The effects of weather and mobility on respiratory viruses dynamics before and during the COVID-19 pandemic in the USA and Canada.

The flu season is caused by a combination of different pathogens, including influenza viruses (IVS), that cause the flu, and non-influenza respiratory viruses (NIRVs), that cause common colds or influenza-like illness. These viruses exhibit similar dynamics and meteorological conditions have historically been regarded as a principal modulator of their epidemiology, with outbreaks in the winter and almost no circulation during the summer, in temperate regions. However, after the emergence of SARS-CoV2, in late 2019, the dynamics of these respiratory viruses were strongly perturbed worldwide: some infections displayed near-eradication, while others experienced temporal shifts or occurred "off-season". This disruption raised questions regarding the dominant role of weather while also providing an unique opportunity to investigate the roles of different determinants on the epidemiological dynamics of IVs and NIRVs. Here, we employ statistical analysis and modelling to test the effects of weather and mobility in viral dynamics, before and during the COVID-19 pandemic. Leveraging epidemiological surveillance data on several respiratory viruses, from Canada and the USA, from 2016 to 2023, we found that whereas in the pre-COVID-19 pandemic period, weather had a strong effect, in the pandemic period the effect of weather was strongly reduced and mobility played a more relevant role. These results, together with previous studies, indicate that behavioral changes resulting from the non-pharmacological interventions implemented to control SARS-CoV2, interfered with the dynamics of other respiratory viruses, and that the past dynamical equilibrium was disturbed, and perhaps permanently altered, by the COVID-19 pandemic.

Competition dynamics in long-term propagations of Schizosaccharomyces pombe strain communities.

Experimental evolution studies with microorganisms such as bacteria and yeast have been an increasingly important and powerful tool to draw long-term inferences of how microbes interact. However, while several strains of the same species often exist in natural environments, many ecology and evolution studies in microbes are typically performed with isogenic populations of bacteria or yeast. In the present study, we firstly perform a genotypic and phenotypic characterization of two laboratory and eight natural strains of the yeast Schizosaccharomyces pombe. We then propagated, in a rich resource environment, yeast communities of 2, 3, 4, and 5 strains for hundreds of generations and asked which fitness-related phenotypes-maximum growth rate or relative competitive fitness-would better predict the outcome of a focal strain during the propagations. While the strain's growth rates would wrongly predict long-term coexistence, pairwise competitive fitness with a focal strain qualitatively predicted the success or extinction of the focal strain by a simple multigenotype population genetics model, given the initial community composition. Interestingly, we have also measured the competitive fitness of the ancestral and evolved communities by the end of the experiment (≈370 generations) and observed frequent maladaptation to the abiotic environment in communities with more than three members. Overall, our results aid establishing pairwise competitive fitness as good qualitative measurement of long-term community composition but also reveal a complex adaptive scenario when trying to predict the evolutionary outcome of those communities.

Epigenetic gene silencing alters the mechanisms and rate of evolutionary adaptation.

Epigenetic, non-DNA sequence-based inheritance can potentially contribute to adaptation but, due to its transient nature and the difficulty involved in uncoupling it from genetic variation, it is unclear whether it has any effect on long-term evolution. However, short-term epigenetic inheritance may interact with genetic change by modifying the rate and type of adaptive mutations. Here, we test this notion in an experimental evolution set-up in yeast. We tune low, intermediate and high levels of heritable silencing of a URA3 reporter under selection by insertion at different positions within silent subtelomeric chromatin in otherwise isogenic Saccharomyces cerevisiae. Heritable silencing does not impact mutation rate but drives population size expansion and rapid epigenetic adaptation. This eventually leads to genetic assimilation of the silent phenotype by mutations that reduce or abolish URA3 expression. Moreover, at intermediate or low levels of heritable silencing we find that populations evolve more rapidly by accumulation of adaptive mutations, in part through acquisition of novel alleles that enhance gene silencing, aiding accelerated adaptation. We provide an experimental proof of concept that defines the impact and mechanisms of how short-term epigenetic inheritance can shape adaptive evolution.

Power law fitness landscapes and their ability to predict fitness.

Whether or not evolution by natural selection is predictable depends on the existence of general patterns shaping the way mutations interact with the genetic background. This interaction, also known as epistasis, has been observed during adaptation (macroscopic epistasis) and in individual mutations (microscopic epistasis). Interestingly, a consistent negative correlation between the fitness effect of beneficial mutations and background fitness (known as diminishing returns epistasis) has been observed across different species and conditions. We tested whether the adaptation pattern of an additional species, Schizosaccharomyces pombe, followed the same trend. We used strains that differed by the presence of large karyotype differences and observed the same pattern of fitness convergence. Using these data along with published datasets, we measured the ability of different models to describe adaptation rates. We found that a phenotype-fitness landscape shaped like a power law is able to correctly predict adaptation dynamics in a variety of species and conditions. Furthermore we show that this model can provide a link between the observed macroscopic and microscopic epistasis. It may be very useful in the development of algorithms able to predict the adaptation of microorganisms from measures of the current phenotypes. Overall, our results suggest that even though adaptation quickly slows down, populations adapting to lab conditions may be quite far from a fitness peak.

Genome architecture is a selectable trait that can be maintained by antagonistic pleiotropy.

