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Optimization of RP-LC-MS Top-down Protein Analysis on an Orbitrap Fusion Lumos Tribrid MS with the Advanced Peak Determination Algorithm

Reputable Mentor II
Reputable Mentor II
Vlad Zabrouskov1, Luca Fornelli2, Ryan Fellers2, Kristina Srzentic2, Joshua Silveira1, Helene Cardasis1, Graeme C. McAlister1, Christian Thoeing3, Derek Bailey1, Andreas Kuehn3, Mike Senko1, Shannon Eliuk1, Romain Huguet1, Neil Kelleher3
ASMS 2018
Purpose: Top-down data-dependent analysis workflows are typically plagued by repeated interrogation of different charge states of the same protein precursor. Through the development of an improved precursor charge state determination algorithm, we are able to better associate all the ions representing a single proteoform in real-time. This added information improves the data-dependent decisions we can make during the workflow, which in turn, maximizes the depth of analysis. We demonstrate here the impact of this new algorithm on top-down analysis using a Thermo Scientific™ Orbitrap Fusion™ Lumos™ Tribrid™ mass spectrometer. Methods: A commercial intact protein standard mixture and E.coli lysate were analyzed by top-down data-dependent analysis using a Thermo Scientific™ Vanquish™ UHPLC and an Orbitrap Fusion Lumos MS. Multiple parameter settings were evaluated using both the traditional precursor detection algorithm (SPD) and the newly developed Advanced Precursor Determination (APD) algorithm. Results: Data dependent parameters were optimized to minimize redundant sampling of each protein and to improve sampling depth in both the ‘low-high’ and the ‘high-high’ modes of operation. The APD algorithm has a significant impact on the system’s ability to make intelligent data-dependent decisions during top-down analysis, and represents a major step forward for top-down LC-MS analysis.

1 Thermo Fisher Scientific, San Jose, CA 2 Northwestern University, Evanston, IL 3 Thermo Fisher Scientific, Bremen, Germany
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Last update:
‎10-15-2021 06:09 AM
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