Biology subjects

Hallatschek, O.

Publications and source records attributed to Hallatschek, O..

At least 19 recordsLinked to original sources

bioRxiv2026

Inferring Migration Networks with Time-Lagged F2 Statistics

Major demographic events, such as population bottlenecks, founder effects, range expansions, and admixture events, have left lasting imprints on human genetic diversity. Ancient DNA (aDNA) sequencing now makes it increasingly possible to observe these signals across time, opening new avenues to address long-standing questions in human demographic history. Yet, deciphering this genetic archive of demographic history is challenging due to high levels of noise, and the complex ways in which demographic processes shape genetic variation. Here, leveraging the linear time evolution of the expectation of neutral allele frequencies, we develop a method to uncover systematic patterns of gene flow from metapopulation time-series data. We show that directional migration rates can be inferred via linear regression on time-dependent genetic dissimilarity between populations, quantified by an extended F2 statistic evaluated between successive time points. Despite small sample sizes, the method reliably infers migration rates from simulated data by integrating information across multiple time slices. Applied to aDNA sampled from the last 6000 years, we recover signals of well-documented migrations and infer an ancient pan-European migration network. While complementing existing tools that estimate static ancestry proportions, our framework tracks how ancestry is dynamically redistributed through time.

evolutionary biology↗

bioRxiv2026

The evolution of genetic drift over 50,000 generations

Random variation in reproductive success-genetic drift-profoundly shapes genetic diversity and evolutionary trajectories. The strength of drift depends on the variance in descendant number, [Formula], which governs key evolutionary outcomes: for instance, the establishment probability of a beneficial mutation scales inversely with [Formula]. However, whether [Formula] itself evolves over long timescales has remained unclear, because allele-frequency fluctuations depend on drift only through the effective population size, [Formula], which blends census population size with descendant-number variance. Here, we disentangle these components by using model-based Bayesian inference combined with joint tracking of (i) frequency fluctuations of neutrally barcoded lineages and (ii) census population sizes across growth cycles in theE. coliLong-Term Evolution Experiment (LTEE). Analyzing 33 clones spanning the ancestor through 50,000 generations in two replicate populations (Ara-2 and Ara+2), we find that the strength of genetic drift evolved markedly-and divergently-between the two replicate populations. Both census size and [Formula] changed substantially through time, with most variation in Ne driven by shifts in [Formula] rather than census size. After approximately 2,000 generations, the [Formula] of the two populations diverged sharply: Ara+2 generally remained close to a bottleneck-only null expectation, whereas Ara-2 exhibited 1.5-5x stronger drift, consistent with an evolved increase in stochasticity during growth. These results imply that mutations can alter both the mean and the variance of the descendant-number distribution, and we show that the joint distribution of mutational effects on fitness and on [Formula] can substantially modulate the rate of adaptation. The key parameter governing genetic drift can therefore itself evolve in the LTEE, with direct consequences for adaptation.

evolutionary biology↗

bioRxiv2025

Frequency-dependent fitness effects are ubiquitous

In simple microbial populations, the fitness effects of selected mutations are typically assumed to be constant, regardless of mutant frequency. This assumption underpins predictions about evolutionary dynamics, epistasis, and the maintenance of genetic diversity. Here, we systematically test this assumption using beneficial mutations from early generations of the Escherichia coli Long-Term Evolution Experiment (LTEE). Using flow cytometry-based competition assays, we find that frequency-dependent fitness effects are the norm rather than the exception, occurring in approximately 80% of strain pairs tested. Most competitions exhibit negative frequency-dependence, where fitness advantages decline as mutant frequency increases. We demonstrate that the strength of frequency-dependence is predictable from invasion fitness measurements, which explain approximately half of the biological variation in frequency-dependent slopes. We also observe violations of fitness transitivity in several strain combinations, indicating that competitive outcomes cannot always be predicted from fitness measured against a single reference strain. High-resolution measurements reveal that frequency-dependence changes substantially within the growth cycle, with the net per-cycle effect reflecting the balance of opposing dynamics at different growth phases. Our results demonstrate that even in a model system designed to minimize ecological complexity, subtle interactions between closely related genotypes create frequency-dependent selection that can fundamentally alter evolutionary trajectories.

