Phosphorylation by the PknB serine/threonine kinase stimulates dimer formation by WalR
Bibliographic record
Abstract
Abstract WalKR is a two-component system that regulates cell wall homeostasis and other processes in low-GC Gram-positive bacteria. It is essential for viability in Staphylococcus aureus and regulates genes that encode the autolysins and other critical proteins. The sensor kinase WalK phosphorylates WalR at aspartic acid residue 53 (D53) in the receiver domain, stimulating promoter DNA binding. Unlike other response regulators, WalR is thought to have a second kinase, the serine/threonine kinase PknB, which phosphorylates the receiver domain at threonine residue 101. We previously reported that a walR mutation that changed T101 to a methionine conferred low level resistance to vancomycin and greatly increased susceptibility to tunicamycin along with several other phenotypic traits. In this work we demonstrate similarities between pknB null and the WalR T101M mutants that support a regulatory role for PknB-mediated phosphorylation of WalR. Using a combination of in vitro and in vivo approaches, we confirm the specificity of this posttranslational modification and confirm that phosphorylation at both D53 and T101 is important for dimer formation. Importantly, using an in silico approach, we have discovered that phosphorylation at T101 creates an intermolecular hydrogen bond between the phosphate group and E108, that strengthens contacts along the WalR dimerization interface. This is the first time that a clear molecular role has been assigned to this posttranslational modification and it is the strongest molecular evidence to date for a direct functional relationship between PknB and WalR. We propose that, together with primary activation by WalK, PknB serves as a second potentiating input into the WalKR system, stimulating WalR dimer formation, and target DNA binding and tethering this transcriptional event to important extracellular stimuli.
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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) | 0.003 | 0.001 |
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".