Methods and kits for detecting cell signals

Abstract

The present disclosure provides a cell comprising a barcode array incorporated in its genome, and a genome editing system, that can be activated by a cell signal. Said cell can be used, among others, to detect the intensity of the cell signal according to the degree of editing of the barcode array.

Description

P-639878-PCP-639878-PC [UCLA 2025-049]METHODS AND KITS FOR DETECTING CELL SIGNALSCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority to U.S. provisional patent application serial no. 63 / 699,372, filed September 26, 2024, and is incorporated here by reference in its entirety.STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] This invention was made with government support under Grant Number EY031782, awarded by the National Institutes of Health. The government has certain rights in the invention.INCORPORATION BY REFERENCE OF SEQUENCE LISTING

[0003] The instant application contains a Sequence Listing conforming the rules of WIPO Standard ST.26 which has been submitted electronically in XML format and is hereby incorporated by reference in its entirety. The XML copy, created on September 24, 2025, is named P-639878-PC_SQL_24SEP25.xml, and is 298,677 bytes in size.TECHNICAL FIELD

[0004] The present disclosure relates to the field of cellular and molecular biology, specifically to methods for measuring cell signals.BACKGROUND

[0005] In multicellular organisms, the behavior and fate of cells are orchestrated by signaling pathways. Cells interpret the intensity and duration of these signals to produce the appropriate response. For example, during development, signaling gradients provide spatial and temporal cues that guide cell fate decisions. Immune response is also coordinated by cell-cell signaling; the amplitude and duration of signals from the T cell receptor can determine whether a T cell activates, proliferates, and differentiates, or becomes tolerant. Similarly, neoplastic cell division and cancer metastasis often involve aberrant signaling levels. WNT signaling isP-639878-PC frequently up- or down-regulated in different types of cancer, and the pathway activity level can serve as a prognostic indicator of patient outcomes. In all these contexts, explaining or predicting cellular behavior hinges on accurately measuring the activity of signaling pathways in individual cells over time.

[0006] The significance of cell signaling has spurred development of several strategies for capturing the molecular history of cells. Time lapse microscopy is the most direct approach. It typically involves reporters that express a fluorescent protein at a level proportionate to the amount of signaling activity. Time lapse imaging provides superb temporal resolution; however, it is limited to optically accessible samples, and relatively short time scales. There is also a tradeoff between temporal resolution and the size of the sample that can be effectively analyzed. Despite significant progress in microscopy techniques, it remains difficult to reliably track large numbers of cells in complex in vivo environments over extended time periods.SUMMARY

[0007] In some aspects, disclosed herein is a cell comprising: a. at least one barcode array incorporated in its genome, comprising at least one barcode sequence targetable by a genome editing system, and optionally operably linked to a first inducible promoter, and b. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to a second promoter responsive to a cell signal, and a base editing enzyme, wherein said cell signal induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering the base editing of said barcode sequence.

[0008] In some related aspects, the cell signal comprises an oncogenic signal, a metastasis signal, a cell division signal, an inflammatory signal, a growth factor signal, a DNA damage signal, a hypoxia signal, a stress response signal, an apoptotic signal, a differentiation signal, an angiogenesis signal, an immune response signal, an oxidative stress signal, a metabolic signal, a cytokine signal, a wound healing signal, a migration signal, an adhesion signal, an oncogenic signal, a survival signal, a senescence signal, an autophagy signal, a tumor suppressor signal, a receptor tyrosine kinase signal, a hormone signal, a chemokine signal, a neuroinflammatory signal, a heat shock signal, a mitogenic signal, a pathogen-associated signal, a matrix remodeling signal, a reactive oxygen species (ROS) signal, an unfolded protein response (UPR) signal, a cytokine storm signal, a fibrosis signal, a viral infection signal, a lipidP-639878-PC signaling event, a mitochondrial stress signal, an ER stress signal, a mechanical stress signal, an extracellular matrix (ECM) signal, a checkpoint activation signal, an immune checkpoint signal, a pro-inflammatory signal, a pathophysiological signal, a disease signal, an antiinflammatory signal, an angiogenic signal, a fibrotic signal, an immune evasion signal, a developmental signal, a regeneration signal, a hormonal, an imbalance signal, or any combination thereof.

[0009] In some related aspects, the cell signal comprises WNT, BMP, p53, TNF-a, NF-KB, EGF, HIF-la, TGF-0, Notch, c-Myc, Ras, Akt, STAT3, IL-6, IL-10, Hedgehog, VEGF, ERK, PI3K, MAPK, JAK, Smad, FoxO, IFN-y, Rb, PDGF, FGF, IGF-1, SHP2, AP-1, GSK-30, CREB, IKK, CDK4, PTEN, 0-catenin, CXCL12, CXCR4, MMP-9, MMP-2, Cyclin DI, Cyclin E, HER2, HER3, ERa, AR, PPARy, CCR5, CD44, or CDK2, or any combination thereof.

[0010] In some related aspects, the second promoter comprises an endogenous promoter or parts thereof, an endogenous enhancer or parts thereof, or any combination thereof. In some related aspects, the cell signal is WNT, and optionally said second promoter comprises SEQ ID NO.: 1. In some related aspects, the cell signal is BMP, and optionally said second promoter comprises SEQ ID NO.: 2. In some related aspects, the genome editing system is selected from Adenine Base Editor (ABE), Cytosine Base Editors (CBEs), CRISPR-Cas9, TALEN, ZFN, and CRISPR / Casl2a (Cpfl).

[0011] In some related aspects, the genome editing system comprises ABE. In some related aspects, the barcode sequences contain only one editable nucleotide within the activity window of editing system. In some related aspects, the barcode sequence comprises SEQ ID NO.: 3 or SEQ ID NO.: 5. In some related aspects, the barcode array comprises 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 barcode sequences. In some embodiments, the barcode array comprises 1 to 30 barcode sequences.

[0012] In some related aspects, the at least one barcode array comprises 12 barcode sequences. In some related aspects, the at least one barcode array comprises handles separating said barcode sequences. In some related aspects, the at least one barcode array comprises SEQ ID NO.: 4 or SEQ ID NO.: 6. In some related aspects, the first inducible promoter is selected from a T3 promoter, a T7 promoter, or a SP6 promoter.

[0013] In some related aspects, the first inducible promoter comprises a T3 promoter comprising SEQ ID NO.: 7. In some related aspects, the cell comprises more than one barcodeP-639878-PC array incorporated in its genome. In some related aspects, the degree of editing of the barcode array is indicative of the intensity of the cell signal. In some embodiments, the cell comprises two independent barcode arrays. In some embodiments, each barcode array has a distinct gRNA that targets each barcode array.

[0014] In some aspects disclosed herein is a method for detecting the intensity of a cell signal, comprising: a. providing a cell comprising: i. at least one barcode array incorporated in its genome and comprising at least one barcode sequence targetable by a genome editing system, and ii. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to a promoter responsive to said cell signal, and a base editing enzyme, wherein said cell signal induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering the base editing of said barcode sequence; b. optionally inducing transcription of the at least one barcode array; c. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively; d. measuring the readouts of said first and second detection probes; e. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of the intensity of the cell signal. In some embodiments, the cell comprises more than one barcode array incorporated into its genome. In some embodiments, the cell comprises two independent barcode arrays. In some embodiments, each barcode array has a distinct gRNA that targets each barcode sequence. In some embodiment, the barcode arrays are simultaneously measured. In some embodiments the barcode arrays are sequentially measured.

[0015] In some aspects disclosed herein is a method for detecting the degree of editing of a transcript in a cell, comprising: a. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the transcript, respectively; b. measuring the readouts of said first and second detection probes; c. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of the degree of editing of said transcript.

[0016] In some aspects, disclosed herein is a method for detecting the degree of editing of a barcode in a cell, comprising: a. providing a cell comprising at least one barcode array incorporated in its genome and comprising at least one barcode sequence targetable by a genome editing system; b. optionally inducing transcription of the barcode arrays; and c. contacting the cell with a first detection and a second detection probe, complementary to theP-639878-PC edited and the unedited form of the barcode sequence, respectively; d. measuring the readouts of said first and second detection probes; e. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of degree of editing of said barcode.

[0017] In some aspects, disclosed herein is a method for detecting the activity of a promoter and / or an enhancer region, comprising: a. providing a cell comprising: i. at least one barcode array incorporated in its genome and comprising at least one barcode sequence targetable by a genome editing system, and ii. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to said promoter and / or enhancer region, and a base editing enzyme, wherein activation of said promoter and / or enhancer region induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering base editing of said barcode sequence; b. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively, c. measuring the readouts of said first and second detection probes, d. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of the activity of said promoter and / or enhancer region.

[0018] In some related aspects, the promoter and / or said enhancer are endogenous to the cell.

[0019] In some aspects, disclosed herein is a kit comprising: a. a cell comprising: i. at least one barcode array incorporated in its genome, comprising at least one barcode sequence targetable by a genome editing system, and optionally operably linked to a first inducible promoter, and ii. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to a promoter responsive to said cell signal, and a base editing enzyme, wherein said cell signal induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering base editing of said barcode sequence; and b. optionally a means for inducing transcription of the barcode arrays; c. a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively.BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Some embodiments of the invention are herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings inP-639878-PC detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of embodiments of the invention. In this regard, the description taken with the drawings makes apparent to those skilled in the art how embodiments of the invention may be practiced.

[0021] Figures 1 A- ID illustrate molecular recording with in situ ratiometric barcode readout. Figure 1 A shows that each barcode is a genomic site that can be edited to provide two possible states, represented by white and gray ovals. When edit rate is proportional to signal intensity, the number of edited barcodes maintain a record of signaling activity in the lineage of each cell. Barcode edits can be read out together with spatial information and gene expression profile of the cells at the endpoint. The nuclei are shaded in varying grayscales, representing the fraction of edited barcodes in each nucleus. Figure IB shows the workflow of ratiometric barcode readout. Barcode arrays are transcribed in situ, using recombinant T3 RNA polymerase. Accumulation of transcripts in the active site amplifies the signal. Barcode transcripts are then probed with an equimolar mixture of two fluorescently labeled probes, whose sequence differs in only one nucleotide, corresponding to the edited and unedited states (C and T respectively). The two probes compete for binding to each target site and their relative binding reflects the fraction of edited versus unedited barcodes. Figure 1C shows the design of the INSCRIBE cell lines. Each cell contains doxycycline (Dox) inducible ABE, signal responsive gRNA and H2B-CFP, and barcode arrays compatible with ratiometric readout. All three components are stably integrated using piggyBac transposase. Each barcode consists of a gRNA target site that partially overlaps with the probe target sequence. The sequence of a single barcode in the BC1 array with its corresponding gRNA target site and the probe binding site are shown. The editing window of ABE is shaded in orange. Each barcode array contains 12 identical barcodes. In these examples, it is shown that the WNT and BMP pathways are activated by CHIR and BMP2, respectively, in the corresponding INSCRIBE cell lines. Signal dependent expression of gRNA leads to accumulation of edits in barcode arrays. It is also accompanied by expression of H2B-CFP, which is used as a proxy for signaling activity in short term (3 day) recording experiments. Figure ID shows that ABE expression is further controlled through stabilization of ecDHFR degron by trimethoprim (TMP).

[0022] Figures 2A-2D illustrate an experimental example of molecular recording with in situ ratiometric barcode readout. Figure 2A shows representative images of cells with known edit states. Each column shows one edit level, with the fluorescence channel corresponding toP-639878-PC unedited and edited probes, in magenta and green, respectively. As the number of edited barcodes in the arrays increases from 0 to 12 (left to right), signal in the edited channel increases and signal in the unedited channel diminishes. Figure 2B shows intensity ratio, defined as log2- scaled ratio between the fluorescence intensity in the edited and unedited channels, increases with increasing number of edits in the barcode arrays. Figure 2C shows that regardless of the position of the edited barcode within the array, arrays with one edit show similar intensity ratios, which are higher than the array with no edit and lower than the array with two edits. ‘ 1 ’ stands for edited barcode, ‘0’ stands for unedited barcode, and the red arrow indicates the direction of T3 transcription. Figure 2D shows that the number of edits in barcode arrays can be inferred from fluorescence images of two competing probes. Confusion matrix compares the true edit numbers against the predicted outputs from the CNN model. The frequency values are normalized so that each row sums to one. All results in this figure are from analysis of the BC1 array.

[0023] Figures 3A-3D illustrate validation of ratiometric barcode readout for the BC2 array. Figure 3A shows a representative images of cells with the BC2 array with known edit states. Figure 3B shows the distribution of intensity ratio for each edit number of BC2 array. Figure 3C shows a comparison of arrays with different edit configuration confirms that the number of edits, not their position within the array, determines intensity ratio. Figure 3D shows the classification of BC2 arrays using the CNN model demonstrates accuracy comparable to that achieved for the BC1 arrays. Confusion matrix compares the true edit numbers against the predicted outputs from the CNN model. The frequency values are normalized so that each row sums to one. All results in this figure are from analysis of the BC2 array.

[0024] Figures 4A-4D illustrate screening of monoclonal INSCRIBE cell lines. Split violin plots show the distribution of single cell edit levels after pathway stimulation compared to the unstimulated control condition for monoclonal cell lines from three INSCRIBE recording configurations, WNT-BC1 (Figure 4A), BMP-BC1 (Figure 4B), and BMP-BC2 (Figure 4C). The WNT pathway was activated by 3 pM CHIR and the BMP pathway was activated by 64 ng / ml BMP2. All the recordings were performed for 3 days, using 100 ng / ml of Dox and 10 pM of TMP. The lines used for further analysis (#21 for WNT-BC1, #16 for BMP-BC1, and #17 for BMP-BC2) are highlighted by red dotted rectangles. Figure 4D shows the population median of single-cell barcode edit levels for BMP-BC1 (green) and BMP-BC2 cells (pink) across different BMP2 levels. Bars represent the interquartile ranges. All the recordings wereP-639878-PC performed over 3 days with 10 M of TMP, using 100 ng / ml of Dox for monoclonal screen (Figures 4A-4C), 2500 ng / ml Dox for WNT recording and 500 ng / ml Dox for BMP recording (Figure 4D). Edit level in each cel! is calculated as the average of intensity ratios for ail its barcode arrays.

[0025] Figures 5 A-5M illustrate the experimental recording of the activity of WNT and BMP pathways in a dose dependent manner. Figures 5 A, 5B, and 5C show scatter plots displaying the population median of single-cell barcode edit levels versus H2B-CFP intensity for WNT- BC1 (Figure 5 A), BMP-BC1 (Figure 5B), and BMP-BC2 (Figure 5C) cells. Edit level in each cell is calculated as the average of intensity ratios for all its barcode arrays. The varying levels of signal inducer, indicated by color. Bars represent the interquartile ranges. Figures 5D-5H show Scatter plots display the population median of single-cell barcode edit levels versus H2B- CFP intensity across monoclonal cell lines. Each subplot corresponds to an individual monoclonal. The varying levels of signal inducer, indicated by color. Bars represent the interquartile ranges. Figures 51, 5J, and 5K, illustrate correlation of single-cell barcode edit levels with H2B-CFP intensities for WNT-BC1 (Figure 51), BMP-BC1 (Figure 5 J), and BMP- BC2 (Figure 5K) cells. Each point in the scatter plots represents a single cell, with colors indicating the level of the inducer. Edit level in each cell is calculated either as the average of intensity ratios (g, left; j , left; m, left) or as the average of CNN classifier predicted edits (Figure 51, right; Figure 5J, right; Figure 5K, right) across all its barcode arrays. Spearman correlation coefficients across the inducer dosages and associated p values are shown for each plot. All the recording experiments were performed over 3 days with 10 pM of TMP. Figures 5L, and 5M show correlation of single-cell barcode edit levels with H2B-CFP intensities across monoclonal cell lines. Each subplot corresponds to an individual monoclonal. Each point in the scatter plots represents a single cell, with colors indicating the level of the inducer. Spearman correlation coefficients across the inducer dosages and associated p values are shown for each subplot. ABE expression was induced by 2500 ng / ml Dox for WNT recording (Figures 5A, 5D, 5E, 51, and 5M) and 500 ng / ml Dox for BMP recording (Figures 5B, 5C, 5F, 5G, 5H, 5 J, 5K, and 5M).

[0026] Figures 6A-6I illustrate the robustness of signal recording in the INSCRIBE cell lines with respect to the Dox concentration. Figures 6A-6C illustrate the recording of the WNT pathway activity by WNT-BC1 cells. Population medians and the interquartile ranges of single cell H2B-CFP intensities (Figure 6A) and edit levels (Figure 6B) are plotted against CHIR concentration, with colors indicating different Dox levels. While editing requires expression ofP-639878-PCDox inducible ABE, H2B-CFP expression is expected to be independent of Dox. The scatter plot (Figure 6C) shows correlation between barcode edit level and H2B-CFP intensity in single cells after 3 days of recording with 3 pM CHIR. Each point in the scatter plots represents a single cell, with colors indicating the Dox concentration. Cells from recording experiments with Dox concentration ranging from 100 to 2500 ng / ml are intermixed. Similar results were obtained for BMP-BC1 cells (Figure 6D, 6E, and 6F) and BMP-BC2 cells (Figure 6G, 6H, and 61). Scatter plots show the results for 3 day recording in the presence of 256 ng / ml BMP2 for BMP-BC1 cells (Figure 6F) and 16 ng / ml BMP2 for BMP-BC2 cells (Figure 61). Edit level in each cell is calculated as the average of intensity ratios for all its barcode arrays.

