Precise determination of input-output mapping for multimodal gene circuits using data from transient transfection

Area of Science:

• Synthetic Biology
• Molecular Systems Biology
• Biotechnology

Background:

• Gene circuit input/output (I/O) mapping is crucial for understanding natural and synthetic systems.
• Stable genetic integration is ideal for characterizing synthetic circuits but is time-consuming.
• Transient transfection is rapid but generates noisy data, questioning its relevance for I/O mapping.

Purpose of the Study:

• To develop a data processing workflow for extracting precise I/O mapping from transient transfection flow cytometry data.
• To validate the workflow's accuracy by comparing results from transient transfection with stable integration simulations.
• To enable rapid characterization of synthetic gene circuits using readily available, albeit noisy, experimental data.

Main Methods:

• Developed the Peakfinder algorithm for flow cytometry data (PFAFF) workflow.
• Utilized multivariate modes of input/output expression from binned flow cytometry data.
• Simulated flow cytometry data for seven multi-node circuit architectures under stable and transient conditions.

Main Results:

• The PFAFF workflow accurately extracts I/O mapping from simulated transient transfection data.
• Results from transient transfection data closely approximated those from simulated stable integration.
• The method proved effective even for complex bi-modal circuit architectures.

Conclusions:

• The PFAFF workflow provides a robust method for determining gene network I/O mapping from noisy transient transfection data.
• This approach significantly accelerates the characterization of synthetic gene circuits.
• The method offers a reliable approximation of ground truth I/O relationships, bridging the gap between rapid transfection and stable integration.