Deciphering lipid structures based on platform-independent decision rules

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.

FAIMS Shotgun Lipidomics for Enhanced Class- and Charge-State Separation Complemented by Automated Ganglioside Annotation

The analysis of gangliosides is extremely challenging, given their structural complexity, lack of reference standards, databases, and software solutions. Here, we introduce a fast 6 min high field asymmetric ion mobility spectrometry (FAIMS) shotgun lipidomics workflow, along with a dedicated software solution for ganglioside detection. By ramping FAIMS compensation voltages, ideal ranges for different ganglioside classes were obtained. FAIMS revealed both class- and charge-state separation behavior based on the glycan headgroup moiety. The number of sialic acids attached to the glycan moiety correlates positively with their preferred charge states, i.e., trisialylated gangliosides were mainly present as [M - 3H]3- ions, whereas [M - 4H]4- and [M - 5H]5- ions were observed for GQ1 and GP1. For data evaluation, we developed a shotgun/FAIMS extension for the open-source Lipid Data Analyzer (LDA), enabling automated annotation of gangliosides up to the molecular lipid species level. This extension utilized combined orthogonal fragmentation spectra from CID, HCD, and 213 nm UVPD ion activation methods and covers 29 ganglioside classes, including acetylated and fucosylated modifications. With our new workflow and software extension 117 unique gangliosides species were identified in porcine brain extracts. While conventional shotgun lipidomics favored the observation of singly charged ganglioside species, the utilization of FAIMS made multiply charged lipid species accessible, resulting in an increased number of detected species, primarily due to an improved signal-to-noise ratio arising from FAIMS charge state filtering. Therefore, this FAIMS-driven workflow, complemented by new software capabilities, offers a promising strategy for complex ganglioside and glycosphingolipid characterization in shotgun lipidomics.

Unsaturated fatty acid perturbation combats emerging triazole antifungal resistance in the human fungal pathogen Aspergillus fumigatus

Contemporary antifungal therapies utilized to treat filamentous fungal infections are inhibited by intrinsic and emerging drug resistance. Consequently, there is an urgent need to develop novel antifungal compounds that are effective against drug-resistant filamentous fungi. Here, we utilized an Aspergillus fumigatus cell-based high-throughput screen to identify small molecules with antifungal activity that also potentiated triazole activity. The screen identified 16 hits with promising activity against A. fumigatus. A nonspirocyclic piperidine, herein named MBX-7591, exhibited synergy with triazole antifungal drugs and activity against pan-azole-resistant A. fumigatus isolates. MBX-7591 has additional potent activity against Rhizopus species and CO2-dependent activity against Cryptococcus neoformans. Chemical, genetic, and biochemical mode of action analyses revealed that MBX-7591 increases cell membrane saturation by decreasing oleic acid content. MBX-7591 has low toxicity in vivo and shows good efficacy in decreasing fungal burden in a murine model of invasive pulmonary aspergillosis. Taken together, our results suggest MBX-7591 is a promising hit with a novel mode of action for further antifungal drug development to combat the rising incidence of triazole-resistant filamentous fungal infections.IMPORTANCEThe incidence of infections caused by fungi continues to increase with advances in medical therapies. Unfortunately, antifungal drug development has not kept pace with the incidence and importance of fungal infections, with only three major classes of antifungal drugs currently available for use in the clinic. Filamentous fungi, also called molds, are particularly recalcitrant to contemporary antifungal therapies. Here, a recently developed Aspergillus fumigatus cell reporter strain was utilized to conduct a high-throughput screen to identify small molecules with antifungal activity. An emphasis was placed on small molecules that potentiated the activity of contemporary triazole antifungals and led to the discovery of MBX-7591. MBX-7591 potentiates triazole activity against drug-resistant molds such as A. fumigatus and has activity against Mucorales fungi. MBX-7591's mode of action involves inhibiting the conversion of saturated to unsaturated fatty acids, thereby impacting fungal membrane integrity. MBX-7591 is a novel small molecule with antifungal activity poised for lead development.

Lipidomics of phospholipase A2 reveals exquisite specificity in macrophages

Phospholipase A2 (PLA2) constitutes a superfamily of enzymes that hydrolyze phospholipids at their sn-2 fatty acyl position. Our laboratory has demonstrated that PLA2 enzymes regulate membrane remodeling and cell signaling by their specificity toward their phospholipid substrates at the molecular level. Recent in vitro studies show that each type of PLA2, including Group IVA cytosolic PLA2 (cPLA2), Group V secreted PLA2 (sPLA2), Group VIA calcium independent PLA2 (iPLA2) and Group VIIA lipoprotein-associated PLA2, also known as platelet-activating factor acetyl hydrolase, can discriminate exquisitely between fatty acids at the sn-2 position. Thus, these enzymes regulate the production of diverse PUFA precursors of inflammatory metabolites. We now determined PLA2 specificity in macrophage cells grown in cell culture, where the amounts and localization of the phospholipid substrates play a role in which specific phospholipids are hydrolyzed by each enzyme type. We used PLA2 stereospecific inhibitors in tandem with a novel UPLC-MS/MS-based lipidomics platform to quantify more than a thousand unique phospholipid molecular species demonstrating cPLA2, sPLA2, and iPLA2 activity and specificity toward the phospholipids in living cells. The observed specificity follows the in vitro capability of the enzymes and can reflect the enrichment of certain phospholipid species in specific membrane locations where particular PLA2's associate. For assaying, we target 20:4-PI for cPLA2, 22:6-PG for sPLA2, and 18:2-PC for iPLA2. These new results provide great insight into the physiological role of PLA2 enzymes in cell membrane remodeling and could shed light on how PLA2 enzymes underpin inflammation and other lipid-related diseases.

Advanced Tandem Mass Spectrometric Analysis of Complex Mixtures of Triacylglycerol Regioisomers: A Case Study of Bovine Milk Fat

Comprehensive analysis of triacylglycerol (TAG) regioisomers is extremely challenging, with many variables that can influence the results. Previously, we reported a novel algorithmic method for resolving regioisomers of complex mixtures of TAGs. In the current study, the TAG Analyzer software and its mass spectrometric fragmentation model were further developed and validated for a much wider range of TAGs. To demonstrate the method, we performed for the first time a comprehensive analysis of TAG regioisomers of bovine milk fat, a very important and one of the most complex TAG mixtures in nature containing FAs ranging from short to long carbon chains. This analysis method forms a solid basis for further investigation of TAG regioisomer profiles in various natural fats and oils, potentially aiding in the development of new and healthier foods and nutraceuticals with targeted lipid structures.

