Aaron O Bailey, Kenneth R Durbin, Matthew T Robey, Lee K Palmer, William K Russell
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引用次数: 0
Abstract
Liquid chromatography-mass spectrometry (LC-MS) intact mass analysis and LC-MS/MS peptide mapping are decisional assays for developing biological drugs and other commercial protein products. Certain PTM types, such as truncation and oxidation, increase the difficulty of precise proteoform characterization owing to inherent limitations in peptide and intact protein analyses. Top-down MS (TDMS) can resolve this ambiguity via fragmentation of specific proteoforms. We leveraged the strengths of flow-programmed (fp) denaturing online buffer exchange (dOBE) chromatography, including robust automation, relatively high ESI sensitivity, and long MS/MS window time, to support a TDMS platform for industrial protein characterization. We tested data-dependent (DDA) and targeted strategies using 14 different MS/MS scan types featuring combinations of collisional- and electron-based fragmentation as well as proton transfer charge reduction. This large, focused dataset was processed using a new software platform, named TDAcquireX, that improves proteoform characterization through TDMS data aggregation. A DDA-based workflow provided objective identification of αLac truncation proteoforms with a two-termini clipping search. A targeted TDMS workflow facilitated the characterization of αLac oxidation positional isomers. This strategy relied on using sliding window-based fragment ion deconvolution to generate composite proteoform spectral match (cPrSM) results amenable to fragment noise filtering, which is a fundamental enhancement relevant to TDMS applications generally.
期刊介绍:
PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.