Allele surfing promotes microbial adaptation from standing variation

Substrate geometry affects population dynamics in a bacterial biofilm

Biofilms inhabit a range of environments, such as dental plaques or soil micropores, often characterized by noneven surfaces. However, the impact of surface irregularities on the population dynamics of biofilms remains elusive, as most experiments are conducted on flat surfaces. Here, we show that the shape of the surface on which a biofilm grows influences genetic drift and selection within the biofilm. We culture Escherichia coli biofilms in microwells with a corrugated bottom surface and observe the emergence of clonal sectors whose size corresponds to that of the corrugations, despite no physical barrier separating different areas of the biofilm. The sectors are remarkably stable and do not invade each other; we attribute this stability to the characteristics of the velocity field within the biofilm, which hinders mixing and clonal expansion. A microscopically detailed computer model fully reproduces these findings and highlights the role of mechanical interactions such as adhesion and friction in microbial evolution. The model also predicts clonal expansion to be limited even for clones with a significant growth advantage-a finding which we confirm experimentally using a mixture of antibiotic-sensitive and antibiotic-resistant mutants in the presence of sublethal concentrations of the antibiotic rifampicin. The strong suppression of selection contrasts sharply with the behavior seen in range expansion experiments in bacterial colonies grown on agar. Our results show that biofilm population dynamics can be affected by patterning the surface and demonstrate how a better understanding of the physics of bacterial growth can be used to control microbial evolution.

Fitness effects of a demography-dispersal trade-off in expandingSaccharomyces cerevisiaemats

Fungi expand in space and time to form complex multicellular communities. The mechanisms by which they do so can vary dramatically and determine the life-history and dispersal traits of expanding populations. These traits influence deterministic and stochastic components of evolution, resulting in complex eco-evolutionary dynamics during colony expansion. We perform experiments on budding yeast strains genetically engineered to display rough-surface and smooth-surface phenotypes in colony-like structures called 'mats'. Previously, it was shown that the rough-surface strain has a competitive advantage over the smooth-surface strain when grown on semi-solid media. We experimentally observe the emergence and expansion of segments with a distinct smooth-surface phenotype during rough-surface mat development. We propose a trade-off between dispersal and local carrying capacity to explain the relative fitness of these two phenotypes. Using a modified stepping-stone model, we demonstrate that this trade-off gives the high-dispersing, rough-surface phenotype a competitive advantage from standing variation, but that it inhibits this phenotype's ability to invade a resident smooth-surface population via mutation. However, the trade-off improves the ability of the smooth-surface phenotype to invade in rough-surface mats, replicating the frequent emergence of smooth-surface segments in experiments. Together, these computational and experimental findings advance our understanding of the complex eco-evolutionary dynamics of fungal mat expansion.

Genome size variation and evolution during invasive range expansion in an introduced plant

Plants demonstrate exceptional variation in genome size across species, and their genome sizes can also vary dramatically across individuals and populations within species. This aspect of genetic variation can have consequences for traits and fitness, but few studies attributed genome size differentiation to ecological and evolutionary processes. Biological invasions present particularly useful natural laboratories to infer selective agents that might drive genome size shifts across environments and population histories. Here, we test hypotheses for the evolutionary causes of genome size variation across 14 invading populations of yellow starthistle, Centaurea solstitialis, in California, United States. We use a survey of genome sizes and trait variation to ask: (1) Is variation in genome size associated with developmental trait variation? (2) Are genome sizes smaller toward the leading edge of the expansion, consistent with selection for "colonizer" traits? Or alternatively, does genome size increase toward the leading edge of the expansion, consistent with predicted consequences of founder effects and drift? (3) Finally, are genome sizes smaller at higher elevations, consistent with selection for shorter development times? We found that 2C DNA content varied 1.21-fold among all samples, and was associated with flowering time variation, such that plants with larger genomes reproduced later, with lower lifetime capitula production. Genome sizes increased toward the leading edge of the invasion, but tended to decrease at higher elevations, consistent with genetic drift during range expansion but potentially strong selection for smaller genomes and faster development time at higher elevations. These results demonstrate how genome size variation can contribute to traits directly tied to reproductive success, and how selection and drift can shape that variation. We highlight the influence of genome size on dynamics underlying a rapid range expansion in a highly problematic invasive plant.

Concurrent invasions of European starlings in Australia and North America reveal population-specific differentiation in shared genomic regions

A species' success during the invasion of new areas hinges on an interplay between the demographic processes common to invasions and the specific ecological context of the novel environment. Evolutionary genetic studies of invasive species can investigate how genetic bottlenecks and ecological conditions shape genetic variation in invasions, and our study pairs two invasive populations that are hypothesized to be from the same source population to compare how each population evolved during and after introduction. Invasive European starlings (Sturnus vulgaris) established populations in both Australia and North America in the 19th century. Here, we compare whole-genome sequences among native and independently introduced European starling populations to determine how demographic processes interact with rapid evolution to generate similar genetic patterns in these recent and replicated invasions. Demographic models indicate that both invasive populations experienced genetic bottlenecks as expected based on invasion history, and we find that specific genomic regions have differentiated even on this short evolutionary timescale. Despite genetic bottlenecks, we suggest that genetic drift alone cannot explain differentiation in at least two of these regions. The demographic boom intrinsic to many invasions as well as potential inversions may have led to high population-specific differentiation, although the patterns of genetic variation are also consistent with the hypothesis that this infamous and highly mobile invader adapted to novel selection (e.g., extrinsic factors). We use targeted sampling of replicated invasions to identify and evaluate support for multiple, interacting evolutionary mechanisms that lead to differentiation during the invasion process.

Specialization at an expanding front

As a population grows, spreading to new environments may favor specialization. In this paper, we introduce and explore a model for specialization at the front of a colony expanding synchronously into new territory. We show through numerical simulations that, by gaining fitness through accumulating mutations, progeny of the initial seed population can differentiate into distinct specialists. With competition and selection limited to the growth front, the emerging specialists first segregate into sectors, which then expand to dominate the entire population. We quantify the scaling of the fixation time with the size of the population and observe different behaviors corresponding to distinct universality classes: unbounded and bounded gains in fitness lead to superdiffusive (z=3/2) and diffusive (z=2) stochastic wanderings of the sector boundaries, respectively.

