Single-cell metabolomics: changes in the metabolome of freshly isolated and cultured neurons

The development of the occurrence and metastasis of breast cancer by single-cell sequencing

Breast cancer is currently the most frequent malignant tumor and the leading cause of cancer death among women globally. Although the five-year survival rate for early breast cancer has risen to more than 90%, medication resistance persists in advanced breast cancer and some intractable breast cancer, resulting in a poor prognosis, a high recurrence rate, and a low survival rate. Single-cell sequencing (SCS) is the study of a single cell's gene structure and expression level differences in order to discover unusual molecular subgroups, disease development, and a variety of mechanisms. This review briefly discusses single-cell sequencing and its application, and lists the research on single-cell sequencing in the development and metastasis of breast cancer, in order to bring fresh ideas for the comprehensive treatment of breast cancer.

Multiscale metabolomics techniques: Insights into neuroscience research

The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.

Challenges of Spatially Resolved Metabolism in Cancer Research

Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies.

A review of the current state of single-cell proteomics and future perspective

Single-cell methodologies and technologies have started a revolution in biology which until recently has primarily been limited to deep sequencing and imaging modalities. With the advent and subsequent torrid development of single-cell proteomics over the last 5 years, despite the fact that proteins cannot be amplified like transcripts, it has now become abundantly clear that it is a worthy complement to single-cell transcriptomics. In this review, we engage in an assessment of the current state of the art of single-cell proteomics including workflow, sample preparation techniques, instrumentation, and biological applications. We investigate the challenges associated with working with very small sample volumes and the acute need for robust statistical methods for data interpretation. We delve into what we believe is a promising future for biological research at single-cell resolution and highlight some of the exciting discoveries that already have been made using single-cell proteomics, including the identification of rare cell types, characterization of cellular heterogeneity, and investigation of signaling pathways and disease mechanisms. Finally, we acknowledge that there are a number of outstanding and pressing problems that the scientific community vested in advancing this technology needs to resolve. Of prime importance is the need to set standards so that this technology becomes widely accessible allowing novel discoveries to be easily verifiable. We conclude with a plea to solve these problems rapidly so that single-cell proteomics can be part of a robust, high-throughput, and scalable single-cell multi-omics platform that can be ubiquitously applied to elucidating deep biological insights into the diagnosis and treatment of all diseases that afflict us.

An attempt to simultaneously quantify the polysaccharide, total lipid, protein and pigment in single Cyclotella cryptica cell by Raman spectroscopy

BACKGROUND

At present, the conventional methods for determining photosynthetic products of microalgae are usually based on a large number of cell mass to reach the measurement baseline, and the result can only reveal the average state at the population level, which is not feasible for large-scale and rapid screening of specific phenotypes from a large number of potential microalgae mutants. In recent years, single-cell Raman spectra (SCRS) has been proved to be able to rapidly and simultaneously quantify the biochemical components of microalgae. However, this method has not been reported to analyze the biochemical components of Cyclotella cryptica (C. cryptica). Thus, SCRS was first attempt to determine these four biochemical components in this diatom.

RESULTS

The method based on SCRS was established to simultaneously quantify the contents of polysaccharide, total lipids, protein and Chl-a in C. cryptica, with thirteen Raman bands were found to be the main marker bands for the diatom components. Moreover, Partial Least Square Regression (PLSR) models based on full spectrum can reliably predict these four cellular components, with Pearson correlation coefficient for these components reached 0.949, 0.904, 0.801 and 0.917, respectively. Finally, based on SCRS data of one isogenic sample, the pairwise correlation and dynamic transformation process of these components can be analyzed by Intra-ramanome Correlation Analysis (IRCA), and the results showed silicon starvation could promote the carbon in C. cryptica cells to flow from protein and pigment metabolism to polysaccharide and lipid metabolism.

CONCLUSIONS

First, method for the simultaneous quantification of the polysaccharide, total lipid, protein and pigment in single C. cryptica cell are established. Second, the instant interconversion of intracellular components was constructed through IRCA, which is based on data set of one isogenic population and more precision and timeliness. Finally, total results indicated that silicon deficiency could promote the carbon in C. cryptica cells to flow from protein and pigment metabolism to polysaccharide and lipid metabolism.

Mass spectrometry-based strategies for single-cell metabolomics

Single cell analysis has drawn increasing interest from the research community due to its capability to interrogate cellular heterogeneity, allowing refined tissue classification and facilitating novel biomarker discovery. With the advancement of relevant instruments and techniques, it is now possible to perform multiple omics including genomics, transcriptomics, metabolomics or even proteomics at single cell level. In comparison with other omics studies, single-cell metabolomics (SCM) represents a significant challenge since it involves many types of dynamically changing compounds with a wide range of concentrations. In addition, metabolites cannot be amplified. Although difficult, considerable progress has been made over the past decade in mass spectrometry (MS)-based SCM in terms of processing technologies and biochemical applications. In this review, we will summarize recent progress in the development of promising MS platforms, sample preparation methods and SCM analysis of various cell types (including plant cell, cancer cell, neuron, embryo cell, and yeast cell). Current limitations and future research directions in the field of SCM will also be discussed.