[0027] Figures 7A -7D illustrate the recording duration of the WNT and BMP signaling in INSCRIBE cells. Figure 7A shows schematic of experimental workflow for time dependent recording of signaling activity. ABE expression was induced by 500 ng / ml Dox and 10 pM of TMP. The WNT and BMP pathways were activated by addition of 3 pM CHIR and 64 ng / ml BMP2, respectively. Cells were cultured in recording condition for varying amounts of time and processed for ratiometric barcode readout together. Figure 7B shows representative images showing the editing level of single cells across different recording durations. Figures 7C and 7D show the population median of single cell edit levels plotted against recording time for each cell line, indicated by color coding. Edit level in each cell is calculated either as the average of intensity ratios (Figure 7C), or as the average of CNN classifier predicted edits (Figure 7D) across all its barcode arrays. Bars represent the interquartile ranges and shaded areas show the 95% confidence interval for the medians. Pairwise F-tests were performed on population median of single cell edit levels over time after fitting linear-to-plateau model, with FDR- adjusted p-values indicated on the plots.

[0028] Figures 8A-8H illustrate the evaluation of genomic stability and edit patterns of INSCRIBE barcode arrays by sequencing. Figure 8A shows WNT-BC1 cells or BC2 only cells from the same population were subject to imaging-based ratiometric readout and next generation amplicon sequencing. WNT-BC1 recording was induced by 500 ng / ml Dox, 10 pM of TMP, and 3 pM CHIR for 3 days. Figure 8B shows a histogram of barcode array length, recovered from amplicon sequencing, for WNT-BC1 cells after recording (three replicates) as well as an unstimulated control population maintained in culture for over a year. The length distribution for the barcode array amplified from a plasmid is included as a reference. Figure 8C shows a heatmap showing the proportion of edited barcode arrays recovered fromP-639878-PC ratiometric barcode readout and amplicon sequencing. Edited arrays in imaging-based analysis are identified as those whose edit level based on the CNN model output is above 95th percentile of arrays in unstimulated control condition. The paired t-test p value across the replicates from ratiometric readout and amplicon sequencing is shown. Figure 8D shows the distribution of number of edits in edited barcode arrays based on ratiometric readout (pink) and amplicon sequencing (green). For imaging-based analysis, the CNN model output is binned into 12 classes. The shaded areas represent the mean + standard deviation across three replicates. The Chi-squared p value between the distribution from ratiometric readout and amplicon sequencing is shown. Figure 8E shows a heatmap of edit level for each gRNA target site in the BC1 and BC2 array under edited and control conditions, as recovered from amplicon sequencing. Results of the same analysis for reference plasmids with known edit status (‘001011011100’ for BC1 array and ‘100110110100’ for BC2 array) demonstrate the single base pair accuracy of long read amplicon sequencing. Figure 8F shows the edit status of all edited barcode arrays recovered by amplicon sequencing from three replicates of WNT recording experiments. Figure 8G shows edit level for each gRNA target site in the BC 1 (green) and BC2 array (pink) under edited conditions, corresponding with Figure 8E. Figure 8H shows the edit status of all edited barcode arrays recovered by amplicon sequencing after 3 days of BC2 recording.

[0029] Figures 9A-9B illustrate a comparison of number of edits recovered by ratiometric readout and amplicon sequencing. Figure 9A shows an image of DNA electrophoresis gel showing the length of amplicons from WNT-BC1 recording experiments (left, corresponding with Figure 8B), and from transient transfection mediated BC2 array recording . (right). Figure 9B shows a histogram of BC2 array lengths recovered by amplicon sequencing after transfection, compared to untransfected control populations maintained in culture for over a year. Amplified barcode array from a plasmid is included as a reference.

[0030] Figures 10A-10F illustrate the reconstruction accuracy and noise in signal recording by INSCRIBE. Figure 10A shows a scatter plot showing the single cell inferred edit level against the true edit probability for varying number of barcode arrays. Each point in the scatter plots represents a simulated single cell, with the array number indicated by color, and the R2for Pearson correlation between inferred edit level and true edit probability indicated by dot size. 50 cells were simulated for each edit probability and barcode array number. Figure 10B shows the R2values for Pearson correlation between inferred edit level and true edit probabilityP-639878-PC across different numbers of barcode arrays per cell. Figure IOC shows the distribution of the number of barcode arrays detected in individual cells for each INSCRIBE cell line. Here the data from different recording durations are combined (0 to 7 days for WNT-BC1 and BMP- BC1, 0 to 6 days for BMP-BC2). WNT-BC1, BMP-BC1, and BMP-BC2 cells were stimulated by 3 pM CHIR, 256 ng / ml BMP2, and 16 ng / ml BMP2, respectively. 500 ng / ml Dox and 10 pM of TMP was used to induce ABE expression. Figure 10D, 10E and 10F show the plots show population median (line) and the interquartile range (shaded area) for the standard deviation against the mean of edit levels of barcode arrays within a cell. Cells with arrays of known edit patterns were used to calculate the readout noise (blue). Experimental results for recording with each INSCRIBE cell line were obtained as described in C (pink). Only cells with more than one array were included in the analysis. Simulations were performed either under the assumption of equal edit probability for all arrays in the same cell (brown) or with added normal noise to vary edit probability for different arrays of a cell (green). The standard deviation of normal noise was 0.21, 0.28, and 0.09 for WNT-BC1 (Figure 10D), BMP-BC1 (Figure 10E), and BMP-BC2 (Figure 10F), respectively.

[0031] Figures 11 A- 1 IM illustrate the enduring effects of cell-to-cell variability in response to WNT and BMP signals. Figure 11A WNT-BC1, BMP-BC1, and BMP-BC2 cells were exposed to 3 pM CHIR for 3 days, 256 ng / ml BMP2 for 3 days, and 64 ng / ml BMP2 for 2 days, respectively, twice with varying time intervals in between. Recording was induced only during the first stimulation, by addition of Dox (100 ng / ml for WNT pathway and 500 ng / ml for BMP pathway ) and 10 pM TMP. Figures 11B-11D show population average (points) and standard deviation (bars) of single cell H2B-CFP intensity after restimulation (pink) of the WNT pathway (pinkWNT-BCl (Figure 1 IB), BMP-BC1 (Figure 11C) and BMP-BC2 (Figure 1 ID) cells), corresponding with Figure 7H. In the control group (green), cells were stimulated only once during the first 3 days of recording, and CHIR or BMP2 was not added to the media during the second stimulation period. The results indicate that H2B-CFP intensity reaches a basal level after the rest period (green). Therefore, the H2B-CFP produced during the first stimulation does not impact the endpoint measurements after restimulation. Figures 1 IE-11G show population average (points) and standard deviation (bars) of single cell edit levels after restimulation n of (pink) or under control condition (green), for WNT-BC1 (Figure 1 IE), BMP- BC1 (Figure 1 IF) and BMP-BC2 (Figure 11G) cells , corresponding with Figure 7H. Figure 11H shows the normalized spearman correlation between the first and second response levels for varying time intervals between stimulations of the WNT-BC1 (blue), BMP-BCl(pink) andP-639878-PCBMP-BC2 (green) cells. The first response level was measured either by intensity ratio (solid line) or the CNN model (dashed line). The second response level was measured by endpoint H2B-CFP intensity. Spearman correlations were normalized to the maximum and minimum values observed for each cell line across varying time intervals. Pairwise F-tests were performed on normalized Spearman correlations over time after fitting cubic polynomial regressions, with FDR-adjusted p-values indicated on the plot. Figure 111 shows the two- dimensional kernel density estimate (2D KDE) plots display the distribution of single cell edit levels and CFP levels together. Edit level in each cell is calculated as the average of intensity ratios across all its barcode arrays. The control and stimulated groups (pooled time points from Fig. 7b) are color coded. Subplots correspond to WNT-BC1 , BMP-BC1 or BMP-BC2. The red line indicate the 95th percentile of edit level and CFP level in control groups. Figures 11 J and 11 K show spatial coordinates of cells in one representative field of view for WNT-BC 1 (Figure 11 J) and BMP-BC1 (Figure 1 IK) restimulated after 18 days of rest. Each cell is represented as a point at its centroid, with point size proportional to H2B-CFP intensity and color indicating edit level. A microscopy image of a region within the field of view is displayed on the right, with arrows highlighting examples of cells exhibiting low and high H2B-CFP intensity, corresponding to weak and strong second responses, respectively. Edit level in each cell is calculated as the average of intensity ratios across all its barcode arrays. Cell nuclei are shown only as outlines for clarity. Figure HL shows the normalized spearman correlation between the first and second response levels for varying time intervals between stimulations of the WNT-BC1 (blue), BMP-BCl(pink) and BMP-BC2 (green) cells. The first response level was measured either by intensity ratio (solid line) or the CNN model (dashed line). The second response level was measured by endpoint H2B-CFP intensity. Spearman correlations were normalized to the maximum and minimum values observed for each cell line across varying time intervals. The cells with both the edit level, inferred by intensity ratio, and H2B-CFP intensity below the 95th percentile of unstimulated control cells are excluded. Pairwise F-tests were performed on normalized Spearman correlations over time after fitting cubic polynomial regressions, with FDR-adjusted p-values indicated on the plot. Figure 1 IM, spatial coordinates of cells in one representative field of view for BMP-BC2 restimulated after 18 days of rest. Each cell is represented as a point at its centroid, with point size proportional to H2B-CFP intensity and color indicating edit level. A microscopy image of a region within the field of view is displayed on the right, with arrows highlighting examples of cells exhibiting low and high H2B-CFP intensity, corresponding to weak and strong second responses, respectively.P-639878-PC

[0032] Figures 12A-12C show representative images showing the editing level and the corresponding H2B-CFP intensity of the same cell. For each INSCRIBE cell lines, WNT-BC1 (Figure 12A), BMP-BC1 (Figure 12B), and BMP-BC2 (Figure 12C).

[0033] Figure 13 shows radar plots display the INSCRIBE components' copy numbers across monoclonal cell lines. Each subplot corresponds to an individual monoclonal, annotated with its INSCRIBE recording configuration and monoclonal identifier, with the exception of WNT- BC1-21, BMP-BC1-16, and BMP-BC2-17 that are abbreviated as WNT-BC1, BMP-BC1, and BMP-BC2, respectively.

[0034] Figures 14 A- 14D show ratiometric barcode readout following in situ measurement of BMP target genes by multiplexed single molecule FISH. Figure 14A shows representative images show single molecule FISH of target mRNAs, followed by ratiometric readout of barcode arrays in a BMP-BC2 cell. Cytoplasmic (Cyto) and nuclear (Nuc) boundaries are shown only as outlines for clarity. Figure 14B shows box plot shows the expression level of target mRNAs in BMP-BC2 Control (green) and BMP-BC2 Simulated (pink) cells. Statistical significance between groups was assessed using the Mann- Whitney U test. Figure 14C shows scatter plot shows the correlation of single-cell ID3 mRNA counts between initial and second hybridizations. Each point represents a single cell. Pearson correlation coefficients and associated p values are shown. Figure 14D shows Spearman correlation matrix of single cell measurements for stimulated BMP-BC2 cells. The spearman correlation coefficients are color coded, with point size proportional to the associated p values. BMP-BC2 cells stimulated with 256 ng / ml of BMP2 for 1 day.DETAILED DESCRIPTION

[0035] Unless otherwise defined, all technical and / or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the invention, exemplary methods and / or materials are described below. In case of conflict, the patent specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be necessarily limiting. Each literature reference or other citation referred to herein is incorporated herein by reference in its entirety.P-639878-PC

[0036] In the description presented herein, each of the steps of the invention and variations thereof are described. This description is not intended to be limiting and changes in the components, sequence of steps, and other variations would be understood to be within the scope of the present invention.

[0037] It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination or as suitable in any other described embodiment of the invention. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements.

[0038] Genetic engineering provides an alternative to direct observation. Using site-specific recombination, cells can be permanently labeled upon activation of a signaling pathway. This powerful technique has enabled numerous groundbreaking discoveries. However, it seldom offers the precision and spatiotemporal resolution required for quantitative association of signaling levels and cellular phenotypes. Site-specific recombination typically has a binary outcome: cells that activated the recombinase at high enough level to catalyze the recombination versus those that did not.

[0039] Molecular recording offers a promising solution to these challenges by engineering cells to record their signaling history in their genome, as targeted mutations that can be detected at a later time (Figure 1A). This approach is enabled by the multitude of genome editing methods, including recombinases, CRISPR / Cas9, CRISPR integrases, base editors, and prime editors, which can alter the sequence of genomic DNA in living cells. The pattern and frequency of mutations can be used to reconstruct molecular history of the cells, as well as lineage relationship between them. Recording longitudinal information in the genome allows researchers to use high-throughput snapshot methods, such as single cell sequencing and spatial genomics, to capture history of the cells as well as their endpoint state. It also circumvents the need for direct real time observation of the system.

[0040] An ideal system for genetically recording signaling activity should provide accurate single-cell measurements, be compatible with collecting additional information (such as gene expression and spatial context), have the potential to simultaneously record multiple signals,P-639878-PC and be user-friendly without requiring specialized tools or equipment. Existing methods that use next generation sequencing for readout, while promising, disrupt spatial organization, which is often essential for understanding tissue biology and function. Further, due to the digital and probabilistic nature of DNA editing, a large number of memory elements are required to achieve robust analog recording. This is accomplished either through integration of multiple barcode arrays in each cell, or by targeting several endogenous sites. However, it is difficult to consistently recover both the transcriptional profile and the sequence of multiple genomic targets from individual cells by single cell sequencing, as this occurs infrequently. Consequently, existing molecular recording strategies have limited accuracy at the single-cell level.

[0041] Imaging-based methods preserve spatial information, can decode numerous target sites in each cell, and are compatible with gene expression profiling. However, performing the many rounds of hybridization and imaging that is required to read out the recorded information is challenging. Sequential imaging is also time consuming, limiting the total sample area that can be analyzed in a reasonable timeframe. As a result, application of imaging-based molecular recording has remained limited. Here is introduced a novel approach for detecting the number of edits in DNA barcodes based on the fluorescence intensity of only two probes. This approach, which is termed herein ratiometric barcode readout, bypasses the sequential hybridization and imaging process, thereby solving the main hurdle for widespread application of imaging-based molecular recording. Using ratiometric barcode readout, a scalable method is developed for spatially resolved quantitative reconstruction of signaling activity at the single cell level, called, IN situ Single Cell Recording of signal Intensity as Barcode Edits (INSCRIBE). INSCRIBE uses a CRISPR A-to-G base editor (ABE) to mutate specific sites within synthetic barcode arrays that are distributed in multiple loci across the genome. As testbeds we use two deeply conserved morphogen pathways, WNT and BMP, which pattern tissues across metazoans. In their canonical forms, WNT stabilizes P-catenin to drive TCF / LEF-dependent transcription, whereas BMP signals through receptor-mediated phosphorylation of SM AD 1 / 5 / 8 to regulate gene expression. Using signal responsive cis- regulatory elements, Human Embryonic Kidney (HEK293) cell lines were created in which frequency of barcode edits is proportional to activity of WNT or BMP signaling pathways. Exogenous stimulation with CHIR for WNT and BMP2 for the BMP pathway were used to show that either the amplitude or duration of signaling in these cell lines can be recovered from endpoint measurements that involve only a single round of imaging.P-639878-PC

[0042] Using INSCRIBE, single cell variability was analyzed in response to WNT and BMP stimulation. Even in a clonal population, individual cells can exhibit varying levels of response, although they are exposed to the same level of inducer. It was asked whether this heterogeneity reflects stable and heritable differences between cells. Comparing the magnitude of response between two sequential stimulations revealed a persistent memory in the BMP pathway, which can last up to 18 days. This disclosure demonstrates the utility of INSCRIBE in providing novel biological insight and addressing otherwise intractable questions. In some embodiments, disclosed herein is a cell comprising: a. At least one barcode array incorporated in its genome, comprising at least one barcode sequence targetable by a genome editing system, and optionally operably linked to a first inducible promoter, and b. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to a second promoter responsive to a cell signal, and a base editing enzyme, wherein said cell signal induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering the base editing of said barcode sequence.

[0043] In some embodiments, disclosed herein is a method for detecting the intensity of a cell signal, comprising: a. providing a cell comprising: i. at least one barcode array incorporated in its genome and comprising at least one barcode sequence targetable by a genome editing system, and ii. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to a promoter responsive to said cell signal, and a base editing enzyme,P-639878-PC wherein said cell signal induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering the base editing of said barcode sequence; b. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively; c. measuring the readouts of said first and second detection probes; d. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of the intensity of the cell signal.Cell Signals

[0044] In some embodiments, a cell signal comprises the increase of concentration of a molecule. In some embodiments, a cell signal comprises the decrease of concentration of a molecule. In some embodiments, a cell signal comprises the activation of a signaling pathway. In some embodiments, a cell signal comprises the inhibition of a signaling pathway. In some embodiments, a cell signal comprises the modification of protein activity. In some embodiments, a cell signal comprises the release of cytokines. In some embodiments, a cell signal comprises changes in membrane potential. In some embodiments, a cell signal comprises alterations in a gene expression level. In some embodiments, a cell signal comprises the production of reactive oxygen species (ROS). In some embodiments, a cell signal comprises the induction of apoptosis. In some embodiments, a cell signal comprises the engagement of immune receptors. In some embodiments, a cell signal comprises the activation of transcription factors.

[0045] A skilled artisan would appreciate that the intensity of a cell signal refers to the strength or magnitude of the signaling response that a cell exhibits in response to external stimuli or intracellular processes. In some embodiments, the intensity of a cell signal is a function of the concentration of signaling molecules. In some embodiments, the intensity of a cell signal is a function of the activation of a signaling pathway. In some embodiments, the intensity of a cell signal is a function of the level of gene expression. In some embodiments,P-639878-PC the intensity of a cell signal is a function of the duration of a signaling event. In some embodiments, the intensity of a cell signal is a function of the magnitude of a signaling event. In some embodiments, the intensity of a cell signal is a function of the frequency of a signaling event. In some embodiments, the intensity of a cell signal is a function of the amplitude of and electrical signals. In some embodiments, the intensity of a cell signal is a function of the strength of receptor- ligand interactions.

