Creating a Reliable Mass Spectral–Retention Time Library for All Ion Fragmentation-Based Metabolomics

Abstract

Accurate metabolite identification remains one of the primary challenges in a metabolomics study. A reliable chemical spectral library increases the confidence in annotation, and the availability of raw and annotated data in public databases facilitates the transfer of Liquid chromatography coupled to mass spectrometry (LC–MS) methods across laboratories. Here, we illustrate how the combination of MS2 spectra, accurate mass, and retention time can improve the confidence of annotation and provide techniques to create a reliable library for all ion fragmentation (AIF) data with a focus on the characterization of the retention time. The resulting spectral library incorporates information on adducts and in-source fragmentation in AIF data, while noise peaks are effectively minimized through multiple deconvolution processes. We also report the development of the Mass Spectral LIbrary MAnager (MS-LIMA) tool to accelerate library sharing and transfer across laboratories. This library construction strategy improves the confidence in annotation for AIF data in LC–MS-based metabolomics and will facilitate the sharing of retention time and mass spectral data in the metabolomics community.

Comparative Evaluation of Data Dependent and Data Independent Acquisition Workflows Implemented on an Orbitrap Fusion for Untargeted Metabolomics

“…Due to the width of isolation windows, the direct link between a specific precursor ion and its corresponding fragments is often lost, which renders MS/MS data interpretation of unknown metabolites much more difficult than that of MS/MS data resulting from DDA protocols. All-Ion Fragmentation (AIF) is another form of DIA acquisition that has been successfully applied to metabolomics or lipidomic approaches [21][22][23]. The present paper dealing only with SWATH-like DIA as applied to low-mass metabolites (essentially below 700 Da), DIA accounts hereafter for SWATH-like approaches.…”

Untargeted LC-MS Metabolomics for the Analysis of Micro-scaled Extracellular Metabolites from Hepatocytes

“…Injection volume was 1 µL (injection sequence Table S2). The LC-MS method was described in previous publications [16][17][18] . Briefly, metabolite separation was performed on an Agilent 1290 Infinity II system using SeQuant ZIC-HILIC (Merck, Darmstadt, Germany) column.…”

Untargeted LC-MS metabolomics for the analysis of micro-scaled extracellular metabolites fromhepatocytes

“…Injection volume was 1 μL (injection sequence Table S2). The LC-MS method is described in previous publications [14][15][16] . Briefly, metabolite separation was Tables S3 and S4).…”

“…Briefly, metabolite separation was Tables S3 and S4). An in-house MS2 spectral library containing experimental MS2 spectra and retention times (RT) for 391 compounds obtained from standards 14,16 was used for annotation of detected features using three criteria: (i) accurate mass (AM) match (tolerance: 0.01 Da), (ii) RT match (tolerance: 1 min), and (iii) MS2 spectrum match (similarity >70%). The MS2 similarity was scored by the simple dot product without any weighting (at least two MS2 peaks match with the reference spectra).…”