Biology subjects

Wodarz, D.

Publications and source records attributed to Wodarz, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Microbiomes change the rules of host evolution

Microbiomes are pervasive determinants of host phenotype and fitness, yet their consequences for host population genetics remain poorly understood. Here we show that microbiome-associated population structure can fundamentally alter the evolutionary dynamics of host populations. We develop a general framework that maps hosts distributed among an arbitrary number of microbial states onto an effective population size, $N_{\mathrm{eff}}$, and effective selection coefficient, $s_{\mathrm{eff}}$, thereby reducing potentially high-dimensional host--microbiome dynamics to the quantities governing genetic drift and selection. Applying the framework to five empirically anchored host--microbe systems spanning ciliates, insects, and plants with bacterial, algal, and fungal associates reveals substantial departures from classical population-genetic predictions. Microbiome-associated structure can considerably alter both the effective strength of genetic drift and the strength of selection acting on host genetic variation, shifting populations into evolutionary regimes that differ markedly from those predicted from census size and intrinsic mutational effects alone. These changes can have profound consequences for evolutionary outcomes, including either suppression or enhancement of selection for both advantageous and disadvantageous mutations, sometimes reaching orders-of-magnitude differences. The effects are not determined simply by whether a microbial association is beneficial or detrimental, but by the ecological processes governing microbial acquisition, transmission, loss, and host demography. Our results provide a population-genetic extension of the holobiont perspective: when microbial associations generate distinct demographic states among hosts, they can alter the evolutionary forces acting on the host genome without requiring the host and microbiome to constitute a single hereditary unit.

evolutionary biology↗

bioRxiv2026

Hierarchical tissue structure creates history-dependent barriers to clonal invasion

Tissues of higher organisms are maintained by hierarchies of stem and progenitor cell compartments regulated by homeostatic feedback. Somatic mutations generate genetically distinct clones whose evolutionary success depends not only on their fitness but also on the tissue architecture in which they arise. In previous work, we showed that this hierarchical organization creates invasion barriers that prevent advantageous mutants originating in downstream compartments from expanding unless their fitness exceeds a critical threshold. Here, we extend this framework to populations containing multiple competing mutant clones. We derive a general invasion criterion showing that the threshold for mutant expansion is determined by the equilibrium established by the resident clones and therefore depends on the evolutionary history of the system. Established clones modify the invasion barriers encountered by subsequent mutants, making clonal evolution history-dependent. The theory predicts competitive exclusion between clones entering the same compartment and shows that resident clones can prevent the establishment of later mutants. Using a model previously parameterized for murine hematopoiesis, we showed that our framework provides a mechanistic explanation for mutation-order effects involving JAK2 V617F and TET2 mutations in myeloproliferative neoplasms. Our results identify invasion barriers as a principle governing history-dependent clonal evolution in hierarchical tissues.

evolutionary biology↗

bioRxiv2026

Superspreaders increase deleterious mutant burden and can accelerate the evolution of complex traits in pathogens

Degree heterogeneity in contact networks is known to accelerate the spread of infectious diseases through the presence of superspreaders, but its evolutionary consequences remain less understood. Here we study how network heterogeneity shapes the fate of competing pathogen strains in a stochastic susceptible-infected-susceptible framework. We show that heterogeneous networks act as strong suppressors of selection: both advantageous and disadvantageous mutants exhibit fixation probabilities close to neutral expectations, in stark contrast to well-mixed populations. We derive an analytical theory that captures this effect through a single suppression factor determined by network structure and infection dynamics, and validate it against simulations on synthetic and empirical contact networks. Mechanistically, suppression arises because most transmission events are effectively neutral, while selection acts only in rare configurations. As a consequence, heterogeneous networks substantially increase the persistence of deleterious mutants and elevate mutation-selection balance, but they can either accelerate or decelerate multi-step evolutionary processes such as fitness valley crossing. Our results reveal a fundamental trade-off induced by superspreaders: While they enhance epidemic spread, they weaken selective pressures and thereby promote evolutionary diversification.

evolutionary biology↗

bioRxiv2025

Cellular turnover can increase or decrease the mutant burden in expanding cell population

