Sing along with the environment: extended mean-field models for collective behaviour in cell populations

Description

Mean-field models have significantly advanced our understanding of ordering phenomena in condensed matter systems. In this talk, I will argue that they can also be employed to study dynamic self-organisation in biological systems, where the behavior of individual components is often more complex. As an example, I will discuss spontaneous rhythmic behavior in cell populations. A quantitative description of this oscillatory phenomenon has thus far been hampered by incomplete knowledge of the underlying intracellular processes, particularly when isolated cells appear to be quiescent. However, by analysing the temporal response of a cell to environmental signals, it is possible to associate certain behavioural trait, such as adaption, with collective oscillations in the cell population[1]. As the cell density increases beyond a threshold, an oscillating signal in a suitable frequency range becomes self-sustained due to active feedback from individual cells. We find that this overarching principle is at work in several natural and synthetic oscillatory systems where cells communicate through a chemical signal. Applying the theoretical scheme to 2D bacterial suspensions, we found that run-and-tumble cells of sufficiently high density spontaneously develop weak circular motion with a laminar flow profile in the thin fluid layer. The theoretical results are compared with weak collective oscillations discovered earlier in Yilin Wu’s lab[2], which can be considered as a vector version of our fundamental theory.

[1]   Shou-Wen Wang and Lei-Han Tang, Emergence of collective oscillations in adaptive cells, Nature Communications 10, 5613 (2019).

[2]   Chong Chen, Song Liu, Xia-qing Shi, Hugues Chaté & Yilin Wu, Weak synchronization and large-scale collective oscillation in dense bacterial suspensions, Nature 542, 210-214 (2017).

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