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Orbitrap_SciLib
Reputable Mentor II
Reputable Mentor II
Gregory K. Potts1, Bhavin Patel2, Leigh Foster2, John C. Rogers2
ASMS 2017 Poster
Antibodies have been adopted as investigative tools to empower research and diagnostic applications in academia and industry. In this role, antibodies have been utilized to enrich protein targets for the detection and quantification of proteins and their post-translational modification (PTMs) from complex samples. While hundreds of thousands of antibodies are commercially available, many of these antibodies are poorly characterized.1,2 This lack of characterization places a burden on researchers due to delayed project timelines, increased costs, and potentially flawed research conclusions. To verify antibody quality and performance, we have created a comprehensive workflow to assess antibody specificity using immunoprecipitation combined with mass spectrometry (IP-MS). In preliminary experiments, we performed deep proteome analyses of 12 cultured cancer cell lines using a bottom-up MS workflow to analyze unfractionated and fractionated peptide samples. Each unfractionated digest identified 3,800-4,500 unique protein groups, and each fractionated digest identified 7,500-9,000 protein groups. These protein expression profiles were incorporated into a library to facilitate the selection of cell lysates which expressed protein targets at low to medium abundance for subsequent IP-MS analysis. An initial screen of over 650 antibodies to nearly 100 key cancer signaling proteins determined that over 70% of antibodies which were previously validated for immunocapture could be used to bind and identify their intended targets by IP-MS, and over 45% of screened antibodies not previously validated for IP applications successfully pulled down their intended targets. Utilizing MS-based label free quantification (LFQ), we developed a system to generate a fold-enrichment score to better visualize an antibody’s selectivity for its intended target compared to the non-specifically bound proteins identified in each IP experiment. Beyond simply determining the presence or absence of an antibody’s target following IP, we show that our IP-MS approach is uniquely capable of calculating a fold-enrichment score for interacting proteins or potential off-target proteins. For example, in multiple CDH1, CTNNB1, and TP53 IP-MS experiments, screened antibodies enriched their targets by several orders of magnitude versus background and bound to known protein interactors as determined using the STRING database and GO term enrichment. To demonstrate the efficacy of these antibodies, we used a subset to simultaneously immunocapture twelve proteins in the Akt/mTOR pathway, and then quantified the proteins and their phosphorylation in three hIGF-1 stimulated and unstimulated cell lines using MS-based targeted quantification.


1 Abbvie, Abbott Park, IL 2 Thermo Fisher Scientific, Rockford, IL
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‎10-15-2021 11:32 AM
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