Cross-talk between GlcNAcylation and phosphorylation: site-specific phosphorylation dynamics in response to globally elevated O-GlcNAc

Abstract

Protein GlcNAcylation serves as a nutrient/stress sensor to modulate the functions of many nuclear and cytoplasmic proteins. O-GlcNAc cycles on serine or threonine residues like phosphorylation, is nearly as abundant, and functions, at least partially, via its interplay with phosphorylation. Here, we describe changes in site-specific phosphorylation dynamics in response to globally elevated GlcNAcylation. By combining sequential phospho-residue enrichment, iTRAQ labeling, and high throughput mass spectrometric analyses, phosphorylation dynamics on 711 phosphopeptides were quantified. Based upon their insensitivity to phosphatase inhibition, we conclude that approximately 48% of these phosphorylation sites were not actively cycling in the conditions of the study. However, increased GlcNAcylation influenced phosphate stoichiometry at most of the sites that did appear to be actively cycling. Elevated GlcNAcylation resulted in lower phosphorylation at 280 sites and caused increased phosphorylation at 148 sites. Thus, the cross-talk or interplay between these two abundant posttranslational modifications is extensive, and may arises both by steric competition for occupancy at the same or proximal sites and by each modification regulating the other's enzymatic machinery. The phosphoproteome dynamics presented by this large set of quantitative data not only delineates the complex interplay between phosphorylation and GlcNAcyation, but also provides insights for more focused investigations of specific roles of O-GlcNAc in regulating protein functions and signaling pathways.

Fig. 1.

Effects of elevated GlcNAcylation and phosphorylation on each other. NIH 3T3 cells were untreated and treated with okadaic acid (225 nM), PUGNAc (100 μM), and 20 μM NAG-thiazoline as indicated for 2.5 h before harvest. Cell lysates (20 μg for each group) were resolved in SDS/PAGE, transferred, and blotted with phosphothreonine or O-GlcNAc antibody. The same membrane was stripped and blotted with anti-actin for loading control. OA, okadaic acid; P/N, combined treatment with PUGNAc and NAG-thiazoline.

Fig. 2.

Quantitative proteomics approach used to delineate global interplay between phosphorylation and GlcNAcylation. (A) Flow chart for phosphosite detection and site-specific quantitation. (B) Flow chart for protein expression level quantitation using iTRAQ. (C) Formula used to calculate RORs.

Fig. 3.

Summary of large-scale identification and quantitation. (A) Distribution of detected phosphoserine, threonine, and tyrosine sites. (B) Total number of identified proteins and distribution of protein expression level dynamics. (C) Distribution of phosphorylation ROR dynamics. (D–F) Log₂ ratios of site-specific phosphorylation RORs under indicated conditions. Positions at the heat maps correspond to the same phosphorylation sites.

Fig. 4.

Detection and quantitation of phosphopeptides. Selected samples originating from nuclear factor 1/B (A), DNA replication licensing factor MCM4 (B), myristoylated alanine-rich C-kinase substrate (C), and insulin receptor substrate 2 (D). (Insets) Indicate the intensities of iTRAQ reporter ions.

Fig. 5.

DNA/RNA-binding proteins showed different patterns of phosphorylation dynamics after treatment of O-GlcNAcase inhibitors compared with cytosketetal and cytoskeleton-binding proteins.