Utilizing Skyline to analyze lipidomics data containing liquid chromatography, ion mobility spectrometry and mass spectrometry dimensions

A multiplexed targeted method for profiling of serum gangliosides and glycosphingolipids: application to GM2-gangliosidosis

The analysis of gangliosides and glycosphingolipids is crucial for understanding cellular membrane structure and function as well as to accurately diagnose certain inborn errors of metabolism. GM2-gangliosidosis represents a rare and fatal group of lysosomal storage disorders characterized by accumulation of GM2 gangliosides in various tissues and organs. These disorders arise due to deficiency or functional impairment of the β-hexosaminidase A or B enzymes, which are responsible for degradation of GM2 ganglioside. Deficient enzyme activity primarily leads to the accumulation of GM2 gangliosides within the lysosomes of cells. Accurate and rapid diagnostic methods that detect increased levels of GM2 gangliosides in patients with GM2-gangliosidosis can play a significant role in early diagnosis and appropriate treatment of this condition. To address this need, we developed a multiplexed liquid chromatography-tandem mass spectrometry method targeting 84 species of gangliosides and other glycosphingolipids involved in ganglioside metabolism. Reproducibility, linearity, extraction efficiency, and sample stability were evaluated and proof-of-concept data obtained from analysis of serum samples from confirmed cases of GM2-gangliosidosis. This method has the potential to simultaneously monitor the biosynthesis of gangliosides and the lysosomal catabolic pathway serving as a valuable tool for screening and diagnosing an important group of lysosomal storage disorders.

Evaluating Solid Phase Adsorption Toxin Tracking (SPATT) for passive monitoring of per- and polyfluoroalkyl substances (PFAS) with Ion Mobility Spectrometry-Mass Spectrometry (IMS-MS)

Detection and monitoring of per- and polyfluoroalkyl substances (PFAS) in aquatic environments has become an increasingly higher priority of regulatory agencies as public concern for human intake of these chemicals continues to grow. While many methods utilize active sampling strategies ("grab samples") for precise PFAS quantitation, here we evaluate the efficacy of low-cost passive sampling devices (Solid Phase Adsorption Toxin Tracking, or SPATTs) for spatial and temporal PFAS assessment of aquatic systems. For this study, passive samplers were initially deployed in North Carolina along the Cape Fear River during the summer and fall of 2016 and 2017. These were originally intended for the detection of microcystins and monitoring potentially harmful algal blooms, though this period also coincided with occurrences of PFAS discharge from a local fluorochemical manufacturer into the river. Additional samplers were then deployed in 2022 to evaluate changes in PFAS fingerprint and abundances. Assessment of PFAS showed legacy compounds were observed across almost all sampling sites over all 3 years (PFHxS, PFOS, PFHxA, etc.), while emerging replacement PFAS (e.g., Nafion byproducts) were predominantly localized downstream from the manufacturer. Furthermore, samplers deployed downstream from the manufacturer in 2022 noted sharp decreases in observed signal for replacement PFAS in comparison to samplers deployed in 2016 and 2017, indicating mitigation and remediation efforts in the area were able to reduce localized fluorochemical contamination.

Streamlining Phenotype Classification and Highlighting Feature Candidates: A Screening Method for Non-Targeted Ion Mobility Spectrometry-Mass Spectrometry (IMS-MS) Data

Nontargeted analysis (NTA) is increasingly utilized for its ability to identify key molecular features beyond known targets in complex samples. NTA is particularly advantageous in exploratory studies aimed at identifying phenotype-associated features or molecules able to classify various sample types. However, implementing NTA involves extensive data analyses and labor-intensive annotations. To address these limitations, we developed a rapid data screening capability compatible with NTA data collected on a liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) platform that allows for sample classification while highlighting potential features of interest. Specifically, this method aggregates the thousands of IMS-MS spectra collected across the LC space for each sample and collapses the LC dimension, resulting in a single summed IMS-MS spectrum for screening. The summed IMS-MS spectra are then analyzed with a bootstrapped Lasso technique to identify key regions or coordinates for phenotype classification via support vector machines. Molecular annotations are then performed by examining the features present in the selected coordinates, highlighting potential molecular candidates. To demonstrate this summed IMS-MS screening approach, we applied it to clinical plasma lipidomic NTA data and exposomic NTA data from water sites with varying contaminant levels. Distinguishing coordinates were observed in both studies, enabling the evaluation of phenotypic molecular annotations and resulting in screening models capable of classifying samples with up to a 25% increase in accuracy compared to models using annotated data.

