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

J Proteome Res. 2021 Nov 5;20(11):5203-5211. doi: 10.1021/acs.jproteome.1c00624. Epub 2021 Oct 20.

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.

Keywords: label-free quantification; large-scale; mass spectrometry; quantitative proteomics; reproducibility; surfaceome; target discovery.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Mass Spectrometry / methods
  • Proteome* / analysis
  • Proteomics* / methods
  • Reproducibility of Results
  • Workflow

Substances

  • Proteome