Quantifying stochastic establishment of mutants in microbial adaptation

Studies of microbial evolution, especially in applied contexts, have focused on the role of selection in shaping predictable, adaptive responses to the environment. However, chance events - the appearance of novel genetic variants and their establishment, i.e. outgrowth from a single cell to a sizeable population - also play critical initiating roles in adaptation. Stochasticity in establishment has received little attention in microbiology, potentially due to lack of awareness as well as practical challenges in quantification. However, methods for high-replicate culturing, mutant labelling and detection, and statistical inference now make it feasible to experimentally quantify the establishment probability of specific adaptive genotypes. I review methods that have emerged over the past decade, including experimental design and mathematical formulas to estimate establishment probability from data. Quantifying establishment in further biological settings and comparing empirical estimates to theoretical predictions represent exciting future directions. More broadly, recognition that adaptive genotypes may be stochastically lost while rare is significant both for interpreting common lab assays and for designing interventions to promote or inhibit microbial evolution.

Timing of antibiotic administration determines the spread of plasmid-encoded antibiotic resistance during microbial range expansion

Plasmids are the main vector by which antibiotic resistance is transferred between bacterial cells within surface-associated communities. In this study, we ask whether there is an optimal time to administer antibiotics to minimize plasmid spread in new bacterial genotypes during community expansion across surfaces. We address this question using consortia of Pseudomonas stutzeri strains, where one is an antibiotic resistance-encoding plasmid donor and the other a potential recipient. We allowed the strains to co-expand across a surface and administered antibiotics at different times. We find that plasmid transfer and transconjugant proliferation have unimodal relationships with the timing of antibiotic administration, where they reach maxima at intermediate times. These unimodal relationships result from the interplay between the probabilities of plasmid transfer and loss. Our study provides mechanistic insights into the transfer and proliferation of antibiotic resistance-encoding plasmids within microbial communities and identifies the timing of antibiotic administration as an important determinant.

Proliferating active matter

The fascinating patterns of collective motion created by autonomously driven particles have fuelled active-matter research for over two decades. So far, theoretical active-matter research has often focused on systems with a fixed number of particles. This constraint imposes strict limitations on what behaviours can and cannot emerge. However, a hallmark of life is the breaking of local cell number conservation by replication and death. Birth and death processes must be taken into account, for example, to predict the growth and evolution of a microbial biofilm, the expansion of a tumour, or the development from a fertilized egg into an embryo and beyond. In this Perspective, we argue that unique features emerge in these systems because proliferation represents a distinct form of activity: not only do the proliferating entities consume and dissipate energy, they also inject biomass and degrees of freedom capable of further self-proliferation, leading to myriad dynamic scenarios. Despite this complexity, a growing number of studies document common collective phenomena in various proliferating soft-matter systems. This generality leads us to propose proliferation as another direction of active-matter physics, worthy of a dedicated search for new dynamical universality classes. Conceptual challenges abound, from identifying control parameters and understanding large fluctuations and nonlinear feedback mechanisms to exploring the dynamics and limits of information flow in self-replicating systems. We believe that, by extending the rich conceptual framework developed for conventional active matter to proliferating active matter, researchers can have a profound impact on quantitative biology and reveal fascinating emergent physics along the way.

State-dependent evolutionary models reveal modes of solid tumour growth

Spatial properties of tumour growth have profound implications for cancer progression, therapeutic resistance and metastasis. Yet, how spatial position governs tumour cell division remains difficult to evaluate in clinical tumours. Here, we demonstrate that faster division on the tumour periphery leaves characteristic genetic patterns, which become evident when a phylogenetic tree is reconstructed from spatially sampled cells. Namely, rapidly dividing peripheral lineages branch more extensively and acquire more mutations than slower-dividing centre lineages. We develop a Bayesian state-dependent evolutionary phylodynamic model (SDevo) that quantifies these patterns to infer the differential division rates between peripheral and central cells. We demonstrate that this approach accurately infers spatially varying birth rates of simulated tumours across a range of growth conditions and sampling strategies. We then show that SDevo outperforms state-of-the-art, non-cancer multi-state phylodynamic methods that ignore differential sequence evolution. Finally, we apply SDevo to single-time-point, multi-region sequencing data from clinical hepatocellular carcinomas and find evidence of a three- to six-times-higher division rate on the tumour edge. With the increasing availability of high-resolution, multi-region sequencing, we anticipate that SDevo will be useful in interrogating spatial growth restrictions and could be extended to model non-spatial factors that influence tumour progression.

Evolutionary rescue of resistant mutants is governed by a balance between radial expansion and selection in compact populations

Mutation-mediated treatment resistance is one of the primary challenges for modern antibiotic and anti-cancer therapy. Yet, many resistance mutations have a substantial fitness cost and are subject to purifying selection. How emerging resistant lineages may escape purifying selection via subsequent compensatory mutations is still unclear due to the difficulty of tracking such evolutionary rescue dynamics in space and time. Here, we introduce a system of fluorescence-coupled synthetic mutations to show that the probability of evolutionary rescue, and the resulting long-term persistence of drug resistant mutant lineages, is dramatically increased in dense microbial populations. By tracking the entire evolutionary trajectory of thousands of resistant lineages in expanding yeast colonies we uncover an underlying quasi-stable equilibrium between the opposing forces of radial expansion and natural selection, a phenomenon we term inflation-selection balance. Tailored computational models and agent-based simulations corroborate the fundamental nature of the observed effects and demonstrate the potential impact on drug resistance evolution in cancer. The described phenomena should be considered when predicting multi-step evolutionary dynamics in any mechanically compact cellular population, including pathogenic microbial biofilms and solid tumors. The insights gained will be especially valuable for the quantitative understanding of response to treatment, including emerging evolution-based therapy strategies.

Mechanisms driving spatial distribution of residents in colony biofilms: an interdisciplinary perspective

Biofilms are consortia of microorganisms that form collectives through the excretion of extracellular matrix compounds. The importance of biofilms in biological, industrial and medical settings has long been recognized due to their emergent properties and impact on surrounding environments. In laboratory situations, one commonly used approach to study biofilm formation mechanisms is the colony biofilm assay, in which cell communities grow on solid-gas interfaces on agar plates after the deposition of a population of founder cells. The residents of a colony biofilm can self-organize to form intricate spatial distributions. The assay is ideally suited to coupling with mathematical modelling due to the ability to extract a wide range of metrics. In this review, we highlight how interdisciplinary approaches have provided deep insights into mechanisms causing the emergence of these spatial distributions from well-mixed inocula.

