Single-Cell Mass Spectrometry Reveals Changes in Lipid and Metabolite Expression in RAW 264.7 Cells upon Lipopolysaccharide Stimulation

Single-Cell Untargeted Lipidomics Using Liquid Chromatography and Data-Dependent Acquisition after Live Cell Selection

We report the development and validation of an untargeted single-cell lipidomics method based on microflow chromatography coupled to a data-dependent mass spectrometry method for fragmentation-based identification of lipids. Given the absence of single-cell lipid standards, we show how the methodology should be optimized and validated using a dilute cell extract. The methodology is applied to dilute pancreatic cancer and macrophage cell extracts and standards to demonstrate the sensitivity requirements for confident assignment of lipids and classification of the cell type at the single-cell level. The method is then coupled to a system that can provide automated sampling of live, single cells into capillaries under microscope observation. This workflow retains the spatial information and morphology of cells during sampling and highlights the heterogeneity in lipid profiles observed at the single-cell level. The workflow is applied to show changes in single-cell lipid profiles as a response to oxidative stress, coinciding with expanded lipid droplets. This demonstrates that the workflow is sufficiently sensitive to observing changes in lipid profiles in response to a biological stimulus. Understanding how lipids vary in single cells will inform future research into a multitude of biological processes as lipids play important roles in structural, biophysical, energy storage, and signaling functions.

Advances in multimodal mass spectrometry for single-cell analysis and imaging enhancement

Multimodal mass spectrometry (MMS) incorporates an imaging modality with probe-based mass spectrometry (MS) to enable precise, targeted data acquisition and provide additional biological and chemical data not available by MS alone. Two categories of MMS are covered; in the first, an imaging modality guides the MS probe to target individual cells and to reduce acquisition time by automatically defining regions of interest. In the second category, imaging and MS data are coupled in the data analysis pipeline to increase the effective spatial resolution using a higher resolution imaging method, correct for tissue deformation, and incorporate fine morphological features in an MS imaging dataset. Recent methodological and computational developments are covered along with their application to single-cell and imaging analyses.

A Guide to MALDI Imaging Mass Spectrometry for Tissues

Imaging mass spectrometry is a well-established technology that can easily and succinctly communicate the spatial localization of molecules within samples. This review communicates the recent advances in the field, with a specific focus on matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) applied on tissues. The general sample preparation strategies for different analyte classes are explored, including special considerations for sample types (fresh frozen or formalin-fixed,) strategies for various analytes (lipids, metabolites, proteins, peptides, and glycans) and how multimodal imaging strategies can leverage the strengths of each approach is mentioned. This work explores appropriate experimental design approaches and standardization of processes needed for successful studies, as well as the various data analysis platforms available to analyze data and their strengths. The review concludes with applications of imaging mass spectrometry in various fields, with a focus on medical research, and some examples from plant biology and microbe metabolism are mentioned, to illustrate the breadth and depth of MALDI IMS.

Metabolomics: A useful tool for ischemic stroke research

Ischemic stroke (IS) is a multifactorial and heterogeneous disease. Despite years of studies, effective strategies for the diagnosis, management and treatment of stroke are still lacking in clinical practice. Metabolomics is a growing field in systems biology. It is starting to show promise in the identification of biomarkers and in the use of pharmacometabolomics to help patients with certain disorders choose their course of treatment. The development of metabolomics has enabled further and more biological applications. Particularly, metabolomics is increasingly being used to diagnose diseases, discover new drug targets, elucidate mechanisms, and monitor therapeutic outcomes and its potential effect on precision medicine. In this review, we reviewed some recent advances in the study of metabolomics as well as how metabolomics might be used to identify novel biomarkers and understand the mechanisms of IS. Then, the use of metabolomics approaches to investigate the molecular processes and active ingredients of Chinese herbal formulations with anti-IS capabilities is summarized. We finally summarized recent developments in single cell metabolomics for exploring the metabolic profiles of single cells. Although the field is relatively young, the development of single cell metabolomics promises to provide a powerful tool for unraveling the pathogenesis of IS.

