Demographic feedbacks during evolutionary rescue can slow or speed adaptive evolution.

Populations declining toward extinction can persist via genetic adaptation in a process called evolutionary rescue. Predicting evolutionary rescue has applications ranging from conservation biology to medicine, but requires understanding and integrating the multiple effects of a stressful environmental change on population processes. Here we derive a simple expression for how generation time, a key determinant of the rate of evolution, varies with population size during evolutionary rescue. Change in generation time is quantitatively predicted by comparing how intraspecific competition and the source of maladaptation each affect the rates of births and deaths in the population. Depending on the difference between two parameters quantifying these effects, the model predicts that populations may experience substantial changes in their rate of adaptation in both positive and negative directions, or adapt consistently despite severe stress. These predictions were then tested by comparison to the results of individual-based simulations of evolutionary rescue, which validated that the tolerable rate of environmental change varied considerably as described by analytical results. We discuss how these results inform efforts to understand wildlife disease and adaptation to climate change, evolution in managed populations and treatment resistance in pathogens.

Evolvability Costs of Niche Expansion.

What prevents generalists from displacing specialists, despite obvious competitive advantages of utilizing a broad niche? The classic genetic explanation is antagonistic pleiotropy: genes underlying the generalism produce 'jacks-of-all-trades' that are masters of none. However, experiments challenge this assumption that mutations enabling niche expansion must reduce fitness in other environments. Theory suggests an alternative cost of generalism: decreased evolvability, or the reduced capacity to adapt. Generalists using multiple environments experience relaxed selection in any one environment, producing greater relative lag load. Additionally, mutations fixed by generalist lineages early during their evolution that avoid or compensate for antagonistic pleiotropy may limit access to certain future evolutionary trajectories. Hypothesized evolvability costs of generalism warrant further exploration, and we suggest outstanding questions meriting attention.

Exploring the expanse between theoretical questions and experimental approaches in the modern study of evolvability.

Despite several decades of computational and experimental work across many systems, evolvability remains on the periphery with regards to its status as a widely accepted and regularly applied theoretical concept. Here we propose that its marginal status is partly a result of large gaps between the diverse but disconnected theoretical treatments of evolvability and the relatively narrower range of studies that have tested it empirically. To make this case, we draw on a range of examples-from experimental evolution in microbes, to molecular evolution in proteins-where attempts have been made to mend this disconnect. We highlight some examples of progress that has been made and point to areas where synthesis and translation of existing theory can lead to further progress in the still-new field of empirical measurements of evolvability.

Evolutionary rescue via niche construction: Infrequent construction can prevent post-invasion extinction.

A population experiencing habitat loss can avoid extinction by undergoing genetic adaptation-a process known as evolutionary rescue. Here we analytically approximate the probability of evolutionary rescue via a niche-constructing mutation that allows carriers to convert a novel, unfavorable reproductive habitat to a favorable state at a cost to their fecundity. We analyze competition between mutants and non-niche-constructing wild types, who ultimately require the constructed habitats to reproduce. We find that over-exploitation of the constructed habitats by wild types can generate damped oscillations in population size shortly after mutant invasion, thereby decreasing the probability of rescue. Such post-invasion extinction is less probable when construction is infrequent, habitat loss is common, the reproductive environment is large, or the population's carrying capacity is small. Under these conditions, wild types are less likely to encounter the constructed habitats and, consequently, mutants are more likely to fix. These results suggest that, without a mechanism that deters wild type inheritance of the constructed habitats, a population undergoing rescue via niche construction may remain prone to short-timescale extinction despite successful mutant invasion.

Bet-hedging via dispersal aids the evolution of plastic responses to unreliable cues.

Adaptive plasticity is expected to evolve when informative cues predict environmental variation. However, plastic responses can be maladaptive even when those cues are informative, if prediction mistakes are shared across members of a generation. These fitness costs can constrain the evolution of plasticity when initial plastic mutants use of cues of only moderate reliability. Here, we model the barriers to the evolution of plasticity produced by these constraints and show that dispersal across a metapopulation can overcome them. Constraints are also lessened, though not eliminated, when plastic responses are free to evolve gradually and in concert with increased reliability. Each of these factors be viewed as a form of bet-hedging: by lessening correlations in the fates of relatives, dispersal acts as diversifying bet-hedging, while producing submaximal responses to a cue can be understood as a conservative bet-hedging strategy. While poor information may constrain the evolution of plasticity, the opportunity for bet-hedging may predict when that constraint can be overcome.

