A Computational Synaptic Antibody Characterization and Screening Framework for Array Tomography

Abstract

Application-specific validation of antibodies is a critical prerequisite for their successful use. Here we introduce an automated framework for characterization and screening of antibodies against synaptic molecules for high-resolution immunofluorescence array tomography (AT). The proposed Synaptic Antibody Screening Tool (SACT), is designed to provide an automatic, robust, flexible, and efficient tool for antibody characterization at scale. By allowing the user to define the molecular composition and size of synapses expected to contain the antigen, the method detects and characterizes puncta and synapses, and outputs automatically computed characteristics such as synapse density and target specificity ratio, which reflect the sensitivity and specificity of immunolabeling with a given antibody. These measurements provide an objective way to characterize and compare the performance of different antibodies against the same target, and can be used to objectively select the antibodies best suited for AT and potentially for other immunolabeling applications.