Biology subjects

Steiner, U. K.

Publications and source records attributed to Steiner, U. K..

15 recordsLinked to original sources

bioRxiv2025

Population Consequences of Single-Cell Damage Dynamics: Theory and Experiment under Glucose Limitation in E. coli

Microbial population growth arises from the survival and division of individual cells. However, under environmental stress, how reduced population fitness emerges from the single-cell dynamics remains poorly understood. Cellular aging and damage accumulation are often overlooked in linking these levels. Here, we use both theory and experiment to investigate how stochastic and asymmetric damage dynamics shape population outcomes. Theoretically, we apply a jump-diffusion damage model within a structured population framework to explore the roles of damage rate, noise, and partitioning asymmetry. Our theoretical analyses show that these parameters influence population growth both at equilibrium and during transient dynamics, suggesting that their cellular regulation may be a key strategy for sustaining population fitness. Experimentally, we expose Escherichia coli to glucose limitation and monitor stress responses using a RpoS fluorescent reporter, tracking both single-cell behavior in a microfluidic device combined with time-lapse fluorescence microscopy and population growth in a plate reader. Glucose limitation leads to the effects of elevated stress, reduced division, and increased mortality, which are consistently observed across scales. Using parameter estimates from single-cell data, our model deepens insights on population-level dynamics and highlights damage-noise driven, damage-dependent mortality as a key factor under stress. Together, these findings establish a quantitative framework linking intracellular stress to population fitness under environmental stress.

evolutionary biology↗

bioRxiv2025

Optimal division asymmetry in E. coli bacteria

Cell division asymmetry underlies many fundamental biological processes, including the evolution of aging. Despite this importance, understanding whether the observed division asymmetry has been optimized by evolution remains little explored. Here we first show that size and transcription signal asymmetries have evolved to an optimum, as increased or decreased asymmetries lowers population growth. We then highlight how variance and covariance in growth and transcription signal asymmetry influence population growth. This latter exploration reveals how sensitive deviations to the optimum are, and that selective forces act primarily on variance in transcription signal asymmetry and less so on other cell intrinsic noise or growth asymmetries. Our findings are based on advancing integral projection models to two traits and we parameterize these models with single-cell data of mother and daughter E. coli bacterial cells collected using microfluidic devices. We discuss how trade-offs between growth and the transcription signal we explore has shaped this optimum. Our findings provide insights on how division asymmetries and resulting cellular heterogeneity can have profound biological consequences--contributing to processes such as cancer development, antibiotic treatment failure, and the rejuvenation of cell lineages, including in mammalian stem cells.

evolutionary biology↗

bioRxiv2024

Rapid growth and the evolution of complete metamorphosis in insects

More than 60% of all animal species are insects that undergo complete metamorphosis. The key innovation of these holometabolous insects is a pupal stage between the larva and adult when most structures are completely rebuilt. Why this extreme lifestyle evolved is unclear. Here we test the hypothesis that a trade-off between growth and differentiation explains the evolution of this novelty. Using a comparative approach, we find that holometabolous insects grow much faster than hemimetabolous insects. Using a theoretical model, we then show how holometaboly evolves under a growth-differentiation trade-off and identify conditions under which such temporal decoupling of growth and differentiation is favored. Our work supports the notion that the holometabolous life history evolved to remove developmental constraints on fast growth, primarily under high mortality.

evolutionary biology↗

bioRxiv2023

Declining old pole physiology gradually enhances gene expression asymmetry in bacteria

