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

Single-Cell Endoscopy for Multifunctional Live-Cell Molecular Analysis

Molecular analyses of individual cells with high resolution, specificity, and sensitivity can not only reveal cellular heterogeneity but also provide a better understanding of diseases and accelerate drug discoveries. Single-cell endoscopy is an advanced live-cell technique that relies on a smart endoscope that allows minimally invasive probing of the interiors of individual cells. Compared with other single-cell analysis techniques, single-cell endoscopy has shown great promise in applications such as flexible single-cell manipulation, ultrasensitive sensing, and precise intracellular delivery. In this review, we aim to map out the landscape of recent advances in single-cell endoscopy techniques by focusing on both fundamental considerations and significant progress over the past decade. Specifically, we summarize the predominant live-cell endoscopes, including their fabrication and characterization. Furthermore, a series of valuable intracellular molecular sensing events, such as nucleic acids, proteins, ions, etc., are introduced with a main emphasis on how single-cell endoscopy can solve these issues and what merits single-cell endoscopy can provide. Finally, we briefly outline the remaining challenges and directions for the future development of single-cell endoscopy techniques.

Single-Cell Peptide Profiling to Distinguish Stickleback Ecotypes with Divergent Breeding Behavior

Variation in parenting behavior is widespread across the animal kingdom, both within and between species. There are two ecotypes of the three-spined stickleback fish (Gasterosteus aculeatus) that exhibit dramatic differences in their paternal behavior. Males of the common ecotype are highly attentive fathers, tending to young from eggs to fry, while males of the white ecotype desert offspring as eggs. As the pituitary is a key regulator in the hypothalamic-pituitary-adrenal (HPA) axis and the hypothalamic-pituitary-gonadal (HPG) axis between the brain and body, its peptides may influence parenting behaviors. Here, we utilized matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) for high-throughput peptide analysis in single cells of pituitaries from both three-spined stickleback ecotypes. Peptide mass fingerprinting was performed using an in silico generated peptide library to identify detected prohormones. Differential analysis revealed POMC-derived peptides, MCH-derived peptides, and oxytocin as significantly different between the two ecotypes, with higher oxytocin levels in the common ecotype. Interestingly, these subtle chemical differences were not captured by Leiden clustering of the cellular phenotypes. These results call for further investigation of the neurochemical basis for parenting in sticklebacks.

Single-cell lipidomics: protocol development for reliable cellular profiling using capillary sampling

Single-cell lipidomics enables detailed analysis of the lipidomes of cells, but is challenged by small sample volumes, the risk of background interference and a lack of validation data. In this study, we explore the effect of different sampling variables on the lipid profiles of single pancreatic cancer cells, detected using liquid chromatography-mass spectrometry (LC-MS). We use automated and manual capillary sampling methods to isolate living single cells and evaluate different sampling media, capillary tips, aspiration volume, and temperature and humidity control. We demonstrate that automated and manual capillary sampling yield comparable lipid profiles when key parameters are controlled. Our findings highlight that appropriate blank correction, capillary tip type, and the control of aspiration volumes are all critical to preserving detection sensitivity. Conversely, choice of sampling medium does not affect lipidomics results. We also set out suggested best practices for these methodological variables, laying a foundation for robust, adaptable workflows in single-cell lipidomics for applications such as biomarker discovery and metabolic research.

Enhancing lipid production in plant cells through automated high-throughput genome engineering and phenotyping

Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB) in maize (Zea mays) and Nicotiana benthamiana. FAST-PB enables genome editing and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated that FAST-PB could streamline Golden Gate cloning, with the capacity to construct 96 vectors in parallel. Using FAST-PB in protoplasts, we found that PEG2050 increased transfection efficiency by over 45%. For proof-of-concept, we established a reporter-gene-free method for CRISPR editing and phenotyping via mutation of high chlorophyll fluorescence 136. We show that diverse lipids were enhanced up to 6-fold using CRISPR activation of lipid controlling genes. In callus cells, an automated transformation platform was employed to regenerate plants with enhanced lipid traits through introducing multigene cassettes. Lastly, FAST-PB enabled high-throughput single-cell lipid profiling by integrating MALDI-MS with the biofoundry, protoplast, and callus cells, differentiating engineered and unengineered cells using single-cell lipidomics. These innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering and change what is possible using single-cell metabolomics in plants.

Development and Validation of RoboCap, a Robotic Capillary Platform to Automate Capillary Electrophoresis Mass Spectrometry En Route to High-Throughput Single-Cell Proteomics

Current developments in single-cell mass spectrometry (MS) aim to deepen proteome coverage while enhancing analytical speed to study entire cell populations, one cell at a time. Custom-built microanalytical capillary electrophoresis (μCE) played a critical role in the foundation of discovery single-cell MS proteomics. However, requirements for manual operation, substantial expertise, and low measurement throughput have so far hindered μCE-based single-cell studies on large numbers of cells. Here, we design and construct a robotic capillary (RoboCap) platform that grants single-cell CE-MS with automation for proteomes limited to less than ∼100 nL. RoboCap remotely controls precision actuators to translate the sample to the fused silica separation capillary, using vials in this work. The platform is hermetically enclosed and actively pressurized to inject ∼1-250 nL of the sample into a CE separation capillary, with errors below ∼5% relative standard deviation (RSD). The platform and supporting equipment were operated and monitored remotely on a custom-written Virtual Instrument (LabView). Detection performance was validated empirically on ∼5-250 nL portions of the HeLa proteome digest using a trapped ion mobility mass spectrometer (timsTOF PRO). RoboCap improved CE-ESI sample utilization to ∼20% from ∼3% on the manual μCE, the closest reference technology. Proof-of-principle experiments found proteome identification and quantification to robustly return ∼1,800 proteins (∼13% RSD) from ∼20 ng of the HeLa proteome digest on this earlier-generation detector. RoboCap automates CE-MS for limited sample amounts, paving the way to electrophoresis-based high-throughput single-cell proteomics.

