threshold decision mechanisms of collective behavior on disease spread.

Humans are a hyper-social species, which greatly impacts the spread of infectious diseases. How do social dynamics impact epidemiology and what are the implications for public health policy? Here, we develop a model of disease transmission that incorporates social dynamics and a behavior that reduces the spread of disease, a voluntary nonpharmaceutical intervention (NPI). We use a "tipping-point" dynamic, previously used in the sociological literature, where individuals adopt a behavior given a sufficient prevalence of the behavior in the population. The thresholds at which individuals adopt the NPI behavior are modulated by the perceived risk of infection, i.e., the disease prevalence and transmission rate, costs to adopt the NPI behavior, and the behavior of others. Social conformity creates a type of "stickiness" whereby individuals are resistant to changing their behavior due to the population's inertia. In this model, we observe a nonmonotonicity in the attack rate as a function of various biological and social parameters such as the transmission rate, efficacy of the NPI, costs of the NPI, weight of social consequences of shirking the social norm, and the degree of heterogeneity in the population. We also observe that the attack rate can be highly sensitive to these parameters due to abrupt shifts in the collective behavior of the population. These results highlight the complex interplay between the dynamics of epidemics and norm-driven collective behaviors.

Life history optimisation drives latitudinal gradients and responses to global change in marine fishes.

Within many species, and particularly fish, fecundity does not scale with mass linearly; instead, it scales disproportionately. Disproportionate intraspecific size-reproduction relationships contradict most theories of biological growth and present challenges for the management of biological systems. Yet the drivers of reproductive scaling remain obscure and systematic predictors of how and why reproduction scaling varies are lacking. Here, we parameterise life history optimisation model to predict global patterns in the life histories of marine fishes. Our model predict latitudinal trends in life histories: Polar fish should reproduce at a later age and show steeper reproductive scaling than tropical fish. We tested and confirmed these predictions using a new, global dataset of marine fish life histories, demonstrating that the risks of mortality shape maturation and reproductive scaling. Our model also predicts that global warming will profoundly reshape fish life histories, favouring earlier reproduction, smaller body sizes, and lower mass-specific reproductive outputs, with worrying consequences for population persistence.

A null model for the distribution of fitness effects of mutations.

The distribution of fitness effects (DFE) of new mutations is key to our understanding of many evolutionary processes. Theoreticians have developed several models to help understand the patterns seen in empirical DFEs. Many such models reproduce the broad patterns seen in empirical DFEs but these models often rely on structural assumptions that cannot be tested empirically. Here, we investigate how much of the underlying "microscopic" biological processes involved in the mapping of new mutations to fitness can be inferred from "macroscopic" observations of the DFE. We develop a null model by generating random genotype-to-fitness maps and show that the null DFE is that with the largest possible information entropy. We further show that, subject to one simple constraint, this null DFE is a Gompertz distribution. Finally, we illustrate how the predictions of this null DFE match empirically measured DFEs from several datasets, as well as DFEs simulated from Fisher's geometric model. This suggests that a match between models and empirical data is often not a very strong indication of the mechanisms underlying the mapping of mutation to fitness.

No life-history cost of tebufenozide resistance in the smaller tea tortrix moth.

BACKGROUND: Tebufenozide is widely used to control populations of the smaller tea tortrix, Adoxophyes honmai. However, A. honmai has evolved resistance such that straightforward pesticide application is an untenable long-term approach for population control. Evaluating the fitness cost of resistance is key to devising a management strategy that slows the evolution of resistance. RESULTS: We used three approaches to assess the life-history cost of tebufenozide resistance with two strains of A. honmai: a tebufenozide-resistant strain recently collected from the field in Japan and a susceptible strain that has been maintained in the laboratory for decades. First, we found that the resistant strain with standing genetic variation did not decline in resistance in the absence of insecticide over four generations. Second, we found that genetic lines that spanned a range of resistance profiles did not show a negative correlation between their LD50 , the dosage at which 50 % of individuals died, and life-history traits that are correlates of fitness. Third, we found that the resistant strain did not manifest life-history costs under food limitation. Our crossing experiments indicate that the allele at an ecdysone receptor locus known to confer resistance explained much of the variance in resistance profiles across genetic lines. CONCLUSION: Our results indicate that the point mutation in the ecdysone receptor, which is widespread in tea plantations in Japan, does not carry a fitness cost in the tested laboratory conditions. The absence of a cost of resistance and the mode of inheritance have implications for which strategies may be effective in future resistance management efforts. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Pathogen evolution during vaccination campaigns.

Following the initiation of the unprecedented global vaccination campaign against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), attention has now turned to the potential impact of this large-scale intervention on the evolution of the virus. In this Essay, we summarize what is currently known about pathogen evolution in the context of immune priming (including vaccination) from research on other pathogen species, with an eye towards the future evolution of SARS-CoV-2.

