Type I-F CRISPR-Cas Distribution and Array Dynamics in <i>Legionella pneumophila</i>
Bibliographic record
Abstract
Abstract In bacteria and archaea, several distinct types of CRISPR-Cas systems provide adaptive immunity through broadly similar mechanisms: short nucleic acid sequences derived from foreign DNA, known as spacers, engage in complementary base pairing with invasive genetic elements setting the stage for nucleases to degrade the target DNA. A hallmark of type I CRISPR-Cas systems is their ability to acquire spacers in response to both new and previously encountered invaders (naïve and primed acquisition, respectively). Our phylogenetic analyses of 43 L. pneumophila type I-F CRISPR-Cas systems and their resident genomes suggest that many of these systems have been horizontally acquired. These systems are frequently encoded on plasmids and can co-occur with nearly identical chromosomal loci. We show that two such co-occurring systems are highly protective and undergo efficient primed acquisition in the lab. Furthermore, we observe that targeting by one system’s array can prime spacer acquisition in the other. Lastly, we provide experimental and genomic evidence for a model in which primed acquisition can efficiently replenish a depleted type I CRISPR array following a mass spacer deletion event.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".