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

Lipidomics by HILIC-Ion Mobility-Mass Spectrometry

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

Metabolism of Benzalkonium Chlorides by Human Hepatic Cytochromes P450

Benzalkonium chlorides (BACs) are widely used as disinfectants in cleaning products, medical products, and the food processing industry. Despite a wide range of reported toxicities, limited studies have been conducted on the metabolism of these compounds in animal models and none in human-derived cells or tissues. In this work, we report on the metabolism of BACs in human liver microsomes (HLM) and by recombinant human hepatic cytochrome P450 (CYP) enzymes. BAC metabolism in HLM was NADPH-dependent and displayed apparent half-lives that increased with BAC alkyl chain length (C10 < C12 < C14 < C16), suggesting enhanced metabolic stability of the more lipophilic, longer chain BACs. Metabolites of d7-benzyl labeled BAC substrates retained all deuteriums and there was no evidence of N-dealkylation. Tandem mass spectrometry fragmentation of BAC metabolites confirmed that oxidation occurs on the alkyl chain region. Major metabolites of C10-BAC were identified as ω-hydroxy-, (ω-1)-hydroxy-, (ω, ω-1)-diol-, (ω-1)-ketone-, and ω-carboxylic acid-C10-BAC by liquid chromatography-mass spectrometry comparison with synthetic standards. In a screen of hepatic CYP isoforms, recombinant CYP2D6, CYP4F2, and CYP4F12 consumed substantial quantities of BAC substrates and produced the major microsomal metabolites. The use of potent pan-CYP4 inhibitor HET0016, the specific CYP2D6 inhibitor quinidine, or both confirmed major contributions of CYP4- and CYP2D6-mediated metabolism in the microsomal disappearance of BACs. Kinetic characterization of C10-BAC metabolite formation in HLM demonstrated robust Michaelis-Menten kinetic parameters for ω-hydroxylation (Vmax = 380 pmol/min/mg, Km = 0.69 μM) and (ω-1)-hydroxylation (Vmax = 126 pmol/min/mg, Km = 0.13 μM) reactions. This work illustrates important roles for CYP4-mediated ω-hydroxylation and CYP2D6/CYP4-mediated (ω-1)-hydroxylation during the hepatic elimination of BACs, an environmental contaminant of emerging concern. Furthermore, we demonstrate that CYP-mediated oxidation of C10-BAC mitigates the potent inhibition of cholesterol biosynthesis exhibited by this short-chain BAC.

LipidIMMS Analyzer: integrating multi-dimensional information to support lipid identification in ion mobility-mass spectrometry based lipidomics

SUMMARY

Ion mobility-mass spectrometry (IM-MS) has showed great application potential for lipidomics. However, IM-MS based lipidomics is significantly restricted by the available software for lipid structural identification. Here, we developed a software tool, namely, LipidIMMS Analyzer, to support the accurate identification of lipids in IM-MS. For the first time, the software incorporates a large-scale database covering over 260 000 lipids and four-dimensional structural information for each lipid [i.e. m/z, retention time (RT), collision cross-section (CCS) and MS/MS spectra]. Therefore, multi-dimensional information can be readily integrated to support lipid identifications, and significantly improve the coverage and confidence of identification. Currently, the software supports different IM-MS instruments and data acquisition approaches.

AVAILABILITY AND IMPLEMENTATION

The software is freely available at: http://imms.zhulab.cn/LipidIMMS/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A fast UPLC-HILIC method for an accurate quantification of dendrogenin A in human tissues

Dendrogenin A (DDA) is a newly-discovered steroidal alkaloid, which remains to date the first ever found in mammals. DDA is a cholesterol metabolites that induces cancer cell differentiation and death in vitro and in vivo, and thus behave like a tumor suppressor metabolite. Preliminary studies performed on 10 patients with estrogen receptor positive breast cancers (ER⁽⁺⁾BC) showed a strong decrease in DDA levels between normal matched tissue and tumors. This suggests that a deregulation on DDA metabolism is associated with breast carcinogenesis. To further investigate DDA metabolism on large cohorts of patients we have developed an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS) procedure for the quantification of DDA in liquid and in solid tissues. This method enabled the identification of DDA analogues such as its geometric isomer C17 and dendrogenin B (C26) in human samples showing that other 5,6α-epoxycholesterol conjugation products with biogenic amines exist as endogenous metabolites . We report here the first complete method of quantification of DDA in liquid and solid tissues using hydrophilic interaction liquid chromatography (HILIC). Two different methods of extraction using either a Bligh and Dyer organic extraction or protein precipitation were successfully applied to quantify DDA in solid and liquid tissues. The protein precipitation method was the fastest. The fact that this method is automatable opens up possibilities to study DDA metabolism in large cohorts of patients.

