Mechanistic Modeling of CRISPRi/CRISPRa

This repository contains supplementary information for the paper:

Scott, Helen, Alessandro Occhialini, Scott C. Lenaghan, and Jacob Beal. 2024. "Simulations Predict Stronger CRISPRi Transcriptional Repression in Plants for Identical than Heterogeneous Target Sites." bioRxiv. https://doi.org/10.1101/2024.04.22.590637

If you make use of any of the contents of this repository, please cite this paper.

Abstract

Plant synthetic biologists have been working to adapt the CRISPRa and CRISPRi promoter regulation methods for applications such as improving crops or installing other valuable pathways. With other organisms, strong transcriptional control has typically required multiple gRNA target sites, which poses a critical engineering choice between heterogeneous sites, which allow each gRNA to target existing locations in a promoter, and identical sites, which typically require modification of the promoter. Here we investigate the consequences of this choice for CRISPRi plant promoter regulation via simulation-based analysis, using model parameters based on single gRNA regulation and constitutive promoters in N. benthamiana. Using models of 2 to 6 gRNA target sites to compare heterogeneous versus identical sites for tunability, sensitivity to parameter values, and sensitivity to cell-to-cell variation, we find that identical gRNA target sites are predicted to yield far more effective transcriptional repression than heterogeneous sites.

Contents of Repository

• Python code that generates SBOL models each potential promoter architecture.
• Python code to export SBOL models into ODE equations in LaTeX and executable ODE simulation models in MATLAB.
• Simulation runners for experimentation with the models.
• Results and figures generated from these simulations.

Running the code

How to Make a Circuit Model

The routines for building SBOL circuit components are in sbol/builders.py. Import the module and run via a script like sbol/make_sbol_models.py. The resulting circuit models we generated are saved in sbol/gRNA_models.nt.

Generating LaTeX Equations

The routines for generating LaTeX from SBOL circuits are in sbol/latex_generation.py. Import the module and run via a script like sbol/sbol_to_latex.py. The generated LaTeX equations can be embedded in a LaTeX document like equations/view_generated_equations.tex. The resulting LaTeX equations we generated are saved in equations/generated_equations.tex and are viewable in equations/view_generated_equations.pdf.

Generating MATLAB Code

The routines for generating MATLAB code from SBOL circuits are in sbol/matlab_generation.py. Import the module and run via a script like sbol/sbol_to_matlab.py. The resulting MATLAB models we generated are saved in the models/ directory.