Login / Signup

Combining Selective Enrichment and a Boosting Approach to Globally and Site-Specifically Characterize Protein Co-translational O -GlcNAcylation.

Senhan XuKejun YinRonghu Wu
Published in: Analytical chemistry (2023)
Protein O -GlcNAcylation plays extremely important roles in mammalian cells, regulating signal transduction and gene expression. This modification can happen during protein translation, and systematic and site-specific analysis of protein co-translational O -GlcNAcylation can advance our understanding of this important modification. However, it is extraordinarily challenging because normally O -GlcNAcylated proteins are very low abundant and the abundances of co-translational ones are even much lower. Here, we developed a method integrating selective enrichment, a boosting approach, and multiplexed proteomics to globally and site-specifically characterize protein co-translational O -GlcNAcylation. The boosting approach using the TMT labeling dramatically enhances the detection of co-translational glycopeptides with low abundance when enriched O -GlcNAcylated peptides from cells with a much longer labeling time was used as a boosting sample. More than 180 co-translational O -GlcNAcylated proteins were site-specifically identified. Further analyses revealed that among co-translational glycoproteins, those related to DNA binding and transcription are highly overrepresented using the total identified O -GlcNAcylated proteins in the same cells as the background. Compared with the glycosylation sites on all glycoproteins, co-translational sites have different local structures and adjacent amino acid residues. Overall, an integrative method was developed to identify protein co-translational O -GlcNAcylation, which is very useful to advance our understanding of this important modification.
Keyphrases
  • amino acid
  • gene expression
  • protein protein
  • dna binding
  • binding protein
  • transcription factor
  • single cell
  • small molecule
  • cell proliferation
  • microbial community
  • label free
  • wastewater treatment
  • network analysis