Ion mobility mass spectrometry enhances low-abundance species detection in untargeted lipidomics

Blood-Derived Lipid and Metabolite Biomarkers in Cardiovascular Research from Clinical Studies: A Recent Update

The primary prevention, early detection, and treatment of cardiovascular disease (CVD) have been long-standing scientific research goals worldwide. In the past decades, traditional blood lipid profiles have been routinely used in clinical practice to estimate the risk of CVDs such as atherosclerotic cardiovascular disease (ASCVD) and as treatment targets for the primary prevention of adverse cardiac events. These blood lipid panel tests often fail to fully predict all CVD risks and thus need to be improved. A comprehensive analysis of molecular species of lipids and metabolites (defined as lipidomics and metabolomics, respectively) can provide molecular insights into the pathophysiology of the disease and could serve as diagnostic and prognostic indicators of disease. Mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based lipidomics and metabolomics analysis have been increasingly used to study the metabolic changes that occur during CVD pathogenesis. In this review, we provide an overview of various MS-based platforms and approaches that are commonly used in lipidomics and metabolomics workflows. This review summarizes the lipids and metabolites in human plasma/serum that have recently (from 2018 to December 2022) been identified as promising CVD biomarkers. In addition, this review describes the potential pathophysiological mechanisms associated with candidate CVD biomarkers. Future studies focused on these potential biomarkers and pathways will provide mechanistic clues of CVD pathogenesis and thus help with the risk assessment, diagnosis, and treatment of CVD.

Collision Cross Section Prediction Based on Machine Learning

Ion mobility-mass spectrometry (IM-MS) is a powerful separation technique providing an additional dimension of separation to support the enhanced separation and characterization of complex components from the tissue metabolome and medicinal herbs. The integration of machine learning (ML) with IM-MS can overcome the barrier to the lack of reference standards, promoting the creation of a large number of proprietary collision cross section (CCS) databases, which help to achieve the rapid, comprehensive, and accurate characterization of the contained chemical components. In this review, advances in CCS prediction using ML in the past 2 decades are summarized. The advantages of ion mobility-mass spectrometers and the commercially available ion mobility technologies with different principles (e.g., time dispersive, confinement and selective release, and space dispersive) are introduced and compared. The general procedures involved in CCS prediction based on ML (acquisition and optimization of the independent and dependent variables, model construction and evaluation, etc.) are highlighted. In addition, quantum chemistry, molecular dynamics, and CCS theoretical calculations are also described. Finally, the applications of CCS prediction in metabolomics, natural products, foods, and the other research fields are reflected.

Four-dimensional trapped ion mobility spectrometry lipidomics for high throughput clinical profiling of human blood samples

Lipidomics encompassing automated lipid extraction, a four-dimensional (4D) feature selection strategy for confident lipid annotation as well as reproducible and cross-validated quantification can expedite clinical profiling. Here, we determine 4D descriptors (mass to charge, retention time, collision cross section, and fragmentation spectra) of 200 lipid standards and 493 lipids from reference plasma via trapped ion mobility mass spectrometry to enable the implementation of stringent criteria for lipid annotation. We use 4D lipidomics to confidently annotate 370 lipids in reference plasma samples and 364 lipids in serum samples, and reproducibly quantify 359 lipids using level-3 internal standards. We show the utility of our 4D lipidomics workflow for high-throughput applications by reliable profiling of intra-individual lipidome phenotypes in plasma, serum, whole blood, venous and finger-prick dried blood spots.

Anandamide and other N-acylethanolamines: A class of signaling lipids with therapeutic opportunities

N-acylethanolamines (NAEs), including N-palmitoylethanolamine (PEA), N-oleoylethanolamine (OEA), N-arachidonoylethanolamine (AEA, anandamide), N-docosahexaenoylethanolamine (DHEA, synaptamide) and their oxygenated metabolites are a lipid messenger family with numerous functions in health and disease, including inflammation, anxiety and energy metabolism. The NAEs exert their signaling role through activation of various G protein-coupled receptors (cannabinoid CB₁ and CB₂ receptors, GPR55, GPR110, GPR119), ion channels (TRPV1) and nuclear receptors (PPAR-α and PPAR-γ) in the brain and periphery. The biological role of the oxygenated NAEs, such as prostamides, hydroxylated anandamide and DHEA derivatives, are less studied. Evidence is accumulating that NAEs and their oxidative metabolites may be aberrantly regulated or are associated with disease severity in obesity, metabolic syndrome, cancer, neuroinflammation and liver cirrhosis. Here, we comprehensively review NAE biosynthesis and degradation, their metabolism by lipoxygenases, cyclooxygenases and cytochrome P450s and the biological functions of these signaling lipids. We discuss the latest findings and therapeutic potential of modulating endogenous NAE levels by inhibition of their degradation, which is currently under clinical evaluation for neuropsychiatric disorders. We also highlight NAE biosynthesis inhibition as an emerging topic with therapeutic opportunities in endocannabinoid and NAE signaling.

