Dynamic clustering and Rab11-dependent regulation of voltage-gated proton channels at the plasma membrane
- Journal
- Life sciences (Q1)
- Published
- 2 October 2026
- Study design
- Unclassified
- Evidence level
- Level 5, Expert Opinion (CEBM 5)
- Authors
- Luisa Ribeiro-Silva, Manoel Arcisio-Miranda
- PMID
- 42826881
- DOI
- 10.1016/j.lfs.2026.124719
Why clinicians should know about it
- Picked for Histology (top studies of the week, 4 October 2026): Ranked by evidence level and journal quartile
Abstract
AIMS: Voltage-gated proton channels (HV1) play a key role in intracellular pH homeostasis in immune cells and have been implicated in the neurological damage after a stroke and the prognosis and malignancy of several tumors. Thus, the molecular mechanisms governing HV1 surface abundance are of great clinical significance but have not yet been established. MATERIALS AND METHODS: Human HV1 tagged with mCherry or EGFP was expressed in CHO-K1 cells. Channel organization and mobility were assessed by TIRF microscopy with single particle tracking, association with intracellular compartments by dynamic colocalization with fluorescently tagged markers, and channel function by whole-cell patch-clamp recording. KEY FINDINGS: HV1 channels form submicron clusters at and near the plasma membrane, which are mostly mobile and move predominantly by confined diffusion. This movement is independent of the cytoskeleton, although depolymerization of either network reduced proton current density and microtubule depolymerization additionally reduced cluster size. HV1 showed strong dynamic colocalization with Rab11, a recycling endosome marker. Co-expression of a dominant negative Rab11 increased proton current density but did not alter the cluster density, suggesting a modulatory role for Rab11 in channel activity. SIGNIFICANCE: Our work reveals a novel regulatory mechanism for HV1 channels in which dynamic clustering and Rab11 association alter channel activity with implications in disease contexts where HV1 is dysregulated.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.