Recent additions and access to a multidimensional lipidomic database containing liquid chromatography, ion mobility spectrometry, and tandem mass spectrometry information

The importance of lipids in biology continues to grow with their recent linkages to more diseases and conditions, microbiome fluctuations, and environmental exposures. These associations have motivated researchers to evaluate lipidomic changes in numerous matrices and studies. Lipidomic analyses, however, present numerous challenges as lipid species have broad chemistries that require different extraction methods and instrumental analyses to evaluate and separate their many isomers and isobars. Increasing knowledge about different lipid characteristics is therefore crucial for improving their separation and identification. Here, we present a multidimensional database for lipids analyzed on a platform combining reversed-phase liquid chromatography, drift tube ion mobility spectrometry, collision-induced dissociation, and mass spectrometry (RPLC-DTIMS-CID-MS). This platform and the different separation characteristics it provides enables more confident lipid annotations when compared to traditional tandem mass spectrometry platforms, especially when analyzing highly isomeric molecules such as lipids. This database expands on our previous publication containing only human plasma and bronchoalveolar lavage fluid lipids and provides experimental RPLC retention times, IMS collision cross section (CCS) values, and m/z information for 877 unique lipids from additional biofluids and tissues. Specifically, the database contains 1504 precursor [M + H]+, [M + NH4]+, [M + Na]+, [M-H]-, [M-2H]2-, [M + HCOO]-, and [M + CH3COO]- ion species and their associated CID fragments which are commonly targeted in clinical and environmental studies, in addition to being present in the chloroform layer of Folch extractions. Furthermore, this multidimensional RPLC-DTIMS-CID-MS database spans 5 lipid categories (fatty acids, sterols, sphingolipids, glycerolipids, and glycerophospholipids) and 24 lipid classes. We have also created a webpage (tarheels.live/bakerlab/databases/) to enhance the accessibility of this resource which will be populated regularly with new lipids as we identify additional species and integrate novel standards.

Lipid profiling identifies modifiable signatures of cardiometabolic risk in children and adolescents with obesity

Pediatric obesity is a progressive, chronic disease that can lead to serious cardiometabolic complications. Here we investigated the peripheral lipidome in 958 children and adolescents with overweight or obesity and 373 with normal weight, in a cross-sectional study. We also implemented a family-based, personalized program to assess the effects of obesity management on 186 children and adolescents in a clinical setting. Using mass spectrometry-based lipidomics, we report an increase in ceramides, alongside a decrease in lysophospholipids and omega-3 fatty acids with obesity metabolism. Ceramides, phosphatidylethanolamines and phosphatidylinositols were associated with insulin resistance and cardiometabolic risk, whereas sphingomyelins showed inverse associations. Additionally, a panel of three lipids predicted hepatic steatosis as effectively as liver enzymes. Lipids partially mediated the association between obesity and cardiometabolic traits. The nonpharmacological management reduced levels of ceramides, phospholipids and triglycerides, indicating that lowering the degree of obesity could partially restore a healthy lipid profile in children and adolescents.

Proteomic and Lipidomic Plasma Evaluations Reveal Biomarkers for Domoic Acid Toxicosis in California Sea Lions

Domoic acid is a neurotoxin secreted by the marine diatom genus, Pseudo-nitzschia , during toxic algal bloom events. California sea lions ( Zalophus californianus ) are exposed to domoic acid through ingestion of fish that feed on toxic diatoms, resulting in a domoic acid toxicosis (DAT), which can vary from mild to fatal. Sea lions with mild disease can be treated if toxicosis is detected early after exposure, therefore, rapid diagnosis of DAT is essential but also challenging. In this work, we performed multi-omics analyses, specifically proteomic and lipidomic, on blood samples from 31 California sea lions. Fourteen sea lions were diagnosed with DAT based on clinical signs and postmortem histological examination of brain tissue, and 17 had no evidence of DAT. Proteomic analyses revealed three apolipoproteins with statistically significant lower abundance in the DAT individuals compared to the non-DAT individuals. These proteins are known to transport lipids in the blood. Lipidomic analyses highlighted 29 lipid levels that were statistically different in the DAT versus non-DAT comparison, 28 of which were downregulated while only one was upregulated. Furthermore, of the 28 downregulated lipids, 15 were triglycerides, illustrating their connection with the perturbed apolipoproteins and showing their potential for use in rapid DAT diagnoses.