MS3 Imaging Enables the Simultaneous Analysis of Phospholipid C═C and sn-Position Isomers in Tissues

Mass spectrometry (MS) imaging of lipids in tissues with high structure specificity is challenging in the effective fragmentation of position-selective structures and the sensitive detection of multiple lipid isomers. Herein, we develop an MS3 imaging method for the simultaneous analysis of phospholipid C═C and sn-position isomers by on-tissue photochemical derivatization, nanospray desorption electrospray ionization (nano-DESI), and a dual-linear ion trap MS system. A novel laser-based sensing probe is developed for the real-time adjustment of the probe-to-surface distance for nano-DESI. This method is validated in mouse brain and kidney sections, showing its capability of sensitive resolving and imaging of the fatty acyl chain composition, the sn-position, and the C═C location of phospholipids in an MS3 scan. MS3 imaging of phospholipids has shown the capability of differentiation of cancerous, fibrosis, and adjacent normal regions in liver cancer tissues.

Lipid storage disease in 4 sibling superb birds-of-paradise (Lophorina superba)

Pedigree analysis, clinical, gross, microscopic, ultrastructural, and lipidomic findings in 4 female superb bird-of-paradise (SBOP, Lophorina superba) siblings led to the diagnosis of a primary inherited glycerolipid storage disease. These birds were the offspring of a related breeding pair (inbreeding coefficient = 0.1797) and are the only known SBOPs to display this constellation of lesions. The birds ranged from 0.75 to 4.3 years of age at the time of death. Two birds were euthanized and 1 died naturally due to the disease, and 1 died of head trauma with no prior clinical signs. Macroscopic findings included hepatomegaly and pallor (4/4), cardiac and renal pallor (2/4), and coelomic effusion (1/4). Microscopic examination found marked tissue distortion due to cytoplasmic lipid vacuoles in hepatocytes (4/4), cardiomyocytes (4/4), renal tubular epithelial cells (4/4), parathyroid gland principal cells (2/2), exocrine pancreatic cells (3/3), and the glandular cells of the ventriculus and proventriculus (3/3). Ultrastructurally, the lipids were deposited in single to coalescing or fused droplets lined by an inconspicuous or discontinuous monolayer membrane. Lipidomic profiling found that the cytoplasmic lipid deposits were primarily composed of triacylglycerols. Future work, including sequencing of the SBOP genome and genotyping, will be required to definitively determine the underlying genetic mechanism of this disease.

In Silico-Predicted Dynamic Oxlipidomics MS/MS Library: High-Throughput Discovery and Characterization of Unknown Oxidized Lipids

Nontargeted lipidomics using liquid chromatography-tandem mass spectrometry can detect thousands of molecules in biological samples. However, the annotation of unknown oxidized lipids is limited to the structures present in libraries, restricting the analysis and interpretation of experimental data. Here, we describe Doxlipid, a computational tool for oxidized lipid annotation that predicts a dynamic MS/MS library for every experiment. Doxlipid integrates three key simulation algorithms to predict libraries and covers 32 subclasses of oxidized lipids from the three main classes. In the evaluation, Doxlipid achieves very high prediction and characterization performance and outperforms the current oxidized lipid annotation methods. Doxlipid, combined with a molecular network, further annotates unknown chemical analogs in the same reaction or pathway. We demonstrate the broad utility of Doxlipid by analyzing oxidized lipids in ferroptosis hepatocellular carcinoma, tissue samples, and other biological samples, substantially advancing the discovery of biological pathways at the trace oxidized lipid level.

MARS: A Multipurpose Software for Untargeted LC-MS-Based Metabolomics and Exposomics

Untargeted metabolomics is a growing field, in which recent advances in high-resolution mass spectrometry coupled with liquid chromatography (LC-MS) have facilitated untargeted approaches as a result of improvements in sensitivity, mass accuracy, and resolving power. However, a very large amount of data are generated. Consequently, using computational tools is now mandatory for the in-depth analysis of untargeted metabolomics data. This article describes MetAbolomics ReSearch (MARS), an all-in-one vendor-agnostic graphical user interface-based software applying LC-MS analysis to untargeted metabolomics. All of the analytical steps are described (from instrument data conversion and processing to statistical analysis, annotation/identification, quantification, and preliminary biological interpretation), and tools developed to improve annotation accuracy (e.g., multiple adducts and in-source fragmentation detection, trends across samples, and the MS/MS validator) are highlighted. In addition, MARS allows in-house building of reference databases, to bypass the limits of freely available MS/MS spectra collections. Focusing on the flexibility of the software and its user-friendliness, which are two important features in multipurpose software, MARS could provide new perspectives in untargeted metabolomics data analysis.

Lipids as Emerging Biomarkers in Neurodegenerative Diseases

Biomarkers are molecules that can be used to observe changes in an individual's biochemical or medical status and provide information to aid diagnosis or treatment decisions. Dysregulation in lipid metabolism in the brain is a major risk factor for many neurodegenerative disorders, including frontotemporal dementia, Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Thus, there is a growing interest in using lipids as biomarkers in neurodegenerative diseases, with the anionic phospholipid bis(monoacylglycerol)phosphate and (glyco-)sphingolipids being the most promising lipid classes thus far. In this review, we provide a general overview of lipid biology, provide examples of abnormal lysosomal lipid metabolism in neurodegenerative diseases, and discuss how these insights might offer novel and promising opportunities in biomarker development and therapeutic discovery. Finally, we discuss the challenges and opportunities of lipid biomarkers and biomarker panels in diagnosis, prognosis, and/or treatment response in the clinic.

Oleic Acid Metabolism in Response to Glucose in C. elegans

A key response to glucose stress is an increased production of unsaturated fatty acids to balance the increase in saturated fatty acids in the membrane. The C. elegans homolog of stearoyl-CoA desaturase, FAT-7, introduces the first double bond into saturated C18 fatty acids yielding oleic acid, and is a critical regulatory point for surviving cold and glucose stress. Here, we incorporated 13C stable isotopes into the diet of nematodes and quantified the 13C-labelled fatty acid using GC-MS and HPLC/MS-MS to track its metabolic response to various concentrations of glucose. Previous work has analyzed the membrane composition of C. elegans when responding to mild glucose stress and showed few alterations in the overall fatty acid composition in the membrane. Here, in nematodes exposed to higher concentrations of glucose, a specific reduction in oleic acid and linoleic acid was observed. Using time courses and stable isotope tracing, the response of fatty acid metabolism to increasing levels of glucose stress is characterized, revealing the funneling of monounsaturated fatty acids to preserve the abundance of polyunsaturated fatty acids. Taken together, higher levels of glucose unveil a specific reduction in oleic and linolenic acid in the metabolic rewiring required to survive glucose stress.

