Genetically distinct pathways guide effector export through the type <scp>VI</scp> secretion system
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bacterial secretion systems often employ molecular chaperones to recognize and facilitate export of their substrates. Recent work demonstrated that a secreted component of the type VI secretion system (T6SS), haemolysin co-regulated protein (Hcp), binds directly to effectors, enhancing their stability in the bacterial cytoplasm. Herein, we describe a quantitative cellular proteomics screen for T6S substrates that exploits this chaperone-like quality of Hcp. Application of this approach to the Hcp secretion island I-encoded T6SS (H1-T6SS) of Pseudomonas aeruginosa led to the identification of a novel effector protein, termed Tse4 (type VI secretion exported 4), subsequently shown to act as a potent intra-specific H1-T6SS-delivered antibacterial toxin. Interestingly, our screen failed to identify two predicted H1-T6SS effectors, Tse5 and Tse6, which differ from Hcp-stabilized substrates by the presence of toxin-associated PAAR-repeat motifs and genetic linkage to members of the valine-glycine repeat protein G (vgrG) genes. Genetic studies further distinguished these two groups of effectors: Hcp-stabilized effectors were found to display redundancy in interbacterial competition with respect to the requirement for the two H1-T6SS-exported VgrG proteins, whereas Tse5 and Tse6 delivery strictly required a cognate VgrG. Together, we propose that interaction with either VgrG or Hcp defines distinct pathways for T6S effector export.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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 it