Functional optimization of gene clusters by combinatorial design and assembly

Michael J. Smanski, Swapnil Bhatia, Dehua Zhao, Yong Jin Park, Lauren B.A. Woodruff, Georgia Giannoukos, Dawn Ciulla, Michele Busby, Johnathan Calderon, Robert Nicol, D. Benjamin Gordon, Douglas Densmore, Christopher A. Voigt

Research output: Contribution to journalArticlepeer-review

188 Scopus citations

Abstract

Large microbial gene clusters encode useful functions, including energy utilization and natural product biosynthesis, but genetic manipulation of such systems is slow, difficult and complicated by complex regulation. We exploit the modularity of a refactored Klebsiella oxytoca nitrogen fixation (nif) gene cluster (16 genes, 103 parts) to build genetic permutations that could not be achieved by starting from the wild-type cluster. Constraint-based combinatorial design and DNA assembly are used to build libraries of radically different cluster architectures by varying part choice, gene order, gene orientation and operon occupancy. We construct 84 variants of the nifUSVWZM operon, 145 variants of the nifHDKY operon, 155 variants of the nifHDKYENJ operon and 122 variants of the complete 16-gene pathway. The performance and behavior of these variants are characterized by nitrogenase assay and strand-specific RNA sequencing (RNA-seq), and the results are incorporated into subsequent design cycles. We have produced a fully synthetic cluster that recovers 57% of wild-type activity. Our approach allows the performance of genetic parts to be quantified simultaneously in hundreds of genetic contexts. This parallelized design-build-test-learn cycle, which can access previously unattainable regions of genetic space, should provide a useful, fast tool for genetic optimization and hypothesis testing.

Original languageEnglish (US)
Pages (from-to)1241-1249
Number of pages9
JournalNature biotechnology
Volume32
Issue number12
DOIs
StatePublished - Dec 1 2014
Externally publishedYes

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