Impact of Fluoxetine on Herbivorous Zooplankton and Planktivorous Fish.

The contamination of freshwater environments by pharmaceuticals is a growing problem. Modern healthcare uses nearly 3000 substances, many of which are designed to work at low dosages and act on physiological systems that have been evolutionarily conserved across taxa. Because drugs affect the organisms from different trophic levels, pharmaceutical pollution is likely to disturb species interactions. However, such effects are still only poorly understood. We investigated the impacts of environmentally relevant concentrations of the common drug fluoxetine (Prozac), an increasingly common contaminant of European waters, on predation behavior of crucian carp (Carassius carassius), a common planktivorous European fish, and the somatic growth of its prey, the water flea (Daphnia magna), a widespread planktonic crustacean. We exposed these two organisms to environmentally relevant levels of fluoxetine (360 ng L-1 ): the fish for 4 weeks and the water fleas for two generations. We tested the growth of the daphnids and the hunting behavior (reaction distance at which fish attacked Daphnia and feeding rate) of the fish under drug contamination. We found that Daphnia exposed to fluoxetine grew larger than a nonexposed cohort. The hunting behavior of C. carassius was altered when they were exposed to the drug; the reaction distance was shorter, and the feeding rate was slower. These effects occurred regardless of Daphnia size and the treatment regime they were subjected to. Our results suggest that contamination of freshwater environments with fluoxetine can disrupt the top-down ecological control of herbivores by reducing the hunting efficiency of fish and, as a consequence, may lead to increases in cladoceran population numbers. Environ Toxicol Chem 2023;42:385-392. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection.

The efficacy of digital contact tracing against coronavirus disease 2019 (COVID-19) epidemic is debated: Smartphone penetration is limited in many countries, with low coverage among the elderly, the most vulnerable to COVID-19. We developed an agent-based model to precise the impact of digital contact tracing and household isolation on COVID-19 transmission. The model, calibrated on French population, integrates demographic, contact and epidemiological information to describe exposure and transmission of COVID-19. We explored realistic levels of case detection, app adoption, population immunity, and transmissibility. Assuming a reproductive ratio R = 2.6 and 50% detection of clinical cases, a ~20% app adoption reduces peak incidence by ~35%. With R = 1.7, >30% app adoption lowers the epidemic to manageable levels. Higher coverage among adults, playing a central role in COVID-19 transmission, yields an indirect benefit for the elderly. These results may inform the inclusion of digital contact tracing within a COVID-19 response plan.

Mating preferences can drive expansion or contraction of major histocompatibility complex gene family.

Major histocompatibility complex (MHC)-based mating rules can evolve as a way to avoid inbreeding or to increase offspring immune competence. While the role of mating preference in shaping the MHC diversity in vertebrates has been acknowledged, its impact on individual MHC diversity has not been considered. Here, we use computer simulations to investigate how simple mating rules favouring MHC-dissimilar partners affect the evolution of the number of MHC variants in individual genomes, accompanying selection for resistance to parasites. We showed that the effect of such preferences could sometimes be dramatic. If preferences are aimed at avoiding identical alleles, the equilibrium number of MHC alleles is much smaller than under random mating. However, if the mating rule minimizes the ratio of shared to different alleles in partners, MHC number is higher than under random mating. Additionally, our simulations revealed that a negative correlation between the numbers of MHC variants in mated individuals can arise from simple rules of MHC-disassortative mating. Our results reveal unexpected potential of MHC-based mating preferences to drive MHC gene family expansions or contractions and highlight the need to study the mechanistic basis of such preferences, which is currently poorly understood.

Evolution of major histocompatibility complex gene copy number.

MHC genes, which code for proteins responsible for presenting pathogen-derived antigens to the host immune system, show remarkable copy-number variation both between and within species. However, the evolutionary forces driving this variation are poorly understood. Here, we use computer simulations to investigate whether evolution of the number of MHC variants in the genome can be shaped by the number of pathogen species the host population encounters (pathogen richness). Our model assumed that while increasing a range of pathogens recognised, expressing additional MHC variants also incurs costs such as an increased risk of autoimmunity. We found that pathogen richness selected for high MHC copy number only when the costs were low. Furthermore, the shape of the association was modified by the rate of pathogen evolution, with faster pathogen mutation rates selecting for increased host MHC copy number, but only when pathogen richness was low to moderate. Thus, taking into account factors other than pathogen richness may help explain wide variation between vertebrate species in the number of MHC genes. Within population, variation in the number of unique MHC variants carried by individuals (INV) was observed under most parameter combinations, except at low pathogen richness. This variance gave rise to positive correlations between INV and host immunocompetence (proportion of pathogens recognised). However, within-population variation in host immunocompetence declined with pathogen richness. Thus, counterintuitively, pathogens can contribute more to genetic variance for host fitness in species exposed to fewer pathogen species, with consequences to predictions from "Hamilton-Zuk" theory of sexual selection.

The effect of extrinsic mortality on genome size evolution in prokaryotes.

Mortality has a significant role in prokaryotic ecology and evolution, yet the impact of variations in extrinsic mortality on prokaryotic genome evolution has received little attention. We used both mathematical and agent-based models to reveal how variations in extrinsic mortality affect prokaryotic genome evolution. Our results suggest that the genome size of bacteria increases with increased mortality. A high extrinsic mortality increases the pool of free resources and shortens life expectancy, which selects for faster reproduction, a phenotype we called 'scramblers'. This phenotype is realised by the expansion of gene families involved in nutrient acquisition and metabolism. In contrast, a low mortality rate increases an individual's life expectancy, which results in natural selection favouring tolerance to starvation when conditions are unfavourable. This leads to the evolution of small, streamlined genomes ('stayers'). Our models predict that large genomes, gene family expansion and horizontal gene transfer should be observed in prokaryotes occupying ecosystems exposed to high abiotic stress, as well as those under strong predator- and/or pathogen-mediated selection. A comparison of genome size of cyanobacteria in relatively stable marine versus more turbulent freshwater environments corroborates our predictions, although other factors between these environments could also be responsible.

A Model of Genome Size Evolution for Prokaryotes in Stable and Fluctuating Environments.

Temporal variability in ecosystems significantly impacts species diversity and ecosystem productivity and therefore the evolution of organisms. Different levels of environmental perturbations such as seasonal fluctuations, natural disasters, and global change have different impacts on organisms and therefore their ability to acclimatize and adapt. Thus, to understand how organisms evolve under different perturbations is a key for predicting how environmental change will impact species diversity and ecosystem productivity. Here, we developed a computer simulation utilizing the individual-based model approach to investigate genome size evolution of a haploid, clonal and free-living prokaryotic population across different levels of environmental perturbations. Our results show that a greater variability of the environment resulted in genomes with a larger number of genes. Environmental perturbations were more effectively buffered by populations of individuals with relatively large genomes. Unpredictable changes of the environment led to a series of population bottlenecks followed by adaptive radiations. Our model shows that the evolution of genome size is indirectly driven by the temporal variability of the environment. This complements the effects of natural selection directly acting on genome optimization. Furthermore, species that have evolved in relatively stable environments may face the greatest risk of extinction under global change as genome streamlining genetically constrains their ability to acclimatize to the new environmental conditions, unless mechanisms of genetic diversification such as horizontal gene transfer will enrich their gene pool and therefore their potential to adapt.