Speaker
Description
Recent advances in cell free transcription-translation (TXTL) systems have renewed interest in quantitative cell-free gene expression modelling. Ordinary Differential Equation (ODE) models can describe TXTL dynamics, enabling users to explore a design space difficult to probe experimentally. A common modelling limitation is the unknown effect of variability in inputs with respect to the desired output. To address this lack of trust in the modelling, robust sensitivity analysis was applied; the results of which are shown here.
A mechanistic model of an E. coli-derived cell-free gene expression system is developed, extending prior formulations\cite{M} to retain the complete reaction network while avoiding quasi-steady state assumptions for fast reversible reactions. The system is described by ODEs derived from the extended stoichiometric and kinetic structure of the reaction network. To assess parameter influence, Sobol sensitivity analysis was performed to produce first- and total-order Sobol indices with respective confidence intervals. These indices identified which inputs would benefit from precise measurement to more efficiently determine key behaviours. One notable result was that model behaviour was highly sensitive to degradation and to the reversible kinetics of the promoter-sigma factor and promoter-RNA polymerase complexes.
This work introduces a customisable framework for statistical analysis of ODE systems, enabling user-defined equations and parameter ranges.
Bibliography
@Article{M,
author={Marshall, Ryan
and Noireaux, Vincent},
title={Quantitative modeling of transcription and translation of an all-E. coli cell-free system},
journal={Scientific Reports},
year={2019},
month={Aug},
day={19},
volume={9},
number={1},
pages={11980},
issn={2045-2322},
doi={10.1038/s41598-019-48468-8},
url={https://doi.org/10.1038/s41598-019-48468-8}
}
