Identification of Lipid Heterogeneity and Diversity in the Developing Human Brain

Single-Cell Lipidomics by LC-MS Interlaboratory Study Reveals the Impact of X-ray Irradiation on a Pancreatic Cancer Cell Line and Its Bystanders

Live single-cell lipidomics by liquid chromatography mass spectrometry (LC-MS) is a nascent and rapidly growing field which can shed new light on infectious diseases, cancer, immunology, and drug delivery. There are now a growing number of laboratories that can isolate single cells and laboratories that can perform lipidomics analysis at correspondingly low sample volumes, but there is a lack of validation data. We have carried out the first interlaboratory LC-MS lipidomics experiment for single cells, aimed at filling this gap. We present a novel workflow to enable interlaboratory studies, comprising live-cell imaging and single-cell isolation, followed by freeze-drying, international shipping, reconstitution, and untargeted lipidomics analysis. We applied this methodology to reveal radiation-induced bystander effects in pancreatic cancer cells. X-ray irradiated cells and their bystanders sampled live 48 h postirradiation demonstrated reduced lipid abundance compared to controls, with distinct changes in molar ratios of several polyunsaturated lipids. This demonstrates for the first time that radiation can cause considerable cellular lipid remodelling, not only at the site of delivery. A striking similarity in lipid changes was observed between the two participating laboratories despite differences in sample preparation and analysis methods. Our results are further corroborated by live-cell imaging analysis of lipid droplets. This work serves as an important validation and demonstration of the nascent and rapidly growing field of live single-cell lipidomics.

Bidirectional Mendelian randomization analysis of plasma lipidome and psychiatric disorders

BACKGROUND

Evidence from observational studies and clinical experiments suggests a close association between plasma lipidome and psychiatric disorders. However, the causal relationship between plasma lipidome and psychiatric disorders remains insufficiently determined. Plasma lipidome are relatively easy to measure and regulate clinically, and they play a crucial role in neuronal signal transduction, making them a focus of interest as potential therapeutic targets for psychiatric disorders.

METHODS

In this study, we utilized the latest Finnish population-based genome-wide association study (GWAS) data on 179 lipid species. We downloaded data on five psychiatric disorders from the IEU database, including schizophrenia, bipolar disorder, depression, autism from the PGC consortium, and anxiety disorder from the Neale lab. Using two-sample bidirectional Mendelian randomization (MR) analysis, we assessed the relationship between these 179 lipid species and the risk of the five psychiatric disorders. To validate the assumptions of Mendelian randomization, we conducted tests for horizontal pleiotropy and heterogeneity.

RESULTS

After applying FDR correction to assess the relationship between 179 lipid species traits and the risk of five psychiatric disorders, our analysis provided evidence of a causal relationship specifically between genetic susceptibility in the plasma lipidome and bipolar disorder. This relationship notably involves eight phosphatidylcholines (PCs) and two sterols, with PCs displaying a dual and complex role in the disorder. Reverse Mendelian randomization (MR) analysis did not reveal a significant causal impact of psychiatric disorders on the plasma lipidome.

LIMITATIONS

Despite using two-sample bidirectional Mendelian randomization analysis, the complex biological pathways and potential confounding factors may still affect the accuracy of the causal relationships. The impact of genetic variations on the lipidome and psychiatric disorders may involve multiple mechanisms, which cannot be fully elucidated in this study.

CONCLUSION

This study identified a causal relationship between genetic susceptibility in plasma lipidome and bipolar disorder, indicating that plasma lipidome may influence the risk of psychiatric disorders and providing direction for exploring them as potential intervention targets. The findings not only deepen our understanding of the etiology of psychiatric disorders but also provide a critical theoretical foundation for future clinical interventions and prevention strategies, potentially contributing to the development of novel therapeutic approaches.

Maternal omega-3 polyunsaturated fatty acids improved levels of DHA-enriched phosphatidylethanolamines and enriched lipid clustering in the neuronal membranes of C57BL/6 mice fetal brains during gestation

The composition of brain lipids is crucial for neurodevelopment and brain function. Diets enriched in omega (n)-3 polyunsaturated fatty acids (PUFA) can modulate brain lipid composition. However, the influence of maternal n-3 PUFA intake on fetal brain lipidome and neuronal membrane structure during gestation is not well studied. Eight-week-old female C57BL/6 mice were fed low or high n-3 PUFA semi-purified diets for two weeks before mating and during gestation. Fetal brain lipidome and neuronal membrane structure were studied at gestation day (GD) 12.5 (mid) and 18.5 (late) using liquid chromatography high-resolution accurate mass tandem mass spectrometry and computational techniques. Maternal diets high in n-3 PUFA increased fetal brain total phosphoethanolamine, phosphoinositol, phosphoglycerol, and phosphoserine glycerophospholipids, compared to the low n-3 PUFA diet. Docosahexaenoic acid (DHA, 22:6n-3)-enriched phosphatidylethanolamine (PE), phosphatidylcholine (PC), phosphatidylserine (PS), and lyso-PC (LPC) fatty acyl species increased as gestation progressed in the high n-3 PUFA group, compared to low n-3 PUFA. These fatty acyl species and phospholipids promote neurotransmission, memory, and cognition. A high n-3 PUFA diet increased the area per lipid in fetal neuronal membranes as gestation progressed, indicating improved membrane fluidity. Furthermore, a high n-3 PUFA diet increased the clustering of membrane lipids associated with neurotransmission, memory, and cognition (ceramide, PE, and cholesteryl ester) as gestation progressed. Our findings show for the first time that maternal diets high in n-3 PUFA before and during gestation improve fetal brain lipidome and membrane area per lipid that may enhance brain development and function.

