Abiotic factors modulate interspecies competition mediated by the type VI secretion system effectors in <i>Vibrio cholerae</i>
Bibliographic record
Abstract
Abstract Vibrio cholerae , the etiological pathogen of cholera, relies on its type VI secretion system (T6SS) as an effective weapon to survive in highly competitive communities. The anti-bacterial and anti-eukaryotic functions of T6SS depend on its secreted effectors that target multiple essential cellular processes. However, the mechanisms that account for effector diversity and different effectiveness during interspecies competition remain elusive. Here, we report that environmental cations and temperature play a key role in dictating effector-mediated competition of Vibrio cholerae . We found that V. cholerae could employ its cell-wall-targeting effector TseH to outcompete the otherwise resistant Escherichia coli and the V. cholerae immunity deletion mutant ΔtsiH when Ca 2+ and Mg 2+ were supplemented. The E. coli Δ phoQ mutant was more sensitive to TseH-mediated killing during competition, suggesting the metal-sensing PhoPQ two-component system is protective to E. coli from TseH activity. Using transcriptome analysis, we found multiple stress response systems, including acid stress response, oxidative stress response, and osmotic stress response, were activated in E. coli expressing TseH in comparison with E. coli expressing the inactive mutant TseH H64A . The membrane-targeting lipase effector TseL also exhibited reduced killing against E. coli when divalent cations were removed. In addition, competition analysis of E. coli with V. cholerae single-effector active strains reveals a temperature-dependent susceptibility of E. coli to effectors, VasX, VgrG3, and TseL. These findings suggest that abiotic factors, that V. cholerae frequently encounters in natural habitats, play a crucial role in dictating the competitive fitness conferred by the type VI secretion system in complex multispecies communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".