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    Use of HCA in subproteome-immunization and screening of hybridoma supernatants to define distinct antibody binding patterns

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    Authors
    Szafran, Adam T.
    Mancini, Maureen G.
    Nickerson, Jeffrey A.
    Edwards, Dean P.
    Mancini, Michael A.
    UMass Chan Affiliations
    Department of Cell and Developmental Biology
    Document Type
    Journal Article
    Publication Date
    2016-03-01
    Keywords
    High content analysis
    High throughput imaging
    Hybridoma
    Machine learning
    Monoclonal antibody
    Nuclear matrix
    Biochemistry, Biophysics, and Structural Biology
    Cell Biology
    
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    Link to Full Text
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4891975/
    Abstract
    Understanding the properties and functions of complex biological systems depends upon knowing the proteins present and the interactions between them. Recent advances in mass spectrometry have given us greater insights into the participating proteomes, however, monoclonal antibodies remain key to understanding the structures, functions, locations and macromolecular interactions of the involved proteins. The traditional single immunogen method to produce monoclonal antibodies using hybridoma technology are time, resource and cost intensive, limiting the number of reagents that are available. Using a high content analysis screening approach, we have developed a method in which a complex mixture of proteins (e.g., subproteome) is used to generate a panel of monoclonal antibodies specific to a subproteome located in a defined subcellular compartment such as the nucleus. The immunofluorescent images in the primary hybridoma screen are analyzed using an automated processing approach and classified using a recursive partitioning forest classification model derived from images obtained from the Human Protein Atlas. Using an ammonium sulfate purified nuclear matrix fraction as an example of reverse proteomics, we identified 866 hybridoma supernatants with a positive immunofluorescent signal. Of those, 402 produced a nuclear signal from which patterns similar to known nuclear matrix associated proteins were identified. Detailed here is our method, the analysis techniques, and a discussion of the application to further in vivo antibody production.
    Source
    Methods. 2016 Mar 1;96:75-84. doi: 10.1016/j.ymeth.2015.10.021. Epub 2015 Oct 30. Link to article on publisher's site
    DOI
    10.1016/j.ymeth.2015.10.021
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/26499
    PubMed ID
    26521976
    Related Resources
    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ymeth.2015.10.021
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