Nonspecific DNA binding by P1 ParA determines the distribution of plasmid partition and repressor activities
Bibliographic record
Abstract
The faithful segregation, or "partition," of many low-copy number bacterial plasmids is driven by plasmid-encoded ATPases that are represented by the P1 plasmid ParA protein. ParA binds to the bacterial nucleoid via an ATP-dependent nonspecific DNA (nsDNA)-binding activity, which is essential for partition. ParA also has a site-specific DNA-binding activity to the par operator ( parOP ), which requires either ATP or ADP, and which is essential for it to act as a transcriptional repressor but is dispensable for partition. Here we examine how DNA binding by ParA contributes to the relative distribution of its plasmid partition and repressor activities, using a ParA with an alanine substitution at Arg 351 , a residue previously predicted to participate in site-specific DNA binding. In vivo , the parA R351A allele is compromised for partition, but its repressor activity is dramatically improved so that it behaves as a "super-repressor." In vitro , ParA R351A binds and hydrolyzes ATP, and undergoes a specific conformational change required for nsDNA binding, but its nsDNA-binding activity is significantly damaged. This defect in turn significantly reduces the assembly and stability of partition complexes formed by the interaction of ParA with ParB, the centromere-binding protein, and DNA. In contrast, the R351A change shows only a mild defect in site-specific DNA binding. We conclude that the partition defect is due to altered nsDNA binding kinetics and affinity for the bacterial chromosome. Furthermore, the super-repressor phenotype is explained by an increased pool of non-nucleoid bound ParA that is competent to bind parOP and repress transcription.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".