Expanding cell populations, including bacterial colonies and tumors, continuously accumulate mutations as they grow. Yet how mutant burden depends on the cellular death-to-birth ratio in spatially structured populations has not been addressed, despite clinical studies associating higher tumor turnover with both better and worse patient outcomes across cancers. This question is especially relevant for deleterious mutants, which can become advantageous if the environment changes, such as when treatment begins. Mutant accumulation has been studied extensively in well-mixed populations. Here, we derive a new closed-form approximation for the mean deleterious mutant burden at a specified population size when cell death is nonzero, serving as a baseline for comparisons to spatial structure. We show that spatial structure, a defining feature of solid tumors, can fundamentally alter how mutant burden depends on the death-to-birth ratio. Relationships that increase monotonically in well-mixed populations can become nonmonotonic or even decrease in spatially expanding populations, depending on population size and the fitness cost of mutants. These results provide a mechanistic framework for understanding why higher tumor turnover has been associated with either improved or worsened outcomes across patients and cancer types. An analysis of the probability that a colony regrows after an environmental change (such as treatment initiation) reveals a similar pattern: spatial structure can reverse or reshape this dependence. Overall, our findings establish spatial structure as a key determinant of how cellular death-to-birth ratios shape mutant accumulation, with implications for interpreting clinical data and predicting the burden of preexisting mutants during tumor evolution. Significance statementThe number of mutants present when a growing cell population reaches a given size shapes its capacity to adapt, since deleterious mutants can become advantageous once conditions change, such as when cancer treatment begins. Clinical studies report contradictory links between tumor cell turnover (death-to-birth ratio) and patient outcomes, with higher turnover linked to both better and worse prognosis. Building on established theory for well-mixed populations, we show that spatial population structure, a key feature of solid tumors, can make mutant burden increase, decrease, or vary non-monotonically with the death-to-birth ratio, depending on tumor size and mutant fitness cost, patterns absent in the well-mixed system. This resolves the contradiction and clarifies how tumor turnover shapes its potential to evolve and progress.

evolutionary biology↗

bioRxiv2025

Population structure reverses selection of variants with proportionally scaled birth and death rates

A frequently observed phenomenon across the kingdom of life is that a higher reproduction rate can be accompanied by higher mortality. During tumor progression, variants emerge that both reproduce and die faster; faster replicating viruses can be characterized by a faster decay rate; and more frequent pregnancy can be accompanied by a higher chance to die due to predation in ecological systems. Variants with proportionally scaled birth and death rates have been called quasi-neutral mutants. Although life-time reproductive success is not changed, such variants are characterized by fixation probabilities that are somewhat lower (higher) than expected for neutral mutants if birth and death rates are proportionally larger (smaller). Studies were performed in the context of well-mixed populations, and despite the deviation from neutrality, quasi-neutral mutants do not have characteristics of disadvantageous or advantageous mutants, as their fixation probabilities still scale with their initial fractions. Here, we report that in deme-or spatially structured populations, variants with proportionally increased (decreased) birth and death rates become truly disadvantageous (advantageous), and calculate their effective fitness. Furthermore, if mutants have a higher life-time reproductive output than the wild-types and are thus advantageous, a proportional increase of birth and death rates can render them strongly disadvantageous, and vice versa. This changes our understanding of how life-time reproductive success correlates with selection, and has implications for evolutionary dynamics across a range of biological systems.

evolutionary biology↗

bioRxiv2024

Mutant scaling laws reveal that accelerated mutant evolution via gene amplifications requires spatially structured population growth

Principles of evolution in spatially structured expanding populations have recently received much attention, but more work remains to be performed, especially for complex, multi-step evolutionary processes, where mutations are accumulated in an expanding population. A key limitation is that the simulation of spatially explicit stochastic computational models is essential, but not feasible for larger population sizes characteristic of prokaryotic and eukaryotic cell populations. We describe a methodological advance by deriving scaling laws that allow the straightforward prediction of the number of single-hit, double-hit and multi-hit mutants as a function of wild-type population size in spatially expanding populations. While this is a versatile tool to address a range of cutting-edge evolutionary questions, here we apply this methodology to reconcile apparently contradicting data from experimental evolution studies regarding the role of gene amplifications for the emergence of point mutations in bacteria. Applying the scaling laws, we demonstrate that in populations that expand in a 2D or a 3D spatial setting, gene amplifications can significantly promote mutant emergence, and that this is not possible in well-mixed populations. In support of the predictions, experiments that do show accelerated mutant evolution through gene amplifications grew bacteria in spatially restricted lawns, while those that failed to show an effect grew bacteria in non-spatial liquid media.

