Interference-driven spacer acquisition is dominant over naive and primed adaptation in a native CRISPR–Cas system
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CRISPR-Cas systems provide bacteria with adaptive immunity against foreign nucleic acids by acquiring short, invader-derived sequences called spacers. Here, we use high-throughput sequencing to analyse millions of spacer acquisition events in wild-type populations of Pectobacterium atrosepticum. Plasmids not previously encountered, or plasmids that had escaped CRISPR-Cas targeting via point mutation, are used to provoke naive or primed spacer acquisition, respectively. The origin, location and order of spacer acquisition show that spacer selection through priming initiates near the site of CRISPR-Cas recognition (the protospacer), but on the displaced strand, and is consistent with 3'-5' translocation of the Cas1:Cas2-3 acquisition machinery. Newly acquired spacers determine the location and strand specificity of subsequent spacers and demonstrate that interference-driven spacer acquisition ('targeted acquisition') is a major contributor to adaptation in type I-F CRISPR-Cas systems. Finally, we show that acquisition of self-targeting spacers is occurring at a constant rate in wild-type cells and can be triggered by foreign DNA with similarity to the bacterial chromosome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it