The evolution of age-specific choosiness and reproductive isolation in a model with overlapping generations.

The strength of mate choice (choosiness) often varies with age, but theory to understand this variation is scarce. Additionally, theory has investigated the evolution of choosiness in speciation scenarios but has ignored that most organisms have overlapping generations. We investigate whether speciation can result in variation of choosiness with age, and whether such variation can in turn affect speciation. We develop a population-genetic model of the evolution of choosiness in organisms with overlapping generations in the context of secondary contact between two divergent populations. We assume that females choose males that match their phenotype, such that choosiness evolves by sexual selection. We demonstrate that speciation can result in the evolution of age-specific choosiness when the mating trait is under divergent ecological selection and age is not used as a mating cue. The cause of this result is that allele frequencies differ between choosy females and males. However, we find that the evolution of age-specific choosiness does not affect the overall level of reproductive isolation compared to a case without age-structure, supporting previous speciation theory. Overall, our results connect life history and speciation theory, and the mechanisms that we highlight have implications for the understanding of the role of sex-specific selection in the evolution of choosiness.

The economics of managing evolution.

Humans are altering biological systems at unprecedented rates, and these alterations often have longer-term evolutionary impacts. Most obvious is the spread of resistance to pesticides and antibiotics. There are a wide variety of management strategies available to slow this evolution, and there are many reasons for using them. In this paper, we focus on the economic aspects of evolution management and ask: When is it economically beneficial for an individual decision-maker to invest in evolution management? We derive a simple dimensionless inequality showing that it is cost-effective to manage evolution when the percentage increase in the effective life span of the biological resource that management generates is larger than the percentage increase in annual profit that could be obtained by not managing evolution. We show how this inequality can be used to determine optimal investment choices for single decision-makers, to determine Nash equilibrium investment choices for multiple interacting decision-makers, and to examine how these equilibrium choices respond to regulatory interventions aimed at stimulating investment in evolution management. Our results are illustrated with examples involving Bacillus thuringiensis (Bt) crops and antibiotic use in fish farming.

The origins and potential future of SARS-CoV-2 variants of concern in the evolving COVID-19 pandemic.

One year into the global COVID-19 pandemic, the focus of attention has shifted to the emergence and spread of SARS-CoV-2 variants of concern (VOCs). After nearly a year of the pandemic with little evolutionary change affecting human health, several variants have now been shown to have substantial detrimental effects on transmission and severity of the virus. Public health officials, medical practitioners, scientists, and the broader community have since been scrambling to understand what these variants mean for diagnosis, treatment, and the control of the pandemic through nonpharmaceutical interventions and vaccines. Here we explore the evolutionary processes that are involved in the emergence of new variants, what we can expect in terms of the future emergence of VOCs, and what we can do to minimise their impact.

Demystifying individual heterogeneity.

Among-individual variation in vital rates, such as mortality and birth rates, exists in nearly all populations. Recent studies suggest that this individual heterogeneity produces substantial life-history and fitness differences among individuals, which in turn scale up to influence population dynamics. However, our ability to understand the consequences of individual heterogeneity is limited by inconsistencies across conceptual frameworks in the field. Studies of individual heterogeneity remain filled with contradicting and ambiguous terminology that introduces risks of misunderstandings, conflicting models and unreliable conclusions. Here, we synthesise the existing literature into a single and comparatively straightforward framework with explicit terminology and definitions. This work introduces a distinction between potential vital rates and realised vital rates to develop a coherent framework that maps directly onto mathematical models of individual heterogeneity. We suggest the terms "fixed condition" and "dynamic condition" be used to distinguish potential vital rates that are permanent from those that can change throughout an individual's life. To illustrate, we connect the framework to quantitative genetics models and to common classes of statistical models used to infer individual heterogeneity. We also develop a population projection matrix model that provides an example of how our definitions are translated into precise quantitative terms.

The evolution of age-specific choosiness when mating.

Mate choice is a crucial element of many processes in evolutionary biology. Empirical research has shown that mating preference and choosiness often change with age. Understanding the evolutionary causes of patterns of age-specific choosiness is challenging because different mechanisms can give rise to the same pattern. Instead of focusing on the optimal age-specific choosiness strategy given fitness trade-offs, we approach this question from a more general standpoint and ask how the strength of selection on choosiness changes with the age at which it is expressed. We show that the strength of selection on a modifier of choosiness at a given age depends on the relative contribution of this age class to the pool of offspring but does not depend directly on the strength of selection on fitness components at the age affected by the modifier. We illustrate our results by contrasting two life histories from the literature. We further show how mutation-selection balance at the choosiness locus can shape age-specific choosiness. Our results provide new insights for understanding the evolution of choosiness throughout life, with implications for understanding the evolution of mate choice and reproductive isolation.

