Open-ended molecular recording of sequential cellular events into dna

ABSTRACT Genetically encoded DNA recorders noninvasively convert transient biological events into durable mutations in a cell’s genome, allowing for the later reconstruction of cellular

experiences by DNA sequencing. We present a DNA recorder, peCHYRON, that achieves high-information, durable, and temporally resolved multiplexed recording of multiple cellular signals in

mammalian cells. In each step of recording, prime editor, a Cas9-reverse transcriptase fusion protein, inserts a variable triplet DNA sequence alongside a constant propagator sequence that

deactivates the previous and activates the next step of insertion. Insertions accumulate sequentially in a unidirectional order, editing can continue indefinitely, and high information is

achieved by coexpressing a variety of prime editing guide RNAs (pegRNAs), each harboring unique triplet DNA sequences. We demonstrate that the constitutive expression of pegRNA collections

generates insertion patterns for the straightforward reconstruction of cell lineage relationships and that the inducible expression of specific pegRNAs results in the accurate recording of

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SIMILAR CONTENT BEING VIEWED BY OTHERS LINEAGE TRACING AND ANALOG RECORDING IN MAMMALIAN CELLS BY SINGLE-SITE DNA WRITING Article 22 March 2021 A TIME-RESOLVED, MULTI-SYMBOL MOLECULAR

RECORDER VIA SEQUENTIAL GENOME EDITING Article Open access 06 July 2022 MOLECULAR RECORDING USING DNA TYPEWRITER Article 06 June 2024 DATA AVAILABILITY All NGS datasets can be found at the

National Center for Biotechnology Information (NCBI)’s Sequence Read Archive, accession number PRJNA1159905, and demultiplexing instructions can be found at

https://gthub.com/liusynevolab/peCHYRON-sequencing_data. Flow cytometry data and analysis can be found at http://github.com/liusynevolab/peCHYRON-flow-cytometry. Full plasmid maps are

available at https://github.com/liusynevolab/peCHYRON-plasmids-July2023. Plasmids we believe are most likely to be useful will be available at Addgene. See Supplementary Dataset 3 for a

guide to these data and reagents. Please contact C.C.L. and T.B.L. for other reagents. Source data are provided with this paper. CODE AVAILABILITY Code and all data necessary to rerun the

analyses for each of Figs. 5 and 6, and their associated Extended Data and Supplementary Figures are available at http://github.com/liusynevolab/peCHYRON-Fig5 and

http://github.com/liusynevolab/peCHYRON-Fig6. All other code is available athttp://github.com/liusynevolab/peCHYRON. REFERENCES * Sheth, R. U. & Wang, H. H. DNA-based memory devices for

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  Google Scholar  Download references ACKNOWLEDGEMENTS We thank C. Duong and S. K. Paul for technical assistance; L. Koblan, J.J. Li, K. Simeonov, members of the Liu Laboratory, O.

Razorenova and J. Woytash for helpful discussions and D. Liu (Broad Institute), T. Lu (MIT) and H. El-Samad (UCSF) for plasmids. This work was funded by National Institutes of Health (NIH)

grant nos. R35GM136297, DP2GM119163 and R21GM126287 to C.C.L.; NIH grant nos. K99GM140254 and R00GM140254, and start-up funds from Rice University to T.B.L.; NSF GRFP and AHA Predoctoral

Fellowships to C.K.C. and a fellowship from the NSF-Simons Center for Multiscale Cell Fate Research (NSF Award no. 1763272) to T.B.L. V.J.H. is supported by Medical Scientist Training

Program grant no. T32-GM008620. Sequencing on the Illumina MiniSeq was performed by the Genetic Design and Engineering Center at Rice University, which receives financial support from the

Cancer Prevention and Research Institute of Texas (Award no. RP210116). This work used resources of the UCI GRT Hub, parts of which are supported by NIH grants to the Comprehensive Cancer

Center (grant no. P30CA-062203) and the UCI Skin Biology Resource Based Center (grant no. P30AR075047) at the University of California, Irvine, as well as to the GRT Hub for instrumentation

(grant nos. 1S10OD010794-01 and 1S10OD021718-01). AUTHOR INFORMATION Author notes * These authors contributed equally: Theresa B. Loveless, Courtney K. Carlson. AUTHORS AND AFFILIATIONS *

Department of Biomedical Engineering, University of California, Irvine, CA, USA Theresa B. Loveless, Courtney K. Carlson, Catalina A. Dentzel Helmy, Vincent J. Hu, Guohao Liang, Michelle

Ficht, Arushi Singhai, Marcello J. Pajoh-Casco & Chang C. Liu * Center for Synthetic Biology, University of California, Irvine, CA, USA Theresa B. Loveless, Courtney K. Carlson, Catalina

A. Dentzel Helmy, Vincent J. Hu, Guohao Liang, Michelle Ficht, Arushi Singhai, Marcello J. Pajoh-Casco & Chang C. Liu * NSF-Simons Center for Multiscale Cell Fate, University of

California, Irvine, CA, USA Theresa B. Loveless & Chang C. Liu * Department of BioSciences, Rice University, Houston, TX, USA Theresa B. Loveless, Catalina A. Dentzel Helmy, Sara K.