Gene expression is a heterogeneous process at the single-cell level. This heterogeneity is often coupled to individual growth rates, which are also highly stochastic, leading to the emergence of multiple physiological states within bacterial populations. Although recent advances have shown that cellular aging acts as a deterministic driver of growth asymmetry, the relationship between aging and gene expression heterogeneity remains elusive. Here we show that old poles undergo a progressive decline in gene expression as mother cells age, contributing to enhance phenotypic heterogeneity in bacterial populations. We quantified the activity of promoters with distinct activity profiles: a constitutive promoter, whose expression positively correlates with growth, and the promoter of RpoS, the general stress response sigma factor, for which growth and expression are mutually inhibitory. We demonstrate that mother cells have lower gene expression for both promoters. This asymmetry could not be explained by metabolic rate differences, but rather by the increasing intracellular heterogeneity of mother cells. As a mother ages, the declining activity of its old pole produces intracellular gradients in gene expression. This intracellular asymmetry manifests in the next generation as mother-daughter asymmetry, thus representing a source of phenotypic heterogeneity for the population. Our results show that bacterial asymmetry is built into the declining physiology of mother cells across generations, illustrating the deterministic nature of aging in bacterial systems. These findings provide further evidence for cellular aging as a mechanism to enhance the variance of metabolic states found in bacterial populations, with possible consequences for stress response and survival.

evolutionary biology↗

bioRxiv2023

Structured demographic buffering: A framework to explore the environment drivers and demographic mechanisms underlying demographic buffering

Environmental stochasticity is a key determinant of population viability. Decades of work exploring how environmental stochasticity influences population dynamics have highlighted the ability of some natural populations to limit the negative effects of environmental stochasticity, one of these strategies being demographic buffering. Whilst various methods exist to quantify demographic buffering, we still do not know which environment factors and demographic characteristics are most responsible for the demographic buffering observed in natural populations. Here, we introduce a framework to quantify the relative effects of three key drivers of demographic buffering: environment components (e.g., temporal autocorrelation and variance), population structure, and demographic rates (e.g., progression and fertility). Using Integral Projection Models, we explore how these drivers impact the demographic buffering abilities of three plant species with different life histories and demonstrate how our approach successfully characterises a populations capacity to demographically buffer against environmental stochasticity in a changing world.

ecology↗

bioRxiv2023

Demographic Consequences of Damage Dynamics in Single-Cell Ageing

Ageing is driven by damage accumulation leading to a decline in function over time. In single-cell systems, in addition to this damage accumulation within individuals, asymmetric damage partitioning at cell division can play a crucial role in shaping demographic ageing patterns. Despite empirical single-cell studies providing quantitative data at the molecular and demographic level, a comprehensive theory of how cellular damage production and asymmetric partitioning propagate and influence demographic patterns is still lacking. Here, we present a generic and flexible damage model using a stochastic differential equation approach that incorporates stochastic damage accumulation and asymmetric damage partitioning at cell divisions. We formulate an analytical approximation linking cellular and damage parameters to demographic ageing patterns. Interestingly, the lifespan of cells follows an inverse-gaussian distribution whose underlying properties derive from cellular and damage parameters. We demonstrate how stochasticity (noise) in damage production, asymmetry in damage partitioning, and division frequency shape lifespan distribution. Confronting the model to various empirical E.coli data reveals non-exponential scaling in mortality rates, a scaling that cannot be captured by classical Gompertz-Makeham models. Our findings provide a deep understanding of how fundamental processes contribute to cellular damage dynamics and generate demographic patterns. Our damage models generic nature offers a valuable framework for investigating ageing in diverse biological systems. SignificanceAsymmetries and randomness in cellular events play important roles in establishing the diversity at evolutionary and demographic scales. Looking at single-cells, ageing processes are influenced by stochastic damage accumulation and asymmetric damage partitioning at cell divisions. Utilising stochastic differential equations, we develop a cellular damage model that encapsulate both noisy damage accumulation within cells and asymmetric damage partitioning among cells when they divide. In doing so we bridge molecular stochastic processes, demographic fates of individuals, and population level demographic distributions. Our model aligns with empirical data from E.coli single-cell studies and advances our understanding compared to traditional demographic models. The generic and adaptable nature of our model paves the way for broader applications in ageing research across biological systems, highlighting the influences of stochasticity and asymmetry on cellular biology.