SYNOPSIS

Multi-omics evaluations reveal blood apolipoproteins and triglycerides are altered in domoic acid toxicosis in California sea lions.

GRAPHIC ABSTRACT

Elucidating the role of lipid interactions in stabilizing the membrane protein KcsA

The significant effects of lipid binding on the functionality of potassium channel KcsA have been validated by brilliant studies. However, the specific interactions between lipids and KcsA, such as binding parameters for each binding event, have not been fully elucidated. In this study, we employed native mass spectrometry to investigate the binding of lipids to KcsA and their effects on the channel. The tetrameric structure of KcsA remains intact even in the absence of lipid binding. However, the subunit architecture of the E71A mutant, which is constantly open at low pH, relies on tightly associated copurified lipids. Furthermore, we observed that lipids exhibit weak binding to KcsA at high pH when the channel is at a closed/inactivation state in the absence of permeant cation K+. This feeble interaction potentially facilitates the association of K+ ions, leading to the transition of the channel to a resting closed/open state. Interestingly, both anionic and zwitterionic lipids strongly bind to KcsA at low pH when the channel is in an open/inactivation state. We also investigated the binding patterns of KcsA with natural lipids derived from E. coli and Streptomyces lividans. Interestingly, lipids from E. coli exhibited much stronger binding affinity compared to the lipids from S. lividans. Among the natural lipids from S. lividans, free fatty acids and triacylglycerols demonstrated the tightest binding to KcsA, whereas no detectable binding events were observed with natural phosphatidic acid lipids. These findings suggest that the lipid association pattern in S. lividans, the natural host for KcsA, warrants further investigation. In conclusion, our study sheds light on the role of lipids in stabilizing KcsA and highlights the importance of specific lipid-protein interactions in modulating its conformational states.

Reproducible mass spectrometry data processing and compound annotation in MZmine 3

Untargeted mass spectrometry (MS) experiments produce complex, multidimensional data that are practically impossible to investigate manually. For this reason, computational pipelines are needed to extract relevant information from raw spectral data and convert it into a more comprehensible format. Depending on the sample type and/or goal of the study, a variety of MS platforms can be used for such analysis. MZmine is an open-source software for the processing of raw spectral data generated by different MS platforms. Examples include liquid chromatography-MS, gas chromatography-MS and MS-imaging. These data might typically be associated with various applications including metabolomics and lipidomics. Moreover, the third version of the software, described herein, supports the processing of ion mobility spectrometry (IMS) data. The present protocol provides three distinct procedures to perform feature detection and annotation of untargeted MS data produced by different instrumental setups: liquid chromatography-(IMS-)MS, gas chromatography-MS and (IMS-)MS imaging. For training purposes, example datasets are provided together with configuration batch files (i.e., list of processing steps and parameters) to allow new users to easily replicate the described workflows. Depending on the number of data files and available computing resources, we anticipate this to take between 2 and 24 h for new MZmine users and nonexperts. Within each procedure, we provide a detailed description for all processing parameters together with instructions/recommendations for their optimization. The main generated outputs are represented by aligned feature tables and fragmentation spectra lists that can be used by other third-party tools for further downstream analysis.

Assessing Per- and Polyfluoroalkyl Substances in Fish Fillet Using Non-Targeted Analyses

Per- and polyfluoroalkyl substances (PFAS) are a class of thousands of man-made chemicals that are persistent and highly stable in the environment. Fish consumption has been identified as a key route of PFAS exposure for humans. However, routine fish monitoring targets only a handful of PFAS, and non-targeted analyses have largely only evaluated fish from heavily PFAS-impacted waters. Here, we evaluated PFAS in fish fillets from recreational and drinking water sources in central North Carolina to assess whether PFAS are present in these fillets that would not be detected by conventional targeted methods. We used liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) to collect full scan feature data, performed suspect screening using an in-house library of 100 PFAS for high confidence feature identification, searched for additional PFAS features using non-targeted data analyses, and quantified perfluorooctanesulfonic acid (PFOS) in the fillet samples. A total of 36 PFAS were detected in the fish fillets, including 19 that would not be detected using common targeted methods, with a minimum of 6 and a maximum of 22 in individual fish. Median fillet PFOS levels were concerningly high at 11.6 to 42.3 ppb, and no significant correlation between PFOS levels and number of PFAS per fish was observed. Future PFAS monitoring in this region should target more of these 36 PFAS, and other regions not considered heavily PFAS contaminated should consider incorporating non-targeted analyses into ongoing fish monitoring studies.