Ross, Matt C. Demelo & Ali Murtaza * Graduate Program in Mathematical, Computational and Systems Biology, University of California, Irvine, CA, USA Vincent J. Hu * Department of

Chemistry, University of California, Irvine, CA, USA Chang C. Liu * Department of Molecular Biology and Biochemistry, University of California, Irvine, CA, USA Chang C. Liu Authors * Theresa

B. Loveless View author publications You can also search for this author inPubMed Google Scholar * Courtney K. Carlson View author publications You can also search for this author inPubMed 

Google Scholar * Catalina A. Dentzel Helmy View author publications You can also search for this author inPubMed Google Scholar * Vincent J. Hu View author publications You can also search

for this author inPubMed Google Scholar * Sara K. Ross View author publications You can also search for this author inPubMed Google Scholar * Matt C. Demelo View author publications You can

also search for this author inPubMed Google Scholar * Ali Murtaza View author publications You can also search for this author inPubMed Google Scholar * Guohao Liang View author publications

You can also search for this author inPubMed Google Scholar * Michelle Ficht View author publications You can also search for this author inPubMed Google Scholar * Arushi Singhai View

author publications You can also search for this author inPubMed Google Scholar * Marcello J. Pajoh-Casco View author publications You can also search for this author inPubMed Google Scholar

* Chang C. Liu View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS T.B.L. and C.C.L. conceived the project. T.B.L., C.K.C. and C.C.L.

coinvented the recording architecture. C.K.C. wrote code used for analysis in all figures. Experiments were carried out as follows: Fig. 2 (and associated Extended Data and Supplementary

figures) by T.B.L., C.K.C., C.A.D.H., G.L., M.F., S.K.R. and A.S.; Fig. 3 by C.A.D.H., S.K.R., T.B.L., M.J.P.-C. and M.C.D.; Fig. 4 by T.B.L., M.F. and C.K.C. and Figs. 5 and 6 by C.A.D.H

and T.B.L. Analysis was carried out as follows: Fig. 2 by C.K.C. and T.B.L.; Fig. 3 by T.B.L., C.K.C. and M.J.P.-C.; Fig. 4 by V.J.H. and T.B.L.; Fig. 5 by M.C.D. and Fig. 6 by C.K.C.,

T.B.L. and A.M. Supervision was done and funding acquired by C.C.L and T.B.L. All figures were created by T.B.L. Visualizations were made as follows: C.K.C. made the Graphical Abstract,

Figs. 1 and 4a, Extended Data Figs. 3b, 7 and 10 and Supplementary Figs. 1c and 6b and M.C.D. made Fig. 2d. T.B.L., C.K.C. and C.C.L. wrote the manuscript, which was reviewed and approved by

all authors. CORRESPONDING AUTHORS Correspondence to Theresa B. Loveless or Chang C. Liu. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW

PEER REVIEW INFORMATION _Nature Chemical Biology_ thanks Harris Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. ADDITIONAL INFORMATION

PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. EXTENDED DATA EXTENDED DATA FIG. 1 SCREEN FOR

EFFICIENT INSERTION SEQUENCES. A, Efficient pegRNAs that target 6xHis and insert a different 20-bp sequence (A→B) were rare. A high-throughput screen was used to identify pegRNAs that could

alternate with the 20-bp variant of the 6xHis tag to iteratively edit the peCHYRON locus. In the screen, a library of ~100,000 pegRNAs with variable insertion sequences was transfected into

293T cells along with PE2. High enrichment values correspond to pegRNAs that frequently edited the 6xHis target site without being over-represented in the original transfection mix. The

50,000 library members whose enrichment could be calculated were plotted, and the inset shows the top 50. B, Sequences that can efficiently insert downstream of 6xHis were identified. Top

hits and some non-enriched control sequences from the high-throughput screen were individually cloned, and their insertion efficiencies were assayed. All experiments were conducted in