Characterization of the Impact of Drug Metabolism on the Gas-Phase Structures of Drugs Using Ion Mobility-Mass Spectrometry

Conventional strategies for drug metabolite identification employ a combination of liquid chromatography-mass spectrometry (LC-MS), which offers higher throughput but provides limited structural information, and nuclear magnetic resonance spectroscopy, which can achieves the most definitive identification but lacks throughput. Ion mobility-mass spectrometry (IM-MS) is a rapid, two-dimensional analysis that separates ions on the basis of their gas-phase size and shape (reflected by collision cross section, CCS) and their mass-to-charge (m/z) ratios. The rapid nature of IM separation combined with the structural information provided by CCS make IM-MS a promising technique for obtaining more structural information on drug metabolites without sacrificing analytical throughput. Here, we present an in vitro biosynthesis coupled with IM-MS strategy for rapid generation and analysis of drug metabolites. Drug metabolites were generated in vitro using pooled subcellular fractions derived from human liver and analyzed using a rapid flow injection-IM-MS method. We measured CCS values for 19 parent drugs and their 37 metabolites generated in vitro (78 values in total), representing a wide variety of metabolic modifications. Post-IM fragmentation and computational modeling were used to support metabolite identifications and explore the structural characteristics driving behaviors observed in IM separation. Overall, we found the effects of metabolic modifications on the gas-phase structures of the metabolites to be highly dependent upon the structural characteristics of the parent compounds and the specific position of the modification. This in vitro biosynthesis coupled with rapid IM-MS analysis workflow represents a promising platform for rapid and high-confidence identification of drug metabolites, applicable at a large scale.

Multi-omics investigation reveals benzalkonium chloride disinfectants alter sterol and lipid homeostasis in the mouse neonatal brain

Lipids are critical for neurodevelopment; therefore, disruption of lipid homeostasis by environmental chemicals is expected to have detrimental effects on this process. Previously, we demonstrated that the benzalkonium chlorides (BACs), a class of commonly used disinfectants, alter cholesterol biosynthesis and lipid homeostasis in neuronal cell cultures in a manner dependent on their alkyl chain length. However, the ability of BACs to reach the neonatal brain and alter sterol and lipid homeostasis during neurodevelopment in vivo has not been characterized. Therefore, the goal of this study was to use targeted and untargeted mass spectrometry and transcriptomics to investigate the effect of BACs on sterol and lipid homeostasis, and to predict the mechanism of toxicity of BACs on neurodevelopmental processes. After maternal dietary exposure to 120 mg BAC/kg body weight/day, we quantified BAC levels in the mouse neonatal brain, demonstrating for the first time that BACs can cross the blood-placental barrier and enter the developing brain. Transcriptomic analysis of neonatal brains using RNA sequencing revealed alterations in canonical pathways related to cholesterol biosynthesis, liver X receptor-retinoid X receptor (LXR/RXR) signaling, and glutamate receptor signaling. Mass spectrometry analysis revealed decreases in total sterol levels and downregulation of triglycerides and diglycerides, which were consistent with the upregulation of genes involved in sterol biosynthesis and uptake as well as inhibition of LXR signaling. In conclusion, these findings demonstrate that BACs target sterol and lipid homeostasis and provide new insights for the possible mechanisms of action of BACs as developmental neurotoxicants.

Hybrid SWATH/MS and HR-SRM/MS acquisition for phospholipidomics using QUAL/QUANT data processing

A hybrid SWATH/MS and HR-SRM/MS acquisition approach using multiple unit mass windows and 100 u precursor selection windows has been developed to interface with a chromatographic lipid class separation. The method allows for the simultaneous monitoring of sum compositions in MS1 and up to 48 lipids in MS2 per lipid class. A total of 240 lipid sum compositions from five phospholipid classes could be monitored in MS2 (HR-SRM/MS) while there was no limitation in the number of analytes in MS1 (HR-SIM/MS). On average, 92 lipid sum compositions and 75 lipid species could be quantified in human plasma samples. The robustness and precision of the workflow has been assessed using technical triplicates of the subject samples. Lipid identification was improved using a combined qualitative and quantitative data processing based on prediction instead of library search. Lipid class specific extracted ion currents of precursors and the corresponding molecular species fragments were extracted based on the information obtained from lipid building blocks and a combinatorial strategy. The SWATH/MS approach with the post-acquisition processing is not limited to the analyzed phospholipid classes and can be applied to other analytes and samples of interest. Graphical abstract.