The Biological Hierarchy, Time, and Temporal 'Omics in Evolutionary Biology: A Perspective

Sequencing data-genomics, transcriptomics, epigenomics, proteomics, and metabolomics-have revolutionized biological research, enabling a more detailed study of processes, ranging from subcellular to evolutionary, that drive biological organization. These processes, collectively, are responsible for generating patterns of phenotypic variation and can operate over dramatically different timescales (milliseconds to billions of years). While researchers often study phenotypic variation at specific levels of biological organization to isolate processes operating at that particular scale, the varying types of sequence data, or 'omics, can also provide complementary inferences to link molecular and phenotypic variation to produce an integrated view of evolutionary biology, ranging from molecular pathways to speciation. We briefly describe how 'omics has been used across biological levels and then demonstrate the utility of integrating different types of sequencing data across multiple biological levels within the same study to better understand biological phenomena. However, single-time-point studies cannot evaluate the temporal dynamics of these biological processes. Therefore, we put forward temporal 'omics as a framework that can better enable researchers to study the temporal dynamics of target processes. Temporal 'omics is not infallible, as the temporal sampling regime directly impacts inferential ability. Thus, we also discuss the role the temporal sampling regime plays in deriving inferences about the environmental conditions driving biological processes and provide examples that demonstrate the impact of the sampling regime on biological inference. Finally, we forecast the future of temporal 'omics by highlighting current methodological advancements that will enable temporal 'omics to be extended across species and timescales. We extend this discussion to using temporal multi-omics to integrate across the biological hierarchy to evaluate and link the temporal dynamics of processes that generate phenotypic variation.

Single cell metabolism: current and future trends

Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.

Metabolomics-based mass spectrometry methods to analyze the chemical content of 3D organoid models

Metabolomics, the study of metabolites present in biological samples, can provide a global view of sample state as well as insights into biological changes caused by disease or environmental interactions. Mass spectrometry (MS) is commonly used for metabolomics analysis given its high-throughput capabilities, high sensitivity, and capacity to identify multiple compounds in complex samples simultaneously. MS can be coupled to separation methods that can handle small volumes, making it well suited for analyzing the metabolome of organoids, miniaturized three-dimensional aggregates of stem cells that model in vivo organs. Organoids are being used in research efforts to study human disease and development, and in the design of personalized drug treatments. For organoid models to be useful, they need to recapitulate morphological and chemical aspects, such as the metabolome, of the parent tissue. This review highlights the separation- and imaging-based MS-based metabolomics methods that have been used to analyze the chemical contents of organoids. Future perspectives on how MS techniques can be optimized to determine the accuracy of organoid models and expand the field of organoid research are also discussed.

Single-Neuron RNA Modification Analysis by Mass Spectrometry: Characterizing RNA Modification Patterns and Dynamics with Single-Cell Resolution

The entire collection of post-transcriptional modifications to RNA, known as the epitranscriptome, has been increasingly recognized as a critical regulatory layer in the cellular translation machinery. However, contemporary methods for the analysis of RNA modifications are limited to the detection of highly abundant modifications in bulk tissue samples, potentially obscuring unique epitranscriptomes of individual cells with population averages. We developed an approach, single-neuron RNA modification analysis by mass spectrometry (SNRMA-MS), that enables the detection and quantification of numerous post-transcriptionally modified nucleosides in single cells. When compared to a conventional RNA extraction approach that does not allow detection of RNA modifications in single cells, SNRMA-MS leverages an optimized sample preparation approach to detect up to 16 RNA modifications in individual neurons from the central nervous system of Aplysia californica. SNRMA-MS revealed that the RNA modification profiles of identified A. californica neurons with different physiological functions were mostly cell specific. However, functionally homologous neurons tended to demonstrate similar modification patterns. Stable isotope labeling with CD3-Met showed significant differences in RNA methylation rates that were dependent on the identity of the modification and the cell, with metacerebral cells (MCCs) displaying the fastest incorporation of CD3 groups into endogenous RNAs. Quantitative SNRMA-MS showed higher intracellular concentrations for 2'-O-methyladenosine and 2'-O-methylcytidine in homologous R2/LPl1 cell pairs than in MCCs. Overall, SNRMA-MS is the first analytical approach capable of simultaneously quantifying numerous RNA modifications in single neurons and revealing cell-specific modification profiles.

The limitless applications of single-cell metabolomics

Single-cell metabolomics (SCM) is currently one of the most powerful tools for performing high-throughput metabolic analysis at the cellular level. The power of single-cell metabolomics to determine the metabolic profiles of individual cells makes it very suitable for decoding cell heterogeneity. SCM bears great potential in cell type identification and differentiation within cell colonies. With the development of various equipment and techniques, SCM analysis has become possible for a wide range of biological samples. Many fields have incorporated this cutting-edge analytic tool to generate fruitful findings. This review article pays close attention to the prevalent techniques utilized in SCM and the exciting new findings and applications developed by studies in phytology, neurology, and oncology using SCM.

Spray-Capillary-Based Capillary Electrophoresis Mass Spectrometry for Metabolite Analysis in Single Cells

Single-cell capillary electrophoresis mass spectrometry (CE-MS) is a promising platform to analyze cellular contents and probe cell heterogeneity. However, current single-cell CE-MS methods often rely on offline microsampling processes and may demonstrate low sampling precision and accuracy. We have recently developed an electrospray-assisted device, spray-capillary, for low-volume sample extraction. With the spray-capillary, low-volume samples (pL-nL) are drawn into the sampling end of the device, which can be used directly for CE separation and online MS detection. Here, we redesigned the spray-capillary by utilizing a capillary with a <15 μm tapered tip so that it can be directly inserted into single cells for sample collection and on-capillary CE-MS analysis. We evaluated the performance of the modified spray-capillary by performing single-cell microsampling on single onion cells with varying sample injection times and direct MS analysis or online CE-MS analysis. We have demonstrated, for the first time, online sample collection and CE-MS for the analysis of single cells. This application of the modified spray-capillary device facilitates the characterization and relative quantification of hundreds of metabolites in single cells.

