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BiochemistrybioRxiv
Preprint

Benchmarking the Performance of a Commercial Electrostatic Linear Ion Trap (ELIT) Charge Detection Mass Spectrometer For Higher-Order Antibody Aggregate Analysis

Shang-Yin WuiD, Xing-Miao Guo, Jia-Yi LviD, Yingzi LiiD, Lei Gu, Zachary Tian, Yongsheng Xiao, Emily Christofi, Anisha HarisiD, Haoyun Lu, Rui WangiD, Huan-Fang Xie, Hongwen Li, Pan YuanjiangiD, Mowei ZhouiD, Wei‐Jie FangiD

Abstract

Higher-order antibody aggregates remain challenging to characterize using conventional mass spectrometry because of their low abundance, broad mass distributions, and extensive heterogeneity. Here, the practical performance of a commercial electrostatic linear ion trap charge detection mass spectrometer (XevoTM CDMS) was evaluated for therapeutic antibody analysis. The platform provided reproducible mass and charge measurements, with repeatability and intermediate-precision RSDs below 1%, and maintained consistent mass determination across the concentration and solution conditions examined. Controlled mixtures of antibody-derived species showed a linear molar-ratio-dependent ion response, supporting semi-quantitative estimation of relative species abundance under defined conditions. For heat-stressed trastuzumab, CDMS measurements were qualitatively consistent with SEC-MALS, mass photometry, and conventional native MS, while enabling direct mass determination of individual ions within highly heterogeneous high-molecular-weight (HMW) populations that exhibited extensive charge-state overlap and could not be reliably deconvoluted by conventional native MS. High-duty-cycle acquisition increased sampling of low-abundance, high-m/z ions and improved access to higher-order aggregate signals. Joint single ion mass-charge analysis further differentiated statistical ion families within the broad HMW fraction and related major mass differences to independently obtained compositional information. These results support commercial XevoTM CDMS as a practical multidimensional platform for antibody aggregate characterization.

PDFDOI

02 /Specification & Classification

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