Terminal Reassortment Drives the Quantum Evolution of Type III Effectors in Bacterial Pathogens
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Bibliographic record
Abstract
Many bacterial pathogens employ a type III secretion system to deliver type III secreted effectors (T3SEs) into host cells, where they interact directly with host substrates to modulate defense pathways and promote disease. This interaction creates intense selective pressures on these secreted effectors, necessitating rapid evolution to overcome host surveillance systems and defenses. Using computational and evolutionary approaches, we have identified numerous mosaic and truncated T3SEs among animal and plant pathogens. We propose that these secreted virulence genes have evolved through a shuffling process we have called "terminal reassortment." In terminal reassortment, existing T3SE termini are mobilized within the genome, creating random genetic fusions that result in chimeric genes. Up to 32% of T3SE families in species with relatively large and well-characterized T3SE repertoires show evidence of terminal reassortment, as compared to only 7% of non-T3SE families. Terminal reassortment may permit the near instantaneous evolution of new T3SEs and appears responsible for major modifications to effector activity and function. Because this process plays a more significant role in the evolution of T3SEs than non-effectors, it provides insight into the evolutionary origins of T3SEs and may also help explain the rapid emergence of new infectious agents.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it