Lipidomics of coconut, almond and soybean milks - Comprehensive characterization of triacylglycerol class and comparison with bovine milk

Nowadays, plant-based milk consumption, as part of a healthy diet, is continuously increasing. In this paper, for the first time a lipidomic analysis on molecular species of triacylglycerol (TG) fraction of plant-based beverages (almond, soy, coconut) was performed by liquid chromatography quadrupole time-of-flight mass spectrometry. A total of 557 TG molecular species was measured, showing significantly different profiles between milk alternatives, compared with bovine milk. The most abundant TG molecular species were TG 18:1_18:1_18:1 and 18:1_18:1_18:2 for almond, TG 18:2_18:2_18:2 and 16:0_18:2_18:2 for soy, TG 12:0_10:0_12:0 and 12:0_12:0_14:0 for coconut. Unconventional fatty acids were detected in almond and soy. The main TG with ethereal linkage were TG-O 56:2, TG-O 56:4, and TG-O 56:5, while the main oxygenated TG was TG 54:5;1O. A total of 30 molecular species were identified as biomarkers for milk differentiation by principal component analysis, providing an interesting support for milk authentication and detection of adulteration on a larger sampling.

Improved Structural Characterization of Glycerophospholipids and Sphingomyelins with Real-Time Library Searching

In mass spectrometry-based lipidomics, complex lipid mixtures undergo chromatographic separation, are ionized, and are detected using tandem MS (MSn) to simultaneously quantify and structurally characterize eluting species. The reported structural granularity of these identified lipids is strongly reliant on the analytical techniques leveraged in a study. For example, lipid identifications from traditional collisionally activated data-dependent acquisition experiments are often reported at either species level or molecular species level. Structural resolution of reported lipid identifications is routinely enhanced by integrating both positive and negative mode analyses, requiring two separate runs or polarity switching during a single analysis. MS3+ can further elucidate lipid structure, but the lengthened MS duty cycle can negatively impact analysis depth. Recently, functionality has been introduced on several Orbitrap Tribrid mass spectrometry platforms to identify eluting molecular species on-the-fly. These real-time identifications can be leveraged to trigger downstream MSn to improve structural characterization with lessened impacts on analysis depth. Here, we describe a novel lipidomics real-time library search (RTLS) approach, which utilizes the lipid class of real-time identifications to trigger class-targeted MSn and to improve the structural characterization of phosphotidylcholines, phosphotidylethanolamines, phosphotidylinositols, phosphotidylglycerols, phosphotidylserine, and sphingomyelins in the positive ion mode. Our class-based RTLS method demonstrates improved selectivity compared to the current methodology of triggering MSn in the presence of characteristic ions or neutral losses.

Ultraviolet exposure regulates skin metabolome based on the microbiome

Skin metabolites (< 1500 Da) play a critical role in barrier function, hydration, immune response, microbial invasion, and allergen penetration. We aimed to understand the global metabolic profile changes of the skin in relation to the microbiome and UV exposure and exposed germ-free (devoid of microbiome), disinfected mice (partially devoid of skin microbiome) and control mice with intact microbiome to immunosuppressive doses of UVB radiation. Targeted and untargeted lipidome and metabolome profiling was performed with skin tissue by high-resolution mass spectrometry. UV differentially regulated various metabolites such as alanine, choline, glycine, glutamine, and histidine in germ-free mice compared to control mice. Membrane lipid species such as phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin were also affected by UV in a microbiome-dependent manner. These results shed light on the dynamics and interactions between the skin metabolome, microbiome, and UV exposure and open new avenues for the development of metabolite- or lipid-based applications to maintain skin health.

The impact of different calibration matrices on the determination of insulin-like growth factor 1 by high-resolution-LC-MS in acromegalic and growth hormone deficient patients

OBJECTIVES

Calibration is an important source of variability in liquid chromatography mass spectrometry (LC-MS) methods for insulin-like growth factor 1 (IGF-1). This study investigated the impact of different calibrator matrices on IGF-1 measurements by LC-MS. Moreover, the comparability of immunoassays and LC-MS was assessed.

DESIGN & METHODS

Calibrators from 12.5 to 2009 ng/ml were prepared by spiking WHO international Standard (ID 02/254 NIBSC, UK) into the following matrices: native human plasma, fresh charcoal-treated human plasma (FCTHP), old charcoal-treated human plasma, deionized water, bovine serum albumin (BSA), and rat plasma (RP). A validated in-house LC-MS method was calibrated repeatedly with these calibrators. Then, serum samples from 197 growth hormone excess and deficiency patients were analysed with each calibration.

RESULTS

The seven calibration curves had different slopes leading to markedly different patient results. The largest differences in IGF-1 concentration from the median (interquartile range) was observed with the calibrator in water and the calibrator in RP (336.4 [279.6-417.0] vs. 112.5 [71.2-171.2], p < 0.001). The smallest difference was observed with calibrators in FCTHP and BSA (141.8 [102.0-198.5] vs. 127.9 [86.9-186.0], p < 0.049). Compared to LC-MS with calibrators in FCTHP, immunoassays showed relevant proportional bias (range: -43% to -68%), constant bias (range: 22.84 to 57.29 ng/ml) and pronounced scatter. Comparing the immunoassays with each other revealed proportional bias of up to 24%.

CONCLUSIONS

The calibrator matrix is critical for the measurement of IGF-1 by LC-MS. Regardless of the calibrator matrix, LC-MS shows poor agreement with immunoassays. Also, the agreement between different immunoassays is variable.

Lipidomics analysis in drug discovery and development

Despite being a relatively new addition to the Omics' landscape, lipidomics is increasingly being recognized as an important tool for the identification of druggable targets and biochemical markers. In this review we present recent advances of lipid analysis in drug discovery and development. We cover current state of the art technologies which are constantly evolving to meet demands in terms of sensitivity and selectivity. A careful selection of important examples is then provided, illustrating the versatility of lipidomics analysis in the drug discovery and development process. Integration of lipidomics with other omics', stem-cell technologies, and metabolic flux analysis will open new avenues for deciphering pathophysiological mechanisms and the discovery of novel targets and biomarkers.

Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

Lipidomics-Paving the Road towards Better Insight and Precision Medicine in Rare Metabolic Diseases

Even though the application of Next-Generation Sequencing (NGS) has significantly facilitated the identification of disease-associated mutations, the diagnostic rate of rare diseases is still below 50%. This causes a diagnostic odyssey and prevents specific treatment, as well as genetic counseling for further family planning. Increasing the diagnostic rate and reducing the time to diagnosis in children with unclear disease are crucial for a better patient outcome and improvement of quality of life. In many cases, NGS reveals variants of unknown significance (VUS) that need further investigations. The delineation of novel (lipid) biomarkers is not only crucial to prove the pathogenicity of VUS, but provides surrogate parameters for the monitoring of disease progression and therapeutic interventions. Lipids are essential organic compounds in living organisms, serving as building blocks for cellular membranes, energy storage and signaling molecules. Among other disorders, an imbalance in lipid homeostasis can lead to chronic inflammation, vascular dysfunction and neurodegenerative diseases. Therefore, analyzing lipids in biological samples provides great insight into the underlying functional role of lipids in healthy and disease statuses. The method of choice for lipid analysis and/or huge assemblies of lipids (=lipidome) is mass spectrometry due to its high sensitivity and specificity. Due to the inherent chemical complexity of the lipidome and the consequent challenges associated with analyzing it, progress in the field of lipidomics has lagged behind other omics disciplines. However, compared to the previous decade, the output of publications on lipidomics has increased more than 17-fold within the last decade and has, therefore, become one of the fastest-growing research fields. Combining multiple omics approaches will provide a unique and efficient tool for determining pathogenicity of VUS at the functional level, and thereby identifying rare, as well as novel, genetic disorders by molecular techniques and biochemical analyses.

LipidA-IDER to Explore the Global Lipid A Repertoire of Drug-Resistant Gram-Negative Bacteria

With the global emergence of drug-resistant bacteria causing difficult-to-treat infections, there is an urgent need for a tool to facilitate studies on key virulence and antimicrobial resistant factors. Mass spectrometry (MS) has contributed substantially to the elucidation of the structure-function relationships of lipid A, the endotoxic component of lipopolysaccharide which also serves as an important protective barrier against antimicrobials. Here, we present LipidA-IDER, an automated structure annotation tool for system-level scale identification of lipid A from high-resolution tandem mass spectrometry (MS²) data. LipidA-IDER was validated against previously reported structures of lipid A in the reference bacteria, Escherichia coli and Pseudomonas aeruginosa. Using MS² data of variable quality, we demonstrated LipidA-IDER annotated lipid A with a performance of 71.2% specificity and 70.9% sensitivity, offering greater accuracy than existing lipidomics software. The organism-independent workflow was further applied to a panel of six bacterial species: E. coli and Gram-negative members of ESKAPE pathogens. A comprehensive atlas comprising 188 distinct lipid A species, including remodeling intermediates, was generated and can be integrated with software including MS-DIAL and Metabokit for identification and semiquantitation. Systematic comparison of a pair of polymyxin-sensitive and polymyxin-resistant Acinetobacter baumannii isolated from a human patient unraveled multiple key lipid A structural features of polymyxin resistance within a single analysis. Probing the lipid A landscape of bacteria using LipidA-IDER thus holds immense potential for advancing our understanding of the vast diversity and structural complexity of a key lipid virulence and antimicrobial-resistant factor. LipidA-IDER is freely available at https://github.com/Systems-Biology-Of-Lipid-Metabolism-Lab/LipidA-IDER.

Computational mass spectrometry accelerates C = C position-resolved untargeted lipidomics using oxygen attachment dissociation

Mass spectrometry-based untargeted lipidomics has revealed the lipidome atlas of living organisms at the molecular species level. Despite the double bond (C = C) position being a crucial factor in biological system, the C = C defined structures have not yet been characterized comprehensively. Here, we present an approach for C = C position-resolved untargeted lipidomics using a combination of oxygen attachment dissociation and computational mass spectrometry to increase the annotation rate. We validated the accuracy of our platform as per the authentic standards of 85 lipids and the biogenic standards of 52 molecules containing polyunsaturated fatty acids (PUFAs) from the cultured cells fed with various fatty acid-enriched media. By analyzing human and mice-derived samples, we characterized 648 unique lipids with the C = C position-resolved level encompassing 24 lipid subclasses defined by LIPIDMAPS. Our platform also illuminated the unique profiles of tissue-specific lipids containing n-3 and/or n-6 very long-chain PUFAs (carbon [Formula: see text] 28 and double bonds [Formula: see text] 4) in the eye, testis, and brain of the mouse.

Decoding Distinct Ganglioside Patterns of Native and Differentiated Mesenchymal Stem Cells by a Novel Glycolipidomics Profiling Strategy

Gangliosides are an indispensable glycolipid class concentrated on cell surfaces with a critical role in stem cell differentiation. Nonetheless, owing to the lack of suitable methods for scalable analysis covering the full scope of ganglioside molecular diversity, their mechanistic properties in signaling and differentiation remain undiscovered to a large extent. This work introduces a sensitive and comprehensive ganglioside assay based on liquid chromatography, high-resolution mass spectrometry, and multistage fragmentation. Complemented by an open-source data evaluation workflow, we provide automated in-depth lipid species-level and molecular species-level annotation based on decision rule sets for all major ganglioside classes. Compared to conventional state-of-the-art methods, the presented ganglioside assay offers (1) increased sensitivity, (2) superior structural elucidation, and (3) the possibility to detect novel ganglioside species. A major reason for the highly improved sensitivity is the optimized spectral readout based on the unique capability of two parallelizable mass analyzers for multistage fragmentation. We demonstrated the high-throughput universal capability of our novel analytical strategy by identifying 254 ganglioside species. As a proof of concept, 137 unique gangliosides were annotated in native and differentiated human mesenchymal stem cells including 78 potential cell-state-specific markers and 38 previously unreported gangliosides. A general increase of the ganglioside numbers upon differentiation was observed as well as cell-state-specific clustering based on the ganglioside species patterns. The combination of the developed glycolipidomics assay with the extended automated annotation tool enables comprehensive in-depth ganglioside characterization as shown on biological samples of interest. Our results suggest ganglioside patterns as a promising quality control tool for stem cells and their differentiation products. Additionally, we believe that our analytical workflow paves the way for probing glycolipid-based biochemical processes shedding light on the enigmatic processes of gangliosides and glycolipids in general.

LipidMS 3.0: an R-package and a web-based tool for LC-MS/MS data processing and lipid annotation

MOTIVATION

LipidMS was initially envisioned to use fragmentation rules and data-independent acquisition (DIA) for lipid annotation. However, data-dependent acquisition (DDA) remains the most widespread acquisition mode for untargeted LC-MS/MS-based lipidomics. Here we present LipidMS 3.0, an R package that not only adds DDA and new lipid classes to its pipeline, but also the required functionalities to cover the whole data analysis workflow from pre-processing (i.e., peak-peaking, alignment and grouping) to lipid annotation.

