Multiplex recording of cellular events over time on CRISPR biological tape

Abstract

Although dynamics underlie many biological processes, our ability to robustly and accurately profile time-varying biological signals and regulatory programs remains limited. Here we describe a framework for storing temporal biological information directly in the genomes of a cell population. We developed a "biological tape recorder" in which biological signals trigger intracellular DNA production that is then recorded by the CRISPR-Cas adaptation system. This approach enables stable recording over multiple days and accurate reconstruction of temporal and lineage information by sequencing CRISPR arrays. We further demonstrate a multiplexing strategy to simultaneously record the temporal availability of three metabolites (copper, trehalose, and fucose) in the environment of a cell population over time. This work enables the temporal measurement of dynamic cellular states and environmental changes and suggests new applications for chronicling biological events on a large scale.

Fig. 1:. Temporal recording in arrays by CRISPR expansion (TRACE).

(a) Akin to an audio tape, temporal biological signals can be stored in DNA arrays within a cell population. (b) TRACE functions by first transforming an input biological signal to an altered abundance of a trigger DNA pool (orange). This trigger DNA pool, alongside reference DNA (blue) is then recorded as spacers into genomic CRISPR arrays of a cell population in a unidirectional fashion, enabling recording of temporal information. (c) The pTrig trigger plasmid includes a mini-F origin for stable maintenance and an IPTG-inducible phage P1 replication system for copy number increase. (d) qPCR measurement of pTrig relative copy number (log10 scale) in cells exposed to no IPTG or 1mM IPTG for 6 hours. (e) The pRec recording plasmid includes an aTc-inducible E. coli Cas1 and Cas2 expression cassette. (f) Experimental induction scheme and CRISPR array sequencing approach. (g) Cells with pRec or pRec+pTrig were exposed to 100 ng/μL aTc and no or 1mM IPTG and subjected to sequencing; resulting arrays with a single new spacer and identified source (genome, pRec or pTrig) are plotted as a percentage of all measured CRISPR arrays. Error bars represent standard deviation of three biological replicates.

Fig. 2:. Temporal recording of four day input profiles.

(a) Cell populations were subjected to daily exposures over four sequential days, constituting all 16 possible temporal signal profiles. b) Resulting CRISPR arrays were sequenced with (black line) and without (grey dashed line) a size-enrichment method and the frequency (log10 scale) of unexpanded (un) and expanded arrays of different lengths (L1 to maximum detectable L5) are plotted. (c) Input profiles are grouped by number of pTrig inductions, and the percentage of pTrig spacers in each profile is displayed; red line indicates mean and standard deviation. (d) 50 L4 arrays sampled from the full dataset for the input profile [on, on, off, off] are shown (shaded: pTrig spacer, unshaded: reference spacer, positions p1 to p4, 5′-to-3′ of array). Spacer incorporation can be analyzed across arrays of different lengths (L) and positions (p) as a heatmap displaying percentage of pTrig spacers detected at each location. (e) CRISPR arrays derived from recordings of all 16 temporal signal profiles. (f) The input signal profile (left) and corresponding L4 arrays (right, shown in reverse order to improve visual comparison) are displayed.

Fig. 3:. Reconstructing temporal signal profiles and population lineages.

(a) CRISPR array populations can be described as a frequency distribution constituting of all permutations of reference (R, blue) and trigger (T, orange) spacers for a given array length (L); L3 arrays are depicted. (b) As an example, for two distinct profiles of equal number of inductions, observed (black) and model predicted (white) L3 array type frequencies are plotted; L3 positional averages are shown for reference (inset). (c) Euclidean distance between observed data (rows) and predicted model (columns) array type distributions (L2, L3 and L4 array distributions concatenated) was calculated and normalized by row. The correct temporal signal profile is indicated by a white asterisk, and the model with minimum distance to the data is indicated by black outline on the diagonal. (d) Number of profiles correctly classified utilizing L1 to L4 arrays individually or L2-L4 arrays together as in (c); grey dashed line indicates expected random classification (1/16). (e) A defined branching history was utilized when performing the temporal recording experiment. (f) The mapping locations for genomic spacers within L1 arrays was utilized as sequence identity of the spacer and the Jaccard distance between all samples (1 – proportion of spacers shared between two samples) is displayed. Lineage reconstruction was performed using the Fitch-Margoliash method on this distance matrix and is displayed on the left; only one lineage is not fully differentiated (cells receiving induction on d1).

Fig. 4:. Multiplex temporal recording with a barcoded sensor population.

(a) The direct repeat (DR) of a CRISPR array can be barcoded to associate sensors with specific arrays; generated distal DR barcode sequences are shown. Sensors of copper, trehalose and fucose were linked to the pTrig system and introduced into barcoded strains. The copper sensor utilizes a native promoter with endogenous transcription factor expression, while the trehalose and fucose sensors utilize an engineered transcription factor. (b) The three barcoded sensor strains were mixed and exposed to 8 combinatorial inputs of the three chemicals; the resulting percentage of pTrig spacers for each barcoded sensor strain is displayed (average of three biological replicates). (c) The strain mixture was exposed to combinatorial inputs over three days. As an example, profile #5 is displayed, along with CRISPR arrays for each sensor (plotted as in Fig. 2, but the color map is rescaled for each sensor to aid visualization), and resulting classification (correct: blue checkmark or incorrect: red X). (d) 16 profiles were tested (6 defined, 10 randomly generated) of 512 (8^3) possible profiles; the resulting classification is shown as in (c). (e) Single channel classification accuracy: profiles were classified for each sensor using L2 and L3 arrays; grey dashed line indicates expected random classification (2/16). (f) Multi-channel classification accuracy: predictions were considered across all three sensors, and the number classified correctly within a Hamming distance threshold is shown (black line) compared to the expected random classification (grey dashed line).