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.
| Original language | English (US) |
|---|---|
| Article number | 51 |
| Journal | Frontiers in Neuroanatomy |
| Volume | 12 |
| DOIs | |
| State | Published - Jul 17 2018 |
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Keywords
- Antibodies
- Antibody characterization
- Array tomography
- Automatic algorithms
- Proteometric composition
- Synapse
- Synapse detection
ASJC Scopus subject areas
- Anatomy
- Neuroscience (miscellaneous)
- Cellular and Molecular Neuroscience
Cite this
A Computational Synaptic Antibody Characterization Tool for Array Tomography. / Simhal, Anish K.; Gong, Belvin; Trimmer, James; Weinberg, Richard J.; Smith, Stephen J.; Sapiro, Guillermo; Micheva, Kristina D.
In: Frontiers in Neuroanatomy, Vol. 12, 51, 17.07.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A Computational Synaptic Antibody Characterization Tool for Array Tomography
AU - Simhal, Anish K.
AU - Gong, Belvin
AU - Trimmer, James
AU - Weinberg, Richard J.
AU - Smith, Stephen J.
AU - Sapiro, Guillermo
AU - Micheva, Kristina D.
PY - 2018/7/17
Y1 - 2018/7/17
N2 - 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.
AB - 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.
KW - Antibodies
KW - Antibody characterization
KW - Array tomography
KW - Automatic algorithms
KW - Proteometric composition
KW - Synapse
KW - Synapse detection
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UR - http://www.scopus.com/inward/citedby.url?scp=85054860675&partnerID=8YFLogxK
U2 - 10.3389/fnana.2018.00051
DO - 10.3389/fnana.2018.00051
M3 - Article
AN - SCOPUS:85054860675
VL - 12
JO - Frontiers in Neuroanatomy
JF - Frontiers in Neuroanatomy
SN - 1662-5129
M1 - 51
ER -