Ion Mobility Mass Spectrometry Development and Applications

Although as an analytical method with high specificity and high sensitivity, mass spectrometry (MS) has a wide range of applications in many fields, it still needs other technologies as the assist and supplement to enhance the scope and capability of analysis. Coupling with ion mobility (IM) can make an enhancement effect in the field of pharmaceutical analysis as a supplementary method. The two-dimensional mass technology improves the confidence of compounds annotations while increasing peak capacity, with the gradual deepening of theoretical research on IM-MS, it has shown unique advantages in the complex analysis conditions. IM-MS owns great potential for improving the depth, range, dimension of in-depth drug research. In this review, the principle, instruments and methods, applications, advantages and limitations of IM-MS are described. Here, we also elaborate on the prospects in structural evaluation, separation, and identification of complex compounds for the drug discovery and development phase and the great advantages of macromolecules and omics.

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

In Silico Collision Cross Section Calculations to Aid Metabolite Annotation

The interpretation of ion mobility coupled to mass spectrometry (IM-MS) data to predict unknown structures is challenging and depends on accurate theoretical estimates of the molecular ion collision cross section (CCS) against a buffer gas in a low or atmospheric pressure drift chamber. The sensitivity and reliability of computational prediction of CCS values depend on accurately modeling the molecular state over accessible conformations. In this work, we developed an efficient CCS computational workflow using a machine learning model in conjunction with standard DFT methods and CCS calculations. Furthermore, we have performed Traveling Wave IM-MS (TWIMS) experiments to validate the extant experimental values and assess uncertainties in experimentally measured CCS values. The developed workflow yielded accurate structural predictions and provides unique insights into the likely preferred conformation analyzed using IM-MS experiments. The complete workflow makes the computation of CCS values tractable for a large number of conformationally flexible metabolites with complex molecular structures.

New Advances in Tissue Metabolomics: A Review

Metabolomics offers a hypothesis-generating approach for biomarker discovery in clinical medicine while also providing better understanding of the underlying mechanisms of chronic diseases. Clinical metabolomic studies largely rely on human biofluids (e.g., plasma, urine) as a more convenient specimen type for investigation. However, biofluids are non-organ specific reflecting complex biochemical processes throughout the body, which may complicate biochemical interpretations. For these reasons, tissue metabolomic studies enable deeper insights into aberrant metabolism occurring at the direct site of disease pathogenesis. This review highlights new advances in metabolomics for ex vivo analysis, as well as in situ imaging of tissue specimens, including diverse tissue types from animal models and human participants. Moreover, we discuss key pre-analytical and post-analytical challenges in tissue metabolomics for robust biomarker discovery with a focus on new methodological advances introduced over the past six years, including innovative clinical applications for improved screening, diagnostic testing, and therapeutic interventions for cancer.

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.

Lipids: biomarkers of healthy aging

Life expectancy, and longevity have been increasing in recent years. However, this is, in most cases, accompanied by age-related diseases. Thus, it became essential to better understand the mechanisms inherent to aging, and to establish biomarkers that characterize this physiological process. Among all biomolecules, lipids appear to be a good target for the study of these biomarkers. In fact, some lipids have already been associated with age-related diseases. With the development of analytical techniques such as Mass Spectrometry, and Nuclear Magnetic Resonance, Lipidomics has been increasingly used to study pathological, and physiological states of an organism. Thus, the study of serum, and plasma lipidome in centenarians, and elderly individuals without age-related diseases can be a useful tool for the identification of aging biomarkers, and to understand physiological aging, and longevity. This review focus on the importance of lipids as biomarkers of aging, and summarize the changes in the lipidome that have been associated with aging, and longevity.

Recent applications of ion mobility spectrometry in natural product research

Ion mobility spectrometry (IMS) is a rapid separation technique capable of extracting complementary structural information to chromatography and mass spectrometry (MS). IMS, especially in combination with MS, has experienced inordinate growth in recent years as an analytical technique, and elicited intense interest in many research fields. In natural product analysis, IMS shows promise as an additional tool to enhance the performance of analytical methods used to identify promising drug candidates. Potential benefits of the incorporation of IMS into analytical workflows currently used in natural product analysis include the discrimination of structurally similar secondary metabolites, improving the quality of mass spectral data, and the use of mobility-derived collision cross-section (CCS) values as an additional identification criterion in targeted and untargeted analyses. This review aims to provide an overview of the application of IMS to natural product analysis over the last six years. Instrumental aspects and the fundamental background of IMS will be briefly covered, and recent applications of the technique for natural product analysis will be discussed to demonstrate the utility of the technique in this field.

