Assessment of altered lipid homeostasis by HILIC-ion mobility-mass spectrometry-based lipidomics

Several common methods of making vesicles (except an emulsion method) capture intended lipid ratios

Researchers choose different methods of making giant unilamellar vesicles in order to satisfy different constraints of their experimental designs. A challenge of using a variety of methods is that each may produce vesicles of different lipid compositions, even if all vesicles are made from a common stock mixture. Here, we use mass spectrometry to investigate ratios of lipids in vesicles made by five common methods: electroformation on indium tin oxide slides, electroformation on platinum wires, gentle hydration, emulsion transfer, and extrusion. We made vesicles from either 5-component or binary mixtures of lipids chosen to span a wide range of physical properties: di(18:1)PC, di(16:0)PC, di(18:1)PG, di(12:0)PE, and cholesterol. For a mixture of all five of these lipids, ITO electroformation, Pt electroformation, gentle hydration, and extrusion methods result in only minor shifts (≤ 5 mol%) in lipid ratios of vesicles relative to a common stock solution. In contrast, emulsion transfer results in ∼80% less cholesterol than expected from the stock solution, which is counterbalanced by a surprising overabundance of saturated PC-lipid relative to all other phospholipids. Experiments using binary mixtures of some of the lipids largely support results from the 5-component mixture. Exact values of lipid ratios variations likely depend on the details of each method, so a broader conclusion is that experiments that increment lipid ratios in small steps will be highly sensitive to the method of lipid formation and to sample-to-sample variations, which are low (roughly ±2 mol% in the 5-component mixture and either scale proportionally with increasing mole fraction or remain low). Experiments that increment lipid ratios in larger steps or that seek to explain general trends or new phenomena will be less sensitive to the method used.

SIGNIFICANCE STATEMENT

Small changes to the amounts and types of lipids in membranes can drastically affect the membrane's behavior. Unfortunately, it is unknown whether (or to what extent) different methods of making vesicles alter the ratios of lipids in membranes, even when identical stock solutions are used. This presents challenges for researchers when comparing data with colleagues who use different methods. Here, we measure ratios of lipid types in vesicle membranes produced by five methods. We assess each method's reproducibility and compare resulting vesicle compositions across methods. In doing so, we provide a quantitative basis that the scientific community can use to estimate whether differences between their results can be simply attributed to differences between methods or to sample-to-sample variations.

MOCCal: A Multiomic CCS Calibrator for Traveling Wave Ion Mobility Mass Spectrometry

Ion mobility mass spectrometry (IM-MS) is a rapid, gas-phase separation technology that can resolve ions on the basis of their size-to-charge and mass-to-charge ratios. Since each class of biomolecule has a unique relationship between size and mass, IM-MS spectra of complex biological samples are organized into trendlines that each contain one type of biomolecule (i.e., lipid, peptide, metabolite). These trendlines can aid in the identification of unknown ions by providing a general classification, while more specific identifications require the conversion of IM arrival times to collision cross section (CCS) values to minimize instrument-to-instrument variability. However, the process of converting IM arrival times to CCS values varies between the different IM devices. Arrival times from traveling wave ion mobility (TWIM) devices must undergo a calibration process to obtain CCS values, which can impart biases if the calibrants are not structurally similar to the analytes. For multiomic mixtures, several different types of calibrants must be used to obtain the most accurate CCS values from TWIM platforms. Here we describe the development of a multiomic CCS calibration tool, MOCCal, to automate the assignment of unknown features to the power law calibration that provides the most accurate CCS value. MOCCal calibrates every experimental arrival time with up to three class-specific calibration curves and uses the difference (in Å2) between the calibrated TWCCSN2 value and DTCCSN2 vs m/z regression lines to determine the best calibration curve. Using real and simulated multiomic samples, we demonstrate that MOCCal provides accurately calibrated TWCCSN2 values for small molecules, lipids, and peptides.

Elucidating the impact of bacterial lipases, human serum albumin, and FASII inhibition on the utilization of exogenous fatty acids by Staphylococcus aureus

IMPORTANCE

Incorporation of host-derived exogenous fatty acids (eFAs), particularly unsaturated fatty acids (UFAs), by Staphylococcus aureus could affect the bacterial membrane fluidity and susceptibility to antimicrobials. In this work, we found that glycerol ester hydrolase (Geh) is the primary lipase hydrolyzing cholesteryl esters and, to a lesser extent, triglycerides and that human serum albumin (HSA) could serve as a buffer of eFAs, where low levels of HSA facilitate the utilization of eFAs but high levels of HSA inhibit it. The fact that the type II fatty acid synthesis (FASII) inhibitor, AFN-1252, leads to an increase in UFA content even in the absence of eFA suggests that membrane property modulation is part of its mechanism of action. Thus, Geh and/or the FASII system look to be promising targets to enhance S. aureus killing in a host environment by restricting eFA utilization or modulating membrane properties, respectively.

Membrane Lipids Augment Cell Envelope Stress Signaling and Resistance to Antibiotics and Antimicrobial Peptides in Enterococcus faecalis

Enterococci have evolved resistance mechanisms to protect their cell envelopes against bacteriocins and host cationic antimicrobial peptides (CAMPs) produced in the gastrointestinal environment. Activation of the membrane stress response has also been tied to resistance to the lipopeptide antibiotic daptomycin. However, the actual effectors mediating resistance have not been elucidated. Here, we show that the MadRS (formerly YxdJK) membrane antimicrobial peptide defense system controls a network of genes, including a previously uncharacterized three gene operon (madEFG) that protects the E. faecalis cell envelope from antimicrobial peptides. Constitutive activation of the system confers protection against CAMPs and daptomycin in the absence of a functional LiaFSR system and leads to persistence of cardiac microlesions in vivo. Moreover, changes in the lipid cell membrane environment alter CAMP susceptibility and expression of the MadRS system. Thus, we provide a framework supporting a multilayered envelope defense mechanism for resistance and survival coupled to virulence.

MALDI-IM-MS Imaging of Brain Sterols and Lipids in a Mouse Model of Smith-Lemli-Opitz Syndrome

Smith-Lemli-Opitz syndrome (SLOS) is a neurodevelopmental disorder caused by genetic mutations in the DHCR7 gene, encoding the enzyme 3β-hydroxysterol-Δ7-reductase (DHCR7) that catalyzes the last step of cholesterol synthesis. The resulting deficiency in cholesterol and accumulation of its precursor, 7-dehydrocholesterol (7-DHC), have a profound impact on brain development, which manifests as developmental delay, cognitive impairment, and behavioral deficits. To understand how the brain regions are differentially affected by the defective Dhcr7, we aim to map the regional distribution of sterols and other lipids in neonatal brains from a Dhcr7-KO mouse model of SLOS, using mass spectrometry imaging (MSI). MSI enables spatial localization of biomolecules in situ on the surface of a tissue section, which is particularly useful for mapping the changes that occur within a metabolic disorder such as SLOS, and in an anatomically complex organ such as the brain. In this work, using MALDI-ion mobility (IM)-MSI, we successfully determined the regional distribution of features that correspond to cholesterol, 7-DHC/desmosterol, and the precursor of desmosterol, 7-dehydrodesmosterol, in WT and Dhcr7-KO mice. Interestingly, we also observed m/z values that match the major oxysterol metabolites of 7-DHC (DHCEO and hydroxy-7-DHC), which displayed similar patterns as 7-DHC. We then identified brain lipids using m/z and CCS at the Lipid Species-level and curated a database of MALDIIM-MS-derived lipid CCS values. Subsequent statistical analysis of regions-of-interest allowed us to identify differentially expressed lipids between Dhcr7-KO and WT brains, which could contribute to defects in myelination, neurogenesis, neuroinflammation, and learning and memory in SLOS.

