Contact-independent killing mediated by a T6SS effector with intrinsic cell-entry properties
Bibliographic record
Abstract
Abstract Bacterial type VI secretion systems (T6SSs) inject toxic effectors into adjacent eukaryotic and prokaryotic cells. It is generally thought that this process requires physical contact between the two cells. Here, we provide evidence of contact-independent killing by a T6SS-secreted effector. We show that the pathogen Yersinia pseudotuberculosis uses a T6SS (T6SS-3) to secrete a nuclease effector that kills other bacteria in vitro and facilitates gut colonization in mice. The effector (Tce1) is a small protein that acts as a Ca 2+ - and Mg 2+ -dependent DNase, and its toxicity is inhibited by a cognate immunity protein, Tci1. As expected, T6SS-3 mediates canonical, contact-dependent killing by directly injecting Tce1 into adjacent cells. In addition, T6SS-3 also mediates killing of neighboring cells in the absence of cell-to-cell contact, by secreting Tce1 into the extracellular milieu. Efficient contact-independent entry of Tce1 into target cells requires proteins OmpF and BtuB in the outer membrane of target cells. The discovery of a contact-independent, long-range T6SS toxin delivery provides a new perspective for understanding the physiological roles of T6SS in competition. However, the mechanisms mediating contact-independent uptake of Tce1 by target cells remain unclear.
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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 | 0.001 |
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".