synthesis-infectious-bacteriophages-an-e-coli-based-cell-free

Synthesis of Infectious Bacteriophages in an <em>E. coli-</em>based Cell-free Expression System

A new generation of cell-free transcription-translation (TXTL) systems, engineered to have a greater versatility and modularity, provide novel ...

Since the pioneering work of Plaxco, Simons, and Baker, it is now well known that the rates of protein folding strongly correlate with the average sequence separation (absolute contact order (ACO)) of native contacts. In spite of multitude of papers, our understanding to the basis of the relation between folding speed and ACO is still lacking. We model the transition state as a gaussian polymer chain decorated with weak springs between native contacts while the unfolded state is modeled as a gaussian chain only. Using these hamiltonians, our perturbative calculation explicitly shows folding speed and ACO are linearly related when only the first order term in the series is considered. However, to the second order, we notice the existence of two new topological metrics, termed COC(1) and COC(2) (COC stands for contact order correction). These additional correction terms are needed to properly account for the entropy loss due to overlapping (nested or linked) loops that are not well described by simple addition of entropies in ACO. COC(1) and COC(2) are related to fluctuations and correlations among different sequence separations. The new metric combining ACO, COC(1), and COC(2) improves folding speed dependence on native topology when applied to three different databases: (i) two-state proteins with only α∕β and β proteins, (ii) two-state proteins (α∕β, β and purely helical proteins all combined), and (iii) master set (multi-state and two-state) folding proteins. Furthermore, the first principle calculation provides us direct physical insights to the meaning of the fit parameters. The coefficient of ACO, for example, is related to the average strength of the contacts, while the constant term is related to the protein folding speed limit. With the new scaling law, our estimate of the folding speed limit is in close agreement with the widely accepted value of 1 μs observed in proteins and RNA. Analyzing an exhaustive set (7367) of monomeric proteins from protein data bank, we find our new topology based metric (combining ACO, COC(1), and COC(2)) scales as N(0.54), N being the number of amino acids in a protein. This is in remarkable agreement with a previous argument based on random systems that predict protein folding speed depends on exp (-N(0.5)). The first principle calculation presented here provides deeper insights to the role of topology in protein folding and unifies many parallel arguments, seemingly disconnected, demonstrating the existence of universal mechanism in protein folding kinetics that can be understood from simple polymer physics based principles.

Why and how does native topology dictate the folding speed of a protein?

We report on and provide a detailed characterization of the performance and properties of a recently developed, all Escherichia coli, cell-free transcription and translation system. Gene expression is entirely based on the endogenous translation components and transcription machinery provided by an E. coli cytoplasmic extract, thus expanding the repertoire of regulatory parts to hundreds of elements. We use a powerful metabolism for ATP regeneration to achieve more than 2 mg/mL of protein synthesis in batch mode reactions, and more than 6 mg/mL in semicontinuous mode. While the strength of cell-free expression is increased by a factor of 3 on average, the output signal of simple gene circuits and the synthesis of entire bacteriophages are increased by orders of magnitude compared to previous results. Messenger RNAs and protein degradation, respectively tuned using E. coli MazF interferase and ClpXP AAA+ proteases, are characterized over a much wider range of rates than the first version of the cell-free toolbox. This system is a highly versatile cell-free platform to construct complex biological systems through the execution of DNA programs composed of synthetic and natural bacterial regulatory parts.

Article	Year
Why and how does native topology dictate the folding speed of a protein? The Journal of chemical physics\| PubMed ID: 23206039	2012
The All E. coli TX-TL Toolbox 2.0: A Platform for Cell-Free Synthetic Biology. ACS synthetic biology\| PubMed ID: 26818434	2016

Mark Rustad

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