Characterizing the Role of the Type VI Secretion System in Interbacterial Species Interactions and Pathogenesis
Bibliographic record
Abstract
Bacteria require molecular mechanisms to properly sense and respond to their environment. This allows them to compete for specific niches, persist in polymicrobial communities, and contribute to virulence and pathogenesis. One mechanism Gram-negative bacteria have adapted is the use of type VI secretion systems (T6SS). The T6SS is a large needle complex that spans across the entire bacterial cell wall and functions through a contraction mechanism that results in the delivery of toxic effector proteins into neighbouring cells. Virulence is achieved through the targeting of essential components found in either eukaryotic or prokaryotic organisms, including cell wall, membrane lipids, and DNA. Despite the importance of the T6SS as an interbacterial weapon, there still exists an incomplete understanding of how T6SS expressing species can co-exist and the implications of antagonistic responses in shaping polymicrobial communities. Further, these species are often subject to a changing environment and yet, the role of environmental signals and their influence on interspecies interactions and the expression of the T6SS, remain largely unknown. Here, I examined the role of the T6SS in the context of multispecies communities. Using a mix of two antagonistic T6SS strains, Vibrio cholerae V52 and Aeromonas hydrophila SSU, both species co-existed despite active bacterial killing. Fluorescence microscopy analyses revealed survival was possible through the formation of sister-cell clusters. Cluster formation was dependent on T6SS effector delivery, highlighting a unique mechanism where destructive responses can mediate protection within a community. I also examined the environmental signals that activate the T6SS using Pseudomonas aeruginosa PAO1, a strain with a tightly regulated T6SS, as a model system. Results reveal that extracellular DNA, prevalent in cystic fibrosis sputum, activates the H1-T6SS cluster of P. aeruginosa. The addition of excess magnesium ions in the media negates the effect of eDNA on T6SS activation, suggesting eDNA may be a chelator of membrane ions and T6SS activation is a consequence of a perturbed membrane. Overall, I provide new insight into how bacterial communities are shaped, and the type of adaptations bacteria undergo to better survive and compete in the environment.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".