Metabolomic profiling of rare cell populations isolated by flow cytometry from tissues

Little is known about the metabolic regulation of rare cell populations because most metabolites are hard to detect in small numbers of cells. We previously described a method for metabolomic profiling of flow cytometrically isolated hematopoietic stem cells (HSCs) that detects 60 metabolites in 10,000 cells (Agathocleous et al., 2017). Here we describe a new method involving hydrophilic liquid interaction chromatography and high-sensitivity orbitrap mass spectrometry that detected 160 metabolites in 10,000 HSCs, including many more glycolytic and lipid intermediates. We improved chromatographic separation, increased mass resolution, minimized ion suppression, and eliminated sample drying. Most metabolite levels did not significantly change during cell isolation. Mouse HSCs exhibited increased glycerophospholipids relative to bone marrow cells and methotrexate treatment altered purine biosynthesis. Circulating human melanoma cells were depleted for purine intermediates relative to subcutaneous tumors, suggesting decreased purine synthesis during metastasis. These methods facilitate the routine metabolomic analysis of rare cells from tissues.

Recent Advances in Trace Bioanalysis by Capillary Electrophoresis

Recently, single cell analysis is becoming more and more important to elucidate cellular heterogeneity. Except for nucleic acid that can be amplified by PCR, the required technical level for single cell analysis is extremely high and the appropriate design of sample preparation and a sensitive analytical system is necessary. Capillary/microchip electrophoresis (CE/MCE) can separate biomolecules in nL-scale solution with high resolution, and it is highly compatible with trace samples like a single cell. Coupled with highly sensitive detectors such as laser-induced fluorescence and nano-electrospray ionization-mass spectrometry, zmol level analytes can be detected. For further enhancing sensitivity, online sample preconcentration techniques can be employed. By integrating these high-sensitive techniques, single cell analysis of metabolites, proteins, and lipids have been achieved. This review paper highlights successful research on CE/MCE-based trace bioanalysis in recent 10 years. Firstly, an overview of basic knowledge on CE/MCE including sensitivity enhancement techniques is provided. Applications to trace bioanalysis are then introduced with discussion on current issues and future prospects.

State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing

Multi-omics, variously called integrated omics, pan-omics, and trans-omics, aims to combine two or more omics data sets to aid in data analysis, visualization and interpretation to determine the mechanism of a biological process. Multi-omics efforts have taken center stage in biomedical research leading to the development of new insights into biological events and processes. However, the mushrooming of a myriad of tools, datasets, and approaches tends to inundate the literature and overwhelm researchers new to the field. The aims of this review are to provide an overview of the current state of the field, inform on available reliable resources, discuss the application of statistics and machine/deep learning in multi-omics analyses, discuss findable, accessible, interoperable, reusable (FAIR) research, and point to best practices in benchmarking. Thus, we provide guidance to interested users of the domain by addressing challenges of the underlying biology, giving an overview of the available toolset, addressing common pitfalls, and acknowledging current methods' limitations. We conclude with practical advice and recommendations on software engineering and reproducibility practices to share a comprehensive awareness with new researchers in multi-omics for end-to-end workflow.

Charting Metabolism Heterogeneity by Nanostructure Imaging Mass Spectrometry: From Biological Systems to Subcellular Functions

The study of metabolism heterogeneity is essential to understand the role of metabolites in supporting and regulating biological functions. To this end, several mass spectrometry imaging (MSI) approaches have been proposed for the detection of small molecule metabolites. However, high noise from the ionization matrix and low metabolome coverage hinder their applicability for untargeted metabolomics studies across space. In this context, nanostructure imaging (/initiator) mass spectrometry (NIMS) and NIMS with fluorinated gold nanoparticles (f-AuNPs) are attractive strategies for comprehensive MSI of metabolites in biological systems, which can provide heterogeneous metabolome coverage, ultrahigh sensitivity, and high lateral resolution. In particular, NIMS with f-AuNPs permits the simultaneous detection of polar metabolites and lipids in a single and cohesive analytical session, thus allowing the systems-level interpretation of metabolic changes. In this Perspective article, we discuss the use of NIMS and f-AuNPs in the exploration of metabolism heterogeneity and provide a critical outlook on future applications of this technology for revealing the metabolic architecture that supports biological functions in health and disease, from whole organisms to tissues, single cells, and subcellular compartments.

Deciphering Metabolic Heterogeneity by Single-Cell Analysis

Single-cell analysis provides insights into cellular heterogeneity and dynamics of individual cells. This Feature highlights recent developments in key analytical techniques suited for single-cell metabolic analysis with a special focus on mass spectrometry-based analytical platforms and RNA-seq as well as imaging techniques that reveal stochasticity in metabolism.

Ultrasensitive Single Cell Metabolomics by Capillary Electrophoresis-Mass Spectrometry with a Thin-Walled Tapered Emitter and Large-Volume Dual Sample Preconcentration

Single cell metabolome analysis is essential for studying microscale life phenomena such as neuronal networks and tumor microenvironments. Capillary electrophoresis-mass spectrometry (CE-MS) is one of the most sensitive technologies; however, its sensitivity is still not enough for single cell analysis on general human cells such as HeLa. To address these issues, we first developed an efficient ionization emitter, named as a "nanoCESI" emitter, that had a thin-walled (∼10 μm) and tapered (5-10 μm) end. The thin conductive wall enabled sheathless ionization and minimized the flow rate of ionizing sample, and the tapered end efficiently ionized analytes via an electrospray ionization mechanism, providing up to 3.5-fold increase in sensitivity compared with a conventional sheathless emitter. Fifty repetitive analyses on 20 amino acids were successfully achieved with a nanoCESI emitter. Relative standard deviations of 50 analyses were 1.5%, 4.4%, and 6.8% for migration time, peak height, and peak area, respectively, where a limit of detection (LOD) of 170 pM (850 zmol) was achieved. Second, a sample enrichment method, large-volume dual preconcentration by isotachophoresis and stacking (LDIS), was applied to a newly designed protocol of nanoCESI-MS. This approach achieved up to 380-fold enhanced sensitivity and LOD of 450 fM. Compared with normal sheathless CE-MS, coupling of nanoCESI and LDIS provided up to 800-fold increase of sensitivity in total. Finally, metabolome analyses of single HeLa cells were performed, where 20 amino acids were successfully quantified with triple-quadrupole MS and 40 metabolites were identified with quadrupole-time-of-flight MS, as a promising analytical platform for microscale bioanalysis for the next generation.

