Edwardsiella tarda Alter Their Protein Expression Profiles at Permissive Human Temperatures and Control the Host Cytoskeleton for their Benefit
Bibliographic record
Abstract
Edwardsiella tarda is an emerging enteric pathogen that infects both warm‐water fish and humans. While it is known that E. tarda utilizes syringe‐like type III and type VI secretion systems to deliver effector proteins into fish host cells during infection, little is known about E. tarda pathogenesis in humans at the sub‐cellular level. To investigate the pathogenic strategies employed by E. tarda we tested two hypotheses; (1) E. tarda alter the expression of secreted proteins at 37°C and (2) E. tarda hijack the host cytoskeletal system in human cells as part of their pathogenesis. To test these hypotheses we grew E. tarda at 30°C and at 37°C and compared type III and type VI secretion system protein expression profiles at the two temperatures. Some strains of E. tarda produced more secreted proteins at 37°C than at 30°C, which suggests greater activity from the pathogen's secretion systems at human body temperature. When E. tarda infections in HeLa cells were examined microscopically, we found cytoskeletal and organellar alterations in infected cells as compared to uninfected controls, demonstrating effector‐driven sub‐cellular alterations. Taken together our results indicate that E. tarda hone their protein expression machinery to their environment and control crucial aspects of their host cells during their infectious processes. Grant Funding Source : Natural Science and Engineering Research Council of Canada
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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".