Narrow-window DIA: Ultra-fast quantitative analysis of comprehensive proteomes with high sequencing depth

Abstract Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here, we present an ultra-fast scanning data-independent acquisition (DIA) strategy consisting on 2-Th precursor isolation windows, dissolving the differences between data-dependent and independent methods. This is achieved by pairing a Quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer that provides >200 Hz MS/MS scanning speed, high resolving power and sensitivity, as well as low ppm-mass accuracy. Narrow-window DIA enables profiling of up to 100 full yeast proteomes per day, or ∼10,000 human proteins in half-an-hour. Moreover, multi-shot acquisition of fractionated samples allows comprehensive coverage of human proteomes in ∼3h, showing comparable depth to next-generation RNA sequencing and with 10x higher throughput compared to current state-of-the-art MS. High quantitative precision and accuracy is demonstrated with high peptide coverage in a 3-species proteome mixture, quantifying 14,000+ proteins in a single run in half-an-hour.Teaser Accurate and precise label-free quantification with comprehensive proteome coverage using narrow-window DIA.

Medienart:

Preprint

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

bioRxiv.org - (2023) vom: 10. Juni Zur Gesamtaufnahme - year:2023

Sprache:

Englisch

Beteiligte Personen:

Guzman, Ulises H [VerfasserIn]
Martinez Del Val, Ana [VerfasserIn]
Ye, Zilu [VerfasserIn]
Damoc, Eugen [VerfasserIn]
Arrey, Tabiwang N. [VerfasserIn]
Pashkova, Anna [VerfasserIn]
Denisov, Eduard [VerfasserIn]
Petzoldt, Johannes [VerfasserIn]
Peterson, Amelia C. [VerfasserIn]
Harking, Florian [VerfasserIn]
Østergaard, Ole [VerfasserIn]
Stewart, Hamish [VerfasserIn]
Xuan, Yue [VerfasserIn]
Hermanson, Daniel [VerfasserIn]
Hock, Christian [VerfasserIn]
Makarov, Alexander [VerfasserIn]
Zabrouskov, Vlad [VerfasserIn]
Olsen, Jesper V. [VerfasserIn]

Links:

Volltext [kostenfrei]

Themen:

570
Biology

doi:

10.1101/2023.06.02.543374

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI039817342