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.

Recent Advances and New Perspectives in Capillary Electrophoresis-Mass Spectrometry for Single Cell "Omics"

Accurate clinical therapeutics rely on understanding the metabolic responses of individual cells. However, the high level of heterogeneity between cells means that simply sampling from large populations of cells is not necessarily a reliable approximation of an individual cell's response. As a result, there have been numerous developments in the field of single-cell analysis to address this lack of knowledge. Many of these developments have focused on the coupling of capillary electrophoresis (CE), a separation technique with low sample consumption and high resolving power, and mass spectrometry (MS), a sensitive detection method for interrogating all ions in a sample in a single analysis. In recent years, there have been many notable advancements at each step of the single-cell CE-MS analysis workflow, including sampling, manipulation, separation, and MS analysis. In each of these areas, the combined improvements in analytical instrumentation and achievements of numerous researchers have served to drive the field forward to new frontiers. Consequently, notable biological discoveries have been made possible by the implementation of these methods. Although there is still room in the field for numerous further advances, researchers have effectively minimized various limitations in detection of analytes, and it is expected that there will be many more developments in the near future.

Cell-Type-Specific Proteomics: A Neuroscience Perspective

Cell-type-specific analysis has become a major focus for many investigators in the field of neuroscience, particularly because of the large number of different cell populations found in brain tissue that play roles in a variety of developmental and behavioral disorders. However, isolation of these specific cell types can be challenging due to their nonuniformity and complex projections to different brain regions. Moreover, many analytical techniques used for protein detection and quantitation remain insensitive to the low amounts of protein extracted from specific cell populations. Despite these challenges, methods to improve proteomic yield and increase resolution continue to develop at a rapid rate. In this review, we highlight the importance of cell-type-specific proteomics in neuroscience and the technical difficulties associated. Furthermore, current progress and technological advancements in cell-type-specific proteomics research are discussed with an emphasis in neuroscience.

Different Bioactive Neuropeptides are Expressed in Two Sub-Classes of GABAergic RME Nerve Ring Motorneurons in Ascaris suum

Neuropeptides can have significant effects on neurons and synapses, but among the ∼250 predicted peptides in nematodes, few have been characterized functionally. Here, we report new neuropeptides in the 4 RME nerve ring motorneurons of the nematode Ascaris suum. These GABAergic neurons are involved in three-dimensional head movement. Mass spectrometry (MS) of single dissected RMEs detected a total of 12 neuropeptides (encoded by five genes), nine of which are novel. None of these are expressed in the DI/VI inhibitory GABAergic motorneurons that synapse onto body wall muscle. Using peptide sequences obtained by tandem MS, we cloned the peptide-encoding transcripts and synthesized riboprobes for in situ hybridization (ISH). This complementary technique corroborated the results from single-cell MS, showing that the dissections were not contaminated with adhering tissue from other cells. We also synthesized a multiple antigenic peptide to raise a highly specific antibody against one of the endogenous peptides, which labeled the same cells detected by MS and ISH. Our results show that the RMEs can be divided into two subsets: RMED/V (expressing afp-2, afp-15, Asu-nlp-58, and high levels of afp-16) and RMEL/R (expressing afp-15 and low levels of afp-4 and afp-16). Almost all of these peptides are bioactive in A. suum.

Design and Application of Sensors for Chemical Cytometry

The bulk cell population response to a stimulus, be it a growth factor or a cytotoxic agent, neglects the cell-to-cell variability that can serve as a friend or as a foe in human biology. Biochemical variations among closely related cells furnish the basis for the adaptability of the immune system but also act as the root cause of resistance to chemotherapy by tumors. Consequently, the ability to probe for the presence of key biochemical variables at the single-cell level is now recognized to be of significant biological and biomedical impact. Chemical cytometry has emerged as an ultrasensitive single-cell platform with the flexibility to measure an array of cellular components, ranging from metabolite concentrations to enzyme activities. We briefly review the various chemical cytometry strategies, including recent advances in reporter design, probe and metabolite separation, and detection instrumentation. We also describe strategies for improving intracellular delivery, biochemical specificity, metabolic stability, and detection sensitivity of probes. Recent applications of these strategies to small molecules, lipids, proteins, and other analytes are discussed. Finally, we assess the current scope and limitations of chemical cytometry and discuss areas for future development to meet the needs of single-cell research.

Single Cell Neurometabolomics

Metabolomics, the characterization of metabolites and their changes within biological systems, has seen great technological and methodological progress over the past decade. Most metabolomic experiments involve the characterization of the small-molecule content of fluids or tissue homogenates. While these microliter and larger volume metabolomic measurements can characterize hundreds to thousands of compounds, the coverage of molecular content decreases as sample sizes are reduced to the nanoliter and even to the picoliter volume range. Recent progress has enabled the ability to characterize the major molecules found within specific individual cells. Especially within the brain, a myriad of cell types are colocalized, and oftentimes only a subset of these cells undergo changes in both healthy and pathological states. Here we highlight recent progress in mass spectrometry-based approaches used for single cell metabolomics, emphasizing their application to neuroscience research. Single cell studies can be directed to measuring differences between members of populations of similar cells (e.g., oligodendrocytes), as well as characterizing differences between cell types (e.g., neurons and astrocytes), and are especially useful for measuring changes occurring during different behavior states, exposure to diets and drugs, neuronal activity, and disease. When combined with other omics approaches such as transcriptomics, and with morphological and physiological measurements, single cell metabolomics aids fundamental neurochemical studies, has great potential in pharmaceutical development, and should improve the diagnosis and treatment of brain diseases.

