ArticleCommunications biology2025
Multiplexed phosphoproteomics of low cell numbers using SPARCE.
Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A phosphoproteome atlas of human cell lines reveals the landscape of kinase activity.Nature structural & molecular biology · 2026Article
- Post-translational modifications in the oral microenvironment: Stem cell regulation from periodontal regeneration to oral cancer therapy.World journal of stem cells · 2025Review
- The pursuit of ultrasensitive phosphoproteomics to unravel signalling in rare cells.Communications biology · 2025Review
- A scalable proteogenomic framework for dissecting phospho-signaling pathways in primary immune cells.bioRxiv : the preprint server for biology · 2025Article
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5 authors.
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Abstract
Understanding cellular diversity and disease mechanisms requires a global analysis of proteins and their modifications. While next-generation sequencing has advanced our understanding of cellular heterogeneity, it fails to capture downstream signalling networks. Ultrasensitive mass spectrometry-based proteomics enables unbiased protein-level analysis of low cell numbers, down to single cells. However, phosphoproteomics remains limited to high-input samples due to sample losses and poor reaction efficiencies associated with processing low cell numbers. Isobaric stable isotope labelling is a promising approach for reproducible and accurate quantification of low abundant phosphopeptides. Here, we introduce SPARCE (Streamlined Phosphoproteomic Analysis of Rare CElls) for multiplexed phosphoproteomic analysis of low cell numbers. SPARCE integrates cell isolation, water-based lysis, on-tip TMT labelling, and phosphopeptide enrichment. SPARCE outperforms traditional methods by enhancing labelling efficiency and phosphoproteome coverage. To demonstrate the utility of SPARCE, we analysed four patient-derived glioblastoma stem cell lines, reliably quantifying phosphosite changes from 1000 FACS-sorted cells. This workflow expands the possibilities for signalling analysis of rare cell populations.
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