Lipidomic consequences of phospholipid synthesis defects in Escherichia coli revealed by HILIC-ion mobility-mass spectrometry

Our understanding of phospholipid biosynthesis in Gram-positive and Gram-negative bacteria is derived from the prototypical Gram-negative organism Escherichia coli. The inner and outer membranes of E. coli are largely composed of phosphatidylethanolamine (PE), minor amounts of phosphatidylglycerol (PG) and cardiolipin (CL). We report here the utility of hydrophilic interaction liquid chromatography (HILIC) paired with ion mobility-mass spectrometry (IM-MS) for the comprehensive analysis of the E. coli lipidome. Using strains with chromosomal deletions in the PG and CL synthesis genes pgsA and clsABC, respectively, we show that defective phospholipid biosynthesis in E. coli results in fatty-acid specific changes in select lipid classes and the presence of the minor triacylated phospholipids, acylphosphatidyl glycerol (acylPG) and N-acylphosphatidylethanolamine (N-acylPE). Notably, acylPGs were accumulated in the clsABC-KO strain, but were absent in other mutant strains. The separation of 1-lyso and 2-lyso-phosphatidylethanolamines (lysoPEs) is demonstrated in both the HILIC and IM dimensions. Using our previously validated calibration method, collision cross section values of nearly 200 phospholipids found in E. coli were determined on a traveling wave IM-MS platform, including newly reported values for cardiolipins, positional isomers of lysoPEs, acylPGs and N-acylPEs.

Lipidomics Reveals Changes in Metabolism, Indicative of Anesthetic-Induced Neurotoxicity in Developing Brains

Numerous studies have demonstrated that treatment with high dose anesthetics for a prolonged duration induces brain injury in infants. However, whether anesthetic treatment leading to neurotoxicity is associated with alterations in lipid metabolism and homeostasis is still unclear. This review first outlines the lipidomics tools for analysis of lipid molecular species that can inform alterations in lipid species after anesthetic exposure. Then the available data indicating anesthetics cause changes in lipid profiles in the brain and serum of infant monkeys in preclinical studies are summarized, and the potential mechanisms leading to the altered lipid metabolism and their association with anesthetic-induced brain injury are also discussed. Finally, whether lipid changes identified in serum of infant monkeys can serve as indicators for the early detection of anesthetic-induced brain injury is described. We believe extensive studies on alterations in lipids after exposure to anesthetics will allow us to better understand anesthetic-induced neurotoxicity, unravel its underlying biochemical mechanisms, and develop powerful biomarkers for early detection/monitoring of the toxicity.

Increasing Compound Identification Rates in Untargeted Lipidomics Research with Liquid Chromatography Drift Time-Ion Mobility Mass Spectrometry

Unknown metabolites represent a bottleneck in untargeted metabolomics research. Ion mobility-mass spectrometry (IM-MS) facilitates lipid identification because it yields collision cross section (CCS) information that is independent from mass or lipophilicity. To date, only a few CCS values are publicly available for complex lipids such as phosphatidylcholines, sphingomyelins, or triacylglycerides. This scarcity of data limits the use of CCS values as an identification parameter that is orthogonal to mass, MS/MS, or retention time. A combination of lipid descriptors was used to train five different machine learning algorithms for automatic lipid annotations, combining accurate mass ( m/ z), retention time (RT), CCS values, carbon number, and unsaturation level. Using a training data set of 429 true positive lipid annotations from four lipid classes, 92.7% correct annotations overall were achieved using internal cross-validation. The trained prediction model was applied to an unknown milk lipidomics data set and allowed for class 3 level annotations of most features detected in this application set according to Metabolomics Standards Initiative (MSI) reporting guidelines.

Contemporary lipidomic analytics: opportunities and pitfalls

Recent advances in analytical techniques have greatly enhanced the depth of coverage, however lipidomic studies are still restricted to analysing only a subset of known lipids. Numerous complementary techniques are used for investigation of cellular lipidomes, including mass spectrometry (MS), nuclear magnetic resonance and vibrational spectroscopy. The development in electrospray ionization (ESI) MS has accelerated lipidomics research in the past two decades and represents one of the most widely used technique. The versatility of ESI-MS systems allows development of methods to detect and quantify a large diversity of lipid species and classes. However, highly targeted and specific approaches can preclude global analysis of many lipid classes. Indeed, experimental procedures are generally optimised for the lipid species, or lipid class of interest. Therefore, careful consideration of experimental procedures is required for characterisation of biological lipidomes. The current review will describe the lipidomic approaches for considering tissue lipid physiology. Discussion of the main sequences in a lipidomics workflow will be presented, including preparation of samples, accurate quantitation of lipid species and statistical modelling.

