Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152046
Title: Streamlined MRM method transfer between instruments assisted with HRMS matching and retention-time prediction
Authors: Yang, J. J.
Han, Yuan
Mah, C. H.
Wanjaya, Elvy Riani
Peng, Brenda Ang Sze
Xu, Tengfei
Liu, Min
Huan, T.
Fang, Mingliang
Keywords: Engineering::Civil engineering
Issue Date: 2019
Source: Yang, J. J., Han, Y., Mah, C. H., Wanjaya, E. R., Peng, B. A. S., Xu, T., Liu, M., Huan, T. & Fang, M. (2019). Streamlined MRM method transfer between instruments assisted with HRMS matching and retention-time prediction. Analytica Chimica Acta, 1100, 88-96. https://dx.doi.org/10.1016/j.aca.2019.12.002
Project: M4011732.030
M4081915
M060030008
M4061617
Journal: Analytica Chimica Acta
Abstract: Multiple reaction monitoring (MRM) mode using liquid-chromatography tandem mass spectrometry (e.g., LC-QqQ-MS/MS) has been extensively employed in the small molecule analysis with trace levels in complex samples owing to its high sensitivity. However, most of the reported MRM methods are developed using authentic standards, which are often costly yet not readily available. To address this question, a practical platform for the MRM method transfer between different LC-QqQ-MS/MS instruments, assisted by the high-resolution mass spectrometry (LC-HRMS) and retention time (RT) prediction, has been developed in this study. The reported platform can take advantage of both the high sensitivity of LC-MRM method and ion transition pairs from the previous publications. LC-HRMS can provide the accurate mass measurement of the compounds, though high-quality MS/MS fragments are usually difficult to obtain for chemicals at trace levels. Retention time matching and peaks matching between both instrumental platforms rule out isobaric candidates. With an additional retention time prediction filter from quantitative structure retention relationship (QSRR) model based on random forest feature selection (Pearson r2 = 0.63), identification of small molecules is achieved at a high confidence level without using authentic standards. The developed platform has been validated with robustness by examining spiked environmental chemicals in sludge water samples, biological urine, and cell extracts.
URI: https://hdl.handle.net/10356/152046
ISSN: 0003-2670
DOI: 10.1016/j.aca.2019.12.002
Rights: © 2019 Elsevier B.V. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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