Links between evolutionary processes and phenotypic robustness in microbes.

The costs and benefits of random phenotypic heterogeneity in microbes have been vigorously debated and experimental tested for decades; yet, this conversation is largely independent from discussion of phenotypic robustness in other disciplines. In this review I connect microbial examples of stochasticity with studies on the ecological and population-genetic consequences of phenotypic variability. These topics illustrate the complexity of selection pressures on phenotypic robustness and provide inspiration that this complexity can be parsed with theoretical advances and the experimental power of microbial systems.

Asymmetric Evolvability Leads to Specialization without Trade-Offs.

AbstractMany organisms are specialized, and these narrow niches are often explained with trade-offs-the inability for one organism to express maximal performance in two or more environments. However, evidence is lacking that trade-offs are sufficient to explain specialists. Several lines of theoretical inquiry suggest that populations can specialize without explicit trade-offs, as a result of relaxed selection in generalists for their performance in rare environments. Here, I synthesize and extend these approaches, showing that emergent asymmetries in evolvability can push a population toward specialization in the absence of trade-offs and in the presence of substantial ecological costs of specialism. Simulations are used to demonstrate how adaptation to a more common environment interferes with adaptation to a less common but otherwise equal alternative environment and that this interference is greatly exacerbated at low recombination rates. This adaptive process of specialization can effectively trap populations in a suboptimal niche. These modeling results predict that transient differences in evolvability across traits during a single episode of adaptation could have long-term consequences for a population's niche.

Developmental noise and ecological opportunity across space can release constraints on the evolution of plasticity.

Phenotypic plasticity is a potentially definitive solution to environment heterogeneity, driving biologists to understand why it is not ubiquitous in nature. While costs and constraints may limit the success of plasticity, we are still far from a complete theory of when these limitations actually proscribe adaptive plasticity. Here I use a simple model of plasticity incorporating developmental noise to explore the competitive and evolutionary relationships of specialist and generalist genotypes spreading across a heterogeneous landscape. Results show that plasticity can arise in the context of specialism, preadapting genotypes to later evolve toward plastic generalism. Developmental noise helps a mutant with imperfect plasticity successfully compete against its ancestor, providing an evolutionary path by which subsequent mutations can refine plasticity toward its optimum. These results address how the complex selection pressures across a heterogeneous environment can help evolution find paths around constraints arising from developmental mechanisms.

Existing Host Range Mutations Constrain Further Emergence of RNA Viruses.

RNA viruses are capable of rapid host shifting, typically due to a point mutation that confers expanded host range. As additional point mutations are necessary for further expansions, epistasis among host range mutations can potentially affect the mutational neighborhood and frequency of niche expansion. We mapped the mutational neighborhood of host range expansion using three genotypes of the double-stranded RNA (dsRNA) bacteriophage φ6 (wild type and two isogenic host range mutants) on the novel host Pseudomonas syringae pv. atrofaciens. Both Sanger sequencing of 50 P. syringae pv. atrofaciens mutant clones for each genotype and population Illumina sequencing revealed the same high-frequency mutations allowing infection of P. syringae pv. atrofaciens. Wild-type φ6 had at least nine different ways of mutating to enter the novel host, eight of which are in p3 (host attachment protein gene), and 13/50 clones had unchanged p3 genes. However, the two isogenic mutants had dramatically restricted neighborhoods: only one or two mutations, all in p3. Deep sequencing revealed that wild-type clones without mutations in p3 likely had changes in p12 (morphogenic protein), a region that was not polymorphic for the two isogenic host range mutants. Sanger sequencing confirmed that 10/13 of the wild-type φ6 clones had nonsynonymous mutations in p12, and 2 others had point mutations in p9 and p5. None of these genes had previously been associated with host range expansion in φ6. We demonstrate, for the first time, epistatic constraint in an RNA virus due to host range mutations themselves, which has implications for models of serial host range expansion.IMPORTANCE RNA viruses mutate rapidly and frequently expand their host ranges to infect novel hosts, leading to serial host shifts. Using an RNA bacteriophage model system (Pseudomonas phage φ6), we studied the impact of preexisting host range mutations on another host range expansion. Results from both clonal Sanger and Illumina sequencing show that extant host range mutations dramatically narrow the neighborhood of potential host range mutations compared to that of wild-type φ6. This research suggests that serial host-shifting viruses may follow a small number of molecular paths to enter additional novel hosts. We also identified new genes involved in φ6 host range expansion, expanding our knowledge of this important model system in experimental evolution.