Poisson integral type quarantine in a stochastic SIR system.

We propose a SIR system that includes a Poisson measure term to model the quarantine of infected individuals. An inequality concerning the term representing the transmission rate is given to establish the stochastic stability of the disease free equilibrium. It is further shown that if R0 > 1 then the long-run behavior the system will reside within a neighborhood of the equilibrium in the underlying deterministic version of this system.

Nongenetic inheritance and multigenerational plasticity in the nematode C. elegans.

A rapidly growing body of literature in several organisms suggests that environmentally-induced adaptive changes in phenotype can be transmitted across multiple generations. Although within-generation plasticity has been well documented, multigenerational plasticity represents a significant departure from conventional evolutionary thought. Studies of C. elegans have been particularly influential because this species exhibits extensive phenotypic plasticity, it is often essentially isogenic, and it has well-documented molecular and cellular mechanisms through which nongenetic inheritance occurs. However, while experimentalists are eager to claim that nongenetic modes of inheritance characterized in this and other model systems enhance fitness, many biologists remain skeptical given the extraordinary nature of this claim. We establish three criteria to evaluate how compelling the evidence for adaptive multigenerational plasticity is, and we use these criteria to critically examine putative cases of it in C. elegans. We conclude by suggesting potentially fruitful avenues for future research.

On the evolutionary epidemiology of SARS-CoV-2.

There is no doubt that the novel coronavirus SARS-CoV-2 that causes COVID-19 is mutating and thus has the potential to adapt during the current pandemic. Whether this evolution will lead to changes in the transmission, the duration, or the severity of the disease is not clear. This has led to considerable scientific and media debate, from raising alarms about evolutionary change to dismissing it. Here we review what little is currently known about the evolution of SARS-CoV-2 and extend existing evolutionary theory to consider how selection might be acting upon the virus during the COVID-19 pandemic. Although there is currently no definitive evidence that SARS-CoV-2 is undergoing further adaptation, continued evidence-based analysis of evolutionary change is important so that public health measures can be adjusted in response to substantive changes in the infectivity or severity of COVID-19.

The Price equation and evolutionary epidemiology.

The Price equation has found widespread application in many areas of evolutionary biology, including the evolutionary epidemiology of infectious diseases. In this paper, we illustrate the utility of this approach to modelling disease evolution by first deriving a version of Price's equation that can be applied in continuous time and to populations with overlapping generations. We then show how this version of Price's equation provides an alternative perspective on pathogen evolution by considering the epidemiological meaning of each of its terms. Finally, we extend these results to the case where population size is small and generates demographic stochasticity. We show that the particular partitioning of evolutionary change given by Price's equation is also a natural way to partition the evolutionary consequences of demographic stochasticity, and demonstrate how such stochasticity tends to weaken selection on birth rate (e.g. the transmission rate of an infectious disease) and enhance selection on mortality rate (e.g. factors, like virulence, that cause the end of an infection). In the long term, if there is a trade-off between virulence and transmission across parasite strains, the weaker selection on transmission and stronger selection on virulence that arises from demographic stochasticity will tend to drive the evolution of lower levels of virulence. This article is part of the theme issue 'Fifty years of the Price equation'.

Evolutionary consequences of feedbacks between within-host competition and disease control.

Lay Summary: Competition often occurs among diverse parasites within a single host, but control efforts could change its strength. We examined how the interplay between competition and control could shape the evolution of parasite traits like drug resistance and disease severity.

Fighting the Public Health Burden of AIDS With the Human Pegivirus.

Highly active antiretroviral therapy has revolutionized the battle against human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS). From its current global rollout, HIV/AIDS morbidity and mortality has been greatly reduced, yet there exists substantial interest in the development of new therapies to further mitigate the HIV/AIDS health burden and to inhibit any fallout from the development of antiretroviral drug resistance. One potential intervention is the human pegivirus (HPgV). HPgV is not known to cause disease, and most remarkably it is shown to delay the progression of HIV to AIDS. However, the health benefit of increasing HPgV prevalence in the community of HIV-infected men remains unknown at the public health level. We evaluated the utility of HPgV biovaccination for mitigating the HIV/AIDS health burden using mathematical models. Importantly, our work considers the potential concern that HPgV will, itself, evolve to become disease-causing by permitting mutant disease-causing HPgV strains to potentially arise during treatment. Our findings show that HPgV biovaccination rates of 12.5%-50% annually could prevent 4.2-23.6 AIDS incidences and 3.3-18.8 AIDS deaths, and could save 2.9-18.6 disability-adjusted life years per 1,000 people. Together, these findings indicate that HPgV biovaccination could be an effective therapy for reducing HIV/AIDS morbidity and mortality, and thus warrants further exploration.