Advances in mass spectrometry-enabled multiomics at single-cell resolution

Biological organisms are multifaceted, intricate systems where slight perturbations can result in extensive changes in gene expression, protein abundance and/or activity, and metabolic flux. These changes occur at different timescales, spatially across cells of heterogeneous origins, and within single-cells. Hence, multimodal measurements at the smallest biological scales are necessary to capture dynamic changes in heterogeneous biological systems. Of the analytical techniques used to measure biomolecules, mass spectrometry (MS) has proven to be a powerful option due to its sensitivity, robustness, and flexibility with regard to the breadth of biomolecules that can be analyzed. Recently, many studies have coupled MS to other analytical techniques with the goal of measuring multiple modalities from the same single-cell. It is with these concepts in mind that we focus this review on MS-enabled multiomic measurements at single-cell or near-single- cell resolution.

Bioconcentration Assessment of Three Cationic Surfactants in Permanent Fish Cell Lines

Cationic surfactants are used in many industrial processes and in consumer products with concurrent release into the aquatic environment, where they may accumulate in aquatic organisms to regulatoryly relevant thresholds. Here, we aimed to better understand the bioconcentration behavior of three selected cationic surfactants, namely N,N-dimethyldecylamine (T10), N-methyldodecylamine (S12), and N,N,N-trimethyltetradecylammonium cation (Q14), in the cells of fish liver (RTL-W1) and gill (RTgill-W1) cell lines. We conducted full mass balances for bioconcentration tests with the cell cultures, in which the medium, the cell surface, the cells themselves, and the plastic compartment were sampled and quantified for each surfactant by HPLC MS/MS. Accumulation in/to cells correlated with the surfactants' alkyl chain lengths and their membrane lipid-water partitioning coefficient, DMLW. Cell-derived bioconcentration factors (BCF) of T10 and S12 were within a factor of 3.5 to in vivo BCF obtained from the literature, while the cell-derived BCF values for Q14 were >100 times higher than the in vivo BCF. From our experiments, rainbow trout cell lines appear as a suitable conservative in vitro screening method for bioconcentration assessment of cationic surfactants and are promising for further testing.

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.

On-capillary alkylation micro-reactor: a facile strategy for proteo-metabolome profiling in the same single cells

Single-cell multi-omics analysis can provide comprehensive insights to study cell-to-cell heterogeneity in normal and disease physiology. However, due to the lack of amplification technique, the measurement of proteome and metabolome in the same cell is challenging. Herein, a novel on-capillary alkylation micro-reactor (OCAM) was developed to achieve proteo-metabolome profiling in the same single cells, by which proteins were first covalently bound to an iodoacetic acid functionalized open-tubular capillary micro-reactor via sulfhydryl alkylation reaction, and metabolites were rapidly eluted, followed by on-column digestion of captured proteins. Compared with existing methods for low-input proteome sample preparation, OCAM exhibited improved efficiency, anti-interference ability and recovery, enabling the identification of an average of 1509 protein groups in single HeLa cells. This strategy was applied to single-cell proteo-metabolome analysis of mouse oocytes at different stages, 3457 protein groups and 171 metabolites were identified in single oocytes, which is the deepest coverage of proteome and metabolome from single mouse oocytes to date, achieving complementary characterization of metabolic patterns during oocyte maturation.

Sample Preparation Method for MALDI Mass Spectrometry Imaging of Fresh-Frozen Spines

Technologies assessing the lipidomics, genomics, epigenomics, transcriptomics, and proteomics of tissue samples at single-cell resolution have deepened our understanding of physiology and pathophysiology at an unprecedented level of detail. However, the study of single-cell spatial metabolomics in undecalcified bones faces several significant challenges, such as the fragility of bone, which often requires decalcification or fixation leading to the degradation or removal of lipids and other molecules. As such, we describe a method for performing mass spectrometry imaging on undecalcified spine that is compatible with other spatial omics measurements. In brief, we use fresh-frozen rat spines and a system of carboxyl methylcellulose embedding, cryofilm, and polytetrafluoroethylene rollers to maintain tissue integrity while avoiding signal loss from variations in laser focus and artifacts from traditional tissue processing. This reveals various tissue types and lipidomic profiles of spinal regions at 10 μm spatial resolutions using matrix-assisted laser desorption/ionization mass spectrometry imaging. We expect this method to be adapted and applied to the analysis of the spinal cord, shedding light on the mechanistic aspects of cellular heterogeneity, development, and disease pathogenesis underlying different bone-related conditions and diseases. This study furthers the methodology for high spatial metabolomics of spines and adds to the collective efforts to achieve a holistic understanding of diseases via single-cell spatial multiomics.