High-throughput analysis of lipidomic phenotypes of methicillin-resistant Staphylococcus aureus by coupling in situ 96-well cultivation and HILIC-ion mobility-mass spectrometry

Antimicrobial resistance is a major threat to human health as resistant pathogens spread globally, and the development of new antimicrobials is slow. Since many antimicrobials function by targeting cell wall and membrane components, high-throughput lipidomics for bacterial phenotyping is of high interest for researchers to unveil lipid-mediated pathways when dealing with a large number of lab-selected or clinical strains. However, current practice for lipidomic analysis requires the cultivation of bacteria on a large scale, which does not replicate the growth conditions for high-throughput bioassays that are normally carried out in 96-well plates, such as susceptibility tests, growth curve measurements, and biofilm quantitation. Analysis of bacteria grown under the same condition as other bioassays would better inform the differences in susceptibility and other biological metrics. In this work, a high-throughput method for cultivation and lipidomic analysis of antimicrobial-resistant bacteria was developed for standard 96-well plates exemplified by methicillin-resistant Staphylococcus aureus (MRSA). By combining a 30-mm liquid chromatography (LC) column with ion mobility (IM) separation, elution time could be dramatically shortened to 3.6 min for a single LC run without losing major lipid features. Peak capacity was largely rescued by the addition of the IM dimension. Through multi-linear calibration, the deviation of retention time can be limited to within 5%, making database-based automatic lipid identification feasible. This high-throughput method was further validated by characterizing the lipidomic phenotypes of antimicrobial-resistant mutants derived from the MRSA strain, W308, grown in a 96-well plate.

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.

Collision cross section measurement and prediction methods in omics

Omics studies such as metabolomics, lipidomics, and proteomics have become important for understanding the mechanisms in living organisms. However, the compounds detected are structurally different and contain isomers, with each structure or isomer leading to a different result in terms of the role they play in the cell or tissue in the organism. Therefore, it is important to detect, characterize, and elucidate the structures of these compounds. Liquid chromatography and mass spectrometry have been utilized for decades in the structure elucidation of key compounds. While prediction models of parameters (such as retention time and fragmentation pattern) have also been developed for these separation techniques, they have some limitations. Moreover, ion mobility has become one of the most promising techniques to give a fingerprint to these compounds by determining their collision cross section (CCS) values, which reflect their shape and size. Obtaining accurate CCS enables its use as a filter for potential analyte structures. These CCS values can be measured experimentally using calibrant-independent and calibrant-dependent approaches. Identification of compounds based on experimental CCS values in untargeted analysis typically requires CCS references from standards, which are currently limited and, if available, would require a large amount of time for experimental measurements. Therefore, researchers use theoretical tools to predict CCS values for untargeted and targeted analysis. In this review, an overview of the different methods for the experimental and theoretical estimation of CCS values is given where theoretical prediction tools include computational and machine modeling type approaches. Moreover, the limitations of the current experimental and theoretical approaches and their potential mitigation methods were discussed.

Molecular Basis of Cell Membrane Adaptation in Daptomycin-Resistant Enterococcus faecalis

Daptomycin is a last-resort lipopeptide antibiotic that disrupts cell membrane (CM) and peptidoglycan homeostasis. Enterococcus faecalis has developed a sophisticated mechanism to avoid daptomycin killing by re-distributing CM anionic phospholipids away from the septum. The CM changes are orchestrated by a three-component regulatory system, designated LiaFSR, with a possible contribution of cardiolipin synthase (Cls). However, the mechanism by which LiaFSR controls the CM response and the role of Cls are unknown. Here, we show that cardiolipin synthase activity is essential for anionic phospholipid redistribution and daptomycin resistance since deletion of the two genes ( cls1 and cls2 ) encoding Cls abolished CM remodeling. We identified LiaY, a transmembrane protein regulated by LiaFSR, as an important mediator of CM remodeling required for re-distribution of anionic phospholipid microdomains via interactions with Cls1. Together, our insights provide a mechanistic framework on the enterococcal response to cell envelope antibiotics that could be exploited therapeutically.

Elucidating the Impact of Bacterial Lipases, Human Serum Albumin, and FASII Inhibition on the Utilization of Exogenous Fatty Acids by Staphylococcus aureus

Staphylococcus aureus only synthesizes straight-chain or branched-chain saturated fatty acids (SCFAs or BCFAs) via the type II fatty acid synthesis (FASII) pathway, but as a highly adaptive pathogen, S. aureus can also utilize host-derived exogenous fatty acids (eFAs), including SCFAs and unsaturated fatty acids (UFAs). S. aureus secretes three lipases, Geh, sal1, and SAUSA300_0641, which could perform the function of releasing fatty acids from host lipids. Once released, the FAs are phosphorylated by the fatty acid kinase, FakA, and incorporated into the bacterial lipids. In this study, we determined the substrate specificity of S. aureus secreted lipases, the effect of human serum albumin (HSA) on eFA incorporation, and the effect of FASII inhibitor, AFN-1252, on eFA incorporation using comprehensive lipidomics. When grown with major donors of fatty acids, cholesteryl esters (CEs) and triglycerides (TGs), Geh was found to be the primary lipase responsible for hydrolyzing CEs, but other lipases could compensate for the function of Geh in hydrolyzing TGs. Lipidomics showed that eFAs were incorporated into all major S. aureus lipid classes and that fatty acid-containing HSA can serve as a source of eFAs. Furthermore, S. aureus grown with UFAs displayed decreased membrane fluidity and increased production of reactive oxygen species (ROS). Exposure to AFN-1252 enhanced UFAs in the bacterial membrane, even without a source of eFAs, indicating a FASII pathway modification. Thus, the incorporation of eFAs alters the S. aureus lipidome, membrane fluidity, and ROS formation, which could affect host-pathogen interactions and susceptibility to membrane-targeting antimicrobials.

