Navigation through the Plasma Membrane Molecular Landscape Shapes Random Organelle Movement

Alison Dun, Gabriel James Lord, Rhodri Simon Wilson, Deirdre Kavanagh, Katarzyna Cialowicz, Shuzo Sugita, Seungmee Park, Lei Yang, Annya M. Smyth, Andreas Papadopulos, Colin Rickman, Rory R. Duncan

Research output: Contribution to journalArticle

3 Citations (Scopus)
65 Downloads (Pure)

Abstract

Eukaryotic plasma membrane organization theory has long been controversial, in part due to a dearth of suitably high-resolution techniques to probe molecular architecture in situ and integrate information from diverse data streams [1]. Notably, clustered patterning of membrane proteins is a commonly conserved feature across diverse protein families (reviewed in [2]), including the SNAREs [3], SM proteins [4, 5], ion channels [6, 7], and receptors (e.g., [8]). Much effort has gone into analyzing the behavior of secretory organelles [9-13], and understanding the relationship between the membrane and proximal organelles [4, 5, 12, 14] is an essential goal for cell biology as broad concepts or rules may be established. Here we explore the generally accepted model that vesicles at the plasmalemma are guided by cytoskeletal tracks to specific sites on the membrane that have clustered molecular machinery for secretion [15], organized in part by the local lipid composition [16]. To increase our understanding of these fundamental processes, we integrated nanoscopy and spectroscopy of the secretory machinery with organelle tracking data in a mathematical model, iterating with knockdown cell models. We find that repeated routes followed by successive vesicles, the re-use of similar fusion sites, and the apparently distinct vesicle "pools" are all fashioned by the Brownian behavior of organelles overlaid on navigation between non-reactive secretory protein molecular depots patterned at the plasma membrane.

Original languageEnglish
Pages (from-to)408–414
Number of pages7
JournalCurrent Biology
Volume27
Issue number3
Early online date12 Jan 2017
DOIs
Publication statusPublished - 6 Feb 2017

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