Literature DB >> 21620890

A novel algorithm to generate kymographs from dynamic axons for the quantitative analysis of axonal transport.

Joshua Chetta1, Sameer B Shah.   

Abstract

The biological and clinical relevance of axonal transport has driven the development of a variety of new approaches to its study, including the generation of fluorescence or brightfield movies of moving cargoes within axons. Kymograph analysis is a simple and effective tool used to analyze axonal transport in neurons. Typically, kymographs are built by having a user trace the path of the axon in one frame of a time-lapse movie and extracting intensity profiles from subsequent frames along that path. This method cannot accommodate movies in which translation of the axon, or changes in axonal orientation or geometry, occur. Both are frequently observed in long-term movies of neurons, both in vitro and in vivo. To solve this problem and automate the creation of kymographs from these movies, we developed a two step algorithm. The first step implemented a simple image registration algorithm that aligned axons based on identification of a reference point on the axon in each image. The second step used a Hough transformation (HT) to automatically detect the axonal contour in each frame. Intensity profiles along this contour were then used to construct a kymograph. This algorithm was able to build an accurate kymograph of mitochondrial and actin transport in dynamic cultured sensory neurons, which were not amenable to previously used analytical methods. Although developed as a tool for analyzing transport, this algorithm is easily modified to analyze movies for the directionality and speed of axonal outgrowth, another metric of interest to neuroscientists.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21620890     DOI: 10.1016/j.jneumeth.2011.05.013

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  8 in total

1.  Bidirectional actin transport is influenced by microtubule and actin stability.

Authors:  Joshua Chetta; James M Love; Brian G Bober; Sameer B Shah
Journal:  Cell Mol Life Sci       Date:  2015-06-05       Impact factor: 9.261

2.  Prior-Apprised Unsupervised Learning of Subpixel Curvilinear Features in Low Signal/Noise Images.

Authors:  Shuhui Yin; Ming Tien; Haw Yang
Journal:  Biophys J       Date:  2020-04-19       Impact factor: 4.033

3.  Kymolyzer, a Semi-Autonomous Kymography Tool to Analyze Intracellular Motility.

Authors:  Himanish Basu; Lai Ding; Gulcin Pekkurnaz; Michelle Cronin; Thomas L Schwarz
Journal:  Curr Protoc Cell Biol       Date:  2020-06

4.  A fast and scalable kymograph alignment algorithm for nanochannel-based optical DNA mappings.

Authors:  Charleston Noble; Adam N Nilsson; Camilla Freitag; Jason P Beech; Jonas O Tegenfeldt; Tobias Ambjörnsson
Journal:  PLoS One       Date:  2015-04-13       Impact factor: 3.240

5.  Automated Multi-Peak Tracking Kymography (AMTraK): A Tool to Quantify Sub-Cellular Dynamics with Sub-Pixel Accuracy.

Authors:  Anushree R Chaphalkar; Kunalika Jain; Manasi S Gangan; Chaitanya A Athale
Journal:  PLoS One       Date:  2016-12-19       Impact factor: 3.240

6.  A comparative quantitative assessment of axonal and dendritic mRNA transport in maturing hippocampal neurons.

Authors:  Gunja K Pathak; James M Love; Joshua Chetta; Sameer B Shah
Journal:  PLoS One       Date:  2013-07-22       Impact factor: 3.240

7.  Ribosomal trafficking is reduced in Schwann cells following induction of myelination.

Authors:  James M Love; Sameer B Shah
Journal:  Front Cell Neurosci       Date:  2015-08-19       Impact factor: 5.505

8.  KymographClear and KymographDirect: two tools for the automated quantitative analysis of molecular and cellular dynamics using kymographs.

Authors:  Pierre Mangeol; Bram Prevo; Erwin J G Peterman
Journal:  Mol Biol Cell       Date:  2016-04-20       Impact factor: 4.138

  8 in total

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