MS1-Level Proteome Quantification Platform Allowing Maximally Increased Multiplexity for SILAC and In Vitro Chemical Labeling
datasetposted on 24.03.2020 by Yeon Choi, Kyowon Jeong, Sanghee Shin, Joon Won Lee, Young-suk Lee, Sangtae Kim, Sun Ah Kim, Jaehun Jung, Kwang Pyo Kim, V. Narry Kim, Jong-Seo Kim
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Quantitative proteomic platforms based on precursor intensity in mass spectrometry (MS1-level) uniquely support in vivo metabolic labeling with superior quantification accuracy but suffer from limited multiplexity (≤3-plex) and frequent missing quantities. Here we present a new MS1-level quantification platform that allows maximal multiplexing with high quantification accuracy and precision for the given labeling scheme. The platform currently comprises 6-plex in vivo SILAC or in vitro diethylation labeling with a dedicated algorithm and is also expandable to higher multiplexity (e.g., nine-plex for SILAC). For complex samples with broad dynamic ranges such as total cell lysates, our platform performs highly accurately and free of missing quantities. Furthermore, we successfully applied our method to measure protein synthesis rate under heat shock response in human cells by 6-plex pulsed SILAC experiments, demonstrating the unique biological merits of our in vivo platform to disclose translational regulations for cellular response to stress.