evolutionary biology↗

bioRxiv2024

Compartmental structure in the secondary lymphoid tissue can slow down in vivo HIV-1 evolution in the presence of strong CTL responses

Human immunodeficiency virus (HIV-1) replicates in the secondary lymphoid tissues, which are characterized by complex compartmental structures. While Cytotoxic T lymphocytes (CTL) readily access infected cells in the extrafollicular compartments, they do not home to follicular compartments, which thus represent an immune-privileged site. Using mathematical models, we have previously shown that this compartmental tissue structure can delay the emergence of CTL escape mutants. Here, we show computationally that the compartmental structure can have an impact on the evolution of advantageous mutants that are not related to CTL recognition: (i) Compartmental structure can influence the fixation probability of an advantageous mutant, with weakened selection occurring if CTL responses are of intermediate strength. (ii) Compartmental structure is predicted to reduce the rate mutant generation, which becomes more pronounced for stronger CTL responses. (iii) Compartmental structure is predicted to slow down the overall rate of mutant invasion, with the effect becoming more pronounced for stronger CTL responses. Altogether, this work shows that in vivo virus evolution proceeds slower in models with compartmental structure compared to models that assume equivalent virus load in the absence of compartmental structure, especially for strong CTL-mediated virus control. This has implications for understanding the rate of disease progression.

evolutionary biology↗

bioRxiv2023

Dynamically adjusted cell fate decisions and resilience to mutant invasion during steady state hematopoiesis revealed by an experimentally parameterized mathematical model

A major next step in hematopoietic stem cell (HSC) biology is to obtain a thorough quantitative understanding of cellular and evolutionary dynamics involved in undisturbed hematopoiesis. Mathematical models are key in this respect, and are most powerful when parameterized experimentally and containing sufficient biological complexity. Mathematical models of hematopoiesis have either been parameterized experimentally without non-linear dynamics, or they include these complexities but have not been parameterized to the same extent. We bridge this gap using mouse data to parameterize a mathematical model of hematopoiesis that includes homeostatic control mechanisms as well as clonal evolution. We find that non-linear feedback control drastically changes the interpretation of kinetic estimates at homeostasis. This suggests that short-term HSC and multipotent progenitors (MPPs) can dynamically adjust to sustain themselves in the absence of long-term HSCs, even if they differentiate more often than they self-renew in undisturbed homeostasis. Additionally, the presence of feedback control in the model renders the system resilient against mutant invasion. Invasion barriers, however, can be overcome by a combination of age-related changes in stem cell differentiation and a mutant-associated inflammatory environment. This helps us understand the evolution of e.g. TET2, DNMT3A, or JAK2 mutants, and how to potentially reduce mutant burden.

evolutionary biology↗

bioRxiv2023

Human immunodeficiency virus (HIV) dynamics in secondary lymphoid tissues and the evolution of cytotoxic T lymphocyte (CTL) escape mutants

In the secondary lymphoid tissues, human immunodeficiency virus (HIV) can replicate both in the follicular and the extrafollicular compartments. Yet, virus is concentrated in the follicular compartment in the absence of antiretroviral therapy, in part due to the lack of cytotoxic T lymphocyte (CTL)-mediated activity there. CTL home to the extrafollicular compartment, where they can suppress virus load to relatively low levels. We use mathematical models to show that this compartmentalization can explain seemingly counterintuitive observations. First, it can explain the observed constancy of the viral decline slope during antiviral therapy irrespective of the presence of CTL in SIV-infected macaques, under the assumption that CTL-mediated lysis significantly contributes to virus suppression. Second, it can account for the relatively long times it takes for CTL escape mutants to emerge during chronic infection even if CTL-mediated lysis is responsible for virus suppression. The reason is the heterogeneity in CTL activity, and the consequent heterogeneity in selection pressure between the follicular and extrafollicular compartments. Hence, to understand HIV dynamics more thoroughly, this analysis highlights the importance of measuring virus populations separately in the extrafollicular and follicular compartments rather than using virus load in peripheral blood as an observable; this hides the heterogeneity between compartments that might be responsible for the particular patters seen in the dynamics and evolution of the HIV in vivo.