[0046] In some embodiments, a cell signal comprises an oncogenic signal. In some embodiments, a cell signal comprises a metastasis signal. In some embodiments, a cell signal comprises a cell division signal. In some embodiments, a cell signal comprises an inflammatory signal. In some embodiments, a cell signal comprises a pathophysiological signal. In some embodiments, a cell signal comprises a disease signal. In some embodiments, a cell signal comprises a growth factor signal. In some embodiments, a cell signal comprises a DNA damage signal. In some embodiments, a cell signal comprises a hypoxia signal. In some embodiments, a cell signal comprises a stress response signal. In some embodiments, a cell signal comprises an apoptotic signal. In some embodiments, a cell signal comprises a differentiation signal. In some embodiments, a cell signal comprises an angiogenesis signal. In some embodiments, a cell signal comprises an immune response signal. In some embodiments, a cell signal comprises an oxidative stress signal. In some embodiments, a cell signal comprises a metabolic signal.

[0047] In some embodiments, a cell signal comprises a cytokine signal. In some embodiments, a cell signal comprises a wound healing signal. In some embodiments, a cell signal comprises a migration signal. In some embodiments, a cell signal comprises an adhesion signal. In some embodiments, a cell signal comprises a survival signal. In some embodiments, a cell signal comprises a senescence signal. In some embodiments, a cell signal comprises an autophagy signal. In some embodiments, a cell signal comprises a tumor suppressor signal. In some embodiments, a cell signal comprises a receptor tyrosine kinase signal. In some embodiments, a cell signal comprises a hormone signal. In some embodiments, a cell signal comprises a chemokine signal. In some embodiments, a cell signal comprises a neuroinflammatory signal. In some embodiments, a cell signal comprises a heat shock signal. In some embodiments, a cell signal comprises a mitogenic signal. In some embodiments, a cell signal comprises a pathogen-associated signal. In some embodiments, a cell signal comprises a matrix remodeling signal. In some embodiments, a cell signal comprises a reactive oxygen species (ROS) signal.P-639878-PC

[0048] In some embodiments, a cell signal comprises an unfolded protein response (UPR) signal. In some embodiments, a cell signal comprises a cytokine storm signal. In some embodiments, a cell signal comprises a fibrosis signal. In some embodiments, a cell signal comprises a viral infection signal. In some embodiments, a cell signal comprises a lipid signaling event. In some embodiments, a cell signal comprises a mitochondrial stress signal. In some embodiments, a cell signal comprises an ER stress signal. In some embodiments, a cell signal comprises a mechanical stress signal. In some embodiments, a cell signal comprises an extracellular matrix (ECM) signal. In some embodiments, a cell signal comprises a checkpoint activation signal. In some embodiments, a cell signal comprises an immune checkpoint signal. In some embodiments, a cell signal comprises a pro-inflammatory signal. In some embodiments, a cell signal comprises an anti-inflammatory signal.

[0049] In some embodiments, a cell signal comprises an angiogenic signal. In some embodiments, a cell signal comprises a fibrotic signal. In some embodiments, a cell signal comprises an immune evasion signal. In some embodiments, a cell signal comprises a developmental signal. In some embodiments, a cell signal comprises a regeneration signal. In some embodiments, a cell signal comprises a hormonal signal. In some embodiments, a cell signal comprises an imbalance signal.

[0050] In some embodiments, a cell signal comprises a change of intracellular concentration of a signaling molecule. In some embodiments, a cell signal comprises a change of extracellular concentration of a signaling molecule. In some embodiments, a signaling molecule comprises WNT. In some embodiments, a signaling molecule comprises BMP. In some embodiments, a signaling molecule comprises p53. In some embodiments, a signaling molecule comprises TNF-a. In some embodiments, a signaling molecule comprises NF-KB. In some embodiments, a signaling molecule comprises EGF. In some embodiments, a signaling molecule comprises HIF-la. In some embodiments, a signaling molecule comprises TGF-p. In some embodiments, a signaling molecule comprises Notch. In some embodiments, a signaling molecule comprises c-Myc.

[0051] In some embodiments, a signaling molecule comprises Ras. In some embodiments, a signaling molecule comprises Akt. In some embodiments, a signaling molecule comprises STAT3. In some embodiments, a signaling molecule comprises IL-6. In some embodiments, a signaling molecule comprises IL-ip. In some embodiments, a signaling molecule comprises Hedgehog. In some embodiments, a signaling molecule comprises VEGF. In someP-639878-PC embodiments, a signaling molecule comprises ERK. In some embodiments, a signaling molecule comprises PI3K. In some embodiments, a signaling molecule comprises MAPK. In some embodiments, a signaling molecule comprises JAK. In some embodiments, a signaling molecule comprises Smad. In some embodiments, a signaling molecule comprises FoxO.

[0052] In some embodiments, a signaling molecule comprises IFN-y. In some embodiments, a signaling molecule comprises Rb. In some embodiments, a signaling molecule comprises PDGF. In some embodiments, a signaling molecule comprises FGF. In some embodiments, a signaling molecule comprises IGF-1. In some embodiments, a signaling molecule comprises SHP2. In some embodiments, a signaling molecule comprises AP-1. In some embodiments, a signaling molecule comprises GSK-3 . In some embodiments, a signaling molecule comprises CREB. Tn some embodiments, a signaling molecule comprises IKK. In some embodiments, a signaling molecule comprises CDK4. In some embodiments, a signaling molecule comprises PTEN. In some embodiments, a signaling molecule comprises P-catenin. In some embodiments, a signaling molecule comprises CXCL12. In some embodiments, a signaling molecule comprises CXCR4. In some embodiments, a signaling molecule comprises MMP-9. In some embodiments, a signaling molecule comprises MMP-2. In some embodiments, a signaling molecule comprises Cyclin DI.

[0053] In some embodiments, a signaling molecule comprises Cyclin E. In some embodiments, a signaling molecule comprises HER2. In some embodiments, a signaling molecule comprises HER3. In some embodiments, a signaling molecule comprises ERa. In some embodiments, a signaling molecule comprises AR. In some embodiments, a signaling molecule comprises PPARy. In some embodiments, a signaling molecule comprises CCR5. In some embodiments, a signaling molecule comprises CD44. In some embodiments, a signaling molecule comprises CDK2.

[0054] A skilled artisan would appreciate that the methods disclosed herein can be applied to any cell of interest. In some embodiments, a cell is a human cell. In some embodiments, a cell is an animal cell. In some embodiments, a cell is a plant cell. In some embodiments, a cell is selected from the group comprising HEK293, MCF-7, HeLa, A549, THP-1, Jurkat, CHO, NIH 3T3, COS-7, RAW 264.7, C2C12, HepG2, SH-SY5Y, K562, or PC-3 cell.

[0055] In some embodiments, a cell comprises a primary cell. In some embodiments, a cell comprises a cell from an immortalized cell line. In some embodiments, a cell comprises a cellP-639878-PC derived from a patient. In some embodiments, a cell is selected from the group comprising: stem cells, cancer cells, neuronal cells, muscle cells, epithelial cells, fibroblasts, immune cells, T cells, B cells, macrophages, endothelial cells, hepatocytes, pancreatic cells, insulinproducing P-cells, adipocytes, chondrocytes, keratinocytes, germ cells, sperm cells, egg cells, glial cells.Barcode Arrays

[0056] In some embodiments, the term “barcode” refers to a specific polynucleotide sequence that is incorporated into a genome to enable tracking cellular activity. These barcodes serve as unique identifiers for individual cells, allowing monitoring changes in gene expression, cell behavior, and lineage over time. Particularly, barcodes that can be modified using techniques like adenine base editing (ABE) enhance the ability to study dynamic cellular processes by enabling precise alterations to the barcode sequences. For example, Askary A, et al. In situ readout of DNA barcodes and single base edits facilitated by in vitro transcription. Nat Biotechnol. 2020 Jan;38(l):66-75, which is incorporated herein by reference, teaches how ABE can be used to edit DNA barcodes. The method disclosed therein involves incorporating a barcode sequence into the genome and then using ABE to achieve targeted edits, enabling researchers to monitor cellular changes under different conditions.

[0057] In some embodiments, a barcode sequence comprises any polynucleotide sequence that can be edited by a genome editing system. In some embodiments, a barcode sequence can be edited by Base Editor (ABE). In some embodiments, a barcode sequence can be edited by Cytosine Base Editors (CBEs). In some embodiments, a barcode sequence can be edited by CRISPR-Cas9. In some embodiments, a barcode sequence can be edited by prime editing. In some embodiments, a barcode sequence can be edited by TALEN. In some embodiments, a barcode sequence can be edited by ZFN. In some embodiments, a barcode sequence can be edited by CRISPR / Casl2a (Cpfl).

[0058] A barcode sequence can vary in length, but they are preferably designed to be around 15 to 35 bases long. This length allows for sufficient specificity and uniqueness to track individual cells or cellular activities while still being manageable for editing. The precise length can depend on the experimental design and the desired level of resolution for tracking changes in genetic information. Barcode sequences of any length can be used in the methods disclosed herein. In some embodiments, a barcode sequence is 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,P-639878-PC21, 22, 23, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, or 40 bases long. In some embodiments, a barcode sequence is 31 bases long.

[0059] In some embodiments, a barcode comprises a probe site, which is used in conjunction with a complementary detection probe to detect the barcode. In some embodiments, said probe site is 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25 base pairs long.

[0060] In some embodiments, a barcode sequence is targetable by a genome editing enzyme. In some embodiments, a barcode comprises a gRNA target site, to which a gRNA molecule guides a genome editing enzyme. In some embodiments, said gRNA target site is 5, 6, 7, 8, 9, 10, 1 1, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25 base pairs long. In some embodiments, the probe site and the gRNA target site partially overlap. In some embodiments, gRNA target sites comprise only one editable nucleotide, thus ensuring that edit outcomes are pure and predictable.

[0061] In some embodiments, probe sequences are designed with a GC content and a Tm temperature to allow optimal detection, according to methods known to the artisan. In some embodiments, a probe sequence comprises about 50% GC content. In some embodiments, a probe sequence comprises a predicted Tm between 56 and 60°C.

[0062] In some embodiments, a barcode sequence comprises SEQ ID NO.: 3. In some embodiments, a barcode sequence comprises SEQ ID NO.: 5.

[0063] As used herein, a barcode array refers to a number of barcode sequences that are close to each other in the genome. In some embodiments, a barcode array comprises 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 barcode sequences. In some embodiments, a barcode array comprises more than 30 barcode sequences. In some embodiments, a barcode array comprises 12 barcode sequences.

[0064] In some embodiments, a barcode array comprises a promoter to drive expression of the barcode. In some embodiments, said promoter comprises a T3 promoter, a T7 promoter or a SP6 promoter. In some embodiments, said promoter comprises a T3 promoter. In some embodiments, each barcode sequence is flanked by a handle to achieve ordered assembly and identification. In some embodiments, said handles are 4 base pair long. In some embodiments, a handle comprises a polynucleotide as set forth in SEQ ID NO: 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, or 21.P-639878-PC

[0065] In some embodiments, a barcode array comprises identical barcode sequences. In some embodiments, the barcode systems of an array are targetable by different genome editing enzymes.

[0066] In some embodiments, a barcode array comprises SEQ ID NO: 4. In some embodiments, a barcode array comprises SEQ ID NO: 6.

[0067] In some embodiments, a barcode sequence can be edited by an Adenine Base Editor (ABE). In some embodiments, a barcode sequence can be edited by Cytosine Base Editor (CBE). In some embodiments, a barcode sequence can be edited by CRISPR / Cas9. In some embodiments, a barcode sequence can be edited by Prime Editing. In some embodiments, a barcode sequence can be edited by TALENs. In some embodiments, a barcode sequence can be edited by Zinc Finger Nucleases (ZFNs). In some embodiments, a barcode sequence can be edited by CRISPR / Casl2a. In some embodiments, a barcode sequence can be edited by CRISPR / Cpfl. In some embodiments, a barcode sequence can be edited by meganucleases.

[0068] Once a barcode array has been edited, it is transcribed, for example following the activation of a promoter operably linked to it, thus producing a number of transcripts of the barcode. In some embodiments, the barcode array is transcribed by exogenously activating its promoter. In some embodiments, the barcode array is operatively linked to a T3 promoter, and it is activated by a T3 molecule. In some embodiments, a T3 promoter comprises SEQ ID NO.: 7. In some embodiments, the barcode array is operatively linked to a T7 promoter. In some embodiments, the barcode array is operatively linked to a SP6 promoter.

[0069] A skilled artisan would appreciate that any number of barcode arrays can be incorporated to the cell genome. In some embodiments, said arrays are identical. In some embodiments, said arrays are different, are edited by different genome editing systems directed by different gRNAs. In that case, each of said different gRNAs can be responsive to a different said signal, thus allowing to study different cell signals at the same time. In said case, each different barcode can be detected by different detection probes.

[0070] In some embodiments, 1 barcode array is incorporated into the cell genome. In some embodiments, 2 barcode arrays are incorporated into the cell genome. In some embodiments, 3 barcode arrays are incorporated into the cell genome. In some embodiments, 4 barcode arrays are incorporated into the cell genome. In some embodiments, 5 barcode arrays are incorporated into the cell genome. In some embodiments, 6 barcode arrays are incorporated into the cellP-639878-PC genome. In some embodiments, 7 barcode arrays are incorporated into the cell genome. In some embodiments, 8 barcode arrays are incorporated into the cell genome. In some embodiments, 9 barcode arrays are incorporated into the cell genome. In some embodiments, 10 barcode arrays are incorporated into the cell genome. In some embodiments, more than 10 barcode arrays are incorporated into the cell genome.

[0071] In some embodiments, a cell comprises more than one barcode array. In some embodiments, a cell comprises two barcode arrays. In some embodiments, each barcode array has a distinct gRNA that targets each barcode array. In some embodiments, the barcodes are simultaneously measured. In some embodiments, the barcode arrays are sequentially measured.Genome Editing Systems

[0072] A skilled artisan would appreciate that genome editing systems refer to molecular tools designed to make precise alterations to the DNA of a cell. Any of these systems can be used to implement the methods disclosed herein. Systems as CRISPR / Cas9 use a guide RNA (gRNA) to direct the Cas9 nuclease to a specific DNA sequence, where it induces a doublestrand break. This break can be repaired by the cell’s natural repair mechanisms, such as non- homologous end joining (NHEI), which often results in small insertions or deletions, or homology-directed repair (HDR) when a donor template is provided, allowing for more precise edits. Variants like CRISPR / Casl2a (Cpfl) expand the toolkit, with Casl2a targeting different PAM sequences.

[0073] Systems like base editors, including Adenine Base Editors (ABEs) and Cytosine Base Editors (CBEs), allow for single-nucleotide changes without inducing double-strand breaks. These systems use a modified Cas9 nickase fused to a deaminase enzyme to convert one base into another, such as adenine to guanine (ABE) or cytosine to thymine (CBE). Other systems include prime editing, which uses a Cas9 nickase fused to a reverse transcriptase and a prime editing guide RNA (pegRNA) to directly write new genetic information into the DNA, enabling precise substitutions, insertions, or deletions without double-strand breaks or donor templates. An artisan would recognize the advantages that each of these systems offer for the implementation of the methods disclosed herein.

[0074] In some embodiments, a genome editing system comprises a gRNA specific to a barcode sequence and a base editing enzyme capable of editing said barcode sequence. In some embodiments, the gRNA is operably linked to a promoter, or a promoter element, that isP-639878-PC responsive to a cell signal. In other words, the transcription of the gRNA is activated following said cell signal. In such a manner, the presence of a predetermined cell signal activates transcription of the gRNA, which in turn guides the base editing system to the barcode sequence, thus triggering base editing of said barcode sequence. An artisan would appreciate that, in this manner, the presence of a cell signal will keep recorded in the barcode sequence.

[0075] The present disclosure provides a method for determining the intensity of a cell signal. Thus, the number of edited barcode sequences in an array is indicative of the degree of expression of the gRNA, which in turn depends on the intensity of the cell signal. In other words, the more intense a signal, the more edited a barcode array will be.

[0076] In some embodiments, the gRNA is operably linked to an endogenous promoter, or parts thereof. In some embodiments, the gRNA is operably linked to an endogenous enhancer or parts thereof. In some embodiments, the gRNA is operably linked to an endogenous promoter and endogenous enhancer, or parts thereof. In some embodiments, said endogenous promoter and / or enhancer is activated by their respective endogenous signals. In such cases, the degree of barcode editing is indicative of the endogenous activation of said promoter and / or enhancer by their respective endogenous signals. In some embodiments, said design is useful to elucidate the activation of an endogenous gene.

[0077] In some embodiments, the gRNA is operably linked to a WNT-responsive element. In some embodiments, a WNT-responsive element comprises SEQ ID NO.: 1. In some embodiments, the gRNA is operably linked to a BMP-responsive element. In some embodiments, a BMP -responsive element comprises SEQ ID NO.: 2.Ratiometric Barcode Readouts

[0078] In order to detect the degree of editing of the barcode arrays, cells are contacted with detection probes complementary to the edited and the unedited form of the barcode sequence. Thus, in some embodiments, the cells are contacted with at two detection probes, the first complementary to the edited form of the barcode transcript, and the second complementary to the unedited form of the barcode transcript.

[0079] A skilled artisan would appreciate that, as used herein, a detection probe refers to any molecule that binds to specific RNA sequence, enabling the visualization and quantification of gene expression at the cellular level. In some embodiments, detection probes includeP-639878-PC fluorescently labeled oligonucleotides, such as Fluorescence In Situ Hybridization (FISH) probes, which hybridize to complementary RNA sequences within fixed cells or tissue samples.

[0080] These detection probes used for transcript detection can be labeled with any type of markers that enable visualization by microscopy, each labeling offering distinct advantages depending on the experimental needs. In some embodiments, the probes comprise fluorescent labeling, where probes are conjugated with fluorophores such as Alexa Fluor dyes, FITC, or Cy dyes. In some embodiments, the detection probes are conjugated with Alexa 647 fluorophore. In some embodiments, the detection probes are conjugated with Alexa 546 fluorophore. These fluorophores emit light at specific wavelengths when excited by a corresponding laser or light source, allowing for the detection of the hybridized probes in fluorescence microscopy.