Region-specific quantitation of glycosphingolipids in the elderly human brain with Nanoflow MEA Chip Q/ToF mass spectrometry

Glycosphingolipids are a unique class of bioactive lipids responsible for lateral membrane organization and signaling found in high abundance in the central nervous system. Using nanoflow MEA Chip Q/ToF mass spectrometry, we profiled the intact glycosphingolipids of the elderly human brain in a region-specific manner. By chromatographic separation of glycan and ceramide isomers, we determined gangliosides to be the highest source of heterogeneity between regions with the expression of a- and b-series glycan structures. Investigation of these trends showed that specific glycan structures were, in part, determined by the structure of their lipid backbone. This study provides insight into the dynamic process of membrane remodeling in the brain during aging.

Recent Developments in Single-Cell Metabolomics by Mass Spectrometry─A Perspective

Recent advancements in single-cell (sc) resolution analyses, particularly in sc transcriptomics and sc proteomics, have revolutionized our ability to probe and understand cellular heterogeneity. The study of metabolism through small molecules, metabolomics, provides an additional level of information otherwise unattainable by transcriptomics or proteomics by shedding light on the metabolic pathways that translate gene expression into functional outcomes. Metabolic heterogeneity, critical in health and disease, impacts developmental outcomes, disease progression, and treatment responses. However, dedicated approaches probing the sc metabolome have not reached the maturity of other sc omics technologies. Over the past decade, innovations in sc metabolomics have addressed some of the practical limitations, including cell isolation, signal sensitivity, and throughput. To fully exploit their potential in biological research, however, remaining challenges must be thoroughly addressed. Additionally, integrating sc metabolomics with orthogonal sc techniques will be required to validate relevant results and gain systems-level understanding. This perspective offers a broad-stroke overview of recent mass spectrometry (MS)-based sc metabolomics advancements, focusing on ongoing challenges from a biologist's viewpoint, aimed at addressing pertinent and innovative biological questions. Additionally, we emphasize the use of orthogonal approaches and showcase biological systems that these sophisticated methodologies are apt to explore.

Gangliosides and Cholesterol: Dual Regulators of Neuronal Membrane Framework in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation. Diagnosing ASD is complex, and the criteria for diagnosis, as well as the term ASD, have changed during the last decades. Diagnosis is made based on observation and accomplishment of specific diagnostic criteria, while a particular biomarker of ASD does not yet exist. However, studies universally report a disequilibrium in membrane lipid content, pointing to a unique neurolipid signature of ASD. This review sheds light on the possible role of cholesterol and gangliosides, complex membrane glycosphingolipids, in the development of ASD. In addition to maintaining membrane integrity, neuronal signaling, and synaptic plasticity, these lipids play a role in neurotransmitter release and calcium signaling. Evidence linking ASD to lipidome changes includes low cholesterol levels, unusual ganglioside levels, and unique metabolic profiles. ASD symptoms may be mitigated with therapeutic interventions targeting the lipid composition of membranes. However, restoring membrane equilibrium in the central nervous system remains a challenge. This review underscores the need for comprehensive research into lipid metabolism to uncover practical insights into ASD etiology and treatment as lipidomics emerges as a major area in ASD research.

Don't Be Surprised When These Surprise You: Some Infrequently Studied Sphingoid Bases, Metabolites, and Factors That Should Be Kept in Mind During Sphingolipidomic Studies

Sphingolipidomic mass spectrometry has provided valuable information-and surprises-about sphingolipid structures, metabolism, and functions in normal biological processes and disease. Nonetheless, many noteworthy compounds are not routinely determined, such as the following: most of the sphingoid bases that mammals biosynthesize de novo other than sphingosine (and sometimes sphinganine) or acquire from exogenous sources; infrequently considered metabolites of sphingoid bases, such as N-(methyl)n-derivatives; "ceramides" other than the most common N-acylsphingosines; and complex sphingolipids other than sphingomyelins and simple glycosphingolipids, including glucosyl- and galactosylceramides, which are usually reported as "monohexosylceramides". These and other subspecies are discussed, as well as some of the circumstances when they are likely to be seen (or present and missed) due to experimental conditions that can influence sphingolipid metabolism, uptake from the diet or from the microbiome, or as artifacts produced during extraction and analysis. If these compounds and factors are kept in mind during the design and interpretation of lipidomic studies, investigators are likely to be surprised by how often they appear and thereby advance knowledge about them.