NAPE-specific phospholipase D regulates LRRK2 association with neuronal membranes

N-acylphosphatidylethanolamines (NAPEs) are glycerophospholipid precursors for bioactive lipid amides and potential regulators of membrane function. They are hydrolyzed by NAPE-specific phospholipase D (NAPE-PLD) and have been implicated in neurodegenerative disorders such as Parkinson's disease. Here, we used siRNA-mediated silencing of NAPE-PLD in human SH-SY5Y cells and NAPE-PLD^-/- mice to determine whether NAPEs influence the membrane association of LRRK2, a multifunctional protein kinase that is frequently mutated in persons with sporadic Parkinson's disease. NAPE-PLD deletion caused a significant accumulation of non-metabolized NAPEs, which was accompanied by a shift of LRRK2 from membrane to cytosol and a reduction in total LRRK2 content. Conversely, exposure of intact SH-SY5Y cells to bacterial PLD lowered NAPE levels and enhanced LRRK2 association with membranes. The results suggest that NAPE-PLD activity may contribute to the control of LRRK2 localization by regulating membrane NAPE levels.

Traveling Wave Ion Mobility-Mass Spectrometry to Enhance the Detection of Low Abundance Features in Untargeted Lipidomics

Ion mobility has become a valuable tool in mass spectrometry-based lipidomics workflows, thanks to its ability to separate ions in the gas phase based on their size and conformation. Over the last years, it was demonstrated that the comparative analysis of ion mobility data has the potential to highlight the presence of low abundance species in untargeted lipidomics. The present chapter illustrates the background of the topic and guides the reader from the sample preparation to the data analysis of an untargeted lipidomics experiment performed using ion mobility.

Identification and quantification of amino acids and related compounds based on Differential Mobility Spectrometry

A new metabolite descriptor allowing fast quantification for the diagnosis of metabolic diseases.

A protective role for N-acylphosphatidylethanolamine phospholipase D in 6-OHDA-induced neurodegeneration

N-acylphosphatidylethanolamine phospholipase D (NAPE-PLD) catalyzes the cleavage of membrane NAPEs into bioactive fatty-acid ethanolamides (FAEs). Along with this precursor role, NAPEs might also serve autonomous signaling functions. Here, we report that injections of 6-hydroxydopamine (6-OHDA) into the mouse striatum cause a local increase in NAPE and FAE levels, which precedes neuronal cell death. NAPE, but not FAE, accumulation is enhanced in mice lacking NAPE-PLD, which display a substantial reduction in 6-OHDA-induced neurotoxicity, as shown by increased survival of substantia nigra dopamine neurons, integrity of striatal dopaminergic fibers, and striatal dopamine metabolite content. Reduced damage is accompanied by attenuation of the motor response evoked by apomorphine. Furthermore, NAPE-PLD silencing protects cathecolamine-producing SH-SY5Y cells from 6-OHDA-induced reactive oxygen species formation, caspase-3 activation and death. Mechanistic studies in mice suggest the existence of multiple molecular contributors to the neuroprotective effects of NAPE-PLD deletion, including suppression of Rac1 activity and attenuated transcription of several genes (Cadps, Casp9, Egln1, Kcnj6, Spen, and Uchl1) implicated in dopamine neuron survival and/or Parkinson's disease. The findings point to a previously unrecognized role for NAPE-PLD in the regulation of dopamine neuron function, which may be linked to the control of NAPE homeostasis in membranes.

Gender specific decrease of a set of circulating N-acylphosphatidyl ethanolamines (NAPEs) in the plasma of Parkinson's disease patients

INTRODUCTION

Current markers of Parkinson's disease (PD) fail to detect the early progression of disease state. Conversely, current omics techniques allow the investigation of hundreds of molecules potentially altered by disease conditions. Based on evidence previously collected by our group in a mouse model of PD, we speculated that a particular set of circulating lipids might be significantly altered by the pathology.

OBJECTIVES

The aim of current study was to evaluate the potential of a particular set of N-acyl-phosphatidylethanolamines (NAPEs) as potential non-invasive plasma markers of ongoing neurodegeneration from Parkinson's disease in human subjects.