293T6xHis cells with PEmax; we used lower concentrations of plasmids than usual for this transfection, so insertion efficiencies are expected to be lower than in other experiments. Insertion

sequences are ordered from left to right from most-enriched to least-enriched in the original screen. Each point represents one of three separately-transfected biological replicates, and

error bars correspond to the standard deviation. EXTENDED DATA FIG. 2 IDENTIFICATION OF EFFICIENT PROPAGATING PEGRNAS. A, Heatmap of editing efficiencies for the top ten A→B propagator

sequences identified in an initial screen similar to Extended Data Fig. 1b. For each A→B propagator sequence (B1-B10), a library of signatures was tested, using PBS lengths ranging from 9-15

nts (row labels). B, Heatmap of editing efficiencies for pegRNAs that target the top ten propagator sequences shown in (a) and insert the 20-bp 6xHis sequence (B→A). Libraries encoding

pegRNAs with all possible signatures, at each PBS length from 9-15 nts (row labels), were transfected into 293T6xHis cells in which the corresponding B sequence had been installed at the

recording locus. C, A→B and B→A pegRNAs can achieve propagation. Plasmids expressing PE2 and the top-performing pegRNA libraries identified in (a) and (b) were transfected into 293T6xHis

cells. The lengths of insertions at the recording locus were assayed after 2 rounds of transfection over 6 days. Insertions of 20 bp were considered to correspond to 1 round of recording, 40

 bp to 2 rounds, and so forth. D, A variety of signatures can be installed by the top-performing A-B4. libraries of pegRNAs. From the screens shown in (a) and (b), the log2 enrichment of

each of the 64 possible signatures was calculated for the A→B (left) and B→A (right) pegRNA libraries. EXTENDED DATA FIG. 3 CANNIBALIZATION BY PECHYRON. A, Editing at the recording locus and

pegRNA genes in peCHYRON cells. Prime editor and pegRNAs were integrated into the genome of 293T6xHis cells as PiggyBac Transposase cargo, and integrants were selected with puromycin. 45

days after transfection, the recording locus (where editing is desired) and all pegRNA-expressing loci (where cannibalization occurs) were sequenced. The graph indicates the proportion of

loci that were edited. Data from loci expressing A→B or B→A pegRNAs from each of three types of U6 promoters, human (h), mouse (m), and bovine (b), are shown. B, More detailed cartoon

showing cannibalization of B→A pegRNA gene by the A→B pegRNA. After transcription and coupling with prime editor, the spacer sequence of the A→B pegRNA can recognize either the target site

at the recording locus or the PAM-adjacent target site on the antisense strand of the B→A pegRNA gene. Note the B→A pegRNA only inserts 17 nt of the target sequence recognized by the A→B

pegRNA, but the complete 20-bp target site and PAM are present in the B→A pegRNA gene because prime editing requires a scaffold sequence that complements with the region downstream of the

nick, to enable flap equilibration after reverse transcription. This cartoon only shows cannibalization of the B→A pegRNA gene, but cannibalization can also occur in the inverse direction

(the A→B pegRNA gene is cannibalized by the B→A pegRNA). EXTENDED DATA FIG. 4 LONG-TERM RECORDING WITH PECHYRON. A, At 27 days but not 46 days, the extent of cannibalization with and without

the protective nick were significant by two-tailed unpaired t test (P < 0.0001 for A→B, t = 16.84, df=4, difference between means = 10.72 ± 0.6366, 95% confidence interval 8.955 to

12.49, and P = 0.005 for B→A, t = 5.594, df=4, difference between means = 20.79 ± 3.717, 95% confidence interval 10.47 to 31.11). The unpaired t test assumes equal within-group variance,

which was confirmed by F test in both cases. Throughout this figure, each dot represents one of three biological replicates. B, At early timepoints, in the presence of the protective nicking

guide, we noted that most cannibalization led to shorter pegRNA genes, while most cannibalization in the absence of the protective nick led to the longer genes that would be created by the

expected prime edits. The measure of center is the mean and error bars reflect the standard deviation of 3 biological replicates. C, The fitness cost of peCHYRON components was acceptable,

but silencing occurred. At the time of initial cell selection, 6 days after transfection, 5,000 cells from each protective-nicking guide replicate were each mixed with 5,000 cells from the

parent, non-fluorescent cell line. The proportion of blue, red, and green fluorescent cells was determined by flow cytometry at the indicated time points. The number of cells