Selection in a growing colony biases results of mutation accumulation experiments

Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments can be performed with different effective population sizes. In MA experiments with bacteria, a single founder is grown to a size of a colony (~ 10⁸). It is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth. In this work, we simulate colony growth via a mathematical model, and use our model to mimic an MA experiment. We demonstrate that selection ensures that, in an MA experiment, fraction of all mutations that are beneficial is over-represented by a factor of almost two, and that the distribution of fitness effects of beneficial and deleterious mutations are inaccurately captured in an MA experiment. Given this, the estimate of mutation rates from MA experiments is non-trivial. We then perform an MA experiment with 160 lines of E. coli, and show that due to the effect of selection in a growing colony, the size and sector of a colony from which the experiment is propagated impacts the results. Overall, we demonstrate that the results of MA experiments need to be revisited taking into account the action of selection in a growing colony.

Growth instabilities shape morphology and genetic diversity of microbial colonies

Cellular populations assume an incredible variety of shapes ranging from circular molds to irregular tumors. While we understand many of the mechanisms responsible for these spatial patterns, little is known about how the shape of a population influences its ecology and evolution. Here, we investigate this relationship in the context of microbial colonies grown on hard agar plates. This a well-studied system that exhibits a transition from smooth circular disks to more irregular and rugged shapes as either the nutrient concentration or cellular motility is decreased. Starting from a mechanistic model of colony growth, we identify two dimensionless quantities that determine how morphology and genetic diversity of the population depend on the model parameters. Our simulations further reveal that population dynamics cannot be accurately described by the commonly-used surface growth models. Instead, one has to explicitly account for the emergent growth instabilities and demographic fluctuations. Overall, our work links together environmental conditions, colony morphology, and evolution. This link is essential for a rational design of concrete, biophysical perturbations to steer evolution in the desired direction.

Lineage dynamics in growing biofilms: Spatial patterns of standing vs. de novo diversity

Microbial biofilms show high phenotypic and genetic diversity, yet the mechanisms underlying diversity generation and maintenance remain unclear. Here, we investigate how spatial patterns of growth activity within a biofilm lead to spatial patterns of genetic diversity. Using individual-based computer simulations, we show that the active layer of growing cells at the biofilm interface controls the distribution of lineages within the biofilm, and therefore the patterns of standing and de novo diversity. Comparing biofilms of equal size, those with a thick active layer retain more standing diversity, while de novo diversity is more evenly distributed within the biofilm. In contrast, equal-sized biofilms with a thin active layer retain less standing diversity, and their de novo diversity is concentrated at the top of the biofilm, and in fewer lineages. In the context of antimicrobial resistance, biofilms with a thin active layer may be more prone to generate lineages with multiple resistance mutations, and to seed new resistant biofilms via sloughing of resistant cells from the upper layers. Our study reveals fundamental "baseline" mechanisms underlying the patterning of diversity within biofilms.

Laws of Spatially Structured Population Dynamics on a Lattice

We consider spatial population dynamics on a lattice, following a type of a contact (birth–death) stochastic process. We show that simple mathematical approximations for the density of cells can be obtained in a variety of scenarios. In the case of a homogeneous cell population, we derive the cellular density for a two-dimensional (2D) spatial lattice with an arbitrary number of neighbors, including the von Neumann, Moore, and hexagonal lattice.are not allowed in the abstract, please move them to the main text, please remember to check the order of references in the full text after revision. We then turn our attention to evolutionary dynamics, where mutant cells of different properties can be generated. For disadvantageous mutants, we derive an approximation for the equilibrium density representing the selection–mutation balance. For neutral and advantageous mutants, we show that simple scaling (power) laws for the numbers of mutants in expanding populations hold in 2D and 3D, under both flat (planar) and range population expansion. These models have relevance for studies in ecology and evolutionary biology, as well as biomedical applications including the dynamics of drug-resistant mutants in cancer and bacterial biofilms.

Rare and localized events stabilize microbial community composition and patterns of spatial self-organization in a fluctuating environment

Spatial self-organization is a hallmark of surface-associated microbial communities that is governed by local environmental conditions and further modified by interspecific interactions. Here, we hypothesize that spatial patterns of microbial cell-types can stabilize the composition of cross-feeding microbial communities under fluctuating environmental conditions. We tested this hypothesis by studying the growth and spatial self-organization of microbial co-cultures consisting of two metabolically interacting strains of the bacterium Pseudomonas stutzeri. We inoculated the co-cultures onto agar surfaces and allowed them to expand (i.e. range expansion) while fluctuating environmental conditions that alter the dependency between the two strains. We alternated between anoxic conditions that induce a mutualistic interaction and oxic conditions that induce a competitive interaction. We observed co-occurrence of both strains in rare and highly localized clusters (referred to as “spatial jackpot events”) that persist during environmental fluctuations. To resolve the underlying mechanisms for the emergence of spatial jackpot events, we used a mechanistic agent-based mathematical model that resolves growth and dispersal at the scale relevant to individual cells. While co-culture composition varied with the strength of the mutualistic interaction and across environmental fluctuations, the model provides insights into the formation of spatially resolved substrate landscapes with localized niches that support the co-occurrence of the two strains and secure co-culture function. This study highlights that in addition to spatial patterns that emerge in response to environmental fluctuations, localized spatial jackpot events ensure persistence of strains across dynamic conditions.

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. Here, we quantify the effect of both positive and negative selection in MA studies, demonstrating that selective effects can substantially bias the distribution of fitness effects (DFE) and mutation rates estimated from typical MA protocols in microbes. We then present a simple correction for this bias which applies to both beneficial and deleterious mutations, and can be used to correct the observed DFE in multiple environments. We use simulated MA experiments to illustrate the extent to which the MA-inferred DFE differs from the underlying true DFE, and demonstrate that the proposed correction accurately reconstructs the true DFE over a wide range of scenarios; we also provide an example of these corrections applied to experimental data. These results highlight that positive selection during microbial MA experiments is in fact not negligible, but can be corrected to gain a more accurate understanding of fundamental evolutionary parameters. This article is protected by copyright. All rights reserved.

Hydrodynamic flow and concentration gradients in the gut enhance neutral bacterial diversity

The gut microbiota features important genetic diversity, and the specific spatial features of the gut may shape evolution within this environment. We investigate the fixation probability of neutral bacterial mutants within a minimal model of the gut that includes hydrodynamic flow and resulting gradients of food and bacterial concentrations. We find that this fixation probability is substantially increased, compared with an equivalent well-mixed system, in the regime where the profiles of food and bacterial concentration are strongly spatially dependent. Fixation probability then becomes independent of total population size. We show that our results can be rationalized by introducing an active population, which consists of those bacteria that are actively consuming food and dividing. The active population size yields an effective population size for neutral mutant fixation probability in the gut.

