More Like this

1. Multiple infection of cells changes the dynamics of basic viral evolutionary processes

   https://doi.org/10.1002/evl3.95  

   Wodarz, Dominik ; Levy, David N. ; Komarova, Natalia L. ( February 2019 , Evolution Letters)

   The infection of cells by multiple copies of a given virus can impact viral evolution in a variety of ways, yet some of the most basic evolutionary dynamics remain underexplored. Using computational models, we investigate how infection multiplicity affects the fixation probability of mutants, the rate of mutant generation, and the timing of mutant invasion. An important insight from these models is that for neutral and disadvantageous phenotypes, rare mutants initially enjoy a fitness advantage in the presence of multiple infection of cells. This arises because multiple infection allows the rare mutant to enter more target cells and to spread faster, while it does not accelerate the spread of the resident wild-type virus. The rare mutant population can increase by entry into both uninfected and wild-type-infected cells, while the established wild-type population can initially only grow through entry into uninfected cells. Following this initial advantageous phase, the dynamics are governed by drift or negative selection, respectively, and a higher multiplicity reduces the chances that mutants fix in the population. Hence, while increased infection multiplicity promotes the presence of neutral and disadvantageous mutants in the short-term, it makes it less likely in the longer term. We show how these theoretical insights can be useful for the interpretation of experimental data on virus evolution at low and high multiplicities. The dynamics explored here provide a basis for the investigation of more complex viral evolutionary processes, including recombination, reassortment, as well as complementary/inhibitory interactions.

    

   more » « less
2. Spatial population genetics with fluid flow

   https://doi.org/10.1088/1361-6633/ac8231  

   Benzi, Roberto ; Nelson, David R ; Shankar, Suraj ; Toschi, Federico ; Zhu, Xiaojue ( August 2022 , Reports on Progress in Physics)

   The growth and evolution of microbial populations is often subjected to advection by fluid flows in spatially extended environments, with immediate consequences for questions of spatial population genetics in marine ecology, planktonic diversity and origin of life scenarios. Here, we review recent progress made in understanding this rich problem in the simplified setting of two competing genetic microbial strains subjected to fluid flows. As a pedagogical example we focus on antagonsim, i.e., two killer microorganism strains, each secreting toxins that impede the growth of their competitors (competitive exclusion), in the presence of stationary fluid flows. By solving two coupled reaction–diffusion equations that include advection by simple steady cellular flows composed of characteristic flow motifs in two dimensions (2D), we show how local flow shear and compressibility effects can interact with selective advantage to have a dramatic influence on genetic competition and fixation in spatially distributed populations. We analyze several 1D and 2D flow geometries including sources, sinks, vortices and saddles, and show how simple analytical models of the dynamics of the genetic interface can be used to shed light on the nucleation, coexistence and flow-driven instabilities of genetic drops. By exploiting an analogy with phase separation with nonconserved order parameters, we uncover how thesegeneticdrops harness fluid flows for novel evolutionary strategies, even in the presence of number fluctuations, as confirmed by agent-based simulations as well.

    

   more » « less
3. Breeding transients in capture–recapture modeling and their consequences for local population dynamics

   https://doi.org/10.1038/s41598-020-72778-x  

   Oro, Daniel ; Doak, Daniel F. ( December 2020 , Scientific Reports)

   null (Ed.)

   Abstract Standard procedures for capture–mark–recapture modelling (CMR) for the study of animal demography include running goodness-of-fit tests on a general starting model. A frequent reason for poor model fit is heterogeneity in local survival among individuals captured for the first time and those already captured or seen on previous occasions. This deviation is technically termed a transience effect. In specific cases, simple, uni-state CMR modeling showing transients may allow researchers to assess the role of these transients on population dynamics. Transient individuals nearly always have a lower local survival probability, which may appear for a number of reasons. In most cases, transients arise due to permanent dispersal, higher mortality, or a combination of both. In the case of higher mortality, transients may be symptomatic of a cost of first reproduction. A few studies working at large spatial scales actually show that transients more often correspond to survival costs of first reproduction rather than to permanent dispersal, bolstering the interpretation of transience as a measure of costs of reproduction, since initial detections are often associated with first breeding attempts. Regardless of their cause, the loss of transients from a local population should lower population growth rate. We review almost 1000 papers using CMR modeling and find that almost 40% of studies fitting the searching criteria (N = 115) detected transients. Nevertheless, few researchers have considered the ecological or evolutionary meaning of the transient phenomenon. Only three studies from the reviewed papers considered transients to be a cost of first reproduction. We also analyze a long-term individual monitoring dataset (1988–2012) on a long-lived bird to quantify transients, and we use a life table response experiment (LTRE) to measure the consequences of transients at a population level. As expected, population growth rate decreased when the environment became harsher while the proportion of transients increased. LTRE analysis showed that population growth can be substantially affected by changes in traits that are variable under environmental stochasticity and deterministic perturbations, such as recruitment, fecundity of experienced individuals, and transient probabilities. This occurred even though sensitivities and elasticities of these parameters were much lower than those for adult survival. The proportion of transients also increased with the strength of density-dependence. These results have implications for ecological and evolutionary studies and may stimulate other researchers to explore the ecological processes behind the occurrence of transients in capture–recapture studies. In population models, the inclusion of a specific state for transients may help to make more reliable predictions for endangered and harvested species. 