‘triple-positive’ for all colors, or positive for any color, is plotted. D, Silencing was tracked as in c. E, Cells tended to lose recording loci over time. In the parent cell line, the

first A site is knocked into one copy of the site3 locus, of which there are three copies in 293T cells. The proportion of site3 reads aligning to the locus including the A site was

calculated at the timepoints indicated, in the cells containing the protective nicking guide. EXTENDED DATA FIG. 5 CHARACTERIZATION OF PECHYRON PERFORMANCE. A more expansive plotting of the

data shown in Fig. 3b. EXTENDED DATA FIG. 6 RATES OF PECHYRON RECORDING. A, Editing rates declined only gradually over the course of the experiment shown in Fig. 3. Based on the distribution

of edit lengths detected at each timepoint, we calculated the rate of editing between each pair of timepoints as the average change in edits from time t to time t + 1. The plotted value at

each timepoint is the calculated rate for the period ending at that timepoint. For example, the value at 27 days is the rate from 0-27 days, the value at 34 days is the rate from 27-34 days,

_etc_. Each line reflects the editing rates of one biological replicate. Transient negative values likely reflect a slightly lower growth rate in cells that edit faster. B, As in a, but

with a single rate calculated from 41-66 days. C, Rates of editing were maintained as arrays grew longer. For the period from 27 to 34 days, the rate of each conversion step (for example,

step 1 converts a locus with no edits to one with a single edit) was calculated for each replicate. D, peCHYRON recording cell lines were created from 293 T and SV40-immortalized mouse

embryonic fibroblasts in parallel and grown for 15 days. Two technical replicates for each of two biological replicates are shown. Source data EXTENDED DATA FIG. 7 RECORDING OF TRANSFECTION

ORDER WITH PECHYRON. A, General approach to recording pulses (or any time-dependent signals) that are linked to expression of pegRNAs with known signature mutations. A pair of A→B and B→A

pegRNAs are expressed together for any signal to be recorded, so that one pegRNA of the pair will record the signal regardless of the state (A or B) of the active link in the recording

locus, and both pegRNAs can continuously record the signal if it is present for a long duration. Colored shapes represent signature mutations. B, Methods of peCHYRON sequence analysis. For

the simplest analysis, which treatments happened in a cell population can be inferred by calculating the proportion of each unigram, or type of signature. The order of treatments can be

deciphered by considering the extended bigrams of signature mutations it contains. Essentially, each signature forms one bigram with every signature that appears after it in a read.

Alternatively, records can be analyzed by stretching each record to a constant length, so it may be pooled with all other records from a population of cells and used to calculate the

proportion of each signature at each position along the stretched records. EXTENDED DATA FIG. 8 RECORDING OF INDUCER DURATION WITH PECHYRON. A, As described for Fig. 5a, the proportions of

signatures in Replicate 1 samples that were D were calculated. We then applied k-means clustering on these values, choosing the cluster number by automatic evaluation of an elbow plot by

identifying the number of clusters for which the second derivative of the inertia is a peak; bars are colored based on cluster membership. B, As in a, for Replicate 2. C, As in a, but for I.

D, As in c, for Replicate 2. EXTENDED DATA FIG. 9 RECORDING OF INDUCER ORDER WITH PECHYRON. A, As described for Fig. 5b, ratios of DC to CD bigrams were calculated. In this case, we

calculated bigrams only for those samples that did not cluster with the lowest D proportions in Extended Data Figure 8a. We then applied k-means clustering to the log2 of the bigram ratios,

choosing the cluster number automatically as in Extended Data Figure 8, and colored bars based on their cluster membership. These data are for Replicate 1. B, As in a, for Replicate 2. C, As

in a, but ratios of IC to CI bigrams. D, As in c, for Replicate 2. E, As in a, but ratios of DI to ID bigrams. F, As in e, for Replicate 2. EXTENDED DATA FIG. 10 SIGNATURE LOCATION ON THE

PECHYRON ARRAY AS A PROXY FOR TIME. Stretched records underlying the analysis shown in Fig. 6. Points represent biological replicates and lines are the mean of the biological replicates.

Data is organized according to the inducer, or lack thereof, that each sample was exposed to during the 3 epochs. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Figs. 1–7

and Table 1. REPORTING SUMMARY SUPPLEMENTARY DATASET 1 Detailed results from screen shown in Extended Data Fig. 1a. SUPPLEMENTARY DATASET 2 Data and entropy calculations underlying Extended

Data Fig. 6 and Fig. 4. SUPPLEMENTARY DATASET 3 Guide to plasmids used, HTS datasets available at the NCBI Sequence Read Archive, HTS primers and cell lines. SOURCE DATA SOURCE DATA EXTENDED

DATA FIG. 6 Detailed calculations. RIGHTS AND PERMISSIONS Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing

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and applicable law. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Loveless, T.B., Carlson, C.K., Dentzel Helmy, C.A. _et al._ Open-ended molecular recording of sequential

cellular events into DNA. _Nat Chem Biol_ 21, 512–521 (2025). https://doi.org/10.1038/s41589-024-01764-5 Download citation * Received: 07 July 2023 * Accepted: 29 September 2024 * Published:

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