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Supporting Non-Target Identification by Adding Hydrogen Deuterium Exchange MS/MS Capabilities to MetFrag
Ruttkies, C., E. Schymanski, N. Strehmel, J. Hollender, S. Neumann, A. Williams, AND M. Krauss. Supporting Non-Target Identification by Adding Hydrogen Deuterium Exchange MS/MS Capabilities to MetFrag. Analytical and Bioanalytical Chemistry. Springer, New York, NY, 411(19):4683, (4700). https://doi.org/10.1007/s00216-019-01885-0
The identification of unknown chemicals in complex samples via non-target screening with liquid chromatographic (LC) separation followed by high resolution (HR) mass spectrometric (MS) analysis remains challenging due to the vast chemical space and still relatively limited coverage of spectra in reference libraries. While techniques such as nuclear magnetic resonance (NMR) spectroscopy yield rich structural information and are well-suited for structure elucidation, NMR is often unachievable with the low concentrations available in complex samples. In LC-HR-MS, information about structural properties is obtained by fragmenting detected substances to yield MS/MS spectra. The resulting spectra can then be compared to spectral libraries, or interpreted by software using in silico fragmentation approaches. Unlike NMR, however, the MS/MS spectra typical in LC-HR-MS/MS are often information-poor. Thus, alternative ways of obtaining additional structural information are needed for non-target identification methods reliant on LC-HRMS. While techniques such as direct labelling experiments can be used in metabolomics experiments to gain additional information [3, 4], this is impractical in the context of most real complex samples, e.g. environmental samples. The aim of this study was to investigate how hydrogen-deuterium exchange experiments could assist structural elucidation in non-targeted HR-MS experiments using high-throughput or automated in silico fragmentation techniques. The in silico fragmenter MetFrag was modified to include additional scoring terms to account for the HDX on small datasets starting with the theory discussed above. Once the method was established it was tested on a set of several mixtures of chemicals containing 762 unique compounds and analyzed in both positive and negative mode. Following this, HDX experiments were performed on a water sample from the river Danube near Novi Sad (Serbia) to assess the feasibility of applying HDX experiments in the context of a real complex water sample.
Liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) is increasingly popular for the non-targeted exploration of complex samples, where tandem mass spectrometry (MS/MS) is used to characterize the structure of unknown compounds. However, mass spectra do not always contain sufficient information to unequivocally identify the correct structure. Additional information can be gained using hydrogen deuterium exchange (HDX) experiments. The exchange of “easily exchangeable" Hs (connected to heteroatoms), with predominantly [M+D]+ ions in positive mode and [M-D]- in negative mode was observed. To enable high throughput processing, new scoring terms were incorporated into the in silico fragmenter MetFrag. These were initially developed on small datasets and then tested on 762 substances of environmental interest. Pairs of spectra (normal and deuterated) were found for 593 of these substances (506 positive mode, 155 negative mode spectra). The new scoring terms resulted in 29 additional correct identifications (78 vs 49). Compounds with dual functionality (polar head group, long apolar tail) exhibited dramatic retention time shifts. The results of standard measurements were confirmed using targets and tentatively-identified surfactant species in an environmental sample collected from the river Danube near Novi Sad (Serbia). The changes to MetFrag have been integrated into the command line version available at http://c-ruttkies.github.io/MetFrag and all resulting spectra and compounds are available on MassBank and the CompTox Chemicals Dashboard. The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the U.S. EPA.
Record Details:Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL CENTER FOR COMPUTATIONAL TOXICOLOGY