MetAnalyzer: Automated Untargeted Metabolomics Data Analysis with Experimental MS/MS Spectral Library

Brief introduction: Untargeted metabolomics has the potential to implicate unexpected pathways with a unique phenotype or disease process. However, the major bottleneck of untargeted metabolomics has been the challenge of determining the identities of the peaks found to be dysregulated in the untargeted profiling data. Currently, identifying metabolites in LC-MS based metabolomics experiments solely relies on high resolution MS data. The problem with this approach is that there may be several molecular formulas that are appropriate for the accurate mass data (depending on the resolution of the instrument), and numerous potential isomers for each molecular formula.Here, we demonstrated to utilize high resolution precursor ion (MS) and tandem mass spectral (MS/MS) fragmentation data to identify metabolites. Integral to this approach is high resolution precursor data, which narrows down potential molecular formulas, and high resolution fragmentation data, which allows for accurate classification by identification of neutral losses and fragment ions. Matching the accurate mass and fragmentation data with standard MS/MS spectra in database provides a more convincing identification than accurate mass alone.In Dr. Zhu lab, we develop MetAnalyzer program tointegrate the metabolite quantitative analysis and structure elucidate all together as an automated untargeted metabolomics data analysis workflow. The metabolite MS/MS spectral library is in-house ZhuMetLib spectral library, now containing standard spectra for ~1500 metabolites.

Availability of MetAnalyzer: Not available for public use before publication.

ZhuMetLib: An In-house, Standard MS/MS Spectral Library for Untargeted Metabolomics

Brief introduction: ZhuMetLib is a metabolite tandem spectral library with ~1500 metabolites. Most of these metabolites are polar compounds, and purchased from commercial vendors (like Sigma, J&K Scientific). Experimentally, we acquired the MS/MS spectral for each metabolite using AB Sciex TripleTOF 5600/6600 Q-TOF system with 14 different levels of CE energy, from 10 eV to 70 eV with an interval of 5 eV. An additional ramped CE energy level 35+/-15 eV is also acquired. Then these acquired MS/MS data for chemical standards were submitted to generate consensus spectra following the protocol in previous publication (with slight modifications in our lab). Finally, each of the spectrum is manually checked by at least two well-trained mass spectrometrists in the lab. Currently, ZhuMetLib is used for automated metabolite identification with our in-house program MetAnalyzer.