Spatial segregation and cooperation in radially expanding microbial colonies under antibiotic stress

Antibiotic resistance in microbial communities reflects a combination of processes operating at different scales. In this work, we investigate the spatiotemporal dynamics of bacterial colonies comprised of drug-resistant and drug-sensitive cells undergoing range expansion under antibiotic stress. Using the opportunistic pathogen Enterococcus faecalis with plasmid-encoded β-lactamase, we track colony expansion dynamics and visualize spatial patterns in fluorescently labeled populations exposed to antibiotics. We find that the radial expansion rate of mixed communities is approximately constant over a wide range of drug concentrations and initial population compositions. Imaging of the final populations shows that resistance to ampicillin is cooperative, with sensitive cells surviving in the presence of resistant cells at otherwise lethal concentrations. The populations exhibit a diverse range of spatial segregation patterns that depend on drug concentration and initial conditions. Mathematical models indicate that the observed dynamics are consistent with global cooperation, despite the fact that β-lactamase remains cell-associated. Experiments confirm that resistant colonies provide a protective effect to sensitive cells on length scales multiple times the size of a single colony, and populations seeded with (on average) no more than a single resistant cell can produce mixed communities in the presence of the drug. While biophysical models of drug degradation suggest that individual resistant cells offer only short-range protection to neighboring cells, we show that long-range protection may arise from synergistic effects of multiple resistant cells, providing surprisingly large protection zones even at small population fractions.

Causes and consequences of pattern diversification in a spatially self-organizing microbial community

Surface-attached microbial communities constitute a vast amount of life on our planet. They contribute to all major biogeochemical cycles, provide essential services to our society and environment, and have important effects on human health and disease. They typically consist of different interacting genotypes that arrange themselves non-randomly across space (referred to hereafter as spatial self-organization). While spatial self-organization is important for the functioning, ecology, and evolution of these communities, the underlying determinants of spatial self-organization remain unclear. Here, we performed a combination of experiments, statistical modeling, and mathematical simulations with a synthetic cross-feeding microbial community consisting of two isogenic strains. We found that two different patterns of spatial self-organization emerged at the same length and time scales, thus demonstrating pattern diversification. This pattern diversification was not caused by initial environmental heterogeneity or by genetic heterogeneity within populations. Instead, it was caused by nongenetic heterogeneity within populations, and we provide evidence that the source of this nongenetic heterogeneity is local differences in the initial spatial positionings of individuals. We further demonstrate that the different patterns exhibit different community-level properties; namely, they have different expansion speeds. Together, our results demonstrate that pattern diversification can emerge in the absence of initial environmental heterogeneity or genetic heterogeneity within populations and can affect community-level properties, thus providing novel insights into the causes and consequences of microbial spatial self-organization.

Geometrically regulating evolutionary dynamics in biofilms

The theoretical understanding of evolutionary dynamics in spatially structured populations often relies on nonspatial models. Biofilms are among such populations where a more accurate understanding is of theoretical interest and can reveal new solutions to existing challenges. Here, we studied how the geometry of the environment affects the evolutionary dynamics of expanding populations, using the Eden model. Our results show that fluctuations of subpopulations during range expansion in two- and three-dimensional environments are not Brownian. Furthermore, we found that the substrate's geometry interferes with the evolutionary dynamics of populations that grow upon it. Inspired by these findings, we propose a periodically wedged pattern on surfaces prone to develop biofilms. On such patterned surfaces, natural selection becomes less effective and beneficial mutants would have a harder time establishing. Additionally, this modification accelerates genetic drift and leads to less diverse biofilms. Both interventions are highly desired for biofilms.

The Consequences of Budding versus Binary Fission on Adaptation and Aging in Primitive Multicellularity

Early multicellular organisms must gain adaptations to outcompete their unicellular ancestors, as well as other multicellular lineages. The tempo and mode of multicellular adaptation is influenced by many factors including the traits of individual cells. We consider how a fundamental aspect of cells, whether they reproduce via binary fission or budding, can affect the rate of adaptation in primitive multicellularity. We use mathematical models to study the spread of beneficial, growth rate mutations in unicellular populations and populations of multicellular filaments reproducing via binary fission or budding. Comparing populations once they reach carrying capacity, we find that the spread of mutations in multicellular budding populations is qualitatively distinct from the other populations and in general slower. Since budding and binary fission distribute age-accumulated damage differently, we consider the effects of cellular senescence. When growth rate decreases with cell age, we find that beneficial mutations can spread significantly faster in a multicellular budding population than its corresponding unicellular population or a population reproducing via binary fission. Our results demonstrate that basic aspects of the cell cycle can give rise to different rates of adaptation in multicellular organisms.

Mutability of demographic noise in microbial range expansions

Demographic noise, the change in the composition of a population due to random birth and death events, is an important driving force in evolution because it reduces the efficacy of natural selection. Demographic noise is typically thought to be set by the population size and the environment, but recent experiments with microbial range expansions have revealed substantial strain-level differences in demographic noise under the same growth conditions. Many genetic and phenotypic differences exist between strains; to what extent do single mutations change the strength of demographic noise? To investigate this question, we developed a high-throughput method for measuring demographic noise in colonies without the need for genetic manipulation. By applying this method to 191 randomly-selected single gene deletion strains from the E. coli Keio collection, we find that a typical single gene deletion mutation decreases demographic noise by 8% (maximal decrease: 81%). We find that the strength of demographic noise is an emergent trait at the population level that can be predicted by colony-level traits but not cell-level traits. The observed differences in demographic noise from single gene deletions can increase the establishment probability of beneficial mutations by almost an order of magnitude (compared to in the wild type). Our results show that single mutations can substantially alter adaptation through their effects on demographic noise and suggest that demographic noise can be an evolvable trait of a population.

Theoretical modelling of competitive microbial range expansion with heterogeneous mechanical interactions

Microbial range expansion experiments provide insight into the complex link between dynamic structure, pattern formation and evolutionary dynamics of growing populations. In this work, we develop a theoretical model in order to investigate the interplay of growth statistics and mechanical interactions which are implemented as division driven pushing and swapping of cells. For the case of the competitive growth of a strongly and a weakly interacting strain we investigate the influence of different mean division times, as well as different mechanical interactions on the development of the colony. Our results show that the susceptibility to cell division induced pushing has a much stronger influence on the structure of the colony than cell sorting towards the colony's perimeter. Motivated by microbial range expansion experiments of Neisseria gonorrhoeae bacteria, we also consider the influence of mutating cells on the structure of the colony. We show that the outgrowth of the three different strains is strongly influenced by the relative strengths of their mechanical interaction. The experimentally observed patterns are reproduced for mechanical interactions of the mutants, which range between those of the strongly and weakly interacting strain.

