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Updated: Oct 19, 2025

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
Published on: March 14, 2013
Recent Developments Toward Integrated Metabolomics Technologies (UHPLC-MS-SPE-NMR and MicroED) for Higher-Throughput
Rajarshi Ghosh1,2,3,4, Guanhong Bu5,6, Brent L Nannenga5,6
1Division of Biochemistry, University of Missouri, Columbia, MO, United States.
Abstract:
Metabolomics has emerged as a powerful discipline to study complex biological systems from a small molecule perspective. The success of metabolomics hinges upon reliable annotations of spectral features obtained from MS and/or NMR. In spite of tremendous progress with regards to analytical instrumentation and computational tools, < 20% of spectral features are confidently identified in most untargeted metabolomics experiments. This article explores the integration of multiple analytical instruments such as UHPLC-MS/MS-SPE-NMR and the cryo-EM method MicroED to achieve large-scale and confident metabolite identifications in a higher-throughput manner. UHPLC-MS/MS-SPE allows for the simultaneous automated purification of metabolites followed by offline structure elucidation and structure validation by NMR and MicroED. Large-scale study of complex metabolomes such as that of the model plant legume Medicago truncatula can be achieved using an integrated UHPLC-MS/MS-SPE-NMR metabolomics platform. Additionally, recent developments in MicroED to study structures of small organic molecules have enabled faster, easier and precise structure determinations of metabolites. A MicroED small molecule structure elucidation workflow (e.g., crystal screening, sample preparation, data collection and data processing/structure determination) has been described. Ongoing MicroED methods development and its future scope related to structure elucidation of specialized metabolites and metabolomics are highlighted. The incorporation of MicroED with a UHPLC-MS/MS-SPE-NMR instrumental ensemble offers the potential to accelerate and achieve higher rates of metabolite identification.
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