Single-Cell Mass Spectrometry of Metabolites Extracted from Live Cells by Fluidic Force Microscopy

Single-cell metabolite analysis provides valuable information on cellular function and response to external stimuli. While recent advances in mass spectrometry reached the sensitivity required to investigate metabolites in single cells, current methods commonly isolate and sacrifice cells, inflicting a perturbed state and preventing complementary analyses. Here, we propose a two-step approach that combines nondestructive and quantitative withdrawal of intracellular fluid with subpicoliter resolution using fluidic force microscopy, followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The developed method enabled the detection and identification of 20 metabolites recovered from the cytoplasm of individual HeLa cells. The approach was further validated in ¹³C-glucose feeding experiments, which showed incorporation of labeled carbon atoms into different metabolites. Metabolite sampling, followed by mass spectrometry measurements, enabled the preservation of the physiological context and the viability of the analyzed cell, providing opportunities for complementary analyses of the cell before, during, and after metabolite analysis.

Tapered-Tip Capillary Electrophoresis Nano-Electrospray Ionization Mass Spectrometry for Ultrasensitive Proteomics: the Mouse Cortex

Ultrasensitive characterization of the proteome raises the potential to understand how differential gene expression orchestrates cell heterogeneity in the brain. Here, we report a microanalytical capillary electrophoresis nano-flow electrospray ionization (CE-nanoESI) interface for mass spectrometry to enable the measurement of limited amounts of proteins in the mouse cortex. Our design integrates a custom-built CE system to a tapered-tip metal emitter in a co-axial sheath-flow configuration. This interface can be constructed in <15 min using readily available components, facilitating broad adaptation. Tapered-tip CE-nanoESI generates stable electrospray by reproducibly anchoring the Taylor cone, minimizes sample dilution in the ion source, and ensures efficient ion generation by sustaining the cone-jet spraying regime. Parallel reaction monitoring provided a 260-zmol lower limit of detection for angiotensin II (156,000 copies). CE was able to resolve a complex mixture of peptides in ~330,000 theoretical plates and identify ~15 amol (~1 pg) of BSA or cytochrome c. Over 30 min of separation, 1 ng protein digest from the mouse cortex yielded 217 nonredundant proteins encompassing a ~3-log-order concentration range using a quadrupole time-of-flight mass spectrometer. Identified proteins included many products from genes that are traditionally used to mark oligodendrocytes, astrocytes, and microglia. Finally, key proteins involved in neurodegenerative disorders were detected (e.g., parkinsonism and spastic paraplegia). CE-nanoESI-HRMS delivers sufficient sensitivity to detect proteins in limited amounts of tissues and cell populations to help understand how gene expression differences maintain cell heterogeneity in the brain. Graphical Abstract ᅟ.

Single-cell mass spectrometry with multi-solvent extraction identifies metabolic differences between left and right blastomeres in the 8-cell frog (Xenopus) embryo

Single-cell metabolic mass spectrometry enables the discovery (untargeted) analysis of small molecules in individual cells. Using single-cell capillary electrophoresis high-resolution mass spectrometry (CE-HRMS), we recently uncovered small-molecule differences between embryonic cells located along the animal-vegetal and dorsal-ventral axes of the 16-cell frog (Xenopus laevis) embryo, raising the question whether metabolic cell heterogeneity also exists along the left-right body axis. To address this question, we here advance single-cell CE-HRMS for identifying and quantifying metabolites in higher analytical sensitivity, and then use the methodology to compare metabolite production between left and right cells. Our strategy utilizes multiple solvents with complementary physicochemical properties to extract small molecules from single cells and improve electrophoretic separation, increasing metabolite ion signals for quantification and tandem HRMS. As a result, we were able to identify 55 different small molecules in D1 cells that were isolated from 8-cell embryos. To quantify metabolite production between left and right cells, we analyzed n = 24 different D1 cells in technical duplicate-triplicate measurements. Statistical and multivariate analysis based on 80 of the most repeatedly quantified compounds revealed 10 distinct metabolites that were significantly differentially accumulated in the left or right cells (p < 0.05 and fold change ≥1.5). These metabolites were enriched in the arginine-proline metabolic pathway in the right, but not the left D1 cells. Besides providing analytical benefits for single-cell HRMS, this work provides new metabolic data on the establishment of normal body asymmetry in the early developing embryo.

Toward Analysis of Proteins in Single Cells: A Quantitative Approach Employing Isobaric Tags with MALDI Mass Spectrometry Realized with a Microfluidic Platform

Protein identification and quantification in individual cells is essential to understand biological processes such as those involved in cell apoptosis, cancer, biomarker discovery, disease diagnostics, pathology, or therapy. Compared with present single cell genome analysis, probing the protein content of single cells has been hampered by the lack of a protein amplification technique. Here, we report the development of a quantitative mass spectrometric approach combined with microfluidic technology reaching the detection sensitivity of high abundant proteins in single cells. A microfluidic platform with a series of chambers and valves, ensuring a set of defined wells for absolute quantification of targeted proteins, was developed and combined with isotopic labeling strategies employing isobaric tags for relative and absolute quantitation (iTRAQ)-labels. To this aim, we adapted iTRAQ labeling to an on-chip protocol. Simultaneous protein digestion and labeling performed on the microfluidic platform rendered the labeling strategy compatible with all necessary manipulation steps on-chip, including the matrix delivery for MALDI-TOF analysis. We demonstrate this approach with the apoptosis related protein Bcl-2 and quantitatively assess the number of Bcl-2 molecules detected. We anticipate that this approach will eventually allow quantification of protein expression on the single cell level.