Analytical Techniques for Single-Cell Biochemical Assays of Lipids

Lipids are essential cellular components forming membranes, serving as energy reserves, and acting as chemical messengers. Dysfunction in lipid metabolism and signaling is associated with a wide range of diseases including cancer and autoimmunity. Heterogeneity in cell behavior including lipid signaling is increasingly recognized as a driver of disease and drug resistance. This diversity in cellular responses as well as the roles of lipids in health and disease drive the need to quantify lipids within single cells. Single-cell lipid assays are challenging due to the small size of cells (∼1 pL) and the large numbers of lipid species present at concentrations spanning orders of magnitude. A growing number of methodologies enable assay of large numbers of lipid analytes, perform high-resolution spatial measurements, or permit highly sensitive lipid assays in single cells. Covered in this review are mass spectrometry, Raman imaging, and fluorescence-based assays including microscopy and microseparations.

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.

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.

FACS-assisted single-cell lipidome analysis of phosphatidylcholines and sphingomyelins in cells of different lineages

Recent advances in single-cell genomics and transcriptomics technologies have transformed our understanding of cellular heterogeneity in growth, development, ageing, and disease; however, methods for single-cell lipidomics have comparatively lagged behind in development. We have developed a method for the detection and quantification of a wide range of phosphatidylcholine and sphingomyelin species from single cells that combines fluorescence-assisted cell sorting with automated chip-based nanoESI and shotgun lipidomics. We show herein that our method is capable of quantifying more than 50 different phosphatidylcholine and sphingomyelin species from single cells and can easily distinguish between cells of different lineages or cells treated with exogenous fatty acids. Moreover, our method can detect more subtle differences in the lipidome between cell lines of the same cancer type. Our approach can be run in parallel with other single-cell technologies to deliver near-complete, high-throughput multi-omics data on cells with a similar phenotype and has the capacity to significantly advance our current knowledge on cellular heterogeneity.

Single-cell mass spectrometry

Owing to recent advances in mass spectrometry (MS), tens to hundreds of proteins, lipids, and small molecules can be measured in single cells. The ability to characterize the molecular heterogeneity of individual cells is necessary to define the full assortment of cell subtypes and identify their function. We review single-cell MS including high-throughput, targeted, mass cytometry-based approaches and antibody-free methods for broad profiling of the proteome and metabolome of single cells. The advantages and disadvantages of different methods are discussed, as well as the challenges and opportunities for further improvements in single-cell MS. These methods is being used in biomedicine in several applications including revealing tumor heterogeneity and high-content drug screening.

Mass spectrometry imaging to explore molecular heterogeneity in cell culture

Molecular analysis on the single-cell level represents a rapidly growing field in the life sciences. While bulk analysis from a pool of cells provides a general molecular profile, it is blind to heterogeneities between individual cells. This heterogeneity, however, is an inherent property of every cell population. Its analysis is fundamental to understanding the development, function, and role of specific cells of the same genotype that display different phenotypical properties. Single-cell mass spectrometry (MS) aims to provide broad molecular information for a significantly large number of cells to help decipher cellular heterogeneity using statistical analysis. Here, we present a sensitive approach to single-cell MS based on high-resolution MALDI-2-MS imaging in combination with MALDI-compatible staining and use of optical microscopy. Our approach allowed analyzing large amounts of unperturbed cells directly from the growth chamber. Confident coregistration of both modalities enabled a reliable compilation of single-cell mass spectra and a straightforward inclusion of optical as well as mass spectrometric features in the interpretation of data. The resulting multimodal datasets permit the use of various statistical methods like machine learning-driven classification and multivariate analysis based on molecular profile and establish a direct connection of MS data with microscopy information of individual cells. Displaying data in the form of histograms for individual signal intensities helps to investigate heterogeneous expression of specific lipids within the cell culture and to identify subpopulations intuitively. Ultimately, t-MALDI-2-MSI measurements at 2-µm pixel sizes deliver a glimpse of intracellular lipid distributions and reveal molecular profiles for subcellular domains.

Single-Cell Multiomics Analysis for Drug Discovery

Given the heterogeneity seen in cell populations within biological systems, analysis of single cells is necessary for studying mechanisms that cannot be identified on a bulk population level. There are significant variations in the biological and physiological function of cell populations due to the functional differences within, as well as between, single species as a result of the specific proteome, transcriptome, and metabolome that are unique to each individual cell. Single-cell analysis proves crucial in providing a comprehensive understanding of the biological and physiological properties underlying human health and disease. Omics technologies can help to examine proteins (proteomics), RNA molecules (transcriptomics), and the chemical processes involving metabolites (metabolomics) in cells, in addition to genomes. In this review, we discuss the value of multiomics in drug discovery and the importance of single-cell multiomics measurements. We will provide examples of the benefits of applying single-cell omics technologies in drug discovery and development. Moreover, we intend to show how multiomics offers the opportunity to understand the detailed events which produce or prevent disease, and ways in which the separate omics disciplines complement each other to build a broader, deeper knowledge base.

