Identifications of Putative PKA Substrates with Quantitative Phosphoproteomics and Primary-Sequence-Based Scoring

Area of Science:

• Molecular Biology
• Cell Signaling
• Biochemistry

Background:

• Protein kinase A (PKA) regulates critical cellular processes like proliferation, differentiation, and apoptosis.
• Understanding PKA's direct interactions with its substrates is crucial for elucidating its diverse cellular functions.
• Identifying PKA targets in living cells is essential for a comprehensive understanding of PKA signaling pathways.

Purpose of the Study:

• To identify direct PKA target substrates in living human cells using a high-throughput approach.
• To expand the known PKA signaling network by proposing a confident list of PKA substrate candidates.
• To differentiate direct PKA targets from indirect effects by integrating quantitative phosphoproteomics and computational modeling.

Main Methods:

• Perturbation of PKA activity using drug stimulations in human cells.
• Quantitative phosphoproteome analysis using Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS).
• Development of a computational model to predict kinase sequence specificity for substrate recognition.
• Integration of quantitative phosphorylation data with sequence specificity models to identify PKA targets.

Main Results:

• LC-MS/MS analysis identified 2755 and 3191 phosphopeptides upon PKA activation or inhibition.
• A computational model was built to characterize PKA sequence specificity.
• 29 reliable PKA targeting residue candidates were identified in living cells, including 8 known substrates.
• 18 of the identified sites were confirmed to be site-specifically phosphorylated in vitro.

Conclusions:

• This study successfully identified a confident list of PKA substrate candidates in living human cells.
• The findings expand the current knowledge of the PKA signaling network.
• The integrated approach of phosphoproteomics and computational modeling provides a robust method for identifying kinase-substrate interactions.