Gene-free minimal system for synthetic quorum sensing in protocell communities

Gene-free minimal system for synthetic quorum sensing in protocell communities

Schematic diagram of a synthetic quorum sensing system. (a) PDDA-ATP coacervate encapsulates trypsinogen and BZAR. When trypsin is introduced externally, an autocatalytic feedback loop activates local trypsinogen, leading to cleavage of the caged fluorogenic substrate BZAR and release of rhodamine-110. Trypsin diffuses between coacervates, allowing signal transduction between compartments. At low population densities, signaling remains below threshold and minimal fluorescence occurs. At high population densities, autocatalytic feedback and intercoacervate communication lead to population-wide signal amplification. (b) Chemical reaction showing trypsin-mediated hydrolysis of the fluorogenic substrate BZAR to generate rhodamine-110 and autocatalytic conversion of trypsinogen to trypsin. — chemrxiv.org

Synthetic communication networks are key to engineering life-like behavior within artificial cells. Inspired by nature’s quorum sensing, we developed a coacervate-based system that exhibits quorum-sensing-like communication driven by an autocatalytic trypsin-trypsinogen feedback loop.

These membrane-less compartments allow the diffusion and amplification of signaling molecules, resulting in density-dependent population activation similar to natural population responses. At high population densities, signal accumulation triggers a system-wide fluorescence response, whereas at low population densities, signaling remains off.

By varying trypsin, trypsinogen, and population density, activation thresholds varied by nearly an order of magnitude, with signal amplification accelerating fourfold at high population densities. This gene-free platform establishes a minimal route to programmable collective dynamics in synthetic protocellular communities.

Gene-free minimal system for synthetic quorum sensing in protocell communitieschemrxiv.org (open access)

astrobiology, genomics,

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