ArticleCells2022
Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity.
Article in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The trial behind it
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Who cites it
7 citing papers in PubMed, 15 citations in OpenAlex.
- SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.Proteomics · 2025Article
- Trends in Mass Spectrometry-Based Single-Cell Proteomics.Analytical chemistry · 2025Review
- Advancements in Single-Cell Proteomics and Mass Spectrometry-Based Techniques for Unmasking Cellular Diversity in Triple Negative Breast Cancer.Proteomics. Clinical applications · 2025Review
- Enhanced feature matching in single-cell proteomics characterizes IFN-γ response and co-existence of cell states.Nature communications · 2024Article
- Diversity of post-translational modifications and cell signaling revealed by single cell and single organelle mass spectrometry.Communications biology · 2024Article
- Inhibition of TRAP1 Accelerates the DNA Damage Response, Activation of the Heat Shock Response and Metabolic Reprogramming in Colon Cancer Cells.Frontiers in bioscience (Landmark edition) · 2023Article
- Bottom-Up Proteomics: Advancements in Sample Preparation.International journal of molecular sciences · 2023Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of proteins in single cells. However, significant challenges remain in analyzing an extremely small amount of proteins collected from a single cell, as a proteome-wide amplification of proteins is not currently feasible. Here, we report an integrated spectral library-based single-cell proteomics (SLB-SCP) platform that is ultrasensitive and well suited for a large-scale analysis. To overcome the low MS/MS signal intensity intrinsically associated with a single-cell analysis, this approach takes an alternative approach by extracting a breadth of information that specifically defines the physicochemical characteristics of a peptide from MS1 spectra, including monoisotopic mass, isotopic distribution, and retention time (hydrophobicity), and uses a spectral library for proteomic identification. This conceptually unique MS platform, coupled with the DIRECT sample preparation method, enabled identification of more than 2000 proteins in a single cell to distinguish different proteome landscapes associated with cellular types and heterogeneity. We characterized individual normal and cancerous pancreatic ductal cells (HPDE and PANC-1, respectively) and demonstrated the substantial difference in the proteomes between HPDE and PANC-1 at the single-cell level. A significant upregulation of multiple protein networks in cancer hallmarks was identified in the PANC-1 cells, functionally discriminating the PANC-1 cells from the HPDE cells. This integrated platform can be built on high-resolution MS and widely accepted proteomic software, making it possible for community-wide applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.