Characterization of CRISPRi Dynamics Using Optogenetics and Mathematical

Modeling

Castillo-Hair SM1, Igoshin OA1,2,3, Tabor JJ1,2
1. Department of Bioengineering, Rice University, Houston, TX 77005, United States
2. Department of Biosciences, Rice University, Houston, TX 77005, United States
3. Center for Theoretical Biophysics, Rice University, Houston, TX 77005, United States
CRISPR interference (CRISPRi) can be used to repress transcription from virtually any promoter in bacteria, yeast, or mammalian cells [1-3], and to construct multilayered synthetic gene circuits [4,5]. In this system, inactivated nuclease dCas9 forms a complex with a 102-nucleotide long single guide RNA (sgRNA), which is then directed to a segment of DNA complementary to a 20-nucleotide region in the sgRNA. If the DNA segment is a promoter or the coding region of a gene, dCas9 will then block transcription initiation or elongation, effectively acting as a transcriptional repressor. Though the steady state response from sgRNA to output transcription rate has begun to be studied, a thorough characterization of CRISPRi dynamics has not been performed. A quantitative understanding of CRISPRi dynamics would enable researchers to create precise, time varying perturbations in a wide range of natural gene networks, and establish design principles for engineering analog gene circuits.
Here, we study CRISPRi repression dynamics in E. coli using our previously developed CcaS/CcaR optogenetic system [6]. We use light-induced sgRNA expression to find that the dose-response curve follows a power-law-like scaling, and that it is very sensitive to small levels of sgRNA, in agreement with previous work [4]. Under typical operating conditions, repression is found to occur within minutes, with expression from the target decreasing within one cell cycle, whereas de-repression requires 2-3 cell cycles. Using a combination of mathematical modeling and experiments, we find that fast repression occurs because sgRNA:dCas9:DNA forms quickly, whereas slow de-repression occurs due to a need for stable sgRNA:dCas9 complexes to be diluted and new DNA to be synthesized. We then use the mathematical model to identify specific system re-designs that allows us to tune and accelerate de- repression dynamics. Finally, we use a combination of modeling and experiments with competing sgRNAs to study how competition for dCas9 (i.e. dCas9 loading) affects system performance. This work should inform future optimizations to CRISPRi system that will allow the reliable and predictable construction of large analog circuits in single cells.

References

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[6] Sebastian R. Schmidl, et al. Refactoring and Optimization of Light-Switchable Escherichia coli Two- Component Systems. ACS Synth. Biol. 3, 820â??831 (2014)