Chromosomal rearrangements are mutations contributing to both within and between species variation; however their contribution to fitness is yet to be measured. Here we show that chromosomal rearrangements are pervasive in natural isolates of Schizosaccharomyces pombe and contribute to reproductive isolation. To determine the fitness effects of chromosome structure, we constructed two inversions and eight translocations without changing the coding sequence. We show that chromosomal rearrangements contribute to both reproductive success in meiosis and growth rate in mitosis with a strong genotype by environment interaction. These changes are accompanied by alterations in gene expression. Strikingly, we find several examples leading to antagonistic pleiotropy. Even though chromosomal rearrangements may have a deleterious effect during sexual reproduction, some compensate with a strong growth advantage in mitosis. Our results constitute the first quantification of fitness effects caused by de novo mutations that result in chromosomal rearrangement variation and suggest a mechanism for their maintenance in natural populations.

Nonlinear fitness landscape of a molecular pathway.

Genes are regulated because their expression involves a fitness cost to the organism. The production of proteins by transcription and translation is a well-known cost factor, but the enzymatic activity of the proteins produced can also reduce fitness, depending on the internal state and the environment of the cell. Here, we map the fitness costs of a key metabolic network, the lactose utilization pathway in Escherichia coli. We measure the growth of several regulatory lac operon mutants in different environments inducing expression of the lac genes. We find a strikingly nonlinear fitness landscape, which depends on the production rate and on the activity rate of the lac proteins. A simple fitness model of the lac pathway, based on elementary biophysical processes, predicts the growth rate of all observed strains. The nonlinearity of fitness is explained by a feedback loop: production and activity of the lac proteins reduce growth, but growth also affects the density of these molecules. This nonlinearity has important consequences for molecular function and evolution. It generates a cliff in the fitness landscape, beyond which populations cannot maintain growth. In viable populations, there is an expression barrier of the lac genes, which cannot be exceeded in any stationary growth process. Furthermore, the nonlinearity determines how the fitness of operon mutants depends on the inducer environment. We argue that fitness nonlinearities, expression barriers, and gene-environment interactions are generic features of fitness landscapes for metabolic pathways, and we discuss their implications for the evolution of regulation.

Fitness effects of mutations in bacteria.

Mutation is the primary source of variation in any organism. Without it, natural selection cannot operate and organisms cannot adapt to novel environments. Mutation is also generally a source of defect: many mutations are not neutral but cause fitness decreases in the organisms where they arise. In bacteria, another important source of variation is horizontal gene transfer. This source of variation can also cause beneficial or deleterious effects. Determining the distribution of fitness effects of mutations in different environments and genetic backgrounds is an active research field. In bacteria, knowledge of these distributions is key for understanding important traits. For example, for determining the dynamics of microorganisms with a high genomic mutation rate (mutators), and for understanding the evolution of antibiotic resistance, and the emergence of pathogenic traits. All of these characteristics are extremely relevant for human health both at the individual and population levels. Experimental evolution has been a valuable tool to address these questions. Here, we review some of the important findings of mutation effects in bacteria revealed through laboratory experiments.

Rate and effects of spontaneous mutations that affect fitness in mutator Escherichia coli.

Knowledge of the mutational parameters that affect the evolution of organisms is of key importance in understanding the evolution of several characteristics of many natural populations, including recombination and mutation rates. In this study, we estimated the rate and mean effect of spontaneous mutations that affect fitness in a mutator strain of Escherichia coli and review some of the estimation methods associated with mutation accumulation (MA) experiments. We performed an MA experiment where we followed the evolution of 50 independent mutator lines that were subjected to repeated bottlenecks of a single individual for approximately 1150 generations. From the decline in mean fitness and the increase in variance between lines, we estimated a minimum mutation rate to deleterious mutations of 0.005 (+/-0.001 with 95% confidence) and a maximum mean fitness effect per deleterious mutation of 0.03 (+/-0.01 with 95% confidence). We also show that any beneficial mutations that occur during the MA experiment have a small effect on the estimate of the rate and effect of deleterious mutations, unless their rate is extremely large. Extrapolating our results to the wild-type mutation rate, we find that our estimate of the mutational effects is slightly larger and the inferred deleterious mutation rate slightly lower than previous estimates obtained for non-mutator E. coli.

The effect of spatial structure on adaptation in Escherichia coli.

Populations of organisms are generally organized in a given spatial structure. However, the vast majority of population genetic studies are based on populations in which every individual competes globally. Here we use experimental evolution in Escherichia coli to directly test a recently made prediction that spatial structure slows down adaptation and that this cost increases with the mutation rate. This was studied by comparing populations of different mutation rates adapting to a liquid (unstructured) medium with populations that evolved in a Petri dish on solid (structured) medium. We find that mutators adapt faster to both environments and that adaptation is slower if there is spatial structure. We observed no significant difference in the cost of structure between mutator and wild-type populations, which suggests that clonal interference is intense in both genetic backgrounds.

Adaptive mutations in bacteria: high rate and small effects.

Evolution by natural selection is driven by the continuous generation of adaptive mutations. We measured the genomic mutation rate that generates beneficial mutations and their effects on fitness in Escherichia coli under conditions in which the effect of competition between lineages carrying different beneficial mutations is minimized. We found a rate on the order of 10(-5) per genome per generation, which is 1000 times as high as previous estimates, and a mean selective advantage of 1%. Such a high rate of adaptive evolution has implications for the evolution of antibiotic resistance and pathogenicity.