evolutionary biology↗

bioRxiv2022

Adaptive and neutral processes that select on life course diversification

Heterogeneity among individuals in fitness components is what selection acts upon. One of the fundamental questions in evolution is how such heterogeneity arises and is maintained. Fundamental evolutionary theories predict that selection acts against such heterogeneity but contrasting these predictions substantial non-genetic and non-environmental driven variability in phenotypes can be observed; not only under highly controlled lab conditions, but also in less controlled settings. Here we ask, by analysing structured population models across a large range of biological taxa, how selective forces act on the processes that generate variation among life courses. Our findings suggest that non-genetic, non-environmental driven variation is in general neither truly neutral, selected for, or selected against. Much variation exists among species and populations within species, with mean patterns suggesting close to neutral evolution of life course variability. Populations that show greater diversity of life courses do not show, in general, increased or decreased population growth rates, and selective forces acting on the processes of diversification seem not to generally increase or decrease life course variability. Approaches in quantitative genetics that identified similar lack of understanding of maintenance of variability might be extended to include non-genetic and non-environmental driven variability. We believe to be only at the beginning in understanding the evolution and maintenance of non-genetic non environmental variation.

evolutionary biology↗

bioRxiv2021

A different type of tolerance: selection for and phenotypic characteristics of antibiotic tolerance evaluated at the single cell level under recurring antibiotic exposure in Escherichia coli.

Despite increasing interest, non-heritable, phenotypic drug resistance, such as tolerance and persistence towards antibiotics, remains less characterized compared to genetic resistance. Non-heritable drug resistance challenges antibiotic treatment and have implications towards heritable resistance evolution. Phenotypically resistant cells have commonly been characterized as growth arrested cells prior and during antibiotic application that quickly resume growth post-application. Here, we add novel combinations of characteristics of phenotypic resistant E. coli single cells--that are of particular interest towards genetically fixed resistance--, and contrast those to susceptible cells of the isoclonal initial population by exposure to different levels of recurrent antibiotic. We find that phenotypic resistant cells reduced their growth rate by about 50% compared to growth rates prior to antibiotic exposure, but cells do not go into near growth arrest. The growth reduction is induced by antibiotic exposure and not caused by a stochastic switch or predetermined state as frequently described. Cells exhibiting constant intermediate growth survived best under antibiotic exposure and, contrary to expectations, selection did not primarily act on fast growing cells. Our findings support diverse modes of phenotypic resistance, and we revealed resistant cell characteristics that supports acclaims of an underappreciated role of phenotypic resistant cells towards resistance evolution.

evolutionary biology↗

bioRxiv2020

Hurricane-induced demographic changes in a nonhuman primate population

Major disturbance events can have large impacts on the demography and dynamics of animal populations. Hurricanes are one example of an extreme climatic event, predicted to increase in frequency due to climate change, and thus expected to be a considerable threat to population viability. However, little is understood about the underlying demographic mechanisms shaping population response following these extreme disturbances. Here, we analyze 45 years of the most comprehensive free-ranging nonhuman primate demographic dataset to determine the effects of major hurricanes on the variability and maintenance of long-term population fitness. For this, we use individual-level data to build matrix population models and perform perturbation analyses. Despite reductions in population growth rate mediated through reduced fertility, our study reveals a demographic buffering during hurricane years. As long as survival does not decrease, our study shows that hurricanes do not result in detrimental effects at the population level, demonstrating the unbalanced contribution of survival and fertility to population fitness in long-lived animal populations.