METHODS

A panel of seven NAPEs were quantified by LC-MS/MS in the plasma of 587 individuals (healthy controls, n = 319; Parkinson's disease, n = 268); Random Forest classification and statistical modeling was applied to compare Parkinson's disease versus controls. All p-values obtained in different tests were corrected for multiplicity by controlling the false discovery rate (FDR).

RESULTS

The results indicate that this panel of NAPEs is able to distinguish female PD patients from the corresponding healthy controls. Further to this, the observed downregulation of these NAPEs is in line with the results in plasma of a mouse model of Parkinson's (6-OHDA).

CONCLUSIONS

In the current study we have shown the downregulation of NAPEs in plasma of PD patients and we thus speculate that these lipids might serve as candidate biomarkers for PD. We also suggest a molecular mechanism, explaining our findings, which involves gut microbiota.

Mast Cell-Derived Histamine Regulates Liver Ketogenesis via Oleoylethanolamide Signaling

The conversion of lipolysis-derived fatty acids into ketone bodies (ketogenesis) is a crucial metabolic adaptation to prolonged periods of food scarcity. The process occurs primarily in liver mitochondria and is initiated by fatty-acid-mediated stimulation of the ligand-operated transcription factor, peroxisome proliferator-activated receptor-α (PPAR-α). Here, we present evidence that mast cells contribute to the control of fasting-induced ketogenesis via a paracrine mechanism that involves secretion of histamine into the hepatic portal circulation, stimulation of liver H₁ receptors, and local biosynthesis of the high-affinity PPAR-α agonist, oleoylethanolamide (OEA). Genetic or pharmacological interventions that disable any one of these events, including mast cell elimination, deletion of histamine- or OEA-synthesizing enzymes, and H₁ blockade, blunt ketogenesis without affecting lipolysis. The results reveal an unexpected role for mast cells in the regulation of systemic fatty-acid homeostasis, and suggest that OEA may act in concert with lipolysis-derived fatty acids to activate liver PPAR-α and promote ketogenesis.

A new retrospective, multi-evidence veterinary drug screening method using drift tube ion mobility mass spectrometry

RATIONALE

The retrospectivity (the ability to retrospect to a previously unknown compound in raw data) is very meaningful for food safety and risk assessment when facing new emerging drugs. Accurate mass and retention time based screening may lead false positive and false negative results so new retrospective, reliable platform is desirable.

METHODS

Different concentration levels of standards with and without matrix were analyzed using ion mobility (IM)-quadrupole-time-of-flight (Q-TOF) for collecting retrospective accurate mass, retention time, drift time and tandem MS evidence for identification in a single experiment. The isomer separation ability of IM and the four-dimensional (4D) feature abundance quantification abilities were evaluated for veterinary drugs for the first time.

RESULTS

The sensitivity of the IM-Q-TOF workflow was obviously higher than that of the traditional database searching algorithm [find by formula (FbF) function] for Q-TOF. In addition, the IM-Q-TOF workflow contained most of the results from FbF and removed the false positive results. Some isomers were separated by IM and the 4D feature abundance quantitation removed interference with similar accurate mass and showed good linearity.

CONCLUSION

A new retrospective, multi-evidence platform was built for veterinary drug screening in a single experiment. The sensitivity was significantly improved and the data can be used for quantification. The platform showed its potential to be used for food safety and risk assessment.

Lipid Cell Biology: A Focus on Lipids in Cell Division

Cells depend on hugely diverse lipidomes for many functions. The actions and structural integrity of the plasma membrane and most organelles also critically depend on membranes and their lipid components. Despite the biological importance of lipids, our understanding of lipid engagement, especially the roles of lipid hydrophobic alkyl side chains, in key cellular processes is still developing. Emerging research has begun to dissect the importance of lipids in intricate events such as cell division. This review discusses how these structurally diverse biomolecules are spatially and temporally regulated during cell division, with a focus on cytokinesis. We analyze how lipids facilitate changes in cellular morphology during division and how they participate in key signaling events. We identify which cytokinesis proteins are associated with membranes, suggesting lipid interactions. More broadly, we highlight key unaddressed questions in lipid cell biology and techniques, including mass spectrometry, advanced imaging, and chemical biology, which will help us gain insights into the functional roles of lipids.

Improving the discovery of secondary metabolite natural products using ion mobility-mass spectrometry

Secondary metabolite discovery requires an unbiased, comprehensive workflow to detect unknown unknowns for which little to no molecular knowledge exists. Untargeted mass spectrometry-based metabolomics is a powerful platform, particularly when coupled with ion mobility for high-throughput gas-phase separations to increase peak capacity and obtain gas-phase structural information. Ion mobility data are described by the amount of time an ion spends in the drift cell, which is directly related to an ion's collision cross section (CCS). The CCS parameter describes the size, shape, and charge of a molecule and can be used to characterize unknown metabolomic species. Here, we describe current and emerging applications of ion mobility-mass spectrometry for prioritization, discovery and structure elucidation, and spatial/temporal characterization.

