Diversity, Activity, and Evolution of CRISPR Loci in <i>Streptococcus thermophilus</i>
Bibliographic record
Abstract
Clustered regularly interspaced short palindromic repeats (CRISPR) are hypervariable loci widely distributed in prokaryotes that provide acquired immunity against foreign genetic elements. Here, we characterize a novel Streptococcus thermophilus locus, CRISPR3, and experimentally demonstrate its ability to integrate novel spacers in response to bacteriophage. Also, we analyze CRISPR diversity and activity across three distinct CRISPR loci in several S. thermophilus strains. We show that both CRISPR repeats and cas genes are locus specific and functionally coupled. A total of 124 strains were studied, and 109 unique spacer arrangements were observed across the three CRISPR loci. Overall, 3,626 spacers were analyzed, including 2,829 for CRISPR1 (782 unique), 173 for CRISPR2 (16 unique), and 624 for CRISPR3 (154 unique). Sequence analysis of the spacers revealed homology and identity to phage sequences (77%), plasmid sequences (16%), and S. thermophilus chromosomal sequences (7%). Polymorphisms were observed for the CRISPR repeats, CRISPR spacers, cas genes, CRISPR motif, locus architecture, and specific sequence content. Interestingly, CRISPR loci evolved both via polarized addition of novel spacers after exposure to foreign genetic elements and via internal deletion of spacers. We hypothesize that the level of diversity is correlated with relative CRISPR activity and propose that the activity is highest for CRISPR1, followed by CRISPR3, while CRISPR2 may be degenerate. Globally, the dynamic nature of CRISPR loci might prove valuable for typing and comparative analyses of strains and microbial populations. Also, CRISPRs provide critical insights into the relationships between prokaryotes and their environments, notably the coevolution of host and viral genomes.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".