Lipids shape brain function through ion channel and receptor modulations: physiological mechanisms and clinical perspectives

Lipids represent the most abundant molecular type in the brain, with a fat content of ∼60% of the dry brain weight in humans. Despite this fact, little attention has been paid to circumscribe the dynamic role of lipids in brain function and disease. Membrane lipids such as cholesterol, phosphoinositide, sphingolipids, arachidonic acid, and endocannabinoids finely regulate both synaptic receptors and ion channels that ensure critical neural functions. After a brief introduction on brain lipids and their respective properties, we review here their role in regulating synaptic function and ion channel activity, action potential propagation, neuronal development, and functional plasticity and their contribution in the development of neurological and neuropsychiatric diseases. We also provide possible directions for future research on lipid function in brain plasticity and diseases.

Lipidomic profiling of mouse brain and human neuron cultures reveals a role for Mboat7 in mTOR-dependent neuronal migration

Mutations in lipid regulator genes are a frequent cause of autism spectrum disorder, including those regulating phosphatidylinositol (PI) and phosphoinositide 3-kinase signaling. MBOAT7 encodes a key acyltransferase in PI synthesis and is mutated in an autism-related condition with neurodevelopmental delay and epilepsy. Using liquid chromatography-tandem mass spectrometry, we analyzed the PI-associated glycerolipidome in mice and humans during neurodevelopment and found dynamic regulation at times corresponding to neural apoptosis in the brains of Mboat7 knockout mice. Mboat7 function was necessary for polyunsaturated lipid synthesis and cortical neural migration, and loss resulted in massive accumulation of the precursor lysophosphatidylinositol and hyperactive mTOR signaling. Inhibiting mTOR signaling rescued migration defects. Our findings demonstrate roles for lipid remodeling during neurodevelopment and implicate lipid regulation in neuronal migration, revealing potential paths to treatment for MBOAT7 deficiency.

Effects of Sex and Western Diet on Spatial Lipidomic Profiles for the Hippocampus, Cortex, and Corpus Callosum in Mice Using MALDI MSI

Diet is inextricably linked to human health and biological functionality. Reduced cognitive function among other health issues has been correlated with a western diet (WD) in mouse models, indicating that increases in neurodegeneration could be fueled in part by a poor diet. In this study, we use matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) to spatially map the lipidomic profiles of male and female mice that were fed a high-fat, high-sucrose WD for a period of 7 weeks. Our findings concluded that the cortex and corpus callosum showed significant lipid variation by WD in female mice, while there was little to no variation in the hippocampus, regardless of sex. On the other hand, lipid profiles were significantly affected by sex in all regions. Overall, 83 lipids were putatively identified in the mouse brain; among them, HexCer(40:1;O3) and PE(34:0) were found to have the largest statistical difference based on diet for female mice in the cortex and corpus callosum, respectively. Additional lipid changes are noted and can serve as a metric for understanding the brain's metabolomic response to changes in diet, particularly as it relates to disease.

Effects of a Serotonergic Psychedelic on the Lipid Bilayer

Serotonergic psychedelics, known for their hallucinogenic effects, have attracted interest due to their ability to enhance neuronal plasticity and potential therapeutic benefits. Although psychedelic-enhanced neuroplasticity is believed to require activation of 5-hydroxytryptamine (serotonin) 2A receptors (5-HT2ARs), serotonin itself is less effective in promoting such plasticity. Also, the psychoplastogenic effects of these molecules correlate with their lipophilicity, leading to suggestions that they act by influencing the intracellular receptors. However, their lipophilicity also implies that a significant quantity of lipids is accumulated in the lipid bilayer, potentially altering the physical properties of the membrane. Here, we probe whether the serotonergic psychedelic 2,5-dimethoxy-4-iodoamphetamine (DOI) can affect the properties of artificial lipid bilayers and if that can potentially affect processes such as membrane fusion. Solid-state NMR spectroscopy shows that the DOI strongly induces disorder in the lipid acyl chains. Atomic force microscopy shows that it can shrink the ordered domains in a biphasic lipid bilayer and can reduce the force needed to form nanopores in the membrane. Fluorescence correlation spectroscopy shows that DOI can promote vesicle association, and total internal fluorescence microscopy shows that it enhances vesicle fusion to a supported lipid bilayer. While serotonin has also recently been shown to cause similar effects, DOI is more than two orders of magnitude more potent in evoking these. Our results suggest that the receptor-independent effects of serotonergic psychedelics on lipid membranes may contribute to their biological actions, especially those that require significant membrane remodeling, such as neuronal plasticity.

GMP affected assembly behaviors of phosphatidylethanolamine monolayers elucidated by multi-resolved SFG-VS and BAM

The interaction between nucleotide molecules and lipid molecules plays important roles in cell activities, but the molecular mechanism is very elusive. In the present study, a small but noticeable interaction between the negatively charged phosphatidylethanolamine (PE) and Guanosine monophosphate (GMP) molecules was observed from the PE monolayer at the air/water interface. As shown by the sum frequency generation (SFG) spectra and Pi-A isotherm of the PE monolayer, the interaction between the PE and GMP molecules imposes very small changes to the PE molecules. However, the Brewster angle microscopy (BAM) technique revealed that the assembly conformations of PE molecules are significantly changed by the adsorption of GMP molecules. By comparing the SFG spectra of PE monolayers after the adsorption of GMP, guanosine and guanine, it is also shown that the hydrogen bonding effect plays an important role in the nucleotide-PE interactions. These results provide fundamental insight into the structure changes during the nucleotide-lipid interaction, which may shed light on the molecular mechanism of viral infection, DNA drug delivery, and cell membrane curvature control in the brain or neurons.