Using Dicationic Ion-Pairing Compounds To Enhance the Single Cell Mass Spectrometry Analysis Using the Single-Probe: A Microscale Sampling and Ionization Device

A unique mass spectrometry (MS) method has been developed to determine the negatively charged species in live single cells using the positive ionization mode. The method utilizes dicationic ion-pairing compounds through the miniaturized multifunctional device, the single-probe, for reactive MS analysis of live single cells under ambient conditions. In this study, two dicationic reagents, 1,5-pentanediyl-bis(1-butylpyrrolidinium) difluoride (C5(bpyr)2F2) and 1,3-propanediyl-bis(tripropylphosphonium) difluoride (C3(triprp)2F2), were added in the solvent and introduced into single cells to extract cellular contents for real-time MS analysis. The negatively charged (1- charged) cell metabolites, which form stable ion-pairs (1+ charged) with dicationic compounds (2+ charged), were detected in positive ionization mode with a greatly improved sensitivity. We have tentatively assigned 192 and 70 negatively charged common metabolites as adducts with (C5(bpyr)2F2) and (C3(triprp)2F2), respectively, in three separate SCMS experiments in the positive ion mode. The total number of tentatively assigned metabolites is 285 for C5(bpyr)2F2 and 143 for C3(triprp)2F2. In addition, the selectivity of dicationic compounds in the complex formation allows for the discrimination of overlapped ion peaks with low abundances. Tandem (MS/MS) analyses at the single cell level were conducted for selected adduct ions for molecular identification. The utilization of the dicationic compounds in the single-probe MS technique provides an effective approach to the detection of a broad range of metabolites at the single cell level.

Microfluidic Devices for the Measurement of Cellular Secretion

The release of chemical information from cells and tissues holds the key to understanding cellular behavior and dysfunction. The development of methodologies that can measure cellular secretion in a time-dependent fashion is therefore essential. Often these measurements are made difficult by the high-salt conditions of the cellular environment, the presence of numerous other secreted factors, and the small mass samples that are produced when frequent sampling is used to resolve secretory dynamics. In this review, the methods that we have developed for measuring hormone release from islets of Langerhans are dissected to illustrate the practical difficulties of studying cellular secretions. Other methods from the literature are presented that provide alternative approaches to particularly challenging areas of monitoring cellular secretion. The examples presented in this review serve as case studies and should be adaptable to other cell types and systems for unique applications.

Single-cell profiling approaches to probing tumor heterogeneity

Tumor heterogeneity is a major hindrance in cancer classification, diagnosis and treatment. Recent technological advances have begun to reveal the true extent of its heterogeneity. Single-cell analysis (SCA) is emerging as an important approach to detect variations in morphology, genetic or proteomic expression. In this review, we revisit the issue of inter- and intra-tumor heterogeneity, and list various modes of SCA techniques (cell-based, nucleic acid-based, protein-based, metabolite-based and lipid-based) presently used for cancer characterization. We further discuss the advantages of SCA over pooled cell analysis, as well as the limitations of conventional techniques. Emerging trends, such as high-throughput sequencing, are also mentioned as improved means for cancer profiling. Collectively, these applications have the potential for breakthroughs in cancer treatment.

Mass Spectrometry of Single GABAergic Somatic Motorneurons Identifies a Novel Inhibitory Peptide, As-NLP-22, in the Nematode Ascaris suum

Neuromodulators have become an increasingly important component of functional circuits, dramatically changing the properties of both neurons and synapses to affect behavior. To explore the role of neuropeptides in Ascaris suum behavior, we devised an improved method for cleanly dissecting single motorneuronal cell bodies from the many other cell processes and hypodermal tissue in the ventral nerve cord. We determined their peptide content using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). The reduced complexity of the peptide mixture greatly aided the detection of peptides; peptide levels were sufficient to permit sequencing by tandem MS from single cells. Inhibitory motorneurons, known to be GABAergic, contain a novel neuropeptide, As-NLP-22 (SLASGRWGLRPamide). From this sequence and information from the A. suum expressed sequence tag (EST) database, we cloned the transcript (As-nlp-22) and synthesized a riboprobe for in situ hybridization, which labeled the inhibitory motorneurons; this validates the integrity of the dissection method, showing that the peptides detected originate from the cells themselves and not from adhering processes from other cells (e.g., synaptic terminals). Synthetic As-NLP-22 has potent inhibitory activity on acetylcholine-induced muscle contraction as well as on basal muscle tone. Both of these effects are dose-dependent: the inhibitory effect on ACh contraction has an IC50 of 8.3 × 10(-9) M. When injected into whole worms, As-NLP-22 produces a dose-dependent inhibition of locomotory movements and, at higher levels, complete paralysis. These experiments demonstrate the utility of MALDI TOF/TOF MS in identifying novel neuromodulators at the single-cell level. Graphical Abstract ᅟ.

Analysis of metabolites in single cells-what is the best micro-platform?

This review covers new innovations and developments in the field of single-cell level analysis of metabolites, involving the role of microfluidic and microarray platforms to manipulate and handle the cells prior their detection. Microfluidic and microarray platforms have shown great promise. The latest developments demonstrate their potential to identify a particular cell or even an ensemble of cells (sharing a common property or phenotype) that co-exist in a much larger cell population. The reason for this is the capability of these platforms to perform several complex analytical processes, such as: cleanup, sorting, derivatization, separation, and detection, with great robustness, speed, and reduced sample/reagent consumption. Here, we present several examples that illustrate the rapid strides that have been made for the routine analysis of metabolites by coupling different microfluidics and microarrays devices to a wide range of analytical detectors (e.g. fluorescent microscopy, electrochemical, and mass spectrometry). Herein, we also present selected examples detailing the use of microfluidics and microarrays in the visualization of the natural occurring cell-to-cell heterogeneity in isogenic populations, in particular during the response to external cues. The possibility to accurate monitor the cell-to-cell heterogeneity based on different levels of key metabolites is of clinical relevance, since cell-to-cell heterogeneity can influence, for example, the outcome of a drug treatment.

