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Fully automated and integrated proteomics sample preparation platform for high-throughput drug target identification

Wu, Q.; Zheng, J.; Sui, X.; Fu, C.; Cui, X.; Liao, B.; Ji, H.; Luo, Y.; He, A.; Lu, X.; Tan, C. S. H.; Tian, R.

2023-07-16 systems biology
10.1101/2023.07.14.548974 bioRxiv
Show 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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