Green light for lipid fingerprinting

The use of targeted lipidomic approaches for the analysis of plant lipids has steadily increased during recent years. We review recent developments of these methods and suggest the introduction of discovery lipidomics as additional approach through a new workflow, lipid fingerprinting, that integrates the advantages of shotgun lipidomics (quantitative data) with LC-MS-based strategies (higher resolution and/or coverage). This article is part of a Special Issue entitled:BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

Recent advances in expanding the coverage of the lipidome

The lipidome comprises a large array of molecules with diverse physicochemical properties. Lipids are structural components of cells, act as a source of energy, and function as signaling mediators. Alterations in lipid metabolism are involved in the onset and progression of a variety of diseases, including metabolic syndrome and cancer. Because of this, interest in lipidomics, the comprehensive characterization of the lipidome by mass spectrometry, has intensified in recent years. However, obtaining a truly complete overview of all lipids in a sample has remained very challenging due to their enormous structural diversity. Here, we provide an overview of the collection of analytical approaches used to study various lipid classes, emphasizing innovations in sample preparation and liquid chromatography-mass spectrometry (LC-MS). Additionally, we provide practical suggestions for increasing the coverage of the lipidome.

Drift tube ion mobility and four-dimensional molecular feature extraction enable data-independent tandem mass spectrometric 'omics' analysis without quadrupole selection

RATIONALE

Quadrupole-based tandem mass spectrometry (MS/MS) plays a critical role in 'omics' studies. However, when a particular m/z precursor is selected by the quadrupole, ions other than the precursor are not transmitted through, and the sensitivity and dynamic range thus diminish. Therefore, separation techniques such as ion mobility (IM) are coupled with MS/MS to improve it.

METHODS

In this workflow, every IM-mass spectrometry (MS) scan was followed by one high-voltage collision energy (CE) scan. The precursors were separated in IM drift time and dissociated after IM; the four-dimensional molecular feature extraction (4D MFE) algorithm was used to align the precursors and their MS/MS spectra based on retention time and drift time distribution. A complicated peptide mixture was selected to exemplify the workflow in a proteomics study.

RESULTS

The new IM-MS-based workflow achieved similar performance in finding proteins compared to the traditional quadrupole-based MS/MS method. However, a significant difference was found between the proteins found by these two methods. For the four concentration levels analyzed, at least 23% more proteins were found by combining the new methods than only using the traditional quadrupole-based MS/MS method.

CONCLUSIONS

The established workflow used the 4D MFE algorithm to analyze a complicated 4D dataset and was demonstrated to find more proteins not found by the traditional quadrupole-based MS/MS method in proteomics application. It is thus an important complementary MS/MS mode for 'omics' studies. Copyright © 2016 John Wiley & Sons, Ltd.

Tandem Mass Spectrometry in Combination with Product Ion Mobility for the Identification of Phospholipids

Concerted tandem and traveling wave ion mobility mass spectrometry (CTS analysis) is a unique method that results in a four-dimensional data set including nominal precursor ion mass, product ion mobility, accurate mass of product ion, and ion abundance. This nontargeted lipidomics CTS approach was applied in both positive- and negative-ion mode to phospholipids present in human serum, and the data set was used to evaluate the value of product ion mobility in identifying lipids in a complex mixture. It was determined that the combination of diagnostic product ions and unique collisional cross-section values of product ions is a powerful tool in the structural identification of lipids in a complex biological sample.

Analytical pitfalls and challenges in clinical metabolomics

Metabolomics-based strategies have become an integral part of modern clinical research, allowing for a better understanding of pathophysiological conditions and disease mechanisms, as well as providing innovative tools for more adequate diagnostic and prognosis approaches. Metabolomics is considered an essential tool in precision medicine, which aims for personalized prevention and tailor-made treatments. Nevertheless, multiple pitfalls may be encountered in clinical metabolomics during the entire workflow, hampering the quality of the data and, thus, the biological interpretation. This review describes the challenges underlying metabolomics-based experiments, discussing step by step the potential pitfalls of the analytical process, including study design, sample collection, storage, as well as preparation, chromatographic and electrophoretic separation, detection and data analysis. Moreover, it offers practical solutions and strategies to tackle these challenges, ensuring the generation of high-quality data.