Met4DX: A Mass Spectrum-oriented Computational Method for Ion Mobility-resolved Untargeted Metabolomics
Introduction: Ion mobility (IM) adds a new dimension to liquid chromatography-mass spectrometry-based untargeted metabolomics which significantly enhances coverage, sensitivity, and resolving power for analyzing the metabolome, particularly metabolite isomers. However, the high dimensionality of IM-resolved metabolomics data presents a great challenge to data processing, restricting its widespread applications. Here, we develop a mass spectrum-oriented bottom-up assembly algorithm for IM-resolved metabolomics that utilizes mass spectra to assemble four-dimensional peaks in a reverse order of multidimensional separation. We further develop the end-to-end computational framework Met4DX for peak detection, quantification and identification of metabolites in IM-resolved metabolomics. Benchmarking and validation of Met4DX demonstrates superior performance compared to existing tools with regard to coverage, sensitivity, peak fidelity and quantification precision. Importantly, Met4DX successfully detects and differentiates co-eluted metabolite isomers with small differences in the chromatographic and IM dimensions. Together, Met4DX advances metabolite discovery in biological organisms by deciphering the complex 4D metabolomics data.
With our further developments, Met4DX has evolved into a fast, robust, and convenient mass spectrometry data processing tool for metabolomics and lipidomics. The versatile tool facilitates the processing of both 3-dimensional LC-MS data and 4-dimensional LC-IM-MS data, encompassing main functions such as data conversion, peak detection, retention time correction, peak grouping, assignment of MS/MS spectra, metabolite identification and others. Met4DX is freely available at our website.
Web Link of Met4DX: http://met4dx.zhulab.cn/
Publications：
M. Luo, Y. Yin, Z. Zhou, H. Zhang, X. Chen, H. Wang, and Z.-J. Zhu*, A Mass Spectrum-oriented Computational Method for Ion Mobility-resolved Untargeted Metabolomics, Nature Communications, 2023, 14: 1813. Web Link