Classification of Large Cellular Populations and Discovery of Rare Cells Using Single Cell Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Cell-to-cell variability and functional heterogeneity are integral features of multicellular organisms. Chemical classification of cells into cell type is important for understanding cellular specialization as well as organismal function and organization. Assays to elucidate these chemical variations are best performed with single cell samples because tissue homogenates average the biochemical composition of many different cells and oftentimes include extracellular components. Several single cell microanalysis techniques have been developed but tend to be low throughput or require preselection of molecular probes that limit the information obtained. Mass spectrometry (MS) is an untargeted, multiplexed, and sensitive analytical method that is well-suited for studying chemically complex individual cells that have low analyte content. In this work, populations of cells from the rat pituitary, the rat pancreatic islets of Langerhans, and from the Aplysia californica nervous system, are classified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI) MS by their peptide content. Cells were dispersed onto a microscope slide to generate a sample where hundreds to thousands of cells were separately located. Optical imaging was used to determine the cell coordinates on the slide, and these locations were used to automate the MS measurements to targeted cells. Principal component analysis was used to classify cellular subpopulations. The method was modified to focus on the signals described by the lower principal components to explore rare cells having a unique peptide content. This approach efficiently uncovers and classifies cellular subtypes as well as discovers rare cells from large cellular populations.

Different neuropeptides are expressed in different functional subsets of cholinergic excitatory motorneurons in the nematode Ascaris suum

Neuropeptides are known to have dramatic effects on neurons and synapses; however, despite extensive studies of the motorneurons in the parasitic nematode Ascaris suum, their peptide content had not yet been described. We determined the peptide content of single excitatory motorneurons by mass spectrometry and tandem mass spectrometry. There are two subsets of ventral cord excitatory motorneurons, each with neuromuscular output either anterior or posterior to their cell body, mediating forward or backward locomotion, respectively. Strikingly, the two sets of neurons contain different neuropeptides, with AF9 and six novel peptides (As-NLP-21.1-6) in anterior projectors, and the six afp-1 peptides in addition to AF2 in posterior projectors. In situ hybridization confirmed the expression of these peptides, validating the integrity of the dissection technique. This work identifies new components of the functional behavioral circuit, as well as potential targets for antiparasitic drug development.

Mass spectrometry-based characterization of endogenous peptides and metabolites in small volume samples

Technologies to assay single cells and their extracellular microenvironments are valuable in elucidating biological function, but there are challenges. Sample volumes are low, the physicochemical parameters of the analytes vary widely, and the cellular environment is chemically complex. In addition, the inherent difficulty of isolating individual cells and handling small volume samples complicates many experimental protocols. Here we highlight a number of mass spectrometry (MS)-based measurement approaches for characterizing the chemical content of small volume analytes, with a focus on methods used to detect intracellular and extracellular metabolites and peptides from samples as small as individual cells. MS has become one of the most effective means for analyzing small biological samples due to its high sensitivity, low analyte consumption, compatibility with a wide array of sampling approaches, and ability to detect a large number of analytes with different properties without preselection. Having access to a flexible portfolio of MS-based methods allows quantitative, qualitative, untargeted, targeted, multiplexed, and spatially resolved investigations of single cells and their similarly scaled extracellular environments. Combining MS with on-line and off-line sample conditioning tools, such as microfluidic and capillary electrophoresis systems, significantly increases the analytical coverage of the sample's metabolome and peptidome, and improves individual analyte characterization/identification. Small volume assays help to reveal the causes and manifestations of biological and pathological variability, as well as the functional heterogeneity of individual cells within their microenvironments and within cellular populations. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

Analysis of endogenous nucleotides by single cell capillary electrophoresis-mass spectrometry

Analytical technologies that enable investigations at the single cell level facilitate a range of studies; here a lab-fabricated capillary electrophoresis-electrospray ionization-mass spectrometry (CE-ESI-MS) platform was used to analyze anionic metabolites from individual Aplysia californica neurons. The system employs a customized coaxial sheath-flow nanospray interface connected to a separation capillary, with the sheath liquid and separation buffer optimized to ensure a stable spray. The method provided good repeatability of separation and reliable detection sensitivity for 16 mono-, di- and triphosphate nucleosides. For a range of anionic analytes, including cyclic adenosine monophosphate (cAMP), adenosine diphosphate (ADP) and adenosine triphosphate (ATP), the detection limits were in the low nanomolar range (<22 nM). A large Aplysia R2 neuron was used to demonstrate the ability of CE-ESI-MS to quantitatively characterize anionic metabolites within individual cells, with 15 nucleotides and derivatives detected. Following the method validation process, we probed smaller, 60 μm diameter Aplysia sensory neurons where sample stacking was used as a simple on-line analyte preconcentration approach. The calculated energy balance ([ATP] + 0.5 × [ADP])/([AMP] + [ADP] + [ATP]) of these cells was comparable with the value obtained from bulk samples.

