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Synthetic biology outside the cell: linking computational tools to cell-free systems.

Lewis DD, Villarreal FD, Wu F, Tan C - Front Bioeng Biotechnol (2014)

Bottom Line: Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems.At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems.We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

View Article: PubMed Central - PubMed

Affiliation: Integrative Genetics and Genomics, University of California Davis , Davis, CA , USA ; Department of Biomedical Engineering, University of California Davis , Davis, CA , USA.

ABSTRACT
As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

No MeSH data available.


Models of ribosome binding sites (RBS) and their potential applications for in vitro systems. (A) A thermodynamic model for the calculation of RBS strength based on its sequence. The RBS calculator (Salis, 2011) is based on the calculation of the mRNA–ribosome binding energy (ΔGtotal). The sequence upstream of the Shine–Dalgarno (SD) site determines a penalty score ΔGstandby that is due to the work required to unfold secondary structures in this region. (B) The strengths of several RBS (controlling translation of GFP) were comparable when assayed both in vivo and in vitro [different RBS-GFP constructs in the x-axis, relative fluorescence (au) in the y-axis]. Figures modified with permission from Espah Borujeni et al. (2014) and Chappell et al. (2013).
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Figure 8: Models of ribosome binding sites (RBS) and their potential applications for in vitro systems. (A) A thermodynamic model for the calculation of RBS strength based on its sequence. The RBS calculator (Salis, 2011) is based on the calculation of the mRNA–ribosome binding energy (ΔGtotal). The sequence upstream of the Shine–Dalgarno (SD) site determines a penalty score ΔGstandby that is due to the work required to unfold secondary structures in this region. (B) The strengths of several RBS (controlling translation of GFP) were comparable when assayed both in vivo and in vitro [different RBS-GFP constructs in the x-axis, relative fluorescence (au) in the y-axis]. Figures modified with permission from Espah Borujeni et al. (2014) and Chappell et al. (2013).

Mentions: Ribosomal binding site strengths can be predicted using multiple tools, including RBS calculator (Salis, 2011) (Figure 8A), UTR Designer (Seo et al., 2013), and RBSDesigner (Bujara et al., 2010). These tools compute differences of free energy between the folded secondary structures of a RBS (representing the state when mRNA is not bound to ribosomes) and its unfolded state (bound to the ribosome). The relative functionality and limitations of these RBS models were recently reviewed elsewhere (Reeve et al., 2014).


Synthetic biology outside the cell: linking computational tools to cell-free systems.

Lewis DD, Villarreal FD, Wu F, Tan C - Front Bioeng Biotechnol (2014)

Models of ribosome binding sites (RBS) and their potential applications for in vitro systems. (A) A thermodynamic model for the calculation of RBS strength based on its sequence. The RBS calculator (Salis, 2011) is based on the calculation of the mRNA–ribosome binding energy (ΔGtotal). The sequence upstream of the Shine–Dalgarno (SD) site determines a penalty score ΔGstandby that is due to the work required to unfold secondary structures in this region. (B) The strengths of several RBS (controlling translation of GFP) were comparable when assayed both in vivo and in vitro [different RBS-GFP constructs in the x-axis, relative fluorescence (au) in the y-axis]. Figures modified with permission from Espah Borujeni et al. (2014) and Chappell et al. (2013).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4260521&req=5

Figure 8: Models of ribosome binding sites (RBS) and their potential applications for in vitro systems. (A) A thermodynamic model for the calculation of RBS strength based on its sequence. The RBS calculator (Salis, 2011) is based on the calculation of the mRNA–ribosome binding energy (ΔGtotal). The sequence upstream of the Shine–Dalgarno (SD) site determines a penalty score ΔGstandby that is due to the work required to unfold secondary structures in this region. (B) The strengths of several RBS (controlling translation of GFP) were comparable when assayed both in vivo and in vitro [different RBS-GFP constructs in the x-axis, relative fluorescence (au) in the y-axis]. Figures modified with permission from Espah Borujeni et al. (2014) and Chappell et al. (2013).
Mentions: Ribosomal binding site strengths can be predicted using multiple tools, including RBS calculator (Salis, 2011) (Figure 8A), UTR Designer (Seo et al., 2013), and RBSDesigner (Bujara et al., 2010). These tools compute differences of free energy between the folded secondary structures of a RBS (representing the state when mRNA is not bound to ribosomes) and its unfolded state (bound to the ribosome). The relative functionality and limitations of these RBS models were recently reviewed elsewhere (Reeve et al., 2014).

Bottom Line: Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems.At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems.We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

View Article: PubMed Central - PubMed

Affiliation: Integrative Genetics and Genomics, University of California Davis , Davis, CA , USA ; Department of Biomedical Engineering, University of California Davis , Davis, CA , USA.

ABSTRACT
As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

No MeSH data available.