Metabolomic profiling of single enlarged lysosomes

Lysosomes are critical for cellular metabolism and are heterogeneously involved in various cellular processes. The ability to measure lysosomal metabolic heterogeneity is essential for understanding their physiological roles. We therefore built a single-lysosome mass spectrometry (SLMS) platform integrating lysosomal patch-clamp recording and induced nano-electrospray ionization (nanoESI)/mass spectrometry (MS) that enables concurrent metabolic and electrophysiological profiling of individual enlarged lysosomes. The accuracy and reliability of this technique were validated by supporting previous findings, such as the transportability of lysosomal cationic amino acids transporters such as PQLC2 and the lysosomal trapping of lysosomotropic, hydrophobic weak base drugs such as lidocaine. We derived metabolites from single lysosomes in various cell types and classified lysosomes into five major subpopulations based on their chemical and biological divergence. Senescence and carcinoma altered metabolic profiles of lysosomes in a type-specific manner. Thus, SLMS can open more avenues for investigating heterogeneous lysosomal metabolic changes during physiological and pathological processes.

Transmission-Mode MALDI Mass Spectrometry Imaging of Single Cells: Optimizing Sample Preparation Protocols

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) makes it possible to simultaneously visualize the spatial distribution of dozens to hundreds of different biomolecules (e.g., phospho- and glycolipids) in tissue sections and in cell cultures. The implementation of novel desorption and (post-)ionization techniques has recently pushed the pixel size of this imaging technique to the low micrometer scale and below and thus to a cellular and potentially sub-cellular level. However, to fully exploit this potential for cell biology and biomedicine, sample preparation becomes highly demanding. Here, we investigated the effect of several key parameters on the quality of the sample preparation and achievable spatial resolution, that include the washing, drying, chemical fixation, and matrix coating steps. The incubation of cells with formalin for about 5 min in combination with isotonic washing and mild drying produced a robust protocol that largely preserved not only cell morphologies, but also the molecular integrities of amine group-containing cell membrane phospholipids (phosphatidylethanolamines and -serines). A disadvantage of the chemical fixation is an increased permeabilization of cell membranes, resulting in leakage of cytosolic compounds. We demonstrate the pros and cons of the protocols with four model cell lines, cultured directly on indium tin oxide (ITO)-coated glass slides. Transmission (t-)mode MALDI-2-MSI enabled on a Q Exactive plus Orbitrap mass spectrometer was used to analyze the cultures at a pixel size of 2 μm. Phase contrast light microscopy and scanning electron microscopy were used as complementary methods. The protocols described could prove to be an important contribution to the advancement of single-cell MALDI imaging, especially for the characterization of cell-to-cell heterogeneities at a molecular level.

Single cell metabolomics using mass spectrometry: Techniques and data analysis

Mass spectrometry (MS) based techniques are gaining popularity for metabolomics research due to their high sensitivity, wide detection range, and capability of molecular identification. Utilizing such powerful technique to explore the cellular metabolism at the single cell level not only appreciates the subtle cell-to-cell difference (i.e., cell heterogeneity), but also gains biological merits corresponding to individual cells or small cell subpopulations. In this review article, we first briefly summarize recent advances in single cell MS experimental techniques, and then emphasize on the single cell metabolomics data analysis approaches. Through implementation of statistical analysis and more advanced data analysis methods, single cell metabolomics is expected to find more potential applications in the translational and clinical fields in the future.

