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用于阵列断层成像的计算性突触抗体表征工具

A Computational Synaptic Antibody Characterization Tool for Array Tomography.

作者信息

Simhal Anish K, Gong Belvin, Trimmer James S, Weinberg Richard J, Smith Stephen J, Sapiro Guillermo, Micheva Kristina D

机构信息

Electrical and Computer Engineering, Duke University, Durham, NC, United States.

Department of Neurobiology, Physiology and Behavior, University of California, Davis, Davis, CA, United States.

出版信息

Front Neuroanat. 2018 Jul 17;12:51. doi: 10.3389/fnana.2018.00051. eCollection 2018.

DOI:10.3389/fnana.2018.00051
PMID:30065633
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6057115/
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 Characterization Tool (SACT) is designed to provide an automatic, robust, flexible, and efficient tool for antibody characterization at scale. SACT automatically detects puncta of immunofluorescence labeling from candidate antibodies and determines whether a punctum belongs to a synapse. The molecular composition and size of the target synapses expected to contain the antigen is determined by the user, based on biological knowledge. Operationally, the presence of a synapse is defined by the colocalization or adjacency of the candidate antibody punctum to one or more reference antibody puncta. The outputs of SACT are automatically computed measurements such as target synapse density and target specificity ratio that reflect the sensitivity and specificity of immunolabeling with a given candidate 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.

摘要

抗体的应用特异性验证是其成功使用的关键前提。在此,我们介绍一种自动化框架,用于针对高分辨率免疫荧光阵列断层扫描(AT)对针对突触分子的抗体进行表征和筛选。所提出的突触抗体表征工具(SACT)旨在提供一种用于大规模抗体表征的自动、稳健、灵活且高效的工具。SACT自动检测候选抗体的免疫荧光标记斑点,并确定一个斑点是否属于突触。预期包含抗原的目标突触的分子组成和大小由用户根据生物学知识确定。在操作上,突触的存在由候选抗体斑点与一个或多个参考抗体斑点的共定位或相邻性来定义。SACT的输出是自动计算的测量值,如目标突触密度和目标特异性比率,这些值反映了用给定候选抗体进行免疫标记的敏感性和特异性。这些测量提供了一种客观的方法来表征和比较针对同一目标的不同抗体的性能,并且可用于客观地选择最适合AT以及潜在地适用于其他免疫标记应用的抗体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ccbb/6057115/094f4f164a8b/fnana-12-00051-g0011.jpg
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