Activation of ROCK and MLCK tunes regional stress fiber formation and mechanics via preferential myosin light chain phosphorylation
Bibliographic record
Abstract
The assembly and mechanics of actomyosin stress fibers (SFs) depend on myosin regulatory light chain (RLC) phosphorylation, which is driven by myosin light chain kinase (MLCK) and Rho-associated kinase (ROCK). Although previous work suggests that MLCK and ROCK control distinct pools of cellular SFs, it remains unclear how these kinases differ in their regulation of RLC phosphorylation or how phosphorylation influences individual SF mechanics. Here, we combine genetic approaches with biophysical tools to explore relationships between kinase activity, RLC phosphorylation, SF localization, and SF mechanics. We show that graded MLCK overexpression increases RLC monophosphorylation (p-RLC) in a graded manner and that this p-RLC localizes to peripheral SFs. Conversely, graded ROCK overexpression preferentially increases RLC diphosphorylation (pp-RLC), with pp-RLC localizing to central SFs. Interrogation of single SFs with subcellular laser ablation reveals that MLCK and ROCK quantitatively regulate the viscoelastic properties of peripheral and central SFs, respectively. The effects of MLCK and ROCK on single-SF mechanics may be correspondingly phenocopied by overexpression of mono- and diphosphomimetic RLC mutants. Our results point to a model in which MLCK and ROCK regulate peripheral and central SF viscoelastic properties through mono- and diphosphorylation of RLC, offering new quantitative connections between kinase activity, RLC phosphorylation, and SF viscoelasticity.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".