Spatial metabolomics principles and application to cancer research

Mass spectrometry imaging (MSI) is an emerging technology in cancer metabolomics. Desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) MSI are complementary techniques to identify hundreds of metabolites in space with close to single-cell resolution. This technology leap enables research focusing on tumor heterogeneity, cancer cell plasticity, and the communication signals between cancer and stromal cells in the tumor microenvironment (TME). Currently, unprecedented knowledge is generated using spatial metabolomics in fundamental cancer research. Yet, also translational applications are emerging, including the assessment of spatial drug distribution in organs and tumors. Moreover, clinical research investigates the use of spatial metabolomics as a rapid pathology tool during cancer surgeries. Here, we summarize MSI applications, the knowledge gained by this technology in space, future directions, and developments needed.

Spatial lipidomics of fresh-frozen spines

Technologies assessing the lipidomics, genomics, epigenomics, transcriptomics, and proteomics of tissue samples at single-cell resolution have deepened our understanding of physiology and pathophysiology at an unprecedented level of detail. However, the study of single-cell spatial metabolomics in undecalcified bones faces several significant challenges, such as the fragility of bone which often requires decalcification or fixation leading to the degradation or removal of lipids and other molecules and. As such, we describe a method for performing mass spectrometry imaging on undecalcified spine that is compatible with other spatial omics measurements. In brief, we use fresh-freeze rat spines and a system of carboxyl methylcellulose embedding, cryofilm, and polytetrafluoroethylene rollers to maintain tissue integrity, while avoiding signal loss from variations in laser focus and artifacts from traditional tissue processing. This reveals various tissue types and lipidomic profiles of spinal regions at 10 μm spatial resolutions using matrix-assisted laser desorption/ionization mass spectrometry imaging. We expect this method to be adapted and applied to the analysis of spinal cord, shedding light on the mechanistic aspects of cellular heterogeneity, development, and disease pathogenesis underlying different bone-related conditions and diseases. This study furthers the methodology for high spatial metabolomics of spines, as well as adds to the collective efforts to achieve a holistic understanding of diseases via single-cell spatial multi-omics.

Autofocusing MALDI MS imaging of processed food exemplified by the contaminant acrylamide in German gingerbread

Acrylamide is a toxic reaction product occurring in dry-heated food such as bakery products. To meet the requirements laid down in recent international legal norms calling for reduction strategies in food prone to acrylamide formation, efficient chromatography-based quantification methods are available. However, for an efficient mitigation of acrylamide levels, not only the quantity, but also the contaminant's distributions are of interest especially in inhomogeneous food consisting of multiple ingredients. A promising tool to investigate the spatial distribution of analytes in food matrices is mass spectrometry imaging (MS imaging). In this study, an autofocusing MALDI MS imaging method was developed for German gingerbread as an example for highly processed and instable food with uneven surfaces. Next to endogenous food constituents, the process contaminant acrylamide was identified and visualized keeping a constant laser focus throughout the measurement. Statistical analyses based on relative acrylamide intensities suggest a higher contamination of nut fragments compared to the dough. In a proof-of-concept experiment, a newly developed in-situ chemical derivatization protocol is described using thiosalicylic acid for highly selective detection of acrylamide. This study presents autofocusing MS imaging as a suitable complementary method for the investigation of analytes' distributions in complex and highly processed food.

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.

Subcellular omics: a new frontier pushing the limits of resolution, complexity and throughput

We argue that the study of single-cell subcellular organelle omics is needed to understand and regulate cell function. This requires and is being enabled by new technology development.

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.

Mouse Pancreatic Peptide Hormones Probed at the Sub-Single-Islet Level: The Effects of Acute Corticosterone Treatment

We combine liquid chromatography coupled with ion mobility spectrometry-mass spectrometry to elucidate how short exposure to corticosterone (Cort) alters the output of mouse pancreatic islet hormones. The workflow enables the robust separation of mouse insulin 1 (Ins1) and insulin 2 (Ins2) and the detection of major islet hormones in a homogenate equivalent to 100-150 islet cells. We show that Ins2 has a unique structure and is degraded much faster than Ins1. Further investigation indicates that Ins2 may populate both T and R states, whereas Ins1 may not. The assemblies of Ins1's B-chain also introduce more structural heterogeneity than Ins2. Collectively, these features account for their unique degradation profiles, the diabetes risk associated with Ins1, and the protective effect of Ins2. In the same experiments, we observe that the ratio of amylin to Ins1 increased significantly in Cort-treated mice (15:1) compared to the control mice (42:1), correlating well with β-cell proliferation observed in immunoassays on the same animal model. We observe no increase in intact full-length insulin levels but more of the truncated forms, indicating that enzymatic activity is accelerated. Our data provide a molecular basis for reduced insulin action induced by Cort and connections between insulin turnover and insulin resistance.

