Continuous Genetic Recording with Self-Targeting CRISPR-Cas in Human Cells
Bibliographic record
Abstract
Abstract The ability to longitudinally track and record molecular events in vivo would provide a unique opportunity to monitor signaling dynamics within cellular niches and to identify critical factors in orchestrating cellular behavior. We present a self-contained analog memory device that enables the recording of molecular stimuli in the form of DNA mutations in human cells. The memory unit consists of a self-targeting guide RNA (stgRNA) cassette that repeatedly directs Streptococcus pyogenes Cas9 nuclease activity towards the DNA that encodes the stgRNA, thereby enabling localized, continuous DNA mutagenesis as a function of stgRNA expression. We analyze the temporal sequence evolution dynamics of stgRNAs containing 20, 30 and 40 nucleotide SDSes (Specificity Determining Sequences) and create a population-based recording metric that conveys information about the duration and/or intensity of stgRNA activity. By expressing stgRNAs from engineered, inducible RNA polymerase (RNAP) III promoters, we demonstrate programmable and multiplexed memory storage in human cells triggered by doxycycline and isopropyl β-D-1-thiogalactopyranoside (IPTG). Finally, we show that memory units encoded in human cells implanted in mice are able to record lipopolysaccharide (LPS)-induced acute inflammation over time. This tool, which we call Mammalian Synthetic Cellular Recorder Integrating Biological Events (mSCRIBE), provides a unique strategy for investigating cell biology in vivo and in situ and may drive further applications that leverage continuous evolution of targeted DNA sequences in mammalian cells. One Sentence Summary By designing self-targeting guide RNAs that repeatedly direct Cas9 nuclease activity towards their own DNA, we created multiplexed analog memory operators that can record biologically relevant information in vitro and in vivo , such as the magnitude and duration of exposure to TNAα.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".