Spatial organization in microbial range expansion emerges from trophic dependencies and successful lineages

Evidence suggests that bacterial community spatial organization affects their ecological function, yet details of the mechanisms that promote spatial patterns remain difficult to resolve experimentally. In contrast to bacterial communities in liquid cultures, surface-attached range expansion fosters genetic segregation of the growing population with preferential access to nutrients and reduced mechanical restrictions for cells at the expanding periphery. Here we elucidate how localized conditions in cross-feeding bacterial communities shape community spatial organization. We combine experiments with an individual based mathematical model to resolve how trophic dependencies affect localized growth rates and nucleate successful cell lineages. The model tracks individual cell lineages and attributes these with trophic dependencies that promote counterintuitive reproductive advantages and result in lasting influences on the community structure, and potentially, on its functioning. We examine persistence of lucky lineages in structured habitats where expansion is interrupted by physical obstacles to gain insights into patterns in porous domains.

Eco-evolutionary dynamics of range expansion

Understanding the movement of species' ranges is a classic ecological problem that takes on urgency in this era of global change. Historically treated as a purely ecological process, range expansion is now understood to involve eco-evolutionary feedbacks due to spatial genetic structure that emerges as populations spread. We synthesize empirical and theoretical work on the eco-evolutionary dynamics of range expansion, with emphasis on bridging directional, deterministic processes that favor evolved increases in dispersal and demographic traits with stochastic processes that lead to the random fixation of alleles and traits. We develop a framework for understanding the joint influence of these processes in changing the mean and variance of expansion speed and its underlying traits. Our synthesis of recent laboratory experiments supports the consistent role of evolution in accelerating expansion speed on average, and highlights unexpected diversity in how evolution can influence variability in speed: results not well predicted by current theory. We discuss and evaluate support for three classes of modifiers of eco-evolutionary range dynamics (landscape context, trait genetics, and biotic interactions), identify emerging themes, and suggest new directions for future work in a field that stands to increase in relevance as populations move in response to global change.

Mutant Evolution in Spatially Structured and Fragmented Expanding Populations

Mutant evolution in spatially structured systems is important for a range of biological systems, but aspects of it still require further elucidation. Adding to previous work, we provide a simple derivation of growth laws that characterize the number of mutants of different relative fitness in expanding populations in spatial models of different dimensionalities. These laws are universal and independent of "microscopic" modeling details. We further study the accumulation of mutants and find that, with advantageous and neutral mutants, more of them are present in spatially structured, compared to well-mixed colonies of the same size. The behavior of disadvantageous mutants is subtle: if they are disadvantageous through a reduction in division rates, the result is the same, and it is the opposite if the disadvantage is due to a death rate increase. Finally, we show that in all cases, the same results are observed in fragmented, nonspatial patch models. This suggests that the patterns observed are the consequence of population fragmentation, and not spatial restrictions per se We provide an intuitive explanation for the complex dependence of disadvantageous mutant evolution on spatial restriction, which relies on desynchronized dynamics in different locations/patches, and plays out differently depending on whether the disadvantage is due to a lower division rate or a higher death rate. Implications for specific biological systems, such as the evolution of drug-resistant cell mutants in cancer or bacterial biofilms, are discussed.

Radial Expansion Facilitates the Maintenance of Double Antibiotic Resistances

Most microbes live in spatially confined subpopulations. Under spatial structure conditions, the efficacy of natural selection is often reduced (relative to homogeneous conditions) due to the increased importance of genetic drift and local competition. Additionally, under spatial structure conditions, the fittest genotype may not always be the one with better access to the heterogeneous distribution of nutrients. The effect of radial expansion may be particularly relevant for the elimination of antibiotic resistance mutations, as their dynamics within bacterial populations are strongly dependent on their growth rate. Here, we use Escherichia coli to systematically compare the allele frequency of streptomycin, rifampin, and fluoroquinolone single and double resistance mutants after 24 h of coexistence with a susceptible strain under radial expansion (local competition) and homogeneous (global competition) conditions. We show that there is a significant effect of structure on the maintenance of double resistances which is not observed for single resistances. Radial expansion also facilitates the persistence of double resistances when competing against their single counterparts. Importantly, we found that spatial structure reduces the rate of compensation of the double mutant RpsL^K43T RpoB^H526Y and that a strongly compensatory mutation in homogeneous conditions becomes deleterious under spatial structure conditions. Overall, our results unravel the importance of spatial structure for facilitating the maintenance and accumulation of multiple resistances over time and for determining the identity of compensatory mutations.

The spatial Muller's ratchet: Surfing of deleterious mutations during range expansion

During a range expansion, deleterious mutations can "surf" on the colonization front. The resultant decrease in fitness is known as expansion load. An Allee effect is known to reduce the loss of genetic diversity of expanding populations, by changing the nature of the expansion from "pulled" to "pushed". We study the impact of an Allee effect on the formation of an expansion load with a new model, in which individuals have the genetic structure of a Muller's ratchet. A key feature of Muller's ratchet is that the population fatally accumulates deleterious mutations due to the stochastic loss of the fittest individuals, an event called a click of the ratchet. We observe fast clicks of the ratchet at the colonization front owing to small population size, followed by a slow fitness recovery due to migration of fit individuals from the bulk of the population, leading to a transient expansion load. For large population size, we are able to derive quantitative features of the expansion wave, such as the wave speed and the frequency of individuals carrying a given number of mutations. Using simulations, we show that the presence of an Allee effect reduces the rate at which clicks occur at the front, and thus reduces the expansion load.

