4.7 Article

Experimentally Validated Model Enables Debottlenecking of in Vitro Protein Synthesis and Identifies a Control Shift under in Vivo Conditions

Journal

ACS SYNTHETIC BIOLOGY
Volume 6, Issue 10, Pages 1913-1921

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acssynbio.7b00117

Keywords

ribosomes; translation factors; translation rate; cell-free synthetic biology

Funding

  1. Bundesministerium fur Bildung and Forschung (BMBF) [FKZ031A157]
  2. European Union [289326, KBBE.2011.3.6-03]

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Cell-free (in vitro) protein synthesis (CFPS) systems provide a versatile tool that can be used to investigate different aspects of the transcription-translation machinery by reducing cells to the basic functions of protein formation. Recent improvements in reaction stability and lysate preparation offer the potential to expand the scope of in vitro biosynthesis from a research tool to a multifunctional and versatile platform for protein production and synthetic biology. To date, even the best-performing CFPS systems are drastically slower than in vivo references. Major limitations are imposed by ribosomal activities that progress in an order of magnitude slower on the mRNA template. Owing to the complex nature of the ribosomal machinery, conventional trial and error experiments only provide little insight into how the desired performance could be improved. By applying a DNA-sequence-oriented mechanistic model, we analyzed the major differences between cell-free in vitro and in vivo protein synthesis. We successfully identified major limiting elements of in vitro translation, namely the supply of ternary complexes consisting of EFTu and tRNA. Additionally, we showed that diluted in vitro systems suffer from reduced ribosome numbers. On the basis of our model, we propose a new experimental design predicting 90% increased translation rates, which were well achieved in experiments. Furthermore, we identified a shifting control in the translation rate, which is characterized by availability of the ternary complex under in vitro conditions and the initiation of translation in a living cell. Accordingly, the model can successfully be applied to sensitivity analyses and experimental design.

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