evolutionary biology↗

bioRxiv2025

Barrier-Free Microhabitats: Self-Organized Seclusion in Microbial Communities

Bacteria frequently colonize natural microcavities such as gut crypts, plant apoplasts, and soil pores. Recent studies have shown that the physical structure of these spaces plays a crucial role in shaping the stability and resilience of microbial populations (1, 2). Here, we demonstrate that protected microhabitats can emerge dynamically, even in the absence of physical barriers. Interactions with surface features--such as roughness or friction--lead microbial populations to self-organize into effectively segregated subpopulations. Our numerical and analytical models reveal that this self-organization persists even when strains have different growth rates, allowing slower-growing strains to avoid competitive exclusion. These findings suggest that emergent spatial structuring can serve as a fundamental mechanism for maintaining microbial diversity, despite selection pressures, competition, and genetic drift.

biophysics↗

bioRxiv2024

Asynchronous abundance fluctuations can drive giant genotype frequency fluctuations

Large stochastic population abundance fluctuations are ubiquitous across the tree of life1-7, impacting the predictability of population dynamics and influencing eco-evolutionary outcomes. It has generally been thought that these large abundance fluctuations do not strongly impact evolution, as the relative frequencies of alleles in the population will be unaffected if the abundance of all alleles fluctuate in unison. However, we argue that large abundance fluctuations can lead to significant genotype frequency fluctuations if different genotypes within a population experience these fluctuations asynchronously. By serially diluting mixtures of two closely related E. coli strains, we show that such asynchrony can occur, leading to giant frequency fluctuations that far exceed expectations from models of genetic drift. We develop a flexible, effective model that explains the abundance fluctuations as arising from correlated offspring numbers between individuals, and the large frequency fluctuations result from even slight decoupling in offspring numbers between genotypes. This model accurately describes the observed abundance and frequency fluctuation scaling behaviors. Our findings suggest chaotic dynamics underpin these giant fluctuations, causing initially similar trajectories to diverge exponentially; subtle environmental changes can be magnified, leading to batch correlations in identical growth conditions. Furthermore, we present evidence that such decoupling noise is also present in mixed-genotype S. cerevisiae populations. We demonstrate that such decoupling noise can strongly influence evolutionary outcomes, in a manner distinct from genetic drift. Given the generic nature of asynchronous fluctuations, we anticipate that they are widespread in biological populations, significantly affecting evolutionary and ecological dynamics.

evolutionary biology↗

bioRxiv2023

Rediversification Following Ecotype Isolation Reveals Hidden Adaptive Potential

Microbial communities play a critical role in ecological processes, and their diversity is key to their functioning. However, little is known about if communities can regenerate ecological diversity following species removal or extinction, and how the rediversified communities would compare to the original ones. Here we show that simple two-ecotype communities from the E. coli Long Term Evolution Experiment (LTEE) consistently rediversified into two ecotypes following the isolation of one of the ecotypes, coexisting via negative frequency-dependent selection. Communities separated by more than 30,000 generations of evolutionary time rediversify in similar ways. The rediversified ecotype appears to share a number of growth traits with the ecotype it replaces. However, the rediversified community is also different compared to the original community in ways relevant to the mechanism of ecotype coexistence, for example in stationary phase response and survival. We found substantial variation in the transcriptional states between the two original ecotypes, whereas the differences within the rediversified community were comparatively smaller, but with unique patterns of differential expression. Our results suggest that evolution may leave room for alternative diversification processes even in a maximally reduced community of only two strains. We hypothesize that the presence of alternative evolutionary pathways may be even more pronounced in communities of many species, highlighting an important role for perturbations, such as species removal, in evolving ecological communities.

evolutionary biology↗

bioRxiv2023

Tipping points emerge from weak mutualism inmetacommunities

The coexistence of obligate mutualists is often precariously close to tipping points where small environmental changes can drive catastrophic shifts in species composition. For example, microbial ecosystems can collapse by the decline of a strain that provides an essential resource on which other strains cross-feed. Here, we show that tipping points, ecosystem collapse, bistability and hysteresis arise even with very weak (non-obligate) mutualism provided the population is spatially structured. Based on numeric solutions of a metacommunity model and mean-field analyses, we demonstrate that weak mutualism lowers the minimal dispersal rate necessary to avoid stochastic extinction, while species need to overcome a mean threshold density to survive in this low dispersal rate regime. Moreover, we show that, starting with a randomly interacting species pool, metapopulation structure tends to select for an ecosystem with mutualistic interactions. Bistable metacommunities could, therefore, be a natural outcome of evolutionary dynamics in structured ecosystems.

