Research

Population dynamics

Collective behaviour in microbial populations and the emergence of subpopulations

Even genetically identical cells don't all behave the same way, and that diversity isn't just random noise. It emerges from how cells time their gene circuits, allocate resources, and respond to their environment, driving distinct subpopulations that interact to produce collective behaviour.

Spontaneous emergence of subpopulations

Clonal microbial populations are not homogeneous and spontaneously self-organise into phenotypically distinct subpopulations (SPs, typically detected based on fluorescent reporters) whose interactions shape the collective behaviour of the whole. Understanding how this structured diversity arises and gives rise to complex population-level dynamics is a central question in microbial biophysics.

Switching cost, not noise, drives fixation

Beyond classical stochastic switching, we showed that SPs behave as competing ecological species, with fixation dynamics governed not by random biological noise alone but by the timing of gene circuit activation and its underlying metabolic cost (switching cost). Specifically, heterogeneity in the timing of gene expression, amplified by environmental fluctuations, can drive phenotypic escape (i.e., allowing cells the escape high expression level correlated with high burden) and the stable fixation of distinct SPs.

Resource allocation as a biophysical constraint

A key finding of our group is that this timing is regulated by resource allocation i.e., the cellular cost of switching between phenotypic states acts as a biophysical constraint shaping which SPs emerge, at what frequency, and under which conditions. At the population level, these mechanisms can generate collective dynamics (bistability, oscillations, hysteresis…) that are not determined by gene network topology alone, but emerge from the coupling between subpopulation switching kinetics, resource allocation, and environmental feedback.

Key publications
Henrion L., Martínez J.A., Vandenbroucke V., Delvenne M., Telek S., Zicler A., Grünberger A., Delvigne F., 2023. Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability. Nature Communications 14, 6128. doi.org/10.1038/s41467-023-41917-z ↗
Delvigne F., Martínez J.A., 2023. Advances in automated and reactive flow cytometry for synthetic biotechnology. Current Opinion in Biotechnology 83, 102974. doi.org/10.1016/j.copbio.2023.102974 ↗
Sassi H., Nguyen T.M., Telek S., Gosset G., Grünberger A., Delvigne F., 2019. Segregostat: a novel concept to control phenotypic diversification dynamics on the example of Gram-negative bacteria. Microbial Biotechnology 12, 1064–1075. doi.org/10.1111/1751-7915.13442 ↗
Phenotypic heterogeneity engineering in bacterial cell factories
Single-cell approaches (flow cytometry, droplet microfluidics and single-cell cultivation) used to resolve population dynamics over time.