Evaluation of Ion Mobility Spectrometry for Improving Constitutional Assignment in Natural Product Mixtures

The comprehensive chemical characterization of biological samples remains a central challenge in the field of natural products. Conventional workflows using liquid chromatography (LC)-coupled high-resolution tandem mass spectrometry (MS/MS or MS2) allow the detection of relevant small molecules whil...

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Bibliographic Details
Published in:Journal of natural products (Washington, D.C.) D.C.), 2022-03, Vol.85 (3), p.519-529
Main Authors: Carnevale Neto, Fausto, Clark, Trevor N, Lopes, Norberto P, Linington, Roger G
Format: Article
Language:English
Subjects:
Biological Products
Cross-Sectional Studies
Ion Mobility Spectrometry
Plant Extracts
Tandem Mass Spectrometry
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Summary:The comprehensive chemical characterization of biological samples remains a central challenge in the field of natural products. Conventional workflows using liquid chromatography (LC)-coupled high-resolution tandem mass spectrometry (MS/MS or MS2) allow the detection of relevant small molecules while providing diagnostic fragment ions for their structural assignment. Still, many natural product extracts are of a molecular complexity that challenges the resolving power of modern LC–MS2 pipelines. In this study, we examined the effect of integrating ion mobility spectrometry (IMS) to our LC–MS2 platform for the characterization of natural product mixtures. IMS provides an additional axis of separation in the gas phase as well as experimental collision cross-sectional (CCS) values. We analyzed a mixture of 20 commercial standards at 2 concentration ranges, either solubilized in solvent or spiked into an actinobacterial extract. Data were acquired in positive ion mode using both data-dependent acquisition (DDA) and data-independent acquisition (DIA) MS2 fragmentation approaches and assessed for both chemical coverage and spectral quality. IMS-DIA identified the largest number of standards in the spiked extract at the lower concentration of standards (17), followed by IMS-DDA (10), DDA (8), and DIA (6). In addition, we examined how these data sets performed in the Global Natural Products Social Molecular Networking (GNPS) platform. Overall, integrating IMS increased both metabolite detection and the quality of MS2 spectra, particularly for samples analyzed in DIA mode.
ISSN:0163-3864
1520-6025
DOI:10.1021/acs.jnatprod.1c01048