The genetics of evolutionary radiations

With the realization that much of the biological diversity on Earth has been generated by discrete evolutionary radiations, there has been a rapid increase in research into the biotic (key innovations) and abiotic (key environments) circumstances in which such radiations took place. Here we focus on the potential importance of population genetic structure and trait genetic architecture in explaining radiations. We propose a verbal model describing the stages of an evolutionary radiation: first invading a suitable adaptive zone and expanding both spatially and ecologically through this zone; secondly, diverging genetically into numerous distinct populations; and, finally, speciating. There are numerous examples of the first stage; the difficulty, however, is explaining how genetic diversification can take place from the establishment of a, presumably, genetically depauperate population in a new adaptive zone. We explore the potential roles of epigenetics and transposable elements (TEs), of neutral process such as genetic drift in combination with trait genetic architecture, of gene flow limitation through isolation by distance (IBD), isolation by ecology and isolation by colonization, the possible role of intra-specific competition, and that of admixture and hybridization in increasing the genetic diversity of the founding populations. We show that many of the predictions of this model are corroborated. Most radiations occur in complex adaptive zones, which facilitate the establishment of many small populations exposed to genetic drift and divergent selection. We also show that many radiations (especially those resulting from long-distance dispersal) were established by polyploid lineages, and that many radiating lineages have small genome sizes. However, there are several other predictions which are not (yet) possible to test: that epigenetics has played a role in radiations, that radiations occur more frequently in clades with small gene flow distances, or that the ancestors of radiations had large fundamental niches. At least some of these may be testable in the future as more genome and epigenome data become available. The implication of this model is that many radiations may be hard polytomies because the genetic divergence leading to speciation happens within a very short time, and that the divergence history may be further obscured by hybridization. Furthermore, it suggests that only lineages with the appropriate genetic architecture will be able to radiate, and that such a radiation will happen in a meta-population environment. Understanding the genetic architecture of a lineage may be an essential part of accounting for why some lineages radiate, and some do not.

Interaction-dependent effects of surface structure on microbial spatial self-organization

Surface-attached microbial communities consist of different cell types that, at least to some degree, organize themselves non-randomly across space (referred to as spatial self-organization). While spatial self-organization can have important effects on the functioning, ecology and evolution of communities, the underlying determinants of spatial self-organization remain unclear. Here, we hypothesize that the presence of physical objects across a surface can have important effects on spatial self-organization. Using pairs of isogenic strains of Pseudomonas stutzeri, we performed range expansion experiments in the absence or presence of physical objects and quantified the effects on spatial self-organization. We demonstrate that physical objects create local deformities along the expansion frontier, and these deformities increase in magnitude during range expansion. The deformities affect the densities of interspecific boundaries and diversity along the expansion frontier, and thus affect spatial self-organization, but the effects are interaction-dependent. For competitive interactions that promote sectorized patterns of spatial self-organization, physical objects increase the density of interspecific boundaries and diversity. By contrast, for cross-feeding interactions that promote dendritic patterns, they decrease the density of interspecific boundaries and diversity. These qualitatively different outcomes are probably caused by fundamental differences in the orientations of the interspecific boundaries. Thus, in order to predict the effects of physical objects on spatial self-organization, information is needed regarding the interactions present within a community and the general geometric shapes of spatial self-organization that emerge from those interactions. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Population Genomics of an Anadromous Hilsa Shad Tenualosa ilisha Species across Its Diverse Migratory Habitats: Discrimination by Fine-Scale Local Adaptation

The migration of anadromous fish in heterogenic environments unceasingly imposes a selective pressure that results in genetic variation for local adaptation. However, discrimination of anadromous fish populations by fine-scale local adaptation is challenging because of their high rate of gene flow, highly connected divergent population, and large population size. Recent advances in next-generation sequencing (NGS) have expanded the prospects of defining the weakly structured population of anadromous fish. Therefore, we used NGS-based restriction site-associated DNA (NextRAD) techniques on 300 individuals of an anadromous Hilsa shad (Tenualosa ilisha) species, collected from nine strategic habitats, across their diverse migratory habitats, which include sea, estuary, and different freshwater rivers. The NextRAD technique successfully identified 15,453 single nucleotide polymorphism (SNP) loci. Outlier tests using the F_ST OutFLANK and pcadapt approaches identified 74 and 449 SNPs (49 SNPs being common), respectively, as putative adaptive loci under a divergent selection process. Our results, based on the different cluster analyses of these putatively adaptive loci, suggested that local adaptation has divided the Hilsa shad population into two genetically structured clusters, in which marine and estuarine collection sites were dominated by individuals of one genetic cluster and different riverine collection sites were dominated by individuals of another genetic cluster. The phylogenetic analysis revealed that all the riverine populations of Hilsa shad were further subdivided into the north-western riverine (turbid freshwater) and the north-eastern riverine (clear freshwater) ecotypes. Among all of the putatively adaptive loci, only 36 loci were observed to be in the coding region, and the encoded genes might be associated with important biological functions related to the local adaptation of Hilsa shad. In summary, our study provides both neutral and adaptive contexts for the observed genetic divergence of Hilsa shad and, consequently, resolves the previous inconclusive findings on their population genetic structure across their diverse migratory habitats. Moreover, the study has clearly demonstrated that NextRAD sequencing is an innovative approach to explore how dispersal and local adaptation can shape genetic divergence of non-model anadromous fish that intersect diverse migratory habitats during their life-history stages.

Evolution in range expansions with competition at rough boundaries

When a biological population expands into new territory, genetic drift develops an enormous influence on evolution at the propagating front. In such range expansion processes, fluctuations in allele frequencies occur through stochastic spatial wandering of both genetic lineages and the boundaries between genetically segregated sectors. Laboratory experiments on microbial range expansions have shown that this stochastic wandering, transverse to the front, is superdiffusive due to the front's growing roughness, implying much faster loss of genetic diversity than predicted by simple flat front diffusive models. We study the evolutionary consequences of this superdiffusive wandering using two complementary numerical models of range expansions: the stepping stone model, and a new interpretation of the model of directed paths in random media, in the context of a roughening population front. Through these approaches we compute statistics for the times since common ancestry for pairs of individuals with a given spatial separation at the front, and we explore how environmental heterogeneities can locally suppress these superdiffusive fluctuations.

Expansion history and environmental suitability shape effective population size in a plant invasion

The margins of an expanding range are predicted to be challenging environments for adaptation. Marginal populations should often experience low effective population sizes (N_e ) where genetic drift is high due to demographic expansion and/or census population size is low due to unfavourable environmental conditions. Nevertheless, invasive species demonstrate increasing evidence of rapid evolution and potential adaptation to novel environments encountered during colonization, calling into question whether significant reductions in N_e are realized during range expansions in nature. Here we report one of the first empirical tests of the joint effects of expansion dynamics and environment on effective population size variation during invasive range expansion. We estimate contemporary values of N_e using rates of linkage disequilibrium among genome-wide markers within introduced populations of the highly invasive plant Centaurea solstitialis (yellow starthistle) in North America (California, USA), and within native Eurasian populations. As predicted, we find that N_e within the invaded range is positively correlated with both expansion history (time since founding) and habitat quality (abiotic climate). History and climate had independent additive effects with similar effect sizes, indicating an important role for both factors in this invasion. These results support theoretical expectations for the population genetics of range expansion, though whether these processes can ultimately arrest the spread of an invasive species remains an unanswered question.