Probe-based mass spectrometry approaches for single-cell and single-organelle measurements

Exploring the chemical content of individual cells not only reveals underlying cell-to-cell chemical heterogeneity but is also a key component in understanding how cells combine to form emergent properties of cellular networks and tissues. Recent technological advances in many analytical techniques including mass spectrometry (MS) have improved instrumental limits of detection and laser/ion probe dimensions, allowing the analysis of micron and submicron sized areas. In the case of MS, these improvements combined with MS's broad analyte detection capabilities have enabled the rise of single-cell and single-organelle chemical characterization. As the chemical coverage and throughput of single-cell measurements increase, more advanced statistical and data analysis methods have aided in data visualization and interpretation. This review focuses on secondary ion MS and matrix-assisted laser desorption/ionization MS approaches for single-cell and single-organelle characterization, which is followed by advances in mass spectral data visualization and analysis.

Spatial lipidomics maps brain alterations associated with mild traumatic brain injury

Traumatic brain injury (TBI) is a global public health problem with 50-60 million incidents per year, most of which are considered mild (mTBI) and many of these repetitive (rmTBI). Despite their massive implications, the pathologies of mTBI and rmTBI are not fully understood, with a paucity of information on brain lipid dysregulation following mild injury event(s). To gain more insight on mTBI and rmTBI pathology, a non-targeted spatial lipidomics workflow utilizing high resolution mass spectrometry imaging was developed to map brain region-specific lipid alterations in rats following injury. Discriminant multivariate models were created for regions of interest including the hippocampus, cortex, and corpus callosum to pinpoint lipid species that differentiated between injured and sham animals. A multivariate model focused on the hippocampus region differentiated injured brain tissues with an area under the curve of 0.99 using only four lipid species. Lipid classes that were consistently discriminant included polyunsaturated fatty acid-containing phosphatidylcholines (PC), lysophosphatidylcholines (LPC), LPC-plasmalogens (LPC-P) and PC potassium adducts. Many of the polyunsaturated fatty acid-containing PC and LPC-P selected have never been previously reported as altered in mTBI. The observed lipid alterations indicate that neuroinflammation and oxidative stress are important pathologies that could serve to explain cognitive deficits associated with rmTBI. Therapeutics which target or attenuate these pathologies may be beneficial to limit persistent damage following a mild brain injury event.

Lipidome atlas of the adult human brain

Lipids are the most abundant but poorly explored components of the human brain. Here, we present a lipidome map of the human brain comprising 75 regions, including 52 neocortical ones. The lipidome composition varies greatly among the brain regions, affecting 93% of the 419 analyzed lipids. These differences reflect the brain's structural characteristics, such as myelin content (345 lipids) and cell type composition (353 lipids), but also functional traits: functional connectivity (76 lipids) and information processing hierarchy (60 lipids). Combining lipid composition and mRNA expression data further enhances functional connectivity association. Biochemically, lipids linked with structural and functional brain features display distinct lipid class distribution, unsaturation extent, and prevalence of omega-3 and omega-6 fatty acid residues. We verified our conclusions by parallel analysis of three adult macaque brains, targeted analysis of 216 lipids, mass spectrometry imaging, and lipidome assessment of sorted murine neurons.

Protein-Mediated Changes in Membrane Fluidity and Ordering: Insights into the Molecular Mechanism and Implications for Cellular Function

Probing protein-membrane interactions is vital for understanding biological functionality for various applications such as drug development, targeted drug delivery, and creation of functional biomaterials for medical and industrial purposes. In this study, we have investigated interaction of Human Serum Albumin (HSA) with two different lipids, dipalmitoylphosphatidylglycerol (dDPPG) and dipalmitoylphosphatidylcholine (dDPPC), using Vibrational Sum Frequency Generation spectroscopy at different membrane fluidity values. In the liquid-expanded (LE) state of the lipid, HSA (at pH 3.5) deeply intercalated lipid chains through a combination of electrostatic and hydrophobic interactions, which resulted in more ordering of the lipid chains. However, in the liquid-condensed (LC) state, protein intercalation is decreased due to tighter lipid packing. Moreover, our findings revealed distinct differences in HSA's interaction with dDPPG and dDPPC lipids. The interaction with dDPPC remained relatively weak compared to dDPPG. These results shed light on the significance of protein mediated changes in lipid characteristics, which hold considerable implications for understanding membrane protein behavior, lipid-mediated cellular processes, and lipid-based biomaterial design.

