Stochastic offspring distributions amplify selection bias in mutation accumulation experiments.

Mutation accumulation (MA) experiments play an important role in understanding evolution. For microbial populations, such experiments often involve periods of population growth, such that a single individual can make a visible colony, followed by severe bottlenecks. Previous work has quantified the effect of positive and negative selection on MA experiments, demonstrating for example that with 20 generations of growth between bottlenecks, big-benefit mutations can be over-represented by a factor of five or more (Wahl and Agashe, 2022).

Non-hypermutator cancers access driver mutations through reversals in germline mutational bias.

Cancer is an evolutionary disease driven by mutations in asexually-reproducing somatic cells. In asexual microbes, bias reversals in the mutation spectrum can speed adaptation by increasing access to previously undersampled beneficial mutations. By analyzing tumors from 20 tissues, along with normal tissue and the germline, we demonstrate this effect in cancer.

Within-host evolution of SARS-CoV-2: how often are mutations transmitted from symptomatic infections?

Despite a relatively low mutation rate, the large number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has allowed for substantial genetic change, leading to a multitude of emerging variants. Using a recently determined mutation rate (per site replication), as well as within-host parameter estimates for symptomatic SARS-CoV-2 infection, we apply a stochastic transmission-bottleneck model to describe the survival probability of SARS-CoV-2 mutations as a function of bottleneck size and selection coefficient. For narrow bottlenecks, we find that mutations affecting per-target-cell attachment rate (with phenotypes associated with fusogenicity and ACE2 binding) have similar transmission probabilities to mutations affecting viral load clearance (with phenotypes associated with humoral evasion).

Shifts in Mutation Bias Promote Mutators by Altering the Distribution of Fitness Effects.

AbstractRecent experimental evidence demonstrates that shifts in mutational biases-for example, increases in transversion frequency-can change the distribution of fitness effects of mutations (DFE). In particular, reducing or reversing a prevailing bias can increase the probability that a de novo mutation is beneficial. It has also been shown that mutator bacteria are more likely to emerge if the beneficial mutations they generate have a larger effect size than observed in the wild type.

Shifts in mutation spectra enhance access to beneficial mutations.

Biased mutation spectra are pervasive, with wide variation in the magnitude of mutational biases that influence genome evolution and adaptation. How do such diverse biases evolve? Our experiments show that changing the mutation spectrum allows populations to sample previously undersampled mutational space, including beneficial mutations. The resulting shift in the distribution of fitness effects is advantageous: Beneficial mutation supply and beneficial pleiotropy both increase, while deleterious load reduces.

Multiple cohort study of hospitalized SARS-CoV-2 in-host infection dynamics: Parameter estimates, identifiability, sensitivity and the eclipse phase profile.

Within-host SARS-CoV-2 modelling studies have been published throughout the COVID-19 pandemic. These studies contain highly variable numbers of individuals and capture varying timescales of pathogen dynamics; some studies capture the time of disease onset, the peak viral load and subsequent heterogeneity in clearance dynamics across individuals, while others capture late-time post-peak dynamics. In this study, we curate multiple previously published SARS-CoV-2 viral load data sets, fit these data with a consistent modelling approach, and estimate the variability of in-host parameters including the basic reproduction number, R, as well as the best-fit eclipse phase profile.

Surviving environmental change: when increasing population size can increase extinction risk.

Populations threatened by an abrupt environmental change-due to rapid climate change, pathogens or invasive competitors-may survive if they possess or generate genetic combinations adapted to the novel, challenging condition. If these genotypes are initially rare or non-existent, the emergence of lineages that allow a declining population to survive is known as 'evolutionary rescue'. By contrast, the genotypes required for survival could, by chance, be common before the environmental change.

Hazardous Loss of Genetic Diversity through Selective Sweeps in Asexual Populations.

AbstractWith the twofold cost of sex, derived asexual organisms have an immediate reproductive advantage over their sexual sisters. Yet the "twiggy" phylogenetic distribution of asexual lineages implies that they become extinct relatively quickly over evolutionary time. Meanwhile, bacteria and archaea have persisted for billions of years without requiring sexual reproduction.

Selection bias in mutation accumulation.

Mutation accumulation (MA) experiments, in which de novo mutations are sampled and subsequently characterized, are an essential tool in understanding the processes underlying evolution. In microbial populations, MA protocols typically involve a period of population growth between severe bottlenecks, such that a single individual can form a visible colony. While it has long been appreciated that the action of positive selection during this growth phase cannot be eliminated, it is typically assumed to be negligible.

Host life-history traits influence the distribution of prophages and the genes they carry.

Bacterial strains with a short minimal doubling time-'fast-growing' hosts-are more likely to contain prophages than their slow-growing counterparts. Pathogenic bacterial species are likewise more likely to carry prophages. We develop a bioinformatics pipeline to examine the distribution of prophages in fast- and slow-growing lysogens, and pathogenic and non-pathogenic lysogens, analysing both prophage length and gene content for each class.

Mosaic vaccination: How distributing different vaccines across a population could improve epidemic control.

Although vaccination has been remarkably effective against some pathogens, for others, rapid antigenic evolution results in vaccination conferring only weak and/or short-lived protection. Consequently, considerable effort has been invested in developing more evolutionarily robust vaccines, either by targeting highly conserved components of the pathogen (universal vaccines) or by including multiple immunological targets within a single vaccine (multi-epitope vaccines). An unexplored third possibility is to vaccinate individuals with one of a number of qualitatively different vaccines, creating a "mosaic" of individual immunity in the population.

Estimating the risk of pandemic avian influenza.