Spatially resolved characterization of tissue metabolic compartments in fasted and high-fat diet livers

Cells adapt their metabolism to physiological stimuli, and metabolic heterogeneity exists between cell types, within tissues, and subcellular compartments. The liver plays an essential role in maintaining whole-body metabolic homeostasis and is structurally defined by metabolic zones. These zones are well-understood on the transcriptomic level, but have not been comprehensively characterized on the metabolomic level. Mass spectrometry imaging (MSI) can be used to map hundreds of metabolites directly from a tissue section, offering an important advance to investigate metabolic heterogeneity in tissues compared to extraction-based metabolomics methods that analyze tissue metabolite profiles in bulk. We established a workflow for the preparation of tissue specimens for matrix-assisted laser desorption/ionization (MALDI) MSI that can be implemented to achieve broad coverage of central carbon, nucleotide, and lipid metabolism pathways. Herein, we used this approach to visualize the effect of nutrient stress and excess on liver metabolism. Our data revealed a highly organized metabolic tissue compartmentalization in livers, which becomes disrupted under high fat diet. Fasting caused changes in the abundance of several metabolites, including increased levels of fatty acids and TCA intermediates while fatty livers had higher levels of purine and pentose phosphate-related metabolites, which generate reducing equivalents to counteract oxidative stress. This spatially conserved approach allowed the visualization of liver metabolic compartmentalization at 30 μm pixel resolution and can be applied more broadly to yield new insights into metabolic heterogeneity in vivo.

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.

Mass Spectrometry Approaches Empowering Neuropeptide Discovery and Therapeutics

The discovery of insulin in the early 1900s ushered in the era of research related to peptides acting as hormones and neuromodulators, among other regulatory roles. These essential gene products are found in all organisms, from the most primitive to the most evolved, and carry important biologic information that coordinates complex physiology and behavior; their misregulation has been implicated in a variety of diseases. The evolutionary origins of at least 30 neuropeptide signaling systems have been traced to the common ancestor of protostomes and deuterostomes. With the use of relevant animal models and modern technologies, we can gain mechanistic insight into orthologous and paralogous endogenous peptides and translate that knowledge into medically relevant insights and new treatments. Groundbreaking advances in medicine and basic science influence how signaling peptides are defined today. The precise mechanistic pathways for over 100 endogenous peptides in mammals are now known and have laid the foundation for multiple drug development pipelines. Peptide biologics have become valuable drugs due to their unique specificity and biologic activity, lack of toxic metabolites, and minimal undesirable interactions. This review outlines modern technologies that enable neuropeptide discovery and characterization, and highlights lessons from nature made possible by neuropeptide research in relevant animal models that is being adopted by the pharmaceutical industry. We conclude with a brief overview of approaches/strategies for effective development of peptides as drugs. SIGNIFICANCE STATEMENT: Neuropeptides, an important class of cell-cell signaling molecules, are involved in maintaining a range of physiological functions. Since the discovery of insulin's activity, over 100 bioactive peptides and peptide analogs have been used as therapeutics. Because these are complex molecules not easily predicted from a genome and their activity can change with subtle chemical modifications, mass spectrometry (MS) has significantly empowered peptide discovery and characterization. This review highlights contributions of MS-based research towards the development of therapeutic peptides.

In situ SERS monitoring of intracellular H2O2 in single living cells based on label-free bifunctional Fe3O4@Ag nanoparticles

Visualization of signaling molecules in single living cells is crucial for understanding cellular metabolism and physiology, which can provide valuable insights into early diagnoses and treatments of diseases. Highly sensitive in situ monitoring of intracellular analytes released from single living cells by virtue of label-free nanosensors is urgently needed, which can avoid interferences from molecular labeling. Here, we proposed an ultrasensitive strategy for in situ imaging of intracellular H₂O₂ in single living cancer cells by surface-enhanced Raman scattering (SERS) spectroscopy with the utilization of label-free Fe₃O₄@Ag core-satellite nanoparticles (NPs). The Fe₃O₄@Ag NPs can efficiently and selectively catalyze the oxidation of the peroxidase substrate 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of H₂O₂. Additionally, they exhibit excellent SERS activity that allows for in situ monitoring of intracellular H₂O₂ in living cells through establishing the correlation between the H₂O₂ level and the SERS intensity of the catalytic oxidation product of TMB. The H₂O₂ concentration is revealed through the SERS intensity of oxidized TMB with a good linear response in a wide range from 1 fM to 1 mM. Moreover, the intracellular H₂O₂ level in live cancer cells and imaging of the distribution of H₂O₂ inside single cells can be achieved by using such a label-free nanosensor based strategy. Our work demonstrates that the label-free Fe₃O₄@Ag NP-based SERS imaging and quantification strategy is a promising and powerful approach to assess intracellular H₂O₂ in living cells and allows us to monitor single-cell signaling molecules with nanoscale resolution.

Inkjet-Patterned Microdroplets as Individual Microenvironments for Adherent Single Cell Culture

Adhesion of single cells is the foundation of manifold cellular behaviors and life processes. However, investigating the function of a specific cell is still challenging due to deficiency of adhesion or interference from surrounding cells. Herein, an open microfluidic system is reported for culturing adherent single cells, implemented by a micrometer-scale droplet matrix on an inkjet-printed polylysine template. The target cells are isolated from any cell from other droplets, and their adhesion strength is determined to be comparable to conventional petri dishes via an in-situ investigation with a microfluidic extractor. On this proposed platform, isolated single cells are observed to display an entirely distinct spreading behavior featuring total absence of elongation, indicating drastic cell behavior change from their "singleness." This system has high versatility and compatibility for various assaying methods, assuring a promising potential in detailed single cell behavior and cell heterogeneity studies.

Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging

Tissues and organs are composed of distinct cell types that must operate in concert to perform physiological functions. Efforts to create high-dimensional biomarker catalogs of these cells have been largely based on single-cell sequencing approaches, which lack the spatial context required to understand critical cellular communication and correlated structural organization. To probe in situ biology with sufficient depth, several multiplexed protein imaging methods have been recently developed. Though these technologies differ in strategy and mode of immunolabeling and detection tags, they commonly utilize antibodies directed against protein biomarkers to provide detailed spatial and functional maps of complex tissues. As these promising antibody-based multiplexing approaches become more widely adopted, new frameworks and considerations are critical for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets. In this Perspective, we provide essential resources, key considerations for obtaining robust and reproducible imaging data, and specialized knowledge from domain experts and technology developers.

Phospholipid Profiles for Phenotypic Characterization of Adipose-Derived Multipotent Mesenchymal Stromal Cells

Multipotent mesenchymal stromal cells (MSC) have emerged as therapeutic tools for a wide range of pathological conditions. Yet, the still existing deficits regarding MSC phenotype characterization and the resulting heterogeneity of MSC used in different preclinical and clinical studies hamper the translational success. In search for novel MSC characterization approaches to complement the traditional trilineage differentiation and immunophenotyping assays reliably across species and culture conditions, this study explored the applicability of lipid phenotyping for MSC characterization and discrimination. Human peripheral blood mononuclear cells (PBMC), human fibroblasts, and human and equine adipose-derived MSC were used to compare different mesodermal cell types and MSC from different species. For MSC, cells cultured in different conditions, including medium supplementation with either fetal bovine serum or platelet lysate as well as culture on collagen-coated dishes, were additionally investigated. After cell harvest, lipids were extracted by chloroform/methanol according to Bligh and Dyer. The lipid profiles were analysed by an untargeted approach using liquid chromatography coupled to mass spectrometry (LC-MS) with a reversed phase column and an ion trap mass spectrometer. In all samples, phospholipids and sphingomyelins were found, while other lipids were not detected with the current approach. The phospholipids included different species of phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI) and phosphatidylserine (PS) in all cell types, whereas phosphatidylglycerol (PG) species were only present in MSC. MSC from both species showed a higher phospholipid species diversity than PBMC and fibroblasts. Few differences were found between MSC from different culture conditions, except that human MSC cultured with platelet lysate exhibited a unique phenotype in that they exclusively featured PE O-40:4, PG 38:6 and PG 40:6. In search for specific and inclusive candidate MSC lipid markers, we identified PE O-36:3 and PG 40:7 as potentially suitable markers across culture conditions, at which PE O-36:3 might even be used across species. On that basis, phospholipid phenotyping is a highly promising approach for MSC characterization, which might condone some heterogeneity within the MSC while still achieving a clear discrimination even from fibroblasts. Particularly the presence or absence of PG might emerge as a decisive criterion for future MSC characterization.

Droplet Microfluidics with MALDI-MS Detection: The Effects of Oil Phases in GABA Analysis

Microfluidic and mass spectrometry (MS) methods are widely used to sample and probe the chemical composition of biological systems to elucidate chemical correlates of their healthy and disease states. Though matrix-assisted laser desorption/ionization-mass spectrometry (MALDI)-MS has been hyphenated to droplet microfluidics for offline analyses, the effects of parameters related to droplet generation, such as the type of oil phase used, have been understudied. To characterize these effects, five different oil phases were tested in droplet microfluidics for producing samples for MALDI-MS analysis. Picoliter to nanoliter aqueous droplets containing 0.1 to 100 mM γ-aminobutyric acid (GABA) and inorganic salts were generated inside a polydimethylsiloxane microfluidic chip and deposited onto a conductive glass slide. Optical microscopy, Raman spectroscopy, and MALDI-mass spectrometry imaging (MSI) of the droplet samples and surrounding areas revealed patterns of solvent and oil evaporation and analyte deposition. Optical microscopy detected the presence of salt crystals in 50-100 μm diameter dried droplets, and Raman and MSI were used to correlate GABA signals to the visible droplet footprints. MALDI-MS analyses revealed that droplets prepared in the presence of octanol oil led to the poorest detectability of GABA, whereas the oil phases containing FC-40 provided the best detectability; GABA signal was localized to the footprint of 65 pL droplets with a limit of detection of 23 amol. The effect of the surfactant perfluorooctanol on analyte detection was also investigated.

Nanothorn Filter-Facilitated Online Cell Lysis for Rapid and Deep Intracellular Profiling by Single-Cell Mass Spectrometry

Mass spectrometry combined with flow cytometry is emerging for high-throughput single-cell metabolite analysis but still has problems with limited intracellular information coverage. Here, we show a simple and efficient all-in-one system integrating cell injection, cell extraction, online cell lysis, analyte ionization, and mass spectrometric detection for rapid single-HeLa-cell screening with in-depth profiling of cellular metabolites and drugs. Zinc oxide nanothorn-decorated filters with three bore sizes (5.22, 8.36, and 16.75 μm) were fabricated for efficient online lysis of the cell membrane (even nuclear membrane) to facilitate intracellular analyte release and demonstrated to have a size effect for potential subcellular discrimination. The two smaller-bore filters gave 2-11-fold improvements in signal response for representative intracellular metabolites, such as adenosine, glutamine, and leucine/isoleucine. Especially, the smallest-bore filter enabled successful detection of the metabolites in the nucleus, including tetrahydrobiopterin and cyclic guanosine monophosphate. The developed all-in-one system was explored to monitor the uptake of four anticancer drugs, including 5-fluorouracil, doxorubicin, gambogic acid, and paclitaxel in single cells, and further to investigate the drug uptake trends at the subcellular level. The all-in-one system integrates the merits of high-throughput single-cell screening and in-depth intracellular information profiling and is promising for high-coverage single-cell metabolome analysis to serve cell biology research and cancer research.

