The potential of Ion Mobility Mass Spectrometry for high-throughput and high-resolution lipidomics

Fast and broad-coverage lipidomics enabled by ion mobility-mass spectrometry

Aberrant lipid metabolism has been widely recognized as a hallmark of various diseases. However, the comprehensive analysis of distinct lipids is challenging due to the complexity of lipid molecular structures, wide concentration ranges, and numerous isobaric and isomeric lipids. Usually, liquid chromatography-mass spectrometry (LC-MS)-based lipidomics requires a long time for chromatographic separation to achieve optimal separation and selectivity. Ion mobility (IM) adds a new separation dimension to LC-MS, significantly enhancing the coverage, sensitivity, and resolving power. We took advantage of the rapid separation provided by ion mobility and optimized a fast and broad-coverage lipidomics method using the LC-IM-MS technology. The method required only 8 minutes for separation and detected over 1000 lipid molecules in a single analysis of common biological samples. The high reproducibility and accurate quantification of this high-throughput lipidomics method were systematically characterized. We then applied the method to comprehensively measure dysregulated lipid metabolism in patients with colorectal cancer (CRC). Our results revealed 115 significantly changed lipid species between preoperative and postoperative plasma of patients with CRC and also disclosed associated differences in lipid classes such as phosphatidylcholines (PC), sphingomyelins (SM), and triglycerides (TG) regarding carbon number and double bond. Together, a fast and broad-coverage lipidomics method was developed using ion mobility-mass spectrometry. This method is feasible for large-scale clinical lipidomic studies, as it effectively balances the requirements of high-throughput and broad-coverage in clinical studies.

Hyphenation of supercritical fluid chromatography and trapped ion mobility-mass spectrometry for quantitative lipidomics

BACKGROUND

Lipidomics studies require rapid separations with accurate and reliable quantification results to further elucidate the role of lipids in biological processes and their biological functions. Supercritical fluid chromatography (SFC), in particular, can provide this rapid and high-resolution separation. The combination with trapped ion mobility spectrometry (TIMS) has not yet been applied, although the post-ionization separation method in combination with liquid chromatography or imaging techniques has already proven itself in resolving isomeric and isobaric lipids and preventing false identifications. However, a multidimensional separation method should not only allow confident identification but also provide quantitative results to substantiate studies with absolute concentrations.

RESULTS

A SFC method was developed and the hyphenation of SFC and TIMS was further explored towards the separation of different isobaric overlaps. Furthermore, lipid identification was performed using mass spectrometry (MS) and parallel accumulation serial fragmentation (PASEF) MS/MS experiments in addition to retention time and collision cross section (CCS). Quantification was further investigated with short TIMS ramps and performed based on the ion mobility signal of lipids, since TIMS increases the sensitivity by noise filtering. The final method was, as an exemplary study, applied to investigate the function of different ceramide synthases (CerS) in the nematode and model organism Caenorhabditis elegans (C. elegans). Loss of three known CerS hyl-1, hyl-2 and lagr-1 demonstrated different influences on and alterations in the sphingolipidome.

SIGNIFICANCE

This method describes for the first time the combination of SFC and TIMS-MS/MS, which enables a fast and sensitive quantification of lipids. The results of the application to C. elegans samples prove the functionality of the method and support research on the metabolism of sphingolipids in nematodes.

Spatially and temporally probing distinctive glycerophospholipid alterations in Alzheimer's disease mouse brain via high-resolution ion mobility-enabled sn-position resolved lipidomics

Dysregulated glycerophospholipid (GP) metabolism in the brain is associated with the progression of neurodegenerative diseases including Alzheimer's disease (AD). Routine liquid chromatography-mass spectrometry (LC-MS)-based large-scale lipidomic methods often fail to elucidate subtle yet important structural features such as sn-position, hindering the precise interrogation of GP molecules. Leveraging high-resolution demultiplexing (HRdm) ion mobility spectrometry (IMS), we develop a four-dimensional (4D) lipidomic strategy to resolve GP sn-position isomers. We further construct a comprehensive experimental 4D GP database of 498 GPs identified from the mouse brain and an in-depth extended 4D library of 2500 GPs predicted by machine learning, enabling automated profiling of GPs with detailed acyl chain sn-position assignment. Analyzing three mouse brain regions (hippocampus, cerebellum, and cortex), we successfully identify a total of 592 GPs including 130 pairs of sn-position isomers. Further temporal GPs analysis in the three functional brain regions illustrates their metabolic alterations in AD progression.

Arachidonic acid inhibition of the NLRP3 inflammasome is a mechanism to explain the anti-inflammatory effects of fasting

Elevated interleukin (IL)-1β levels, NLRP3 inflammasome activity, and systemic inflammation are hallmarks of chronic metabolic inflammatory syndromes, but the mechanistic basis for this is unclear. Here, we show that levels of plasma IL-1β are lower in fasting compared to fed subjects, while the lipid arachidonic acid (AA) is elevated. Lipid profiling of NLRP3-stimulated mouse macrophages shows enhanced AA production and an NLRP3-dependent eicosanoid signature. Inhibition of cyclooxygenase by nonsteroidal anti-inflammatory drugs decreases eicosanoid, but not AA, production. It also reduces both IL-1β and IL-18 production in response to NLRP3 activation. AA inhibits NLRP3 inflammasome activity in human and mouse macrophages. Mechanistically, AA inhibits phospholipase C activity to reduce JNK1 stimulation and hence NLRP3 activity. These data show that AA is an important physiological regulator of the NLRP3 inflammasome and explains why fasting reduces systemic inflammation and also suggests a mechanism to explain how nonsteroidal anti-inflammatory drugs work.

