Abstract
Cell-free TX-TL is an increasingly mature and useful platform for prototyping, testing, and engineering biological parts and systems. However, to fully accomplish the promises of synthetic biology, mathematical models are required to facilitate the design and predict the behavior of biological components in cell-free extracts. We review here the latest models accounting for transcription, translation, competition, and depletion of resources as well as genome scale models for lysate-based cell-free TX-TL systems, including their current limitations. These models will have to find ways to account for batch-to-batch variability before being quantitatively predictive in cell-free lysate-based platforms.
Highlights
All the processes required to produce proteins in bacteria can be performed by adding DNA to a cell-free platform
Some of the previously described models take into account the limitation of each resource and include a fixed amount of transcription and translation machineries to predict the impact of resource competition in cell-free (Figure 2A; Siegal-Gaskins et al, 2013; Borkowski et al, 2018; Moore et al, 2018)
The models presented while being able to account for transcription, translation and resource competition from a lack of generalizability due both to variability in experimental conditions as batches can differ greatly, and to scarcity of biochemical work measuring those parameters in cell-free setting as has been estimated from in vivo measurements
Summary
All the processes required to produce proteins in bacteria can be performed by adding DNA to a cell-free platform. ODE Models describing transcription, translation, mRNA, and protein degradation processes at various scales have been successfully used to predict mRNA and protein dynamics in lysate-based systems (Stögbauer et al, 2012; Tuza et al, 2013; Siegal-Gaskins et al, 2014; Nieß et al, 2017; Borkowski et al, 2018; Matsuura et al, 2018; Moore et al, 2018).
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