Effective Biophysical Modeling of Cell Free Transcription and Translation Processes

Abstract

Transcription and translation are at the heart of metabolism and signal transduction. In this study, we developed an effective biophysical modeling approach to simulate transcription and translation processes. We tested this approach by simulating the dynamics of two cell free synthetic circuits. First, we considered a simple circuit in which sigma factor 70 induced the expression of green fluorescent protein. This relatively simple case was then followed by a more complex negative feedback circuit in which two control genes were coupled to the expression of a third reporter gene, green fluorescent protein. While many of the model parameters were estimated from previous biophysical literature, the remaining unknown model parameters for each circuit were estimated from messenger RNA (mRNA) and protein measurements using multiobjective optimization. In particular, either the literature parameter estimates were used directly in the model simulations, or characteristic literature values were used to establish feasible ranges for the multiobjective parameter search. Next, global sensitivity analysis was used to determine the influence of individual model parameters on the expression dynamics. Taken together, the effective biophysical modeling approach captured the expression dynamics, including the transcription dynamics, for the two synthetic cell free circuits. While we considered only two circuits here, this approach could potentially be extended to simulate other genetic circuits in both cell free and whole cell biomolecular applications. The model code, parameters, and analysis scripts are available for download under an MIT software license from the Varnerlab GitHub repository.

Footnotes

* Fixed spelling and typos. Rearranged for a better flow.

* https://github.com/varnerlab/Biophysical-TXTL-Model-Code