[0081] An artisan would appreciate that the sequence of a detection probe is complementary to the transcripts of either the edited or the unedited barcode sequence. There are methods known in the art to design detection probes for a transcript, that the artisan can use to implement the methods described herein. In some embodiments, the detection probe for the edited barcode comprises SEQ ID NO.: 101, and the detection probe for the unedited barcode comprises SEQ ID NO.: 102. In some embodiments, the detection probe for the edited barcode comprises SEQ ID NO.: 103, and the detection probe for the unedited barcode comprises SEQ ID NO.: 104.

[0082] In some embodiments, different fluorophores are attached to the different detection probes, thus allowing the simultaneous detection of edited and unedited barcode transcripts within a single sample. In this manner, the intensity and color of the fluorescence quantify the abundance of each of the transcripts.

[0083] Different protocols are known in the art for detecting transcripts with fluorescent probes. Any of them can be used to implement the methods disclosed herein. In an exemplary and non-limiting embodiment, cells are seeded on glass-bottom 96-well plates, as for example Cellvis, P96-1.5H-N, which can be optionally coated with molecules promoting cell adhesion, as 20 pg / ml laminin (Biolamina, LN511). Cells can be left at 37°C overnight. Cells can be seeded at different densities, for example at around 10,000 to 20,000 cells per well, to allow straightforward segmentation while maximizing the number of cells analyzed in each field of view (FOV).P-639878-PC

[0084] Cells can then be washed, for example with 1 x PBS (Gibco, 14190250), followed by fixation buffer, which can consist in a fresh mixture of methanol (Sigma, 494437) and acetic acid (Sigma, A6283) with a 3:1 volume ratio. Cells can be then incubated at room temperature for 20 min. Cells can then be washed, for example twice in nuclease-free water (IDT, 11-04- 02-01) for 5 min each. In order for the barcode array to be expressed, the promoter of the barcode array can be exogenously activated. For example, if the barcode array promoter is T3, transcription can be activated by incubating the cells with 50 pl of T3 transcription mix at 37° C for 3 h, which consists of 0.5 mM NTP (NEB, N0466S), 0.8 U / pl RNase inhibitor (NEB, M0314S), 5 units / pl T3 RNA polymerase (NEB, M0378S) and 1 x RNAPol reaction buffer (NEB, B9012S). After transcription, cells are fixed, for example with fresh 4% formaldehyde solution (Thermo Scientific, 28906) in PBS for 30 min at room temperature followed by two washes with 2 x SSC (Invitrogen, 15557044) for 5 min each, to remove traces of formaldehyde.

[0085] Subsequently, cells are incubated with a hybridization buffer, for example with 50pl of hybridization buffer which consisted of 30% formamide (Invitrogen, AM9344), 10% dextran sulfate (Sigma, D8906), and 2 x SSC at 37 °C for at least 30 min. The cells are then incubated with the detection probes, for example with 4 nM of Alexa Fluor 546 conjugated edited probe (IDT) and 4 nM of Alexa Fluor 647 conjugated unedited probe (IDT) in 50 pl of hybridization buffer for 20 h at 37 °C.

[0086] Then, the hybridized cells can be washed, for example four times (15 min each) at 37°C with prewarmed wash buffer which consisted of 30% formamide (Invitrogen, AM9344), 0.1% Triton-X 100 (Sigma, T8787) and 2 x SSC to remove excess probes, followed by a brief wash with 4 x SSC. Nuclei can be stained, for example with 1 pg / ml DAPI (Thermo Scientific, 62248) in 4 x SSC for 10 min, followed by a wash with 4 x SSC for 5 min. The plate can then be stored in 4 x SSC with 0.02 unit / pl SUPERase RNase inhibitor (Invitrogen, AM2694) at 4°C or imaged immediately. When 96 wells plates are used, reagents can be added at 100 pl per well.

[0087] Fluorescent probes, as those described above, can be read using fluorescence microscopy techniques well-known in the art, thus enabling the visualization and localization of edited and unedited barcode arrays. In some embodiments, the detection probes are read by standard epifluorescence microscopy, which uses a wide-field light source, such as a mercury or xenon arc lamp, along with appropriate excitation and emission filters to detect the fluorescent signal from hybridized probes. This method allows for the detection of signals in aP-639878-PC large field of view, enabling the analysis of multiple cells simultaneously. However, background fluorescence can sometimes obscure the signal, particularly when working with low-abundance transcripts or in complex tissues.

[0088] In some embodiments, detection probes are read by confocal microscopy, which provide higher resolution and specificity by using a laser to excite fluorophores and a pinhole to eliminate out-of-focus light, thus allowing for clearer images with reduced background noise. In some embodiments, detection probes are read by super-resolution microscopy, which may include methods like STED (Stimulated Emission Depletion) or STORM (Stochastic Optical Reconstruction Microscopy), and can be employed to achieve even greater spatial resolution, enabling the detection of single molecules or closely spaced transcripts. In some embodiments, detection probes are read by Structured Illumination Microscopy (SIM) which is faster, and could be used to retrieve larger areas.

[0089] In some embodiments, quantitative analysis of fluorescence signals are performed using image analysis software to measure signal intensity, co-localization, and spatial distribution, which is crucial for high-throughput experiments or when studying subcellular localization of transcripts.

[0090] In some embodiments, the methods herein utilize a cell comprising more than one barcode array. In some embodiments, a cell comprises two barcode arrays. In some embodiments, each barcode array has a distinct gRNA that targets each barcode array. In some embodiments, the barcodes are simultaneously measured. In some embodiments, the barcode arrays are sequentially measured.Fluorescent Microscopy and Image Processing

[0091] Different protocols are known in the art for visualizing and measuring fluorescent detection probes. Any of them can be used to implement the methods disclosed herein. In an exemplary and non-limiting embodiment, immediately before the imaging, the cell buffer is replaced with fresh anti-bleaching buffer, for example 10% glucose (Sigma, G7528), 10 mM Trolox (Sigma, 238813), 1: 100 diluted catalase (Sigma, C3155), 1 mg / mL glucose oxidase (Sigma, G2133) and 50 mM Tris-HCl pH 8.0 (Invitrogen, 15568025) in 4 x SSC. The cells can be imaged, for example, with an inverted fluorescence microscope, as the Zeiss AXIO Observer Z1 which is equipped with a Plan- Apochromat 63x / 1.4 oil immersion objective (Zeiss), ORCA-Flash 4.0 V3 digital CMOS camera (Hamamatsu, C13440) and fluorescenceP-639878-PC lamp illuminators (X-Cite, 120PC Q). Optical sections can be captured with a 21 -plane z-stack at 0.5 pm intervals to cover 10 pm thickness to ensure recovery of all the barcode arrays at different z-planes for each position. Optionally, imaging settings, including the exposure times (10 ms for the DAPI channel, 50 ms for the CFP channel, 300 ms for the 546 channel, and 1000 ms for the 647 channel), can be kept the same for all the experiments to facilitate comparison between images. Positions can be chosen solely based on the DAPI channel to avoid bias. Immersion oil with a refractive index of 1.518 (Zeiss) can be used to minimize spherical aberrations.

[0092] Different methods and software are available in the field and can be used for image processing of the probes signal. Any of them can be used to implement the methods disclosed herein.

[0093] As a non-limiting example, the maximum intensity projection can be calculated according to the following embodiment. To combine information across optical sections while avoiding out-of-focus slices, the focus of each z-slice is assessed by calculating the variance of the Laplacian of the corresponding DAPI image. Then these values are scaled from 0 to 100 and the largest stretch of slices are identified where this normalized measure of focus is above 20. Maximum intensity projection is then applied to this stretch of z-slices for all the channels.

[0094] As a non-limiting example, cell segmentation is done by using the GPU -based ‘cyto’ model of CellPose, a generalist, deep learning-based cell segmentation algorithm. This can be applied only to DAPI stained nuclei in order to avoid incorrect segmentation of neighboring cells. Cells that intersected the border of the image are excluded from the analysis. For segmentation of barcode array spots, classifiers can be manually trained through the interactive pixel classification workflow of Ilastik, based on one randomly picked position out of at least 7 positions for each relevant condition. The classifier can be then applied to the whole data set through batch processing. The probability threshold for Ilastik probability masks can be set to 0.5. Any barcode array spots identified outside of cell nuclei or with the size below 3 pixels can be excluded from the analysis.

[0095] Similarly, intensity can be measured according to methods known in the field. As a non-limiting example, after applying background subtraction with 50 pixels rolling ball radius, the intensity of barcode array spots in each channel can be obtained by the integration of pixel intensity values over the segmented area of the spot. To estimate the edit level of each array,P-639878-PC the intensity ratio can be calculated, defined as the base-2 logarithm of the fluorescence intensity in the edited channel divided by the intensity in the unedited channel. Using this measure, the edit level of each cell can be quantified as the average of intensity ratios for all its barcode arrays. The intensity of H2B-CFP is calculated as the natural log of average pixel intensity over the segmented nuclei.

[0096] The intensity readout of each detection probe is a function of the concentration of the complementary transcripts. Thus, calculating the ratio between the intensity readouts provides an indication of the degree of editing of the barcode array. Consequently, calculating the ratio between the intensity readouts provides an indication of the intensity of the cell signal that activates the gRNA transcription. In some embodiments, the ratio between the readouts is calculated by diving the readout values of the first probe by the readout value of the second probe.

[0097] In some embodiments, the degree of editing of the barcode array is determined by a classifier trained to predict the number of edits based on the readout signals. A number of classifiers known in the art can be used to predict the number of edits of the array. In some embodiments, to train the barcode classifier, two-channel fluorescence images of barcode array spots with known edit states are used. Images containing multiple spots were filtered out. The remaining images are resized, using Python's skimage package, to match the dimensions of the largest image in the dataset. Intensity values are also normalized by scaling each channel according to the maximum intensity value of that channel across the dataset. The labels are then one-hot encoded into 13 classes corresponding to the number of possible edits. A dataset can be split into training, validation, and test sets, with 20% of the data reserved for testing. The remaining 80% can be split further, allocating 25% for validation (resulting in an effective 60 / 20 / 20 split for training, validation, and testing). For data augmentation, rotation, horizontal and vertical flipping, and nearest-neighbor filling can be applied on the training images to enhance the model’s robustness. No augmentation must be applied to the validation and test data.

[0098] In some embodiments, the classifier comprises a convolutional neural network (CNN). In some embodiments, the CNN model comprises four convolutional layers, each with L2 regularization with a factor of 0.001 and leaky ReLU activation with an alpha value of 0.001. Except for the first layer, every convolutional layer can be followed by 2D Max pooling with a 2x2 window and a dropout layer with a dropout rate of 0.2. The model then flattens theP-639878-PC output from convolutional layers to feed into a dense layer, which also utilizes L2 regularization and leaky ReLU activation, followed by a dropout layer with a dropout rate of 0.35. Finally, the output layer consists of a single unit producing 13 output values, corresponding to the probabilities of the barcode array containing between 0 and 12 edits.Further Methods

[0099] A skilled artisan would appreciate that the methods described above can be easily adapted for detecting the degree of editing of an endogenous transcript in a cell. In such case, the use of an exogenous barcode array and of an exogenous genome editing system is not necessary. In some embodiments, the ratiometric method disclosed herein can be used straightforwardly to detect the degree of editing of an endogenous transcript.

[0100] In some embodiments, disclosed herein is a method for detecting the degree of editing of a transcript in a cell, comprising: a. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the transcript, respectively; b. measuring the readouts of said first and second detection probes; c. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of the degree of editing of said transcript.

[0101] A skilled artisan would appreciate that the methods described above can be easily adapted for detecting the degree of editing of an exogenous barcode that identifies a specific condition or perturbation. These barcodes are sometimes termed static barcodes. In such case, the use of an exogenous genome editing system is not necessary. In some embodiments, the ratiometric method disclosed herein can be used straightforwardly to detect the degree of editing of an exogenous barcode.

[0102] In some embodiments, disclosed herein is a method for detecting the degree of editing of a barcode in a cell, comprising: a. providing a cell comprising a barcode array incorporated in its genome and comprising at least one barcode sequence targetable by a genome editing system;P-639878-PC b. optionally inducing transcription of the barcode arrays; and c. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively; d. measuring the readouts of said first and second detection probes; e. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of degree of editing of said barcode,

[0103] A skilled artisan would appreciate that the methods described above can be easily adapted for detecting the activity of any endogenous promoter and / or enhancer. In such case, the gRNA is to be inserted downstream of said promoter and / or enhancer. Upon the endogenous activation of said promoter / enhancer, the gRNA will guide the editing system to an exogenous barcode array.

[0104] In some embodiments, disclosed herein is a method for detecting the activity of a promoter and / or an enhancer region, comprising: a. providing a cell comprising: i. a barcode array incorporated in its genome and comprising at least one barcode sequence targetable by a genome editing system, and ii. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to said promoter and / or enhancer region, and a base editing enzyme, wherein activation of said promoter and / or enhancer region induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering base editing of said barcode sequence; b. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively,P-639878-PC c. measuring the readouts of said first and second detection probes, d. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of the activity of said promoter and / or enhancer region.

[0105] As note herein, for any of the cells and methods disclosed herein, a cell may comprise more than one barcode array. In some embodiments, a cell comprises two barcode arrays. In some embodiments, each barcode array has a distinct gRNA that targets each barcode array. In some embodiments, the barcodes are simultaneously measured. In some embodiments, the barcode arrays are sequentially measured.Kits

[0106] In some embodiments, disclosed herein is a kit comprising: a. a cell comprising: i. at least one barcode array incorporated in its genome, comprising at least one barcode sequence targetable by a genome editing system, and optionally operably linked to a first inducible promoter, and ii. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to a promoter responsive to said cell signal, and a base editing enzyme, wherein said cell signal induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering base editing of said barcode sequence; and b. optionally a means for inducing transcription of the barcode arrays; c. a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively.DefinitionsP-639878-PC

[0107] As used herein, the singular form "a", "an" and "the" include plural references unless the context clearly dictates otherwise.

[0108] As used herein, the term “about”, when used herein in reference to a value, refers to a value that is similar, in context to the referenced value. In general, those skilled in the art, familiar with the context, will appreciate the relevant degree of variance encompassed by “about” in that context. For example, in some embodiments, the term “about” may encompass a range of values that within 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or less of the referred value.

[0109] As used herein, the terms “comprise”, "comprises", "comprising", "includes", "including", “having” and their conjugates mean "including but not limited to".

[0110] As used herein, the term “consisting of’ means “including and limited to”. The term "consisting essentially of" means that the composition, method or structure may include additional ingredients, steps and / or parts, but only if the additional ingredients, steps and / or parts do not materially alter the basic and novel characteristics of the claimed composition, method or structure.

[0111] As used herein, the term "consisting essentially of" means that the composition, method or structure may include additional ingredients, steps and / or parts, but only if the additional ingredients, steps and / or parts do not materially alter the basic and novel characteristics of the claimed composition, method or structure.

[0112] As used herein, the term “corresponding to” refers to a relationship between two or more entities. For example, the term “corresponding to” may be used to designate the position / identity of a structural element in a compound or composition relative to another compound or composition (e.g., to an appropriate reference compound or composition). For example, in some embodiments, a monomeric residue in a polymer (e.g., an amino acid residue in a polypeptide or a nucleic acid residue in a polynucleotide) may be identified as “corresponding to” a residue in an appropriate reference polymer. For example, those of ordinary skill will appreciate that, for purposes of simplicity, residues in a polypeptide are often designated using a canonical numbering system based on a reference related polypeptide, so that an amino acid “corresponding to” a residue at position 190, for example, need not actually be the 190th amino acid in a particular amino acid chain but rather corresponds to the residue found at 190 in the reference polypeptide; those of ordinary skill in the art readily appreciateP-639878-PC how to identify “corresponding” amino acids. For example, those skilled in the art will be aware of various sequence alignment strategies, including software programs such as, for example, BLAST, CS-BLAST, CUSASW++, DIAMOND, FASTA, GGSEARCH / GLSEARCH, Genoogle, HMMER, HHpred / HHsearch, IDF, Infernal, KLAST, USEARCH, parasail, PSI- BLAST, PSI-Search, ScalaBLAST, Sequilab, SAM, SSEARCH, SWAPHI, SWAPHI-LS, SWIMM, or SWIPE that can be utilized, for example, to identify “corresponding” residues in polypeptides and / or nucleic acids in accordance with the present disclosure. Those of skill in the art will also appreciate that, in some instances, the term “corresponding to” may be used to describe an event or entity that shares a relevant similarity with another event or entity (e.g., an appropriate reference event or entity). To give but one example, a gene or protein in one organism may be described as “corresponding to” a gene or protein from another organism in order to indicate, in some embodiments, that it plays an analogous role or performs an analogous function and / or that it shows a particular degree of sequence identity or homology, or shares a particular characteristic sequence element.

[0113] As used herein, “encoding” refers to an RNA molecule that contains a gene that encodes a protein of interest, or a fragment thereof. In another embodiment, an RNA molecule comprises or consists of a protein coding sequence that encodes a protein of interest, or a fragment thereof. In another embodiment, one or more other proteins, or a fragment thereof is also encoded. In another embodiment, the protein of interest, or a fragment thereof, is the only protein encoded. Each possibility represents a separate embodiment of the present disclosure.

[0114] As used herein, the term "fragment" refers to a protein or polypeptide that is shorter or comprises fewer amino acids than the full-length protein or polypeptide. In another embodiment, fragment refers to a nucleic acid encoding the protein fragment that is shorter or comprises fewer nucleotides than the full-length nucleic acid. In one embodiment, the fragment is an N-terminal fragment. In another embodiment, the fragment is a C-terminal fragment. In one embodiment, the fragment is an intrasequential section of the protein, peptide, or nucleic acid.