RESULTS

We applied the new workflow in the data analysis of a commercial human serum pool spiked with 68 representative lipid standards acquired in full scan, DDA and DIA modes. When focusing on the detected lipid standard features and total identified lipids, LipidMS 3.0 data pre-processing performance is similar to XCMS, whereas it complements the annotations returned by MS-DIAL, providing a higher level of structural information and a lower number of incorrect annotations. To extend and facilitate LipidMS 3.0 usage among less experienced R-programming users, the workflow was also implemented as a web-based application.

AVAILABILITY

The LipidMS R-package is freely available at https://CRAN.R-project.org/package=LipidMS and as a website at http://www.lipidms.com.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Membrane Properties of Human Induced Pluripotent Stem Cell-Derived Cultured Red Blood Cells

Cultured red blood cells from human induced pluripotent stem cells (cRBC_iPSCs) are a promising source for future concepts in transfusion medicine. Before cRBC_iPSCs will have entrance into clinical or laboratory use, their functional properties and safety have to be carefully validated. Due to the limitations of established culture systems, such studies are still missing. Improved erythropoiesis in a recently established culture system, closer simulating the physiological niche, enabled us to conduct functional characterization of enucleated cRBC_iPSCs with a focus on membrane properties. Morphology and maturation stage of cRBC_iPSCs were closer to native reticulocytes (nRETs) than to native red blood cells (nRBCs). Whereas osmotic resistance of cRBC_iPSCs was similar to nRETs, their deformability was slightly impaired. Since no obvious alterations in membrane morphology, lipid composition, and major membrane associated protein patterns were observed, reduced deformability might be caused by a more primitive nature of cRBC_iPSCs comparable to human embryonic- or fetal liver erythropoiesis. Blood group phenotyping of cRBC_iPSCs further confirmed the potency of cRBC_iPSCs as a prospective device in pre-transfusional routine diagnostics. Therefore, RBC membrane analyses obtained in this study underscore the overall prospects of cRBC_iPSCs for their future application in the field of transfusion medicine.

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

Lipidomics studies suffer from analytical and annotation challenges because of the great structural similarity of many of the lipid species. To improve lipid characterization and annotation capabilities beyond those afforded by traditional mass spectrometry (MS)-based methods, multidimensional separation methods such as those integrating liquid chromatography, ion mobility spectrometry, collision-induced dissociation and MS (LC-IMS-CID-MS) may be used. Although LC-IMS-CID-MS and other multidimensional methods offer valuable hydrophobicity, structural and mass information, the files are also complex and difficult to assess. Thus, the development of software tools to rapidly process and facilitate confident lipid annotations is essential. In this Protocol Extension, we use the freely available, vendor-neutral and open-source software Skyline to process and annotate multidimensional lipidomic data. Although Skyline ( https://skyline.ms/skyline.url ) was established for targeted processing of LC-MS-based proteomics data, it has since been extended such that it can be used to analyze small-molecule data as well as data containing the IMS dimension. This protocol uses Skyline's recently expanded capabilities, including small-molecule spectral libraries, indexed retention time and ion mobility filtering, and provides a step-by-step description for importing data, predicting retention times, validating lipid annotations, exporting results and editing our manually validated 500+ lipid library. Although the time required to complete the steps outlined here varies on the basis of multiple factors such as dataset size and familiarity with Skyline, this protocol takes ~5.5 h to complete when annotations are rigorously verified for maximum confidence.

Lipidomics profiling of zebrafish liver through untargeted liquid chromatography-high resolution mass spectrometry

Lipidomics analysis of zebrafish tissues has shown promising results to understand disease-related outcomes of exposure to toxic substances at molecular level. However, knowledge about their lipidome is limited, as most untargeted studies only identify the lipids that are statistically significant in their setup. In this work, liquid chromatography-high resolution mass spectrometry was used to study different aspects of the analytical workflow, i.e., extraction solvents (methanol/chloroform/water (3/2/2, v/v/v), methanol/dichloromethane/water (2/3/2, v/v/v) and methanol/methyl-tert-butyl ether/water (3/10/2.5, v/v/v), instrumental response, and strategies used for lipid annotation. The number of high-quality features (relative standard deviation of the intensity values ≤ 10% in the range 10³ -10⁷ counts) was affected by the dilution of lipid extracts, indicating that it is an important parameter for developing untargeted methods. The workflows used allowed the selection of a dilution factor to annotate 712 lipid species (507 bulk lipids) in zebrafish liver using four software (LipidMatch, LipidHunter, MS-DIAL and Lipostar). Retention time mapping was a valuable tool to filter lipid annotations obtained from automatic software annotations. The lipid profiling of zebrafish livers will help in a better understanding of the true constitution of their lipidome at the species level, as well as in the use of zebrafish in toxicological studies. This article is protected by copyright. All rights reserved.

PeakBot: Machine learning based chromatographic peak picking

Motivation

Chromatographic peak picking is among the first steps in data processing workflows of raw LC-HRMS datasets in untargeted metabolomics applications. Its performance is crucial for the holistic detection of all metabolic features as well as their relative quantification for statistical analysis and metabolite identification. Random noise, non-baseline separated compounds and unspecific background signals complicate this task.

Results

A machine-learning-based approach entitled PeakBot was developed for detecting chromatographic peaks in LC-HRMS profile-mode data. It first detects all local signal maxima in a chromatogram, which are then extracted as super-sampled standardized areas (retention-time versus m/z). These are subsequently inspected by a custom-trained convolutional neural network that forms the basis of PeakBot’s architecture. The model reports if the respective local maximum is the apex of a chromatographic peak or not as well as its peak center and bounding box. In training and independent validation datasets used for development, PeakBot achieved a high performance with respect to discriminating between chromatographic peaks and background signals (accuracy of 0.99). For training the machine-learning model a minimum of 100 reference features are needed to learn their characteristics to achieve high-quality peak-picking results for detecting such chromatographic peaks in an untargeted fashion. PeakBot is implemented in python (3.8) and uses the TensorFlow (2.5.0) package for machine-learning related tasks. It has been tested on Linux and Windows OSs.

Availability and implementation

The package is available free of charge for non-commercial use (CC BY-NC-SA). It is available at https://github.com/christophuv/PeakBot.

Supplementary information

Supplementary data are available at Bioinformatics online.