Studying the Effects of Dissolved Noble Gases and High Hydrostatic Pressure on the Spherical DOPC Bilayer Using Molecular Dynamic Simulations

Fine-grained molecular dynamics simulations have been conducted to depict lipid objects enclosed in water and interacting with a series of noble gases dissolved in the medium. The simple point-charge (SPC) water system, featuring a boundary composed of 1,2-Dioleoyl-sn-glycero-3-phosphocholine (DOPC) molecules, maintained stability throughout the simulation under standard conditions. This allowed for the accurate modeling of the effects of hydrostatic pressure at an ambient pressure of 25 bar. The chosen pressure references the 240 m depth of seawater: the horizon frequently used by commercial divers, who comprise the primary patient population of the neurological complication of inert gas narcosis and the consequences of high-pressure neurological syndrome. To quantify and validate the neurological effects of noble gases and discriminate them from high hydrostatic pressure, we reduced the dissolved gas molar concentration to 1.5%, three times smaller than what we previously tested for the planar bilayer (3.5%). The nucleation and growth of xenon, argon and neon nanobubbles proved consistent with the data from the planar bilayer simulations. On the other hand, hyperbaric helium induces only a residual distorting effect on the liposome, with no significant condensed gas fraction observed within the hydrophobic core. The bubbles were distributed over a large volume-both in the bulk solvent and in the lipid phase-thereby causing substantial membrane distortion. This finding serves as evidence of the validity of the multisite distortion hypothesis for the neurological effect of inert gases at high pressure.

Lipid Wizard: Analysis Software for Comprehensive Two-Dimensional Liquid Chromatography-Mass Spectrometry-Based Lipid Profiling

Lipids play a significant role in life activities and participate in the biological system through different pathways. Although comprehensive two-dimensional liquid chromatography-mass spectrometry (2DLC-MS) has been developed to profile lipid abundance changes, lipid identification and quantification from 2DLC-MS data remain a challenge. We created Lipid Wizard, open-source software for lipid assignment and isotopic peak stripping of the 2DLC-MS data. Lipid Wizard takes the peak list deconvoluted from the 2DLC-MS data as input and assigns each isotopic peak to the lipids recorded in the LIPID MAPS database by precursor ion m/z matching. The matched lipids are then filtered by the first-dimension retention time (1D RT), followed by the second-dimension retention time (2D RT), where the 2D RT of each lipid is predicted using an equivalent carbon number (ECN) model. The remaining assigned lipids are used for isotopic peak stripping via an iterative linear regression. The performance of Lipid Wizard was tested using a set of lipid standards and then applied to study the lipid changes in the livers of mice (fat-1) fed with alcohol.

Quantitative mass spectrometry imaging: therapeutics & biomolecules

Mass spectrometry imaging (MSI) has become increasingly utilized in the analysis of biological molecules. MSI grants the ability to spatially map thousands of molecules within one experimental run in a label-free manner. While MSI is considered by most to be a qualitative method, recent advancements in instrumentation, sample preparation, and development of standards has made quantitative MSI (qMSI) more common. In this feature article, we present a tailored review of recent advancements in qMSI of therapeutics and biomolecules such as lipids and peptides/proteins. We also provide detailed experimental considerations for conducting qMSI studies on biological samples, aiming to advance the methodology.

Mass Spectrometry-based Single-Cell Lipidomics: Advancements, Challenges, and the Path Forward

In the past decade, lipidomics, now recognized as standalone subdiscipline of metabolomics, has gained considerable attention. Due to its sensitivity and unparalleled versatility, mass spectrometry (MS) has emerged as the tool of choice for lipid identification and detection. Traditional MS-based lipidomics are performed on bulk cell samples. While informative, these bulk-scale cellular lipidome measurements mask cellular heterogeneity across seemingly homogeneous populations of cells. Unfortunately, single cell lipidomics methodology and analyses are considerably behind genomics, transcriptomics, and proteomics. Therefore, the cell-to-cell heterogeneity and related function remains largely unexplored for lipidomics. Herein, we review recent advances in MS-based single cell lipidomics. We also explore the root causes for the slow development of single-cell lipidomics techniques. We aim to provide insights on the pivotal knowledge gaps that have been neglected, prohibiting the propulsion of the single-cell lipidomics field forward, while also providing our perspective towards future methodologies that can pave a path forward.

Chemical tagging mass spectrometry: an approach for single-cell omics

Single-cell (SC) analysis offers new insights into the study of fundamental biological phenomena and cellular heterogeneity. The superior sensitivity, high throughput, and rich chemical information provided by mass spectrometry (MS) allow MS to emerge as a leading technology for molecular profiling of SC omics, including the SC metabolome, lipidome, and proteome. However, issues such as ionization suppression, low concentration, and huge span of dynamic concentrations of SC components lead to poor MS response for certain types of molecules. It is noted that chemical tagging/derivatization has been adopted in SCMS analysis, and this strategy has been proven an effective solution to circumvent these issues in SCMS analysis. Herein, we review the basic principle and general strategies of chemical tagging/derivatization in SCMS analysis, along with recent applications of chemical derivatization to single-cell metabolomics and multiplexed proteomics, as well as SCMS imaging. Furthermore, the challenges and opportunities for the improvement of chemical derivatization strategies in SCMS analysis are discussed.