[0115] In some embodiments, “homology” refers to identity of a protein sequence encoded by a modified (e.g., nucleoside-modified) polyribonucleotide to a sequence disclosed herein of greater than 70%. In another embodiment, the identity is greater than 72%. In another embodiment, the identity is greater than 75%. In another embodiment, the identity is greater than 78%. In another embodiment, the identity is greater than 80%. In another embodiment,P-639878-PC the identity is greater than 82%. In another embodiment, the identity is greater than 83%. In another embodiment, the identity is greater than 85%. In another embodiment, the identity is greater than 87%. In another embodiment, the identity is greater than 88%. In another embodiment, the identity is greater than 90%. In another embodiment, the identity is greater than 92%. In another embodiment, the identity is greater than 93%. In another embodiment, the identity is greater than 95%. In another embodiment, the identity is greater than 96%. In another embodiment, the identity is greater than 97%. In another embodiment, the identity is greater than 98%. In another embodiment, the identity is greater than 99%. In another embodiment, the identity is 100%.

[0116] Various embodiments and aspects of the present invention as delineated hereinabove and as claimed in the claims section below find experimental support in the following examples.EXAMPLESEXAMPLE 1MethodsDesign of INSCRIBE barcode arrays

[0117] INSCRIBE barcode arrays are made of 12 identical barcodes, each 31bp long, that are assembled together by Golden Gate assembly, as described in Pryor, J. M. et al. Enabling one- pot Golden Gate assemblies of unprecedented complexity using data-optimized assembly design. PLoS One 15, e0238592 (2020). Each barcode includes a 20bp probe site that partially overlaps with a 20bp gRNA target site. Each gRNA target site was designed to contain only one editable A nucleotide within the activity window of ABE, to ensure that edit outcomes are pure and predictable. Probe sequences were designed with 50% GC content and predicted Tm between 56 and 60°C. We also avoided recognition sites of certain restriction enzymes (Bsal, BsmBI, Bpil, Aarl and Xbal) within the memory arrays to facilitate cloning. Identification of individual barcodes within an array in sequencing data is facilitated by unique 4bp cloning scars flanking each barcode.Plasmid constructionP-639878-PC

[0118] The sequence of plasmids, probes, and constructs used in this study are listed in Sequence List. All plasmids were sequence verified by full plasmid sequencing (Plasmidsaurus).

[0119] The Dox-inducible system was designed as an all-in-one plasmid with the PiggyBac ITRs and was synthesized by VectorBulider. The ABEMax (Addgene, 112095) is driven by the tet-responsive promoter (TRE3G). The modified rtTA (Tet-On 3G) is constitutively expressed by EFl A promoter and is followed by self-cleaving P2A peptide and puromycin resistance gene. The degron was synthesized as a gBlock by IDT and inserted downstream of ABEMax within the same open reading frame, following a 3 x GGGS linker. The TetOn- ABEMax plasmid, comprising PiggyBac-TRE3G-ABEMax-ecDHFR_EFla-Tet3G-2A- PuroR, comprises SEQ ID NO.: 24.

[0120] gRNAs targeting all the 12 barcodes of each barcode array were integrated downstream of H2B-CFP coding region, spaced by the triple-helix sequence to stabilize the H2B-CFP mRNA that lacks poly-(A) tail after self-cleavage. The gRNA sequence was flanked by Hammerhead (HH) and Hepatitis Delta Virus (HDV) ribozymes, to release gRNA from transcripts that also encode H2B-CFP. The triple-helix-gRNA-ribozyme sequences were synthesized as gBlocks by IDT and integrated into the target site through HiFi DNA Assembly Cloning Kit (NEB, M5520). WNT- and BMP-responsive promoters were used to drive the expression of the H2B-CFP-gRNA constructs. These plasmids included hygromycin resistance for subsequent selection. The gRNA 1 -Ribozyme sequence (complementary to first 6nt of gRNA-HH-gRNA-gRNA scaffold- HDV) targeting the barcodes of barcode array 1 comprises SEQ ID NO.: 28. gRNAl comprises a nucleotide sequence as set forth in SEQ ID NO.: 99. The whole construct of gRNAl operably linked to a WNT responsive element comprises the elements PiggyBac-(TCF-LEF)7-H2B-CFP-Triplex-HH-gRNAl-HDV_SV40-HygroR, as in SEQ ID NO: 25. The whole construct of gRNAl operably linked to a BMP responsive element comprises the elements PiggyBac-BRE-H2B-CFP-Triplex-HH-gRNAl-HDV_SV40-HygroR, as in SEQ ID NO.: 26. gRNA2 -Ribozyme sequence (complementary to first 6nt of gRNA- HH-gRNA-gRNA scaffold-HDV) targeting the barcodes of barcode array 2 comprises SEQ ID NO.: 29. gRNAl comprises a nucleotide sequence as set forth in SEQ ID NO.: 100. The whole constructs of gRNA2 operably linked to a BMP responsive element comprises the elements PiggyBac-BRE-H2B-CFP-Triplex-HH-gRNA2-HDV_SV40-HygroR, as in SEQ ID NO.: 27.P-639878-PC

[0121] All 12 barcodes and T3 promoter were synthesized as single strand DNA by IDT, then annealed to make double stranded DNA, and assembled together in one reaction by the Bsal restriction enzymes based Golden Gate Assembly (NEB, E1601). The inserts possess Bsal restriction sites at both ends in the proper orientation, each followed by a 4 base pair sequence to achieve ordered assembly. The handle for inserted barcode sites from 1 to 12 and T3 promoter are TGCC-GCAA, GCAA-ACTA, ACTA-TTAC, TTAC-CAGA, CAGA-TGTG, TGTG-GAGC, GAGC-AGGA, AGGA-ATTC, ATTC-CGAA, CGAA-ATAG, ATAG- AAGG, AAGG-AACT, and AACT-ACCG.

[0122] The barcode array 1 (BC1) is as set forth in SEQ ID NO.:4, and the whole construct is as set forth in SEQ ID NO.: 22. The barcode array 2 (BC2) is as set forth in in SEQ ID NO.: 6, and the whole construct is as set forth in SEQ ID NO.: 23.

[0123] 35 plasmids comprising BC1 and BC2 barcode arrays in different editing states were used in the experiments, as indicated in Table 1.

[0124] Table 1. BC1 and BC2 barcode arrays in different editing states.P-639878-PCP-639878-PCP-639878-PC

[0125] Barcode sequences BC1 were detected with probes comprising SEQ ID NOs.: 101 and 102. Barcode sequences BC2 were detected with probes comprising SEQ ID NOs.: 103 and 104.Cell culture

[0126] HEK293 (ATCC, CRL-1573) cells were cultured in DMEM (Gibco, 11960069) supplemented with 10% fetal bovine serum (PEAK, PS-FB4), and 1 x penicillin- streptomy cin- L-glutamine (Gibco, 10378016) on polystyrene plates at 37 °C and 5% CO2.

[0127] For routine passaging, the growth media was removed, after one brief wash with 1 x PBS (Gibco, 14190250), followed by the addition of 0.05% trypsin (Gibco, 25-300-120) and incubation at 37°C in a 5% CO2 incubator for 5 minutes. Trypsin was then neutralized with growth media at room temperature. The cells were then centrifuged for 5 minutes at 300g, the supernatant was discarded, and the cell pellet was resuspended in fresh growth media. The cells were then reseeded into new tissue culture plates for subsequent cell culture.Cell line engineering

[0128] INSCRIBE components were integrated over multiple rounds of transfection and selection. For all transfection rounds, HEK293 cells were plated in 24 well plates at a density of 200,000 cells per well one day before transfection, then co-transfected with 400 ng of the constructs to be integrated and 100 ng of the piggyBac transposase together with 2 pl of Lipofectamine 2000 (Invitrogen, 11668027) according to the manufacturer’s instruction. One day after, the transfected cells were replated to new 24 well plates and selection was started with corresponding antibiotics. The first layer of insertion was a series of synthetic barcode arrays, 35 cell lines for barcode array 1, and 34 cell lines for barcode array 2 to mimic the different edit status that may arise during recording. These cell lines were engineered in parallelP-639878-PC and selected with 5 g / mL blasticidin (Gibco, R21001). After the ratiometric barcode readout revealed that the majority of the cells had barcode arrays inserted, we integrated the signal responsive gRNA reporter through a second round of transfection into the polyclonal cell lines with unedited barcode arrays, then selected with 100 pg / mL hygromycin (Thermo Fisher, 10687-010). After verifying the reporter response through ligand stimulation at cell population level, we integrated the TetOn inducible ABEMax through a third round of transfection on the top of the previous two insertions, then selected with 2 pg / mL puromycin (InvivoGen, ant-pr- 1 ). In each round of selection, the engineered cells from 1 well of 24 well plate were expanded to 3 wells of 6 well plate, which usually takes 2 to 3 weeks, then frozen for subsequent experiments. Finally, we used 100 ng / ml of Dox (Sigma, D9891) and 10 pM TMP (Sigma, 92131), together with 3 pM of CHIR (TOCRIS, 4423) or 64 ng / ml of BMP2 (R&D, 335-BM) to stimulate the polyclonal population for 3 days to detect the proportion of cells harboring all INSCRIBE components with ratiometric barcode readout, based on which we determined the total number of monoclonal lines to be screened.Establishing monoclonal cell lines by cell sorting

[0129] The final verified HEK293 polyclonal cells were trypsinized by 0.05% trypsin (Gibco, 25-300-120) at 37°C in a 5% CO2 incubator for 5 minutes. Subsequently, trypsin was neutralized with growth media at room temperature. The cells were centrifuged for 5 minutes at 300g, the supernatant was discarded, and the cell pellet was resuspended in 1 % BSA (Cell Signaling, 9998S) in PBS. The cell suspension was then filtered through a filter cap into flow cytometry tubes, and stained with 5 pl of 7- Amino- Actinomycin D (7-AAD, BD Pharmingen, 559925) per million cells at 4°C for at least 10 mins. Cell sorting was then performed using a fluorescence-activated cell sorter (BD FACSAria) through the 100 pm nozzle, the 7-AAD negative (the viability) and H2B-CFP negative (no leaky reporter expression) cells were gated and collected as single cell per well into 96-well plates, with 4 plates for each INSCRIBE cell line. Single cells were cultured under 200 pl of standard culture medium at 37°C in a 5% CO2 incubator, and the medium was replaced independently for each well every week.

[0130] The putative antibiotic -resistant colonies were cultured until 80% confluency. The colonies were then dissociated, counted, and diluted to a density of 0.5 cells per 100 pL in N2B27 / 2iLIF medium. We replated the diluted cells into gelatin coated 96 well plates at 100 pL per well. Wells with multiple colonies were marked off and viable cells were expanded to establish monoclonal cell lines.P-639878-PC

[0131] Once the monoclonal lines were recovered and expanded, we used 100 ng / ml of Dox (Sigma, D9891) and 10 pM TMP (Sigma, 92131), together with 3 pM of CHIR (TOCRIS, 4423) or 64 ng / ml of BMP2 (R&D, 335-BM) to stimulate the cells for 3 days. Ratiometric barcode readout was then used to screen the lines.Signal recording upon pathway stimulation

[0132] Dox (Sigma, D9891) was reconstituted in PBS (Gibco, 14190250) to a final concentration of 1 mg / ml. TMP (Sigma, 92131) was reconstituted in DMSO (Sigma, 276855) to a final concentration of 10 mM. CHIR (TOCRIS, 4423) was reconstituted in DMSO to a final concentration of 10 mM. BMP2 (R&D, 335-BM) was reconstituted in a buffer with 4mM HC1 (Fluka, 320331), 0.25% BSA (Cell Signaling, 9998S) to a final concentration of 150 pg / ml. All of these reagents were aliquoted and stored at -20 °C, except for BMP2 which was stored at -80°C, thawed immediately before use and diluted with the appropriate culture medium.

[0133] For the dosage dependent signal recording, 4000 of INSCRIBE cells were seeded on 96 well plate one day before stimulation, then the medium with various concentrations of ligand and Dox combinations was added to each well, followed by recording for three days. For recording signaling duration, 4000 INSCRIBE cells were seeded on 96 well plate at different time points, followed the recording with constant ligand concentration the next day, followed by ratiometric barcode readout at the same time for different durations of recording to eliminate the batch effect. For the signaling memory experiments, 8000 of INSCRIBE cells were seeded on 96 well plate one day before stimulation, after three days (BC1 array) or two days (BC2 array) of initial stimulation and recording (with Dox and TMP), cells were split into 2 wells, 8000 cells each, and cultured in media without ligands. After every three days, cells were split into 4 wells, 8000 cells for each. Two wells were used for the three days (BC1 array) or two days (BC2 array) of the second stimulation (without Dox and TMP) or control. The remaining two wells were maintained in culture without ligands, for the next time point. The ratiometric barcode readout for different time intervals between two stimulations was performed immediately after the second stimulation.Ratiometric barcode readout

[0134] For ratiometric barcode readout, we seeded the cells on glass-bottom 96-well plates (Cellvis, P96-1.5H-N) that were coated with 20 pg / ml laminin (Biolamina, LN511) at 37°CP-639878-PC overnight. The preferred cell density was around 10,000 to 20,000 cells per well, to allow straightforward segmentation while maximizing the number of cells analyzed in each field of view (FOV).

[0135] Cells were washed with 1 x PBS (Gibco, 14190250), followed by fixation with a fresh mixture of methanol (Sigma, 494437) and acetic acid (Sigma, A6283) with a 3: 1 volume ratio at room temperature for 20 min. After two washes in nuclease-free water (IDT, 11-04-02-01) for 5 min each, the cells were incubated with 50 pl of T3 transcription mix at consisting of 0.5 mM NTP (NEB, N0466S), 0.8 U / pl RNase inhibitor (NEB, M0314S), 5 units / pl T3 RNA polymerase (NEB, M0378S) and 1 x RNAPol reaction buffer (NEB, B9012S), at 37 °C, 3 hours. After transcription, cells were fixed with fresh 4% formaldehyde solution (Thermo Scientific, 28906) in PBS for 30 min at room temperature followed by two washes with 2 x SSC (Invitrogen, 15557044) for 5 min each, to remove traces of formaldehyde.

[0136] Subsequently, cells were incubated in 50pl of prewarmed hybridization buffer which consisted of 30% formamide (Invitrogen, AM9344), 10% dextran sulfate (Sigma, D8906), and 2 x SSC at 37 °C for at least 30 min. The cells were then incubated with 4 nM of Alexa Fluor 546 conjugated edited probe (IDT) and 4 nM of Alexa Fluor 647 conjugated unedited probe (IDT) in 50 pl of hybridization buffer for 20 h at 37 °C. Then, the hybridized cells were washed four times (15 min each) at 37 °C with prewarmed wash buffer which consisted of 30% formamide (Invitrogen, AM9344), 0.1% Triton-X 100 (Sigma, T8787) and 2 x SSC to remove excess probes, followed by a brief wash with 4 x SSC. Nuclei were stained with 1 pg / ml DAPI (Thermo Scientific, 62248) in 4 x SSC for 10 min, followed by a wash with 4 x SSC for 5 min.

[0137] Immediately before the imaging, 4 x SSC was replaced with fresh anti-bleaching buffer, which consisted of 10% glucose (Sigma, G7528), 10 mM Trolox (Sigma, 238813), 1 :100 diluted catalase (Sigma, C3155), 1 mg / mL glucose oxidase (Sigma, G2133) and 50 mM Tris- HC1 pH 8.0 (Invitrogen, 15568025) in 4 x SSC. Alternatively, the plate can then be stored in 4 x SSC with 0.02 unit / pl SUPERase RNase inhibitor (Invitrogen, AM2694) at 4°C. Unless otherwise stated, all reagents were added at 100 pl per well.

[0138] For multiple rounds of ratiometric readout, cells after imaging were washed with 4 x SSC for 5 min to remove the anti-bleaching buffer, followed by three washes (15 min each) at 37 °C with prewarmed stripping buffer which consisted of 60% formamide (Invitrogen, AM9344), 0.1% Triton-X 100 (Sigma, T8787), and 4 x SSC. Each stripping step was followedP-639878-PC by a brief wash in 4x SSC. Hybridization, wash, and imaging procedures were then repeated as described above for subsequent barcode arrays.Fluorescence In Situ Hybridization (FISH)

[0139] The sequence of smFISH primary probe pools (SEQ ID Nos: 105-205) and readout probes (SEQ ID Nos: 210-213). For each primary probe, a 30-37 nt mRNA target region was selected, flanked on both sides by three repeats of 15 nt readout probe binding sites. The mRNA target regions were obtained from the PaintS HOP newBalance probe set (hg38, isoformresolved) (Hershberg et al. 2021), and were required to satisfy the following criteria: on_target > 96%, offjarget = 0, repeat_seq = 0, max_kmer < 3 and Tm range from 42 to 47 °C

[0140] For smFISH, we seeded the cells on glass-bottom 96-well plates (Cellvis, P96-1.5H-N) that were coated with 20 pg / ml laminin (Biolamina, LN511) at 37°C overnight. The preferred cell density was around 8,000 to 10,000 cells per well, to allow straightforward segmentation while maximizing the number of cells analyzed in each field of view (FOV) when considering the cytoplasmic size.

[0141] Cells were washed with 1 x PBS (Gibco, 14190250), followed by fixation with fresh 4% formaldehyde solution (Thermo Scientific, 28906) in PBS for 20 min at room temperature. After a wash with 1 x PBS for 5 min to remove traces of formaldehyde, the cells were incubated with 70% ethanol (Sigma, 459844) for an hour at room temperature, followed by two washes with 2 x SSC (Invitrogen, 15557044) for 5 min each.