Accumulation of Large Ion Populations with High Ion Densities and Effects Due to Space Charge in Traveling Wave-Based Structures for Lossless Ion Manipulations (SLIM) IMS-MS

The accumulation of very large ion populations in traveling wave (TW)-based Structures for Lossless ion Manipulations (SLIM) has been studied to better understand aspects of "in-SLIM" ion accumulation, and particularly its use in conjunction with ion mobility spectrometry (IMS). A linear SLIM ion path was implemented that had a "gate" for blocking and accumulating ions for arbitrary time periods. Removing the gate potential caused ions to exit, and the spatial distributions of accumulated ions examined. The ion populations for a set of peptides increased approximately linearly with increased accumulation times until space change effects became significant, after which the peptide precursor ion populations decreased due to growing space charge-related ion activation, reactions, and losses. Ion activation increased with added storage times and the TW amplitude. Lower amplitude TWs in the accumulation/storage region prevented or minimized ion losses or ion heating effects that can also lead to fragmentation. Our results supported the use of an accumulation region close to the SLIM entrance for speeding accumulation, minimizing ion heating, and avoiding ion population profiles that result in IMS peak tailing. Importantly, space charge-driven separations were observed for large populations of accumulated species and attributed to the opposing effects of space charge and the TW. In these separations, ion species form distributions or peaks, sometimes moving against the TW, and are ordered in the SLIM based on their mobilities. Only the highest mobility ions located closest to the gate in the trapped ion population (and where the highest ion densities were achieved) were significantly activated. The observed separations may offer utility for ion prefractionation of ions and increasing the dynamic range measurements, increasing the resolving power of IMS separations by decreasing peak widths for accumulated ion populations, and other purposes benefiting from separations of extremely large ion populations.

Sub-5-min RP-UHPLC-TIMS for high-throughput untargeted lipidomics and its application to multiple matrices

Untargeted lipidomics, with its ability to take a snapshot of the lipidome landscape, is an important tool to highlight lipid changes in pathology or drug treatment models. One of the shortcomings of most untargeted lipidomics based on UHPLC-HRMS is the low throughput, which is not compatible with large-scale screening. In this contribution, we evaluate the application of a sub-5-min high-throughput four-dimensional trapped ion mobility mass spectrometry (HT-4D-TIMS) platform for the fast profiling of multiple complex biological matrices. Human AC-16 cells and mouse brain, liver, sclera, and feces were used as samples. By using a fast 4-min RP gradient, the implementation of TIMS allows us to differentiate coeluting isomeric and isobaric lipids, with correct precursor ion isolation, avoiding co-fragmentation and chimeric MS/MS spectra. Globally, the HT-4D-TIMS allowed us to annotate 1910 different lipid species, 1308 at the molecular level and 602 at the sum composition level, covering 58 lipid subclasses, together with quantitation capability covering more than three orders of magnitude. Notably, TIMS values were highly comparable with respect to longer LC gradients (CV% = 0.39%). These results highlight how HT-4D-TIMS-based untargeted lipidomics possess high coverage and accuracy, halving the analysis time with respect to conventional UHPLC methods, and can be used for fast and accurate untargeted analysis of complex matrices to rapidly evaluate changes of lipid metabolism in disease models or drug discovery campaigns.

Lipid metabolism analysis in esophageal cancer and associated drug discovery

Esophageal cancer is an upper gastrointestinal malignancy with a bleak prognosis. It is still being explored in depth due to its complex molecular mechanisms of occurrence and development. Lipids play a crucial role in cells by participating in energy supply, biofilm formation, and signal transduction processes, and lipid metabolic reprogramming also constitutes a significant characteristic of malignant tumors. More and more studies have found esophageal cancer has obvious lipid metabolism abnormalities throughout its beginning, progress, and treatment resistance. The inhibition of tumor growth and the enhancement of antitumor therapy efficacy can be achieved through the regulation of lipid metabolism. Therefore, we reviewed and analyzed the research results and latest findings for lipid metabolism and associated analysis techniques in esophageal cancer, and comprehensively proved the value of lipid metabolic reprogramming in the evolution and treatment resistance of esophageal cancer, as well as its significance in exploring potential therapeutic targets and biomarkers.

Evaluation of antibody-based single cell type imaging techniques coupled to multiplexed imaging of N-glycans and collagen peptides by matrix-assisted laser desorption/ionization mass spectrometry imaging

The integration of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) with single cell spatial omics methods allows for a comprehensive investigation of single cell spatial information and matrisomal N-glycan and extracellular matrix protein imaging. Here, the performance of the antibody-directed single cell workflows coupled with MALDI-MSI are evaluated. Miralys™ photocleavable mass-tagged antibody probes (MALDI-IHC, AmberGen, Inc.), GeoMx DSP® (NanoString, Inc.), and Imaging Mass Cytometry (IMC, Standard BioTools Inc.) were used in series with MALDI-MSI of N-glycans and extracellular matrix peptides on formalin-fixed paraffin-embedded tissues. Single cell omics protocols were performed before and after MALDI-MSI. The data suggests that for each modality combination, there is an optimal order for performing both techniques on the same tissue section. An overall conclusion is that MALDI-MSI studies may be completed on the same tissue section as used for antibody-directed single cell modalities. This work increases access to combined cellular and extracellular information within the tissue microenvironment to enhance research on the pathological origins of disease.

Tracking the Metabolic Fate of Exogenous Arachidonic Acid in Ferroptosis Using Dual-Isotope Labeling Lipidomics

Lipid metabolism is implicated in a variety of diseases, including cancer, cell death, and inflammation, but lipidomics has proven to be challenging due to the vast structural diversity over a narrow range of mass and polarity of lipids. Isotope labeling is often used in metabolomics studies to follow the metabolism of exogenously added labeled compounds because they can be differentiated from endogenous compounds by the mass shift associated with the label. The application of isotope labeling to lipidomics has also been explored as a method to track the metabolism of lipids in various disease states. However, it can be difficult to differentiate a single isotopically labeled lipid from the rest of the lipidome due to the variety of endogenous lipids present over the same mass range. Here we report the development of a dual-isotope deuterium labeling method to track the metabolic fate of exogenous polyunsaturated fatty acids, e.g., arachidonic acid, in the context of ferroptosis using hydrophilic interaction-ion mobility-mass spectrometry (HILIC-IM-MS). Ferroptosis is a type of cell death that is dependent on lipid peroxidation. The use of two isotope labels rather than one enables the identification of labeled species by a signature doublet peak in the resulting mass spectra. A Python-based software, D-Tracer, was developed to efficiently extract metabolites with dual-isotope labels. The labeled species were then identified with LiPydomics based on their retention times, collision cross section, and m/z values. Changes in exogenous AA incorporation in the absence and presence of a ferroptosis inducer were elucidated.