Phenotypic variability can promote the evolution of adaptive plasticity by reducing the stringency of natural selection.

Adaptive phenotypic plasticity is a potent but not ubiquitous solution to environmental heterogeneity, driving interest in what factors promote and limit its evolution. Here, a novel computational model representing stochastic information flow in development is used to explore evolution from a constitutive phenotype to an adaptively plastic response. Results show that populations tend to evolve robustness to developmental stochasticity, but that this evolved robustness limits evolvability; specifically, robust genotypes have less ability to evolve adaptive plasticity when presented with a mix of both the ancestral environment and a new environment. Analytic calculations and computational experiments confirm that this constraint occurs when the initial mutational steps towards plasticity are pleiotropic, such that mutant fitnesses decline in the environment to which their parents are well-adapted. Greater phenotypic variability improves evolvability in the model by lessening this decline as well as by improving the fitness of partial adaptations to the new environment. By making initial plastic mutations more palatable to natural selection, phenotypic variability can increase the evolvability of an innovative, plastic response without improving evolvability to simpler challenges such as a shifted optimum in a single environment. Populations that evolved robustness by negative feedback between the trait and its rate of change show a particularly strong constraining effect on the evolvability of plasticity, revealing another mechanism by which evolutionary history can limit later innovation. These results document a novel mechanism by which weakening selection could actually stimulate the evolution of a major innovation.

Local Adaptation Interacts with Expansion Load during Range Expansion: Maladaptation Reduces Expansion Load.

The biotic and abiotic factors that facilitate or hinder species range expansions are many and complex. We examine the impact of two genetic processes and their interaction on fitness at expanding range edges: local maladaptation resulting from the presence of an environmental gradient and expansion load resulting from increased genetic drift at the range edge. Results from spatially explicit simulations indicate that the presence of an environmental gradient during range expansion reduces expansion load; conversely, increasing expansion load allows only locally adapted populations to persist at the range edge. Increased maladaptation reduces the speed of range expansion, resulting in less genetic drift at the expanding front and more immigration from the range center, therefore reducing expansion load at the range edge. These results may have ramifications for species being forced to shift their ranges because of climate change or other anthropogenic changes. If rapidly changing climate leads to faster expansion as populations track their shifting climatic optima, populations may suffer increased expansion load beyond previous expectations.

Mapping the fitness landscape of gene expression uncovers the cause of antagonism and sign epistasis between adaptive mutations.

How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial mutations that altered enzyme levels in the central metabolism of Methylobacterium extorquens to uncover the fitness landscape defined by gene expression levels. We found strong antagonism and sign epistasis between these beneficial mutations. Mutations with the largest individual benefit interacted the most antagonistically with other mutations, a trend we also uncovered through analyses of datasets from other model systems. However, these beneficial mutations interacted multiplicatively (i.e., no epistasis) at the level of enzyme expression. By generating a model that predicts fitness from enzyme levels we could explain the observed sign epistasis as a result of overshooting the optimum defined by a balance between enzyme catalysis benefits and fitness costs. Knowledge of the phenotypic landscape also illuminated that, although the fitness peak was phenotypically far from the ancestral state, it was not genetically distant. Single beneficial mutations jumped straight toward the global optimum rather than being constrained to change the expression phenotypes in the correlated fashion expected by the genetic architecture. Given that adaptation in nature often results from optimizing gene expression, these conclusions can be widely applicable to other organisms and selective conditions. Poor interactions between individually beneficial alleles affecting gene expression may thus compromise the benefit of sex during adaptation and promote genetic differentiation.

Mutational robustness can facilitate adaptation.

Robustness seems to be the opposite of evolvability. If phenotypes are robust against mutation, we might expect that a population will have difficulty adapting to an environmental change, as several studies have suggested. However, other studies contend that robust organisms are more adaptable. A quantitative understanding of the relationship between robustness and evolvability will help resolve these conflicting reports and will clarify outstanding problems in molecular and experimental evolution, evolutionary developmental biology and protein engineering. Here we demonstrate, using a general population genetics model, that mutational robustness can either impede or facilitate adaptation, depending on the population size, the mutation rate and the structure of the fitness landscape. In particular, neutral diversity in a robust population can accelerate adaptation as long as the number of phenotypes accessible to an individual by mutation is smaller than the total number of phenotypes in the fitness landscape. These results provide a quantitative resolution to a significant ambiguity in evolutionary theory.

