Journal
SCIENCE
Volume 364, Issue 6440, Pages 593-+Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.aau8287
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Funding
- NSF Expeditions in Computing grant [CCF-1522074]
- DARPA [W911NF-11-2-0056, D16AP00142]
- NSF CAREER award [MCB-1350949]
- NIH [1DP2AI131083-01]
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Eukaryotic genes are regulated by multivalent transcription factor complexes. Through cooperative self-assembly, these complexes perform nonlinear regulatory operations involved in cellular decision-making and signal processing. In this study, we apply this design principle to synthetic networks, testing whether engineered cooperative assemblies can program nonlinear gene circuit behavior in yeast. Using a model-guided approach, we show that specifying the strength and number of assembly subunits enables predictive tuning between linear and nonlinear regulatory responses for single- and multi-input circuits. We demonstrate that assemblies can be adjusted to control circuit dynamics. We harness this capability to engineer circuits that perform dynamic filtering, enabling frequency-dependent decoding in cell populations. Programmable cooperative assembly provides a versatile way to tune the nonlinearity of network connections, markedly expanding the engineerable behaviors available to synthetic circuits.
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