Ion mobility mass spectrometry for the study of mycobacterial mycolic acids

Lipids are highly structurally diverse molecules involved in a wide variety of biological processes. The involvement of lipids is even more pronounced in mycobacteria, including the human pathogen Mycobacterium tuberculosis, which produces a highly complex and diverse set of lipids in the cell envelope. These lipids include mycolic acids, which are among the longest fatty acids in nature and can contain up to 90 carbon atoms. Mycolic acids are ubiquitously found in mycobacteria and are alpha branched and beta hydroxylated lipids. Discrete modifications, such as alpha, alpha', epoxy, methoxy, keto, and carboxy, characterize mycolic acids at the species level. Here, we used high precision ion mobility-mass spectrometry to build a database including 206 mass-resolved collision cross sections (CCSs) of mycolic acids originating from the strict human pathogen M. tuberculosis, the opportunistic strains M. abscessus, M. marinum and M. avium, and the nonpathogenic strain M. smegmatis. Primary differences between the mycolic acid profiles could be observed between mycobacterial species. Acyl tail length and modifications were the primary structural descriptors determining CCS magnitude. As a resource for researchers, this work provides a detailed catalogue of the mass-resolved collision cross sections for mycolic acids along with a workflow to generate and analyse the dataset generated.

Development and application of lipidomics for food research

Lipidomics is an emerging and promising omics derived from metabolomics to comprehensively analyze all of lipid molecules in biological matrices. The purpose of this chapter is to introduce the development and application of lipidomics for food research. First, three aspects of sample preparation are introduced: food sampling, lipid extraction, and transportation and storage. Second, five types of instruments for data acquisition are summarized: direct infusion-mass spectrometry (MS), chromatographic separation-MS, ion mobility-MS, MS imaging, and nuclear magnetic resonance spectroscopy. Third, data acquisition and analysis software are described for the lipidomics software development. Fourth, the application of lipidomics for food research is discussed such as food origin and adulteration analysis, food processing research, food preservation research, and food nutrition and health research. All the contents suggest that lipidomics is a powerful tool for food research based on its ability of lipid component profile analysis.

α-Dicarbonyl compounds in food products: Comprehensively understanding their occurrence, analysis, and control

α-Dicarbonyl compounds (α-DCs) are readily produced during the heating and storage of foods, mainly through the Maillard reaction, caramelization, lipid-peroxidation, and enzymatic reaction. They contribute to both the organoleptic properties (i.e., aroma, taste, and color) and deterioration of foods and are potential indicators of food quality. α-DCs are also important precursors to hazardous substances, such as acrylamide, furan, advanced lipoxidation end products, and advanced glycation end products, which are genotoxic, neurotoxic, and linked to several diseases. Recent studies have indicated that dietary α-DCs can elevate plasma α-DC levels and lead to "dicarbonyl stress." To accurately assess their health risks, quantifying α-DCs in food products is crucial. Considering their low volatility, inability to absorb ultraviolet light, and high reactivity, the analysis of α-DCs in complex food systems is a challenge. In this review, we comprehensively cover the development of scientific approaches, from extraction, enrichment, and derivatization, to sophisticated detection techniques, which are necessary for quantifying α-DCs in different foods. Exposure to α-DCs is inevitable because they exist in most foods. Recently, novel strategies for reducing α-DC levels in foods have become a hot research topic. These strategies include the use of new processing technologies, formula modification, and supplementation with α-DC scavengers (e.g., phenolic compounds). For each strategy, it is important to consider the potential mechanisms underlying the formation and removal of process contaminants. Future studies are needed to develop techniques to control α-DC formation during food processing, and standardized approaches are needed to quantify and compare α-DCs in different foods.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

Different ion mobility-mass spectrometry coupling techniques to promote metabolomics

Metabolomics has become increasingly popular in recent years for many applications ranging from clinical diagnosis, human health to biotechnological questioning. Despite technological advances, metabolomic studies are still currently limited by the difficulty of identifying all metabolites, a class of compounds with great chemical diversity. Although lengthy chromatographic analyses are often used to obtain comprehensive data, many isobar and isomer metabolites still remain unresolved, which is a critical point for the compound identification. Currently, ion mobility spectrometry is being explored in metabolomics as a way to improve metabolome coverage, analysis throughput and isomer separation. In this review, all the steps of a typical workflow for untargeted metabolomics are discussed considering the use of an ion mobility instrument. An overview of metabolomics is first presented followed by a brief description of ion mobility instrumentation. The ion mobility potential for complex mixture analysis is discussed regarding its coupling with a mass spectrometer alone, providing gas-phase separation before mass analysis as well as its combination with different separation platforms (conventional hyphenation but also multidimensional ion mobility couplings), offering multidimensional separation. Various instrumental and analytical conditions for improving the ion mobility separation are also described. Finally, data mining, including software packages and visualization approaches, as well as the construction of ion mobility databases for the metabolite identification are examined.

Ion Mobility-Derived Collision Cross-Sections Add Extra Capability in Distinguishing Isomers and Compounds with Similar Retention Times: The Case of Aphidicolanes

The hyphenation of ion mobility spectrometry with high-resolution mass spectrometry has been widely used in the characterization of various metabolites. Nevertheless, such a powerful tool remains largely unexplored in natural products research, possibly mainly due to the lack of available compounds. To evaluate the ability of collision cross-sections (CCSs) in characterizing compounds, especially isomeric natural products, here we measured and compared the traveling-wave IMS-derived nitrogen CCS values for 75 marine-derived aphidicolanes. We established a CCS database for these compounds which contained 227 CCS values of different adducts. When comparing the CCS differences, 36 of 57 pairs (over 60%) of chromatographically neighboring compounds showed a ΔCCS over 2%. What is more, 64 of 104 isomeric pairs (over 60%) of aphidicolanes can be distinguished by their CCS values, and 13 of 18 pairs (over 70%) of chromatographically indistinguishable isomers can be differentiated from the mobility dimension. Our results strongly supported CCS as an important parameter with good orthogonality and complementarity with retention time. CCS is expected to play an important role in distinguishing complex and diverse marine natural products.

