Memo is a cofilin-interacting protein that influences PLCγ1 and cofilin activities, and is essential for maintaining directionality during ErbB2-induced tumor-cell migration
Bibliographic record
Abstract
Heregulin (HRG) activates ErbB2-ErbB3 heterodimers thereby stimulating many cellular responses, including motility. Memo and PLCgamma1 interact with ErbB2 autophosphorylation sites and are essential for HRG-induced chemotaxis. By tracing HRG-stimulated cell migration in Dunn chambers, we found that Memo- or PLCgamma1 knockdown (KD) strongly impairs cell directionality. Memo has no obvious enzymatic activity and was discovered via its ability to complex with ErbB2. Using the yeast two-hybrid approach to gain insight into Memo function, an interaction between Memo and cofilin, a regulator of actin dynamics, was uncovered. The interaction was confirmed in vitro using recombinant proteins and in vivo in co-immunoprecipitation experiments where Memo was detected in complexes with cofilin, ErbB2 and PLCgamma1. Interestingly, in Memo KD cells, HRG-induced PLCgamma1 phosphorylation was decreased, suggesting that Memo regulates PLCgamma1 activation. Furthermore, HRG-induced recruitment of GFP-cofilin to lamellipodia is impaired in Memo and in PLCgamma1 KD cells, suggesting that both proteins lie upstream of cofilin in models of ErbB2-driven tumor-cell migration. Finally, in vitro F-actin binding and depolymerization assays showed that Memo enhances cofilin depolymerizing and severing activity. In summary, these data indicate that Memo also regulates actin dynamics by interacting with cofilin and enhancing its function.
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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 | 0.001 | 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".