Distinct timescales of RNA regulators enable the construction of a genetic pulse generator

Abstract

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.

Cell-Free Systems: A Proving Ground for Rational Biodesign

“…While the complexity of lysates is considerable, in contrast to cellular systems biology, cell-free systems are amenable to essentially unconstrained perturbation, which greatly facilitates model testing and validation. This has been demonstrated by a number of modeling studies of increasing sophistication (Karzbrun et al, 2011 ; Stögbauer et al, 2012 ; Tuza et al, 2015 ; Gyorgy and Murray, 2016 ; Nieß et al, 2017 ; Marshall and Noireaux, 2019 ), as well as notable examples of model-guided forward engineering of genetic circuits (Hu et al, 2015 , 2018 ; Agrawal et al, 2019 ; Lehr et al, 2019 ; Westbrook et al, 2019 ). Recent development of integrated gene expression and metabolic models have elucidated the factors limiting CFPS (Wayman et al, 2015 ; Vilkhovoy et al, 2018 , 2019 ; Horvath et al, 2020 ), suggesting that combined computational and experimental metabolomic studies are poised to contribute significantly to our understanding of CFPS in lysates.…”

Toward a translationally independent RNA-based synthetic oscillator using deactivated CRISPR-Cas

“…However, the system likely has non-linearity from other mechanisms, such as bound-repressor degradation ( 52 ), with DNA-bound dCas12a-crRNA removed by dilution from cell division and possibly protein degradation, or Michaelis–Menten degradation of the RNAs ( 53 ). Estimating parameters for these mechanisms may require measurements in different contexts, such as in yeast ( 54 , 55 ) or cell-free in vitro systems ( 56 , 57 ). Addition of proteases, RNases, or interfering RNAs may allow tuning of the parameters without measuring.…”

A single-input binary counting module based on serine integrase site-specific recombination

“…After each LR→PB transition, transcription of the next integrase is first switched on by the activator and then switched off by the repressor. Pulse generators using this feed-forward mechanism have been successfully implemented using the LuxR transcriptional activator and the cI transcriptional repressor (36), or with RNA-based small transcription-activating RNA (STAR) activators and a CRISPRi-based transcriptional repressor (37).…”