Single-cell lipidomics enabled by dual-polarity ionization and ion mobility-mass spectrometry imaging

Single-cell (SC) analysis provides unique insight into individual cell dynamics and cell-to-cell heterogeneity. Here, we utilize trapped ion mobility separation coupled with dual-polarity ionization mass spectrometry imaging (MSI) to enable high-throughput in situ profiling of the SC lipidome. Multimodal SC imaging, in which dual-polarity-mode MSI is used to perform serial data acquisition runs on individual cells, significantly enhanced SC lipidome coverage. High-spatial resolution SC-MSI identifies both inter- and intracellular lipid heterogeneity; this heterogeneity is further explicated by Uniform Manifold Approximation and Projection and machine learning-driven classifications. We characterize SC lipidome alteration in response to stearoyl-CoA desaturase 1 inhibition and, additionally, identify cell-layer specific lipid distribution patterns in mouse cerebellar cortex. This integrated multimodal SC-MSI technology enables high-resolution spatial mapping of intercellular and cell-to-cell lipidome heterogeneity, SC lipidome remodeling induced by pharmacological intervention, and region-specific lipid diversity within tissue.

Mass spectrometry imaging as an emerging tool for studying metabolism in human brain organoids

Human brain organoids are emerging models to study human brain development and pathology as they recapitulate the development and characteristics of major neural cell types, and enable manipulation through an in vitro system. Over the past decade, with the advent of spatial technologies, mass spectrometry imaging (MSI) has become a prominent tool for metabolic microscopy, providing label-free, non-targeted molecular and spatial distribution information of the metabolites within tissue, including lipids. This technology has never been used for studies of brain organoids and here, we set out to develop a standardized protocol for preparation and mass spectrometry imaging of human brain organoids. We present an optimized and validated sample preparation protocol, including sample fixation, optimal embedding solution, homogenous deposition of matrices, data acquisition and processing to maximize the molecular information derived from mass spectrometry imaging. We focus on lipids in organoids, as they play critical roles during cellular and brain development. Using high spatial and mass resolution in positive- and negative-ion modes, we detected 260 lipids in the organoids. Seven of them were uniquely localized within the neurogenic niches or rosettes as confirmed by histology, suggesting their importance for neuroprogenitor proliferation. We observed a particularly striking distribution of ceramide-phosphoethanolamine CerPE 36:1; O2 which was restricted within rosettes and of phosphatidyl-ethanolamine PE 38:3, which was distributed throughout the organoid tissue but not in rosettes. This suggests that ceramide in this particular lipid species might be important for neuroprogenitor biology, while its removal may be important for terminal differentiation of their progeny. Overall, our study establishes the first optimized experimental pipeline and data processing strategy for mass spectrometry imaging of human brain organoids, allowing direct comparison of lipid signal intensities and distributions in these tissues. Further, our data shed new light on the complex processes that govern brain development by identifying specific lipid signatures that may play a role in cell fate trajectories. Mass spectrometry imaging thus has great potential in advancing our understanding of early brain development as well as disease modeling and drug discovery.

Single-Cell and Subcellular Analysis Using Ultrahigh Resolution 21 T MALDI FTICR Mass Spectrometry

The mammalian brain contains ∼20,000 distinct lipid species that contribute to its structural organization and function. The lipid profiles of cells change in response to a variety of cellular signals and environmental conditions that result in modulation of cell function through alteration of phenotype. The limited sample material combined with the vast chemical diversity of lipids makes comprehensive lipid profiling of individual cells challenging. Here, we leverage the resolving power of a 21 T Fourier-transform ion cyclotron resonance (FTICR) mass spectrometer for chemical characterization of individual hippocampal cells at ultrahigh mass resolution. The accuracy of the acquired data allowed differentiation of freshly isolated and cultured hippocampal cell populations, as well as finding differences in lipids between the soma and neuronal processes of the same cell. Differences in lipids include TG 42:2 observed solely in the cell bodies and SM 34:1;O2 found only in the cellular processes. The work represents the first mammalian single cells analyzed at ultrahigh resolution and is an advance in the performance of mass spectrometry (MS) for single-cell research.

Large neutral amino acid levels tune perinatal neuronal excitability and survival

Little is known about the critical metabolic changes that neural cells have to undergo during development and how temporary shifts in this program can influence brain circuitries and behavior. Inspired by the discovery that mutations in SLC7A5, a transporter of metabolically essential large neutral amino acids (LNAAs), lead to autism, we employed metabolomic profiling to study the metabolic states of the cerebral cortex across different developmental stages. We found that the forebrain undergoes significant metabolic remodeling throughout development, with certain groups of metabolites showing stage-specific changes, but what are the consequences of perturbing this metabolic program? By manipulating Slc7a5 expression in neural cells, we found that the metabolism of LNAAs and lipids are interconnected in the cortex. Deletion of Slc7a5 in neurons affects the postnatal metabolic state, leading to a shift in lipid metabolism. Additionally, it causes stage- and cell-type-specific alterations in neuronal activity patterns, resulting in a long-term circuit dysfunction.

