Identification and Characterization of Bacterial and Host Factors Involved in Microtubule Disassembly in Epithelial Cells during <i>Edwardsiella</i> Infections
Bibliographic record
Abstract
Enteric bacteria from the genus Edwardsiella cause great losses to a variety of commercially important fish such as the Japanese Eel, Channel Catfish and Turbot. In humans, they cause a gastroenteritis‐like phenotype. These bacteria are known to infect both inflammatory and epithelial cells. Although macrophages are by far the best‐studied cell types during these infections, epithelial cell studies have lagged primarily due to poor infection models. Because these bacteria resemble other intestinal pathogens and because the host cytoskeleton is a common target of intestinal pathogens, we hypothesized that similar infections could be established to evaluate host actin, intermediate filament and microtubule alterations. Here we established two different epithelial cell infections using HeLa and CaCo‐2 cells and demonstrate that only the microtubule cytoskeleton is noticeably altered by these bacteria. We found that microtubules are initially severed then completely disassembled during Edwardsiella infections . To identify the bacterial and host components involved in this phenotype, we screened a 2,758 mutant Edwardsiella genome transposon insertion library and localized all known host microtubule‐severing enzymes (katanin, spastin, and fidgetin). Using the screening approach we were able to narrow the 2,758 Edwardsiella mutants/genes to 15 that are key players in causing MT disassembly in epithelial cells. Immunolocalization experiments showed the katanin subunit A‐like 1, katanin subunit B 1, and katanin subunit B‐like 1 at microtubule cut sites, suggesting their involvement in the microtubule disassembly event. This work not only provides the first evidence of host cytoskeletal alterations during Edwardsiella infections, but also provides a resource for further characterization of molecular components involved in microtubule disassembly in general. Support or Funding Information Funding source: Natural Sciences and Engineering Research Council of Canada (NSERC)and SFU BISC department funds
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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".