Genetic Population Structure and Allele Surfing During Range Expansion in Dynamic Habitats

Expanding populations may loss genetic diversity because sequential founder events throughout a wave of demographic expansion may cause "allele surfing", as the alleles of founder individuals may propagate rapidly through space. The spatial components of allele surfing have been studied by geneticists, but have never been investigate on dynamic and shifting habitats. Here we used an individual-based-model (IBM) to study how interactions between different habitat restoration scenarios and biological characteristics (dispersal capacity) affect the spatial patterns of the genetic structure of a population during demographic expansion. We found that both habitat dynamics and dispersal capacity, as well as their interaction, were the drivers of emergent pattern of genetic diversity and allele surfing. Specifically, allele surfing is more common when a species with low dispersal capacity colonizes a large geographic area with slow restoration (low carrying capacity). Despite this, we showed that allele surfing can be reduced, or even avoided, by dispersal management through suitable habitat restoration. Thus, investigating how colonization generates a spatial variation in genetic diversity, and which parameters control the emergent genetic pattern, are essential steps to planning assisted gene flow, which is fundamental for an effective planning of habitat restoration.

Environmental heterogeneity can tip the population genetics of range expansions

The population genetics of most range expansions is thought to be shaped by the competition between Darwinian selection and random genetic drift at the range margins. Here, we show that the evolutionary dynamics during range expansions is highly sensitive to additional fluctuations induced by environmental heterogeneities. Tracking mutant clones with a tunable fitness effect in bacterial colonies grown on randomly patterned surfaces we found that environmental heterogeneity can dramatically reduce the efficacy of selection. Time-lapse microscopy and computer simulations suggest that this effect arises generically from a local 'pinning' of the expansion front, whereby stretches of the front are slowed down on a length scale that depends on the structure of the environmental heterogeneity. This pinning focuses the range expansion into a small number of 'lucky' individuals with access to expansion paths, altering the neutral evolutionary dynamics and increasing the importance of chance relative to selection.

Emergence of evolutionary driving forces in pattern-forming microbial populations

Evolutionary dynamics are controlled by a number of driving forces, such as natural selection, random genetic drift and dispersal. In this perspective article, we aim to emphasize that these forces act at the population level, and that it is a challenge to understand how they emerge from the stochastic and deterministic behaviour of individual cells. Even the most basic steric interactions between neighbouring cells can couple evolutionary outcomes of otherwise unrelated individuals, thereby weakening natural selection and enhancing random genetic drift. Using microbial examples of varying degrees of complexity, we demonstrate how strongly cell-cell interactions influence evolutionary dynamics, especially in pattern-forming systems. As pattern formation itself is subject to evolution, we propose to study the feedback between pattern formation and evolutionary dynamics, which could be key to predicting and potentially steering evolutionary processes. Such an effort requires extending the systems biology approach from the cellular to the population scale.This article is part of the theme issue 'Self-organization in cell biology'.

Loss of genetic diversity, recovery and allele surfing in a colonizing parasite, Geomydoecus aurei

Understanding the genetic consequences of changes in species distributions has wide-ranging implications for predicting future outcomes of climate change, for protecting threatened or endangered populations and for understanding the history that has led to current genetic patterns within species. Herein, we examine the genetic consequences of range expansion over a 25-year period in a parasite (Geomydoecus aurei) that is in the process of expanding its geographic range via invasion of a novel host. By sampling the genetics of 1,935 G. aurei lice taken from 64 host individuals collected over this time period using 12 microsatellite markers, we test hypotheses concerning linear spatial expansion, genetic recovery time and allele surfing. We find evidence of decreasing allelic richness (AR) with increasing distance from the source population, supporting a linear, stepping stone model of spatial expansion that emphasizes the effects of repeated bottleneck events during colonization. We provide evidence of post-bottleneck genetic recovery, with average AR of infrapopulations increasing about 30% over the 225-generation span of time observed directly in this study. Our estimates of recovery rate suggest, however, that recovery has plateaued and that this population may not reach genetic diversity levels of the source population without further immigration from the source population. Finally, we employ a grid-based sampling scheme in the region of ongoing population expansion and provide empirical evidence for the power of allele surfing to impart genetic structure on a population, even under conditions of selective neutrality and in a place that lacks strong barriers to gene flow.

Bacterial growth: a statistical physicist's guide

Bacterial growth presents many beautiful phenomena that pose new theoretical challenges to statistical physicists, and are also amenable to laboratory experimentation. This review provides some of the essential biological background, discusses recent applications of statistical physics in this field, and highlights the potential for future research.

Collective motion conceals fitness differences in crowded cellular populations

Many cellular populations are tightly-packed, such as microbial colonies and biofilms, or tissues and tumors in multicellular organisms. Movement of one cell in those crowded assemblages requires motion of others, so that cell displacements are correlated over many cell diameters. Whenever movement is important for survival or growth, these correlated rearrangements could couple the evolutionary fate of different lineages. Yet, little is known about the interplay between mechanical forces and evolution in dense cellular populations. Here, by tracking slower-growing clones at the expanding edge of yeast colonies, we show that the collective motion of cells prevents costly mutations from being weeded out rapidly. Joint pushing by neighboring cells generates correlated movements that suppress the differential displacements required for selection to act. This mechanical screening of fitness differences allows slower-growing mutants to leave more descendants than expected under non-mechanical models, thereby increasing their chance for evolutionary rescue. Our work suggests that, in crowded populations, cells cooperate with surrounding neighbors through inevitable mechanical interactions. This effect has to be considered when predicting evolutionary outcomes, such as the emergence of drug resistance or cancer evolution.

High genomic diversity and candidate genes under selection associated with range expansion in eastern coyote (Canis latrans) populations

Range expansion is a widespread biological process, with well-described theoretical expectations associated with the colonization of novel ranges. However, comparatively few empirical studies address the genomic outcomes accompanying the genome-wide consequences associated with the range expansion process, particularly in recent or ongoing expansions. Here, we assess two recent and distinct eastward expansion fronts of a highly mobile carnivore, the coyote (Canis latrans), to investigate patterns of genomic diversity and identify variants that may have been under selection during range expansion. Using a restriction-associated DNA sequencing (RADseq), we genotyped 394 coyotes at 22,935 SNPs and found that overall population structure corresponded to their 19th century historical range and two distinct populations that expanded during the 20th century. Counter to theoretical expectations for populations to bottleneck during range expansions, we observed minimal evidence for decreased genomic diversity across coyotes sampled along either expansion front, which is likely due to hybridization with other Canis species. Furthermore, we identified 12 SNPs, located either within genes or putative regulatory regions, that were consistently associated with range expansion. Of these 12 genes, three (CACNA1C, ALK, and EPHA6) have putative functions related to dispersal, including habituation to novel environments and spatial learning, consistent with the expectations for traits under selection during range expansion. Although coyote colonization of eastern North America is well-publicized, this study provides novel insights by identifying genes associated with dispersal capabilities in coyotes on the two eastern expansion fronts.

