ArticleNature biotechnology2023
Increasing the throughput of sensitive proteomics by plexDIA.
Article in Nature biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 145 papers, 1 of them a synthesis that pooled it.
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Who cites it
145 citing papers in PubMed, 1 synthesis or guideline pooled it, 245 citations in OpenAlex.
- Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments.Nature methods · 2023Guideline
- Implementation of Nonisobaric TMT Analogs for Accurate Precursor-Level Quantification by plexDIA.Rapid communications in mass spectrometry : RCM · 2026Article
- Post-translational modification of proteins in the human testis development pathway.Human reproduction update · 2026Review
- Pushing the limits of single-cell proteomics to investigate bacterial heterogeneity using bacSCP.Nature communications · 2026Article
- Proteomic investigation of signaling dynamics: from static maps to network rewiring.Bioscience reports · 2026Review
- Article
- Top-Down versus Bottom-Up Proteomics in Highly Sensitive LC-MS-Based Profiling of Limited Samples.Analytical chemistry · 2026Article
- Addressing multiple facets of ligand-receptor network inference including single-cell proteomics.Nucleic acids research · 2026Article
- AlphaDIA enables DIA transfer learning for feature-free proteomics.Nature biotechnology · 2026Article
- The proteomics and phosphoproteomics landscape of melanoma under T cell attack.Cell reports. Medicine · 2026Article
- Comparative phosphoproteomic analysis reveals regulatory mechanisms underlying muscle fiber density in goslings.Poultry science · 2026Article
- Accurate quantification in proteomics with QuantUMS.Nature biotechnology · 2026Article
- Single-Cell Proteomic Technologies: Tools in the Quest for Principles.Annual review of biophysics · 2026Review
- Full-DIA enables complete single-cell proteomics from diaPASEF using deep learning.Genome biology · 2026Article
- Proteomic remodeling during tumor cell-induced platelet aggregation unveils metastatic drivers in colorectal cancer.Cancer cell international · 2026Article
- Review
- Resolving Single-Cell Gene Expression by Pseudotemporal Integration of Transcriptomic and Proteomic Datasets.Molecular & cellular proteomics : MCP · 2026Article
- Data-independent acquisition-based quantitative proteomics in plants.Frontiers in plant science · 2026Review
- Article
- Mass spectrometry-based profiling of single-cell histone post-translational modifications to dissect chromatin heterogeneity.Nature communications · 2025Article
85 more citing papers are in PubMed but not listed here.
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Authors and funding
10 authors at 4 institutions in 4 countries.
Funding
Abstract
Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using three-plex non-isobaric mass tags, plexDIA enables quantification of threefold more protein ratios among nanogram-level samples. Using 1-hour active gradients, plexDIA quantified ~8,000 proteins in each sample of labeled three-plex sets and increased data completeness, reducing missing data more than twofold across samples. Applied to single human cells, plexDIA quantified ~1,000 proteins per cell and achieved 98% data completeness within a plexDIA set while using ~5 minutes of active chromatography per cell. These results establish a general framework for increasing the throughput of sensitive and quantitative protein analysis.
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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.