A global survey of bacterial type III secretion systems and their effectors
Bibliographic record
Abstract
The type III secretion system (T3SS) is an important genetic determinant that mediates interactions between Gram-negative bacteria and their eukaryotic hosts. Our understanding of the T3SS continues to expand, yet the availability of new bacterial genomes prompts questions about its diversity, distribution and evolution. Through a comprehensive survey of ∼20 000 bacterial genomes, we identified 174 non-redundant T3SSs from 109 genera and 5 phyla. Many of the bacteria are environmental strains that have not been reported to interact with eukaryotic hosts, while several species groups carry multiple T3SSs. Four ultra-conserved Microsynteny Blocks (MSBs) were defined within the T3SSs, facilitating comprehensive clustering of the T3SSs into 13 major categories, and establishing the largest diversity of T3SSs to date. We subsequently extended our search to identify type III effectors, resulting in 8740 candidate effectors. Lastly, an analysis of the key transcriptional regulators and circuits for the T3SS families revealed that low-level T3SS regulators were more conserved than higher-level regulators. This comprehensive analysis of the T3SSs and their protein effectors provides new insight into the diversity of systems used to facilitate host-bacterial interactions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".