Direct infusion-multiple reaction monitoring cubed (DI-MRM3) enables widely targeted bi-omics of Colla Corii Asini (Chinese name: Ejiao)

Food authenticity is extremely important and widely targeted bi-omics is a promising pipeline attributing to incorporating metabolomics and peptidomics. Colla Corii Asini (CCA, Ejiao) is one of the most popular tonic edible materials, with counterfeit and adulterated products being widespread. An attempt was devoted to develop a high-throughput and reliable DI-MRM3 program facilitating widely targeted bi-omics of CCA. Firstly, predictive MRM program captured metabolites and peptides in trypsin-digestive gelatins. After data alignment and structure annotation, primary parameters such as Q1 → Q3 → QLIT, CE, and EE were optimized for all 17 metabolites and 34 peptides by online ER-MS. Though a single run merely consumed 6.5 min, great selectivity was reached for each analyte. Statistical results showed that nine peptides contributed to distinguish CCA from other gelatins. After cross-validation with LC-MRM, DI-MRM3 was justified to be reproducible and high-throughput for widely targeted bi-omics of CCA, suggesting a meaningful tool for food authenticity.

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

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

Region-Specific Effects of Metformin on Gut Microbiome and Metabolome in High-Fat Diet-Induced Type 2 Diabetes Mouse Model

The glucose-lowering drug metformin alters the composition of the gut microbiome in patients with type 2 diabetes mellitus (T2DM) and other diseases. Nevertheless, most studies on the effects of this drug have relied on fecal samples, which provide limited insights into its local effects on different regions of the gut. Using a high-fat diet (HFD)-induced mouse model of T2DM, we characterize the spatial variability of the gut microbiome and associated metabolome in response to metformin treatment. Four parts of the gut as well as the feces were analyzed using full-length sequencing of 16S rRNA genes and targeted metabolomic analyses, thus providing insights into the composition of the microbiome and associated metabolome. We found significant differences in the gut microbiome and metabolome in each gut region, with the most pronounced effects on the microbiomes of the cecum, colon, and feces, with a significant increase in a variety of species belonging to Akkermansiaceae, Lactobacillaceae, Tannerellaceae, and Erysipelotrichaceae. Metabolomics analysis showed that metformin had the most pronounced effect on microbiome-derived metabolites in the cecum and colon, with several metabolites, such as carbohydrates, fatty acids, and benzenoids, having elevated levels in the colon; however, most of the metabolites were reduced in the cecum. Thus, a wide range of beneficial metabolites derived from the microbiome after metformin treatment were produced mainly in the colon. Our study highlights the importance of considering gut regions when understanding the effects of metformin on the gut microbiome and metabolome.

Investigating mouse hepatic lipidome dysregulation following exposure to emerging per- and polyfluoroalkyl substances (PFAS)

Per- and polyfluoroalkyl substances (PFAS) are environmental pollutants that have been associated with adverse health effects including liver damage, decreased vaccine responses, cancer, developmental toxicity, thyroid dysfunction, and elevated cholesterol. The specific molecular mechanisms impacted by PFAS exposure to cause these health effects remain poorly understood, however there is some evidence of lipid dysregulation. Thus, lipidomic studies that go beyond clinical triglyceride and cholesterol tests are greatly needed to investigate these perturbations. Here, we have utilized a platform coupling liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) separations to simultaneously evaluate PFAS bioaccumulation and lipid metabolism disruptions. For the study, liver samples collected from C57BL/6 mice exposed to either of the emerging PFAS hexafluoropropylene oxide dimer acid (HFPO-DA or "GenX") or Nafion byproduct 2 (NBP2) were assessed. Sex-specific differences in PFAS accumulation and liver size were observed for both PFAS, in addition to disturbed hepatic liver lipidomic profiles. Interestingly, GenX resulted in less hepatic bioaccumulation than NBP2 yet gave a higher number of significantly altered lipids when compared to the control group, implying that the accumulation of substances in the liver may not be a reliable measure of the substance's capacity to disrupt the liver's natural metabolic processes. Specifically, phosphatidylglycerols, phosphatidylinositols, and various specific fatty acyls were greatly impacted, indicating alteration of inflammation, oxidative stress, and cellular signaling processes due to emerging PFAS exposure. Overall, these results provide valuable insight into the liver bioaccumulation and molecular mechanisms of GenX- and NBP2-induced hepatotoxicity.