ecology↗

bioRxiv2022

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we dont yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift will be informative for parameterizing evolutionary models and studying potential mechanisms for increased drift. Author SummaryThe transmission of pathogens like SARS-CoV-2 is strongly affected by chance effects in the contact process between infected and susceptible individuals, collectively referred to as random genetic drift. We have an incomplete understanding of how genetic drift changes across time and locations. To address this gap, we developed a computational method that infers the strength of genetic drift from time series genomic data that corrects for non-biological noise and is computationally scalable to the large numbers of sequences available for SARS-CoV-2, overcoming a major challenge of existing methods. Using this method, we quantified the strength of genetic drift for SARS-CoV-2 transmission in England throughout time and across locations. These estimates constrain potential mechanisms and help parameterize models of SARS-CoV-2 evolution. More generally, the computational scalability of our method will become more important as increasingly large genomic datasets become more common.

evolutionary biology↗

bioRxiv2022

Evolutionary rescue is promoted in compact cellular populations

Mutation-mediated drug resistance is one of the primary causes for the failure of modern antibiotic or chemotherapeutic treatment. Yet, in the absence of treatment many drug resistance mutations are associated with a fitness cost and therefore subject to purifying selection. While, in principle, resistant subclones can escape purifying selection via subsequent compensatory mutations, current models predict such evolutionary rescue events to be exceedingly unlikely. Here, we show that the probability of evolutionary rescue, and the resulting long-term persistence of drug resistant subclones, is dramatically increased in dense microbial populations via an inflation-selection balance that stabilizes the less-fit intermediate state. Tracking the entire evolutionary trajectory of fluorescence-augmented "synthetic mutations" in expanding yeast colonies, we trace the origin of this balance to the opposing forces of radial population growth and a clone-width-dependent weakening of selection pressures, inherent to crowded populations. Additionally conducting agent-based simulations of tumor growth, we 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 the evolutionary dynamics of any sufficiently dense cellular populations, including pathogenic microbial biofilms and solid tumors, and their response to therapeutic interventions. Our experimental approach could be extended to systematically study rates of specific evolutionary trajectories, giving quantitative access to the evolution of complex adaptations.

biophysics↗

bioRxiv2022

Quantifying the Adaptive Potential of a Nascent Bacterial Community

The fitness effects of all possible mutations available to an organism largely shapes the dynamics of evolutionary adaptation. Tremendous progress has been made in quantifying the strength and abundance of selected mutations available to single microbial species in simple environments, lacking strong ecological interactions. However, the adaptive potential of strains that are part of multi-strain communities remains largely unclear. We sought to fill this gap by analyzing a stable community of two closely related ecotypes ("L" and "S") shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We found that the fitness effects of many gene knockouts sensitively depends on the genetic background and the ecological conditions, as set by the abiotic environment and relative frequency of both ecotypes. Despite the idiosyncratic behavior of individual knockouts, we still see consistent statistical patterns of fitness effect variation across both genetic background and community composition. Genes that are in the same operon, or that strongly interact with each other, are more likely to be correlated with each other across backgrounds compared to random pairs of genes. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to drive adaptive potential in a nascent ecological community.

evolutionary biology↗

bioRxiv2021

Self-consistent migration puts tight constraintson the spatio-temporal organization ofspecies-rich metacommunities

Biodiversity is often attributed to a dynamic equilibrium between immigration of species and competition-driven extinction. This equilibrium forms a common basis for studying ecosystem assembly from a static reservoir of migrants-the mainland. Yet, natural ecosystems often consist of many coupled communities (i.e. metacommunities) and migration occurs between these communities. The pool of migrants then depends on what is sustained in the ecosystem, which in turn depends on the dynamic migrant pool. This chicken-and-egg problem of survival and migration is poorly understood in communities of many competing species, except for the neutral case - the "unified neutral theory of biodiversity". Employing spatio-temporal simulations and mean-field analyses, we show that self-consistent migration puts rather tight constraints on the dynamic migration-extinction equilibrium. When the number of species is large, even weak competitions push species to the edge of their global extinction, such that the overall diversity is highly sensitive to perturbations in demographic parameters, including growth and dispersal rates. When migration is short-range, the resulting spatiotemporal abundance patterns follow broad scale-free distributions that correspond to a directed percolation phase transition. The qualitative agreement of our results for short-range and long-range migration suggests that this self-organization process is a general property of species-rich metacommunities. Our study shows that self-sustaining metacommunities are highly sensitive to environmental change and provides insights into how biodiversity can be rescued and maintained.

