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Published on: May 11, 2018
An automated method for the quantification of transgene expression in motor axons of the peripheral nerve
Hans E Anderson1, John H Caldwell2, Richard F Weir1
1Department of Bioengineering, University of Colorado, Anschutz Medical Campus, CO, USA.
Background:
Determination of transgene expression in motor axons of peripheral nerves is important in evaluating the effectiveness of viral transduction. Currently only manual and semi-automatic methods of quantification have been employed for quantification in immunolabeled nerve sections, but automatic methods exist for axon counting only in brightfield sections. Manual and semi-automatic methods can suffer from inter- and intraobserver bias, sampling bias and can be time consuming to implement.
New Method:
A fully automated method using ImageJ and the Nucleus Counter plugin was developed to quantify the fraction of green fluorescent protein (GFP) labeled acetylcholine transferase positive axons in triple immunolabeled peripheral nerve sections. This method utilizes the Nucleus Counter to generate axonal regions of interest which are quantified for colocalization with GFP expression and nonoverlap with Laminin. Thresholding using histograms generated from control animals is used to remove noise.
Results:
The automated method is able to successfully distinguish transgenic GFP expressing mice from wild type. Using computer generated peripheral nerve sections, the automated method has less than 5% error at signal-to-noise ratios greater than 10% of baseline.
Comparisons With Existing Methods:
This method has comparable performance in false positive rates (<1%) and a 95% predictive interval that closely matches existing fully automated methods for quantification in brightfield sections. It outperforms the intra- and interobserver differences of manual and semi-automated methods for quantification.
Conclusions:
This automated quantification method provides a fast and robust means of determining the fraction of labeled axons in peripheral nerve sections.
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