ArticleAngewandte Chemie (International ed. in English)2025
Real-Time Eco-AI, Electrophoresis-Correlative Data-Dependent Acquisition with AI-Based Data Processing Broadens Access to Single-Cell Mass Spectrometry Proteomics.
Article in Angewandte Chemie (International ed. in English), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Aspiration Patch Proteomics Enables CE-ESI-MS Proteotyping of Identified Single Neurons in Intact Brain Tissue.Analytical chemistry · 2026Article
- Integrating Low-Voltage Microfluidics With On-Chip Electrospray Ionization for Miniaturized Protein Analysis.Small methods · 2026Review
- Scientific and operational maturity of CE-MS: are we close?Trends in biotechnology · 2026Review
- Recent Developments and Applications of Capillary and Microchip Electrophoresis in Proteomics and Peptidomics (2023-2025).Journal of separation science · 2026Review
- Deep Proteome Profiling of Rat Dorsal Striatal Synaptoneurosomes Following Methamphetamine Exposure.ACS chemical neuroscience · 2026Article
- Real-Time Eco-AI, Electrophoresis-Correlative Data-Dependent Acquisition with AI-Based Data Processing Broadens Access to Single-Cell Mass Spectrometry Proteomics.Angewandte Chemie (International ed. in English) · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Single-cell mass spectrometry (MS) offers unprecedented sensitivity for profiling cellular proteomes, yet widespread adoption is hindered by the cost of advanced instrumentation. Here, we broaden access to single-cell proteomics by combining capillary electrophoresis (CE), data-dependent acquisition (DDA) with electrophoresis-correlative (Eco) ion sorting, and artificial intelligence (AI)-assisted spectral deconvolution via CHIMERYS (Eco-AI). This "Real-Time Eco-AI" workflow was implemented on a custom-built CE platform coupled to a legacy hybrid quadrupole-orbitrap mass spectrometer (Q Exactive Plus). Despite slower scan speed, lower resolution, and inferior ion transmission efficiency, real-time Eco-DDA sampling and CHIMERYS processing enabled identification of up to ∼15 peptides per spectrum-performance on par with modern Orbitrap Fusion Lumos tribrid systems. From 1 ng of HeLa digest, 2142 proteins were identified, surpassing the 969 proteins detected on a contemporary nanoLC Orbitrap Fusion Lumos. Even from ∼250 pg (a single-cell equivalent), 1799 proteins were identified in <15 min of effective separation, raising a theoretical throughput of 48 samples per day. As proof of principle, Real-Time Eco-AI profiled 1524 proteins from single precursor cells (50-75 µm diameter) in Xenopus laevis blastulae, revealing proteome asymmetry during neural versus epidermal fate specification. These results establish Real-Time Eco-AI as a budget-conscious yet powerful strategy for single-cell proteomics using CE-MS.
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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.