[0142] Subsequently, cells were incubated in 50pl of prewarmed hybridization buffer which consisted of 30% formamide (Invitrogen, AM9344), 10% dextran sulfate (Sigma, D8906), 3 mg / ml PVSA (Sigma, 278424), and 2 x SSC at 37 °C for at least 30 min. The cells were then incubated with 4 nM per probe of primary probe pools (IDT), consisting of 20 probes for ID1 (ID1_R4, SEQ ID Nos: 105-124), 15 probes for ID3 (ID3_R6, SEQ ID Nos: 125-139), 24 probes for ID4 and (ID4+R7, SEQ ID Nos: 140-163) 42 probes for SMAD6 (SMAD6_R9, SEQ ID Nos: 164-205), in 100 pl of hybridization buffer for 20 h at 37 °C. Then, the hybridized cells were washed four times (15 min each) at 37 °C with prewarmed wash buffer which consisted of 30% formamide (Invitrogen, AM9344), 3 mg / ml PVSA (Sigma, 278424), and 2 x SSC, followed by a brief wash with 4 x SSC containing 3 mg / ml PVSA.P-639878-PC

[0143] For cycles of readout probe hybridization and imaging, with the order of ID1 and ID3 for the first round, ID4 and SMAD6 for the second round, and ID3 (rehybridization control) for the third round, fluorescent readout probes (IDT: R4, Alexa 647; R6, Alexa 546; R7, Alexa 647; R9, Alexa 546) were hybridized at 50 nM each in readout buffer, consisting of 10% EC (Sigma, E26258), 10% dextran sulfate (Sigma, D4911) and 2X SSC for 30 min at room temperature. Then, cells were washed with 10% wash buffer which consisted of 10% formamide (Invitrogen, AM9344), 3 mg / ml PVSA (Sigma, 278424), and 4 x SSC, followed by a brief wash with 4 x SSC containing 3 mg / ml PVSA. Cytoplasm and nuclei were stained with 1 pg / ml WGA-647 (Thermo Scientific, W32466) and 1 pg / ml DAPI (Thermo Scientific, 62248) in 4 x SSC for 10 min, followed by a wash with 4 x SSC for 5 min. Nuclei were stained in each round to facilitate image registration. Cell membranes were only stained in the third round.

[0144] Immediately before the imaging, 4 x SSC was replaced with fresh anti-bleaching buffer, which consisted of 10% glucose (Sigma, G7528), 10 mM Trolox (Sigma, 238813), 1 : 100 diluted catalase (Sigma, C3155), 1 mg / mL glucose oxidase (Sigma, G2133) and 50 mM Tris- HC1 pH 8.0 (Invitrogen, 15568025) in 4 x SSC.

[0145] Cells after each rounds of imaging were washed with 4 x SSC for 5 min to remove the anti-bleaching buffer, followed by three washes (5 min each) with 55% wash buffer which consisted of 55% formamide (Invitrogen, AM9344), 3 mg / ml PVSA (Sigma, 278424), and 4 x SSC. Each stripping step was followed by a brief wash in 4x SSC. Cycles of readout probe hybridization and imaging were then repeated as described above for subsequent target mRNAs.

[0146] For smFISH combined with ratiometric readout, a heat-decrosslinking step was performed with 0.1 M sodium bicarbonate and 0.5 M NaCl in water at 65 °C overnight (Kudo et al. 2024). After four washes (15 min each) with 1 x PBS, cells were processed following the ratiometric readout protocol described above.Fluorescence microscopy

[0147] The cells were imaged on the Zeiss AXIO Observer Z1 inverted fluorescence microscope equipped with a Plan- Apochromat 63x / 1.4 oil immersion objective (Zeiss), ORCA-Flash 4.0 V3 digital CMOS camera (Hamamatsu, C13440) and fluorescence lamp illuminators (X-Cite, 120PC Q). Optical sections were captured with a 21-plane z-stack atP-639878-PC0.5 pm intervals to cover 10 (im thickness to ensure recovery of all the barcode arrays at different z-planes for each position. Imaging settings, including the exposure times (10 ms for the DAPI channel, 50 ms for the CFP channel, 300 ms for the 546 channel, 1000 ms for the 647 channel, and 200 ms for the WGA-647), were kept the same for all the experiments to facilitate comparison between images. Positions were chosen solely based on the DAPI channel to avoid bias. Immersion oil with a refractive index of 1.518 (Zeiss) was used to minimize spherical aberrations.Image processing

[0148] Images were processed using custom Python scripts.

[0149] Maximum intensity projection. To combine information across optical sections while avoiding out-of-focus slices, we assessed the focus of each z-slice by calculating the variance of the Laplacian of the corresponding DAPI image. We then scaled these values from 0 to 100 and identified the largest stretch of slices where this normalized measure of focus is above 20. Maximum intensity projection was then applied to this stretch of z-slices for all the channels.

[0150] Registration. For experiments involving multiple rounds of imaging, images were registered using the HyperStackReg plugin in Fiji. An affine transformation model was applied to correct for translation, rotation, scaling, and shear between imaging rounds. Registration was performed using the DAPI channel as a reference, as the nuclear signal provided a stable landmark across cycles.

[0151] Segmentation. For cell segmentation, we used the GPU-based ‘cyto’ model of CellPose3 (Stringer and Pachitariu 2025), a generalist, deep learning-based cell segmentation algorithm. For the ratiometric barcode readout analysis, segmentation was applied only to DAPI-stained nuclei in order to avoid incorrect segmentation of neighboring cells. For the FISH analysis, segmentation was performed on composite images combining WGA-stained cytoplasm and DAPI-stained nuclei, which improve the accuracy of cytoplasmic segmentation. Cells that intersected the border of the image were excluded from the analysis. For segmentation of barcode array spots, we manually trained classifiers through the interactive pixel classification workflow of Ilastik, based on one randomly picked position out of at least 7 positions for each investigated condition. We then applied the classifier to the whole data set through batch processing. The probability threshold for Ilastik probability masks was set to 0.5.P-639878-PCAny barcode array spots identified outside of cell nuclei or with the size below 3 pixels were excluded from the analysis.

[0152] Intensity measurement. After applying background subtraction with 50 pixels rolling ball radius, the intensity of barcode array spots in each channel was obtained by the integration of pixel intensity values over the segmented area of the spot. To estimate the edit level of each array, we calculate the intensity ratio, defined as the base-2 logarithm of the fluorescence intensity in the edited channel divided by the intensity in the unedited channel. Using this measure, the edit level of each cell was quantified as the average of intensity ratios for all its barcode arrays. The intensity of H2B-CFP was calculated as the natural log of average pixel intensity over the segmented nuclei.

[0153] CNN classifier training. To train the barcode classifier, we used two-channel fluorescence images of barcode array spots with known edit states. Images containing multiple spots were filtered out. The remaining images were resized, using Python's skimage package, to match the dimensions of the largest image in the dataset. Intensity values were also normalized by scaling each channel according to the maximum intensity value of that channel across the dataset. The labels were then one-hot encoded into 13 classes corresponding to the number of possible edits. We split the dataset into training, validation, and test sets, with 20% of the data reserved for testing. The remaining 80% was split further, allocating 25% for validation (resulting in an effective 60 / 20 / 20 split for training, validation, and testing). For data augmentation, we applied rotation, horizontal and vertical flipping, and nearest- neighbor filling on the training images to enhance the model’s robustness. No augmentation was applied to the validation and test data.

[0154] The CNN model comprised four convolutional layers, each with L2 regularization with a factor of 0.001 and leaky ReLU activation with an alpha value of 0.001. Except for the first layer, every convolutional layer is followed by 2D Max pooling with a 2x2 window and a dropout layer with a dropout rate of 0.2. The model then flattens the output from convolutional layers to feed into a dense layer, which also utilizes L2 regularization and leaky ReLU activation, followed by a dropout layer with a dropout rate of 0.35. Finally, the output layer consists of a single unit producing 13 output values, corresponding to the probabilities of the barcode array containing between 0 and 12 edits.P-639878-PC

[0155] To evaluate the accuracy of ratiometric readout, we assigned the edit number with the highest probability to each spot. In contrast, for the recording experiments, we calculated the expected value by averaging the products of each state's probability and its corresponding edit number (0 to 12).INSCRIBE components copy number

[0156] The sequence of qPCR primers are SEQ ID Nos: 214-219. The genomic DNA was extracted from 1 million of each selected INSCRIBE monoclonals using the Genomic DNA Purification Kit (NEB, T3010) according to the manufacturer's instructions. In parallel, we plated 12,000 of each selected INSCRIBE monoclonals on glass-bottom 96 well plate (Cellvis, P96-1.5H-N) coated with 20 pg / ml laminin (Biolamina, LN511) for ratiometric barcode array readout. Barcode array number was identified as the average per monoclonals by ratiometric readout. TetOn-ABE and CRE-H2B-CFP-sgRNA copy number were quantified relative to the barcode array using genomic DNA qPCR.

[0157] The targeted 100 bp genomic region was amplified using iTaq Universal SYBR Green Supemix (BIO-RAD 1725120), using primers (IDT) with a melting temperature (Tm) of 60 °C, designed with PrimerQuest (IDT). We targeted blasticidin resistance gene for the barcode array, ABEMax for TetOn-ABE, and CFP for CRE-H2B-CFP-sgRNA. The input for qPCR was 10 ng of genomic DNA, and 300 nM for each primer in a final reaction volume of 10 pl. The samples were incubated for 5 min at 95 °C; 10 s at 95 °C, 30 s at 60 °C for 40 cycles. For each selected INSCRIBE monoclonal, three replicates were performed, taking the average Cq of each INSCRIBE component for following relative quantification.Amplicon sequencing

[0158] For amplicon sequencing combined with ratiometric barcode array readout procedure, 100,000 of WNT-BC1 INSCRIBE cells were seeded on 24 well plate one day before stimulation, then 500 pl medium with 3 pM CHIR, 500 ng / ml Dox and 10 pM of TMP was added to each well, followed by recording for three days. BC2 array only cells were plated in 24 well plates at a density of 200,000 cells per well one day before transfection, then cotransfected 296 ng of CMV-ABEMax plasmid (SEQ ID NO: 208) and 123.6 ng of CAG- sgRNA plasmid (SEQ ID NO: 209) with 2 pl of Lipofectamine 2000 (Invitrogen, 11668027) according to the manufacturer’s instruction, followed by recording for three days. The recorded cells were then split to plate 12,000 INSCRIBE cells on glass-bottom 96 well plate (Cellvis,P-639878-PCP96-1.5H-N) coated with 20 pg / ml laminin (Biolamina, LN511) for ratiometric barcode array readout. The rest of the cells were plated on a new 24 well plate for the amplicon sequencing. The next day, we performed the ratiometric barcode readout and amplicon sequencing for the cells from the same population in parallel.

[0159] The genomic DNA was extracted from the WNT-BC1 INSCRIBE cells or BC2 array only cells using the Genomic DNA Purification Kit (NEB, T3010) according to the manufacturer's instructions. The targeted region was amplified from collected genomic DNA or reference plasmid using high fidelity Herculase II Fusion DNA Polymerase (Agilent, 600675). The input template for PCR was 100 ng of genomic DNA or 1 ng of reference plasmid in a final reaction volume of 50 pl. The samples were incubated for 2 min at 95 °C; 30 s at 95 °C, 30 s at 56 °C and 60 s at 72 °C for 36 cycles; and 10 min at 72 °C. Amplicon libraries contained the barcode arrays with an extra 50bp on each side and were sequenced by the Plasmidsaurus Premium PCR sequencing service, which is based on nanopore long-read sequencing. Raw FASTQ files were aligned to a FASTA-format reference file containing the expected amplicon sequences. Alignment was performed using the bowtie 2, and subsequent analysis and data visualization were performed with custom Python scripts. We extracted base calls from each aligned read at the base-editor target sites. The unique 4bp sequences flanking each barcode were used to identify the position of barcodes in the arrays.Data availability

[0160] All code and processed data required to replicate the analysis is provided through the Github repository https: / / github.com / askarylab / INSCRIBE.EXAMPLE 2Ratiometric readout efficiently recovers barcode array states along with spatial information

[0161] Molecular recording involves engineering cells to accumulate mutations in engineered genomic targets, referred to here as "barcode arrays". If the mutation rate is proportional to the activity of a signaling pathway, the fraction of edited barcodes reflects the cumulative pathway activity in the lineage of each cell (Fig. 1A). As the foundation of a scalable and broadly accessible imaging-based molecular recording system, disclosed herein is a simple method to recover the fraction of edited barcodes in barcode arrays.P-639878-PC

[0162] A method for sensitive in situ readout of DNA barcodes was recently disclosed in Askary, A. et al. In situ readout of DNA barcodes and single base edits facilitated by in vitro transcription. Nat. Biotechnol. 38, 66-75 (2020). That strategy uses a phage RNA polymerase to transcribe the barcode arrays in situ and capture the resulting transcripts in the active site of transcription, which can be visualized as bright spots by Fluorescence In Situ Hybridization (FISH). Hybridization with competing probes can then enable accurate in situ identification of single nucleotide edits. For barcodes with two possible states, edited and unedited, this approach would require two fluorescence channels for each barcode. Since dozens of barcodes are required to accurately infer the signaling history of a cell, decoding the state of each barcode separately would require numerous rounds of hybridization and imaging. It is shown herein that the information needed to infer signaling activity level can be obtained much more efficiently if all barcodes in an array are probed with the same pair of probes against the edited and unedited states (Fig. IB). This approach, called herein ratiometric barcode readout, detects the fraction of edited barcodes in an array, instead of the state of each individual barcode. So, it trades off acquiring unnecessary information for simplicity and scalability.

[0163] The feasibility of ratiometric barcode readout was assessed using cell lines that contain synthetic barcode arrays with known states. The synthetic arrays were designed to contain 12 identical barcodes, placed downstream of a T3 promoter, with a designated single nucleotide varied from A to G within each barcode to mimic the unedited or edited state (Fig. 3A and Fig. 2A). Two independent barcode arrays were designed which can be targeted by orthogonal gRNAs, henceforth referred to as BC1 (Fig. 2A-2D) and BC2 (Fig 3A-3D). DNA constructs were designed to contain barcode arrays with 0 to 12 edits, in different configurations, flanked with piggyBac inverted terminal repeats (ITRs) to enable genomic integration. Then HEK293 cell lines were made, each containing multiple stable integrations for one of these synthetic barcode array constructs.

[0164] After in situ transcription by T3 RNA polymerase, using the previously described approach in Askary, A. et al. In situ readout of DNA barcodes and single base edits facilitated by in vitro transcription. Nat. Biotechnol. 38, 66-75 (2020), two fluorescently labeled probes were hybridized, complementary to the edited and unedited states of the target sites. The resulting images revealed a trend: as the number of edits increased, fluorescence intensity in the channel for the edited state rose, while intensity in the channel for the unedited state diminished (Fig. 2A and Fig. 3A). This effect can be shown quantitatively, by calculating theP-639878-PC ratio of fluorescence intensity in the edited versus unedited channel (Fig. 2B and Fig. 3B). Comparing barcode arrays with the same number of edits, but in different configurations, showed that intensity ratio is a function of the number of edits, not their position within the array (Fig. 2C and Fig. 3C).

[0165] Knowing the true state of each barcode array in these experiments allows training a classifier to predict the number of edits from the microscopy image of an array. A Convolutional Neural Network (CNN) was trained for this task, using images of 23,743 and 15,855 spots, for BC1 and BC2 respectively, corresponding to barcode arrays with 0 to 12 edits (Fig. 2D and Fig. 3D). The trained classifier was able to infer the number of edits in barcode arrays with a macro- averaged Fl score of 0.6 for BC1 and 0.69 for BC2. Accuracy was greater for arrays with a low (0 to 3) or high (10 to 12) number of edits, while the majority of inaccurate predictions occurred in arrays with intermediate edit counts. In total, 91.5% of BC1 arrays and 97.7% of BC2 arrays had predicted edit counts within 2 edits of their actual counts. This confirms that ratiometric barcode readout can infer the edit level of barcode arrays from two- channel images and provides an automated classification tool for this purpose.EXAMPLE 3INSCRIBE enables analog recording of signaling amplitude in single cells

[0166] To demonstrate genetic recording of signaling activity with single cell imaging-based readout, monoclonal HEK293 cell lines were established harboring three components: an inducible ABE, a signal responsive gRNA, and barcode arrays compatible with ratiometric readout (Fig. 1C). The barcode arrays are designed to include 12 target sites for a single guide RNA (gRNA), downstream of T3 promoter (Fig. 1C). Each target site has only one A nucleotide within the editing window of A-to-G base editor (ABE), which overlaps with the probe sequence we use for Fluorescence In Situ Hybridization (FISH) (Fig. 1C). ABE expression in INSCRIBE cell lines can be controlled by doxycycline (Dox) using the Tet-On 3G system. To minimize the possibility of basal editing, ABE is also fused to an ecDHFR degron sequence which can be stabilized by trimethoprim (TMP) (Fig. ID). Edit rate is coupled to either BMP or WNT pathway activity using cis-regulatory elements (CREs) containing multimerized binding sites for BMP SMADs37 and TCF / LEF, respectively. These CREs drive signal dependent production of a transcript encoding both Cyan Fluorescent Protein fused to Histone H2B (H2B-CFP) and a barcode specific gRNA (Fig. 1C). gRNA is released from theP-639878-PC transcript using Hammerhead (HH) and Hepatitis Delta Virus (HDV) ribozymes. To test the performance of different barcode arrays, BMP recorder cell lines with either BC1 or BC2 were made. WNT recorder lines were made only with BC1.

[0167] Constructs were stably integrated in HEK293 cells with three rounds of piggyBac transposition. Multiple monoclonal cell lines were then recovered and analyzed with all INSCRIBE components. BMP signaling was induced by adding 64 ng / ml of recombinant BMP2 and the WNT pathway was stimulated by 3 u M of CHIR99021 (CHIR), a small molecule GSK-3 inhibitor. Canonical BMP and WNT pathway responses are routinely observed in HEK293 cells and their derivatives following stimulation with BMP2 and CHIR, respectively i'Slnte et al. 202I XKudo ei al. 20i0s. Notably, WNT activation has been shown to promote HEK293 proliferation and protect against serum starvation-induced apoptosisei d... Q08), so any confounding effects were minimized by matching seeding density and carefully monitoring cell viability throughout the experiments. In addition, the culture media contained 100 ng / ml of Dox and 10 M TMP. Different clones showed some variability in their baseline edit level and sensitivity to stimulation (Figs. 4A-4C).