Chemical and biological assessments of environmental mixtures: A review of current trends, advances, and future perspectives

Considering the chemical complexity and toxicity data gaps of environmental mixtures, most studies evaluate the chemical risk individually. However, humans are usually exposed to a cocktail of chemicals in real life. Mixture health assessment remains to be a research area having significant knowledge gaps. Characterization of chemical composition and bioactivity/toxicity are the two critical aspects of mixture health assessments. This review seeks to introduce the recent progress and tools for the chemical and biological characterization of environmental mixtures. The state-of-the-art techniques include the sampling, extraction, rapid detection methods, and the in vitro, in vivo, and in silico approaches to generate the toxicity data of an environmental mixture. Application of these novel methods, or new approach methodologies (NAMs), has increased the throughput of generating chemical and toxicity data for mixtures and thus refined the mixture health assessment. Combined with computational methods, the chemical and biological information would shed light on identifying the bioactive/toxic components in an environmental mixture.

Evaluating the Effects of Metal Adduction and Charge Isomerism on Ion-Mobility Measurements using m-Xylene Macrocycles as Models

Gas-phase ion-mobility spectrometry provides a unique platform to study the effect of mobile charge(s) or charge location on collisional cross section and ion separation. Here, we evaluate the effects of cation/anion adduction in a series of xylene and pyridyl macrocycles that contain ureas and thioureas. We explore how zinc binding led to unexpected deprotonation of the thiourea macrocyclic host in positive polarity ionization and subsequently how charge isomerism due to cation (zinc metal) and anion (chloride counterion) adduction or proton competition among acceptors can affect the measured collisional cross sections in helium and nitrogen buffer gases. Our approach uses synthetic chemistry to design macrocycle targets and a combination of ion-mobility spectrometry mass spectrometry experiments and quantum mechanics calculations to characterize their structural properties. We demonstrate that charge isomerism significantly improves ion-mobility resolution and allows for determination of the metal binding mechanism in metal-inclusion macrocyclic complexes. Additionally, charge isomers can be populated in molecules where individual protons are shared between acceptors. In these cases, interactions via drift gas collisions magnify the conformational differences. Finally, for the macrocyclic systems we report here, charge isomers are observed in both helium and nitrogen drift gases with similar resolution. The separation factor does not simply increase with increasing drift gas polarizability. Our study sheds light on important properties of charge isomerism and offers strategies to take advantage of this phenomenon in analytical separations.

Effect of Traveling Waveform Profiles on Collision Cross Section Measurements in Structures for Lossless Ion Manipulations

We evaluated the effect of four different waveform profiles (Square, Sine, Triangle, and asymmetric Sawtooth) on the accuracy of collision cross section (CCS) measurements using traveling wave ion mobility spectrometry (TWIMS) separations in structures for lossless ion manipulations (SLIM). The effects of the waveform profiles on the accuracy of the CCS measurements were evaluated for four classes of compounds (lipids, peptides, steroids, and nucleosides) at different TW speeds (126-206 m/s) and amplitudes (15-89 V). For the lipids and peptides, the TWIMS-based CCS (TWCCS) deviations from the corresponding drift-tube-based CCS (DTCCS) measurements were significantly lower in experiments conducted using the Sawtooth waveform compared to the square waveform. This observation can be rationalized by the lower maximum electric field experienced by ions with a Sawtooth waveform, as compared to the other waveforms, resulting in a lower probability for significant ion heating. We also observed that given approximately comparable resolution for all four waveforms, the Sawtooth waveform resulted in lower TWCCS error and a better agreement with DTCCS values than the Square waveform. In addition, for the steroids and nucleosides, an opposite TWCCS trend was observed, with higher errors with the Sawtooth waveform and lower with the Square waveform, suggesting that these molecules tend to become slightly more compact under ion heating conditions. Under optimum conditions, all TWCCS measurements on the SLIM platform were within 0.5% of those measured in the drift tube ion mobility spectrometry.

Deep-lipidotyping by mass spectrometry: recent technical advances and applications

In-depth structural characterization of lipids is an essential component of lipidomics. There has been a rapid expansion of mass spectrometry methods that are capable of resolving lipid isomers at various structural levels over the past decade. These developments finally make deep-lipidotyping possible, which provides new means to study lipid metabolism and discover new lipid biomarkers. In this review, we discuss recent advancements in tandem mass spectrometry (MS/MS) methods for identification of complex lipids beyond the species (known headgroup information) and molecular species (known chain composition) levels. These include identification at the levels of carbon-carbon double bond (C=C) location and sn-position as well as characterization of acyl chain modifications. We also discuss the integration of isomer-resolving MS/MS methods with different lipid analysis workflows and their applications in lipidomics. The results showcase the distinct capabilities of deep-lipidotyping in untangling the metabolism of individual isomers and sensitive phenotyping by using relative fractional quantitation of the isomers.

Mass Spectrometry-Based Techniques to Elucidate the Sugar Code

Cells encode information in the sequence of biopolymers, such as nucleic acids, proteins, and glycans. Although glycans are essential to all living organisms, surprisingly little is known about the "sugar code" and the biological roles of these molecules. The reason glycobiology lags behind its counterparts dealing with nucleic acids and proteins lies in the complexity of carbohydrate structures, which renders their analysis extremely challenging. Building blocks that may differ only in the configuration of a single stereocenter, combined with the vast possibilities to connect monosaccharide units, lead to an immense variety of isomers, which poses a formidable challenge to conventional mass spectrometry. In recent years, however, a combination of innovative ion activation methods, commercialization of ion mobility-mass spectrometry, progress in gas-phase ion spectroscopy, and advances in computational chemistry have led to a revolution in mass spectrometry-based glycan analysis. The present review focuses on the above techniques that expanded the traditional glycomics toolkit and provided spectacular insight into the structure of these fascinating biomolecules. To emphasize the specific challenges associated with them, major classes of mammalian glycans are discussed in separate sections. By doing so, we aim to put the spotlight on the most important element of glycobiology: the glycans themselves.

Infrared Laser Ablation Microsampling with a Reflective Objective

A Schwarzschild reflective objective with a numerical aperture of 0.3 and working distance of 10 cm was used for laser ablation sampling of tissue for off-line mass spectrometry. The objective focused the laser to a diameter of 5 μm and produced 10 μm ablation spots on thin ink films and tissue sections. Rat brain tissue sections 50 μm thick were ablated in transmission geometry, and the ablated material was captured in a microcentrifuge tube containing solvent. Proteins from ablated tissue sections were quantified with a Bradford assay, which indicated that approximately 300 ng of protein was captured from a 1 mm² area of ablated tissue. Areas of tissue ranging from 0.01 to 1 mm² were ablated and captured for bottom-up proteomics. Proteins were extracted from the captured tissue and digested for liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis for peptide and protein identification.

