EF-hand protein, EfhP, specifically binds Ca2+ and mediates Ca2+ regulation of virulence in a human pathogen Pseudomonas aeruginosa
Bibliographic record
Abstract
Abstract Calcium (Ca2+) is well known as a second messenger in eukaryotes, where Ca2+signaling controls life-sustaining cellular processes. Although bacteria produce the components required for Ca2+signaling, little is known about the mechanisms of bacterial Ca2+signaling. Previously, we have identified a putative Ca2+-binding protein EfhP (PA4107) with two canonical EF-hand motifs and reported that EfhP mediates Ca2+regulation of virulence factors production and infectivity inPseudomonas aeruginosa,a human pathogen causing life-threatening infections. Here, we show that EfhP selectively binds Ca2+with 13.7 µM affinity, and that mutations at the +X and −Z positions within each or both EF-hand motifs abolished Ca2+binding. We also show that the hydrophobicity of EfhP increased in a Ca2+-dependent manner, however no such response was detected in the mutated proteins.15 N-NMR showed Ca2+-dependent chemical shifts in EfhP confirming Ca2+-binding triggered structural rearrangements in the protein. Deletion ofefhPimpairedP. aeruginosasurvival in macrophages and virulence in vivo.Disabling EfhP Ca2+binding abolished Ca2+induction of pyocyanin production in vitro. These data confirm that EfhP selectively binds Ca2+, which triggers its structural changes required for the Ca2+regulation ofP. aeruginosavirulence, thus establishing the role of EfhP as a Ca2+sensor.
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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 | 0.000 |
| 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".