Comparison of Data-Dependent Acquisition, Data-Independent Acquisition, and Parallel Reaction Monitoring in Trapped Ion Mobility Spectrometry-Time-of-Flight Tandem Mass Spectrometry-Based Lipidomics

The parallel accumulation-serial fragmentation (PASEF) approach based on trapped ion mobility spectrometry (TIMS) enables mobility-resolved fragmentation and a higher number of fragments in the same time period compared to conventional MS/MS experiments. Furthermore, the ion mobility dimension offers novel approaches for fragmentation. Using parallel reaction monitoring (prm), the ion mobility dimension allows a more accurate selection of precursor windows, while using data-independent aquisition (dia) spectral quality is improved through ion-mobility filtering. Owing to favorable implementation in proteomics, the transferability of these PASEF modes to lipidomics is of great interest, especially as a result of the high complexity of analytes with similar fragments. However, these novel PASEF modes have not yet been thoroughly evaluated for lipidomics applications. Therefore, data-dependent acquisition (dda)-, dia-, and prm-PASEF were compared using hydrophilic interaction liquid chromatography (HILIC) for phospholipid class separation in human plasma samples. Results show that all three PASEF modes are generally suitable for usage in lipidomics. Although dia-PASEF achieves a high sensitivity in generating MS/MS spectra, the fragment-to-precursor assignment for lipids with both, similar retention time as well as ion mobility, was difficult in HILIC-MS/MS. Therefore, dda-PASEF is the method of choice to investigate unknown samples. However, the best data quality was achieved by prm-PASEF, owing to the focus on fragmentation of specified targets. The high selectivity and sensitivity in generating MS/MS spectra of prm-PASEF could be a potential alternative for targeted lipidomics, e.g., in clinical applications.

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.

Differential Contributions of Distinct Free Radical Peroxidation Mechanisms to the Induction of Ferroptosis

Ferroptosis is a form of regulated cell death driven by lipid peroxidation of polyunsaturated fatty acids (PUFAs). Lipid peroxidation can propagate through either the hydrogen-atom transfer (HAT) or peroxyl radical addition (PRA) mechanism. However, the contribution of the PRA mechanism to the induction of ferroptosis has not been studied. In this study, we aim to elucidate the relationship between the reactivity and mechanisms of lipid peroxidation and ferroptosis induction. We found that while some peroxidation-reactive lipids, such as 7-dehydrocholesterol, vitamins D3 and A, and coenzyme Q10, suppress ferroptosis, both nonconjugated and conjugated PUFAs enhanced cell death induced by RSL3, a ferroptosis inducer. Importantly, we found that conjugated PUFAs, including conjugated linolenic acid (CLA 18:3) and conjugated linoleic acid (CLA 18:2), can induce or potentiate ferroptosis much more potently than nonconjugated PUFAs. We next sought to elucidate the mechanism underlying the different ferroptosis-inducing potency of conjugated and nonconjugated PUFAs. Lipidomics revealed that conjugated and nonconjugated PUFAs are incorporated into distinct cellular lipid species. The different peroxidation mechanisms predict the formation of higher levels of reactive electrophilic aldehydes from conjugated PUFAs than nonconjugated PUFAs, which was confirmed by aldehyde-trapping and mass spectrometry. RNA sequencing revealed that protein processing in the endoplasmic reticulum and proteasome are among the most significantly upregulated pathways in cells treated with CLA 18:3, suggesting increased ER stress and activation of unfolded protein response. These results suggest that protein damage by lipid electrophiles is a key step in ferroptosis.

Integrating the potential of ion mobility spectrometry-mass spectrometry in the separation and structural characterisation of lipid isomers

It is increasingly evident that a more detailed molecular structure analysis of isomeric lipids is critical to better understand their roles in biological processes. The occurrence of isomeric interference complicates conventional tandem mass spectrometry (MS/MS)-based determination, necessitating the development of more specialised methodologies to separate lipid isomers. The present review examines and discusses recent lipidomic studies based on ion mobility spectrometry combined with mass spectrometry (IMS-MS). Selected examples of the separation and elucidation of structural and stereoisomers of lipids are described based on their ion mobility behaviour. These include fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterol lipids. Recent approaches for specific applications to improve isomeric lipid structural information using direct infusion, coupling imaging, or liquid chromatographic separation workflows prior to IMS-MS are also discussed, including: 1) strategies to improve ion mobility shifts; 2) advanced tandem MS methods based on activation of lipid ions with electrons or photons, or gas-phase ion-molecule reactions; and 3) the use of chemical derivatisation techniques for lipid characterisation.

Revealing the differences in collision cross section values of small organic molecules acquired by different instrumental designs and prediction models

The number of open access databases containing experimental and predicted collision cross section (CCS) values is rising and leads to their increased use for compound identification. However, the reproducibility of reference values with different instrumental designs and the comparison between predicted and experimental CCS values is still under evaluation. This study compared experimental CCS values of 56 small molecules (Contaminants of Emerging Concern) acquired by both drift tube (DT) and travelling wave (TW) ion mobility mass spectrometry (IM-MS). The TWIM-MS included two instrumental designs (Synapt G2 and VION). The experimental ^TWCCS_N2 values obtained by the TWIM-MS systems showed absolute percent errors (APEs) < 2% in comparison to experimental DTIMS data, indicating a good correlation between the datasets. Furthermore, ^TWCCS_N2 values of [M - H]^- ions presented the lowest APEs. An influence of the compound class on APEs was observed. The applicability of prediction models based on artificial neural networks (ANN) and multivariate adaptive regression splines (MARS), both built using TWIM-MS data, was investigated for the first time for the prediction of ^DTCCS_N2 values. For [M+H]⁺ and [M - H]^- ions, the 95th percentile confidence intervals of observed APEs were comparable to values reported for both models indicating a good applicability for DTIMS predictions. For the prediction of ^DTCCS_N2 values of [M+Na]⁺ ions, the MARS based model provided the best results with 73.9% of the ions showing APEs below the threshold reported for [M+Na]⁺. Finally, recommendations for database transfer and applications of prediction models for future DTIMS studies are made.

Ion Mobility Shift Reagents for Lipid Double Bonds Based on Paternò-Büchi Photoderivatization with Halogenated Acetophenones

The Paternò-Büchi (PB) reaction is a cycloaddition reaction between a carbon-carbon double bond (C═C) and a photochemically excited carbonyl-containing compound. The constrained ring formed between the C═C bond and the PB reagent is more susceptible to fragmentation by collision-induced dissociation, which facilitates identification of the C═C position within the fatty acyl tails of lipids. Although the original PB reaction using acetone had a low yield of derivatized lipids and therefore a low yield of diagnostic ions, a new generation of PB reagents based on halogenated acetophenones has improved the reaction yield substantially. In this study, we investigated the use of halogenated PB reagents and ion mobility to improve the identification of PB-derivatized lipids by shifting them out of the densely populated lipid region of ion mobility-mass spectrometry (IM-MS) space. Several halogenated PB reagents containing fluorine, chlorine and bromine were investigated for their ability to decrease the collision cross-section (CCS) values of derivatized lipids and yield sufficient intensity for both the derivatized lipid and its diagnostic ions. We found that 4'-chloro-2',6'-difluoroacetophenone (CDFAP) displayed the best performance, with an average decrease in CCS of 4.4% and yield of derivatized lipids and diagnostic ions comparable to the trifluorinated acetophenone reagent proposed by the Xia group. The unique isotope pattern resulting from the chlorine substituent aided in identification of the derivatized lipids and their diagnostic ions, as well. We further demonstrate that derivatization with CDFAP preserves the separation of lipids classes in IM-MS space.

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.

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.