An Integrated Strategy for Mass Spectrometry-Based Multiomics Analysis of Single Cells

Single-cell-based genomics and transcriptomics analysis have revealed substantial cellular heterogeneity among seemingly identical cells. Knowledge of the cellular heterogeneity at multiomics levels is vital for a better understanding of tumor metastasis and drug resistance, stem cell differentiation, and embryonic development. However, unlike genomics and transcriptomics studies, single-cell characterization of metabolites, proteins, and post-translational modifications at the omics level remains challenging due to the lack of amplification methods and the wide diversity of these biomolecules. Therefore, new tools that are capable of investigating these unamplifiable "omes" from the same single cells are in high demand. In this work, a microwell chip was prepared and the internal surface was modified for hydrophilic interaction liquid chromatography-based tandem extraction of metabolites and proteins and subsequent protein digestion. Next, direct electrospray ionization mass spectrometry was adopted for single-cell metabolome identification, and a data-independent acquisition-mass spectrometry approach was established for simultaneous proteome profiling and phosphoproteome analysis without phosphopeptide enrichment. This integrated strategy resulted in 132 putatively annotated compounds, more than 1200 proteins, and the first large-scale phosphorylation data set from single-cell analysis. Application of this strategy in chemical perturbation studies provides a multiomics view of cellular changes, demonstrating its capability for more comprehensive investigation of cellular heterogeneity.

Protocol for multimodal analysis of human kidney tissue by imaging mass spectrometry and CODEX multiplexed immunofluorescence

Here, we describe the preservation and preparation of human kidney tissue for interrogation by histopathology, imaging mass spectrometry, and multiplexed immunofluorescence. Custom image registration and integration techniques are used to create cellular and molecular atlases of this organ system. Through careful optimization, we ensure high-quality and reproducible datasets suitable for cross-patient comparisons that are essential to understanding human health and disease. Moreover, each of these steps can be adapted to other organ systems or diseases, enabling additional atlas efforts.

High-Content Label-Free Single-Cell Analysis with a Microfluidic Device Using Programmable Scanning Electrochemical Microscopy

The cellular heterogeneity and plasticity are often overlooked due to the averaged bulk assay in conventional methods. Optical imaging-based single-cell analysis usually requires specific labeling of target molecules inside or on the surface of the cell membrane, interfering with the physiological homeostasis of the cell. Scanning electrochemical microscopy (SECM), as an alternative approach, enables label-free imaging of single cells, which still confronts the challenge that the long-time scanning process is not feasible for large-scale analysis at the single-cell level. Herein, we developed a methodology combining a programmable SECM (P-SECM) with an addressable microwell array, which dramatically shortened the time consumption for the topography detection of the micropits array occupied by the polystyrene beads as well as the evaluation of alkaline phosphatase (ALP) activity of the 82 single cells compared with the traditional SECM imaging. This new arithmetic was based on the line scanning approach, enabling analysis of over 900 microwells within 1.2 h, which is 10 times faster than conventional SECM imaging. By implementing this configuration with the dual-mediator-based voltage-switching (VSM) mode, we investigated the activity of ALP, a promising marker for cancer stem cells, in hundreds of tumor and stromal cells on a single microwell device. The results discovered that not only a higher ALP activity is presented in cancer cells but also the heterogeneous distribution of kinetic constant (k_f value) of ALP activity can be obtained at the single-cell level. By directly relating large numbers of addressed cells on the scalable microfluidic device to the deterministic routing of the above SECM tip, our platform holds potential as a high-content screening tool for label-free single-cell analysis.

Towards high throughput and high information coverage: advanced single-cell mass spectrometric techniques

Mass spectrometry (MS) is attractive for single-cell analysis because of its high sensitivity, rich information, and large dynamic ranges, especially for the single-cell metabolome and proteome analysis. Efforts have been made to deal with the throughput and information coverage problems in typical manual single-cell MS techniques. In this review, advanced techniques to improve the automation and throughput for single-cell sampling and single-cell metabolome and proteome MS detection have been discussed. Furthermore, representative MS-based strategies that can increase the in-depth cellular information coverage and achieve the more comprehensive single-cell multiomics information during high throughput detection have been highlighted, providing an ongoing perspective of the MS performance for the single-cell research.

Discriminating Leukemia Cellular Heterogeneity and Screening Metabolite Biomarker Candidates using Label-Free Mass Cytometry

Discriminating various leukocyte subsets with specific functions is critical due to their important roles in the development of many diseases. Here, we proposed a general strategy to unravel leukocytes heterogeneity and screen differentiated metabolites as biomarker candidates for leukocyte subtypes using the label-free mass cytometry (CyESI-MS) combined with a homemade data processing workflow. Taking leukemia cells as an example, metabolic fingerprints of single leukemia cells were obtained from 472 HL-60, 416 THP-1, 313 U937, 356 Jurkat, and 366 Ramos cells, with throughput up to 40 cells/min. Five leukemia subtypes were clearly distinguished by unsupervised learning t-SNE analysis of the single-cell metabolic fingerprints. Cell discrimination in the mixed leukemia cell samples was also realized by supervised learning of the single-cell metabolic fingerprints with high recovery and good repetition (98.31 ± 0.24%, -102.35 ± 4.82%). Statistical analysis and metabolite assignment were carried out to screen characteristic metabolites for discrimination and 36 metabolites with significant differences were annotated. Then, differentiated metabolites for pairwise discrimination of five leukemia subtypes were further selected as biomarker candidates. Furthermore, discriminating cultured leukemia cells from human normal leukocytes, separated from fresh human peripheral blood, was performed based on single-cell metabolic fingerprints as well as the proposed biomarker candidates, unveiling the potential of this strategy in clinical research. This work makes efforts to realize high-throughput single-leukocyte metabolic analysis and metabolite-based discrimination of leukocytes. It is expected to be a powerful means for the clinical molecular diagnosis of hematological diseases.