Range expansion can promote the evolution of plastic generalism in coarse-grained landscapes.

Phenotypic plasticity is one way for organisms to deal with variable environments through generalism. However, plasticity is not found universally and its evolution may be constrained by costs and other limitations such as complexity: the need for multiple mutational steps before the adaptation is realized. Theory predicts that greater experienced heterogeneity, such as organisms may encounter when spatial heterogeneity is fine-grained relative to dispersal, should favor the evolution of a broader niche. Here we tested this prediction via simulation. We found that, contrary to classical predictions, coarse-grained landscapes can be the most favorable for the evolution of plasticity, but only when populations encounter those landscapes through range expansion. During these range expansions, coarse-grained landscapes select for each step in the complex mutational pathway to plastic generalism by blocking the dispersal of specialists. These circumstances provide ecological opportunities for innovative mutations that change the niche. Our results indicate a new mechanism by which range expansion and spatially structured landscapes interact to shape evolution and reveal that the environments in which a complex adaptation has the highest fitness may not be the most favorable for its evolution.

Modeling poliovirus replication dynamics from live time-lapse single-cell imaging data.

Viruses experience selective pressure on the timing and order of events during infection to maximize the number of viable offspring they produce. Additionally, they may experience variability in cellular environments encountered, as individual eukaryotic cells can display variation in gene expression among cells. This leads to a dynamic phenotypic landscape that viruses must face to replicate. To examine replication dynamics displayed by viruses faced with this variable landscape, we have developed a method for fitting a stochastic mechanistic model of viral infection to time-lapse imaging data from high-throughput single-cell poliovirus infection experiments. The model's mechanistic parameters provide estimates of several aspects associated with the virus's intracellular dynamics. We examine distributions of parameter estimates and assess their variability to gain insight into the root causes of variability in viral growth dynamics. We also fit our model to experiments performed under various drug treatments and examine which parameters differ under these conditions. We find that parameters associated with translation and early stage viral replication processes are essential for the model to capture experimentally observed dynamics. In aggregate, our results suggest that differences in viral growth data generated under different treatments can largely be captured by steps that occur early in the replication process.

Genetic Context Significantly Influences the Maintenance and Evolution of Degenerate Pathways.

Understanding the evolution of novel physiological traits is highly relevant for expanding the characterization and manipulation of biological systems. Acquisition of new traits can be achieved through horizontal gene transfer (HGT). Here, we investigate drivers that promote or deter the maintenance of HGT-driven degeneracy, occurring when processes accomplish identical functions through nonidentical components. Subsequent evolution can optimize newly acquired functions; for example, beneficial alleles identified in an engineered Methylorubrum extorquens strain allowed it to utilize a "Foreign" formaldehyde oxidation pathway substituted for its Native pathway for methylotrophic growth. We examined the fitness consequences of interactions between these alleles when they were combined with the Native pathway or both (Dual) pathways. Unlike the Foreign pathway context where they evolved, these alleles were often neutral or deleterious when moved into these alternative genetic backgrounds. However, there were instances where combinations of multiple alleles resulted in higher fitness outcomes than individual allelic substitutions could provide. Importantly, the genetic context accompanying these allelic substitutions significantly altered the fitness landscape, shifting local fitness peaks and restricting the set of accessible evolutionary trajectories. These findings highlight how genetic context can negatively impact the probability of maintaining native and HGT-introduced functions together, making it difficult for degeneracy to evolve. However, in cases where the cost of maintaining degeneracy was mitigated by adding evolved alleles impacting the function of these pathways, we observed rare opportunities for pathway coevolution to occur. Together, our results highlight the importance of genetic context and resulting epistasis in retaining or losing HGT-acquired degenerate functions.

Correlational selection in the age of genomics.

