The Twin Arginine Transport System Appears To Be Essential for Viability in <i>Sinorhizobium meliloti</i>
Bibliographic record
Abstract
The twin arginine transport (Tat) system is responsible for transporting prefolded proteins to the periplasmic space. The Tat pathway has been implicated in many bacterial cellular functions, including motility, biofilm formation, and pathogenesis and symbiosis. Since the annotation of Sinorhizobium meliloti Rm1021 genome suggests that there may be up to 94 putative Tat substrates, we hypothesized that characterizing the twin arginine transport system in this organism might yield unique data that could help in the understanding of twin arginine transport. To initiate this work we attempted a targeted mutagenesis of the tat locus. Despite repeated attempts using a number of different types of media, the attempts at mutation construction were unsuccessful unless the experiment was carried out in a strain that was merodiploid for tatABC. In addition, it was shown that a plasmid carrying tatABC was stable in the absence of antibiotic selection in a tat deletion background. Finally, fluorescence microscopy and live/dead assays of these cultures show a high proportion of dead and irregularly shaped cells, suggesting that the loss of tatABC is inversely correlated with viability. Taken together, the results of this work provide evidence that the twin arginine transport system of S. meliloti appears to be essential for viability under all the conditions that we had tested.
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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 | 0.000 |
| 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".