Lia R Serrano, Adrian Pelin, Tabiwang N Arrey, Nicolaie E Damoc, Alicia L Richards, Yuan Zhou, Noah M Lancaster, Trenton M Peters-Clarke, Anna Pashkova, Gwendolyn M Jang, Manon Eckhardt, Scott T Quarmby, Martin Zeller, Daniel Hermanson, Hamish Stewart, Christian Hock, Alexander Makarov, Vlad Zabrouskov, Nevan J Krogan, Joshua J Coon, Danielle L Swaney
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引用次数: 0
Abstract
Classical proteomics experiments offer high-throughput protein quantification but lack direct evidence of the spatial organization of the proteome, including protein-protein interaction (PPIs) networks. While affinity purification mass spectrometry (AP-MS) is the method of choice for generating these networks, technological impediments have stymied the throughput of AP-MS sample collection and therefore constrained the rate and scale of experiments that can be performed. Here, we build on advances in mass spectrometry hardware that have rendered high-flow liquid chromatography separations a viable solution for faster throughput quantitative proteomics. We describe our methodology using the Orbitrap-Astral mass spectrometer with 7 min, high-flow separations to analyze 216 AP-MS samples in ∼29 h. We show that the ion-focusing advancements, rapid mass analysis, and sensitive ion detection facilitate narrow-bin data-independent acquisition on a chromatographically practical timescale. Further, we highlight several aspects of state-of-the-art confidence-scoring software that warrant reinvestigation given the analytical characteristics of the Orbitrap-Astral mass spectrometer through comparisons with an enrichment-based thresholding technique. With our data, we generated an interaction map between 998 human proteins and 59 viral proteins. These results hold promise in expediting the throughput of AP-MS experiments, enabling more high-powered PPI studies.
期刊介绍:
Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".