Characterization of the Mechanisms of Daptomycin Resistance among Gram-Positive Bacterial Pathogens by Multidimensional Lipidomics

Previous work suggests that altered lipid metabolism may be associated with daptomycin resistance in Gram-positive pathogens, but lipidomic changes underlying resistance are not fully understood. We performed untargeted lipidomics by using three-dimensional hydrophilic interaction liquid chromatography-ion mobility-mass spectrometry (HILIC-IM-MS) to characterize alterations in the lipidomes of daptomycin-susceptible and -resistant isogenic strain pairs of Enterococcus faecalis, Staphylococcus aureus, and Corynebacterium striatum. We first validated the HILIC-IM-MS method by replicating the expected alterations of phospholipid metabolism in the previously studied E. faecalis strain pairs, such as reduced phosphatidylglycerols (PGs), while also revealing additional changes in cardiolipins (CLs), lysyl-PGs, and glycolipids. Whole-genome sequencing of the S. aureus and C. striatum strains found that daptomycin resistance was associated with mutations in pgsA, which encodes phosphatidylglycerophosphate synthase, as well as mutations in genes affecting fatty acid biosynthesis and cell wall metabolism. Lipidomics revealed significantly decreased levels of PGs, CLs, and amino acid-modified PGs, as well as accumulation of lipids upstream of PGs, such as glycolipids and phosphatidic acids, in the resistant strains. Notably, the glycolipids, diglucosyldiacylglycerols, were significantly elevated in a fatty acid-dependent manner in the daptomycin-resistant S. aureus strain. In daptomycin-resistant C. striatum, which has a unique cell envelope architecture, the glycolipids, glucuronosyldiacylglycerols, and phosphatidylinositols were significantly elevated. These results demonstrate that alteration of lipid metabolism via mutations in pgsA is a common mechanism of daptomycin resistance in two distinct species of Gram-positive bacteria and point to the potential contribution of altered glycolipid and fatty acid compositions to daptomycin resistance. IMPORTANCE This work comprehensively characterizes lipidomic changes underlying daptomycin resistance in three Gram-positive bacterial species, E. faecalis, S. aureus, and C. striatum, by using a novel three-dimensional lipidomics methodology based on advanced mass spectrometry. We demonstrated a number of advantages of our method in comparison with other methods commonly used in the field, such as high molecular specificity, sensitivity, and throughput. Whole-genome sequencing of the S. aureus and C. striatum strains identified mutations in pgsA, which encodes phosphatidylglycerophosphate synthase, in both resistant strains. Lipidomics revealed significantly decreased levels of lipids downstream of PgsA, as well as accumulation of lipids upstream of PgsA in the resistant strains. Furthermore, we found that changes in individual molecular species of each lipid class depend on the their specific fatty acid compositions. The characteristic changes in individual lipid species could be used as biomarkers for identifying underlying resistance mechanisms and for evaluating potential therapies.

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

Lipids are a large and highly diverse family of biomolecules, which play essential structural, storage and signalling roles in cells and tissues. Although traditional mass spectrometry (MS) approaches used in lipidomics are highly sensitive and selective, lipid analysis remains challenging due to the chemical diversity of lipid structures, multiple isobaric species and incomplete separation using many forms of chromatography. Ion mobility (IM) separates ions in the gas phase based on their physicochemical properties. Addition of IM to the traditional lipidomic workflow both enhances separation of complex lipid mixtures, beneficial for lipid identification, and improves isomer resolution. Herein, we discuss the recent developments in IM-MS for lipidomics.

Advancing the large-scale CCS database for metabolomics and lipidomics at the machine-learning era

Metabolomics and lipidomics aim to comprehensively measure the dynamic changes of all metabolites and lipids that are present in biological systems. The use of ion mobility-mass spectrometry (IM-MS) for metabolomics and lipidomics has facilitated the separation and the identification of metabolites and lipids in complex biological samples. The collision cross-section (CCS) value derived from IM-MS is a valuable physiochemical property for the unambiguous identification of metabolites and lipids. However, CCS values obtained from experimental measurement and computational modeling are limited available, which significantly restricts the application of IM-MS. In this review, we will discuss the recently developed machine-learning based prediction approach, which could efficiently generate precise CCS databases in a large scale. We will also highlight the applications of CCS databases to support metabolomics and lipidomics.

