Functional Divergence of the Paralog Salmonella Effector Proteins SopD and SopD2 and Their Contributions to Infection
Bibliographic record
Abstract
Salmonella enterica is a leading cause of bacterial food-borne illness in humans and is responsible for millions of cases annually. A critical strategy for the survival of this pathogen is the translocation of bacterial virulence factors termed effectors into host cells, which primarily function via protein–protein interactions with host proteins. The Salmonella genome encodes several paralogous effectors believed to have arisen from duplication events throughout the course of evolution. These paralogs can share structural similarities and enzymatic activities but have also demonstrated divergence in host cell targets or interaction partners and contributions to the intracellular lifecycle of Salmonella. The paralog effectors SopD and SopD2 share 63% amino acid sequence similarity and extensive structural homology yet have demonstrated divergence in secretion kinetics, intracellular localization, host targets, and roles in infection. SopD and SopD2 target host Rab GTPases, which represent critical regulators of intracellular trafficking that mediate diverse cellular functions. While SopD and SopD2 both manipulate Rab function, these paralogs display differences in Rab specificity, and the effectors have also evolved multiple mechanisms of action for GTPase manipulation. Here, we highlight this intriguing pair of paralog effectors in the context of host–pathogen interactions and discuss how this research has presented valuable insights into effector 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 | 0.000 | 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 | 0.001 |
| 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".