A two-subpopulation model that reflects heterogeneity of large dense core vesicles in exocytosis.


Journal

Cell cycle (Georgetown, Tex.)
ISSN: 1551-4005
Titre abrégé: Cell Cycle
Pays: United States
ID NLM: 101137841

Informations de publication

Date de publication:
03 2022
Historique:
pubmed: 25 1 2022
medline: 19 4 2022
entrez: 24 1 2022
Statut: ppublish

Résumé

Exocytosis of large dense core vesicles is responsible for hormone secretion in neuroendocrine cells. The population of primed vesicles ready to release upon cell excitation demonstrates large heterogeneity. However, there are currently no models that clearly reflect such heterogeneity. Here, we develop a novel model based on single vesicle release events from amperometry recordings of PC12 cells using carbon fiber microelectrode. In this model, releasable vesicles can be grouped into two subpopulations, namely, SP1 and SP2. SP1 vesicles replenish quickly, with kinetics of ~0.0368 s

Identifiants

pubmed: 35067177
doi: 10.1080/15384101.2022.2026576
pmc: PMC8942488
doi:

Substances chimiques

Phorbol Esters 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

531-546

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Auteurs

Nan Qin (N)

Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity & Infant Hospital, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, China.

Zhixi Chen (Z)

Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity & Infant Hospital, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, China.

Renhao Xue (R)

Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity & Infant Hospital, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, China.

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Classifications MeSH