Towards High-Throughput Physiochemical Optimization of the Vibrio Natriegens Cell-Free Protein Synthesis Platform | AIChE

Towards High-Throughput Physiochemical Optimization of the Vibrio Natriegens Cell-Free Protein Synthesis Platform

Authors 

Cabezas, M. - Presenter, Northwestern University
Jewett, M., Northwestern University
Gordon, B., MIT / Broad Institute
Des Soye, B. J., Northwestern University
There is a growing interest in developing cell-free protein synthesis (CFPS) platforms derived from non-model bacterial hosts in order to (i) accelerate biological design through prototyping genetic parts and (ii) access the production of novel biomolecules. One such CFPS platform is derived from Vibrio natriegens (Vnat), which has potential benefit in making antimicrobial peptides. However, development efforts remain challenging because this requires extensive characterization and optimization of biomolecular processes to make these platforms robust and high-yielding. In addition, most successful platforms utilize phosphoenolpyruvate and other high-energy phosphate bond donors to fuel CFPS which are costly energy substrates whose byproducts poison the reaction. In this work, we try to address these challenges using computational-guided experimentation. First, in an effort to identify cost-effective alternatives, we screened several energy substrates derived from simple sugars and other non-phosphorylated glycolytic metabolites and identified substrate candidates for further reagent optimization. Next, we applied a design of experiments (DoE) approach in combination with a high-throughput automated methodology to rapidly test and screen reaction conditions to optimize the Vnat CFPS platform. Specifically, we tested distinct combinations of CFPS reagents predicted by the DoE algorithm using an acoustic liquid handler system to rapidly generate data to identify best ways to minimize reagent and extract use. We find new physiochemical conditions that increase the relative production cost (g protein produced/$ reagents) relative to the conventional approach. Our work offers a method to rapidly explore a complex parameter space to enable a detailed understanding of how the Vnat platform utilizes resources. We anticipate that this approach can be generalized to develop novel non-model bacterial hosts as chassis for CFPS and accelerate applications in biotechnology.