ecology↗

bioRxiv2018

Adaptive Phenotypic Plasticity for Life History and Less Fitness-Related Traits

Organisms are faced with variable environments and one of the most common solutions to cope with such variability is phenotypic plasticity, a modification of the phenotype to the environment. These modifications influence ecological and evolutionary processes and are assumed to be adaptive. The assumption of adaptive plasticity allows to derive the prediction that the closer to fitness a trait is, the less plastic it would be. To test this hypothesis, we conducted a meta-analysis of 213 studies and measured the plasticity of each reported trait as coefficient of variation (CV). Traits were categorised according to their relationship to fitness into life-history traits (LHt) including reproduction and survival related-traits, and non-life-history traits (N-LHt) including traits related to development, metabolism and physiology, morphology and behaviour. Our results showed, unexpectedly, that although traits differed in their amounts of plasticity, trait plasticity did not correlate with its proximity to fitness. These findings were independent of taxonomic groups or environmental types assessed and raise questions about the ubiquity of adaptive plasticity. We caution about generalising the assumption that all plasticity is adaptive with respect to evolutionary and ecological population processes. More studies are needed that test the adaptive nature of plasticity, and additional theoretical explorations on adaptive and non-adaptive plasticity are encouraged.

evolutionary biology↗

bioRxiv2017

Drivers of diversity in individual life courses: Sensitivity of the population entropy of a Markov chain

Individuals differ in their life courses, but how this diversity is generated, how it has evolved and how maintained is less understood. However, this understanding is crucial to comprehend evolutionary and ecological population dynamics. In structured populations, individual life courses represent sequences of stages that end in death. These sequences can be described by a Markov chain and individuals diversify over the course of their lives by transitioning through diverse discrete stages. The rate at which stage sequences diversify with age can be quantified by the population entropy of a Markov chain. Here, we derive sensitivities of the population entropy of a Markov chain to identify which stage transitions generate--or contribute--most to diversification in stage sequences, i.e. life courses. We then use these sensitivities to reveal potential selective forces on the dynamics of life courses. To do so we correlated the sensitivity of each matrix element (stage transition) with respect to the population entropy, to its sensitivity with respect to fitness {lambda}, the population growth rate. Positive correlation between the two sensitivities would suggest that the stage transitions that selection has acted most strongly on (sensitivities with respect to {lambda}) are also those that contributed most to the diversification of life courses. Using an illustrative example on a seabird population, the Thick-billed Murres on Coats Island, that is structured by reproductive stages, we show that the most influential stage transitions for diversification of life courses are not correlated with the most influential transitions for population growth. Our finding suggests that observed diversification in life courses is neutral rather than adaptive. We are at an early stage of understanding how individual level dynamics shape ecological and evolutionary dynamics, and many discoveries await.

evolutionary biology↗

bioRxiv2017

Demographic variability and heterogeneity among individuals within and among clonal bacteria strains

Identifying what drives individual heterogeneity has been of long interest to ecologists, evolutionary biologists and biodemographers, because only such identification provides deeper understanding of ecological and evolutionary population dynamics. In natural populations one is challenged to accurately decompose the drivers of heterogeneity among individuals as genetically fixed or selectively neutral. Rather than working on wild populations we present here data from a simple bacterial system in the lab, Escherichia coli. Our system, based on cutting-edge microfluidic techniques, provides high control over the genotype and the environment. It therefore allows to unambiguously decompose and quantify fixed genetic variability and dynamic stochastic variability among individuals. We show that within clonal individual variability (dynamic heterogeneity) in lifespan and lifetime reproduction is dominating at about 82-88%, over the 12-18% genetically (adaptive fixed) driven differences. The genetic differences among the clonal strains still lead to substantial variability in population growth rates (fitness), but, as well understood based on foundational work in population genetics, the within strain neutral variability slows adaptive change, by enhancing genetic drift, and lowering overall population growth. We also revealed a surprising diversity in senescence patterns among the clonal strains, which indicates diverse underlying cell-intrinsic processes that shape these demographic patterns. Such diversity is surprising since all cells belong to the same bacteria species, E. coli, and still exhibit patterns such as classical senescence, non-senescence, or negative senescence. We end by discussing whether similar levels of non-genetic variability might be detected in other systems and close by stating the open questions how such heterogeneity is maintained, how it has evolved, and whether it is adaptive.\n\nData depositionThe processed image analysis data, R code, as well as the Leslie matrices will be archived at Dryad.org.

