(59a) Scalable, Accurate, and Systematic Engineering of Synthetic Pathways: Massively Multiplexed DNA Assembly, Next-Gen Sequence Verification, and Model-Guided Design | AIChE

(59a) Scalable, Accurate, and Systematic Engineering of Synthetic Pathways: Massively Multiplexed DNA Assembly, Next-Gen Sequence Verification, and Model-Guided Design

Authors 

Woodruff, L. B. A. - Presenter, Broad Institute of MIT and Harvard
Mikkelsen, T., Broad Institute of MIT and Harvard
Smanski, M. J., Massachusetts Institute of Technology
Gordon, D. B., Broad Institute of MIT and Harvard
Voigt, C. A., Massachusetts Institute of Technology
Nicol, R., Broad Institute of MIT and Harvard

We have developed methods for DNA assembly, whole-construct sequencing, and (re-)design algorithms for large-scale optimization of multi-gene synthetic systems. In this work we applied these approaches to engineer a 16-gene fully synthetic and modular nitrogen-fixing device (100 parts, 23 kb). This synthetic nitrogen fixation (nif) gene cluster converts atmospheric nitrogen into ammonia, which is a critical process for global agricultural productivity. From characterized libraries of parts, we assembled >55,000 sequence-verified cistron modules for the nif gene cluster. This is a 100-1,000-fold improvement in library size over our and comparable previous studies. Approximately 1040 unique nif gene clusters can be built from this library. Additionally, we sequenced 7.5 million nif cistrons in total to quantify assembly error modes and frequencies. From these sequenced-verified cistrons, we used contact-free automated assembly to build permuted whole gene cluster designs. The gene cluster part substitutions and combinations were designed using algorithms based on design of experiments methodologies. In total we built, sequenced, tested, and modeled ~5 MB of systematically permuted gene cluster constructs using these approaches. We engineered improved nitrogen-fixing activity by tuning T7 promoter strength driving expression of each gene or operon flanked by strong terminators within the gene cluster. Multivariate statistical models were developed from these data for model-guided redesign and iterative engineering of the nif gene cluster. We believe the methods and strategies demonstrated here will accelerate mining and transferring biological functions between engineered systems and expand the complexity of synthetic systems that can be written, engineered, and optimized.