Megan K Gautier1, Stephen D Ginsberg2. 1. Center for Dementia Research, Nathan Kline Institute, Orangeburg, NY, USA; Program of Pathobiology and Translational Medicine, Vilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, USA; NYU Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA. 2. Center for Dementia Research, Nathan Kline Institute, Orangeburg, NY, USA; Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA; Department of Neuroscience & Physiology, NYU Grossman School of Medicine, New York, NY, USA; NYU Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA. Electronic address: ginsberg@nki.rfmh.org.
Abstract
BACKGROUND: Phenotypic changes in vesicular compartments are an early pathological hallmark of many peripheral and central diseases. For example, accurate assessment of early endosome pathology is crucial to the study of Down syndrome (DS) and Alzheimer's disease (AD), as well as other neurological disorders with endosomal-lysosomal pathology. NEW METHOD: We describe a method for quantification of immunolabeled early endosomes within transmitter-identified basal forebrain cholinergic neurons (BFCNs) using 3-dimensional (3D) reconstructed confocal z-stacks employing Imaris software. RESULTS: Quantification of 3D reconstructed z-stacks was performed using two different image analysis programs: ImageJ and Imaris. We found ImageJ consistently overcounted the number of early endosomes present within individual BFCNs. Difficulty separating densely packed early endosomes within defined BFCNs was observed in ImageJ compared to Imaris. COMPARISON WITH EXISTING METHODS: Previous methods quantifying endosomal-lysosomal pathology relied on confocal microscopy images taken in a single plane of focus. Since early endosomes are distributed throughout the soma and neuronal processes of BFCNs, critical insight into the abnormal early endosome phenotype may be lost as a result of analyzing only a single image of the perikaryon. Rather than relying on a representative sampling, this protocol enables precise, direct quantification of all immunolabeled vesicles within a defined cell of interest. CONCLUSIONS: Imaris is an ideal program for accurately counting punctate vesicles in the context of dual label confocal microscopy. Superior image resolution and detailed algorithms offered by Imaris make precise and rigorous quantification of individual early endosomes dispersed throughout a BFCN in 3D space readily achievable.
BACKGROUND: Phenotypic changes in vesicular compartments are an early pathological hallmark of many peripheral and central diseases. For example, accurate assessment of early endosome pathology is crucial to the study of Down syndrome (DS) and Alzheimer's disease (AD), as well as other neurological disorders with endosomal-lysosomal pathology. NEW METHOD: We describe a method for quantification of immunolabeled early endosomes within transmitter-identified basal forebrain cholinergic neurons (BFCNs) using 3-dimensional (3D) reconstructed confocal z-stacks employing Imaris software. RESULTS: Quantification of 3D reconstructed z-stacks was performed using two different image analysis programs: ImageJ and Imaris. We found ImageJ consistently overcounted the number of early endosomes present within individual BFCNs. Difficulty separating densely packed early endosomes within defined BFCNs was observed in ImageJ compared to Imaris. COMPARISON WITH EXISTING METHODS: Previous methods quantifying endosomal-lysosomal pathology relied on confocal microscopy images taken in a single plane of focus. Since early endosomes are distributed throughout the soma and neuronal processes of BFCNs, critical insight into the abnormal early endosome phenotype may be lost as a result of analyzing only a single image of the perikaryon. Rather than relying on a representative sampling, this protocol enables precise, direct quantification of all immunolabeled vesicles within a defined cell of interest. CONCLUSIONS: Imaris is an ideal program for accurately counting punctate vesicles in the context of dual label confocal microscopy. Superior image resolution and detailed algorithms offered by Imaris make precise and rigorous quantification of individual early endosomes dispersed throughout a BFCN in 3D space readily achievable.
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