Evolution of Enterococcus faecium in Response to a Combination of Daptomycin and Fosfomycin Reveals Distinct and Diverse Adaptive Strategies

Infections caused by vancomycin-resistant Enterococcus faecium (VREfm) are an important public health threat. VREfm isolates have become increasingly resistant to the front-line antibiotic daptomycin (DAP). As such, the use of DAP combination therapies with other antibiotics like fosfomycin (FOS) has received increased attention. Antibiotic combinations could extend the efficacy of currently available antibiotics and potentially delay the onset of further resistance. We investigated the potential for E. faecium HOU503, a clinical VREfm isolate that is DAP and FOS susceptible, to develop resistance to a DAP-FOS combination. Of particular interest was whether the genetic drivers for DAP-FOS resistance might be epistatic and, thus, potentially decrease the efficacy of a combinatorial approach in either inhibiting VREfm or in delaying the onset of resistance. We show that resistance to DAP-FOS could be achieved by independent mutations to proteins responsible for cell wall synthesis for FOS and in altering membrane dynamics for DAP. However, we did not observe genetic drivers that exhibited substantial cross-drug epistasis that could undermine the DAP-FOS combination. Of interest was that FOS resistance in HOU503 was largely mediated by changes in phosphoenolpyruvate (PEP) flux as a result of mutations in pyruvate kinase (pyk). Increasing PEP flux could be a readily accessible mechanism for FOS resistance in many pathogens. Importantly, we show that HOU503 was able to develop DAP resistance through a variety of biochemical mechanisms and was able to employ different adaptive strategies. Finally, we showed that the addition of FOS can prolong the efficacy of DAP and slow down DAP resistance in vitro.

Recent developments in data acquisition, treatment and analysis with ion mobility-mass spectrometry for lipidomics

Lipids are involved in many biological processes and their study is constantly increasing. To identify a lipid among thousand requires of reliable methods and techniques. Ion Mobility (IM) can be coupled with Mass Spectrometry (MS) to increase analytical selectivity in lipid analysis of lipids. IM-MS has experienced an enormous development in several aspects, including instrumentation, sensitivity, amount of information collected and lipid identification capabilities. This review summarizes the latest developments in IM-MS analyses for lipidomics and focusses on the current acquisition modes in IM-MS, the approaches for the pre-treatment of the acquired data and the subsequent data analysis. Methods and tools for the calculation of Collision Cross Section (CCS) values of analytes are also reviewed. CCS values are commonly studied to support the identification of lipids, providing a quasi-orthogonal property that increases the confidence level in the annotation of compounds and can be matched in CCS databases. The information contained in this review might be of help to new users of IM-MS to decide the adequate instrumentation and software to perform IM-MS experiments for lipid analyses, but also for other experienced researchers that can reconsider their routines and protocols. This article is protected by copyright. All rights reserved.

A High Throughput Lipidomics Method Using Scheduled Multiple Reaction Monitoring

Lipid compositions of cells, tissues, and bio-fluids are complex, with varying concentrations and structural diversity making their identification challenging. Newer methods for comprehensive analysis of lipids are thus necessary. Herein, we propose a targeted-mass spectrometry based lipidomics screening method using a combination of variable retention time window and relative dwell time weightage. Using this method, we identified more than 1000 lipid species within 24-min. The limit of detection varied from the femtomolar to the nanomolar range. About 883 lipid species were detected with a coefficient of variance <30%. We used this method to identify plasma lipids altered due to vitamin B12 deficiency and found a total of 18 lipid species to be altered. Some of the lipid species with ω-6 fatty acid chains were found to be significantly increased while ω-3 decreased in vitamin B12 deficient samples. This method enables rapid screening of a large number of lipid species in a single experiment and would substantially advance our understanding of the role of lipids in biological processes.

Lipidomics Profiling of HepG2 Cells and Interference by Mycotoxins Based on UPLC-TOF-IMS

Discovering the fungus-infected or mycotoxin-contaminated biomarkers is significant for systems biology since the metabolites in biological samples have significant polarity differences in both stochastic gene expression and microenvironmental change. Here, we aim to establish a comprehensive method for a lipidome by ion mobility mass spectrometry (IMS) merged with chemometrics to accurately find out the more scientific markers of cell interference by mycotoxins and for pathogenesis exploration and drug development. The differences in the abundances of several small molecules found in these metabolites were explored through multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), to further screen biomarkers. Good applicability and predictability were demonstrated by R²(X) and Q² (R² = 0.959, Q² = 0.999). Five compounds with m/z values of 512.502 8, 540.5343, 722.525 8, 787.667 5, and 813.683 0 were selected as markers, and four of them were further confirmed by chemical standards (i.e., MSMS of m/z 813.683 0 covering m/z 86.0978, 125.0008, 184.0745, and 185.0781). In summary, we demonstrated the integration of UPLC-TOF-IMS and the chemometrics approach to elucidate identified biomarkers, which also provides a new way of thinking for covering lipid biomarkers or prognostic indicators for mycotoxins.

Temporal changes in the brain lipidome during neurodevelopment of Smith-Lemli-Opitz syndrome mice

Neurodevelopment is an intricately orchestrated program of cellular events that occurs with tight temporal and spatial regulation. While it is known that the development and proper functioning of the brain, which is the second most lipid rich organ behind adipose tissue, greatly rely on lipid metabolism and signaling, the temporal lipidomic changes that occur throughout the course of neurodevelopment have not been investigated. Smith-Lemli-Opitz syndrome is a metabolic disorder caused by genetic mutations in the DHCR7 gene, leading to defective 3β-hydroxysterol-Δ⁷-reductase (DHCR7), the enzyme that catalyzes the last step of the Kandutsch-Russell pathway of cholesterol synthesis. Due to the close regulatory relationship between sterol and lipid homeostasis, we hypothesize that altered or dysregulated lipid metabolism beyond the primary defect of cholesterol biosynthesis is present in the pathophysiology of SLOS. Herein, we applied our HILIC-IM-MS method and LiPydomics Python package to streamline an untargeted lipidomics analysis of developing mouse brains in both wild-type and Dhcr7-KO mice, identifying lipids at Level 3 (lipid species level: lipid class/subclass and fatty acid sum composition). We compared relative lipid abundances throughout development, from embryonic day 12.5 to postnatal day 0 and determined differentially expressed brain lipids between wild-type and Dhcr7-KO mice at specific developmental time points, revealing lipid metabolic pathways that are affected in SLOS beyond the cholesterol biosynthesis pathway, such as glycerolipid, glycerophospholipid, and sphingolipid metabolism. Implications of the altered lipid metabolic pathways in SLOS pathophysiology are discussed.

Mass Spectrometry as a Crucial Analytical Basis for Omics Sciences

This review is devoted to the consideration of mass spectrometric platforms as applied to omics sciences. The most significant attention is paid to omics related to life sciences (genomics, proteomics, meta-bolomics, lipidomics, glycomics, plantomics, etc.). Mass spectrometric approaches to solving the problems of petroleomics, polymeromics, foodomics, humeomics, and exosomics, related to inorganic sciences, are also discussed. The review comparatively presents the advantages of various principles of separation and mass spectral techniques, complementary derivatization, used to obtain large arrays of various structural and quantitative information in the mentioned omics sciences.

