Literature DB >> 24457055

Extraction of protein profiles from primary neurons using active contour models and wavelets.

Danny Misiak1, Stefan Posch2, Marcell Lederer3, Claudia Reinke3, Stefan Hüttelmaier3, Birgit Möller2.   

Abstract

The function of complex networks in the nervous system relies on the proper formation of neuronal contacts and their remodeling. To decipher the molecular mechanisms underlying these processes, it is essential to establish unbiased automated tools allowing the correlation of neurite morphology and the subcellular distribution of molecules by quantitative means. We developed NeuronAnalyzer2D, a plugin for ImageJ, which allows the extraction of neuronal cell morphologies from two dimensional high resolution images, and in particular their correlation with protein profiles determined by indirect immunostaining of primary neurons. The prominent feature of our approach is the ability to extract subcellular distributions of distinct biomolecules along neurites. To extract the complete areas of neurons, required for this analysis, we employ active contours with a new distance based energy. For locating the structural parts of neurons and various morphological parameters we adopt a wavelet based approach. The presented approach is able to extract distinctive profiles of several proteins and reports detailed morphology measurements on neurites. We compare the detected neurons from NeuronAnalyzer2D with those obtained by NeuriteTracer and Vaa3D-Neuron, two popular tools for automatic neurite tracing. The distinctive profiles extracted for several proteins, for example, of the mRNA binding protein ZBP1, and a comparative evaluation of the neuron segmentation results proves the high quality of the quantitative data and proves its practical utility for biomedical analyses.
Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Active contours; Fluorescence microscopy; High-content analysis; Neuron morphology; Protein distribution; Segmentation; Wavelets

Mesh:

Year:  2014        PMID: 24457055     DOI: 10.1016/j.jneumeth.2013.12.009

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


  2 in total

1.  Automated profiling of growth cone heterogeneity defines relations between morphology and motility.

Authors:  Maria M Bagonis; Ludovico Fusco; Olivier Pertz; Gaudenz Danuser
Journal:  J Cell Biol       Date:  2018-12-06       Impact factor: 10.539

2.  Off the beaten track: the molecular structure of long-term memory: three novel hypotheses-electrical, chemical and anatomical (allosteric).

Authors:  John Smythies
Journal:  Front Integr Neurosci       Date:  2015-01-29
  2 in total

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