Recent Analytical Methodologies in Lipid Analysis

Lipids represent a large group of biomolecules that are responsible for various functions in organisms. Diseases such as diabetes, chronic inflammation, neurological disorders, or neurodegenerative and cardiovascular diseases can be caused by lipid imbalance. Due to the different stereochemical properties and composition of fatty acyl groups of molecules in most lipid classes, quantification of lipids and development of lipidomic analytical techniques are problematic. Identification of different lipid species from complex matrices is difficult, and therefore individual analytical steps, which include extraction, separation, and detection of lipids, must be chosen properly. This review critically documents recent strategies for lipid analysis from sample pretreatment to instrumental analysis and data interpretation published in the last five years (2019 to 2023). The advantages and disadvantages of various extraction methods are covered. The instrumental analysis step comprises methods for lipid identification and quantification. Mass spectrometry (MS) is the most used technique in lipid analysis, which can be performed by direct infusion MS approach or in combination with suitable separation techniques such as liquid chromatography or gas chromatography. Special attention is also given to the correct evaluation and interpretation of the data obtained from the lipid analyses. Only accurate, precise, robust and reliable analytical strategies are able to bring complex and useful lipidomic information, which may contribute to clarification of some diseases at the molecular level, and may be used as putative biomarkers and/or therapeutic targets.

CHRISTMAS: Chiral Pair Isobaric Labeling Strategy for Multiplexed Absolute Quantitation of Enantiomeric Amino Acids

Amino acids (AAs) in the d-form are involved in multiple pivotal neurological processes, although their l-enantiomers are most commonly found. Mass spectrometry-based analysis of low-abundance d-AAs has been hindered by challenging enantiomeric separation from l-AAs, low sensitivity for detection, and lack of suitable internal standards for accurate quantification. To address these critical gaps, N,N-dimethyl-l-leucine (l-DiLeu) tags are first validated as novel chiral derivatization reagents for chromatographic separation of 20 pairs of d/l-AAs, allowing the construction of a 4-plex isobaric labeling strategy for enantiomer-resolved quantification through single step tagging. Additionally, the creative design of N,N-dimethyl-d-leucine (d-DiLeu) reagents offers an alternative approach to generate analytically equivalent internal references of d-AAs using d-DiLeu-labeled l-AAs. By labeling cost-effective l-AA standards using paired d- and l-DiLeu, this approach not only enables absolute quantitation of both d-AAs and l-AAs from complex biological matrices with enhanced precision but also significantly boosts the combined signal intensities from all isobaric channels, greatly improving the detection and quantitation of low-abundance AAs, particularly d-AAs. We term this quantitative strategy CHRISTMAS, which stands for chiral pair isobaric labeling strategy for multiplexed absolute quantitation. Leveraging the ion mobility collision cross section (CCS) alignment, interferences from coeluting isomers/isobars are effectively filtered out to provide improved quantitative accuracy. From wild-type and Alzheimer's disease (AD) mouse brains, we successfully quantified 20 l-AAs and 5 d-AAs. The significant presence and differential trends of certain d-AAs compared to those of their l-counterparts provide valuable insights into the involvement of d-AAs in aging, AD progression, and neurodegeneration.

