UniPhos Tip: A Streamlined StageTip for Deep Phosphoproteomic Profiling of Low Input Sample

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ID: 318556
2026
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Abstract
Abstract Phosphoproteomics has emerged as a powerful strategy for dissecting oncogenic signaling networks and therapeutic response mechanisms in clinical research. However, its clinical application for low input samples often remains constrained by extensive multi-step sample handling, cumulative sample loss, and the large protein input requirements of conventional workflows. To address these limitations, we presented UniPhos Tip, an integrated 3-layer packing StageTip composed of Ni-NTA, C18, and SDB-XC that unifies phosphopeptide enrichment, desalting, and optional fractionation within a single device, completing the entire workflow within about 210 minutes. The UniPhos Tip employs a tandemly assembled resin architecture that eliminates inter-tube sample transfers, thereby reducing handling-induced loss and improving analytical robustness. Systematic optimization of washing sequence and fractionation strategy demonstrated that formic acid–based washing increased enrichment specificity from 88% to 96%. The strategy demonstrates robust phosphoproteomic depth under ultra-low input conditions, identifying 3,125 and 4,295 phosphopeptides from 5 µg and 25 µg of peptide inputs, respectively, with high quantitative reproducibility (Spearman ρ > 0.98). Application of the optimized workflow enabled comprehensive detection of phosphorylation sites across major oncogenic signaling cascades, including RTK-RAS-MAPK, PI3K-Akt-mTOR, and JAK-STAT pathways, demonstrating preservation of biologically and pharmacologically relevant network information from limited sample input. Together, UniPhos Tip provides a scalable and low-input–compatible solution for phosphoproteomic sample preparation, bridging workflow simplification with deep and reproducible phosphosite coverage for biologically and clinically relevant applications.
Reference Key
openalex_W7165729423 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Irene‐Ya Tai, S. Chan, Yu‐Ju Chen
Journal bulletin of the chemical society of japan
Year 2026
DOI
10.1093/bulcsj/uoag084
URL
https://doi.org/10.1093/bulcsj/uoag084
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