Pathogenic Acinetobacter species have a functional type I secretion system and contact-dependent inhibition systems
Bibliographic record
Abstract
Pathogenic Acinetobacter species, including Acinetobacter baumannii and Acinetobacter nosocomialis , are opportunistic human pathogens of increasing relevance worldwide. Although their mechanisms of drug resistance are well studied, the virulence factors that govern Acinetobacter pathogenesis are incompletely characterized. Here we define the complete secretome of A. nosocomialis strain M2 in minimal medium and demonstrate that pathogenic Acinetobacter species produce both a functional type I secretion system (T1SS) and a contact-dependent inhibition (CDI) system. Using bioinformatics, quantitative proteomics, and mutational analyses, we show that Acinetobacter uses its T1SS for exporting two putative T1SS effectors, an Repeats-in-Toxin (RTX)-serralysin-like toxin, and the biofilm-associated protein (Bap). Moreover, we found that mutation of any component of the T1SS system abrogated type VI secretion activity under nutrient-limited conditions, indicating a previously unrecognized cross-talk between these two systems. We also demonstrate that the Acinetobacter T1SS is required for biofilm formation. Last, we show that both A. nosocomialis and A. baumannii produce functioning CDI systems that mediate growth inhibition of sister cells lacking the cognate immunity protein. The Acinetobacter CDI systems are widely distributed across pathogenic Acinetobacter species, with many A. baumannii isolates harboring two distinct CDI systems. Collectively, these data demonstrate the power of differential, quantitative proteomics approaches to study secreted proteins, define the role of previously uncharacterized protein export systems, and observe cross-talk between secretion systems in the pathobiology of medically relevant Acinetobacter species.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".