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Recording gene expression order in DNA by CRISPR addition of retron barcodes

Nature volume 608, pages 217–225 (2022)Cite this article

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Abstract

Biological processes depend on the differential expression of genes over time, but methods to make physical recordings of these processes are limited. Here we report a molecular system for making time-ordered recordings of transcriptional events into living genomes. We do this through engineered RNA barcodes, based on prokaryotic retrons1, that are reverse transcribed into DNA and integrated into the genome using the CRISPR–Cas system2. The unidirectional integration of barcodes by CRISPR integrases enables reconstruction of transcriptional event timing based on a physical record through simple, logical rules rather than relying on pretrained classifiers or post hoc inferential methods. For disambiguation in the field, we will refer to this system as a Retro-Cascorder.

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Fig. 1: Cas1–Cas2 integrates retron RT-DNA.
Fig. 2: Diversification of retron-based barcodes.
Fig. 3: Mechanism of RT-DNA spacer acquisition.
Fig. 4: Temporal recordings of gene expression.
Fig. 5: Modelling the limits of retron recording.

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Data availability

All data supporting the findings of this study are available within the article and its Supplementary Information or will be made available from the authors on request. Sequencing data associated with this study are available in the NCBI Sequence Read Archive (PRJNA838025).

Code availability

Custom code to process and analyse data from this study is available on GitHub (https://github.com/Shipman-Lab/Spacer-Seq).

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Acknowledgements

Work was supported by funding from the Simons Foundation Autism Research Initiative (SFARI) Bridge to Independence Award Program, the Pew Biomedical Scholars Program, the NIH/NIGMS (1DP2GM140917-01) and the UCSF Program for Breakthrough Biomedical Research. S.L.S. is a Chan Zuckerberg Biohub investigator and acknowledges additional funding support from the L.K. Whittier Foundation. S.K.L. was supported by an NSF Graduate Research Fellowship (2034836). S.C.L. was supported by a Berkeley Fellowship for Graduate Study. We thank K. Claiborn for editorial assistance.

Author information

Authors and Affiliations

  1. Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA

    Santi Bhattarai-Kline, Sierra K. Lear, Chloe B. Fishman, Santiago C. Lopez & Seth L. Shipman

  2. Graduate Program in Bioengineering, University of California, San Francisco and Berkeley, San Francisco, CA, USA

    Sierra K. Lear & Santiago C. Lopez

  3. Department of Neurobiology, Duke University Medical Center, Durham, NC, USA

    Elana R. Lockshin

  4. Department of Genetics, Harvard Medical School, Boston, MA, USA

    Max G. Schubert & George M. Church

  5. Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA

    Max G. Schubert & George M. Church

  6. Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA

    Jeff Nivala

  7. Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA

    Seth L. Shipman

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Contributions

S.L.S. conceived the study with J.N. and G.M.C. contributing. S.B.-K. and S.L.S. designed experiments and analysed all data. Contributions to data collection were made by S.K.L. (Extended Data Fig. 4), C.B.F. (Extended Data Fig. 5) and S.L.S. (Figs. 1c,e and 3b–e). S.B.-K. collected all other data. E.R.L., M.G.S. and S.C.L. performed preliminary experiments not included in the figures. S.B.-K. performed the computational modelling of recordings. S.B.-K. wrote the manuscript with input from all co-authors.

Corresponding author

Correspondence to Seth L. Shipman.

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Competing interests

S.L.S., G.M.C., M.G.S. and J.N. are named inventors on a patent application assigned to Harvard College, “Method of recording multiplexed biological information into a CRISPR array using a retron” (US20200115706A1).

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Nature thanks Channabasavaiah Gurumurthy and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Accompaniment to Figure 1.

a, Hypothetical Eco1 wild-type ncRNA-linked RT-DNA structure. b, Hypothetical Eco1 v32 ncRNA-linked RT-DNA structure and hypothetical duplexed RT-DNA prespacer structure. Nucleotides that are altered from wild-type Eco1 are shown in orange. c, Hypothetical Eco1 v35 ncRNA-linked RT-DNA structure and hypothetical duplexed RT-DNA prespacer structure. Nucleotides that are altered from wild-type Eco1 are shown in green.

Extended Data Fig. 2 Accompaniment to Figure 2.

Hypothetical barcoded Eco1 v35 ncRNA-linked RT-DNA structure and hypothetical duplexed RT-DNA prespacer structure. Bases used to barcode retrons are shown in red.

Extended Data Fig. 3 Accompaniment to Figure 3.

a, Hypothetical wild-type Eco4 ncRNA-linked RT-DNA structure. ExoVII-dependent RT-DNA cleavage site is shown as a red slash. b, Eco4-derived spacer sequences and orientations. Bases are coloured to match Figure 3f. c, Proportion of Eco4-derived spacers in each orientation. Open circles are individual biological replicates.

Extended Data Fig. 4 Change in YFP fluorescence when expressed using inducible promoters.

The y-axis shows fluorescence (in arbitrary units) normalized to culture density (OD600).

Extended Data Fig. 5 Growth curves (upper plot) and max growth rates (lower plot) of E. coli with different combinations of retron recording components and inducers.

In growth curve plots the solid line is the mean OD600 of three biological replicates, with dotted lines showing the standard deviation. In maximum growth rate plots, each symbol is a single biological replicate. Bars show the mean and standard deviation. Statistically significant differences in maximum growth rate, as calculated by Tukey’s multiple comparison’s test, are highlighted. a, Growth kinetics of E. coli with different combinations of retron recording plasmids, all without inducers. b, Growth kinetics of E. coli with recording plasmid pSBK.079, with and without inducers. c, Growth kinetics of E. coli with signal plasmid pSBK.134, with and without inducers. Only one biological replicate is present in condition 'pSBK.134 + aTc' (pink). d, Growth kinetics of E. coli with signal plasmid pSBK.136, with and without inducers. e, Growth kinetics of E. coli with signal plasmid pSBK.134 and recording plasmid pSBK.079, with and without inducers. f, Growth kinetics of E. coli with signal plasmid pSBK.136 and recording plasmid pSBK.079, with and without inducers.

Extended Data Fig. 6 Accompaniment to Figure 4.

a, Ordering rules for pSBK.134 A-before-B replicates. The scores for each rule, and the composite score, are shown for each individual replicate. X-containing boxes indicate that no informative arrays, for that particular rule, were present in that replicate. b, As in panel a, ordering rules for pSBK.134 B-before-A replicates. c, As in panel a, ordering rules for pSBK.136 A-before-B replicates. d, As in panel a, ordering rules for pSBK.136 B-before-A replicates.

Extended Data Fig. 7 Long-term stability of retron-derived recordings in CRISPR arrays.

a, Ordering rules for 24+24-h, A-before-B recordings during post-recording multiday culture. Individual and composite scores are shown for samples taken on days 0, 2, 5, and 9 of culture. Each open circle represents the score, for that rule, from a single biological replicate. A total of 3 biological replicates are shown here. b, Changes in ordering rule scores over time in biological replicate 1. c, Changes in ordering rule scores over time in biological replicate 2. d, Changes in ordering rule scores over time in biological replicate 3.

Supplementary information

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This file contains Supplementary Fig. 1 and Supplementary Tables 1–4.

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Bhattarai-Kline, S., Lear, S.K., Fishman, C.B. et al. Recording gene expression order in DNA by CRISPR addition of retron barcodes. Nature 608, 217–225 (2022). https://doi.org/10.1038/s41586-022-04994-6

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