Automated analysis of images for molecular quantification in immunohistochemistry

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Guirado , R , Carceller , H , Castillo-Gomez , E , Castren , E & Nacher , J 2018 , ' Automated analysis of images for molecular quantification in immunohistochemistry ' , Heliyon , vol. 4 , no. 6 , 00669 .

Title: Automated analysis of images for molecular quantification in immunohistochemistry
Author: Guirado, Ramon; Carceller, Hector; Castillo-Gomez, Esther; Castren, Eero; Nacher, Juan
Contributor organization: Neuroscience Center
Helsinki In Vivo Animal Imaging Platform (HAIP)
Eero Castren / Principal Investigator
Date: 2018-06
Language: eng
Number of pages: 16
Belongs to series: Heliyon
ISSN: 2405-8440
Abstract: The quantification of the expression of different molecules is a key question in both basic and applied sciences. While protein quantification through molecular techniques leads to the loss of spatial information and resolution, immunohistochemistry is usually associated with time-consuming image analysis and human bias. In addition, the scarce automatic software analysis is often proprietary and expensive and relies on a fixed threshold binarization. Here we describe and share a set of macros ready for automated fluorescence analysis of large batches of fixed tissue samples using FIJI/ImageJ. The quantification of the molecules of interest are based on an automatic threshold analysis of immunofluorescence images to automatically identify the top brightest structures of each image. These macros measure several parameters commonly quantified in basic neuroscience research, such as neuropil density and fluorescence intensity of synaptic puncta, perisomatic innervation and col-localization of different molecules and analysis of the neurochemical phenotype of neuronal subpopulations. In addition, these same macro functions can be easily modified to improve similar analysis of fluorescent probes in human biopsies for diagnostic purposes based on the expression patterns of several molecules.
Subject: Neuroscience
3112 Neurosciences
Peer reviewed: Yes
Rights: cc_by_nc_nd
Usage restriction: openAccess
Self-archived version: publishedVersion

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