evolutionary biology↗

bioRxiv2023

Mutant fixation in the presence of a natural enemy

In the extensive literature about mutant invasion and fixation, populations are typically assumed to exist in isolation from their ecosystem. Yet, populations are part of ecological communities, and enemy-victim (e.g. predator-prey or pathogen-host) dynamics are particularly common. We use computational models to re-visit the established theory about mutant fixation in the presence of a natural enemy, which equally attacks both wild-type and mutant populations. We consider advantageous and disadvantageous mutants, whose fitness is unrelated to the infection. Using spatially structured agent-based as well as patch models of a population that is subject to infection, we investigate the fixation probability of a mutant that is introduced into the population at quasi-equilibrium. We find that infection significantly weakens selection. Thus, the presence of infection increases the fixation probability of disadvantageous mutants and decreases the fixation probability of advantageous mutants, with the magnitude of the effect rising with the infection rate. We show that this occurs because infection induces spatial structures, in which mutant and wild-type individuals are mostly spatially separated. Thus, instead of mutant and wild-type individuals competing with each other, it is mutant and wild-type "patches" that compete, resulting in smaller fitness differences and hence weakened selection. Because natural enemies such as infections are ubiquitous, this has broad applicability to natural systems. Our results imply that the burden of deleterious mutants in natural populations might be significantly higher than expected from mutant invasion theory developed in the absence of natural enemies.

evolutionary biology↗

bioRxiv2022

Deterministic approximation for population dynamics in the presence of advantageous mutants

Spatial stochastic simulations of evolutionary processes are computationally expensive. Here, based on spatially explicit decoupling approximations (SEDA) introduced in [1], we derive a deterministic approximation to a spatial stochastic birth-death process in the presence of two types: the less advantageous resident type and a more advantageous mutant. At the core of this technique are two essential steps: (1) a system of ODEs that approximate spatial interactions among neighboring individuals must be solved; (2) the time-variable has to be rescaled with a factor (called "") that depends on the kinetic parameters of the wild type and mutant individuals. An explicit formula for is derived, which is a power law of division and death rates of the two types. The method is relatively fast and provides excellent time-series agreement with the stochastic simulation results for the spatial agent-based model. The methodology can be used to describe hard selective sweep events, including the expansion of driver mutations in carcinogenesis, bacterial evolution, and aspects of resistance dynamics.

evolutionary biology↗

bioRxiv2021

Effect of human behavior on the evolution of viral strains during an epidemic

It is well known in the literature that human behavior can change as a reaction to disease observed in others, and that such behavioral changes can be an important factor in the spread of an epidemic. It has been noted that human behavioral traits in disease avoidance are under selection in the presence of infectious diseases. Here we explore a complimentary trend: the pathogen itself might experience a force of selection to become less "visible", or less "symptomatic", in the presence of such human behavioral trends. Using a stochastic SIR agent-based model, we investigated the co-evolution of two viral strains with cross-immunity, where the resident strain is symptomatic while the mutant strain is asymptomatic. We assumed that individuals exercised self-regulated social distancing (SD) behavior if one of their neighbors was infected with a symptomatic strain. We observed that the proportion of asymptomatic carriers increased over time with a stronger effect corresponding to higher levels of self-regulated SD. Adding mandated SD made the effect more significant, while the existence of a time-delay between the onset of infection and the change of behavior reduced the advantage of the asymptomatic strain. These results were consistent under random geometric networks, scale-free networks, and a synthetic network that represented the social behavior of the residents of New Orleans.

