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Updated: Mar 27, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
What Does Next-Generation Mass Spectrometry Offer for Proteomics? A Comprehensive Platform Comparison
Filipa Blasco Tavares Pereira Lopes1,2, Daniela Schlatzer1, Tara Sudhadevi3
1Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio 44106, United States.
Abstract:
Next-generation mass spectrometry platforms (Orbitrap Astral, timsTOF Ultra) are reshaping proteomics by enhancing analytical depth and sensitivity. We compared these platforms against Orbitrap Exploris 480 using neonatal mouse lung tissues from a bronchopulmonary dysplasia model (n = 12), employing four acquisition strategies: Exploris 480 DDA/DIA, Astral HR-DIA, and timsTOF Ultra DIA-PASEF. All platforms identified ∼4000 proteins in common, with 98% proteome coverage of data-dependent acquisition (DDA) identifications using data-independent (DIA) methods and 92% concordance between next-generation systems. Orbitrap Astral and timsTOF Ultra quantified >225,000 peptides and 13,000 proteins, representing ∼800% and ∼300% greater depth than Exploris 480 DDA, respectively. Furthermore, new-generation platforms cut recommended sample size by ∼66%. Enhanced proteome depth improved subcellular compartment annotations from 30% (DDA) to 66% (next-generation platforms) and reactome pathway coverage from 58% (DDA) to 90% (next-generation platforms). Differential expression analysis identified up to four times more phenotype-associated proteins in DIA data sets, enriched in mitochondrial, ribosomal, and extracellular components, with up to 44 enriched pathways. Importantly, proteins uniquely detected showed no functional annotation bias. These findings demonstrate that DIA acquisition on multivendor next-generation platforms provides superior proteome coverage and more complete systems biology assessment without introducing bias, enabling enhanced understanding of complex biological systems.
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