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An Automated Image Analysis System to Quantify Endosomal Tubulation.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Newton, TM 

Abstract

Recycling of cargos from early endosomes requires regulation of endosomal tubule formation and fission. This regulation is disrupted in cells depleted of the microtubule severing enzyme spastin, causing elongation of endosomal tubules and mis-trafficking of recycling endosomal cargos such as the transferrin receptor. Spastin is encoded by SPAST, mutations in which are the most frequent cause of autosomal dominant hereditary spastic paraplegia, a condition characterised by a progressive loss of lower limb function resulting from upper motor neuron axonopathy. Investigation of molecular factors involved in endosomal tubule regulation is hindered by the need for manual counting of endosomal tubules. We report here the development of an open source automated system for the quantification of endosomal tubules, using ImageJ and R. We validate the method in cells depleted of spastin and its binding partner IST1. The additional speed and reproducibility of this system compared with manual counting makes feasible screens of candidates to further understand the mechanisms of endosomal tubule formation and fission.

Description

Keywords

image analysis, flourescence imaging, small interfering RNAs, membrane proteins, cell staining, flourescence microscopy, transfection, microtubules

Journal Title

PLoS One

Conference Name

Journal ISSN

1932-6203
1932-6203

Volume Title

11

Publisher

PLOS
Sponsorship
Medical Research Council (MR/M00046X/1)
Spastic Paraplegia Foundation (RFP2014)
Tom Wahlig Stiftung (unknown)
Wellcome Trust (100140/Z/12/Z)
Wellcome Trust (082381/Z/07/Z)
Wellcome Trust (093026/Z/10/Z)
This work was supported by grants to ER; UK Medical Research Council Project Grant [MR/M00046X/1], Wellcome Trust Senior Research Fellowship in Clinical Science [082381], Project Grants from United States Spastic Paraplegia Foundation and from the Tom Wahlig Stiftung. TMN was supported by MRC PhD studentship [G0800117]. CIMR is supported by a Wellcome Trust Strategic Award [100140] and Equipment Grant [093026].