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Upscaling of spectral libraries for HR- EI-MS based non target analytics

  • Non-target (NT) mass spectrometry techniques play a crucial role in metabolomics applications, particularly in areas such as environmental safety. Soft ionization methods, such as electrospray ionization (ESI), are commonly employed due to their ability to generate spectra containing molecular ions, aiding in the identification of unknown peaks. However, ESI may fail to ionize certain compounds effectively, resulting in their absence in NT approaches. In contrast, hard ionization methods like electron impact (EI) can ionize a wide range of compounds but often lack information about the molecular ion. Although extensive databases of EI spectra exist, their nominal mass resolution (NR) limits their utility for modern high-resolution (HR) EI mass spectrometers. Here, the often-applied conversion of HR spectra to nominal mass leads to the loss of unique characteristics, i.e. by grouping distinct masses into more ambiguous nominal masses. Our study aims to (i) quantify the negative impactNon-target (NT) mass spectrometry techniques play a crucial role in metabolomics applications, particularly in areas such as environmental safety. Soft ionization methods, such as electrospray ionization (ESI), are commonly employed due to their ability to generate spectra containing molecular ions, aiding in the identification of unknown peaks. However, ESI may fail to ionize certain compounds effectively, resulting in their absence in NT approaches. In contrast, hard ionization methods like electron impact (EI) can ionize a wide range of compounds but often lack information about the molecular ion. Although extensive databases of EI spectra exist, their nominal mass resolution (NR) limits their utility for modern high-resolution (HR) EI mass spectrometers. Here, the often-applied conversion of HR spectra to nominal mass leads to the loss of unique characteristics, i.e. by grouping distinct masses into more ambiguous nominal masses. Our study aims to (i) quantify the negative impact of such a binning approach and (ii) develop a machine learning (ML) tool capable of enhancing existing nominal mass spectral libraries. In the initial phase, we employed the RECETOX Exposome HR-[EI+]-MS library to assess the influence of HR spectra on identification. We compared the dot product of each spectrum against all others, utilizing bin sizes of 0.001 and 1 Da. The difference in dot product between the second-best candidate and the query spectrum (the best candidate, with a score of 1) was calculated for both HR and nominal mass spectra. Subsequently, we explored the application of ML techniques to predict HR spectra from nominal mass spectra using the before mentioned dataset. Preliminary findings demonstrate the potential of high-resolution spectral libraries. As anticipated, HR spectra consistently exhibited lower similarity scores for the second candidate. This observation likely stems from the high redundancy and resulting ambiguity associated with nominal masses. Even after eliminating spectra containing multiple HR masses mapped to the same nominal mass, the aforementioned trend persisted. Furthermore, initial investigations into ML have revealed its ability to predict up to 40% of HR masses within a 10 mDa precision window.zeige mehrzeige weniger

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Metadaten
Autor*innen:Francesco Friedrich Russo
Koautor*innen:Jan LisecORCiD
Dokumenttyp:Posterpräsentation
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2023
Organisationseinheit der BAM:1 Analytische Chemie; Referenzmaterialien
1 Analytische Chemie; Referenzmaterialien / 1.7 Organische Spuren- und Lebensmittelanalytik
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Freie Schlagwörter:HR-EI-MS; ML
Themenfelder/Aktivitätsfelder der BAM:Chemie und Prozesstechnik
Veranstaltung:Tag der Chemie 2023
Veranstaltungsort:Berlin, Deutschland
Beginndatum der Veranstaltung:05.07.2023
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:08.09.2023
Referierte Publikation:Nein
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