An Optimized SP3 Sample Processing Workflow for In-Depth and Reproducible Phosphoproteomics

TL;DR

This paper introduces an improved workflow for phosphoproteomics using SP3 magnetic beads, significantly increasing phosphopeptide identifications in cell extracts.

Contribution

The novel workflow uses urea washing and omits C18 SPE cleanup, leading to a 2-fold increase in phosphopeptide identifications.

Findings

Application of the optimized protocol to HEK-293T cell extracts nearly doubled phosphopeptide identifications compared to standard SP3 methods.

The workflow significantly improved detection of multiply phosphorylated peptides.

The study highlights the under-representation of PTM cross-talk in current phosphoproteomics workflows.

Abstract

Protein phosphorylation
is a ubiquitous post-translational
modification
(PTM) found across the kingdoms of life and is critical for the regulation
of protein function in health and disease. Advances in high-throughput
mass spectrometry have transformed our ability to interrogate the
phosphoproteome. However, sample preparation methodologies optimized
for phosphoproteomics have not kept pace, compromising the ability
to fully exploit these technological advances. In this study, we present
an optimized phosphoproteomics workflow using carboxylated SP3 magnetic
beads, which have simplified proteomics sample preparation. By employing
a washing step with 8 M urea and omitting the conventional C18 SPE cleanup, we demonstrate a significant improvement in phosphopeptide
identifications, with application of this refined protocol to HEK-293T
cell extracts increasing the number nearly 2-fold compared to standard
SP3 techniques (7908 cf. 4129). We also observed substantial improvement
in the detection of multiply phosphorylated peptides. Our findings
suggest that the complexity of PTM cross-talk using current peptide-based
proteomics workflows is currently under-represented and underscores
the necessity of methodological innovations to better capture the
intricacies of the phosphoproteome landscape.

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