   more » « less
4. Spatial and ontogenetic variance in local densities modify selection on demographic traits

   https://doi.org/10.1111/1365-2435.14335  

   Mutz, Jessie ; Inouye, Brian D. ( April 2023 , Functional Ecology)

   Local density can affect individual performance by altering the strength of species interactions. Within many populations, local densities vary spatially (individuals are patchily distributed) or change across life stages, which should influence the selection and eco‐evolutionary feedback because local density variance affects mean fitness and is affected by traits of individuals. However, most studies on the evolutionary consequences of density‐dependent interactions focus on populations where local densities are relatively constant through time and space.

   We investigated the influence of spatial and ontogenetic variance in local densities within an insect population by comparing a model integrating both types of local density variance with models including only spatial variance, only ontogenetic variance, or no variance. We parameterized the models with experimental data, then used elasticity and invasion analyses to characterize selection on traits that affect either the local density an individual experiences (mean clutch size) or individuals' sensitivity to density (effect of larval crowding on pupal mass).

   Spatial and ontogenetic variance reduced population elasticity to effects of local density by 76% and 34% on average, respectively.

   Spatial variance modified selection and adaptive dynamics by altering the tradeoff between density‐dependent and density‐independent vital rates. In models including spatial variance, strategies that maximized density‐dependent survival were favoured over fecundity‐maximizing strategies even at low population density, counter to predictions of density‐dependent selection theory. Furthermore, only models that included spatial variance, thus linking the scales of oviposition and density‐dependent larval survival, had an evolutionarily stable clutch size.

   Ontogenetic variance weakened selection on mean clutch size and sensitivity to larval crowding by disrupting the relationship between trait values and performance during critical life stages.

   We demonstrate that local density variance can strongly modify selection at empirically observed interaction strengths and identify mechanisms for the effects of spatial and ontogenetic variance. Our findings reveal the potential for local density variance to mediate eco‐evolutionary feedback by shaping selection on demographically important traits.

   Read the freePlain Language Summaryfor this article on the Journal blog.

    

   more » « less
5. A hybrid stochastic-deterministic approach to explore multiple infection and evolution in HIV

   https://doi.org/10.1371/journal.pcbi.1009713  

   Kreger, Jesse ; Komarova, Natalia L. ; Wodarz, Dominik ( December 2021 , PLOS Computational Biology)

   Pascual, Mercedes (Ed.)

   To study viral evolutionary processes within patients, mathematical models have been instrumental. Yet, the need for stochastic simulations of minority mutant dynamics can pose computational challenges, especially in heterogeneous systems where very large and very small sub-populations coexist. Here, we describe a hybrid stochastic-deterministic algorithm to simulate mutant evolution in large viral populations, such as acute HIV-1 infection, and further include the multiple infection of cells. We demonstrate that the hybrid method can approximate the fully stochastic dynamics with sufficient accuracy at a fraction of the computational time, and quantify evolutionary end points that cannot be expressed by deterministic models, such as the mutant distribution or the probability of mutant existence at a given infected cell population size. We apply this method to study the role of multiple infection and intracellular interactions among different virus strains (such as complementation and interference) for mutant evolution. Multiple infection is predicted to increase the number of mutants at a given infected cell population size, due to a larger number of infection events. We further find that viral complementation can significantly enhance the spread of disadvantageous mutants, but only in select circumstances: it requires the occurrence of direct cell-to-cell transmission through virological synapses, as well as a substantial fitness disadvantage of the mutant, most likely corresponding to defective virus particles. This, however, likely has strong biological consequences because defective viruses can carry genetic diversity that can be incorporated into functional virus genomes via recombination. Through this mechanism, synaptic transmission in HIV might promote virus evolvability. 

   more » « less