High-Throughput Analysis of Tissue-Embedded Single Cells by Mass Spectrometry with Bimodal Imaging and Object Recognition

In biological tissues, cell-to-cell variations stem from the stochastic and modulated expression of genes and the varying abundances of corresponding proteins. These variations are then propagated to downstream metabolite products and result in cellular heterogeneity. Mass spectrometry imaging (MSI) is a promising tool to simultaneously provide spatial distributions for hundreds of biomolecules without the need for labels or stains. Technological advances in MSI instrumentation for the direct analysis of tissue-embedded single cells are dominated by improvements in sensitivity, sample pretreatment, and increased spatial resolution but are limited by low throughput. Herein, we introduce a bimodal microscopy imaging system combined with fiber-based laser ablation electrospray ionization (f-LAESI) MSI with improved throughput ambient analysis of tissue-embedded single cells (n > 1000) to provide insight into cellular heterogeneity. Based on automated image analysis, accurate single-cell sampling is achieved by f-LAESI leading to the discovery of cellular phenotypes characterized by differing metabolite levels.

Single-cell lipidomics with high structural specificity by mass spectrometry

Single-cell analysis is critical to revealing cell-to-cell heterogeneity that would otherwise be lost in ensemble analysis. Detailed lipidome characterization for single cells is still far from mature, especially when considering the highly complex structural diversity of lipids and the limited sample amounts available from a single cell. We report the development of a general strategy enabling single-cell lipidomic analysis with high structural specificity. Cell fixation is applied to retain lipids in the cell during batch treatments prior to single-cell analysis. In addition to tandem mass spectrometry analysis revealing the class and fatty acyl-chain for lipids, batch photochemical derivatization and single-cell droplet treatment are performed to identify the C=C locations and sn-positions of lipids, respectively. Electro-migration combined with droplet-assisted electrospray ionization enables single-cell mass spectrometry analysis with easy operation but high efficiency in sample usage. Four subtypes of human breast cancer cells are correctly classified through quantitative analysis of lipid C=C location or sn-position isomers in ~160 cells. Most importantly, the single-cell deep lipidomics strategy successfully discriminates gefitinib-resistant cells from a population of wild-type human lung cancer cells (HCC827), highlighting its unique capability to promote precision medicine.

Development of a Matrix Sublimation Device with Controllable Crystallization Temperature for MALDI Mass Spectrometry Imaging

The size and distribution of matrix crystals deposited on the surface of a tissue section play a key role in the performance of MALDI mass spectrometry imaging (MALDI-MSI). In this study, uniform distribution and a restricted size of matrix crystals were achieved via a homemade matrix sublimation device with controllable crystallization temperature. The crystallization temperature was stably controlled at a subzero temperature, and homogeneous matrix crystals with diameters <0.2 μm were generated on the sample surface. Typical MALDI-MSI experiments of endogenous and exogenous components in the tissues of strawberries, kidneys, and mussels were conducted to examine the performance of the sublimator. Good reproducibility of MALDI-MSI was achieved, and the quality of ion images was significantly improved. These results demonstrate that the developed sublimator should have potential in matrix deposition for further high resolution MALDI-MSI application.

Single cell imaging reveals cisplatin regulating interactions between transcription (co)factors and DNA

Cisplatin is an extremely successful anticancer drug, and is commonly thought to target DNA. However, the way in which cisplatin-induced DNA lesions regulate interactions between transcription factors/cofactors and genomic DNA remains unclear. Herein, we developed a dual-modal microscopy imaging strategy to investigate, in situ, the formation of ternary binding complexes of the transcription cofactor HMGB1 and transcription factor Smad3 with cisplatin crosslinked DNA in single cells. We utilized confocal microscopy imaging to map EYFP-fused HMGB1 and fluorescent dye-stained DNA in single cells, followed by the visualization of cisplatin using high spatial resolution (200-350 nm) time of flight secondary ion mass spectrometry (ToF-SIMS) imaging of the same cells. The superposition of the fluorescence and the mass spectrometry (MS) signals indicate the formation of HMGB1-Pt-DNA ternary complexes in the cells. More significantly, for the first time, similar integrated imaging revealed that the cisplatin lesions at Smad-binding elements, for example GGC(GC)/(CG) and AGAC, disrupted the interactions of Smad3 with DNA, which was evidenced by the remarkable reduction in the expression of Smad-specific luciferase reporters subjected to cisplatin treatment. This finding suggests that Smad3 and its related signalling pathway are most likely involved in the intracellular response to cisplatin induced DNA damage.

