Trapping and visualizing intermediate steps in the mismatch repair pathway <i>in vivo</i>
Bibliographic record
Abstract
During mismatch repair, MutS is responsible for mismatch detection and the recruitment of MutL to the mismatch through a mechanism that is unknown in most organisms. Here, we identified a discrete site on MutS that is occupied by MutL in Bacillus subtilis. The MutL binding site is composed of two adjacent phenylalanine residues located laterally in an exposed loop of MutS. Disruption of this site renders MutS defective in binding MutL in vitro and in vivo, while also eliminating mismatch repair. Analysis of MutS repair complexes in vivo shows that MutS mutants defective in interaction with MutL are 'trapped' in a repetitive loading response. Furthermore, these mutant MutS repair complexes persist on DNA away from the DNA polymerase, suggesting that MutS remains loaded on mismatch proximal DNA awaiting arrival of MutL. We also provide evidence that MutS and MutL interact independent of mismatch binding by MutS in vivo and in vitro, suggesting that MutL can transiently probe MutS to determine if MutS is mismatch bound. Together, these data provide insights into the mechanism that MutS employs to recruit MutL, and the consequences that ensue when MutL recruitment is blocked.
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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) | 0.000 | 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 | 0.001 |
| 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".