Active Instrument Engagement Combined with a Real-Time Database Search for Improved Performance of Sample Multiplexing Workflows.

Autor: Erickson BK; Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States., Mintseris J; Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States., Schweppe DK; Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States., Navarrete-Perea J; Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States., Erickson AR; Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States., Nusinow DP; Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States., Paulo JA; Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States., Gygi SP; Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States.
Jazyk: angličtina
Zdroj: Journal of proteome research [J Proteome Res] 2019 Mar 01; Vol. 18 (3), pp. 1299-1306. Date of Electronic Publication: 2019 Feb 04.
DOI: 10.1021/acs.jproteome.8b00899
Abstrakt: Quantitative proteomics employing isobaric reagents has been established as a powerful tool for biological discovery. Current workflows often utilize a dedicated quantitative spectrum to improve quantitative accuracy and precision. A consequence of this approach is a dramatic reduction in the spectral acquisition rate, which necessitates the use of additional instrument time to achieve comprehensive proteomic depth. This work assesses the performance and benefits of online and real-time spectral identification in quantitative multiplexed workflows. A Real-Time Search (RTS) algorithm was implemented to identify fragment spectra within milliseconds as they are acquired using a probabilistic score and to trigger quantitative spectra only upon confident peptide identification. The RTS-MS 3 was benchmarked against standard workflows using a complex two-proteome model of interference and a targeted 10-plex comparison of kinase abundance profiles. Applying the RTS-MS 3 method provided the comprehensive characterization of a 10-plex proteome in 50% less acquisition time. These data indicate that the RTS-MS 3 approach provides dramatic performance improvements for quantitative multiplexed experiments.
Databáze: MEDLINE
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