Revolutions in Lipid Isomer Resolution: Application of Ultrahigh-Resolution Ion Mobility to Reveal Lipid Diversity

Many families of lipid isomers remain unresolved by contemporary liquid chromatography-mass spectrometry approaches, leading to a significant underestimation of the structural diversity within the lipidome. While ion mobility coupled to mass spectrometry has provided an additional dimension of lipid isomer resolution, some isomers require a resolving power beyond the capabilities of conventional platforms. Here, we present the application of high-resolution traveling-wave ion mobility for the separation of lipid isomers that differ in (i) the location of a single carbon-carbon double bond, (ii) the stereochemistry of the double bond (cis or trans), or, for glycerolipids, (iii) the relative substitution of acyl chains on the glycerol backbone (sn-position). Collisional activation following mobility separation allowed identification of the carbon-carbon double-bond position and sn-position, enabling confident interpretation of variations in mobility peak abundance. To demonstrate the applicability of this method, double-bond and sn-position isomers of an abundant phosphatidylcholine composition were resolved in extracts from a prostate cancer cell line and identified by comparison to pure isomer reference standards, revealing the presence of up to six isomers. These findings suggest that ultrahigh-resolution ion mobility has broad potential for isomer-resolved lipidomics and is attractive to consider for future integration with other modes of ion activation, thereby bringing together advanced orthogonal separations and structure elucidation to provide a more complete picture of the lipidome.

Uncovering per- and polyfluoroalkyl substances (PFAS) with nontargeted ion mobility spectrometry-mass spectrometry analyses

Because of environmental and health concerns, legacy per- and polyfluoroalkyl substances (PFAS) have been voluntarily phased out, and thousands of emerging PFAS introduced as replacements. Traditional analytical methods target a limited number of mainly legacy PFAS; therefore, many species are not routinely assessed in the environment. Nontargeted approaches using high-resolution mass spectrometry methods have therefore been used to detect and characterize unknown PFAS. However, their ability to elucidate chemical structures relies on generation of informative fragments, and many low concentration species are not fragmented in typical data-dependent acquisition approaches. Here, a data-independent method leveraging ion mobility spectrometry (IMS) and size-dependent fragmentation was developed and applied to characterize aquatic passive samplers deployed near a North Carolina fluorochemical manufacturer. From the study, 11 PFAS structures for various per- and polyfluorinated ether sulfonic acids and multiheaded perfluorinated ether acids were elucidated in addition to 36 known PFAS. Eight of these species were previously unreported in environmental media, and three suspected species were validated.

Using Multidimensional Separations to Distinguish Isomeric Amino Acid-Bile Acid Conjugates and Assess Their Presence and Perturbations in Model Systems

Bile acids play key roles in nutrient uptake, inflammation, signaling, and microbiome composition. While previous bile acid analyses have primarily focused on profiling 5 canonical primary and secondary bile acids and their glycine and taurine amino acid-bile acid (AA-BA) conjugates, recent studies suggest that many other microbial conjugated bile acids (or MCBAs) exist. MCBAs are produced by the gut microbiota and serve as biomarkers, providing information about early disease onset and gut health. Here we analyzed 8 core bile acids synthetically conjugated with 22 proteinogenic and nonproteogenic amino acids totaling 176 MCBAs. Since many of the conjugates were isomeric and only 42 different m/z values resulted from the 176 MCBAs, a platform coupling liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) was used for their separation. Their molecular characteristics were then used to create an in-house extended bile acid library for a combined total of 182 unique compounds. Additionally, ∼250 rare bile acid extracts were also assessed to provide additional resources for bile acid profiling and identification. This library was then applied to healthy mice dosed with antibiotics and humans having fecal microbiota transplantation (FMT) to assess the MCBA presence and changes in the gut before and after each perturbation.

Combining native mass spectrometry and lipidomics to uncover specific membrane protein-lipid interactions from natural lipid sources

While it is known that lipids play an essential role in regulating membrane protein structure and function, it remains challenging to identify specific protein-lipid interactions. Here, we present an innovative approach that combines native mass spectrometry (MS) and lipidomics to identify lipids retained by membrane proteins from natural lipid extracts. Our results reveal that the bacterial ammonia channel (AmtB) enriches specific cardiolipin (CDL) and phosphatidylethanolamine (PE) from natural headgroup extracts. When the two extracts are mixed, AmtB retains more species, wherein selectivity is tuned to bias headgroup selection. Using a series of natural headgroup extracts, we show TRAAK, a two-pore domain K+ channel (K2P), retains specific acyl chains that is independent of the headgroup. A brain polar lipid extract was then combined with the K2Ps, TRAAK and TREK2, to understand lipid specificity. More than a hundred lipids demonstrated affinity for each protein, and both channels were found to retain specific fatty acids and lysophospholipids known to stimulate channel activity, even after several column washes. Natural lipid extracts provide the unique opportunity to not only present natural lipid diversity to purified membrane proteins but also identify lipids that may be important for membrane protein structure and function.