Changes in the Cerebrospinal Fluid and Plasma Lipidome in Patients with Rett Syndrome

Rett syndrome (RTT) is defined as a rare disease caused by mutations of the methyl-CpG binding protein 2 (MECP2). It is one of the most common causes of genetic mental retardation in girls, characterized by normal early psychomotor development, followed by severe neurologic regression. Hitherto, RTT lacks a specific biomarker, but altered lipid homeostasis has been found in RTT model mice as well as in RTT patients. We performed LC-MS/MS lipidomics analysis to investigate the cerebrospinal fluid (CSF) and plasma composition of patients with RTT for biochemical variations compared to healthy controls. In all seven RTT patients, we found decreased CSF cholesterol levels compared to age-matched controls (n = 13), whereas plasma cholesterol levels were within the normal range in all 13 RTT patients compared to 18 controls. Levels of phospholipid (PL) and sphingomyelin (SM) species were decreased in CSF of RTT patients, whereas the lipidomics profile of plasma samples was unaltered in RTT patients compared to healthy controls. This study shows that the CSF lipidomics profile is altered in RTT, which is the basis for future (functional) studies to validate selected lipid species as CSF biomarkers for RTT.

Characterization of Constituents with Potential Anti-Inflammatory Activity in Chinese Lonicera Species by UHPLC-HRMS Based Metabolite Profiling

This study centered on detecting potentially anti-inflammatory active constituents in ethanolic extracts of Chinese Lonicera species by taking an UHPLC-HRMS-based metabolite profiling approach. Extracts from eight different Lonicera species were subjected to both UHPLC-HRMS analysis and to pharmacological testing in three different cellular inflammation-related assays. Compounds exhibiting high correlations in orthogonal projections to latent structures discriminant analysis (OPLS-DA) of pharmacological and MS data served as potentially activity-related candidates. Of these candidates, 65 were tentatively or unambiguously annotated. 7-Hydroxy-5,3′,4′,5′-tetramethoxyflavone and three bioflavonoids, as well as three C₃₂- and one C₃₄-acetylated polyhydroxy fatty acid, were isolated from Lonicera hypoglauca leaves for the first time, and their structures were fully or partially elucidated. Of the potentially active candidate compounds, 15 were subsequently subjected to pharmacological testing. Their activities could be experimentally verified in part, emphasizing the relevance of Lonicera species as a source of anti-inflammatory active constituents. However, some compounds also impaired the cell viability. Overall, the approach was found useful to narrow down the number of potentially bioactive constituents in the complex extracts investigated. In the future, the application of more refined concepts, such as extract prefractionation combined with bio-chemometrics, may help to further enhance the reliability of candidate selection.

α-Linolenic acid and product octadecanoids in Styrian pumpkin seeds and oils: How processing impacts lipidomes of fatty acid, triacylglycerol and oxylipin molecular structures

Styrian pumpkin seed oil is a conditioned green-colored oil renowned for nutty smell and taste. Due to α-linolenic acid (ALA) contents below 1% of total fatty acids and the prospect of nutritional health claims based on its potential oxidation products, we investigated the fate of ALA and product oxylipins in the course of down-stream processing of seeds and in oils. Lipidomic analyses with Lipid Data Analyzer 2.8.1 revealed: Processing did not change (1) main fatty acid composition in the oils, (2) amounts of triacylglycerol species, (3) structures of triacylglycerol molecular species containing ALA. (4) Minor precursor ALA in fresh Styrian and normal pumpkins produced 6 product phytoprostanes in either cultivar, quantitatively more in the latter. (5) In oil samples 7 phytoprostanes and 2 phytofurans were detected. The latter two are specific for their presence in pumpkin seed oils, of note, quantitatively more in conditioned oils than in cold-pressed native oils.

Recent advances in metabolomics analysis for early drug development

The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

Metabolite discovery: Biochemistry's scientific driver

Metabolite identification represents a major challenge, and opportunity, for biochemistry. The collective characterization and quantification of metabolites in living organisms, with its many successes, represents a major biochemical knowledgebase and the foundation of metabolism's rebirth in the 21^st century; yet, characterizing newly observed metabolites has been an enduring obstacle. Crystallography and NMR spectroscopy have been of extraordinary importance, although their applicability in resolving metabolism's fine structure has been restricted by their intrinsic requirement of sufficient and sufficiently pure materials. Mass spectrometry has been a key technology, especially when coupled with high-performance separation technologies and emerging informatic and database solutions. Even more so, the collective of artificial intelligence technologies are rapidly evolving to help solve the metabolite characterization conundrum. This perspective describes this challenge, how it was historically addressed, and how metabolomics is evolving to address it today and in the future.

Applications of lipidomics in marine organisms: Progresses, challenges and future perspectives

Marine ecosystems comprise a high diversity of life forms, such as algae, invertebrates, and vertebrates. These organisms have adapted their physiology according to the conditions of the environments in which...

Neuronal HSF-1 coordinates the propagation of fat desaturation across tissues to enable adaptation to high temperatures in C. elegans

To survive elevated temperatures, ectotherms adjust the fluidity of membranes by fine-tuning lipid desaturation levels in a process previously described to be cell autonomous. We have discovered that, in Caenorhabditis elegans, neuronal heat shock factor 1 (HSF-1), the conserved master regulator of the heat shock response (HSR), causes extensive fat remodeling in peripheral tissues. These changes include a decrease in fat desaturase and acid lipase expression in the intestine and a global shift in the saturation levels of plasma membrane's phospholipids. The observed remodeling of plasma membrane is in line with ectothermic adaptive responses and gives worms a cumulative advantage to warm temperatures. We have determined that at least 6 TAX-2/TAX-4 cyclic guanosine monophosphate (cGMP) gated channel expressing sensory neurons, and transforming growth factor ß (TGF-β)/bone morphogenetic protein (BMP) are required for signaling across tissues to modulate fat desaturation. We also find neuronal hsf-1 is not only sufficient but also partially necessary to control the fat remodeling response and for survival at warm temperatures. This is the first study to show that a thermostat-based mechanism can cell nonautonomously coordinate membrane saturation and composition across tissues in a multicellular animal.

Metabolomics and complementary techniques to investigate the plant phytochemical cosmos

Covering: up to 2021Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and are speculated to possess novel bioactive properties. In addition to their role in plant physiology, these metabolites are also relevant as existing and next-generation medicine candidates. Elucidation of the plant metabolite diversity is thus valuable for the successful exploitation of natural resources for humankind. Herein, we present a comprehensive review on recent metabolomics approaches to illuminate molecular networks in plants, including chemical isolation and enzymatic production as well as the modern metabolomics approaches such as stable isotope labeling, ultrahigh-resolution mass spectrometry, metabolome imaging (spatial metabolomics), single-cell analysis, cheminformatics, and computational mass spectrometry. Mass spectrometry-based strategies to characterize plant metabolomes through metabolite identification and annotation are described in detail. We also highlight the use of phytochemical genomics to mine genes associated with specialized metabolites' biosynthesis. Understanding the metabolic diversity through biotechnological advances is fundamental to elucidate the functions of the plant-derived specialized metabolome.