Single-Cell Metabolomics-Based Strategy for Studying the Mechanisms of Drug Action

Studying the mechanisms of drug antitumor activity at the single-cell level can provide information about the responses of cell subpopulations to drug therapy, which is essential for the accurate treatment of cancer. Due to the small size of single cells and the low contents of metabolites, metabolomics-based approaches to studying the mechanisms of drug action at the single-cell level are lacking. Herein, we develop a label-free platform for studying the mechanisms of drug action based on single-cell metabolomics (sMDA-scM) by integrating intact living-cell electro-launching ionization mass spectrometry (ILCEI-MS) with metabolomics analysis. Using this platform, we reveal that non-small-cell lung cancer (NSCLC) cells treated by gefitinib can be clustered into two cell subpopulations with different metabolic responses. The glutathione metabolic pathway of the subpopulation containing 14.4% of the cells is not significantly affected by gefitinib, exhibiting certain resistance characteristics. The presence of these cells masked the judgment of whether cysteine and methionine metabolic pathway was remarkably influenced in the analysis of overall average results, revealing the heterogeneity of the response of single NSCLC cells to gefitinib treatment. The findings provide a basis for evaluating the early therapeutic effects of clinical medicines and insights for overcoming drug resistance in NSCLC subpopulations.

Large-Scale Multi-Omic Approaches and Atlas-Based Profiling for Cellular, Molecular, and Functional Specificity, Heterogeneity, and Diversity in the Endocannabinoid System

The endocannabinoid system (ECS) is a widely-recognized lipid messenger system involved in many aspects of our our lives in health and diseases [...].

Nanocapillary sampling coupled to liquid chromatography mass spectrometry delivers single cell drug measurement and lipid fingerprints

This work describes the development of a new approach to measure drug levels and lipid fingerprints in single living mammalian cells. Nanocapillary sampling is an approach that enables the selection and isolation of single living cells under microscope observation. Here, live single cell nanocapillary sampling is coupled to liquid chromatography for the first time. This allows molecular species to be separated prior to ionisation and improves measurement precision of drug analytes. The efficiency of transferring analytes from the sampling capillary into a vial was optimised in this work. The analysis was carried out using standard flow liquid chromatography coupled to widely available mass spectrometry instrumentation, highlighting opportunities for widespread adoption. The method was applied to 30 living cells, revealing cell-to-cell heterogeneity in the uptake of different drug molecules. Using this system, we detected 14-158 lipid features per single cell, revealing the association between bedaquiline uptake and lipid fingerprints.

Data-Driven and Machine Learning-Based Framework for Image-Guided Single-Cell Mass Spectrometry

Improved throughput of analysis and lowered limits of detection have allowed single-cell chemical analysis to go beyond the detection of a few molecules in such volume-limited samples, enabling researchers to characterize different functional states of individual cells. Image-guided single-cell mass spectrometry leverages optical and fluorescence microscopy in the high-throughput analysis of cellular and subcellular targets. In this work, we propose DATSIGMA (DAta-driven Tools for Single-cell analysis using Image-Guided MAss spectrometry), a workflow based on data-driven and machine learning approaches for feature extraction and enhanced interpretability of complex single-cell mass spectrometry data. Here, we implemented our toolset with user-friendly programs and tested it on multiple experimental data sets that cover a wide range of biological applications, including classifying various brain cell types. Because it is open-source, it offers a high level of customization and can be easily adapted to other types of single-cell mass spectrometry data.

Human Diacylglycerol Kinase ε N-Terminal Segment Regulates the Phosphatidylinositol Cycle, Controlling the Rate but Not the Acyl Chain Composition of Its Lipid Intermediates

Diacylglycerol kinase ε (DGKε), an enzyme of the phosphatidylinositol (PI) cycle, bears a highly conserved hydrophobic N-terminal segment, which was proposed to anchor the enzyme into the membrane. However, the importance of this segment to the DGKε function remains to be determined. To address this question, it is here reported an in silico and in vitro combined research strategy. Capitalizing on the AlphaFold 2.0 predicted structure of human DGKε, it is shown that its hydrophobic N-terminal segment anchors it into the membrane via a transmembrane α-helix. Coarse-grained based elastic network model studies showed that a conformational change in the hydrophobic N-terminal segment determines the proximity between the active site of DGKε and the membrane-water interface, likely regulating its kinase activity. In vitro studies with a purified DGKε construct lacking the hydrophobic N-terminal segment (His-SUMO*-Δ⁵⁰-DGKε) corroborated the role of the N-terminus in regulating DGKε enzymatic properties. The comparison between the enzymatic properties of DGKε and His-SUMO*-Δ⁵⁰-DGKε showed that the conserved N-terminal segment markedly inhibits the enzyme activity and its sensitivity to membrane intrinsic negative curvature, while also playing a role in the modulation of the enzyme by phosphatidylserine. On the other hand, this segment did not strongly affect its diacylglycerol acyl chain specificity, the modulation of the enzyme by membrane morphological changes, or the activation by phosphatidic acid-rich lipid domains. Hence, these results suggest that the conservation of the hydrophobic N-terminal segment of DGKε throughout evolution guaranteed not only membrane anchorage but also an efficient and elegant manner to regulate the rate of the PI cycle.