evolutionary biology↗

bioRxiv2021

The Myogenesis Program Drives Clonal Selection and Drug Resistance in Rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a pediatric cancer with features of skeletal muscle; patients with unresectable or metastatic RMS fare poorly due to high rates of disease recurrence. Here, we use single cell and single nucleus RNA-sequencing to show that RMS tumors recapitulate the spectrum of embryonal myogenesis. Using matched patient samples from a clinical trial and orthotopic patient-derived xenografts (O-PDXs), we show chemotherapy eliminates the most proliferative component with features of myoblasts; after treatment, the quiescent immature population with features of paraxial mesoderm expands to reconstitute the developmental hierarchy of the original tumor. We discovered that this paraxial mesoderm population is dependent on EGFR signaling and is sensitive to EGFR inhibitors. Taken together, this data serves as a proof-of-concept that targeting each developmental state in RMS is an effective strategy for improving outcomes by preventing disease recurrence.

cancer biology↗

bioRxiv2021

Spatial dynamics of feedback and feedforward regulation in cell lineages

Feedback mechanisms within cell lineages are thought to be important for maintaining tissue homeostasis. Mathematical models that assume well-mixed cell populations, together with experimental data, have suggested that negative feedback from differentiated cells on the stem cell self-renewal probability can maintain a stable equilibrium and hence homeostasis. Cell lineage dynamics, however, are characterized by spatial structure, which can lead to different properties. Here, we investigate these dynamics using spatially explicit computational models, including cell division, differentiation, death, and migration / diffusion processes. According to these models, the negative feedback loop on stem cell self-renewal fails to maintain homeostasis, both under the assumption of strong spatial restrictions and fast migration / diffusion. Although homeostasis cannot be maintained, this feedback can regulate cell density and promote the formation of spatial structures in the model. Tissue homeostasis, however, can be achieved if spatially restricted negative feedback on self-renewal is combined with an experimentally documented spatial feedforward loop in which stem cells regulate the fate of transit amplifying cells. This indicates that the dynamics of feedback regulation in tissue cell lineages are more complex than previously thought, and that combinations of spatially explicit control mechanisms are likely instrumental.

systems biology↗

bioRxiv2021

The role of migration in mutant evolution in fragmented populations

Mutant evolution in fragmented populations has been studied extensively in evolutionary biology. With an increased focus on evolutionary dynamics in medical research, quantification of mutant load in fragmented populations with varying levels of migration has become especially important. Examples of fragmented populations are hematopoietic stem cell niches in the bone marrow where cells can re-circulate between niches through the blood, or colonic crypts where movement of cells across different crypts is not thought to be common. Here we use a combination of experiments and theory to investigate the role of migration in mutant distribution. In the case of neutral mutants, the experiments confirmed that while the mean number of mutants is not influenced by migration, the probability distribution is, which manifested itself in a change in the skewedness of the distribution of the mutant numbers in the demes. In the case of disadvantageous mutants, we investigated the phenomenon of the increase in the expected number of mutants compared to that of the selection-mutation balance. In a single deme, this increase is observed when the deme size is lower than the critical size, Nc. In a fragmented system that consists of connected demes with a probability of migration, the increase in mutant numbers above the selection-mutation balance can be maintained in small (N < Nc) demes as long as the migration rate is sufficiently small. The migration rate above which the mutants approach the selection-mutation balance decays exponentially with N/Nc. These findings are relevant in the context of the complex and poorly understood processes that may lead to changes in the clonal composition in tissues and tumors.

evolutionary biology↗

bioRxiv2021

The protective effect of aspirin in colorectal carcinogenesis: a multiscale computational study from mutant evolution to age incidence curves