Analysis of Live Single Cells by Confocal Microscopy and High-Resolution Mass Spectrometry to Study Drug Uptake, Metabolism, and Drug-Induced Phospholipidosis

The analysis of large numbers of cells from a population results in information that does not reflect differences in cell phenotypes. Individual variations in cellular drug uptake, metabolism, and response to drug treatment may have profound effects on cellular survival and lead to the development of certain disease states, drug persistence, and resistance. Herein, we present a method that combines live cell confocal microscopy imaging with high-resolution mass spectrometry to achieve absolute cell quantification of the drug amiodarone (AMIO) and its major metabolite, N-desethylamiodarone (NDEA), in single liver cells (HepG2 and HepaRG cells). The method uses a prototype system that integrates a confocal microscope with an XYZ stage robot to image and automatically sample selected cells from a sample compartment, which is kept under growth conditions, with nanospray tips. Besides obtaining the distributions of AMIO and NDEA cell concentrations across a population of individual cells, as well as variabilities in drug metabolism, the effect of these on phospholipidosis and cell morphology was studied. The method was suited to identify subpopulations of cells that metabolized less drug and to correlate cell drug concentrations with cell phospholipid content, cell volume, sphericity, and other cell phenotypic features. Using principal component analysis (PCA), the treated cells could be clearly distinguished from vehicle control cells (0 μM AMIO) and HepaRG cells from HepG2 cells. The potential of using multidimensional and multimodal information collected from single cells to build predictive models for cell classification is demonstrated.

Effect of MALDI matrices on lipid analyses of biological tissues using MALDI-2 postionization mass spectrometry

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) allows for highly multiplexed, untargeted detection of many hundreds of analytes from tissue. Recently, laser postionization (MALDI-2) has been developed for increased ion yield and sensitivity for lipid IMS. However, the dependence of MALDI-2 performance on the various lipid classes is largely unknown. To understand the effect of the applied matrix on MALDI-2 analysis of lipids, samples including an equimolar lipid standard mixture, various tissue homogenates, and intact rat kidney tissue sections were analyzed using the following matrices: α-cyano-4-hydroxycinnamic acid, 2',5'-dihydroxyacetophenone, 2',5'-dihydroxybenzoic acid (DHB), and norharmane (NOR). Lipid signal enhancement of protonated species using MALDI-2 technology varied based on the matrix used. Although signal improvements were observed for all matrices, the most dramatic effects using MALDI-2 were observed using NOR and DHB. For lipid standards analyzed by MALDI-2, NOR provided the broadest coverage, enabling the detection of all 13 protonated standards, including nonpolar lipids, whereas DHB gave less coverage but gave the highest signal increase for those lipids recorded. With respect to tissue homogenates and rat kidney tissue, mass spectra were compared and showed that the number and intensity of neutral lipids tentatively identified with MALDI-2 using NOR increased significantly (e.g., fivefold intensity increase for triacylglycerol). In the cases of DHB with MALDI-2, the number of protonated lipids identified from tissue homogenates doubled with 152 on average compared with 76 with MALDI alone. High spatial resolution imaging (~20 μm) of rat kidney tissue showed similar results using DHB with 125 lipids tentatively identified from MALDI-2 spectra versus just 72 using standard MALDI. From the four matrices tested, NOR provided the greatest increase in sensitivity for neutral lipids (triacylglycerol, diacylglycerol, monoacylglycerol, and cholesterol ester), and DHB provided the highest overall number of lipids detected using MALDI-2 technology.

Effect of MALDI matrices on lipid analyses of biological tissues using MALDI-2 postionization mass spectrometry

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) allows for highly multiplexed, untargeted detection of many hundreds of analytes from tissue. Recently, laser postionization (MALDI-2) has been developed for increased ion yield and sensitivity for lipid IMS. However, the dependence of MALDI-2 performance on the various lipid classes is largely unknown. To understand the effect of the applied matrix on MALDI-2 analysis of lipids, samples including an equimolar lipid standard mixture, various tissue homogenates, and intact rat kidney tissue sections were analyzed using the following matrices: α-cyano-4-hydroxycinnamic acid, 2',5'-dihydroxyacetophenone, 2',5'-dihydroxybenzoic acid (DHB), and norharmane (NOR). Lipid signal enhancement of protonated species using MALDI-2 technology varied based on the matrix used. Although signal improvements were observed for all matrices, the most dramatic effects using MALDI-2 were observed using NOR and DHB. For lipid standards analyzed by MALDI-2, NOR provided the broadest coverage, enabling the detection of all 13 protonated standards, including nonpolar lipids, whereas DHB gave less coverage but gave the highest signal increase for those lipids recorded. With respect to tissue homogenates and rat kidney tissue, mass spectra were compared and showed that the number and intensity of neutral lipids tentatively identified with MALDI-2 using NOR increased significantly (e.g., fivefold intensity increase for triacylglycerol). In the cases of DHB with MALDI-2, the number of protonated lipids identified from tissue homogenates doubled with 152 on average compared with 76 with MALDI alone. High spatial resolution imaging (~20 μm) of rat kidney tissue showed similar results using DHB with 125 lipids tentatively identified from MALDI-2 spectra versus just 72 using standard MALDI. From the four matrices tested, NOR provided the greatest increase in sensitivity for neutral lipids (triacylglycerol, diacylglycerol, monoacylglycerol, and cholesterol ester), and DHB provided the highest overall number of lipids detected using MALDI-2 technology.