Untargeted Lipidomics of Vesicular Stomatitis Virus-Infected Cells and Viral Particles

The viral lifecycle is critically dependent upon host lipids. Enveloped viral entry requires fusion between viral and cellular membranes. Once an infection has occurred, viruses may rely on host lipids for replication and egress. Upon exit, enveloped viruses derive their lipid bilayer from host membranes during the budding process. Furthermore, host lipid metabolism and signaling are often hijacked to facilitate viral replication. We employed an untargeted HILIC-IM-MS lipidomics approach and identified host lipid species that were significantly altered during vesicular stomatitis virus (VSV) infection. Many glycerophospholipid and sphingolipid species were modified, and ontological enrichment analysis suggested that the alterations to the lipid profile change host membrane properties. Lysophosphatidylcholine (LPC), which can contribute to membrane curvature and serve as a signaling molecule, was depleted during infection, while several ceramide sphingolipids were augmented during infection. Ceramide and sphingomyelin lipids were also enriched in viral particles, indicating that sphingolipid metabolism is important during VSV infection.

A Novel Approach to Characterize the Lipidome of Marine Archaeon Nitrosopumilus maritimus by Ion Mobility Mass Spectrometry

Archaea are differentiated from the other two domains of life by their biomolecular characteristics. One such characteristic is the unique structure and composition of their lipids. Characterization of the whole set of lipids in a biological system (the lipidome) remains technologically challenging. This is because the lipidome is innately complex, and not all lipid species are extractable, separable, or ionizable by a single analytical method. Furthermore, lipids are structurally and chemically diverse. Many lipids are isobaric or isomeric and often indistinguishable by the measurement of mass or even their fragmentation spectra. Here we developed a novel analytical protocol based on liquid chromatography ion mobility mass spectrometry to enhance the coverage of the lipidome and characterize the conformations of archaeal lipids by their collision cross-sections (CCSs). The measurements of ion mobility revealed the gas-phase ion chemistry of representative archaeal lipids and provided further insights into their attributions to the adaptability of archaea to environmental stresses. A comprehensive characterization of the lipidome of mesophilic marine thaumarchaeon, Nitrosopumilus maritimus (strain SCM1) revealed potentially an unreported phosphate- and sulfate-containing lipid candidate by negative ionization analysis. It was the first time that experimentally derived CCS values of archaeal lipids were reported. Discrimination of crenarchaeol and its proposed stereoisomer was, however, not achieved with the resolving power of the SYNAPT G2 ion mobility system, and a high-resolution ion mobility system may be required for future work. Structural and spectral libraries of archaeal lipids were constructed in non-vendor-specific formats and are being made available to the community to promote research of Archaea by lipidomics.

High-resolution imaging and identification of biomolecules using Nano-DESI coupled to ion mobility spectrometry

Simultaneous spatial localization and structural characterization of molecules in complex biological samples currently represents an analytical challenge for mass spectrometry imaging (MSI) techniques. In this study, we describe a novel experimental platform, which substantially expands the capabilities and enhances the depth of chemical information obtained in high spatial resolution MSI experiments performed using nanospray desorption electrospray ionization (nano-DESI). Specifically, we designed and constructed a portable nano-DESI MSI platform and coupled it with a drift tube ion mobility (IM) spectrometer-mass spectrometer. We demonstrate imaging of drift time-separated ions with a high spatial resolution of better than ∼25 μm using uterine tissues on day 4 of pregnancy in mice. Collision cross-section measurements provide unique molecular descriptors of molecules observed in nano-DESI-IM-MSI necessary for their unambiguous identification by comparison with databases. Meanwhile, isomer-specific imaging reveals variations in the isomeric composition across the tissue. Furthermore, IM separation efficiently eliminates isobaric and isomeric interferences originating from solvent peaks, overlapping isotopic peaks of endogenous molecules extracted from the tissue, and products of in-source fragmentation, which is critical to obtaining accurate concentration gradients in the sample using MSI. The structural information provided by the IM separation substantially expands the molecular specificity of high-resolution MSI necessary for unraveling the complexity of biological systems.

Synergy Between Beta-Lactams and Lipo-, Glyco-, and Lipoglycopeptides, Is Independent of the Seesaw Effect in Methicillin-Resistant Staphylococcus aureus

Methicillin-resistant S. aureus (MRSA) are resistant to beta-lactams, but synergistic activity between beta-lactams and glycopeptides/lipopeptides is common. Many have attributed this synergy to the beta-lactam-glycopeptide seesaw effect; however, this association has not been rigorously tested. The objective of this study was to determine whether the seesaw effect is necessary for synergy and to measure the impact of beta-lactam exposure on lipid metabolism. We selected for three isogenic strains with reduced susceptibility to vancomycin, daptomycin, and dalbavancin by serial passaging the MRSA strain N315. We used whole genome sequencing to identify genetic variants that emerged and tested for synergy between vancomycin, daptomycin, or dalbavancin in combination with 6 beta-lactams with variable affinity for staphylococcal penicillin binding proteins (PBPs), including nafcillin, meropenem, ceftriaxone, ceftaroline, cephalexin, and cefoxitin, using time-kills. We observed that the seesaw effect with each beta-lactam was variable and the emergence of the seesaw effect for a particular beta-lactam was not necessary for synergy between that beta-lactam and vancomycin, daptomycin, or dalbavancin. Synergy was more commonly observed with vancomycin and daptomycin based combinations than dalbavancin in time-kills. Among the beta-lactams, cefoxitin and nafcillin were the most likely to exhibit synergy using the concentrations tested, while cephalexin was the least likely to exhibit synergy. Synergy was more common among the resistant mutants than the parent strain. Interestingly N315-D1 and N315-DAL0.5 both had mutations in vraTSR and walKR despite their differences in the seesaw effect. Lipidomic analysis of all strains exposed to individual beta-lactams at subinhibitory concentrations suggested that in general, the abundance of cardiolipins (CLs) and most free fatty acids (FFAs) positively correlated with the presence of synergistic effects while abundance of phosphatidylglycerols (PGs) and lysylPGs mostly negatively correlated with synergistic effects. In conclusion, the beta-lactam-glycopeptide seesaw effect and beta-lactam-glycopeptide synergy are distinct phenomena. This suggests that the emergence of the seesaw effect may not have clinical importance in terms of predicting synergy. Further work is warranted to characterize strains that don't exhibit beta-lactam synergy to identify which strains should be targeted with combination therapy and which ones cannot and to further investigate the potential role of CLs in mediating synergy.

Approaches to Heterogeneity in Native Mass Spectrometry

Native mass spectrometry (MS) is aimed at preserving and determining the native structure, composition, and stoichiometry of biomolecules and their complexes from solution after they are transferred into the gas phase. Major improvements in native MS instrumentation and experimental methods over the past few decades have led to a concomitant increase in the complexity and heterogeneity of samples that can be analyzed, including protein-ligand complexes, protein complexes with multiple coexisting stoichiometries, and membrane protein-lipid assemblies. Heterogeneous features of these biomolecular samples can be important for understanding structure and function. However, sample heterogeneity can make assignment of ion mass, charge, composition, and structure very challenging due to the overlap of tens or even hundreds of peaks in the mass spectrum. In this review, we cover data analysis, experimental, and instrumental advances and strategies aimed at solving this problem, with an in-depth discussion of theoretical and practical aspects of the use of available deconvolution algorithms and tools. We also reflect upon current challenges and provide a view of the future of this exciting field.

