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                <identifier>oai:data.mendeley.com/4dcgs8mvzx.3</identifier>
                <datestamp>2022-12-16T08:02:39Z</datestamp>
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    <dc:creator>REN, Ping</dc:creator>
    <dc:title>RAMIHM generates fully human monoclonal antibodies by rapid mRNA immunization of humanized mice and BCR-seq</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>As a clinical vaccine, lipid nanoparticle (LNP) mRNA demonstrated potent and broad antibody responses, leading to speculation about its potential for antibody discovery. Here, we developed RAMIHM, a highly efficient strategy for developing fully human monoclonal antibodies that employs rapid mRNA immunization of humanized mice followed by single B cell sequencing (scBCR-seq). We immunized humanized transgenic mice with RAMIHM and generated 15 top-ranked clones from peripheral blood, plasma B, and memory B cell populations, demonstrating a high rate of antigen-specificity (93.3%). Two Omicron-specific neutralizing antibodies with high potent and one broad-spectrum neutralizing antibody were discovered. Furthermore, we extended the application of RAMIHM to cancer immunotherapy targets, including a single transmembrane protein CD22 and a multi-transmembrane GPCR target, GPRC5D, which is difficult for traditional protein immunization methods. RAMIHM-scBCR-seq is a broadly applicable platform for the rapid and efficient development of fully human monoclonal antibodies against an assortment of targets.</dc:description>
    <dc:subject>Flow Cytometry</dc:subject>
    <dc:contributor>Lei, Peng</dc:contributor>
    <dc:contributor>Yang, Luojia</dc:contributor>
    <dc:contributor>Suzuki, Kazushi</dc:contributor>
    <dc:contributor>Fang, Zhenhao</dc:contributor>
    <dc:contributor>Renauer, Paul</dc:contributor>
    <dc:contributor>Lin, Qianqian</dc:contributor>
    <dc:contributor>Bai, Meizhu</dc:contributor>
    <dc:contributor>Li, Tongqing</dc:contributor>
    <dc:contributor>Clark, Paul</dc:contributor>
    <dc:contributor>Klein, Deryl</dc:contributor>
    <dc:contributor>Chen, Sidi</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/4dcgs8mvzx.3</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/4dcgs8mvzx.3</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
    <dc:rights>http://creativecommons.org/licenses/by/4.0</dc:rights>
    <dc:relation>https://data.mendeley.com/datasets/4dcgs8mvzx</dc:relation>
    <dc:date>2022-12-16T08:02:39Z</dc:date>
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