Identification and biochemical characterization of the SLC9A7 interactome
Bibliographic record
Abstract
Organellar and cytosolic pH homeostasis is central to most cellular processes, including vesicular trafficking, post-translational modification/processing of proteins, and receptor-ligand interactions. SLC9A7 (NHE7) was identified as a unique (Na+, K+)/H+ exchanger that dynamically cycles between the trans-Golgi network (TGN), endosomes and the plasma membrane. Here we have used mass spectrometry to explore the affinity-captured interactome of NHE7, leading to the identification of cytoskeletal proteins, cell adhesion molecules, membrane transporters, and signaling molecules. Among these binding proteins, calcium-calmodulin, but not apo-calmodulin, binds to NHE7 and regulates the organellar transporter activity. Vimentin was co-immunoprecipitated with endogenous NHE7 protein in human breast cancer MDA-MB-231 cells. A sizable population of NHE7 relocalized to focal complexes in migrating cells and showed colocalization with vimentin and actin in focal complexes. Among the NHE7-binding proteins identified, CD44, a cell surface glycoprotein receptor for hyaluronate and other ligands, showed regulated interaction with NHE7. Pretreatment of the cells with phorbol ester facilitated the NHE7-CD44 interaction and the lipid raft association of CD44. When lipid rafts were chemically disrupted, the NHE7-CD44 interaction was markedly reduced. These results suggest potential dual roles of NHE7 in intracellular compartments and subdomains of cell-surface membranes.
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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 | 0.001 |
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".