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CRISPR RNA-guided integrases for high-efficiency, multiplexed bacterial genome engineering

Nature Biotechnology volume 39, pages 480–489 (2021)Cite this article

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Abstract

Existing technologies for site-specific integration of kilobase-sized DNA sequences in bacteria are limited by low efficiency, a reliance on recombination, the need for multiple vectors, and challenges in multiplexing. To address these shortcomings, we introduce a substantially improved version of our previously reported Tn7-like transposon from Vibrio cholerae, which uses a Type I-F CRISPR–Cas system for programmable, RNA-guided transposition. The optimized insertion of transposable elements by guide RNA–assisted targeting (INTEGRATE) system achieves highly accurate and marker-free DNA integration of up to 10 kilobases at ~100% efficiency in bacteria. Using multi-spacer CRISPR arrays, we achieved simultaneous multiplexed insertions in three genomic loci and facile, multi-loci deletions by combining orthogonal integrases and recombinases. Finally, we demonstrated robust function in biomedically and industrially relevant bacteria and achieved target- and species-specific integration in a complex bacterial community. This work establishes INTEGRATE as a versatile tool for multiplexed, kilobase-scale genome engineering.

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Fig. 1: Streamlined single-plasmid system for RNA-guided DNA integration.
Fig. 2: INTEGRATE supports high-efficiency insertion of large (10-kb) genetic payloads.
Fig. 3: Orthogonal INTEGRATE systems facilitate multiple, iterative insertions.
Fig. 4: Multi-spacer CRISPR arrays direct single-step multiplexed insertions.
Fig. 5: Robust and highly accurate INTEGRATE activity in additional Gram-negative bacteria.

Data availability

NGS data are available in the NCBI Sequence Read Archive (BioProject accession code PRJNA668381). Published genomes used for analyses were obtained from the NCBI (accessions codes CP001509.3, U00096.3, CP009273.1 and AE015451.2). Datasets generated and analyzed in the current study, as well as custom scripts used for the described data analyses, are available from the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

Custom Python scripts used for the described NGS data analyses are available online via GitHub (https://github.com/sternberglab/Vo_etal_2020). The INTEGRATE guide RNA design tool and associated documentation are available online via GitHub (https://github.com/sternberglab/INTEGRATE-guide-RNA-tool).

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Acknowledgements

We thank N. Jaber for laboratory support, J. Bondy-Denomy for discussions, L.F. Landweber for qPCR instrument access, J. Mohabir for assistance with NGS read alignment, the JP Sulzberger Columbia Genome Center for NGS support and M.L. Smith, I. Oussenko and the Genomics Technology Laboratory at the Icahn School of Medicine at Mount Sinai for SMRT sequencing. H.H.W. acknowledges funding support for this work from the National Science Foundation (MCB-1453219), the National Institutes of Health (1U01GM110714 and 1R01AI132403), the Office of Naval Research (N00014-17-1-2353) and the Burroughs Wellcome Fund (PATH1016691). C.R. is supported by a Junior Fellows Scholarship from the Simons Society of Fellows. S.H.S. acknowledges a generous startup package from the Columbia University Irving Medical Center Dean’s Office and the Vagelos Precision Medicine Fund.

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Authors and Affiliations

  1. Department of Pharmacology, Columbia University, New York, NY, USA

    Phuc Leo H. Vo

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

    Carlotta Ronda & Harris H. Wang

  3. Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA

    Sanne E. Klompe, Christopher Acree & Samuel H. Sternberg

  4. Department of Biological Sciences, Columbia University, New York, NY, USA

    Ethan E. Chen

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

    Harris H. Wang

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  1. Phuc Leo H. Vo
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Contributions

P.L.H.V. and S.H.S. conceived of and designed the project, with input from C.R. and H.H.W. P.L.H.V. performed experiments and analyzed data for most E. coli experiments. C.R. performed experiments and analyzed data in K. oxytoca, P. putida and complex bacterial communities, with input from H.H.W. S.E.K. performed target immunity, ShoINT and random fragmentation NGS experiments. E.E.C. helped with cloning and transposition experiments. C.A. assisted with computational analyses of NGS data and the guide RNA design algorithm. P.L.H.V., S.H.S. and all other authors discussed the data and wrote the manuscript.

Corresponding author

Correspondence to Samuel H. Sternberg.

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Competing interests

P.L.H.V., S.E.K. and S.H.S. are inventors on patents and patent applications related to CRISPR–Cas systems and uses thereof. H.H.W. is a scientific advisor to SNIPR Biome. S.H.S. is a co-founder and scientific advisor to Dahlia Biosciences and an equity holder in Dahlia Biosciences and Caribou Biosciences.

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Peer review information Nature Biotechnology thanks Joseph Bondy-Denomy and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Vo, P.L.H., Ronda, C., Klompe, S.E. et al. CRISPR RNA-guided integrases for high-efficiency, multiplexed bacterial genome engineering. Nat Biotechnol 39, 480–489 (2021). https://doi.org/10.1038/s41587-020-00745-y

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