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Fast and efficient template-mediated synthesis of genetic variants

Nature Methods volume 20, pages 841–848 (2023)Cite this article

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Abstract

Efficient methods for the generation of specific mutations enable the study of functional variations in natural populations and lead to advances in genetic engineering applications. Here, we present a new approach, mutagenesis by template-guided amplicon assembly (MEGAA), for the rapid construction of kilobase-sized DNA variants. With this method, many mutations can be generated at a time to a DNA template at more than 90% efficiency per target in a predictable manner. We devised a robust and iterative protocol for an open-source laboratory automation robot that enables desktop production and long-read sequencing validation of variants. Using this system, we demonstrated the construction of 31 natural SARS-CoV2 spike gene variants and 10 recoded Escherichia coli genome fragments, with each 4 kb region containing up to 150 mutations. Furthermore, 125 defined combinatorial adeno-associated virus-2 cap gene variants were easily built using the system, which exhibited viral packaging enhancements of up to 10-fold compared with wild type. Thus, the MEGAA platform enables generation of multi-site sequence variants quickly, cheaply, and in a scalable manner for diverse applications in biotechnology.

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Fig. 1: The MEGAA method for DNA variant synthesis.
Fig. 2: MEGAA cycling, optimization, modeling and automation.
Fig. 3: Generation of SARS-CoV2 spike gene variants and E. coli codon compressed recoded fragments using MEGAA.
Fig. 4: AAV2 cap gene engineering using MEGAAtron.

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Data availability

Processed packaging efficiency data in a previous study were obtained from GitHub (https://github.com/churchlab/AAV_fitness_landscape) to identify insertion sites with potential enhanced packaging efficiency for AAV variants design and correlate with packaging efficiency obtained in this study. The sequencing data generated in this study have been submitted to the NCBI BioProject database under accession number PRJNA834093. Source data are provided with this paper.

Code availability

Scripts used for Oxford Nanopore sequencing data analysis can be accessed at https://github.com/wanglabcumc/MEGAAdt.

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Acknowledgements

The authors thank G. Urtecho, J. Qian and L. Huang for technical support, and K. Beiswenger and other members of the Wang laboratory for advice and comments on the manuscript. H.H.W. acknowledges funding support from the NSF (MCB-2032259), DOE (47879/SCW1710), NIH (1R01DK118044, 1R01EB031935, 2R01AI132403, 75N93021C00014), ONR (N00014-17-1-2353), Burroughs Wellcome Fund (1016691), Irma T. Hirschl Trust and Schaefer Research Award.

Author information

Author notes

  1. These authors contributed equally: Liyuan Liu, Yiming Huang.

Authors and Affiliations

  1. Department of Systems Biology, Columbia University, New York, NY, USA

    Liyuan Liu, Yiming Huang & Harris H. Wang

  2. Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY, USA

    Yiming Huang

  3. Department of Pathology and Cell Biology, Columbia University, New York, NY, USA

    Harris H. Wang

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  1. Liyuan Liu
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Contributions

L.L. and H.H.W. developed the initial concept; L.L. and Y.H. performed the experiments and analyzed the data with input from H.H.W.; Y.H. developed the software and genomic data analysis pipeline. L.L. and H.H.W. wrote the manuscript. All other authors discussed the results and approved the manuscript.

Corresponding author

Correspondence to Harris H. Wang.

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Competing interests

H.H.W. is a scientific advisor of SNIPR Biome, Kingdom Supercultures, Fitbiomics, Arranta Bio, VecX Biomedicines, Genus PLC, and a scientific co-founder of Aclid, all of which are not involved in the study. A patent application on methods described in this paper has been filed by Columbia University. All other authors have no competing interests.

Peer review

Peer review information

Nature Methods thanks Kaihang Wang, Hongzhou Gu, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Lei Tang and Madhura Mukhopadhyay, in collaboration with the Nature Methods team.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–18 and Supplementary Methods.

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Supplementary Tables

Supplementary Tables 1–7.

Source data

Source Data Fig. 1

Unprocessed gel images of Fig. 1b and Supplementary Fig. 3b.

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Liu, L., Huang, Y. & Wang, H.H. Fast and efficient template-mediated synthesis of genetic variants. Nat Methods 20, 841–848 (2023). https://doi.org/10.1038/s41592-023-01868-1

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