Identification of Novel Microcystins Using High-Resolution MS and MSn with Python Code

Baliu-Rodriguez, David; Peraino, Nicholas J.; Premathilaka, Sanduni H.; Birbeck, Johnna A.; Baliu-Rodriguez, Tomás; Westrick, Judy A.; Isailovic, Dragan

doi:10.1021/acs.est.1c04296

Title: Identification of Novel Microcystins Using High-Resolution MS and MSⁿ with Python Code

Journal Article · 11 January 2022 · Environmental Science and Technology

DOI: https://doi.org/10.1021/acs.est.1c04296 · OSTI ID:1876976

Baliu-Rodriguez, David ^[1]; Peraino, Nicholas J. ^[2]; Premathilaka, Sanduni H. ^[3]; Birbeck, Johnna A. ^[2]; Baliu-Rodriguez, Tomás ^[4]; Westrick, Judy A. ^[2];

^[3]

Univ. of Toledo, OH (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Wayne State Univ., Detroit, MI (United States)
Univ. of Toledo, OH (United States)
The Ohio State Univ., Columbus, OH (United States)

Cyanotoxins called microcystins (MCs) are highly toxic and can be present in drinking water sources. Determining the structure of MCs is paramount because of its effect on toxicity. Though over 300 MC congeners have been discovered, many remain unidentified. In this work, a method is described for the putative identification of MCs using liquid chromatography (LC) coupled with high-resolution (HR) Orbitrap mass spectrometry (MS) and a new bottom-up sequencing strategy. Maumee River water samples were collected during a harmful algal bloom and analyzed by LC–MS with simultaneous HRMS and MS/MS. Unidentified ions with characteristic MC fragments (135 and 213 m/z) were recognized as possible novel MC congeners. An innovative workflow was developed for the putative identification of these ions. Python code was written to generate the potential structures of unidentified MCs and to assign ions after the fragmentation for structural confirmation. The workflow enabled the putative identification of eight previously reported MCs for which standards are not available and two newly discovered congeners, MC-HarR and MC-E(OMe)R.

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Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); US Air Force Office of Scientific Research (AFOSR); National Institutes of Health (NIH); USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 1876976

Report Number(s):: LLNL-JRNL-834627; 1052936

Journal Information:: Environmental Science and Technology, Journal Name: Environmental Science and Technology Journal Issue: 3 Vol. 56; ISSN 0013-936X

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

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Title: Identification of Novel Microcystins Using High-Resolution MS and MSn with Python Code

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Title: Identification of Novel Microcystins Using High-Resolution MS and MSⁿ with Python Code