Structures and functions of the gut microbial lipidome

Microbial lipids provide signals that are responsible for maintaining host health and controlling disease. The differences in the structures of microbial lipids have been shown to alter receptor selectivity and agonist/antagonist activity. Advanced lipidomics is an emerging field that helps to elucidate the complex bacterial lipid diversity. The use of cutting-edge technologies is expected to lead to the discovery of new functional metabolites involved in host homeostasis. This review aims to describe recent updates on functional lipid metabolites derived from gut microbiota, their structure-activity relationships, and advanced lipidomics technologies.

Resolving Heparan Sulfate Oligosaccharide Positional Isomers Using Hydrophilic Interaction Liquid Chromatography-Cyclic Ion Mobility Mass Spectrometry

Heparan sulfate (HS) is a linear polysaccharide covalently attached to proteoglycans on cell surfaces and within extracellular matrices in all animal tissues. Many biological processes are triggered by the interactions among HS binding proteins and short structural motifs in HS chains. The determination of HS oligosaccharide structures using liquid chromatography-mass spectrometry (LC-MS) is made challenging by the existence of positional sulfation and acetylation isomers. The determination of uronic acid epimer positions is even more challenging. While hydrophilic interaction liquid chromatography (HILIC) separates HS saccharides based on their composition, there is a very limited resolution of positional isomers. This lack of resolution places a burden on the tandem mass spectrometry step for assigning saccharide isomers. In this work, we explored the use of the ion mobility dimension to separate HS saccharide isomers based on molecular shape in the gas phase. We showed that the combination of HILIC and cyclic ion mobility mass spectrometry (cIM-MS) was extremely useful for resolving HS positional isomers including uronic acid epimers and sulfate positions. Furthermore, HILIC-cIM-MS differentiated multicomponent HS isomeric saccharide mixtures. In summary, HILIC-cIM-MS provided high-quality data for analysis of HS oligosaccharide isomeric mixtures that may prove useful in the discovery of new structural motifs for HS binding proteins and for the targeted quality control analysis of commercial HS products.

Lipid analysis by ion mobility spectrometry combined with mass spectrometry: A brief update with a perspective on applications in the clinical laboratory

Ion mobility spectrometry (IMS) is an analytical technique where ions are separated in the gas phase based on their mobility through a buffer gas in the presence of an electric field. An ion passing through an IMS device has a characteristic collisional cross section (CCS) value that depends on the buffer gas used. IMS can be coupled with mass spectrometry (MS), which characterizes an ion based on a mass-to-charge ratio (m/z), to increase analytical specificity and provide further physicochemical information. In particular, IMS-MS is of ever-increasing interest for the analysis of lipids, which can be problematic to accurately identify and quantify in bodily fluids by liquid chromatography (LC) with MS alone due to the presence of isomers, isobars, and structurally similar analogs. IMS provides an additional layer of separation when combined with front-end LC approaches, thereby, enhancing peak capacity and analytical specificity. CCS (and also ion mobility drift time) can be plotted against m/z ion intensity and/or LC retention time in order to generate in-depth molecular profiles of a sample. Utilization of IMS-MS for routine clinical laboratory testing remains relatively unexplored, but areas do exist for potential implementation. A brief update is provided here on lipid analysis using IMS-MS with a perspective on some applications in the clinical laboratory.

Cross-Platform Evaluation of Commercially Targeted and Untargeted Metabolomics Approaches to Optimize the Investigation of Psychiatric Disease

Metabolomics methods often encounter trade-offs between quantification accuracy and coverage, with truly comprehensive coverage only attainable through a multitude of complementary assays. Due to the lack of standardization and the variety of metabolomics assays, it is difficult to integrate datasets across studies or assays. To inform metabolomics platform selection, with a focus on posttraumatic stress disorder (PTSD), we review platform use and sample sizes in psychiatric metabolomics studies and then evaluate five prominent metabolomics platforms for coverage and performance, including intra-/inter-assay precision, accuracy, and linearity. We found performance was variable between metabolite classes, but comparable across targeted and untargeted approaches. Within all platforms, precision and accuracy were highly variable across classes, ranging from 0.9-63.2% (coefficient of variation) and 0.6-99.1% for accuracy to reference plasma. Several classes had high inter-assay variance, potentially impeding dissociation of a biological signal, including glycerophospholipids, organooxygen compounds, and fatty acids. Coverage was platform-specific and ranged from 16-70% of PTSD-associated metabolites. Non-overlapping coverage is challenging; however, benefits of applying multiple metabolomics technologies must be weighed against cost, biospecimen availability, platform-specific normative levels, and challenges in merging datasets. Our findings and open-access cross-platform dataset can inform platform selection and dataset integration based on platform-specific coverage breadth/overlap and metabolite-specific performance.

Metabolomics meets lipidomics: Assessing the small molecule component of metabolism

Metabolomics, including lipidomics, is emerging as a quantitative biology approach for the assessment of energy flow through metabolism and information flow through metabolic signaling; thus, providing novel insights into metabolism and its regulation, in health, healthy ageing and disease. In this forward-looking review we provide an overview on the origins of metabolomics, on its role in this postgenomic era of biochemistry and its application to investigate metabolite role and (bio)activity, from model systems to human population studies. We present the challenges inherent to this analytical science, and approaches and modes of analysis that are used to resolve, characterize and measure the infinite chemical diversity contained in the metabolome (including lipidome) of complex biological matrices. In the current outbreak of metabolic diseases such as cardiometabolic disorders, cancer and neurodegenerative diseases, metabolomics appears to be ideally situated for the investigation of disease pathophysiology from a metabolite perspective.

Ion mobility-based sterolomics reveals spatially and temporally distinctive sterol lipids in the mouse brain

Aberrant sterol lipid metabolism is associated with physiological dysfunctions in the aging brain and aging-dependent disorders such as neurodegenerative diseases. There is an unmet demand to comprehensively profile sterol lipids spatially and temporally in different brain regions during aging. Here, we develop an ion mobility-mass spectrometry based four-dimensional sterolomics technology leveraged by a machine learning-empowered high-coverage library (>2000 sterol lipids) for accurate identification. We apply this four-dimensional technology to profile the spatially resolved landscapes of sterol lipids in ten functional regions of the mouse brain, and quantitatively uncover ~200 sterol lipids uniquely distributed in specific regions with concentrations spanning up to 8 orders of magnitude. Further spatial analysis pinpoints age-associated differences in region-specific sterol lipid metabolism, revealing changes in the numbers of altered sterol lipids, concentration variations, and age-dependent coregulation networks. These findings will contribute to our understanding of abnormal sterol lipid metabolism and its role in brain diseases.

