bioRxivSystems BiologyPreprint
Fully automated and integrated proteomics sample preparation platform for high-throughput drug target identification
Qiong Di WuiD, Jiangnan ZhengiD, Xintong Sui, Changying FuiD, Xiaozhen CuiiD, Bin Yih LiaoiD, Hongchao JiiD, Yang LuoiD, An HeiD, Xue Mei LuiD, Chris Soon Heng TaniD, Ruijun TianiD
Abstract
With the increased demand of large-cohort proteomic analysis, fast and reproducible sample preparation has become the critical issue that needs to be solved. Herein, we developed a fully automated and integrated proteomics sample preparation workflow (autoSISPROT), enabling the simultaneous processing of 96 samples in less than 2.5 hours. Benefiting from its 96-channel all-in-tip operation, protein digestion, peptide desalting, and TMT labeling could be achieved in a fully automated manner. The autoSISPROT demonstrated good sample preparation performances, including >94% of digestion efficiency, nearly 100% of alkylation efficiency, >98% of TMT labeling efficiency, and >0.9 of intra- and inter-batch Pearson correlation coefficients. Furthermore, by combining with cellular thermal shift assay-coupled to mass spectrometry (CETSA-MS), the autoSISPROT was able to process and TMT-label 40 samples automatically and accurately identify the known target of methotrexate. Importantly, taking advantage of the data independent acquisition and isothermal CETSA-MS, the autoSISPROT was well applied for identifying known targets and potential off-targets of 20 kinase inhibitors by automatedly processing 87 samples, affording over a 10-fold improvement in throughput when compared to classical CETSA-MS. Collectively, we developed a fully automated and integrated workflow for high-throughput proteomics sample preparation and drug target identification.
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