Aspirin intake has been shown to lead to significant protection against colorectal cancer, e.g. with an up to two-fold reduction in colorectal adenoma incidence rates at higher doses. The mechanisms contributing to protection are not yet fully understood. While aspirin is an anti-inflammatory drug and can thus influence the tumor microenvironment, in vitro and in vivo experiments have recently shown that aspirin can also have a direct effect on cellular kinetics and fitness. It reduces the rate of tumor cell division and increases the rate of cell death. The question arises whether such changes in cellular fitness are sufficient to significantly contribute to the epidemiologically observed protection. To investigate this, we constructed a class of mathematical models of in vivo evolution of advanced adenomas, parameterized it with available estimates, and calculated population level incidence. Fitting the predictions to age incidence data revealed that only a model that included colonic crypt competition can account for the observed age-incidence curve. This model was then used to predict modified incidence patterns if cellular kinetics were altered as a result of aspirin treatment. We found that changes in cellular fitness that were within the experimentally observed ranges could reduce advanced adenoma incidence by a sufficient amount to account for age incidence data in aspirin-treated patient cohorts. While the mechanisms that contribute to the protective effect of aspirin are likely complex and multi-factorial, our study demonstrates that direct aspirin-induced changes of tumor cell fitness can significantly contribute to epidemiologically observed reduced incidence patterns.

cancer biology↗

bioRxiv2020

A hybrid stochastic-deterministic approach to explore multiple infection and evolution in HIV

To study viral evolutionary processes within patients, mathematical models have been instrumental. Yet, the need for stochastic simulations of minority mutant dynamics can pose computational challenges, especially in heterogeneous systems where very large and very small subpopulations coexist. Here, we describe a hybrid stochastic-deterministic algorithm to simulate mutant evolution in large viral populations, such as acute HIV-1 infection, and further include the multiple infection of cells. We demonstrate that the hybrid method can approximate the fully stochastic dynamics with sufficient accuracy at a fraction of the computational time, and quantify evolutionary end points that cannot be expressed by deterministic models, such as the mutant distribution or the probability of mutant existence at a given infected cell population size. We apply this method to study the role of multiple infection and intracellular interactions among different virus strains (such as complementation and interference) for mutant evolution. Multiple infection is predicted to increase the number of mutants at a given infected cell population size, due to a larger number of infection events. We further find that viral complementation can significantly enhance the spread of disadvantageous mutants, but only in select circumstances: it requires the occurrence of direct cell-to-cell transmission through virological synapses, as well as a substantial fitness disadvantage of the mutant, most likely corresponding to defective virus particles. This, however, likely has strong biological consequences because defective viruses can carry genetic diversity that can be incorporated into functional virus genomes via recombination. Through this mechanism, synaptic transmission in HIV might promote virus evolvability.

evolutionary biology↗

bioRxiv2020

Quantifying the dynamics of viral recombination during free virus and cell-to-cell transmission in HIV-1 infection

Recombination has been shown to contribute to HIV-1 evolution in vivo, but the underlying dynamics are extremely complex, depending on the nature of the fitness landscapes and of epistatic interactions. A less well-studied determinant of recombinant evolution is the mode of virus transmission in the cell population. HIV-1 can spread by free virus transmission, resulting largely in singly infected cells, and also by direct cell-to-cell transmission, resulting in the simultaneous infection of cells with multiple viruses. We investigate the contribution of these two transmission pathways to recombinant evolution, by applying mathematical models to in vitro experimental data on the growth of fluorescent reporter viruses under static conditions (where both transmission pathways operate), and under gentle shaking conditions, where cell-to-cell transmission is largely inhibited. The parameterized mathematical models are then used to extrapolate the viral evolutionary dynamics beyond the experimental settings. Assuming a fixed basic reproductive ratio of the virus (independent of transmission pathway), we find that recombinant evolution is fastest if virus spread is driven only by cell-to-cell transmission, and slows down if both transmission pathways operate. Recombinant evolution is slowest if all virus spread occurs through free virus transmission. This is due to cell-to-cell transmission (i) increasing infection multiplicity, (ii) promoting the co-transmission of different virus strains from cell to cell, and (iii) increasing the rate at which point mutations are generated as a result of more reverse transcription events. This work further resulted in the estimation of various parameters that characterize these evolutionary processes. For example, we estimate that during cell-to-cell transmission, an average of 3 viruses successfully integrated into the target cell, which can significantly raise the infection multiplicity compared to free virus transmission. In general, our study points towards the importance of infection multiplicity and cell-to-cell transmission for HIV-evolution.

evolutionary biology↗