Profiling 26,000 Aplysia californica neurons by single cell mass spectrometry reveals neuronal populations with distinct neuropeptide profiles

Neuropeptides are a chemically diverse class of cell-to-cell signaling molecules that are widely expressed throughout the central nervous system, often in a cell-specific manner. While cell-to-cell differences in neuropeptides is expected, it is often unclear how exactly neuropeptide expression varies among neurons. Here we created a microscopy-guided, high-throughput single cell matrix-assisted laser desorption/ionization mass spectrometry approach to investigate the neuropeptide heterogeneity of individual neurons in the central nervous system of the neurobiological model Aplysia californica, the California sea hare. In all, we analyzed more than 26,000 neurons from 18 animals and assigned 866 peptides from 66 prohormones by mass matching against an in silico peptide library generated from known Aplysia prohormones retrieved from the UniProt database. Louvain-Jaccard (LJ) clustering of mass spectra from individual neurons revealed 40 unique neuronal populations, or LJ clusters, each with a distinct neuropeptide profile. Prohormones and their related peptides were generally found in single cells from ganglia consistent with the prohormones' previously known ganglion localizations. Several LJ clusters also revealed the cellular colocalization of behaviorally related prohormones, such as an LJ cluster exhibiting achatin and neuropeptide Y, which are involved in feeding, and another cluster characterized by urotensin II, small cardiac peptide, sensorin A, and FRFa, which have shown activity in the feeding network or are present in the feeding musculature. This mass spectrometry-based approach enables the robust categorization of large cell populations based on single cell neuropeptide content and is readily adaptable to the study of a range of animals and tissue types.

Cord blood sphingolipids are associated with atopic dermatitis and wheeze in the first year of life

Background

Allergen-sensitized pregnant mice have increased plasma levels of the lipids β-glucosylceramides (βGlcCers) that are transplacentally transferred to the fetus, increased subsets of proinflammatory dendritic cells in the fetal liver and pup lung, and increased allergen-induced offspring lung inflammation.

Objective

Our aim was to determine whether these preclinical observations extend to a human association of βGlcCers with wheeze and allergic disease in the prospective Wisconsin Infant Study Cohort.

Methods

We measured 74 lipids in cord blood plasma by using mass spectrometry detection of sphingolipids, eicosanoids, and docosinoids, as well as an ELISA for 13-hydroxyoctadecadienoic acid. Lipid profiles were determined by unbiased Uniform Manifold Approximation and Projection dimensional reduction machine learning. Lipid profiles and a proinflammatory lipid index were analyzed for association with maternal allergy and childhood outcomes of wheeze, atopic dermatitis, cord blood leukocytes, and total IgE level at age 1 year.

Results

Uniform Manifold Approximation and Projection analysis of lipids defined 8 cluster-specific plasma lipid profiles. Cluster 6 had significantly lower levels of plasma βGlcCers and a higher frequency of cord blood plasmacytoid dendritic cells that mediate anti-inflammatory responses, which is consistent with an anti-inflammatory profile. For clusters and for each infant, a proinflammatory lipid index was calculated to reflect the sum of the proinflammatory lipids minus the anti-inflammatory lipids that were significantly different than in cluster 6. The cluster proinflammatory lipid index was associated with cord blood basophil frequency and with wheeze and atopic dermatitis in the first year of life. The infant inflammatory lipid index was associated with increased risk of wheeze in the first year of life.

Conclusion

The cord blood proinflammatory lipid index is associated with early-life atopic dermatitis and wheezing.

Integrated Metabolomics and Lipidomics Reveal High Accumulation of Glycerophospholipids in Human Astrocytes under the Lipotoxic Effect of Palmitic Acid and Tibolone Protection

Lipotoxicity is a metabolic condition resulting from the accumulation of free fatty acids in non-adipose tissues which involves a series of pathological responses triggered after chronic exposure to high levels of fatty acids, severely detrimental to cellular homeostasis and viability. In brain, lipotoxicity affects both neurons and other cell types, notably astrocytes, leading to neurodegenerative processes, such as Alzheimer (AD) and Parkinson diseases (PD). In this study, we performed for the first time, a whole lipidomic characterization of Normal Human Astrocytes cultures exposed to toxic concentrations of palmitic acid and the protective compound tibolone, to establish and identify the set of potential metabolites that are modulated under these experimental treatments. The study covered 3843 features involved in the exo- and endo-metabolome extracts obtained from astrocytes with the mentioned treatments. Through multivariate statistical analysis such as PCA (principal component analysis), partial least squares (PLS-DA), clustering analysis, and machine learning enrichment analysis, it was possible to determine the specific metabolites that were affected by palmitic acid insult, such as phosphoethanolamines, phosphoserines phosphocholines and glycerophosphocholines, with their respective metabolic pathways impact. Moreover, our results suggest the importance of tibolone in the generation of neuroprotective metabolites by astrocytes and may be relevant to the development of neurodegenerative processes.