Revealing Fatty Acid Heterogeneity in Staphylococcal Lipids with Isotope Labeling and RPLC-IM-MS

Up to 80% of the fatty acids in Staphylococcus aureus membrane lipids are branched, rather than straight-chain, fatty acids. The branched fatty acids (BCFAs) may have either an even or odd number of carbons, and the branch position may be at the penultimate carbon (iso) or the antepenultimate (anteiso) carbon of the tail. This results in two sets of isomeric fatty acid species with the same number of carbons that cannot be resolved by mass spectrometry. The isomer/isobar challenge is further complicated when the mixture of BCFAs and straight-chain fatty acids (SCFAs) are esterified into diacylated lipids such as the phosphatidylglycerol (PG) species of the S. aureus membrane. No conventional chromatographic method has been able to resolve diacylated lipids containing mixtures of SCFAs, anteiso-odd, iso-odd, and iso-even BCFAs. A major hurdle to method development in this area is the lack of relevant analytical standards for lipids containing BCFA isomers. The diversity of the S. aureus lipidome and its naturally high levels of BCFAs present an opportunity to explore the potential of resolving diacylated lipids containing BCFAs and SFCAs. Using our knowledge of lipid and fatty acid biosynthesis in S. aureus, we have used a stable-isotope-labeling strategy to develop and validate a 30 min C18 reversed-phase liquid chromatography method combined with traveling-wave ion mobility-mass spectrometry to provide resolution of diacylated lipids based on the number of BCFAs that they contain.

A versatile method to separate complex lipid mixtures using 1-butanol as eluent in a reverse-phase UHPLC-ESI-MS system

Simple, robust and versatile LC-MS based methods add to the rapid assessment of the lipidome of biological cells. Here we present a versatile RP-UHPLC-MS method using 1-butanol as the eluent, specifically designed to separate different highly hydrophobic lipids. This method is capable of separating different lipid classes of glycerophospholipid standards, in addition to phospholipids of the same class with a different acyl chain composition. The versatility of this method was demonstrated through analysis of lipid extracts of the bacterium Escherichia coli and the archaeon Sulfolobus acidocaldarius. In contrast to 2-propanol-based methods, the 1-butanol-based mobile phase is capable of eluting highly hydrophobic analytes such as cardiolipins, tetraether lipids and mycolic acids during the gradient instead of the isocratic purge phase, resulting in an enhanced separation of cardiolipins and extending the analytical range for RPLC.

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.

PI5P4Ks drive metabolic homeostasis through peroxisome-mitochondria interplay

PI5P4Ks are a class of phosphoinositide kinases that phosphorylate PI-5-P to PI-4,5-P₂. Distinct localization of phosphoinositides is fundamental for a multitude of cellular functions. Here, we identify a role for peroxisomal PI-4,5-P₂ generated by the PI5P4Ks in maintaining energy balance. We demonstrate that PI-4,5-P₂ regulates peroxisomal fatty acid oxidation by mediating trafficking of lipid droplets to peroxisomes, which is essential for sustaining mitochondrial metabolism. Using fluorescent-tagged lipids and metabolite tracing, we show that loss of the PI5P4Ks significantly impairs lipid uptake and β-oxidation in the mitochondria. Further, loss of PI5P4Ks results in dramatic alterations in mitochondrial structural and functional integrity, which under nutrient deprivation is further exacerbated, causing cell death. Notably, inhibition of the PI5P4Ks in cancer cells and mouse tumor models leads to decreased cell viability and tumor growth, respectively. Together, these studies reveal an unexplored role for PI5P4Ks in preserving metabolic homeostasis, which is necessary for tumorigenesis.

Ion Mobility-High-Resolution Mass Spectrometry (IM-HRMS) for the Analysis of Contaminants of Emerging Concern (CECs): Database Compilation and Application to Urine Samples

Ion mobility mass spectrometry (IM-MS)-derived collision cross section (CCS) values can serve as a valuable additional identification parameter within the analysis of compounds of emerging concern (CEC) in human matrices. This study introduces the first comprehensive database of ^DTCCS_N2 values of 148 CECs and their metabolites including bisphenols, alternative plasticizers (AP), organophosphate flame retardants (OP), perfluoroalkyl chemicals (PFAS), and others. A total of 311 ions were included in the database, whereby the ^DTCCS_N2 values for 113 compounds are reported for the first time. For 105 compounds, more than one ion is reported. Moreover, the ^DTCCS_N2 values of several isomeric CECs and their metabolites are reported to allow a distinction between isomers. Comprehensive quality assurance guidelines were implemented in the workflow of acquiring ^DTCCS_N2 values to ensure reproducible experimental conditions. The reliability and reproducibility of the complied database were investigated by analyzing pooled human urine spiked with 30 AP and OP metabolites at two concentration levels. For all investigated metabolites, the ^DTCCS_N2 values measured in urine showed a percent error of <1% in comparison to database values. ^DTCCS_N2 values of OP metabolites showed an average percent error of 0.12% (50 ng/mL in urine) and 0.15% (20 ng/mL in urine). For AP metabolites, these values were 0.10 and 0.09%, respectively. These results show that the provided database can be of great value for enhanced identification of CECs in environmental and human matrices, which can advance future suspect screening studies on CECs.

Methods of Lipidomic Analysis: Extraction, Derivatization, Separation, and Identification of Lipids

Lipidomics refers to the large-scale study of pathways and networks of cellular lipids in biological systems. A lipidomic analysis often involves the identification and quantification of the thousands of cellular lipid molecular species within a complex biological sample and therefore requires a well optimized method for lipid profiling. In this chapter, the methods for lipidomic analysis, including sample collection and preparation, lipid derivatization and separation, mass spectrometric identification of lipids, data processing and interpretation, and quality control, are overviewed.

LICAR: An Application for Isotopic Correction of Targeted Lipidomic Data Acquired with Class-Based Chromatographic Separations Using Multiple Reaction Monitoring

Lipidomics is developing as an important area in biomedical and clinical research. Reliable quantification of lipid species is required for clinical translation of lipidomic studies. Hydrophilic interaction chromatography (HILIC), normal-phase liquid chromatography (NPLC), and supercritical fluid chromatography (SFC) are commonly used techniques in lipidomics and provide class-based separation of lipids. While co-elution of lipid species and their internal standards is an advantage for accurate quantification, it leads to isotopic overlap between species of the same lipid class. In shotgun lipidomics, isotopic correction is typically done based on elemental formulas of precursor ions. In multiple reaction monitoring (MRM) analyses, however, this approach should not be used, as the overall contribution of heavy isotopes to the MRM transitions' intensities depends on their location in the molecule with respect to the fragmentation pattern. We present an algorithm, provided in the R programming language, for isotopic correction in class-based separation using MRM, extracting relevant structural information from MRM transitions to apply adequate isotopic correction factors. Using standards, we show that our algorithm accurately estimates the isotopic contribution of isotopologues to MRM transitions' measured intensities. Using human plasma as an example, we demonstrate the necessity of adequate isotopic correction for accurate quantitation of lipids measured by MRM with class-based chromatographic separation. We show that over a third of the measured phosphatidylcholine species had their intensity corrected by more than 10%. This isotopic correction algorithm and R-implemented application enable a more accurate quantification of lipids in class-based separation-MRM, a prerequisite for successful translation of lipidomic applications.

