Processing by rhomboid protease is required for <i>Providencia stuartii</i> TatA to interact with TatC and to form functional homo‐oligomeric complexes
Bibliographic record
Abstract
The twin arginine transport (Tat) system transports folded proteins across the prokaryotic cytoplasmic membrane and the plant thylakoid membrane. In Escherichia coli three membrane proteins, TatA, TatB and TatC, are essential components of the machinery. TatA from Providencia stuartii is homologous to E. coli TatA but is synthesized as an inactive pre-protein with an N-terminal extension of eight amino acids. Removal of this extension by the rhomboid protease AarA is required to activate P. stuartii TatA. Here we show that P. stuartii TatA can functionally substitute for E. coli TatA provided that the E. coli homologue of AarA, GlpG, is present. The oligomerization state of the P. stuartii TatA pro-protein was compared with that of the proteolytically activated protein and with E. coli TatA. The pro-protein still formed small homo-oligomers but cannot form large TatBC-dependent assemblies. In the absence of TatB, E. coli TatA or the processed form of P. stuartii TatA form a complex with TatC. However, this complex is not observed with the pro-form of P. stuartii TatA. Taken together our results suggest that the P. stuartii TatA pro-protein is inactive because it is unable to interact with TatC and cannot form the large TatA complexes required for transport.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".