Simple and Reproducible Derivatization with Benzoyl Chloride: Improvement of Sensitivity for Multiple Lipid Classes in RP-UHPLC/MS

The chemical derivatization of multiple lipid classes was developed using benzoyl chloride as a nonhazardous derivatization agent at ambient conditions. The derivatization procedure was optimized with standards for 4 nonpolar and 8 polar lipid classes and measured by reversed-phase ultrahigh-performance liquid chromatography-tandem mass spectrometry. The derivatization and nonderivatization approaches were compared on the basis of the calibration curves of 22 internal standards from 12 lipid classes. The new method decreased the limit of detection 9-fold for monoacylglycerols (0.9-1.0 nmol/mL), 6.5-fold for sphingoid base (0.2 nmol/mL), and 3-fold for diacylglycerols (0.9 nmol/mL). The sensitivity expressed by the ratio of calibration slopes was increased 2- to 10-fold for almost all investigated lipid classes and even more than 100-fold for monoacylglycerols. Moreover, the benzoylation reaction produces a more stable derivative of cholesterol in comparison to the easily in-source fragmented nonderivatized form and enabled the detection of fatty acids in a positive ion mode, which does not require polarity switching as for the nonderivatized form. The intralaboratory comparison with an additional operator without previous derivatization experiences shows the simplicity, robustness, and reproducibility. The stability of the derivatives was determined by periodical measurements during a one month period and five freeze/thaw cycles. The fully optimized derivatization method was applied to human plasma, which allows the detection of 169 lipid species from 11 lipid classes using the high confidence level of identification in reversed-phase (RP)-ultra high performance liquid chromatography (UHPLC)/mass spectrometry (MS). Generally, we detected more lipid species for monoacylglycerols, diacylglycerols, and sphingoid bases in comparison with previously reported papers without the derivatization.

Recommendations for good practice in MS-based lipidomics

In the last 2 decades, lipidomics has become one of the fastest expanding scientific disciplines in biomedical research. With an increasing number of new research groups to the field, it is even more important to design guidelines for assuring high standards of data quality. The Lipidomics Standards Initiative is a community-based endeavor for the coordination of development of these best practice guidelines in lipidomics and is embedded within the International Lipidomics Society. It is the intention of this review to highlight the most quality-relevant aspects of the lipidomics workflow, including preanalytics, sample preparation, MS, and lipid species identification and quantitation. Furthermore, this review just does not only highlights examples of best practice but also sheds light on strengths, drawbacks, and pitfalls in the lipidomic analysis workflow. While this review is neither designed to be a step-by-step protocol by itself nor dedicated to a specific application of lipidomics, it should nevertheless provide the interested reader with links and original publications to obtain a comprehensive overview concerning the state-of-the-art practices in the field.

Effect of Sampling Rate and Data Pretreatment for Targeted and Nontargeted Analysis by Means of Liquid Chromatography Coupled to Drift Time Ion Mobility Quadruple Time-of-Flight Mass Spectrometry

Ion mobility as an additional separation dimension can help to resolve and annotate metabolite and lipid biomarkers and provides important information about the components in a sample. Identifying relevant information in the resulting data is challenging because of the complexity of the data and data evaluation strategies for both targeted or nontargeted workflows. Frequently, feature analysis is used as a first step to search for differences between samples in discovery workflows. However, follow-up experimentation often leads to more targeted data extraction methods. In both cases, optimizing data sets for data extraction can make an important contribution to the overall results. In this work, we evaluate the effect of experimental conditions including acquisition sampling rate and data pretreatment on lipid standards and lipid extracts as examples of complex biological samples analyzed by liquid chromatography coupled to drift time ion mobility quadrupole time-of-flight mass spectrometry. The results show that a reduction of both peak variation and background noise can be achieved by optimizing the sampling rate. The use of data pretreatment including data smoothing, intensity thresholding, and spike removal also play an important role in improving detection and annotation of analytes from complex biological samples, whereas nonoptimal data sampling rates and preprocessing can lead to adverse effects including the loss or alternation of small, or closely eluting, low-abundant peaks.

Advanced tandem mass spectrometry in metabolomics and lipidomics-methods and applications

Metabolomics and lipidomics are new drivers of the omics era as molecular signatures and selected analytes allow phenotypic characterization and serve as biomarkers, respectively. The growing capabilities of untargeted and targeted workflows, which primarily rely on mass spectrometric platforms, enable extensive charting or identification of bioactive metabolites and lipids. Structural annotation of these compounds is key in order to link specific molecular entities to defined biochemical functions or phenotypes. Tandem mass spectrometry (MS), first and foremost collision-induced dissociation (CID), is the method of choice to unveil structural details of metabolites and lipids. But CID fragment ions are often not sufficient to fully characterize analytes. Therefore, recent years have seen a surge in alternative tandem MS methodologies that aim to offer full structural characterization of metabolites and lipids. In this article, principles, capabilities, drawbacks, and first applications of these "advanced tandem mass spectrometry" strategies will be critically reviewed. This includes tandem MS methods that are based on electrons, photons, and ion/molecule, as well as ion/ion reactions, combining tandem MS with concepts from optical spectroscopy and making use of derivatization strategies. In the final sections of this review, the first applications of these methodologies in combination with liquid chromatography or mass spectrometry imaging are highlighted and future perspectives for research in metabolomics and lipidomics are discussed.

Nonalcoholic fatty liver disease stratification by liver lipidomics

Nonalcoholic fatty liver disease (NAFLD) is a common metabolic dysfunction leading to hepatic steatosis. However, NAFLD's global impact on the liver lipidome is poorly understood. Using high-resolution shotgun mass spectrometry, we quantified the molar abundance of 316 species from 22 major lipid classes in liver biopsies of 365 patients, including nonsteatotic patients with normal or excessive weight, patients diagnosed with NAFL (nonalcoholic fatty liver) or NASH (nonalcoholic steatohepatitis), and patients bearing common mutations of NAFLD-related protein factors. We confirmed the progressive accumulation of di- and triacylglycerols and cholesteryl esters in the liver of NAFL and NASH patients, while the bulk composition of glycerophospho- and sphingolipids remained unchanged. Further stratification by biclustering analysis identified sphingomyelin species comprising n24:2 fatty acid moieties as membrane lipid markers of NAFLD. Normalized relative abundance of sphingomyelins SM 43:3;2 and SM 43:1;2 containing n24:2 and n24:0 fatty acid moieties, respectively, showed opposite trends during NAFLD progression and distinguished NAFL and NASH lipidomes from the lipidome of nonsteatotic livers. Together with several glycerophospholipids containing a C22:6 fatty acid moiety, these lipids serve as markers of early and advanced stages of NAFL.