Extending the Lipidome Coverage by Combining Different Mass Spectrometric Platforms: An Innovative Strategy to Answer Chemical Food Safety Issues

From a general public health perspective, a strategy combining non-targeted and targeted lipidomics MS-based approaches is proposed to identify disrupted patterns in serum lipidome upon growth promoter treatment in pigs. Evaluating the relative contributions of the platforms involved, the study aims at investigating the potential of innovative analytical approaches to highlight potential chemical food safety threats. Serum samples collected during an animal experiment involving control and treated pigs, whose food had been supplemented with ractopamine, were extracted and characterised using three MS strategies: Non-targeted RP LC-HRMS; the targeted Lipidyzer™ platform (differential ion mobility associated with shotgun lipidomics) and a homemade LC-HRMS triglyceride platform. The strategy enabled highlighting specific lipid profile patterns involving various lipid classes, mainly in relation to cholesterol esters, sphingomyelins, lactosylceramide, phosphatidylcholines and triglycerides. Thanks to the combination of non-targeted and targeted MS approaches, various compartments of the pig serum lipidome could be explored, including commonly characterised lipids (Lipidyzer™), triglyceride isomers (Triglyceride platform) and unique lipid features (non-targeted LC-HRMS). Thanks to their respective characteristics, the complementarity of the three tools could be demonstrated for public health purposes, with enhanced coverage, level of characterization and applicability.

Detection of acacia honey adulteration with high fructose corn syrup through determination of targeted α‑Dicarbonyl compound using ion mobility-mass spectrometry coupled with UHPLC-MS/MS

High-value acacia honey is often adulterated with inexpensive high fructose corn syrup (HFCS), due to their similar color and sugar composition. α‑Dicarbonyl compounds formed by Maillard reaction or caramelization during heat treatment or storage, differ between HFCS and honey due to differences in starting materials and processing methods. In this study, we compared α-dicarbonyl compounds in acacia honey and HFCS by Ion Mobility-Mass Spectrometry and multivariate statistical analysis. Through α-dicarbonyl compound derivatization with o-phenylenediamine, we screened a marker with 189.1023 m/z and 139.3 Å² Collision Cross-Section that can distinguish HFCS from acacia honey. Nuclear magnetic resonance spectra identified this marker compound as 3,4-dideoxypentosulose. We then used chromatography-coupled tandem mass spectrometry to quantitate 3,4-dideoxypentosulose in market samples of honey and HFCS and found that 3,4-dideoxypentosulose was negligible (<0.098 mg/kg) in honey, but prevalent in HFCS (≧1.174 mg/kg), indicating 3,4-dideoxypentosulose can serve as an alternative indicator of HFCS adulteration of acacia honey.

High-Throughput Microbore Ultrahigh-Performance Liquid Chromatography-Ion Mobility-Enabled-Mass Spectrometry-Based Proteomics Methodology for the Exploratory Analysis of Serum Samples from Large Cohort Studies

The deployment of proteomic analysis in clinical studies represents a significant opportunity to detect and validate biomarkers in translational medicine, improve disease understanding, and provide baseline information on population health. However, comprehensive proteome studies usually employ nanoscale chromatography and often require several hours of analysis/sample. Here, we describe a high-throughput liquid chromatography tandem mass spectrometry (LC/MS/MS) methodology using 1 mm scale chromatography requiring only 15 min/sample, coupled to ion mobility-enabled mass spectrometry. The short run time effected a 6-fold increase in productivity compared with nanoscale LC/MS. The method demonstrated excellent reproducibility with retention time coefficient of variations of less than 0.05% and peak area reproducibility ranging from 5 to 15%. The 1 mm system produced similar chromatographic peak capacity values to the nanoscale miniaturized system, detecting 90% of the Escherichia coli proteins identified by the 75 μm LC/MS system (albeit based on only 75% of the peptides found by the latter). Application to the analysis of serum samples from a human prostate cancer study group resulted in the identification of a total of 533 proteins revealing the differential expression of proteins linked to patients receiving hormone-radiotherapy or undergoing surgery.

An Improved Calibration Approach for Traveling Wave Ion Mobility Spectrometry: Robust, High-Precision Collision Cross Sections

The combination of ion-mobility (IM) separation with mass spectrometry (MS) has impacted global measurement efforts in areas ranging from food analysis to drug discovery. Reasons for the broad adoption of IM-MS include its significantly increased peak capacity, duty-cycle, and ability to reconstruct fragmentation data in parallel, all of which greatly enable the analyses of complex mixtures. More fundamentally, however, measurements of ion-gas molecule collision cross sections (CCSs) are used to support compound identification and quantitation efforts as well as study the structures of large biomolecules. As the first commercialized form of IM-MS, Traveling Wave Ion Mobility (TWIM) devices are operated at low pressures (∼3 mbar) and voltages, are relatively short (∼25 cm), and separate ions on a timescale of tens of milliseconds. These qualities make TWIM ideally suited for hybridization with MS. Owing to the complicated motion of ions in TWIM devices, however, IM transit times must be calibrated to enable CCS measurements. Applicability of these calibrations has hitherto been restricted to primarily singly charged small molecules and some classes of large, multiply charged ions under a significantly narrower range of instrument conditions. Here, we introduce and extensively characterize a dramatically improved TWIM calibration methodology. Using over 2500 experimental TWIM data sets, covering ions that span over 3.5 orders of magnitude of molecular mass, we demonstrate robust calibrations for a significantly expanded range of instrument conditions, thereby opening up new analytical application areas and enabling the expansion of high-precision CCS measurements for both existing and next-generation TWIM instrumentation.

