Searcharxiv⌕ Search

arXiv · 2610.10492

Stochasticity and Environmental Switching Shape Quorum Sensing Evolution in Bacterial Populations

Abstract

Quorum sensing (QS) is classically understood as a mechanism by which bacterial cells sense their own density, but environmental fluctuations make any single cell's estimate unreliable. An alternative view holds that populations pool individual estimates to reach reliable collective decisions. We investigate how a two-autoinducer toggle switch network enables this collective adaptation in fluctuating environments. At the single-cell level, the toggle switch is bistable. Membrane permeability controls autoinducer secretion and is the evolving trait. Using an individual-based model of a spatially structured population, we show that permeability evolves through a collective mechanism. Environmental frequency is the primary determinant of evolutionary outcome. Under strong asymmetry, the dominant trait reaches a high plateau. The trait linked to the rare environment stays low. It rises smoothly as its environment becomes more frequent. Total permeability stays close to a fixed budget; environmental frequency mainly sets how it is split between the two traits. When the two environments are equally frequent, no single trait wins. Both traits coexist, and noise asymmetry between the two sensing channels biases the levels at which they coexist rather than selecting a winner. Coexistence is also the slowest outcome to reach. Higher noise speeds adaptation, but the evolved permeability is non-monotonic in noise, peaking at an intermediate value. Earlier work found that more noise favors collective sensing as long as cells are correct on average. We develop a two-trait adaptive-dynamics model that unifies these regimes. Away from symmetry, it reduces to a closed one-dimensional equation that captures the individual-based results. At symmetry, weak cross-repression gives a single coexistence attractor, consistent with replicate populations maintaining both traits.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Uttam Kumar, Hong-Yan Shih. 2026-10-07. Stochasticity and Environmental Switching Shape Quorum Sensing Evolution in Bacterial Populations. https://arxiv.org/abs/2610.10492

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Cumulants, Moments and Selection

We first describe a fundamental connection between cumulants/moments and selection -- which follows intuitively when heterogeneity is added to Matlthus's population model. In doing so we provide an intuitive explanation of cumulants widely but incorrectly regarded as having no such interpretation. These fundamental relations are more general than Fisher's fundamental theorem of natural selection -- allowing for calculation of the standard deviation, skewness and kurtosis of fitness far into the future -- and are also more precise; indeed it becomes clear that Fisher's theorem is incorrect for fitness in the conventional/natural sense. Thanks to the close connection between selection and moments, a simple relation also exists between the moments of fitness and the moments of mutation -- at equilibrium and also over time; many biologically meaningful claims follow as logical consequences with connections to Haldane's load theory and a more general formula for coefficient of variation of fitness.

q-bio.PE↗

Mathematical statistics of wild mammal biomass

Using the recently published global census of the biomass of wild terrestrial mammals, we perform a detailed mathematical statistical analysis of its distribution over $N_s=4795$ species, drawing on tools developed in economics to characterize wealth inequality. We show that the Lorenz curve of the mammal biomass distribution is characterized by a large Gini coefficient $G=0.944$ exceeding the inequality reported for wealth distribution among world countries. This distribution is compared to the predictions of the Wealth Thermalization Hypothesis (WTH), in which species biomass values are treated as energy levels populated according to a Rayleigh-Jeans (RJ) steady-state distribution. We show that an RJ extended spectral model reproduces the real Lorenz and Pareto curves over four orders of magnitude of biomass variation, capturing the strong condensation of biomass among the rare, heavy-bodied species and its near-absence among the vast majority of light-bodied ones. These results extend the WTH framework, previously validated on distributions of human economic origin, to a biological distribution shaped by ecological and evolutionary constraints, and place the extreme rarity of large-bodied mammal species within the same statistical mathematical description as the oligarchic concentration of wealth in human societies. We finally discuss possible ecological mechanisms that may contribute to the observed distribution, including interspecific interactions, food availability, and competition.

q-bio.PE↗

Discrete vs. continuous dynamics in biology: When do they align and when do they diverge?

Many biological systems are governed by difference equations and exhibit discrete-time dynamics. Examples include the size of a population when generations are non-overlapping, and the incidence of a disease when infections are recorded at fixed intervals. For discrete-time systems lacking exact solutions, continuous-time approximations are frequently employed when small changes occur between discrete time steps. Here, we present an approach motivated by exactly soluble discrete time problems. We show that such systems have continuous-time descriptions (governed by differential equations) whose solutions precisely agree, at the discrete times, with the discrete time solutions, irrespective of the size of changes that occur. For discrete-time systems lacking exact solutions, we develop approximate continuous-time models that can, to high accuracy, capture rapid growth and decay. Our approach employs mappings between difference and differential equations, generating functional solutions that exactly or closely preserve the original discrete time behaviour. It uncovers fundamental structural parallels and also distinctions between the difference equation and the `equivalent' differential equation. The findings we present cover both time-homogeneous and time-inhomogeneous systems. For completeness, we also consider discrete-time systems with the most rapid oscillatory behaviour possible, namely a sign change each time step. We show, for exactly soluble cases, that such systems also have a continuous-time description, but that this comes at the expense of generally complex-valued solutions. This work has applications in, for example, population genetics, ecology and epidemic modelling. By bridging discrete and continuous representations of a system, it enhances insights/analysis of different types of dynamics.

q-bio.PE↗