The circle to lariat ratio of the Ll.LtrB group II intron from Lactococcus lactis is greatly influenced by a variety of biological determinants in vivo
Bibliographic record
Abstract
Bacterial group II introns mostly behave as versatile retromobile genetic elements going through distinct cycles of gain and loss. These large RNA molecules are also ribozymes splicing autocatalytically from their interrupted pre-mRNA transcripts by two different concurrent pathways, branching and circularization. These two splicing pathways were shown to release in bacterial cells significant amounts of branched intron lariats and perfect end-to-end intron circles respectively. On one hand, released intron lariats can invade new sites in RNA and/or DNA by reverse branching while released intron circles are dead end spliced products since they cannot reverse splice through circularization. The presence of two parallel and competing group II intron splicing pathways in bacteria led us to investigate the conditions that influence the overall circle to lariat ratio in vivo. Here we unveil that removing a prominent processing site within the Ll.LtrB group II intron, raising growth temperature of Lactococcus lactis host cells and increasing the expression level of the intron-interrupted gene all increased the relative amount of released intron circles compared to lariats. Strengthening and weakening the base pairing interaction between the intron and its upstream exon respectively increased and decreased the overall levels of released intron circles in comparison to lariats. Host environment was also found to impact the circle to lariat ratio of the Ll.LtrB and Ll.RlxA group II introns from L. lactis and the Ef.PcfG intron from Enterococcus faecalis. Overall, our data show that multiple factors significantly influence the balance between released intron circles and lariats in bacterial cells.
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 | 0.000 |
| 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".