Evaluation of Waveform Profiles for Traveling Wave Ion Mobility Separations in Structures for Lossless Ion Manipulations

Structures for lossless ion manipulations (SLIM) have recently enabled a powerful implementation of traveling wave ion mobility spectrometry (TWIMS) for ultrahigh resolution separations; however, experimental parameters have not been optimized, and potential significant gains may be feasible. Most TWIMS separations have utilized square-shaped waveforms applied by time-dependent voltage stepping across repeating sets of electrodes, but alternative waveforms may provide further improvements to resolution. Here, we characterize five waveforms (including square and sine) in terms of their transmission efficiency, IMS resolution, and resolving power, and explore the effects of TW amplitude and speed on the performance of each. We found, consistent with previous work, separations were generally improved with higher TW amplitudes, moderately improved by lower speeds (limited by ion "surfing" with the waves), and found decreases in signal intensity at the extremes of operating conditions. The triangle and asymmetric "ramp forward" shaped profiles were found to provide modestly greater resolution and resolving power, an observation we tentatively attribute to their relatively uniform fields and minimal low-field regions.

A concise review on lipidomics analysis in biological samples

Lipids are a complex and critical heterogeneous molecular entity, playing an intricate and key role in understanding biological activities and disease processes. Lipidomics aims to quantitatively define the lipid classes, including their molecular species. The analysis of the biological tissues and fluids are challenging due to the extreme sample complexity and occurrence of the molecular species as isomers or isobars. This review documents the overview of lipidomics workflow, beginning from the approaches of sample preparation, various analytical techniques and emphasizing the state-of-the-art mass spectrometry either by shotgun or coupled with liquid chromatography. We have considered the latest ion mobility spectroscopy technologies to deal with the vast number of structural isomers, different imaging techniques. All these techniques have their pitfalls and we have discussed how to circumvent them after reviewing the power of each technique with examples..

Standardizing and increasing the utility of lipidomics: a look to the next decade

Introduction: We present our views on the current application of mass spectrometry (MS) based lipidomics and how lipidomics can develop in the next decade to be most practical use to society. That is not to say that lipidomics has not already been of value. In-fact, in its earlier guise as metabolite profiling most of the pathways of steroid biosynthesis were uncovered and via focused lipidomics many inborn errors of metabolism are routinely clinically identified. However, can lipidomics be extended to improve biochemical understanding of, and to diagnose, the most prevalent diseases of the 21^st century? Areas covered: We will highlight the concept of 'level of identification' and the equally crucial topic of 'quantification'. Only by using a standardized language for these terms can lipidomics be translated to fields beyond academia. We will remind the lipid scientist of the value of chemical derivatization, a concept exploited since the dawn of lipid biochemistry. Expert opinion: Only by agreement of the concepts of identification and quantification and their incorporation in lipidomics reporting can lipidomics maximize its value.

Integrating ion mobility and imaging mass spectrometry for comprehensive analysis of biological tissues: A brief review and perspective

Imaging mass spectrometry (IMS) technologies are capable of mapping a wide array of biomolecules in diverse cellular and tissue environments. IMS has emerged as an essential tool for providing spatially targeted molecular information due to its high sensitivity, wide molecular coverage, and chemical specificity. One of the major challenges for mapping the complex cellular milieu is the presence of many isomers and isobars in these samples. This challenge is traditionally addressed using orthogonal liquid chromatography (LC)-based analysis, though, common approaches such as chromatography and electrophoresis are not able to be performed at timescales that are compatible with most imaging applications. Ion mobility offers rapid, gas-phase separations that are readily integrated with IMS workflows in order to provide additional data dimensionality that can improve signal-to-noise, dynamic range, and specificity. Here, we highlight recent examples of ion mobility coupled to IMS and highlight their importance to the field.

Recent advances in analytical strategies for mass spectrometry-based lipidomics

Lipids are vital biological molecules and play multiple roles in cellular function of mammalian organisms such as cellular membrane anchoring, signal transduction, material trafficking and energy storage. Driven by the biological significance of lipids, lipidomics has become an emerging science in the field of omics. Lipidome in biological systems consists of hundreds of thousands of individual lipid molecules that possess complex structures, multiple categories, and diverse physicochemical properties assembled by different combinations of polar headgroups and hydrophobic fatty acyl chains. Such structural complexity poses a huge challenge for comprehensive lipidome analysis. Thanks to the great innovations in chromatographic separation techniques and the continuous advances in mass spectrometric detection tools, analytical strategies for lipidomics have been highly diversified so that the depth and breadth of lipidomics have been greatly enhanced. This review will present the current state of mass spectrometry-based analytical strategies including untargeted, targeted and pseudotargeted lipidomics. Recent typical applications of lipidomics in biomarker discovery, pathogenic mechanism and therapeutic strategy are summarized, and the challenges facing to the field of lipidomics are also discussed.

Ultrahigh-Resolution Mass Spectrometry-Based Platform for Plasma Metabolomics Applied to Type 2 Diabetes Research

Metabolomics-the endpoint of the omics cascade-is increasingly recognized as a preferred method for understanding the ultimate responses of biological systems to stress. Flow injection electrospray (FIE) mass spectrometry (MS) has advantages for untargeted metabolic fingerprinting due to its simplicity and capability for high-throughput screening but requires a high-resolution mass spectrometer to resolve metabolite features. In this study, we developed and validated a high-throughput and highly reproducible metabolomics platform integrating FIE with ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) MS for analysis of both polar and nonpolar metabolite features from plasma samples. FIE-FTICR MS enables high-throughput detection of hundreds of metabolite features in a single mass spectrum without a front-end separation step. Using plasma samples from genetically identical obese mice with or without type 2 diabetes (T2D), we validated the intra and intersample reproducibility of our method and its robustness for simultaneously detecting alterations in both polar and nonpolar metabolite features. Only 5 min is needed to acquire an ultra-high resolution mass spectrum in either a positive or negative ionization mode. Approximately 1000 metabolic features were reproducibly detected and annotated in each mouse plasma group. For significantly altered and highly abundant metabolite features, targeted tandem MS (MS/MS) analyses can be applied to confirm their identity. With this integrated platform, we successfully detected over 300 statistically significant metabolic features in T2D mouse plasma as compared to controls and identified new T2D biomarker candidates. This FIE-FTICR MS-based method is of high throughput and highly reproducible with great promise for metabolomics studies toward a better understanding and diagnosis of human diseases.

