MassIVE MSV000095009

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Filling the Gaps in Peptide Maps with a Platform Assay for Top-Down Characterization of Purified Protein Samples

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Description

LC-MS intact mass analysis and LC-MS/MS peptide mapping are foundational assays for developing biologic 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 optimized our existing flow-programmed (fp) denaturing online buffer exchange (dOBE) approach to improve ESI sensitivity and increase TDMS sampling time for industrial applications. Using bovine alpha-lactalbumin (aLac), we tested data-dependent (DDA) and targeted strategies with 14 different MS/MS scan types featuring combinations of collisional- and electron-based fragmentation as well as proton transfer charge reduction. This large dataset was processed using a new software platform, named TDAcquireX, that improves proteoform characterization through TDMS data aggregation. A DDA-based (fp)dOBE-TDMS workflow provided high confidence identification of aLac truncation proteoforms. Targeted TDMS data were analyzed using sliding window-based fragment ion deconvolution to generate composite proteoform spectral match (cPrSM) results. This strategy facilitated probability-based noise filtering of deconvoluted fragment results, simultaneously increasing the percentage of matched fragments while decreasing the total number of fragments reported. We used fragment noise filtering to characterize aLac oxidation positional isomers, finding that electron transfer dissociation (ETD) uniquely provided accurate relative occupancy data as a result of oxidation-specific technical challenges. [doi:10.25345/C51V5BR29] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: top-down ; TDMS ; protein characterization ; biopharma ; truncation ; clipping ; charge reduction ; PTCR ; positional isomer

Contact

Principal Investigators:
(in alphabetical order) 		Aaron O. Bailey, AbCellera Biologics, Inc., Canada
Submitting User: aobailey
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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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