Dynamic Range Expansion by Gas-Phase Ion Fractionation and Enrichment for Imaging Mass Spectrometry

In the analysis of biological tissue by imaging mass spectrometry (IMS), the limit of detection and dynamic range are of paramount importance in obtaining experimental results that provide insight into underlying biological processes. Many important biomolecules are present in the tissue milieu in low concentrations and in complex mixtures with other compounds of widely ranging abundances, challenging the limits of analytical technologies. In many IMS experiments, the ion signal can be dominated by a few highly abundant ion species. On trap-based instrument platforms that accumulate ions prior to mass analysis, these high abundance ions can diminish the detection and dynamic range of lower abundance ions. Herein, we describe two strategies for combating these challenges during IMS experiments on a hybrid QhFT-ICR MS. In one iteration, the mass resolving capabilities of a quadrupole mass filter are used to selectively enrich ions of interest via a technique previously termed continuous accumulation of selected ions. Second, we have introduced a supplemental dipolar AC waveform to the quadrupole mass filter of a commercial QhFT-ICR mass spectrometer to perform selected ion ejection prior to the ion accumulation region. This setup allows the selective ejection of the most abundant ion species prior to ion accumulation, thereby greatly improving the molecular depth with which IMS can probe tissue samples. The gain in sensitivity of both of these approaches roughly scales with the number of accumulated laser shots up to the charge capacity of the ion accumulation cell. The efficiencies of these two strategies are described here by performing lipid imaging mass spectrometry analyses of a rat brain.

Concentrating Single Cells in Picoliter Droplets for Phospholipid Profiling on a Microfluidic System

Cellular membranes are composed of a variety of lipids in different amounts and proportions, and alterations of them are usually closely related to various diseases. To reveal the intercellular heterogeneity of the lipid variation, an integrated microfluidic system is designed, which consists of droplet-based inkjet printing, dielectrophoretic electrodes, and de-emulsification interface to achieve on-line single-cell encapsulation, manipulation, and mass spectrometry (MS) detection. This integrated system effectively improves the single-cell encapsulation rate, and meanwhile reduces the matrix interference and continuous oil phase interference to the MS detection. Using this system, the heterogeneities between the normal and cancer cells are compared, and the heterogeneity of the same cells before and after the drug treatment changed obviously, indicating that this system can be used as a promising tool for studying the link between the alterations of lipid homeostasis and various diseases.

Accessible and reproducible mass spectrometry imaging data analysis in Galaxy

BACKGROUND

Mass spectrometry imaging is increasingly used in biological and translational research because it has the ability to determine the spatial distribution of hundreds of analytes in a sample. Being at the interface of proteomics/metabolomics and imaging, the acquired datasets are large and complex and often analyzed with proprietary software or in-house scripts, which hinders reproducibility. Open source software solutions that enable reproducible data analysis often require programming skills and are therefore not accessible to many mass spectrometry imaging (MSI) researchers.

FINDINGS

We have integrated 18 dedicated mass spectrometry imaging tools into the Galaxy framework to allow accessible, reproducible, and transparent data analysis. Our tools are based on Cardinal, MALDIquant, and scikit-image and enable all major MSI analysis steps such as quality control, visualization, preprocessing, statistical analysis, and image co-registration. Furthermore, we created hands-on training material for use cases in proteomics and metabolomics. To demonstrate the utility of our tools, we re-analyzed a publicly available N-linked glycan imaging dataset. By providing the entire analysis history online, we highlight how the Galaxy framework fosters transparent and reproducible research.

CONCLUSION

The Galaxy framework has emerged as a powerful analysis platform for the analysis of MSI data with ease of use and access, together with high levels of reproducibility and transparency.