biophysics↗

bioRxiv2021

Scale-dependent tipping points of bacterial colonization resistance

Bacteria are efficient colonizers of a wide range of secluded micro-habitats, such as soil pores, skin follicles, or intestinal crypts. How the structural diversity of these habitats modulates microbial self-organization remains poorly understood, in part because of the challenge to specifically manipulate the physical structure of microbial environments. Using a microfluidic device to grow bacteria in crypt-like incubation chambers of systematically varied lengths, we show that small variations in the physical structure of the micro-habitat can drastically alter bacterial colonization success and resistance against invaders. Small crypts are un-colonizable, intermediately sized crypts can stably support dilute populations, while beyond a second critical lengthscale, populations phase-separate into a dilute and a jammed region. The jammed state is characterized by extreme colonization resistance, even if the resident strain is suppressed by an antibiotic. Combined with a flexible biophysical model, we demonstrate that colonization resistance and associated priority effects can be explained by a crowding-induced phase transition, which results from a competition between proliferation and density-dependent cell leakage. The emerging sensitivity to scale underscores the need to control for scale in microbial ecology experiments. Systematic flow-adjustable lengthscale variations may serve as a promising strategy to elucidate further scale-sensitive tipping points and to rationally modulate the stability and resilience of microbial colonizers.

ecology↗

bioRxiv2021

Bacterial filamentation drives colony chirality

Chirality is ubiquitous in nature, with consequences at the cellular and tissue scales. As Escherichia coli colonies expand radially, an orthogonal component of growth creates a pinwheel-like pattern that can be revealed by fluorescent markers. To elucidate the mechanistic basis of this colony chirality, we investigated its link to left-handed, single-cell twisting during E. coli elongation. While chemical and genetic manipulation of cell width altered single-cell twisting handedness, colonies ceased to be chiral rather than switching handedness, and anaerobic growth altered colony chirality without affecting single-cell twisting. Chiral angle increased with increasing temperature even when growth rate decreased. Unifying these findings, we discovered that colony chirality was associated with the propensity for cell filamentation. Inhibition of cell division accentuated chirality under aerobic growth and generated chirality under anaerobic growth. Thus, regulation of cell division is intrinsically coupled to colony chirality, providing a mechanism for tuning macroscale spatial patterning.

microbiology↗

bioRxiv2021

Dynamic sampling bias and overdispersion induced by skewed offspring distributions

Natural populations often show enhanced genetic drift consistent with a strong skew in their offspring number distribution. The skew arises because the variability of family sizes is either inherently strong or amplified by population expansions, leading to so-called jackpot events. The resulting allele frequency fluctuations are large and, therefore, challenge standard models of population genetics, which assume sufficiently narrow offspring distributions. While the neutral dynamics backward in time can be readily analyzed using coalescent approaches, we still know little about the effect of broad offspring distributions on the dynamics forward in time, especially with selection. Here, we employ an exact asymptotic analysis combined with a scaling hypothesis to demonstrate that over-dispersed frequency trajectories emerge from the competition of conventional forces, such as selection or mutations, with an emerging time-dependent sampling bias against the minor allele. The sampling bias arises from the characteristic time-dependence of the largest sampled family size within each allelic type. Using this insight, we establish simple scaling relations for allele frequency fluctuations, fixation probabilities, extinction times, and the site frequency spectra that arise when offspring numbers are distributed according to a power law n-(1+). To demonstrate that this coarse-grained model captures a wide variety of non-equilibrium dynamics, we validate our results in traveling waves, where the phenomenon of gene surfing can produce any exponent 1 < < 2. We argue that the concept of a dynamic sampling bias is useful generally to develop both intuition and statistical tests for the unusual dynamics of populations with skewed offspring distributions, which can confound commonly used tests for selection or demographic history.

evolutionary biology↗

bioRxiv2020

Genealogical structure changes as range expansions transition from pushed to pulled

