Diverse NADase effector families mediate interbacterial antagonism via the type VI secretion system
Bibliographic record
Abstract
The bacterial type VI secretion system (T6SS) mediates antagonistic cell–cell interactions between competing Gram-negative bacteria. In plant-beneficial bacteria, this pathway has been shown to suppress the growth of bacterial pathogens; however, the identification and mode of action of T6SS effector proteins that mediate this protective effect remain poorly defined. Here, we identify two previously uncharacterized effectors required for interbacterial antagonism by the plant commensal bacterium Pseudomonas protegens. Consistent with the established effector-immunity paradigm for antibacterial T6SS substrates, the toxic activities of these effectors are neutralized by adjacently encoded cognate immunity determinants. Although one of these effectors, RhsA, belongs to the family of DNase enzymes, the activity of the other was not apparent from its sequence. To determine the mechanism of toxicity of this latter effector, we determined its 1.3 Å crystal structure in complex with its immunity protein and found that it resembles NAD(P)+-degrading enzymes. In line with this structural similarity, biochemical characterization of this effector, termed Tne2 (Type VI secretion NADase effector family 2), demonstrates that it possesses potent NAD(P)+ hydrolase activity. Tne2 is the founding member of a widespread family of interbacterial NADases predicted to transit not only the Gram-negative T6SS but also the Gram-positive type VII secretion system, a pathway recently implicated in interbacterial competition among Firmicutes. Together, this work identifies new T6SS effectors employed by a plant commensal bacterium to antagonize its competitors and broadly implicates NAD(P)+-hydrolyzing enzymes as substrates of interbacterial conflict pathways found in diverse bacterial phyla.
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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 | 0.001 | 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".