Ozone-enabled fatty acid discovery reveals unexpected diversity in the human lipidome

Fatty acid isomers are responsible for an under-reported lipidome diversity across all kingdoms of life. Isomers of unsaturated fatty acids are often masked in contemporary analysis by incomplete separation and the absence of sufficiently diagnostic methods for structure elucidation. Here, we introduce a comprehensive workflow, to discover unsaturated fatty acids through coupling liquid chromatography and mass spectrometry with gas-phase ozonolysis of double bonds. The workflow encompasses semi-automated data analysis and enables de novo identification in complex media including human plasma, cancer cell lines and vernix caseosa. The targeted analysis including ozonolysis enables structural assignment over a dynamic range of five orders of magnitude, even in instances of incomplete chromatographic separation. Thereby we expand the number of identified plasma fatty acids two-fold, including non-methylene-interrupted fatty acids. Detection, without prior knowledge, allows discovery of non-canonical double bond positions. Changes in relative isomer abundances reflect underlying perturbations in lipid metabolism.

An overview of metabolomic and proteomic profiling in bipolar disorder and its clinical value

INTRODUCTION

Bipolar disorder (BD) is a complex psychiatric disease characterized by alternating mood episodes. As for any other psychiatric illness, currently there is no biochemical test that is able to support diagnosis or therapeutic decisions for BD. In this context, the discovery and validation of biomarkers are interesting strategies that can be achieved through proteomics and metabolomics.

AREAS COVERED

In this descriptive review, a literature search including original articles and systematic reviews published in the last decade was performed with the objective to discuss the results of BD proteomic and metabolomic profiling analyses and indicate proteins and metabolites (or metabolic pathways) with potential clinical value.

EXPERT OPINION

A large number of proteins and metabolites have been reported as potential BD biomarkers; however, most studies do not reach biomarker validation stages. An effort from the scientific community should be directed toward the validation of biomarkers and the development of simplified bioanalytical techniques or protocols to determine them in biological samples, in order to translate proteomic and metabolomic findings into clinical routine assays.

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.

Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data

The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature.

A mass spectrum-oriented computational method for ion mobility-resolved untargeted metabolomics

Ion mobility (IM) adds a new dimension to liquid chromatography-mass spectrometry-based untargeted metabolomics which significantly enhances coverage, sensitivity, and resolving power for analyzing the metabolome, particularly metabolite isomers. However, the high dimensionality of IM-resolved metabolomics data presents a great challenge to data processing, restricting its widespread applications. Here, we develop a mass spectrum-oriented bottom-up assembly algorithm for IM-resolved metabolomics that utilizes mass spectra to assemble four-dimensional peaks in a reverse order of multidimensional separation. We further develop the end-to-end computational framework Met4DX for peak detection, quantification and identification of metabolites in IM-resolved metabolomics. Benchmarking and validation of Met4DX demonstrates superior performance compared to existing tools with regard to coverage, sensitivity, peak fidelity and quantification precision. Importantly, Met4DX successfully detects and differentiates co-eluted metabolite isomers with small differences in the chromatographic and IM dimensions. Together, Met4DX advances metabolite discovery in biological organisms by deciphering the complex 4D metabolomics data.

Lipidomics analysis of Sanhuang chicken during cold storage reveals possible molecular mechanism of lipid changes

Lipidomic profiles changes of the Sanhuang chicken breast meat during cold storage (4 °C) were analyzed using ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS)-based lipidomic analysis. Total lipids content decreased 16.8% after storage. Triacylglycerol (TAG), phosphatidylcholine (PC) and phosphatidylethanolamine (PE) significantly decreased, while lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE) increased. Particularly, there was a trend that TAGs with fatty acids of 16:0 and 18:1, and phospholipids containing 18:1, 18:2 and 20:4 were more likely to be downregulated. The increase in the ratio of lysophospholipids/phospholipids and the degree of lipid oxidation demonstrated oxidation and enzymatic hydrolysis are potentially responsible for the lipid transformation. Moreover, 12 lipid species (P < 0.05, VIP > 1, FC < 0.8 or >1.25) were identified to be associated with the spoilage of meat. Glycerophospholipid metabolism and linoleic acid metabolism were the key metabolic pathways involved in the lipid transformations of chilled chicken.