evolutionary biology↗

bioRxiv2017

Two stochastic processes shape diverse senescence patterns in a single-cell organism

Despite advances in aging research, a multitude of aging models, and empirical evidence for diverse senescence patterns, understanding is lacking of the biological processes that shape senescence, both for simple and complex organisms. We show that for a isogenic Escherichia coli bacterial population senescence results from two stochastic processes. A primary random deterioration process within the cell, such as generated by random accumulation of damage, leads to an exponential increase in mortality early in life followed by a late age mortality plateau; a secondary process of stochastic asymmetric transmission of an unknown factor at cell fission influences mortality. This second process is required to explain the difference between the classical mortality plateaus detected for young mothers offspring and the near non-senescence of old mothers offspring as well as the lack of a mother offspring correlation in age at death. We observed that life span is predominantly determined by underlying stochastic stage dynamics. Our findings support models based on stage-specific actions of alleles for the evolution of senescence. This support might be surprising since these models that have not specifically been developed in the context of simple, single cell organisms. We call for exploration of similar stochastic influences beyond simple organisms.

systems biology↗

bioRxiv2017

Drivers of diversification in individual life courses

Heterogeneity in life courses among individuals of a population influences the speed of adaptive evolutionary processes, but it is less clear how biotic and abiotic environmental fluctuations influence such heterogeneity. We investigate principal drivers of variability in sequence of stages during an individuals life in a stage-structured population. We quantify heterogeneity by measuring population entropy, which computes the rate of diversification of individual life courses of a Markov chain. Using individual data of a primate population, we show that density regulates the stage composition of the population, but its entropy and the generating moments of heterogeneity are independent of density. This lack of influence of density on heterogeneity is neither due to low year-to-year variation in entropy nor due to differences in survival among stages, but due to differences in stage transitions. Our analysis thus shows that well-known classical ecological selective forces, such as density regulation, are not linked to potential selective forces governing heterogeneity through underlying stage dynamics. Despite evolution acting heavily on individual variability in fitness components, our understanding is poor whether observed heterogeneity is adaptive and how it evolves and is maintained. Our analysis illustrates how entropy represents a more integrated measure of diversity compared to the population structural composition, giving us new insights about the underlying drivers of individual heterogeneity within populations and potential evolutionary mechanisms.

ecology↗

bioRxiv2017

Ecological and demographic drivers of jellyfish blooms

O_LIJellyfish blooms are conspicuous demographic events with significant ecological and socio-economic impact. Despite worldwide concern about an increased frequency and intensity of jellyfish mass occurrences, predicting their booms and busts remains challenging. C_LIO_LIForecasting how jellyfish populations may respond to environmental change requires taking into account their complex life histories. Metagenic life cycles, which include a benthic polyp stage, can boost jellyfish outbreaks via asexual recruitment of pelagic medusae. C_LIO_LIHere we present stage-structured matrix population models with demographic rates of all life stages of the cosmopolitan jellyfish Aurelia aurita s. l. for different environments. We investigate the life stage-dynamics of such complex populations to illustrate how changes in medusa density depend on non-medusa stage dynamics. C_LIO_LIWe show that increased food availability is an important ecological driver of jellyfish mass occurrence, as it can shift the population structure from polyp- to medusa-dominated. Projecting populations for a winter warming scenario additionally enhanced the booms and busts of jellyfish blooms. C_LIO_LIWe identify demographic key variables that control the intensity and frequency of jellyfish blooms in response to anthropogenic drivers such as habitat eutrophication and climate change. By contributing to an improved understanding of mass occurrence phenomena, our findings provide perspective for future management of ecosystem health. C_LI

ecology↗