Investigating the Applicability of Antibodies Generated within the Human Protein Atlas as Capture Agents in Immunoenrichment Coupled to Mass Spectrometry
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- 作者：Tove Bostr枚m ; Henrik J. Johansson ; Janne Lehti枚 ; Mathias Uhl茅n ; Sophia Hober
- 刊名：Journal of Proteome Research
- 出版年：2014
- 出版时间：October 3, 2014
- 年：2014
- 卷：13
- 期：10
- 页码：4424-4435
- 全文大小：412K
- ISSN：1535-3907
文摘
For identification and characterization of proteins in complex samples, immunoenrichment coupled to mass spectrometry is a good alternative due to the sensitivity of the affinity enrichment and the specificity of mass spectrometry analysis. Antibodies are commonly used affinity agents; however, for high-throughput analysis, antibody availability is usually a bottleneck. Here we present a protocol for immunoenrichment coupled to mass spectrometry in a high-throughput setup, where all steps from bead coupling to mass spectrometry sample preparation are performed in parallel in a 96-well format. Antibodies generated within the Human Protein Atlas project were tested for applicability as capture agents. The antibodies were covalently attached to protein A beads, making it possible to reuse the coupled beads at least three times without destroying the antibody binding efficiency. Target proteins were captured from a U251 MG cell lysate, eluted, digested, and analyzed using mass spectrometry. Of 30 investigated antibodies, around 50% could successfully capture the corresponding native target protein, making the available library of more than 21鈥?00 antibodies a valuable resource for immunoenrichment assays. Due to the diversity of different antibodies regarding affinity and specificity, analyzing antibodies in a high-throughput format is challenging. Even though protocol optimization for individual antibodies can be advantageous for future studies, our method enables a fast screening strategy to determine the usefulness of antibodies in immunoenrichment setups. In addition, we show that the specificity of the antibodies can be investigated by using label-free quantification.