Plasmid Localization and Partition in <i>Enterobacteriaceae</i>
Bibliographic record
Abstract
Plasmids are ubiquitous in the microbial world and have been identified in almost all species of bacteria that have been examined. Their localization inside the bacterial cell has been examined for about two decades; typically, they are not randomly distributed, and their positioning depends on copy number and their mode of segregation. Low-copy-number plasmids promote their own stable inheritance in their bacterial hosts by encoding active partition systems, which ensure that copies are positioned in both halves of a dividing cell. High-copy plasmids rely on passive diffusion of some copies, but many remain clustered together in the nucleoid-free regions of the cell. Here we review plasmid localization and partition (Par) systems, with particular emphasis on plasmids from Enterobacteriaceae and on recent results describing the in vivo localization properties and molecular mechanisms of each system. Partition systems also cause plasmid incompatibility such that distinct plasmids (with different replicons) with the same Par system cannot be stably maintained in the same cells. We discuss how partition-mediated incompatibility is a consequence of the partition mechanism.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".