Metabolomics and lipidomics aim to profile the wide range of metabolites and lipids that are present in biological samples. Recently, ion mobility spectrometry (IMS) has been used to support metabolomics and lipidomics applications to facilitate the separation and the identification of complex mixtures of analytes. IMS is a gas-phase electrophoretic technique that enables the separation of ions in the gas phase according to their charge, shape and size. Occurring within milliseconds, IMS separation is compatible with modern mass spectrometry (MS) operating with microsecond scan speeds. Thus, the time required for acquiring IMS data does not affect the overall run time of traditional liquid chromatography (LC)-MS-based metabolomics and lipidomics experiments. The addition of IMS to conventional LC-MS-based metabolomics and lipidomics workflows has been shown to enhance peak capacity, spectral clarity and fragmentation specificity. Moreover, by enabling determination of a collision cross-section (CCS) value—a parameter related to the shape of ions—IMS can improve the accuracy of metabolite identification. In this protocol, we describe how to integrate traveling-wave ion mobility spectrometry (TWIMS) into traditional LC-MS-based metabolomic and lipidomic workflows. In particular, we describe procedures for the following: tuning and calibrating a SYNAPT High-Definition MS (HDMS) System (Waters) specifically for metabolomics and lipidomics applications; extracting polar metabolites and lipids from brain samples; setting up appropriate chromatographic conditions; acquiring simultaneously m/z, retention time and CCS values for each analyte; processing and analyzing data using dedicated software solutions, such as Progenesis QI (Nonlinear Dynamics); and, finally, performing metabolite and lipid identification using CCS databases and TWIMS-derived fragmentation information.