Matrix-assisted laser desorption/ionization-Fourier-transform ion cyclotron resonance-mass spectrometry analysis of exosomal lipids from human serum

RATIONALE

Exosomes contain biomarkers such as proteins and lipids that help in understanding normal physiology and diseases. Lipids, in particular, are infrequently studied using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) for biomarker discovery. In this study, MALDI was equipped with a high-resolution MS to investigate exosomal lipids from human serum.

METHODS

Exosomal lipids were profiled using MALDI with Fourier-transform ion cyclotron resonance (FTICR)-MS. Four matrices (i.e., α-cyano-4-hydroxycinnamic acid [CHCA], 2,5-dihydroxybenzoic acid, sinapinic acid, and graphene oxide [GO]) and three sample preparation methods (i.e., dried droplet, thin layer, and two layer) were compared for the number of lipid species detected and the relative abundance of each lipid from human serum and human serum exosomes.

RESULTS

In sum, 172 and 89 lipid species were identified from human serum and human serum exosomes, respectively, using all the methods. The highest number of exosome lipid species, 69, was detected using the CHCA matrix, whereas only 8 exosome lipid species were identified using the GO matrix. Among the identified lipid species, phosphatidylcholine was identified most frequently, probably due to the use of a positive ion mode.

CONCLUSIONS

Exosomes and human serum showed comparable lipid profiles as determined using MALDI-FTICR-MS. These findings provide a new perspective on exosomal lipidomics analysis and may serve as a foundation for future lipidomics-based biomarker research using MALDI-FTICR-MS.

Innovation in identifying metabolites from complex metabolome-Highlights of recent analytical platforms and protocols

Metabolites are closely intertwined genotypes that can provide clear information about the final phenotype. The high-throughput analysis platform used to identify candidate metabolites and describe their contributions can help to quickly detect metabolic characteristics from large spectral data, which may lead to peak data preprocessing, statistical analysis and functional interpretation. Developing a comprehensive strategy for discovering and verifying bioactive metabolites can provide a large number of new functional biomarkers, and then more closely reveal their functional changes, which has relevant biological significance for disease diagnosis and prognosis treatment.

Impacts of Gestational FireMaster 550 Exposure on the Neonatal Cortex Are Sex Specific and Largely Attributable to the Organophosphate Esters

INTRODUCTION

Flame retardants (FRs) are common bodily and environmental pollutants, creating concern about their potential toxicity. We and others have found that the commercial mixture FireMaster® 550 (FM 550) or its individual brominated (BFR) and organophosphate ester (OPFR) components are potential developmental neurotoxicants. Using Wistar rats, we previously reported that developmental exposure to FM 550 or its component classes produced sex- and compound-specific effects on adult socioemotional behaviors. The underlying mechanisms driving the behavioral phenotypes are unknown.

METHODS

To further mechanistic understanding, here we conducted transcriptomics in parallel with a novel lipidomics approach using cortical tissues from newborn siblings of the rats in the published behavioral study. Inclusion of lipid composition is significant because it is rarely examined in developmental neurotoxicity studies. Pups were gestationally exposed via oral dosing to the dam to FM 550 or the BFR or OPFR components at environmentally relevant doses.

RESULTS

The neonatal cortex was highly sexually dimorphic in lipid and transcriptome composition, and males were more significantly impacted by FR exposure. Multiple adverse modes of action for the BFRs and OPFRs on neurodevelopment were identified, with the OPFRs being more disruptive than the BFRs via multiple mechanisms including dysregulation of mitochondrial function and disruption of cholinergic and glutamatergic systems. Disrupted mitochondrial function by environmental factors has been linked to a higher risk of autism spectrum disorders and neurodegenerative disorders. Impacted lipid classes included ceramides, sphingomyelins, and triacylglycerides. Robust ceramide upregulation in the OPFR females could suggest a heightened risk of brain metabolic disease.

CONCLUSIONS

This study reveals multiple mechanisms by which the components of a common FR mixture are developmentally neurotoxic and that the OPFRs may be the compounds of greatest concern.