Image-guided MALDI mass spectrometry for high-throughput single-organelle characterization

Peptidergic dense-core vesicles are involved in packaging and releasing neuropeptides and peptide hormones-critical processes underlying brain, endocrine and exocrine function. Yet, the heterogeneity within these organelles, even for morphologically defined vesicle types, is not well characterized because of their small volumes. We present image-guided, high-throughput mass spectrometry-based protocols to chemically profile large populations of both dense-core vesicles and lucent vesicles for their lipid and peptide contents, allowing observation of the chemical heterogeneity within and between these two vesicle populations. The proteolytic processing products of four prohormones are observed within the dense-core vesicles, and the mass spectral features corresponding to the specific peptide products suggest three distinct dense-core vesicle populations. Notable differences in the lipid mass range are observed between the dense-core and lucent vesicles. These single-organelle mass spectrometry approaches are adaptable to characterize a range of subcellular structures.

Multimodal Imaging Mass Spectrometry: Next Generation Molecular Mapping in Biology and Medicine

Imaging mass spectrometry has become a mature molecular mapping technology that is used for molecular discovery in many medical and biological systems. While powerful by itself, imaging mass spectrometry can be complemented by the addition of other orthogonal, chemically informative imaging technologies to maximize the information gained from a single experiment and enable deeper understanding of biological processes. Within this review, we describe MALDI, SIMS, and DESI imaging mass spectrometric technologies and how these have been integrated with other analytical modalities such as microscopy, transcriptomics, spectroscopy, and electrochemistry in a field termed multimodal imaging. We explore the future of this field and discuss forthcoming developments that will bring new insights to help unravel the molecular complexities of biological systems, from single cells to functional tissue structures and organs.

In Situ Visualization of Proteins in Single Cells by Time-of-Flight-Secondary Ion Mass Spectrometry Coupled with Genetically Encoded Chemical Tags

In situ visualization of proteins of interest in single cells is attractive in cell biology, molecular biology, and biomedicine fields. Time-of-flight-secondary ion mass spectrometry (ToF-SIMS) is a powerful tool for imaging small organic molecules in single cells, yet difficult to image biomacromolecules such as proteins and DNA. Herein, a universal strategy is reported to image specific proteins in single cells by ToF-SIMS following genetic incorporation of fluorine-containing unnatural amino acids as a chemical tag into the proteins via a genetic code expansion technique. The method was developed and validated by imaging a green fluorescence protein (GFP) in Escherichia coli (E. coli) and human HeLa cancer cells and then utilized to visualize the characteristic polar distribution of chemotaxis protein CheA in E. coli cells and the interaction between high-mobility group box 1 protein and cisplatin-damaged DNA in HeLa cells. The present work highlights the power of ToF-SIMS imaging combined with genetically encoded chemical tags for in situ visualization of specific proteins as well as the interactions between proteins and drugs or drug-damaged DNA in single cells.

Three-Dimensional Mass Spectrometric Imaging of Biological Structures Using a Vacuum-Compatible Microfluidic Device

Three-dimensional (3D) molecular imaging of biological structures is important for a wide range of research. In recent decades, secondary-ion mass spectrometry (SIMS) has been recognized as a powerful technique for both two-dimensional and 3D molecular imaging. Sample fixations (e.g., chemical fixation and cryogenic fixation methods) are necessary to adapt biological samples to the vacuum condition in the SIMS chamber, which has been demonstrated to be nontrivial and less controllable, thus limiting the wider application of SIMS on 3D molecular analysis of biological samples. Our group recently developed in situ liquid SIMS that offers great opportunities for the molecular study of various liquids and liquid interfaces. In this work, we demonstrate that a further development of the vacuum-compatible microfluidic device used in in situ liquid SIMS provides a convenient freeze-fixation of biological samples and leads to more controllable and convenient 3D molecular imaging. The special design of this new vacuum-compatible liquid chamber allows an easy determination of sputter rates of ice, which is critical for calibrating the depth scale of frozen biological samples. Sputter yield of a 20 keV Ar₁₈₀₀⁺ ion on ice has been determined as 1500 (±8%) water molecules per Ar₁₈₀₀⁺ ion, consistent with our results from molecular dynamics simulations. Moreover, using the information of ice sputter yield, we successfully conduct 3D molecular imaging of frozen homogenized milk and observe network structures of interesting organic and inorganic species. Taken together, our results will significantly benefit various research fields relying on 3D molecular imaging of biological structures.

Spatial Metabolomics of the Human Kidney using MALDI Trapped Ion Mobility Imaging Mass Spectrometry

Low molecular weight metabolites are essential for defining the molecular phenotypes of cells. However, spatial metabolomics tools often lack the sensitivity, specify, and spatial resolution to provide comprehensive descriptions of these species in tissue. MALDI imaging mass spectrometry (IMS) of low molecular weight ions is particularly challenging as MALDI matrix clusters are often nominally isobaric with multiple metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Additional difficulties surrounding low weight metabolite visualization include high resolution imaging, while maintaining sufficient ion numbers for broad and representative analysis of the tissue chemical complement. Here, we use MALDI timsTOF IMS to image low molecular weight metabolites at higher spatial resolution than most metabolite MALDI IMS experiments (20 μm) while maintaining broad coverage within the human kidney. We demonstrate that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different distributions within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for spatial metabolomics experiments. Through this improved sensitivity, we have found >40 low molecular weight metabolites in human kidney tissue, such as argininic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. Future work will involve further exploring metabolomic profiles of human kidneys as a function of age, sex, and race.