Clonality and non-linearity drive facultative-cooperation allele diversity

Kin discrimination describes the differential interaction of organisms with kin versus non-kin. In microorganisms, many genetic loci act as effective kin-discrimination systems, such as kin-directed help and non-kin-directed harm. Another important example is facultative cooperation, where cooperators increase their investment in group-directed cooperation with the abundance of their kin in the group. Many of these kin-discrimination loci are highly diversified, yet it remains unclear what evolutionary mechanisms maintain this diversity, and how it is affected by population structure. Here, we demonstrate the unique dependence of kin-discriminative interactions on population structure, and how this could explain facultative-cooperation allele-diversity. We show mathematically that low relatedness between microbes in non-clonal social groups is needed to maintain the diversity of facultative-cooperation alleles, while high clonality is needed to stabilize this diversity against cheating. Interestingly, we demonstrate with simulations that such population structure occurs naturally in expanding microbial colonies. Finally, analysis of experimental data of quorum-sensing mediated facultative cooperation, in Bacillus subtilis, demonstrates the relevance of our results to realistic microbial interactions, due to their intrinsic non-linear frequency dependence. Our analysis therefore stresses the impact of clonality on the interplay between exploitation and kin discrimination and portrays a way for the evolution of facultative cooperation.

Locality of interactions in three-strain bacterial competition in E. coli

The population dynamics that determine the composition and stability of ecosystems ultimately emerge from interactions between individual organisms. One well-studied system is the three-strain E. coli interaction of a heterogeneously toxin-producing C strain that interacts with a toxin-sensitive S and a toxin-resistant R strain. Here, we employ a multi-scale fluorescence microscopy approach, that has been proven useful in identifying previously unknown or underestimated stochastic effects in C-S competition. This approach allows us to investigate the microscopic interaction of the R strain and to quantify the role of stochastic effects in the spatially structured C-R-S interaction. We show that the early colony patterning at 12 h and at small length scales (near single cell level) is characterized by a number of microscopic variables (the number of C and R cell clusters and the area occupied by S) and is subject to random processes in positioning and toxin production. Then, in a second competition phase, mainly deterministic processes such as bacterial growth and global toxin action determine the following population dynamics. Consequently, together with environmental factors, the microscopic variables were predictive of the competition outcome. However, interactions of neighboring R and C clusters could amplify local variations. If R clusters originated near a C cell cluster, R could profit from the toxin produced by C without bearing the cost of production-a mechanism called cheating. By combining information from the micro- and macro-scale dynamics, we can estimate the distance at which the cheating interaction significantly changes to be in the order of 250 µm. In summary, after an initial phase influenced by stochastic patterning, largely deterministic growth dynamics follow, which are additionally affected by local interactions of neighboring clusters. As such, the results underline the importance of stochasticity and local effects in the context of ecological interactions.

Antagonistic pleiotropy for carbon use is rare in new mutations

Pleiotropic effects of mutations underlie diverse biological phenomena such as ageing and specialization. In particular, antagonistic pleiotropy ("AP": when a mutation has opposite fitness effects in different environments) generates tradeoffs, which may constrain adaptation. Models of adaptation typically assume that AP is common - especially among large-effect mutations - and that pleiotropic effect sizes are positively correlated. Empirical tests of these assumptions have focused on de novo beneficial mutations arising under strong selection. However, most mutations are actually deleterious or neutral, and may contribute to standing genetic variation that can subsequently drive adaptation. We quantified the incidence, nature, and effect size of pleiotropy for carbon utilization across 80 single mutations in Escherichia coli that arose under mutation accumulation (i.e., weak selection). Although ∼46% of the mutations were pleiotropic, only 11% showed AP; among beneficial mutations, only ∼4% showed AP. In some environments, AP was more common in large-effect mutations; and AP effect sizes across environments were often negatively correlated. Thus, AP for carbon use is generally rare (especially among beneficial mutations); is not consistently enriched in large-effect mutations; and often involves weakly deleterious antagonistic effects. Our unbiased quantification of mutational effects therefore suggests that antagonistic pleiotropy may be unlikely to cause maladaptive tradeoffs.

Effective models and the search for quantitative principles in microbial evolution

Microbes evolve rapidly. Yet they do so in idiosyncratic ways, which depend on the specific mutations that are beneficial or deleterious in a given situation. At the same time, some population-level patterns of adaptation are strikingly similar across different microbial systems, suggesting that there may also be simple, quantitative principles that unite these diverse scenarios. We review the search for simple principles in microbial evolution, ranging from the biophysical level to emergent evolutionary dynamics. A key theme has been the use of effective models, which coarse-grain over molecular and cellular details to obtain a simpler description in terms of a few effective parameters. Collectively, these theoretical approaches provide a set of quantitative principles that facilitate understanding, prediction, and potentially control of evolutionary phenomena, though formidable challenges remain due to the ecological complexity of natural populations.

Inferring selection in instances of long-range colonization: The Aleppo pine (Pinus halepensis) in the Mediterranean Basin

Teasing apart the effects of natural selection and demography on current allele frequencies is challenging, due to both processes leaving a similar molecular footprint. In particular, when attempting to identify selection in species that have undergone a recent range expansion, the increase in genetic drift at the edges of range expansions ("allele surfing") can be a confounding factor. To address this potential issue, we first assess the long-range colonization history of the Aleppo pine across the Mediterranean Basin, using molecular markers. We then look for single nucleotide polymorphisms (SNPs) involved in local adaptation using: (a) environmental correlation methods (bayenv2), focusing on bioclimatic variables important for the species' adaptation (i.e., temperature, precipitation and water availability); and (b) FST -related methods (pcadapt). To assess the rate of false positives caused by the allele surfing effect, these results are compared with results from simulated SNP data that mimics the species' past range expansions and the effect of genetic drift, but with no selection. We find that the Aleppo pine shows a previously unsuspected complex genetic structure across its range, as well as evidence of selection acting on SNPs involved with the response to bioclimatic variables such as drought. This study uses an original approach to disentangle the confounding effects of drift and selection in range margin populations. It also contributes to the increased evidence that plant populations are able to adapt to new environments despite the expected accumulation of deleterious mutations that takes place during long-range colonizations.