Outbreaks of highly pathogenic strains of avian influenza (HPAI) cause high mortality in avian populations worldwide. When spread from avian reservoirs to humans, HPAI infections cause mortality in about 50% of human infections. Cases of human-to-human transmission of HPAI are relatively rare, and have, to date, only been reported in situations of close contact.

Robustness and predictability of evolution in bottlenecked populations.

Deterministic and stochastic evolutionary processes drive adaptation in natural populations. The strength of each component process is determined by the population size: deterministic components prevail in very large populations, while stochastic components are the driving mechanisms in small ones. Many natural populations, however, experience intermittent periods of growth, moving through states in which either stochastic or deterministic processes prevail.

Evolution along the parasitism-mutualism continuum determines the genetic repertoire of prophages.

Integrated into their bacterial hosts' genomes, prophage sequences exhibit a wide diversity of length and gene content, from highly degraded cryptic sequences to intact, functional prophages that retain a full complement of lytic-function genes. We apply three approaches-bioinformatics, analytical modelling and computational simulation-to understand the diverse gene content of prophages. In the bioinformatics work, we examine the distributions of over 50,000 annotated prophage genes identified in 1384 prophage sequences, comparing the gene repertoires of intact and incomplete prophages.

Quantifying the forces that maintain prophages in bacterial genomes.

Genome sequencing has revealed that prophages, viral sequences integrated in a bacterial chromosome, are abundant, accounting for as much as 20% of the bacterial genome. These sequences can confer fitness benefits to the bacterial host, but may also instigate cell death through induction. Several recent investigations have revealed that the distribution of prophage lengths is bimodal, with a clear distinction between small and large prophages.

Evolutionary stability of the lysis-lysogeny decision: Why be virulent?

Lytic viruses infect and kill host cells, producing a large number of viral copies. Temperate viruses, in contrast, are able to integrate viral genetic material into the host cell DNA, leaving a viable host cell. The evolutionary advantage of this strategy, lysogeny, has been demonstrated in complex environments that include spatial structure, oscillating population dynamics, or periodic environmental collapse.

Evolutionary emergence of infectious diseases in heterogeneous host populations.

The emergence and re-emergence of pathogens remains a major public health concern. Unfortunately, when and where pathogens will (re-)emerge is notoriously difficult to predict, as the erratic nature of those events is reinforced by the stochastic nature of pathogen evolution during the early phase of an epidemic. For instance, mutations allowing pathogens to escape host resistance may boost pathogen spread and promote emergence.

Effects of Transmission Bottlenecks on the Diversity of Influenza A Virus.

We investigate the fate of mutations that occur during the in-host replication of a pathogenic virus, predicting the probability that such mutations are passed on during disease transmission to a new host. Using influenza A virus as a model organism, we develop a life-history model of the within-host dynamics of the infection, deriving a multitype branching process with a coupled deterministic model to capture the population of available target cells. We quantify the fate of neutral mutations and mutations affecting five life-history traits: clearance, attachment, budding, cell death, and eclipse phase timing.

Prophage as a genetic reservoir: Promoting diversity and driving innovation in the host community.

Sequencing of bacterial genomes has revealed an abundance of prophage sequences in many bacterial species. Since these sequences are accessible, through recombination, to infecting phages, bacteria carry an arsenal of genetic material that can be used by these viruses. We develop a mathematical model to isolate the effects of this phenomenon on the coevolution of temperate phage and bacteria.

Mathematical modelling of CRISPR-Cas system effects on biofilm formation.

Clustered regularly interspaced short palindromic repeats (CRISPR), linked with CRISPR associated (Cas) genes, can confer adaptive immunity to bacteria, against bacteriophage infections. Thus from a therapeutic standpoint, CRISPR immunity increases biofilm resistance to phage therapy. Recently, however, CRISPR-Cas genes have been implicated in reducing biofilm formation in lysogenized cells.

Prophage Provide a Safe Haven for Adaptive Exploration in Temperate Viruses.

Prophage sequences constitute a substantial fraction of the temperate virus gene pool. Although subject to mutational decay, prophage sequences can also be an important source of adaptive mutations for these viral populations. Here we develop a life-history model for temperate viruses, including both the virulent (lytic) and the temperate phases of the life cycle.

Bee++: An Object-Oriented, Agent-Based Simulator for Honey Bee Colonies.

We present a model and associated simulation package (www.beeplusplus.ca) to capture the natural dynamics of a honey bee colony in a spatially-explicit landscape, with temporally-variable, weather-dependent parameters.

The dynamics of mobile promoters: Enhanced stability in promoter regions.

Mobile promoters are emerging as a new class of mobile genetic elements, first identified by examining prokaryote genome sequences, and more recently confirmed by experimental observations in bacteria. Recent datasets have identified over 40,000 putative mobile promoters in sequenced prokaryote genomes, however only one-third of these are in regions of the genome directly upstream from coding sequences, that is, in promoter regions. The presence of many promoter sequences in non-promoter regions is unexplained.

Backward bifurcations, turning points and rich dynamics in simple disease models.

In this paper, dynamical systems theory and bifurcation theory are applied to investigate the rich dynamical behaviours observed in three simple disease models. The 2- and 3-dimensional models we investigate have arisen in previous investigations of epidemiology, in-host disease, and autoimmunity. These closely related models display interesting dynamical behaviors including bistability, recurrence, and regular oscillations, each of which has possible clinical or public health implications.

Extinction probabilities and stationary distributions of mobile genetic elements in prokaryotes: The birth-death-diversification model.

Theoretical approaches are essential to our understanding of the complex dynamics of mobile genetic elements (MGEs) within genomes. Recently, the birth-death-diversification model was developed to describe the dynamics of mobile promoters (MPs), a particular class of MGEs in prokaryotes. A unique feature of this model is that genetic diversification of elements was included.