LiPydomics: A Python Package for Comprehensive Prediction of Lipid Collision Cross Sections and Retention Times and Analysis of Ion Mobility-Mass Spectrometry-Based Lipidomics Data

Comprehensive profiling of lipid species in a biological sample, or lipidomics, is a valuable approach to elucidating disease pathogenesis and identifying biomarkers. Currently, a typical lipidomics experiment may track hundreds to thousands of individual lipid species. However, drawing biological conclusions requires multiple steps of data processing to enrich significantly altered features and confident identification of these features. Existing solutions for these data analysis challenges (i.e., multivariate statistics and lipid identification) involve performing various steps using different software applications, which imposes a practical limitation and potentially a negative impact on reproducibility. Hydrophilic interaction liquid chromatography-ion mobility-mass spectrometry (HILIC-IM-MS) has shown advantages in separating lipids through orthogonal dimensions. However, there are still gaps in the coverage of lipid classes in the literature. To enable reproducible and efficient analysis of HILIC-IM-MS lipidomics data, we developed an open-source Python package, LiPydomics, which enables performing statistical and multivariate analyses ("stats" module), generating informative plots ("plotting" module), identifying lipid species at different confidence levels ("identification" module), and carrying out all functions using a user-friendly text-based interface ("interactive" module). To support lipid identification, we assembled a comprehensive experimental database of m/z and CCS of 45 lipid classes with 23 classes containing HILIC retention times. Prediction models for CCS and HILIC retention time for 22 and 23 lipid classes, respectively, were trained using the large experimental data set, which enabled the generation of a large predicted lipid database with 145,388 entries. Finally, we demonstrated the utility of the Python package using Staphylococcus aureus strains that are resistant to various antimicrobials.

Probing Gas-Phase-Clustering Thermodynamics with Ion Mobility-Mass Spectrometry: Association Energies of Phenylalanine Ions with Gas-Phase Alcohols

Vapor assisted mobility shift measurements were made with atmospheric pressure drift-tube ion mobility-mass spectrometry (IM-MS) to determine the thermodynamic properties of weakly bound ion-molecule clusters formed from protonated phenylalanine and neutral vapor molecules with hydroxyl functional groups. Relative binding energies and gas-phase association energies of amino acid ions clustered with small organic molecules have been established previously using high-pressure mass spectrometry. However, the issue of volatility largely prohibits the use of high-pressure mass spectrometry for the determination of gas-phase associations of amino acid ions clustered with neutral vapor molecules in many instances. In contrast, ion mobility measurements can be made at atmospheric pressure with volatile vapor additives near and above their boiling points, providing access to clustering equilibria not possible using high-vacuum techniques. In this study, we report the gas-phase association energies, enthalpies, and entropies for a protonated phenylalanine ion clustered with three neutral vapor molecules: 2-propanol, 1-butanol, and 2-pentanol based upon measurements at temperatures ranging from 120 to 180 °C. The gas-phase enthalpy and entropy changes ranged between -4 to -7 kcal/mol and -3 to 6 cal/(mol K), respectively. We found enthalpically favored ion-neutral cluster reactions for phenylalanine with entropic barriers for the formation of phenylalanine-1-butanol and phenylalanine-2-pentanol cluster ions, while phenylalanine-2-propanol cluster ion formation is both enthalpically and (weakly) entropically favorable. Under the measurement conditions examined, phenylalanine-vapor modifier cluster ion formation is clearly observed via shifts in the drift time for the three test vapor molecules. In comparison, negligible shifts in mobility are observed for protonated arginine exposed to the same vapor modifiers.

Quantitative and comparative study of plasmalogen molecular species in six edible shellfishes by hydrophilic interaction chromatography mass spectrometry

Shellfishes contain plasmalogens correlating to the functions of brain, heart, etc. Herein, a mild acid hydrolysis and hydrophilic interaction chromatography (HILIC) tandem mass spectrometry method was developed for analyzing plasmalogens in six shellfish species. A total of 19 plasmalogen molecular species were successfully identified, including nine phosphatidylcholine plasmalogen (plasPC), seven phosphatidylethanolamine plasmalogen (plasPE), and three phosphatidylserine plasmalogen (plasPS). The quantitative results indicated that mussel (32 μg·mg^-1) possessed the highest content of plasmalogens, followed by oyster (21 μg·mg^-1) and razor clam (15 μg·mg^-1). The statistic models showed that the plasPE P-18:0/20:5 (m/z 748), plasPE P-16:0/22:2 & P-18:0/20:2 (m/z 754) and plasPS were the most contributing difference between shellfishes. The results indicated that this method was sensitive and precise to determine plasmalogens in shellfish, and mussel was demonstrated to be a good choice for the large-scale preparation of plasmalogens.

Lipidomic and Ultrastructural Characterization of the Cell Envelope of Staphylococcus aureus Grown in the Presence of Human Serum

Comprehensive lipidomics of S. aureus grown in the presence of human serum suggests that human serum lipids can associate with the cell envelope without being truly integrated into the lipid membrane. However, fatty acids derived from human serum lipids, including unsaturated fatty acids, can be incorporated into lipid classes that can be biosynthesized by S. aureus itself. Cholesteryl esters and triglycerides are found to be the major source of incorporated fatty acids upon hydrolysis by lipases. These findings have significant implications for the nature of the S. aureus cell surface when grown in vivo. Changes in phospholipid and glycolipid abundances and fatty acid composition could affect membrane biophysics and function and the activity of membrane-targeting antimicrobials. Finally, the association of serum lipids with the cell envelope has implications for the physicochemical nature of the cell surface and its interaction with host defense systems.

Staphylococcus aureus can incorporate exogenous straight-chain unsaturated and saturated fatty acids (SCUFAs and SCFAs, respectively) to replace some of the normally biosynthesized branched-chain fatty acids and SCFAs. In this study, the impact of human serum on the S. aureus lipidome and cell envelope structure was comprehensively characterized. When S. aureus was grown in the presence of 20% human serum, typical human serum lipids, such as cholesterol, sphingomyelin, phosphatidylethanolamines, and phosphatidylcholines, were present in the total lipid extracts. Mass spectrometry showed that SCUFAs were incorporated into all major S. aureus lipid classes, i.e., phosphatidylglycerols, lysyl-phosphatidylglycerols, cardiolipins, and diglucosyldiacylglycerols. Heat-killed S. aureus retained fewer serum lipids and failed to incorporate SCUFAs, suggesting that association and incorporation of serum lipids with S. aureus require a living or nondenatured cell. Cytoplasmic membranes isolated from lysostaphin-produced protoplasts of serum-grown cells retained serum lipids, but washing cells with Triton X-100 removed most of them. Furthermore, electron microscopy studies showed that serum-grown cells had thicker cell envelopes and associated material on the surface, which was partially removed by Triton X-100 washing. To investigate which serum lipids were preferentially hydrolyzed by S. aureus lipases for incorporation, we incubated individual serum lipid classes with S. aureus and found that cholesteryl esters (CEs) and triglycerides (TGs) are the major donors of the incorporated fatty acids. Further experiments using purified Geh lipase confirmed that CEs and TGs were the substrates of this enzyme. Thus, growth in the presence of serum altered the nature of the cell surface with implications for interactions with the host.

