Abstract
Cell-free gene expression systems present an alternative approach to synthetic biology, where biological gene expression is harnessed inside non-living, in vitro biochemical reactions. Taking advantage of a plethora of recent experimental innovations, they easily overcome certain challenges for computer-aided biological design. For instance, their open nature renders all their components directly accessible, greatly facilitating model construction and validation. At the same time, these systems present their own unique difficulties, such as limited reaction lifetimes and lack of homeostasis. In this Perspective, I propose that cell-free systems are an ideal proving ground to test rational biodesign strategies, as demonstrated by a small but growing number of examples of model-guided, forward engineered cell-free biosystems. It is likely that advances gained from this approach will contribute to our efforts to more reliably and systematically engineer both cell-free as well as living cellular systems for useful applications.
Highlights
A basic aim of synthetic biology is to design and construct biological systems which perform a given function
In contrast to non-biological engineering, synthetic biological systems are open to the possibility of evolutionary design (Arnold, 1998), where function is obtained through directed evolutionary screens. It is still an open question as to whether or not a purely rational engineering approach can be successfully applied to engineer complex biomolecular systems (Davies, 2019)
In this Perspective I would like to focus on a third contribution, and suggest that they offer an ideal proving ground to test the approach of rational computer-aided biodesign as applied to biomolecular systems (Figure 1). They present features which overcome some of the difficulties associated with engineering living cells, and so can be used to more develop and calibrate mechanistic models, as well as generate sufficient data for machine learning approaches. To understand their strengths and weaknesses in the context of synthetic biology, it is first important to consider the differences between cell-free and living cellular systems
Summary
A basic aim of synthetic biology is to design and construct biological systems which perform a given function. Cell-free systems (Garenne and Noireaux, 2019) can contribute in several ways to improve the design process of synthetic biological systems, which span scales from the molecular (genetic regulatory elements, proteins, enzymes), to the systemic (gene regulatory and metabolic networks), and all the way to the extracellular levels (synthetic cells, communication, self-assembly) They can accelerate DBTL cycles through rapid prototyping (Chappell et al, 2013; Niederholtmeyer et al, 2015; Takahashi et al, 2015). In this Perspective I would like to focus on a third contribution, and suggest that they offer an ideal proving ground to test the approach of rational computer-aided biodesign as applied to biomolecular systems (Figure 1) They present features which overcome some of the difficulties associated with engineering living cells, and so can be used to more develop and calibrate mechanistic models, as well as generate sufficient data for machine learning approaches. To understand their strengths and weaknesses in the context of synthetic biology, it is first important to consider the differences between cell-free and living cellular systems
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