Development and comparison of formula assignment algorithms for ultrahigh-resolution mass spectra of natural organic matter

Qing-Long Fu; Manabu Fujii; Thomas Riedel

doi:10.1016/j.aca.2020.05.048

Development and comparison of formula assignment algorithms for ultrahigh-resolution mass spectra of natural organic matter

Anal Chim Acta. 2020 Aug 15:1125:247-257. doi: 10.1016/j.aca.2020.05.048. Epub 2020 May 24.

Authors

Qing-Long Fu¹, Manabu Fujii², Thomas Riedel³

Affiliations

¹ Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Ookayama, Tokyo, Japan.
² Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Ookayama, Tokyo, Japan. Electronic address: fujii.m.ah@m.titech.ac.jp.
³ IWW Water Centre, Moritzstr. 26, 45476, Mülheim an der Ruhr, Germany.

PMID: 32674771
DOI: 10.1016/j.aca.2020.05.048

Abstract

Increasing number of application of ultrahigh-resolution mass spectrometry (UHR-MS) to natural organic matter (NOM) characterization requires an efficient and accurate formula assignment from a number of mass data. Herein, we newly developed two automated batch codes (namely TRFu and FuJHA) and assessed their formula assignment accuracy together with frequently used open access algorithms (i.e., Formularity and WHOI). Overall assignment accuracy for 8719 NOM-like emerging chemicals with known molecular formulae (mass range from 68 Da to 1000 Da) was highest (94%) for TRFu. Further, TRFu showed up to 99.1% formula assignment ratio for a total 76,880 UHR-MS peaks from 35 types of NOM (e.g., aquatic, soil/sediment, biochar). Therefore, as a reliable and practically feasible tool, the automated batch TRFu (freely available at ChemRxiv, https://doi.org/10.26434/chemrxiv.9917399) can precisely characterize UHR-MS spectra of various NOM and could be extended to non-target screening of NOM-like emerging chemicals in natural and engineered environments.

Keywords: Dissolved organic matter; FT-ICR-MS; Formula assignment algorithms; Orbitrap MS; TRFu code.