Longitudinal Large-Scale Semiquantitative Proteomic Data Stability across Multiple Instrument Platforms

Congcong Lu, Tina Glisovic-Aplenc, Kathrin M. Bernt, Kevin Nestler, Joseph Cesare, Lusha Cao, Hyoungjoo Lee, Hossein Fazelinia, Asif Chinwalla, Yang Xu, Olga Shestova, Yi Xing, Saar Gill, Mingyao Li, Benjamin Garcia, Richard Aplenc

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

With the rapid developments in mass spectrometry (MS)-based proteomics methods, label-free semiquantitative proteomics has become an increasingly popular tool for profiling global protein abundances in an unbiased manner. However, the reproducibility of these data across time and LC-MS platforms is not well characterized. Here, we evaluate the performance of three LC-MS platforms (Orbitrap Elite, Q Exactive HF, and Orbitrap Fusion) in label-free semiquantitative analysis of cell surface proteins over a six-year period. Sucrose gradient ultracentrifugation was used for surfaceome enrichment, following gel separation for in-depth protein identification. With our established workflow, we consistently detected and reproducibly quantified >2300 putative cell surface proteins in a human acute myeloid leukemia (AML) cell line on all three platforms. To our knowledge this is the first study reporting highly reproducible semiquantitative proteomic data collection of biological replicates across multiple years and LC-MS platforms. These data provide experimental justification for semiquantitative proteomic study designs that are executed over multiyear time intervals and on different platforms. Multiyear and multiplatform experimental designs will likely enable larger scale proteomic studies and facilitate longitudinal proteomic studies by investigators lacking access to high throughput MS facilities. Data are available via ProteomeXchange with identifier PXD022721.

Original languageEnglish
Pages (from-to)5203-5211
Number of pages9
JournalJournal of Proteome Research
Volume20
Issue number11
DOIs
StatePublished - Nov 5 2021

Keywords

  • label-free quantification
  • large-scale
  • mass spectrometry
  • quantitative proteomics
  • reproducibility
  • surfaceome
  • target discovery

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