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Functional optimization of gene clusters by combinatorial design and assembly

Nature Biotechnology volume 32, pages 1241–1249 (2014)Cite this article

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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.

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Figure 1: Combinatorial design and construction of gene cluster libraries.
Figure 2: Screening results for the nif cluster optimization in K. oxytoca.
Figure 3: Transcriptomic analysis of the optimized refactored clusters and nifUSVWZM library.
Figure 4: Transfer of refactored nif clusters into E. coli MG1655.

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Acknowledgements

M.J.S., D.Z., J.C., R.N., D.B.G. and C.A.V. are supported by the US Defense Advanced Research Projects Agency (DARPA) Living Foundries grant HR0011-12-C-0067 and the US National Science Foundation Synthetic Biology Engineering Research Center (SynBERC) through grant SA5284-11210 and are also supported by the Institute for Collaborative Biotechnologies through contract W911NF-09-0001 from the US Army Research Office. The content of the information does not necessarily reflect the position or the policy of the US government, and no official endorsement should be inferred. S.B. and D.D. are supported by DARPA Living Foundries grant HR0011-12-C-0067. M.J.S. is an HHMI Fellow of the Damon Runyon Cancer Research Foundation, DRG-2129-12. Y.P. is supported by the Samsung Scholarship.

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Authors and Affiliations

  1. Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Michael J Smanski, Dehua Zhao, YongJin Park, Lauren B A Woodruff, Johnathan Calderon, D Benjamin Gordon & Christopher A Voigt

  2. Electrical and Computer Engineering Department, Boston University, Boston, Massachusetts, USA

    Swapnil Bhatia & Douglas Densmore

  3. Broad Technology Labs, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    Lauren B A Woodruff, Georgia Giannoukos, Dawn Ciulla, Michele Busby, Robert Nicol, D Benjamin Gordon & Christopher A Voigt

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Contributions

M.J.S., D.Z. and C.A.V. conceived and designed the experiments and wrote the manuscript. M.J.S. performed the nifUSVWZM, monocistronic and RBS library construction and analysis. D.D. and S.B. performed the clustering analysis, wrote the design files and analyzed data. D.Z. constructed and analyzed the nifHDKY, nifENJ and complete cluster library. Y.P., D.B.G., M.B., G.G., R.N. and D.C. performed the RNA-seq experiments and analysis. L.B.A.W. and J.C. performed experiments.

Corresponding author

Correspondence to Christopher A Voigt.

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Competing interests

S.B. and D.D. are co-founders of Lattice Automation, Inc., a company that produces biodesign automation software.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–27, Supplementary Tables 1 and 2 and Supplementary Notes 1–11 (PDF 9314 kb)

Supplementary Data File 1.eug

Eugene file for nifUSVWZM libray design (XLS 28 kb)

Supplementary Data File 2.eug

Eugene file for newly identified rules for refactored nif cluster (XLS 42 kb)

Supplementary Data File 3.xlsx

Characterization data for nifUSVWZM library (XLSX 6348 kb)

Supplementary Data File 4.xlsx

Characterization data for nifHDKY, nifENJ, and full cluster libraries (XLSX 33 kb)

Supplementary Data File 5.xlsx

Characterization data for 16-gene monocistronic library (XLSX 69 kb)

Supplementary Data File 6.xlsx

Characterization data for 16-gene RBS swapping library (XLSX 42 kb)

Supplementary Data File 7.eug

Eugene file for 16-gene monocistronic library (XLS 27 kb)

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Smanski, M., Bhatia, S., Zhao, D. et al. Functional optimization of gene clusters by combinatorial design and assembly. Nat Biotechnol 32, 1241–1249 (2014). https://doi.org/10.1038/nbt.3063

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