Integrated lipidomics and proteomics reveal cardiolipin alterations, upregulation of HADHA and long chain fatty acids in pancreatic cancer stem cells

Pancreatic cancer stem cells (PCSCs) play a key role in the aggressiveness of pancreatic ductal adenocarcinomas (PDAC); however, little is known about their signaling and metabolic pathways. Here we show that PCSCs have specific and common proteome and lipidome modulations. PCSCs displayed downregulation of lactate dehydrogenase A chain, and upregulation of trifunctional enzyme subunit alpha. The upregulated proteins of PCSCs are mainly involved in fatty acid (FA) elongation and biosynthesis of unsaturated FAs. Accordingly, lipidomics reveals an increase in long and very long-chain unsaturated FAs, which are products of fatty acid elongase-5 predicted as a key gene. Moreover, lipidomics showed the induction in PCSCs of molecular species of cardiolipin with mixed incorporation of 16:0, 18:1, and 18:2 acyl chains. Our data indicate a crucial role of FA elongation and alteration in cardiolipin acyl chain composition in PCSCs, representing attractive therapeutic targets in PDAC.

Non-canonical autophagy drives alternative ATG8 conjugation to phosphatidylserine

Autophagy is a fundamental catabolic process that uses a unique post-translational modification, the conjugation of ATG8 protein to phosphatidylethanolamine (PE). ATG8 lipidation also occurs during non-canonical autophagy, a parallel pathway involving conjugation of ATG8 to single membranes (CASM) at endolysosomal compartments, with key functions in immunity, vision, and neurobiology. It is widely assumed that CASM involves the same conjugation of ATG8 to PE, but this has not been formally tested. Here, we discover that all ATG8s can also undergo alternative lipidation to phosphatidylserine (PS) during CASM, induced pharmacologically, by LC3-associated phagocytosis or influenza A virus infection, in mammalian cells. Importantly, ATG8-PS and ATG8-PE adducts are differentially delipidated by the ATG4 family and bear different cellular dynamics, indicating significant molecular distinctions. These results provide important insights into autophagy signaling, revealing an alternative form of the hallmark ATG8 lipidation event. Furthermore, ATG8-PS provides a specific "molecular signature" for the non-canonical autophagy pathway.

HIGH RESOLUTION MASS SPECTROMETRY IN LIPIDOMICS

The boost of research output in lipidomics during the last decade is tightly linked to improved instrumentation in mass spectrometry. Associated with this trend is the shift from low resolution-toward high-resolution lipidomics platforms. This review article summarizes the state of the art in the lipidomics field with a particular focus on the merits of high mass resolution. Following some theoretical considerations on the benefits of high mass resolution in lipidomics, it starts with a historical perspective on lipid analysis by sector instruments and moves further to today's instrumental approaches, including shotgun lipidomics, liquid chromatography-mass spectrometry, matrix-assisted laser desorption ionization-time-of-flight, and imaging lipidomics. Subsequently, several data processing and data analysis software packages are critically evaluated with all their pros and cons. Finally, this article emphasizes the importance and necessity of quality standards as the field evolves from its pioneering phase into a mature and robust omics technology and lists various initiatives for improving the applicability of lipidomics. © 2020 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.

A map of mass spectrometry-based in silico fragmentation prediction and compound identification in metabolomics

Metabolomics, the comprehensive study of the metabolome, and lipidomics-the large-scale study of pathways and networks of cellular lipids-are major driving forces in enabling personalized medicine. Complicated and error-prone data analysis still remains a bottleneck, however, especially for identifying novel metabolites. Comparing experimental mass spectra to curated databases containing reference spectra has been the gold standard for identification of compounds, but constructing such databases is a costly and time-demanding task. Many software applications try to circumvent this process by utilizing cutting-edge advances in computational methods-including quantum chemistry and machine learning-and simulate mass spectra by performing theoretical, so called in silico fragmentations of compounds. Other solutions concentrate directly on experimental spectra and try to identify structural properties by investigating reoccurring patterns and the relationships between them. The considerable progress made in the field allows recent approaches to provide valuable clues to expedite annotation of experimental mass spectra. This review sheds light on individual strengths and weaknesses of these tools, and attempts to evaluate them-especially in view of lipidomics, when considering complex mixtures found in biological samples as well as mass spectrometer inter-instrument variability.

Metabolomics and Lipidomics: Expanding the Molecular Landscape of Exercise Biology

Dynamic changes in circulating and tissue metabolites and lipids occur in response to exercise-induced cellular and whole-body energy demands to maintain metabolic homeostasis. The metabolome and lipidome in a given biological system provides a molecular snapshot of these rapid and complex metabolic perturbations. The application of metabolomics and lipidomics to map the metabolic responses to an acute bout of aerobic/endurance or resistance exercise has dramatically expanded over the past decade thanks to major analytical advancements, with most exercise-related studies to date focused on analyzing human biofluids and tissues. Experimental and analytical considerations, as well as complementary studies using animal model systems, are warranted to help overcome challenges associated with large human interindividual variability and decipher the breadth of molecular mechanisms underlying the metabolic health-promoting effects of exercise. In this review, we provide a guide for exercise researchers regarding analytical techniques and experimental workflows commonly used in metabolomics and lipidomics. Furthermore, we discuss advancements in human and mammalian exercise research utilizing metabolomic and lipidomic approaches in the last decade, as well as highlight key technical considerations and remaining knowledge gaps to continue expanding the molecular landscape of exercise biology.

Asymmetric opening of the homopentameric 5-HT3A serotonin receptor in lipid bilayers

Pentameric ligand-gated ion channels (pLGICs) of the Cys-loop receptor family are key players in fast signal transduction throughout the nervous system. They have been shown to be modulated by the lipid environment, however the underlying mechanism is not well understood. We report three structures of the Cys-loop 5-HT_3A serotonin receptor (5HT₃R) reconstituted into saposin-based lipid bilayer discs: a symmetric and an asymmetric apo state, and an asymmetric agonist-bound state. In comparison to previously published 5HT₃R conformations in detergent, the lipid bilayer stabilises the receptor in a more tightly packed, ‘coupled’ state, involving a cluster of highly conserved residues. In consequence, the agonist-bound receptor conformation adopts a wide-open pore capable of conducting sodium ions in unbiased molecular dynamics (MD) simulations. Taken together, we provide a structural basis for the modulation of 5HT₃R by the membrane environment, and a model for asymmetric activation of the receptor.

Pentameric ligand-gated ion channels (pLGICs) are key players in neurotransmission and have been shown to be modulated by the lipid environment, however the underlying mechanism is not well understood. Here, the authors report structures of the pLGIC 5-HT_3A serotonin receptor reconstituted into lipid bilayer discs and reveal lipid–protein interactions as well as asymmetric activation of the homopentameric receptor.