Range expansions accelerate evolution through multiple mechanisms including gene surfing and genetic drift. The inference and control of these evolutionary processes ultimately relies on the information contained in genealogical trees. Currently, there are two opposing views on how range expansions shape genealogies. In invasion biology, expansions are typically approximated by a series of population bottlenecks producing genealogies with only pairwise mergers between lineages--a process known as the Kingman coalescent. Conversely, traveling-wave models predict a coalescent with multiple mergers, known as the Bolthausen-Sznitman coalescent. Here, we unify these two approaches and show that expansions can generate an entire spectrum of coalescent topologies. Specifically, we show that tree topology is controlled by growth dynamics at the front and exhibits large differences between pulled and pushed expansions. These differences are explained by the fluctuations in the total number of descendants left by the early founders. High growth cooperativity leads to a narrow distribution of reproductive values and the Kingman coalescent. Conversely, low growth cooperativity results in a broad distribution, whose exponent controls the merger sizes in the genealogies. These broad distribution and non-Kingman tree topologies emerge due to the fluctuations in the front shape and position and do not occur in quasi-deterministic simulations. Overall, our results show that range expansions provide a robust mechanism for generating different types of multiple mergers, which could be similar those observed in populations with strong selection or high fecundity. Thus, caution should be exercised in making inferences about the origin of non-Kingman genealogies. Significance statementSpatial dynamics are important for understanding genetic diversity in many contexts, such as cancer and infectious diseases. Coalescent theory offers a powerful framework for interpreting and predicting patters of genetic diversity in populations, but incorporating spatial structure into the theory has proven difficult. Here, we address this long-standing problem by studying the coalescent in a spatially expanding population. We find the topology of the coalescent changes depending on the growth dynamics at the front. Using analytical arguments, we show that the transition between coalescent topologies is universal and is controlled by a parameter related to the expansion velocity. Our theory makes precise predictions about the effects of population dynamics on genetic diversity at the expansion front, which we confirm in simulations.

evolutionary biology↗

bioRxiv2020

The 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 higher than 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 phenotype of a population.

evolutionary biology↗

bioRxiv2019

From sectors to speckles: The impact of long range migration on gene surfing

Range expansions lead to distinctive patterns of genetic variation in populations, even in the absence of selection. These patterns and their genetic consequences have been well-studied for populations advancing through successive short-ranged migration events. However, most populations harbor some degree of long-range dispersal, experiencing rare yet consequential migration events over arbitrarily long distances. Although dispersal is known to strongly affect spatial genetic structure during range expansions, the resulting patterns and their impact on neutral diversity remain poorly understood. Here, we systematically study the consequences of long-range dispersal on patterns of neutral variation during range expansion in a class of dispersal models which spans the extremes of local (effectively short-ranged) and global (effectively well-mixed) migration. We find that sufficiently long-ranged dispersal leaves behind a mosaic of monoallelic patches, whose number and size are highly sensitive to the distribution of dispersal distances. We develop a coarse-grained model which connects statistical features of these spatial patterns to the evolution of neutral diversity during the range expansion. We show that growth mechanisms that appear qualitatively similar can engender vastly different outcomes for diversity: depending on the tail of the dispersal distance distribution, diversity can either be preserved (i.e. many variants survive) or lost (i.e. one variant dominates) at long times. Our results highlight the impact of spatial and migratory structure on genetic variation during processes as varied as range expansions, species invasions, epidemics, and the spread of beneficial mutations in established populations.

evolutionary biology↗

bioRxiv2019

Impact of crowding on the diversity of expanding populations

Crowding effects are key to the self-organization of densely packed cellular assemblies, such as biofilms, solid tumors, and developing tissues. When cells grow and divide they push each other apart, remodeling the structure and extent of the populations range. It has recently been shown that crowding has a strong impact on the strength of natural selection. However, the impact of crowding on neutral processes remains unclear, which controls the fate of new variants as long as they are rare. Here, we quantify the genetic diversity of expanding microbial colonies and uncover signatures of crowding in the site frequency spectrum. By combining Luria-Delbruck fluctuation tests, lineage tracing in a novel microfluidic incubator, cell-based simulations, and theoretical modeling, we find that the majority of mutations arise behind the expanding frontier, giving rise to clones that are mechanically "pushed out" of the growing region by the proliferating cells in front. These excluded-volume interactions result in a clone size distribution that solely depends on where the mutation first arose relative to the front and is characterized by a simple power-law for low-frequency clones. Our model predicts that the distribution only depends on a single parameter, the characteristic growth layer thickness, and hence allows estimation of the mutation rate in a variety of crowded cellular populations. Combined with previous studies on high-frequency mutations, our finding provides a unified picture of the genetic diversity in expanding populations over the whole frequency range and suggests a practical method to assess growth dynamics by sequencing populations across spatial scales. Significance StatementGrowing cell populations become densely packed as cells proliferate and fill space. Crowding prevents spatial mixing of individuals, significantly altering the evolutionary outcome from established results for well-mixed populations. Despite the fundamental differences between spatial and well-mixed populations, little is known about the impact of crowding on genetic diversity. Looking at microbial colonies growing on plates, we show that the allele frequency spectrum is characterized by a simple power law for low frequencies. Using cell-based simulations and microfluidic experiments, we identify the origin of this distribution in the volume-exclusion interactions within the crowded cellular environment, enabling us to extend this findings to a broad range of densely packed populations. This study highlights the importance of cellular crowding for the emergence of rare genetic variants.

biophysics↗