Surface-Expressed Enolase Contributes to the Pathogenesis of Clinical Isolate SSU of<i>Aeromonas hydrophila</i>
Bibliographic record
Abstract
In this study, we demonstrated that the surface-expressed enolase from diarrheal isolate SSU of Aeromonas hydrophila bound to human plasminogen and facilitated the latter's tissue-type plasminogen activator-mediated activation to plasmin. The bacterial surface-bound plasmin was more resistant to the action of its specific physiological inhibitor, the antiprotease alpha(2)-antiplasmin. We found that immunization of mice with purified recombinant enolase significantly protected the animals against a lethal challenge dose of wild-type (WT) A. hydrophila. Minimal histological changes were noted in organs from mice immunized with enolase and then challenged with WT bacteria compared to severe pathological changes found in the infected and nonimmunized group of animals. This correlated with the smaller bacterial load of WT bacteria in the livers and spleens of enolase-immunized mice than that found in the nonimmunized controls. We also showed that the enolase gene could potentially be important for the viability of A. hydrophila SSU as we could delete the chromosomal copy of the enolase gene only when another copy of the targeted gene was supplied in trans. By site-directed mutagenesis, we altered five lysine residues located at positions 343, 394, 420, 427, and 430 of enolase in A. hydrophila SSU; the mutated forms of enolase were hyperexpressed in Escherichia coli, and the proteins were purified. Our results indicated that lysine residues at positions 420 and 427 of enolase were crucial in plasminogen-binding activity. We also identified a stretch of amino acid residues ((252)FYDAEKKEY(260)) in the A. hydrophila SSU enolase involved in plasminogen binding. To our knowledge, this is the first report of the direct involvement of surface-expressed enolase in the pathogenesis of A. hydrophila SSU infections and of any gram-negative bacteria in general.
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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 | 0.000 |
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 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".