IMPORTANCE Comprehensive lipidomics of S. aureus grown in the presence of human serum suggests that human serum lipids can associate with the cell envelope without being truly integrated into the lipid membrane. However, fatty acids derived from human serum lipids, including unsaturated fatty acids, can be incorporated into lipid classes that can be biosynthesized by S. aureus itself. Cholesteryl esters and triglycerides are found to be the major source of incorporated fatty acids upon hydrolysis by lipases. These findings have significant implications for the nature of the S. aureus cell surface when grown in vivo. Changes in phospholipid and glycolipid abundances and fatty acid composition could affect membrane biophysics and function and the activity of membrane-targeting antimicrobials. Finally, the association of serum lipids with the cell envelope has implications for the physicochemical nature of the cell surface and its interaction with host defense systems.

SWATH-MS for metabolomics and lipidomics: critical aspects of qualitative and quantitative analysis

INTRODUCTION

While liquid chromatography coupled to mass spectrometric detection in the selected reaction monitoring detection mode offers the best quantification sensitivity for omics, the number of target analytes is limited, must be predefined and specific methods developed. Data independent acquisition (DIA), including SWATH using quadrupole time of flight or orbitrap mass spectrometers and generic acquisition methods, has emerged as a powerful alternative technique for quantitative and qualitative analyses since it can cover a wide range of analytes without predefinition.

OBJECTIVES

Here we review the current state of DIA, SWATH-MS and highlight novel acquisition strategies for metabolomics and lipidomics and opportunities for data analysis tools.

METHOD

Different databases were searched for papers that report developments and applications of DIA and in particular SWATH-MS in metabolomics and lipidomics.

RESULTS

DIA methods generate digital sample records that can be mined retrospectively as further knowledge is gained and, with standardized acquisition schemes, used in multiple studies. The different chemical spaces of metabolites and lipids require different specificities, hence different acquisition and data processing approaches must be considered for their analysis.

CONCLUSIONS

Although the hardware and acquisition modes are well defined for SWATH-MS, a major challenge for routine use remains the lack of appropriate software tools capable of handling large datasets and large numbers of analytes.

Breaking Down Structural Diversity for Comprehensive Prediction of Ion-Neutral Collision Cross Sections

Identification of unknowns is a bottleneck for large-scale untargeted analyses like metabolomics or drug metabolite identification. Ion mobility-mass spectrometry (IM-MS) provides rapid two-dimensional separation of ions based on their mobility through a neutral buffer gas. The mobility of an ion is related to its collision cross section (CCS) with the buffer gas, a physical property that is determined by the size and shape of the ion. This structural dependency makes CCS a promising characteristic for compound identification, but this utility is limited by the availability of high-quality reference CCS values. CCS prediction using machine learning (ML) has recently shown promise in the field, but accurate and broadly applicable models are still lacking. Here we present a novel ML approach that employs a comprehensive collection of CCS values covering a wide range of chemical space. Using this diverse database, we identified the structural characteristics, represented by molecular quantum numbers (MQNs), that contribute to variance in CCS and assessed the performance of a variety of ML algorithms in predicting CCS. We found that by breaking down the chemical structural diversity using unsupervised clustering based on the MQNs, specific and accurate prediction models for each cluster can be trained, which showed superior performance than a single model trained with all data. Using this approach, we have robustly trained and characterized a CCS prediction model with high accuracy on diverse chemical structures. An all-in-one web interface (https://CCSbase.net) was built for querying the CCS database and accessing the predictive model to support unknown compound identifications.

Mitochondrial Dysfunctions May Be One of the Major Causative Factors Underlying Detrimental Effects of Benzalkonium Chloride

Benzalkonium chloride (BAC) is currently the most commonly used antimicrobial preservative in ophthalmic solutions, nasal sprays, and cosmetics. However, a large number of clinical and experimental investigations showed that the topical administration of BAC-containing eye drops could cause a variety of ocular surface changes, from ocular discomfort to potential risk for future glaucoma surgery. BAC-containing albuterol may increase the risk of albuterol-related systemic adverse effects. BAC, commonly present in personal care products, in cosmetic products can induce irritation and dose-dependent changes in the cell morphology. The cationic nature of BAC (it is a quaternary ammonium) suggests that one of the major targets of BAC in the cell may be mitochondria, the only intracellular compartment charged negatively. However, the influence of BAC on mitochondria has not been clearly understood. Here, the effects of BAC on energy parameters of rat liver mitochondria as well as on yeast cells were examined. BAC, being a "weaker" uncoupler, potently inhibited respiration in state 3, diminished the mitochondrial membrane potential, caused opening of the Ca2+/Pi-dependent pore, blocked ATP synthesis, and promoted H₂O₂ production by mitochondria. BAC triggered oxidative stress and mitochondrial fragmentation in yeast cells. BAC-induced oxidative stress in mitochondria and yeast cells was almost totally prevented by the mitochondria-targeted antioxidant SkQ1; the protective effect of SkQ1 on mitochondrial fragmentation was only partial. Collectively, these data showed that BAC acts adversely on cell bioenergetics (especially on ATP synthesis) and mitochondrial dynamics and that its prooxidant effect can be partially prevented by the mitochondria-targeted antioxidant SkQ1.

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.

"Lipidomics": Mass spectrometric and chemometric analyses of lipids

Lipids are ubiquitous in the human organism and play essential roles as components of cell membranes and hormones, for energy storage or as mediators of cell signaling pathways. As crucial mediators of the human metabolism, lipids are also involved in metabolic diseases, cardiovascular and renal diseases, cancer and/or hepatological and neurological disorders. With rapidly growing evidence supporting the impact of lipids on both the genesis and progression of these diseases as well as patient wellbeing, the characterization of the human lipidome has gained high interest and importance in life sciences and clinical diagnostics within the last 15 years. This is mostly due to technically advanced molecular identification and quantification methods, mainly based on mass spectrometry. Mass spectrometry has become one of the most powerful tools for the identification of lipids. New lipidic mediators or biomarkers of diseases can be analysed by state-of-the art mass spectrometry techniques supported by sophisticated bioinformatics and biostatistics. The lipidomic approach has developed dramatically in the realm of life sciences and clinical diagnostics due to the available mass spectrometric methods and in particular due to the adaptation of biostatistical methods in recent years. Therefore, the current knowledge of lipid extraction methods, mass-spectrometric approaches, biostatistical data analysis, including workflows for the interpretation of lipidomic high-throughput data, are reviewed in this manuscript.