Plasmid persistence: costs, benefits, and the plasmid paradox
Bibliographic record
Abstract
Plasmids are extrachromosomal DNA elements that can be found throughout bacteria, as well as in other domains of life. Nonetheless, the evolutionary processes underlying the persistence of plasmids are incompletely understood. Bacterial plasmids may encode genes for traits that are sometimes beneficial to their hosts, such as antimicrobial resistance, virulence, heavy metal tolerance, and the catabolism of unique nutrient sources. In the absence of selection for these traits, however, plasmids generally impose a fitness cost on their hosts. As such, plasmid persistence presents a conundrum: models predict that costly plasmids will be lost over time or that beneficial plasmid genes will be integrated into the host genome. However, laboratory and comparative studies have shown that plasmids can persist for long periods, even in the absence of positive selection. Several hypotheses have been proposed to explain plasmid persistence, including host-plasmid co-adaptation, plasmid hitchhiking, cross-ecotype transfer, and high plasmid transfer rates, but there is no clear evidence that any one model adequately resolves the plasmid paradox.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".