In situ isobaric lipid mapping by MALDI-ion mobility separation-mass spectrometry imaging

The highly diverse chemical structures of lipids make their analysis directly from biological tissue sections extremely challenging. Here, we report the in situ mapping and identification of lipids in a freshwater crustacean Gammarus fossarum using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) in combination with an additional separation dimension using ion mobility spectrometry (IMS). The high-resolution trapped ion mobility spectrometry (TIMS) allowed efficient separation of isobaric/isomeric lipids showing distinct spatial distributions. The structures of the lipids were further characterized by MS/MS analysis. It is demonstrated that MALDI MSI with mobility separation is a powerful tool for distinguishing and localizing isobaric/isomeric lipids.

Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics

The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobility - mass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here, we curate an ion mobility CCS atlas, namely AllCCS, and develop an integrated strategy for metabolite annotation using known or unknown chemical structures. The AllCCS atlas covers vast chemical structures with >5000 experimental CCS records and ~12 million calculated CCS values for >1.6 million small molecules. We demonstrate the high accuracy and wide applicability of AllCCS with medium relative errors of 0.5-2% for a broad spectrum of small molecules. AllCCS combined with in silico MS/MS spectra facilitates multi-dimensional match and substantially improves the accuracy and coverage of both known and unknown metabolite annotation from biological samples. Together, AllCCS is a versatile resource that enables confident metabolite annotation, revealing comprehensive chemical and metabolic insights towards biological processes.

Mass spectrometry-based lipidomics in food science and nutritional health: A comprehensive review

With the advance in science and technology as well as the improvement of living standards, the function of food is no longer just to meet the needs of survival. Food science and its associated nutritional health issues have been increasingly debated. Lipids, as complex metabolites, play a key role both in food and human health. Taking advantages of mass spectrometry (MS) by combining its high sensitivity and accuracy with extensive selective determination of all lipid classes, MS-based lipidomics has been employed to resolve the conundrum of addressing both qualitative and quantitative aspects of high-abundance and low-abundance lipids in complex food matrices. In this review, we systematically summarize current applications of MS-based lipidomics in food field. First, common MS-based lipidomics procedures are described. Second, the applications of MS-based lipidomics in food science, including lipid composition characterization, adulteration, traceability, and other issues, are discussed. Third, the application of MS-based lipidomics for nutritional health covering the influence of food on health and disease is introduced. Finally, future research trends and challenges are proposed. MS-based lipidomics plays an important role in the field of food science, promoting continuous development of food science and integration of food knowledge with other disciplines. New methods of MS-based lipidomics have been developed to improve accuracy and sensitivity of lipid analysis in food samples. These developments offer the possibility to fully characterize lipids in food samples, identify novel functional lipids, and better understand the role of food in promoting healt.

Lipid Annotation by Combination of UHPLC-HRMS (MS), Molecular Networking, and Retention Time Prediction: Application to a Lipidomic Study of In Vitro Models of Dry Eye Disease

Annotation of lipids in untargeted lipidomic analysis remains challenging and a systematic approach needs to be developed to organize important datasets with the help of bioinformatic tools. For this purpose, we combined tandem mass spectrometry-based molecular networking with retention time (t_R) prediction to annotate phospholipid and sphingolipid species. Sixty-five standard compounds were used to establish the fragmentation rules of each lipid class studied and to define the parameters governing their chromatographic behavior. Molecular networks (MNs) were generated through the GNPS platform using a lipid standards mixture and applied to lipidomic study of an in vitro model of dry eye disease, i.e., human corneal epithelial (HCE) cells exposed to hyperosmolarity (HO). These MNs led to the annotation of more than 150 unique phospholipid and sphingolipid species in the HCE cells. This annotation was reinforced by comparing theoretical to experimental t_R values. This lipidomic study highlighted changes in 54 lipids following HO exposure of corneal cells, some of them being involved in inflammatory responses. The MN approach coupled to t_R prediction thus appears as a suitable and robust tool for the discovery of lipids involved in relevant biological processes.

Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence

Spatial metabolomics is an emerging field of omics research that has enabled localizing metabolites, lipids, and drugs in tissue sections, a feat considered impossible just two decades ago. Spatial metabolomics and its enabling technology-imaging mass spectrometry-generate big hyper-spectral imaging data that have motivated the development of tailored computational methods at the intersection of computational metabolomics and image analysis. Experimental and computational developments have recently opened doors to applications of spatial metabolomics in life sciences and biomedicine. At the same time, these advances have coincided with a rapid evolution in machine learning, deep learning, and artificial intelligence, which are transforming our everyday life and promise to revolutionize biology and healthcare. Here, we introduce spatial metabolomics through the eyes of a computational scientist, review the outstanding challenges, provide a look into the future, and discuss opportunities granted by the ongoing convergence of human and artificial intelligence.

Lipidomics by HILIC-Ion Mobility-Mass Spectrometry

Lipidomics is a rapidly growing field that enables the characterization of the entire lipidome in cells, tissues, or an organism. Changes in lipid metabolism and homeostasis caused by different disease states or drug treatments can be probed by lipidomics experiments, which can aid our understanding of normal physiology and disease pathology at the molecular level. While current technologies using liquid chromatography coupled with high-resolution mass spectrometry have greatly increased coverage of the lipidome, there are still limitations in resolving the large number of lipid species with similar masses in a narrow mass window. We recently reported that two orthogonal separation techniques, hydrophilic interaction liquid chromatography (HILIC) and ion mobility (IM), enhance the resolution of lipid species based on headgroup polarity and gas-phase size and shape, respectively, of various classes of glycerolipids, glycolipids, phospholipids, and sphingolipids. Here we describe the application of our HILIC-IM-MS lipidomics protocol to the analysis of lipid extracts derived from either tissues or cells, to identify significant changes in the lipidome in response to an internal or external stimulus, such as exposure to environmental chemicals.

The Use of LipidIMMS Analyzer for Lipid Identification in Ion Mobility-Mass Spectrometry-Based Untargeted Lipidomics

Untargeted lipidomics aims to comprehensively measure and characterize all lipid species in biological systems. Ion mobility-mass spectrometry (IM-MS) has showed a great potential for untargeted lipidomic analysis. Coupling with liquid chromatography and data-independent tandem MS techniques, acquired IM-MS data set contains four-dimensional information for lipid identification, including m/z of MS1 ion, retention time (RT), collision cross section (CCS), and MS/MS spectra. In this protocol, we introduced a data processing workflow using an integrative web server, namely, LipidIMMS Analyzer, to support accurate lipid identification. The protocol demonstrated the integration of all four dimensional information to achieve unambiguous identifications of lipids in complex biological samples.