Stabilization of Microbial Communities by Responsive Phenotypic Switching

Clonal microbes can switch between different phenotypes and recent theoretical work has shown that stochastic switching between these subpopulations can stabilize microbial communities. This phenotypic switching need not be stochastic, however, but could also be in response to environmental factors, both biotic and abiotic. Here, motivated by the bacterial persistence phenotype, we explore the ecological effects of such responsive switching by analyzing phenotypic switching in response to competing species. We show that the stability of microbial communities with responsive switching differs generically from that of communities with stochastic switching only. To understand the mechanisms by which responsive switching stabilizes coexistence, we go on to analyze simple two-species models. Combining exact results and numerical simulations, we extend the classical stability results for the competition of two species without phenotypic variation to the case in which one species switches, stochastically and responsively, between two phenotypes. In particular, we show that responsive switching can stabilize coexistence even when stochastic switching on its own does not affect the stability of the community.

💡 Research Summary

This paper investigates how phenotypic switching that is responsive to the presence of competitors influences the stability of microbial communities, contrasting it with the more commonly studied stochastic (random) switching. The authors build on previous work that showed stochastic switching to a rare, slow‑growing phenotype (such as bacterial persisters) can stabilize communities, and they ask whether a switching mechanism that senses and reacts to other species can have qualitatively different ecological outcomes.

The core of the study is a deterministic model for N (>2) well‑mixed species, each possessing two phenotypes: a fast‑growing “B” type and a slow‑growing “P” type. Growth rates (b for B, p for P) and competitive interactions are described by Lotka‑Volterra matrices C, D, E, and F. Cells switch stochastically between phenotypes at rates k (B→P) and ℓ (P→B). In addition, the B phenotype of each species can switch to the P phenotype in direct proportion to the abundances of other species; this responsive switching is captured by matrices R and S (with zero diagonals so a species does not respond to itself). A small parameter ε scales the growth, competition, and switching terms of the P phenotype, making ε≈1 correspond to a persister‑like state that grows very slowly and competes weakly.

To isolate the effect of responsiveness, the authors compare three models: (i) the full responsive‑stochastic model (Eqs. 1), (ii) an “averaged” model that retains only stochastic switching but adjusts the effective stochastic rate k′ = k + R·B* + S·P* so that the equilibrium abundances are identical (Eqs. 2), and (iii) a reduced model that simply omits the responsive terms altogether. By construction, the equilibria of (i) and (ii) coincide, but the Jacobian matrices governing linear stability differ. The authors derive an exact relation between the Jacobians: J* = K* + ε·