Visualizing Interactions along the Escherichia coli Twin-Arginine Translocation Pathway Using Protein Fragment Complementation
Bibliographic record
Abstract
The twin-arginine translocation (Tat) pathway is well known for its ability to export fully folded substrate proteins out of the cytoplasm of gram-negative and gram-positive bacteria. Studies of this mechanism in Escherichia coli have identified numerous transient protein-protein interactions that guide export-competent proteins through the Tat pathway. To visualize these interactions, we have adapted bimolecular fluorescence complementation (BiFC) to detect protein-protein interactions along the Tat pathway of living cells. Fragments of the yellow fluorescent protein (YFP) were fused to soluble and transmembrane factors that participate in the translocation process including Tat substrates, Tat-specific proofreading chaperones and the integral membrane proteins TatABC that form the translocase. Fluorescence analysis of these YFP chimeras revealed a wide range of interactions such as the one between the Tat substrate dimethyl sulfoxide reductase (DmsA) and its dedicated proofreading chaperone DmsD. In addition, BiFC analysis illuminated homo- and hetero-oligomeric complexes of the TatA, TatB and TatC integral membrane proteins that were consistent with the current model of translocase assembly. In the case of TatBC assemblies, we provide the first evidence that these complexes are co-localized at the cell poles. Finally, we used this BiFC approach to capture interactions between the putative Tat receptor complex formed by TatBC and the DmsA substrate or its dedicated chaperone DmsD. Our results demonstrate that BiFC is a powerful approach for studying cytoplasmic and inner membrane interactions underlying bacterial secretory pathways.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".