Evolved interactions stabilize many coexisting phases in multicomponent liquids

Kavli Affiliate: Liedewij Laan

| First 5 Authors: David Zwicker, Liedewij Laan, , ,

| Summary:

Phase separation has emerged as an essential concept for the spatial
organization inside biological cells. However, despite the clear relevance to
virtually all physiological functions, we understand surprisingly little about
what phases form in a system of many interacting components, like in cells.
Here, we introduce a new numerical method based on physical relaxation dynamics
to study the coexisting phases in such systems. We use our approach to optimize
interactions between components, similar to how evolution might have optimized
the interactions of proteins. These evolved interactions robustly lead to a
defined number of phases, despite substantial uncertainties in the initial
composition, while random or designed interactions perform much worse.
Moreover, the optimized interactions are robust to perturbations and they allow
fast adaption to new target phase counts. We thus show that genetically encoded
interactions of proteins provide versatile control of phase behavior. The
phases forming in our system are also a concrete example of a robust emergent
property that does not rely on fine-tuning the parameters of individual
constituents.

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