Ecologists and evolutionary biologists are well aware that natural and sexual selection do not operate on traits in isolation, but instead act on combinations of traits. This long-recognized and pervasive phenomenon is known as multivariate selection, or-in the particular case where it favours correlations between interacting traits-correlational selection. Despite broad acknowledgement of correlational selection, the relevant theory has often been overlooked in genomic research. Here, we discuss theory and empirical findings from ecological, quantitative genetic and genomic research, linking key insights from different fields. Correlational selection can operate on both discrete trait combinations and quantitative characters, with profound implications for genomic architecture, linkage, pleiotropy, evolvability, modularity, phenotypic integration and phenotypic plasticity. We synthesize current knowledge and discuss promising research approaches that will enable us to understand how correlational selection shapes genomic architecture, thereby linking quantitative genetic approaches with emerging genomic methods. We suggest that research on correlational selection has great potential to integrate multiple fields in evolutionary biology, including developmental and functional biology, ecology, quantitative genetics, phenotypic polymorphisms, hybrid zones and speciation processes.

Plasticity via feedback reduces the cost of developmental instability.

Costs of plasticity are thought to have important physiological and evolutionary consequences. A commonly predicted cost to plasticity is that plastic genotypes are likely to suffer from developmental instability. Adaptive plasticity requires that the developing organism can in some way sense what environment it is in or how well it is performing in that environment. These two information pathways-an "environmental signal" or a "performance signal" that indicates how well a developing phenotype matches the optimum in the current environment-can differ in their consequences for the organism and its evolution. Here, we consider how developmental instability might emerge as a side-effect of these two distinct mechanisms. Because a performance cue allows a regulatory feedback loop connecting a trait to a feedback signal, we hypothesized that plastic genotypes using a performance signal would be more developmentally robust compared to those using a purely environmental signal. Using a numerical model of a network of gene interactions, we show that plasticity comes at a cost of developmental instability when the plastic response is mediated via an environmental signal, but not when it is mediated via a performance signal. We also show that a performance signal mechanism can evolve even in a constant environment, leading to genotypes preadapted for plasticity to novel environments even in populations without a history of environmental heterogeneity.

An Amyloid Core Sequence in the Major Candida albicans Adhesin Als1p Mediates Cell-Cell Adhesion.

The human fungal commensal Candida albicans can become a serious opportunistic pathogen in immunocompromised hosts. The C. albicans cell adhesion protein Als1p is a highly expressed member of a large family of paralogous adhesins. Als1p can mediate binding to epithelial and endothelial cells, is upregulated in infections, and is important for biofilm formation. Als1p includes an amyloid-forming sequence at amino acids 325 to 331, identical to the sequence in the paralogs Als5p and Als3p. Therefore, we mutated Val326 to test whether this sequence is important for activity. Wild-type Als1p (Als1pWT) and Als1p with the V326N mutation (Als1pV326N) were expressed at similar levels in a Saccharomyces cerevisiae surface display model. Als1pV326N cells adhered to bovine serum albumin (BSA)-coated beads similarly to Als1pWT cells. However, cells displaying Als1pV326N showed visibly smaller aggregates and did not fluoresce in the presence of the amyloid-binding dye Thioflavin-T. A new analysis tool for single-molecule force spectroscopy-derived surface mapping showed that statistically significant force-dependent Als1p clustering occurred in Als1pWT cells but was absent in Als1pV326N cells. In single-cell force spectroscopy experiments, strong cell-cell adhesion was dependent on an intact amyloid core sequence on both interacting cells. Thus, the major adhesin Als1p interacts through amyloid-like ß-aggregation to cluster adhesin molecules in cis on the cell surface as well as in trans to form cell-cell bonds.IMPORTANCE Microbial cell surface adhesins control essential processes such as adhesion, colonization, and biofilm formation. In the opportunistic fungal pathogen Candida albicans, the agglutinin-like sequence (ALS) gene family encodes eight cell surface glycoproteins that mediate adherence to biotic and abiotic surfaces and cell-cell aggregation. Als proteins are critical for commensalism and virulence. Their activities include attachment and invasion of endothelial and epithelial cells, morphogenesis, and formation of biofilms on host tissue and indwelling medical catheters. At the molecular level, Als5p-mediated cell-cell aggregation is dependent on the formation of amyloid-like nanodomains between Als5p-expressing cells. A single-site mutation to valine 326 abolishes cellular aggregation and amyloid formation. Our results show that the binding characteristics of Als1p follow a mechanistic model similar to Als5p, despite its differential expression and biological roles.