Stimulation and release from neurons via a dual capillary collection device interfaced to mass spectrometry

Neuropeptides are cell to cell signaling molecules that modulate a wide range of physiological processes. Neuropeptide release has been studied in sample sizes ranging from single cells and neuronal clusters, to defined brain nuclei and large brain regions. We have developed and optimized cell stimulation and collection approaches for the efficient measurement of neuropeptide release from neuronal samples using a dual capillary system. The defining feature is a capillary that contains octadecyl-modified silica nanoparticles on its inner wall to capture and extract releasates. This collection capillary is inserted into another capillary used to deliver solutions that chemically stimulate the cells, with solution flowing up the inner capillary to facilitate peptide collection. The efficiency of peptide collection was evaluated using six peptide standards mixed in physiological saline. The extracted peptides eluted from these capillaries were characterized via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with low femtomole detection limits. Using the capillary collection system in small custom-fabricated culturing chambers, individual cultured neurons and neuronal clusters from the model animal Aplysia californica were stimulated with distinct neuronal secretagogues and the releasates were collected and characterized using MALDI-TOF MS.

D-Alanine in the islets of Langerhans of rat pancreas

Relatively high levels of D-alanine (D-Ala), an endogenous D-amino acid, have been found in the endocrine systems of several animals, especially in the anterior pituitary; however, its functional importance remains largely unknown. We observed D-Ala in islets of Langerhans isolated from rat pancreas in significantly higher levels than in the anterior/intermediate pituitary; specifically, 180±60 fmol D-Ala per islet (300±100 nmol/gislet), and 10±2.5 nmol/g of wet tissue in pituitary. Additionally, 12±5% of the free Ala in the islets was in the d form, almost an order of magnitude higher than the percentage of D-Ala found in the pituitary. Surprisingly, glucose stimulation of the islets resulted in D-Ala release of 0.6±0.5 fmol per islet. As D-Ala is stored in islets and released in response to changes in extracellular glucose, D-Ala may have a hormonal role.

Patch clamp electrophysiology and capillary electrophoresis-mass spectrometry metabolomics for single cell characterization

The visual selection of specific cells within an ex vivo brain slice, combined with whole-cell patch clamp recording and capillary electrophoresis (CE)–mass spectrometry (MS)-based metabolomics, yields high chemical information on the selected cells. By providing access to a cell’s intracellular environment, the whole-cell patch clamp technique allows one to record the cell’s physiological activity. A patch clamp pipet is used to withdraw ∼3 pL of cytoplasm for metabolomic analysis using CE–MS. Sampling the cytoplasm, rather than an intact isolated neuron, ensures that the sample arises from the cell of interest and that structures such as presynaptic terminals from surrounding, nontargeted neurons are not sampled. We sampled the rat thalamus, a well-defined system containing gamma-aminobutyric acid (GABA)-ergic and glutamatergic neurons. The approach was validated by recording and sampling from glutamatergic thalamocortical neurons, which receive major synaptic input from GABAergic thalamic reticular nucleus neurons, as well as neurons and astrocytes from the ventral basal nucleus and the dorsal lateral geniculate nucleus. From the analysis of the cytoplasm of glutamatergic cells, approximately 60 metabolites were detected, none of which corresponded to the compound GABA. However, GABA was successfully detected when sampling the cytoplasm of GABAergic neurons, demonstrating the exclusive nature of our cytoplasmic sampling approach. The combination of whole-cell patch clamp with single cell cytoplasm metabolomics provides the ability to link the physiological activity of neurons and astrocytes with their neurochemical state. The observed differences in the metabolome of these neurons underscore the striking cell to cell heterogeneity in the brain.

Ex vivo chemical cytometric analysis of protein tyrosine phosphatase activity in single human airway epithelial cells

We describe a novel method for the measurement of protein tyrosine phosphatase (PTP) activity in single human airway epithelial cells (hAECs) using capillary electrophoresis. This technique involved the microinjection of a fluorescent phosphopeptide that is hydrolyzed specifically by PTPs. Analyses in BEAS-2B immortalized bronchial epithelial cells showed rapid PTP-mediated dephosphorylation of the substrate (2.2 pmol min(-1) mg(-1)) that was blocked by pretreatment of the cells with the PTP inhibitors pervanadate, Zn(2+), and 1,2-naphthoquinone (76%, 69%, and 100% inhibition relative to PTP activity in untreated controls, respectively). These studies were then extended to a more physiologically relevant model system: primary hAECs cultured from bronchial brushings of living human subjects. In primary hAECs, dephosphorylation of the substrate occurred at a rate of 2.2 pmol min(-1) mg(-1) and was also effectively inhibited by preincubation of the cells with the inhibitors pervanadate, Zn(2+), and 1,2-naphthoquinone (91%, 88%, and 87% median PTP inhibition, respectively). Reporter proteolysis in single BEAS-2B cells occurred at a median rate of 43 fmol min(-1) mg(-1) resulting in a mean half-life of 20 min. The reporter displayed a similar median half-life of 28 min in these single primary cells. Finally, single viable epithelial cells (which were assayed for PTP activity immediately after collection by bronchial brushing of a human volunteer) showed dephosphorylation rates ranging from 0.34 to 36 pmol min(-1) mg(-1) (n = 6). These results demonstrate the utility and applicability of this technique for the ex vivo quantification of PTP activity in small, heterogeneous, human cells and tissues.

Small-volume analysis of cell-cell signaling molecules in the brain

Modern science is characterized by integration and synergy between research fields. Accordingly, as technological advances allow new and more ambitious quests in scientific inquiry, numerous analytical and engineering techniques have become useful tools in biological research. The focus of this review is on cutting edge technologies that aid direct measurement of bioactive compounds in the nervous system to facilitate fundamental research, diagnostics, and drug discovery. We discuss challenges associated with measurement of cell-to-cell signaling molecules in the nervous system, and advocate for a decrease of sample volumes to the nanoliter volume regimen for improved analysis outcomes. We highlight effective approaches for the collection, separation, and detection of such small-volume samples, present strategies for targeted and discovery-oriented research, and describe the required technology advances that will empower future translational science.