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

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.