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Distinct timescales of RNA regulators enable the construction of a genetic pulse generator
Author(s) -
Westbrook Alexandra,
Tang Xun,
Marshall Ryan,
Maxwell Colin S.,
Chappell James,
Agrawal Deepak K.,
Dunlop Mary J.,
Noireaux Vincent,
Beisel Chase L.,
Lucks Julius,
Franco Elisa
Publication year - 2019
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.26918
Subject(s) - synthetic biology , modularity (biology) , computational biology , biology , computer science , gene regulatory network , modular design , transcription (linguistics) , cas9 , gene expression , gene , crispr , genetics , linguistics , philosophy , operating system
To build complex genetic networks with predictable behaviors, synthetic biologists use libraries of modular parts that can be characterized in isolation and assembled together to create programmable higher‐order functions. Characterization experiments and computational models for gene regulatory parts operating in isolation are routinely used to predict the dynamics of interconnected parts and guide the construction of new synthetic devices. Here, we individually characterize two modes of RNA‐based transcriptional regulation, using small transcription activating RNAs (STARs) and clustered regularly interspaced short palindromic repeats interference (CRISPRi), and show how their distinct regulatory timescales can be used to engineer a composed feedforward loop that creates a pulse of gene expression. We use a cell‐free transcription‐translation system (TXTL) to rapidly characterize the system, and we apply Bayesian inference to extract kinetic parameters for an ordinary differential equation‐based mechanistic model. We then demonstrate in simulation and verify with TXTL experiments that the simultaneous regulation of a single gene target with STARs and CRISPRi leads to a pulse of gene expression. Our results suggest the modularity of the two regulators in an integrated genetic circuit, and we anticipate that construction and modeling frameworks that can leverage this modularity will become increasingly important as synthetic circuits increase in complexity.