[0168] To assess whether INSCRIBE could record signaling activity of BMP and WNT pathways 3 clones of WNT-BC1 configuration, 3 clones of BMP-BC1 configuration, and 2 clones of BMP-BC2 configuration were further examined. The engineered cells were exposed to varying amounts of BMP2 and CHIR, respectively. After culturing the cells for 3 days, samples were in situ T3 transcribed and hybridized with two fluorescently labeled probes for the edited and unedited states. Cells were then imaged in the two channels associated with the probes, as well as DAPI to label nuclei, and CFP. The reporter for each pathway drives the expression of a chimeric transcript that cleaves into H2B-CFP mRNA and barcode targeting gRNA. Since H2B-CFP protein is relatively stable, it is mainly diluted by cell division that takes approximately 24 to 48 hours. Thus, for short recording experiments (3 days in this case) accumulation of H2B-CFP provides a good proxy for the reporter activity in each cell (Fig. 1C).

[0169] In the resulting images, both barcode probe intensities for all integrations and the corresponding H2B-CFP intensity from the same cell were simultaneously recovered (Fig. 12A-C. Subsequently, the editing level of each cell was quantified as the average of intensity ratio or as the average of CNN classifier predicted edits for all its barcode arrays. For both the BMP and WNT pathways, the edit level of cell populations increases with increasingP-639878-PC concentrations of pathway inducers, in a manner correlated with CFP level (Fig. 5A-5H. More importantly, this trend was also observed at the single cell level (Fig. 5I-5M, demonstrating the ability of INSCRIBE to recover past signaling activity in individual cells. Multiple independent clones for each INSCRIBE configuration confirmed consistent correlation between edit level and CFP expression, ensuring the reproducibility and robustness of the recording system. Across these clones, the copy number of TetOn- ABE and CRE-H2B-CFP-gRNA varied within a narrow range of 1 to 3, whereas barcode array copy number showed greater variability, ranging from 2 to 7 (Fig. 13). For all subsequent experiments, the experiments were focused on one clone for each pathway-barcode array pair with the strongest correlation between single-cell edit level and the corresponding CFP intensity across all inducer dosages, referred to as WNT-BC1, BMP-BC1 and BMP-BC2.

[0170] Further, BC1 and BC2 showed different dynamics in response to BMP2. BMP-BC1 cells had lower edit levels compared to BMP-BC2 cells cultured in the same concentration of BMP2 (Fig. 4D). As a result, higher concentrations of BMP2 (16, 64, and 256ng / ml) led to distinct edit levels in BMP-BC1 cells (Fig. 5J). Whereas, BMP-BC2 cells had distinguishable edit levels for lower concentrations of BMP2 (4, 16, and 64ng / ml), with 256ng / ml of BMP2 leading to saturation (Fig. 5C and 5K). This effect is likely due to differences in the efficiency of gRNAs targeting each barcode array. Therefore, it was expected different barcode arrays to have different dynamic ranges, suitable for recording signals with different amplitudes.

[0171] It was further asked whether the dynamic range of INSCRIBE can be tuned by regulating ABE. Varying Dox levels from 100 to 2500 ng / ml did not have a significant effect on edit levels in any of the tested conditions (Fig. 6A-6I). At 20 ng / ml, ABE was not induced sufficiently for recording BMP pathway activity, while there were detectable edit levels in response to 5 M CHIR. Therefore, regulation of ABE expression appears to have a binary outcome, with edit levels being a function of signaling activity once ABE is present at high enough levels.

[0172] Further, to contrast signal recording with snapshot measurements of downstream gene expression, we performed multiplexed single-molecule FISH in combination with ratiometric barcode readout. BMP-BC2 cells were stimulated with BMP2 (256 ng / ml) for 1 day, after which we imaged CFP levels, quantified transcripts for ID1 , ID3, ID4, and SMAD6 in the same cells, and then carried out ratiometric barcode readout (Fig. 14A. As expected, all four downstream genes were significantly upregulated upon stimulation (Fig. 14B). The strongP-639878-PC correlation of single-cell ID3 mRNA counts between the first and third rounds of hybridization confirmed the robustness of the multiplexed smFISH protocol (Fig. 14C). While the target genes were well correlated with each other, their correlation with either CFP or edit levels was modest, although statistically significant (Fig. 14D). These results indicate that downstream gene expression provides only transient snapshots of pathway activation, in contrast to the cumulative signaling activity captured by INSCRIBE.

[0173] Together, the results here show that INSCRIBE is an analog recording system capable of recovering signaling amplitude over a fixed time window from single cells. The sensitivity of INSCRIBE can be adjusted using different gRNAs. Recording works over a wide range of ABE levels, facilitating implementation of the system in other cell lines or in vivo models.EXAMPLE 4INSCRIBE can record duration of signaling activity

[0174] In addition to intensity, duration of signaling activity is crucial in regulating cellular behavior. Fluorescent reporters dilute over time by degradation and cell division. Therefore, it is difficult to estimate the signaling duration from their endpoint level. In contrast, barcode edits are irreversible and inheritable, making them ideal for recording signaling history. To test if INSCRIBE can recover signaling duration, cells were cultured for different amounts of time under editing conditions (500 ng / ml Dox and 10 M TMP) combined with 64ng / ml BMP2 or 3pM CHIR (Fig. 7A). The average edit level in each cell was estimated based on the endpoint images (Fig. 7B, after determining the intensity ratio or number of edits by CNN classifier in each barcode array. As anticipated, barcode edits accumulated progressively over time in all cases (Fig. 7C and 7D). In BMP-BC1 and WNT-BC1 cells, this increase was nearly monotonic over a span of 7 days. In contrast, BMP-BC2 cells exhibited a rapid increase in edits within the first 3 days, nearing a fully edited state after 4 days. This is consistent with the higher edit rate of BC2 array (Fig. 4D). Together, the results demonstrate that INSCRIBE can record either the amplitude of a signal over a defined time period (Fig. 5A-5M) or the duration of a signal of known intensity (Fig. 7A-7D), all in a format that is image-readable and can be recovered from single cells.EXAMPLE 5P-639878-PCINSCRIBE barcode arrays are stable and efficiently utilized

[0175] Since the barcode arrays contain 12 tandem repeats of identical gRNA target sites, it is important to verify their long term stability in the genome. Collapse of barcode sequences, leading to loss of memory, has been observed in other molecular recording systems. INSCRIBE uses base editing, which avoids double-strand DNA breaks, and is therefore expected to be less prone to collapse during editing. To assess the stability and editing patterns of barcodes in INSCRIBE cells, long-read amplicon sequencing was used. Further, amplicon sequencing was combined with imaging to validate ratiometric readout against an independent method (Fig. 8A).

[0176] Barcode arrays from genomic DNA of WNT-BC1 cells and cells containing only the BC2 array maintained in culture without editing for more than one year, as well as WNT-BC1 cells grown in editing conditions for 3 days, and from BC2 cells 3 days after transfection with CMV-ABEmax and CAG-sgRNA plasmids were amplified. As additional controls, BC1 and BC2 arrays of defined edit states (001011011100 and 100110110100, respectively), amplified from reference plasmids (Fig. 9A). For all samples, amplicon sequencing showed the same distribution of array lengths centered on the correct length of 416 bp, confirming the stability of INSCRIBE barcode arrays (Fig. 8B and Fig. 9B).

[0177] Sequencing results were also consistent with in situ measurement of barcode edits by ratiometric readout. The fraction of barcode arrays with at least one edit was first compared between sequencing reads and ratiometric readout of cells from the same population. A paired t-test across the replicates from ratiometric readout and amplicon sequencing yielded a p-value of 0.469, indicating no statistically significant difference between the two measurement modalities for the proportion of edited barcode arrays. Both methods measured the proportion of edited barcode arrays to be close to 50% in WNT-BC1 cells grown in editing condition for 3 days and close to 5% for the control unstimulated cells (Fig. 8C). Further, within the edited barcode arrays of WNT-BC1 cells after 3 days of recording a Chi-squared test comparing the distributions of edits number estimated by in situ readout or sequencing yielded a p-value of 0.28, indicating no statistically significant difference between the two measurement modalities (Figs. 8D ). Together with the analysis of synthetic barcode arrays with known ground truth (Fig. 1), this provides further assurance that ratiometric readout accurately recovers the fraction of edited sites in the arrays.P-639878-PC

[0178] Estimating the overall signaling activity is most efficient if all target sites within an array have the same probability of being edited. In contrast, if certain sites are more likely to be edited than others, this bias should be accounted for when integrating the results across all barcodes. Since INSCRIBE barcodes have identical sequences and are targeted by the same gRNA, we expect them to have similar edit rates. To test this, it was first confirmed that long- read amplicon sequencing is accurate at the single nucleotide level for both arrays, using an amplicon with a known edit state that was amplified from the reference plasmid (Fig. 8E). Edit levels were then quantified at each of the 12 target sites in barcode arrays of WNT-BC1 cells, with three replicates for the editing condition, as well as in transfected BC2 only cells (Figs. 8E and 8G). Edit levels at each site were significantly higher in the editing condition compared to the control (at least 17 times), while variation across sites was relatively low (standard deviation is 0.088 for BC1 array, and 0.057 for BC2 array). In BC1, a slight positional bias favoring edits near the phage promoter was detected, while BC2 exhibited a more uniform distribution (Fig. 8G) . Combined with the earlier results (Fig. 2C and 3C), this analysis shows that writing and reading of edits are not overly sensitive to the position of a barcode within an array. It was also found that almost all possible combinations of barcode edits are obtained during recording, and no single combination dominates the outcomes (Figs. 8F and 8H), further confirming that the memory capacity of INSCRIBE is used efficiently.EXAMPLE 6The memory capacity of INSCRIBE cells is sufficient for accurate reconstruction

[0179] INSCRIBE cell lines benefit from multiple genomic integrations of barcode arrays, each providing an independent measurement of base editor activity in a cell. To understand how the memory capacity of INSCRIBE cells influences the reconstruction accuracy, the process of writing and reading edits based on the experimental results was simulated. Base editing is a probabilistic process at the single nucleotide level, with each target site having a probability of being edited in unit time. This probability should be proportional to the signaling activity in the cell. The aim is to infer this underlying probability in each cell from the observed edit level of barcode arrays. In simulating the editing process based on the empirical findings (Fig. 8E), it was assumed that the editing probability is uniform across all sites within a barcode array, leading to a binomial distribution with 12 trials. The editing probability was varied from 0 to 1 , in increments of 0.01 , to model different levels of signaling activity, and the same editing probability was applied for different simulated barcode arrays within the same cell.P-639878-PCSubsequently, barcode arrays were grouped to simulate cells containing 1 to 10 barcode array integrations. To recreate the readout process, each simulated barcode array was paired with a real instance of the BC 1 array with the same number of edits, selected randomly from images of cells with known ground truth (Figs. 1 , 2, and 3). The CNN model was used to classify those images and recorded the results as the observed edit level of the simulated barcode arrays. The inferred edit probability in each simulated cell was then calculated by maximum likelihood estimation based on all its barcode arrays.

[0180] The results showed a linear correlation between the inferred and true edit probabilities (Fig. 10A). As the number of barcode arrays per cell increases, the correlation between inferred and true edit probabilities is improved, indicating higher reconstruction accuracy (Fig. 10B). However, there are diminishing returns beyond 5 barcode arrays. Therefore, the number of barcode array integrations in WNT and BMP recording INSCRIBE cell lines (Fig. 10C) is within the range required for accurate single cell reconstruction of signaling activity.

[0181] The integration of multiple barcode arrays can also introduce noise into the recording process, if barcodes at different genomic loci are edited with slightly different rates. To assess this noise, empirical results from each INSCRIBE cell line were compared with simulations similar to those described above (Figs. 10D-10F). In each case, the variability in recovered edit levels was evaluated against the mean of barcode edit level in single cells. It was first established a baseline for the readout noise, resulting solely from the ratiometric readout process. For this measurements of cells with known edit states were used (Fig. 2A-2D and Fig. 3 A-3D), where all barcode arrays in a cell have exactly the same number of edits. For any given edit level, variation in recording experiments (Fig. 10C) was higher than the baseline readout noise. Part of this additional variation can be attributed to the inherent sampling differences, where each barcode array within a cell may end up with a different number of its 12 barcodes edited, even when all arrays in a cell share the same editing probability. This aspect of the recording noise was recorded by simulating cells with integration counts mirroring cells in these (Fig 10C) experiments and applying the same readout noise. The difference between the variation observed in these simulations and the variation seen in experimental results can be attributed to varying edit probabilities of arrays at different genomic loci. To reflect this, simulations were performed where a normally distributed noise was added to the cell's overall edit probability, generating a slightly different edit probability for each array within the cell.P-639878-PC

[0182] The analysis showed that, in all cases, the contribution of readout noise to the overall variation is minimal. For WNT-BC1 and BMP-BC1, the empirical variance was consistent with simulations incorporating normally distributed noise with standard deviations of 0.21 and 0.28, respectively (Fig. 10D-10E). This suggests that different barcode arrays integrations in these cells are edited at somewhat different rates. In contrast, observed variance in BMP-BC2 cells had considerable overlap with simulations that assume equal edit probability for all barcode arrays (Fig. 10F), and a modest normal noise with standard deviation of 0.09 was sufficient to match the experimental results. Therefore, the positional effect of genomic integration on BC2 appears to be weaker than BC1. This may be due to higher accessibility of BC2 integrations or sequence specific differences between gRNAs.EXAMPLE 7INSCRIBE reveals persistent cellular memory in the BMP pathway

[0183] Cell-to-cell variability is a common and essential feature of biological systems, allowing for a range of outcomes that influence adaptability and function. Variability is particularly important in the context of signaling, where differences in cellular responses can influence developmental processes and tissue organization. Even in a genetically identical population, individual cells can display a wide range of behaviors and responses to the same external signals. Origins of this variability can be ascribed to the stochastic nature of protein expression and regulatory features of the signaling pathways. However, the functional consequences of cellular variability are often difficult to identify, because it requires linking the initial heterogeneity to an eventual phenotype. By recording signaling activity level in the genome of the cells, INSCRIBE provides a way to establish this connection.

[0184] Using the INSCRIBE cell lines, it was explored whether initial heterogeneity in pathway activity levels results in persistent differences among cells, affecting their likelihood of exhibiting stronger or weaker responses to subsequent stimulations. Specifically, cells exposed to BMP or WNT signals twice were examined, with varying time intervals between exposures (Fig. 11 A). Despite being genetically identical, individual cells exhibit variability in their response levels to each stimulation. The initial response was recorded in the genome as barcode edits, which are inherited by progeny cells. Recording was turned off during the second exposure and the magnitude of the second response was measured by H2B-CFP accumulation.P-639878-PCIt was asked if there is a correlation between the magnitudes of response to the first and second stimulations, and if so, how this correlation evolves over time. Correlation in this context signifies a memory of the past response level, which persists over several cell generations.

[0185] For both pathways, H2B-CFP produced during the first exposure was diluted to a consistent low baseline level within 3 days after the signal was removed (Figs. 1 IB -1 ID, green data points). In contrast, when cells were stimulated a second time, their H2B-CFP levels were elevated above the baseline by the end of the experiment (Fig. 11B -11D, pink data points), indicating that in the experiments the endpoint CFP intensity reflects only the magnitude of the second response. Similarly, it was confirmed that barcode edits capture only the initial response level by demonstrating that edit levels remained unchanged after the second stimulation, as no Dox and TMP were added to induce recording during this phase (Figs. 1 I E and 1 1 G). While Dox is necessary for the expression of ABE and the accumulation of edits, it is not required for the expression of H2B-CFP from the signal-responsive promoters. This allowed to measure the amplitude of response to the first and second stimulations separately.

[0186] It was then examined the correlation between the first and second response levels at the single-cell level (Fig 11H). As anticipated from the earlier results (Fig 2A-C, Fig 5), immediately after treating WNT-BC1 cells with CHIR for 3 days, BMP-BC1 cells with BMP2 for 3 days, and BMP-BC2 cells with BMP2 for 2 days, there was a strong correlation between CFP and edit levels, whether inferred from intensity ratio or the CNN model. For the WNT pathway, the correlation between the magnitudes of the first and second responses decreased rapidly and consistently as the interval between the two stimulations increased from 3 to 18 days (Figs. 11H and 11J). Experiments were stopped once the raw correlation values, before normalization, reached 0.2. Remarkably, the BMP pathway exhibited distinct dynamics (Fig. 11H). The correlation remained nearly steady, fluctuating between 0.34 to 0.5, for stimulations up to 18 days apart, and declined only for intervals beyond 3 weeks. To test if cells with low reporter activity and therefore little recording have affected our analysis, we carefully controlled for cells with edit levels and H2B-CFP intensities below the 95th percentile of unstimulated control population. 99.9% of WNT-BC1, 98.9% of BMP-BC1, and 100% of BMP-BC2 cells were above this threshold (Fig. I ll), indicating that the contribution of fully silenced cells is minimal. Importantly, the overall patterns of rapid memory loss in WNT pathway and persistent memory in BMP pathway at single cell level were observed, regardless of whether these low-responding cells were included in the analysis or not (Fig. 1 1H and 1 I L).P-639878-PCThis finding reveals that activation of the BMP pathway induces a lasting cellular memory. Descendants of cells that exhibit a strong BMP response tend to maintain an elevated responsiveness to subsequent BMP stimulation, even up to 18 days later (Figs 11K and 11M. This phenomenon cannot be attributed to genetic differences between cells, as the observed memory effect dissipates by 26 days after the initial exposure.EXAMPLE 8Discussion of previous examples

[0187] The fate of a cell is impacted by factors such as lineage and signaling history that are often inaccessible to direct observation. Programming cells to chronicle their molecular history in their genome over time has emerged as a promising solution to this fundamental problem. INSCRIBE is a new approach to imaging-based molecular recording that infers past signaling activity in individual cells from endpoint measurements, without the need for sequential imaging. INSCRIBE permanently records the signaling activity level over a specified time, or the duration of signaling with a known intensity, as a set of single base edits in genomic barcode arrays. The fraction of edited sites can be detected at a later time using ratiometric barcode readout, which only requires ordinary fluorescence microscopy with two channels for each signal of interest.

