A software tool, MS-DIAL, enables the identification of metabolomes by data independent acquisition–based mass spectrometry. Data-independent acquisition (DIA) in liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) provides comprehensive untargeted acquisition of molecular data. We provide an open-source software pipeline, which we call MS-DIAL, for DIA-based identification and quantification of small molecules by mass spectral deconvolution. For a reversed-phase LC-MS/MS analysis of nine algal strains, MS-DIAL using an enriched LipidBlast library identified 1,023 lipid compounds, highlighting the chemotaxonomic relationships between the algal strains.

Structure elucidation of unknown small molecules by mass spectrometry is a challenge despite advances in instrumentation. The first crucial step is to obtain correct elemental compositions. In order to automatically constrain the thousands of possible candidate structures, rules need to be developed to select the most likely and chemically correct molecular formulas.

Lipid Blast is an in silico–generated tandem mass spectral library covering more than 119,000 lipid compounds from 26 different classes, providing a useful tool for lipid identification in metabolomics studies. Current tandem mass spectral libraries for lipid annotations in metabolomics are limited in size and diversity. We provide a freely available computer-generated tandem mass spectral library of 212,516 spectra covering 119,200 compounds from 26 lipid compound classes, including phospholipids, glycerolipids, bacterial lipoglycans and plant glycolipids. We show platform independence by using tandem mass spectra from 40 different mass spectrometer types including low-resolution and high-resolution instruments.

Gas chromatography–mass spectrometry (GC‐MS)–based metabolomics is ideal for identifying and quantitating small‐molecule metabolites (<650 Da), including small acids, alcohols, hydroxyl acids, amino acids, sugars, fatty acids, sterols, catecholamines, drugs, and toxins, often using chemical derivatization to make these compounds sufficiently volatile for gas chromatography. This unit shows how GC‐MS‐based metabolomics allows integration of targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds. Complemented by database annotations using large spectral libraries and validated standard operating procedures, GC‐MS can identify and semiquantify over 200 compounds from human body fluids (e.g., plasma, urine, or stool) per study. Deconvolution software enables detection of more than 300 additional unidentified signals that can be annotated through accurate mass instruments with appropriate data processing workflows, similar to untargeted profiling using liquid chromatography–mass spectrometry. GC‐MS is a mature technology that uses not only classic detectors (quadrupole) but also target mass spectrometers (triple quadrupole) and accurate mass instruments (quadrupole–time of flight). This unit covers sample preparation from mammalian samples, data acquisition, quality control, and data processing. © 2016 by John Wiley & Sons, Inc.