Conserved patterns of sequence diversification provide insight into the evolution of two-component systems in Enterobacteriaceae
Bibliographic record
Abstract
ABSTRACT Two-component regulatory systems (TCS) are a major mechanism used by bacteria to sense and respond to their environments. Many of the same TCS are used by biologically diverse organisms with different regulatory needs, suggesting that the functions of TCS must adapt over evolution. To explore this topic, we analyzed the amino acid sequence divergence patterns of a large set of broadly conserved TCS across different branches of Enterobacteriaceae, a family of Gram-negative bacteria that includes biomedically important genera such as Salmonella , Escherichia , Klebsiella , and others. Our analysis revealed trends in how TCS sequences change across different proteins or functional domains of the TCS, and across different lineages. Based on these trends, we identified individual TCS that exhibit atypical evolutionary patterns. We observed a strong correlation for the extent of sequence variation of a given TCS across different lineages, unveiling a hierarchy TCS sequence conservation with EnvZ/OmpR as the most conserved TCS. We provide evidence that, for the most divergent of the TCS analyzed, PmrA/PmrB, different alleles were horizontally acquired by different branches of this family, and that different PmrA/PmrB sequence variants have highly divergent signal sensing domains. Collectively, this study sheds light on how TCS evolve, and serves as a compendium for how the sequences of the TCS in this family have diverged over the course of evolution.
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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 | 0.001 | 0.001 |
| 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".