[0188] INSCRIBE is made possible through several key innovations. Among others, first, the production of gRNA in a signal-dependent manner is enabled by releasing functional gRNA from Pol2 transcripts using HH and HDV ribozymes. Second, an inducible CRISPR base editor introduces precise and predictable mutations at designated sites within the barcode arrays exclusively during the recording phase. Third, ratiometric barcode readout leverages probe competition to infer the number of mutations in each barcode array. Ratiometric readout drastically reduces the cost and technical challenges associated with existing imaging-based barcode readout methods, enabling greater access for researchers. It also cuts down the overall imaging time significantly, and thereby facilitates analysis of more cells and larger samples. Further, in situ transcription of barcodes by phage RNA polymerase is compatible with FISH- based spatial genomics methods that enable deep characterization of cell states at endpoint. Fourth, by integrating information across multiple target arrays in each cell, INSCRIBE achieves higher single cell reconstruction accuracy. Finally, a computational pipeline wasP-639878-PC developed for analyzing barcode images, including CNN models to classify spots corresponding to each barcode array. Along with straightforward and cost-effective experimental procedures, we anticipate this will facilitate the widespread adoption of INSCRIBE for studying how past signaling events shape development and disease outcomes.

[0189] INSCRIBE was tested in HEK293 cell lines engineered to record the activity of either BMP or WNT pathway. Barcode edits accumulated in INSCRIBE cells in proportion to the inducer level (BMP2 or CHIR concentration) and signaling duration. In contrast with reporter systems that monitor pathway activity by expressing a fluorescent protein, recorder systems like INSCRIBE capture pathway activity as DNA mutations. However, both reporter and recorder assays rely on CREs that drive expression of a transcript proportional to the signaling activity. Signaling pathways can elicit complex and multifaceted responses in cells, with various endogenous targets expressed at different levels and exhibiting distinct dynamics? 1. So a single CRE, or a single gene, may not fully capture all the nuances of cellular response to a signal or pathway activity across all cell types. Therefore, the choice of CRE depends on the specifics of the model system and research objective. In principle, INSCRIBED recording capabilities are not restricted to transcriptional regulation of gRNA through CREs; any signal that can be converted into a proportional change in edit rate can be recorded and read out similarly. For example, future work could link the edit rate to endogenous protein levels, by fusing Cas9 to conditionally stable nanobodies.

[0190] Using INSCRIBE, a persistent memory was discovered in the BMP pathway, evidenced by the correlation between response levels to two stimulations occurring up to 18 days apart. To our knowledge, this phenomenon has not been previously reported, which opens up intriguing questions regarding its underlying mechanism and biological significance. Developmental signaling pathways, including BMP, are utilized repeatedly to regulate various processes such as growth, differentiation, and morphogenesis throughout different stages of development. It can be speculated that memory of past signaling activity could serve to coordinate these diverse aspects of tissue development. For instance, an initial signal gradient might direct cell fate decisions, while a later uniform signal promotes proliferation. By retaining the memory of the initial response, the system can fine-tune the population sizes of different cell types, ensuring proper tissue development and organization.

[0191] The time scale of this memory suggests an epigenetic mechanism, for example chromatin remodeling that correlates with initial response and keeps loci poised for reactivationP-639878-PC in subsequent stimulations in the same cell and its progeny. Certain gene regulatory network motifs, specifically positive autoregulation and positive feedback loops, can also provide a memory of input signals. Positive autoregulation has been demonstrated for BMP2, BMP4 and BMP7. Positive feedback loop is also suggested to be a conserved feature of BMP signaling pathway across vertebrates. Thus, the regulatory architecture of the BMP pathway may play a role in the memory effect described here. However, these effects are less likely to be cell- autonomous.

[0192] While INSCRIBE offers an innovative solution for recording signaling activity, its current implementation also has several limitations that need to be considered. First, the current implementation of INSCRIBE only records cumulative signaling activity, making it difficult to distinguish between an intense, short-lived signal and a lower-intensity, sustained one. Temporal control of recording using inducible ABE can partially address this issue by allowing recordings over different time windows to provide insights into signaling dynamics. Second, for endogenous inputs, dynamic range can present a constraint. Basal pathway activity, feedback, adaptation, and cell-to-cell heterogeneity in native contexts can drive a fast recorder to saturation or leave a slow one below threshold. Accordingly, INSCRIBE’s dynamic range should be calibrated to the expected signal amplitude and recording window. We found that different barcode arrays exhibit varying edit rates based on their gRNA sequences; high edit rates are suitable for weak signals or short recording periods, while low edit rates are better for strong signals or longer durations. Another approach is to use a suboptimal gRNA, such as one with a mismatch for its target site, to decrease the edit rate of a given barcode array. Finally, ABE expression may interfere with some cellular processes through gRNA-independent off- target editing of RNA transcripts. Therefore, newer versions of ABE with reduced off-target RNA-editing activity may be better suited for sensitive applications.

[0193] In summary, INSCRIBE provides a versatile, scalable, and quantitative method for genetic recording of biological signals with in situ readout. The detection of barcode edits is greatly simplified by ratiometric readout, offering a faster, cheaper, and more straightforward approach compared to both sequencing- and imaging-based alternatives. Looking ahead, INSCRIBE is poised to adapt readily to a wide variety of developmental systems and disease models. Orthogonal barcode arrays, like the two developed and characterized here, can be used concurrently to simultaneously record multiple signals. Because ratiometric readout requires only a single round of imaging per signal, expanding to additional channels adds minimalP-639878-PC experimental complexity and is embodied herein. Moreover, in other embodiments, multiple barcode arrays could be assembled into a single construct for easier delivery. Endpoint analysis of cells can be integrated with spatial multi-omics to create enhanced cell atlases that combine past signaling activity, spatial information, gene expression, chromosomal architecture, and chromatin states. By connecting past molecular events to their future outcomes across cells, tissues, and individuals, INSCRIBE will empower development of predictive models of biological processes and pave the way for new strategies to control and manipulate cell fate.

Claims

P-639878-PCCLAIMS1. A cell comprising: a. At least one barcode array incorporated in its genome, comprising at least one barcode sequence targetable by a genome editing system, and optionally operably linked to a first inducible promoter, and b. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to a second promoter responsive to a cell signal, and a base editing enzyme, wherein said cell signal induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering the base editing of said barcode sequence.

2. The cell of claim 2, wherein said cell signal comprises an oncogenic signal, a metastasis signal, a cell division signal, an inflammatory signal, a growth factor signal, a DNA damage signal, a hypoxia signal, a stress response signal, an apoptotic signal, a differentiation signal, an angiogenesis signal, an immune response signal, an oxidative stress signal, a metabolic signal, a cytokine signal, a wound healing signal, a migration signal, an adhesion signal, an oncogenic signal, a survival signal, a senescence signal, an autophagy signal, a tumor suppressor signal, a receptor tyrosine kinase signal, a hormone signal, a chemokine signal, a neuroinflammatory signal, a heat shock signal, a mitogenic signal, a pathogen-associated signal, a matrix remodeling signal, a reactive oxygen species (ROS) signal, an unfolded protein response (UPR) signal, a cytokine storm signal, a fibrosis signal, a viral infection signal, a lipid signaling event, a mitochondrial stress signal, an ER stress signal, a mechanical stress signal, an extracellular matrix (ECM) signal, a checkpoint activation signal, an immune checkpoint signal, a pro-inflammatory signal, a pathophysiological signal, a disease signal, an anti-inflammatory signal, an angiogenic signal, a fibrotic signal, an immune evasion signal, a developmental signal, a regeneration signal, a hormonal, an imbalance signal, or any combination thereof.

3. The cell of claims 1 or 2, wherein said cell signal comprises WNT, BMP, p53, TNF-a,P-639878-PCNF-KB, EGF, HIF-la, TGF-0, Notch, c-Myc, Ras, Akt, STAT3, IL-6, IL-1|3, Hedgehog, VEGF, ERK, PI3K, MAPK, JAK, Smad, FoxO, IFN-y, Rb, PDGF, FGF, IGF-1, SHP2, AP-1, GSK-30, CREB, IKK, CDK4, PTEN, 0-catenin, CXCL12, CXCR4, MMP-9, MMP-2, Cyclin DI, Cyclin E, HER2, HER3, ERa, AR, PPARy, CCR5, CD44, or CDK2, or any combination thereof.

4. The cell of claims 1-3, wherein said second promoter comprises an endogenous promoter or parts thereof, an endogenous enhancer or parts thereof, or any combination thereof.

5. The cell of claims 1-4, wherein said cell signal is WNT, and optionally said second promoter comprises SEQ ID NO.: 1.

6. The cell of claims 1-5, wherein said cell signal is BMP, and optionally said second promoter comprises SEQ ID NO.: 2.

7. The cell of claims 1-6, wherein said genome editing system is selected from Adenine Base Editor (ABE), Cytosine Base Editors (CBEs), CRISPR-Cas9, TALEN, ZFN, and CRISPR / Casl2a (Cpfl).

8. The cell of claims 1-7, wherein said genome editing system comprises ABE.

9. The cell of claims 1-8, wherein said barcode sequences contain only one editable nucleotide within the activity window of editing system.

10. The method of claims 1-9, wherein said barcode sequence comprises SEQ ID NO.: 3 or SEQ ID NO.: 5.

11. The cell of claims 1-10, wherein said at least one barcode array comprises from 1 to 30 barcode sequences.

12. The cell of claims 1-11, wherein said at least one barcode array comprises 12 barcode sequences.

13. The cell of claims 1-12, wherein said at least one barcode array comprises handles separating said barcode sequences.

14. The method of claims 1-13, wherein said at least one barcode array comprises SEQ ID NO.: 4 or SEQ ID NO.: 6.P-639878-PC15. The cell of claims 1-14, wherein said first inducible promoter is selected from a T3 promoter, a T7 promoter, or a SP6 promoter.

16. The cell of claims 1-15, wherein said first inducible promoter comprises a T3 promoter comprising SEQ ID NO.: 7.

17. The cell of claims 1-16, wherein said cell comprises more than one barcode array incorporated in its genome.

18. The cell of claims 1-17, wherein the degree of editing of the barcode array is indicative of the intensity of the cell signal.

19. The cell of claim 17, wherein the cell comprises two independent barcode arrays.

20. The cell of claim 19, wherein each barcode array has a distinct gRNA that targets each barcode array.

21. A method for detecting the intensity of a cell signal, comprising: a. providing a cell comprising: i. at least one barcode array incorporated in its genome and comprising at least one barcode sequence targetable by a genome editing system, and ii. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to a promoter responsive to said cell signal, and a base editing enzyme, wherein said cell signal induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering the base editing of said barcode sequence; b. optionally inducing transcription of the barcode arrays; c. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively;P-639878-PC d. measuring the readouts of said first and second detection probes; e. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of the intensity of the cell signal.

22. The method of claim 21, wherein the intensity of said cell signal comprises the duration and / or the magnitude of said cell signal.

23. The method of claims 21 or 22, wherein said cell signal comprises an oncogenic signal, a metastasis signal, a cell division signal, an inflammatory signal, a growth factor signal, a DNA damage signal, a hypoxia signal, a stress response signal, an apoptotic signal, a differentiation signal, an angiogenesis signal, an immune response signal, an oxidative stress signal, a metabolic signal, a cytokine signal, a wound healing signal, a migration signal, an adhesion signal, an oncogenic signal, a survival signal, a senescence signal, an autophagy signal, a tumor suppressor signal, a receptor tyrosine kinase signal, a hormone signal, a chemokine signal, a neuroinflammatory signal, a heat shock signal, a mitogenic signal, a pathogen-associated signal, a matrix remodeling signal, a reactive oxygen species (ROS) signal, an unfolded protein response (UPR) signal, a cytokine storm signal, a fibrosis signal, a viral infection signal, a lipid signaling event, a mitochondrial stress signal, an ER stress signal, a mechanical stress signal, an extracellular matrix (ECM) signal, a checkpoint activation signal, an immune checkpoint signal, a pro-inflammatory signal, a pathophysiological signal, a disease signal, an anti-inflammatory signal, an angiogenic signal, a fibrotic signal, an immune evasion signal, a developmental signal, a regeneration signal, a hormonal, an imbalance signal, or any combination thereof.

24. The method of claims 21-23, wherein said cell signal comprises WNT, BMP, p53, TNF- a, NF-KB, EGF, HIF-la, TGF-0, Notch, c-Myc, Ras, Akt, STAT3, IL-6, IL- 10, Hedgehog, VEGF, ERK, PI3K, MAPK, JAK, Smad, FoxO, IFN-y, Rb, PDGF, FGF, IGF-1, SHP2, AP-1, GSK-30, CREB, IKK, CDK4, PTEN, 0-catenin, CXCL12, CXCR4, MMP-9, MMP-2, Cyclin DI, Cyclin E, HER2, HER3, ERa, AR, PPARy, CCR5, CD44, or CDK2, or any combination thereof.

25. The method of claims 21-24, wherein said promoter comprises an endogenous promoter or parts thereof, an endogenous enhancer or parts thereof, or any combination thereof.P-639878-PC26. The method of claims 21-25, wherein said cell signal is WNT, and optionally said promoter comprises SEQ ID NO.: 1.

27. The method of claims 21-26, wherein said cell signal is BMP-responsive promoter, and optionally said promoter comprises SEQ ID NO.: 2.

28. The method of claims 21-27, wherein said genome editing system is selected from Adenine Base Editor (ABE), Cytosine Base Editors (CBEs), CRISPR-Cas9, TALEN, ZFN, prime editing, and CRISPR / Casl2a (Cpfl).

29. The method of claims 21-28, wherein said genome editing system comprises ABE.

30. The method of claims 21-29, wherein said barcode sequences contain only one editable nucleotide within the activity window of editing system.

31. The method of claims 21-30, wherein said barcode sequence comprises SEQ ID NO.: 3 or SEQ ID NO.: 5.

32. The method of claims 21-31, wherein said at least one barcode array comprises from 1 to 30 barcode sequences.

33. The method of claims 21-32, wherein said at least one barcode array comprises handles separating said barcode arrays.

34. The method of claims 21-33, wherein said at least one barcode array comprises 12 barcode sequences.

35. The method of claims 21-35, wherein said at least one barcode array comprises SEQ ID NO.: 4 or SEQ ID NO.: 6.

36. The method of claims 21-35, wherein said at least one barcode array is operably linked to an inducible promoter, optionally selected from a T3 promoter, a T7 promoter, and a SP6 promoter.

37. The method of claims 21-36, wherein said barcode comprises a T3 promoter comprising SEQ ID NO.: 7.

38. The method of claims 21-37, wherein said cell comprises more than one barcode arrays incorporated in its genome.P-639878-PC39. The method of claims 21-38, wherein said first and second detection probes are labeled each with a different fluorescent label.

40. The method of claims 21-39, wherein said ratio is calculated by dividing the readout values of the first probe by the readout value of the second probe.

41. The method of claims 21-40, wherein the degree of editing of the barcode array is indicative of the intensity of the cell signal.

42. The method of claims 21-41, wherein the degree of editing of the barcode is determined by a classifier trained to predict the number of edits based on the readout signals.

43. The method of claim 38, wherein the cell comprises two independent barcode arrays.

44. The method of claim 43, wherein each barcode array has a distinct gRNA that targets each barcode array.

45. The method of any one of claims 38, 43 or 44, wherein the barcode arrays are simultaneously measured.

46. The method of any one of claims 38, 43 or 44, wherein the barcode arrays are sequentially measured.

47. A method for detecting the degree of editing of a transcript in a cell, comprising: a. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the transcript, respectively; b. measuring the readouts of said first and second detection probes; c. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of the degree of editing of said transcript.

48. A method for detecting the degree of editing of a barcode in a cell, comprising: a. providing a cell comprising a barcode array incorporated in its genome and comprising at least one barcode sequence targetable by a genome editing system; b. optionally inducing transcription of the barcode arrays; andP-639878-PC c. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively; d. measuring the readouts of said first and second detection probes; e. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of degree of editing of said barcode.

49. A method for detecting the activity of a promoter and / or an enhancer region, comprising: a. providing a cell comprising: i. A barcode array incorporated in its genome and comprising at least one barcode sequence targetable by a genome editing system, and ii. A genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to said promoter and / or enhancer region, and a base editing enzyme, wherein activation of said promoter and / or enhancer region induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering base editing of said barcode sequence; b. contacting the cell with a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively, c. measuring the readouts of said first and second detection probes, d. calculating the ratio between the readouts of said first and second detection probes; wherein said ratio is indicative of the activity of said promoter and / or enhancer region.

50. The method of claim 49, wherein said promoter and / or said enhancer are endogenous to the cell.

51. A kit comprising:P-639878-PC a. a cell comprising: i. at least one barcode array incorporated in its genome, comprising at least one barcode sequence targetable by a genome editing system, and optionally operably linked to a first inducible promoter, and ii. a genome editing system comprising: a polynucleotide encoding a gRNA specific to said barcode sequence and operably linked to a promoter responsive to said cell signal, and a base editing enzyme, wherein said cell signal induces the expression of the gRNA, which guides the base editing enzyme to the barcode sequence, thereby triggering base editing of said barcode sequence; and b. optionally a means for inducing transcription of the at least one barcode array; c. a first detection and a second detection probe, complementary to the edited and the unedited form of the barcode sequence, respectively.

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