Laser cleavable probes for in situ multiplexed glycan detection by single cell mass spectrometry

A single-cell MS approach for multiplexed glycan detection to investigate the relationship between drug resistance and glycans at a single-cell level and quantify multiple glycans, overcoming the limit of low ionization efficiency of glycans.

Glycans binding on the cell surface through glycosylation play a key role in controlling various cellular processes, and glycan analysis at a single-cell level is necessary to study cellular heterogeneity and diagnose diseases in the early stage. Herein, we synthesized a series of laser cleavable probes, which could sensitively detect glycans on single cells and tissues by laser desorption ionization mass spectrometry (LDI-MS). This multiplexed and quantitative glycan detection was applied to evaluate the alterations of four types of glycans on breast cancer cells and drug-resistant cancer cells at a single-cell level, indicating that drug resistance may be related to the upregulation of glycan with a β-d-galactoside (Galβ) group and Neu5Aca2-6Gal(NAc)-R. Moreover, the glycan spatial distribution in cancerous and paracancerous human tissues was also demonstrated by MS imaging, showing that glycans are overexpressed in cancerous tissues. Therefore, this single-cell MS approach exhibits promise for application in studying glycan functions which are essential for clinical biomarker discovery and diagnosis of related diseases.

Exploring the Fundamental Structures of Life: Non-Targeted, Chemical Analysis of Single Cells and Subcellular Structures

Cells are a basic functional and structural unit of living organisms. Both unicellular communities and multicellular species produce an astonishing chemical diversity, enabling a wide range of divergent functions, yet each cell shares numerous aspects that are common to all living organisms. While there are many approaches for studying this chemical diversity, only a few are non-targeted and capable of analyzing hundreds of different chemicals at cellular resolution. Here, we review the non-targeted approaches used to perform comprehensive chemical analyses, provide chemical imaging information, or obtain high-throughput single-cell profiling data. Single-cell measurement capabilities are rapidly increasing in terms of throughput, limits of detection, and completeness of the chemical analyses; these improvements enable their application to understand ever more complex physiological phenomena, such as learning, memory, and behavior.

Lipid Analysis of 30 000 Individual Rodent Cerebellar Cells Using High-Resolution Mass Spectrometry

Single-cell measurements aid our understanding of chemically heterogeneous systems such as the brain. Lipids are one of the least studied chemical classes, and their cell-to-cell heterogeneity remains largely unexplored. We adapted microscopy-guided single-cell profiling using matrix-assisted laser desorption/ionization ion cyclotron resonance mass spectrometry to profile the lipid composition of over 30 000 individual rat cerebellar cells. We detected 520 lipid features, many of which were found in subsets of cells; Louvain clustering identified 101 distinct groups that can be correlated to neuronal and astrocytic classifications and lipid classes. Overall, the two most common lipids found were [PC(32:0)+H]⁺ and [PC(34:1)+H]⁺, which were present within 98.9 and 89.5% of cells, respectively; lipid signals present in <1% of cells were also detected, including [PC(34:1)+K]⁺ and [PG(40:2(OH))+Na]⁺. These results illustrate the vast lipid heterogeneity found within rodent cerebellar cells and hint at the distinct functional consequences of this heterogeneity.

Lipid Heterogeneity between Astrocytes and Neurons Revealed by Single-Cell MALDI-MS Combined with Immunocytochemical Classification

Transcriptomics characterizes cells based on their potential molecular repertoire whereas direct mass spectrometry (MS) provides information on the actual compounds present within cells. Single-cell matrix-assisted laser desorption/ionization (MALDI) MS can measure the chemical contents of individual cells but spectra are difficult to correlate to conventional cell types, limiting the metabolic information obtained. We present a protocol that combines MALDI-MS with immunocytochemistry to assay over a thousand individual rat brain cells. The approach entwines the wealth of knowledge obtained by immunocytochemical profiling with mass spectral information on the predominant lipids within each cell. While many lipid species showed a high degree of similarity between neurons and astrocytes, seventeen significantly differed between the two cell types, including four phosphatidylethanolamines elevated in astrocytes and nine phosphatidylcholines in neurons.

Advances in mass spectrometry based single-cell metabolomics

Single cell metabolomics using mass spectrometry can contribute to understanding biological activities in health and disease.