Proteomics-driven identification of short open reading frame-encoded peptides

Proteomics. 2022 Aug;22(15-16):e2100312. doi: 10.1002/pmic.202100312. Epub 2022 Apr 12.

Abstract

Accumulating evidence has shown that a large number of short open reading frames (sORFs) also have the ability to encode proteins. The discovery of sORFs opens up a new research area, leading to the identification and functional study of sORF encoded peptides (SEPs) at the omics level. Besides bioinformatics prediction and ribosomal profiling, mass spectrometry (MS) has become a significant tool as it directly detects the sequence of SEPs. Though MS-based proteomics methods have proved to be effective for qualitative and quantitative analysis of SEPs, the detection of SEPs is still a great challenge due to their low abundance and short sequence. To illustrate the progress in method development, we described and discussed the main steps of large-scale proteomics identification of SEPs, including SEP extraction and enrichment, MS detection, data processing and quality control, quantification, and function prediction and validation methods.

Keywords: LC/MS/MS; method development; peptidomics; sORF-encode peptides; sample preparation; short open reading frame.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • Open Reading Frames
  • Peptides* / analysis
  • Proteins
  • Proteomics* / methods

Substances

  • Peptides
  • Proteins