Large-Scale Structural Characterization of Drug and Drug-Like Compounds by High-Throughput Ion Mobility-Mass Spectrometry

Ion mobility-mass spectrometry (IM-MS) can provide orthogonal information, i.e., m/z and collision cross section (CCS), for the identification of drugs and drug metabolites. However, only a small number of CCS values are available for drugs, which limits the use of CCS as an identification parameter and the assessment of structure–function relationships of drugs using IM-MS. Here, we report the development of a rapid workflow for the measurement of CCS values of a large number of drug or drug-like molecules in nitrogen on the widely available traveling wave IM-MS (TWIM-MS) platform. Using a combination of small molecule and polypeptide CCS calibrants, we successfully determined the nitrogen CCS values of 1425 drug or drug-like molecules in the MicroSource Discovery Systems’ Spectrum Collection using flow injection analysis of 384-well plates. Software was developed to streamline data extraction, processing, and calibration. We found that the overall drug collection covers a wide CCS range for the same mass, suggesting a large structural diversity of these drugs. However, individual drug classes appear to occupy a narrow and unique space in the CCS–mass 2D spectrum, suggesting a tight structure–function relationship for each class of drugs with a specific target. We observed bimodal distributions for several antibiotic species due to multiple protomers, including the known fluoroquinolone protomers and the new finding of cephalosporin protomers. Lastly, we demonstrated the utility of the high-throughput method and drug CCS database by quickly and confidently confirming the active component in a pharmaceutical product.

LipidCCS: Prediction of Collision Cross-Section Values for Lipids with High Precision To Support Ion Mobility-Mass Spectrometry-Based Lipidomics

The use of collision cross-section (CCS) values derived from ion mobility-mass spectrometry (IM-MS) has been proven to facilitate lipid identifications. Its utility is restricted by the limited availability of CCS values. Recently, the machine-learning algorithm-based prediction (e.g., MetCCS) is reported to generate CCS values in a large-scale. However, the prediction precision is not sufficient to differentiate lipids due to their high structural similarities and subtle differences on CCS values. To address this challenge, we developed a new approach, namely, LipidCCS, to precisely predict lipid CCS values. In LipidCCS, a set of molecular descriptors were optimized using bioinformatic approaches to comprehensively describe the subtle structure differences for lipids. The use of optimized molecular descriptors together with a large set of standard CCS values for lipids (458 in total) to build the prediction model significantly improved the precision. The prediction precision of LipidCCS was externally validated with median relative errors (MRE) of ∼1% using independent data sets across different instruments (Agilent DTIM-MS and Waters TWIM-MS) and laboratories. We also demonstrated that the improved precision in the predicted LipidCCS database (15 646 lipids and 63 434 CCS values in total) could effectively reduce false-positive identifications of lipids. Common users can freely access our LipidCCS web server for the following: (1) the prediction of lipid CCS values directly from SMILES structure; (2) database search; and (3) lipid match and identification. We believe LipidCCS will be a valuable tool to support IM-MS-based lipidomics. The web server is freely available on the Internet ( http://www.metabolomics-shanghai.org/LipidCCS/ ).

Analytical Techniques in Lipidomics: State of the Art

Current studies related to lipid identification and determination, or lipidomics in biological samples, are one of the most important issues in modern bioanalytical chemistry. There are many articles dedicated to specific analytical strategies used in lipidomics in various kinds of biological samples. However, in such literature, there is a lack of articles dedicated to a comprehensive review of the actual analytical methodologies used in lipidomics. The aim of this article is to characterize the lipidomics methods used in modern bioanalysis according to the methodological point of view: (1) chromatography/separation methods, (2) spectroscopic methods and (3) mass spectrometry and also hyphenated methods. In the first part, we discussed thin layer chromatography (TLC), high-pressure liquid chromatography (HPLC), gas chromatography (GC) and capillary electrophoresis (CE). The second part includes spectroscopic techniques such as Raman spectroscopy (RS), Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (NMR). The third part is a synthetic review of mass spectrometry, matrix-assisted laser desorption/ionization (MALDI), hyphenated methods, which include liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and also multidimensional techniques. Other aspects are the possibilities of the application of the described methods in lipidomics studies. Due to the fact that the exploration of new methods of lipidomics analysis and their applications in clinical and medical studies are still challenging for researchers working in life science, we hope that this review article will be very useful for readers.