Single‐Cell Mass Spectrometry Approaches to Explore Cellular Heterogeneity

Microscale measurements of protein complexes from single cells

Proteins execute numerous cell functions in concert with one another in protein-protein interactions (PPI). While essential in each cell, such interactions are not identical from cell to cell. Instead, PPI heterogeneity contributes to cellular phenotypic heterogeneity in health and diseases such as cancer. Understanding cellular phenotypic heterogeneity thus requires measurements of properties of PPIs such as abundance, stoichiometry, and kinetics at the single-cell level. Here, we review recent, exciting progress in single-cell PPI measurements. Novel technology in this area is enabled by microscale and microfluidic approaches that control analyte concentration in timescales needed to outpace PPI disassembly kinetics. We describe microscale innovations, needed technical capabilities, and methods poised to be adapted for single-cell analysis in the near future.

High-throughput single-cell mass spectrometry enables metabolic network analysis by resolving phospholipid C[double bond, length as m-dash]C isomers

Single-cell mass spectrometry (MS) is an essential technology for sensitive and multiplexed analysis of metabolites and lipids for cell phenotyping and pathway studies. However, the structural elucidation of lipids from single cells remains a challenge, especially in the high-throughput scenario. Technically, there is a contradiction between the inadequate sample amount (i.e. a single cell, 0.5-20 pL) for replicate or multiple analysis, on the one hand, and the high metabolite coverage and multidimensional structure analysis that needs to be performed for each single cell, on the other hand. Here, we have developed a high-throughput single-cell MS platform that can perform both lipid profiling and lipid carbon-carbon double bond (C[double bond, length as m-dash]C) location isomer resolution analysis, aided by C[double bond, length as m-dash]C activation in unsaturated lipids by the Paternò-Büchi (PB) reaction and tandem MS, termed single-cell structural lipidomics analysis. The method can achieve a single-cell analysis throughput of 51 cells per minute. A total of 145 lipids were structurally characterized at the subclass level, of which the relative abundance of 17 isomeric lipids differing in the location of C[double bond, length as m-dash]C from 5 lipid precursors was determined. While cell-to-cell variations in MS1-based lipid profiling can be large, an advantage of quantifying lipid C[double bond, length as m-dash]C location isomers is the significantly improved quantitation accuracy. For example, the relative standard deviations (RSDs) of the relative amounts of PC 34:1 C[double bond, length as m-dash]C position isomers in MDA-MB-468 cells are half smaller than those measured for PC 34:1 as a whole by MS1 abundance profiling. Taken together, the developed method can be effectively used for in-depth structural lipid metabolism network analysis by high-throughput analysis of 142 MDA-MB-468 human breast cancer cells.

Concentric Hybrid Nanoelectrospray Ionization-Atmospheric Pressure Chemical Ionization Source for High-Coverage Mass Spectrometry Analysis of Single-Cell Metabolomics

High-coverage mass spectrometry analysis of single-cell metabolomics remains challenging due to the extremely low abundance and wide polarity of metabolites and ultra-small volume in single cells. Herein, a novel concentric hybrid ionization source, nanoelectrospray ionization-atmospheric pressure chemical ionization (nanoESI-APCI), is ingeniously designed to detect polar and nonpolar metabolites simultaneously in single cells. The source is constructed by inserting a pulled glass capillary coaxially into a glass tube that acts as a dielectric barrier layer. Benefitting from the integrated advantages of nanoESI and APCI, its limit of detection is improved by one order of magnitude to 10 pg mL-1. After the operational parameter optimization, 254 metabolites detected in nanoESI-APCI are tentatively identified from a single cell, and 82 more than those in nanoESI. The developed nanoESI-APCI is successively applied to study the metabolic heterogeneity of human hepatocellular carcinoma tissue microenvironment united with laser capture microdissection (LCM), the discrimination of cancer cell types and subtypes, the metabolic perturbations to glucose starvation in MCF7 cells and the metabolic regulation of cancer stem cells. These results demonstrated that the nanoESI-APCI not only opens a new avenue for high-coverage and high-sensitivity metabolomics analysis of single cell, but also facilitates spatially resolved metabolomics study coupled with LCM.

SingPro: a knowledge base providing single-cell proteomic data

Single-cell proteomics (SCP) has emerged as a powerful tool for detecting cellular heterogeneity, offering unprecedented insights into biological mechanisms that are masked in bulk cell populations. With the rapid advancements in AI-based time trajectory analysis and cell subpopulation identification, there exists a pressing need for a database that not only provides SCP raw data but also explicitly describes experimental details and protein expression profiles. However, no such database has been available yet. In this study, a database, entitled 'SingPro', specializing in single-cell proteomics was thus developed. It was unique in (a) systematically providing the SCP raw data for both mass spectrometry-based and flow cytometry-based studies and (b) explicitly describing experimental detail for SCP study and expression profile of any studied protein. Anticipating a robust interest from the research community, this database is poised to become an invaluable repository for OMICs-based biomedical studies. Access to SingPro is unrestricted and does not mandate a login at: http://idrblab.org/singpro/.

Bioanalytical strategies to evaluate cisplatin nanodelivery systems: From synthesis to incorporation in individual cells and biological response

Cisplatin metallodrugs have been widely used in the treatment of multiple cancers over the last years. Nevertheless, its limited effectiveness, development of acquired drug resistances, and toxic effects decrease nowadays their application in clinical settings. Aiming at improving their features, investigations have been oriented towards the coupling of cisplatin to nanocarriers, like liposomes or inorganic nanoparticles. Moreover, these systems can be further developed to allow targeted co-delivery of drugs. In this review, we describe the major nanosystems and the optimal analytical strategies for their assessment. Finally, we describe the main biological effects of these metallodrug conjugates and the available approaches for their study.

Single-cell metabolite profiling enables information-rich classification of lymphocyte types and subtypes

Lymphocytes play crucial roles in the human immune system; however, detailed metabolite characteristics need to be further investigated. Herein, we propose a lymphocyte classification method based on metabolite profiling at the single-cell level. The percentages of different lymphocyte types were calculated with a low margin of error, confirming that the metabolites could serve as a basis for lymphocyte classification. Furthermore, we analyzed the CD4/CD8 ratio in human peripheral blood to verify the feasibility of this method for the classification of lymphocyte subtypes. The proposed method is expected to be a potential tool for the clinical diagnosis of lymphocyte-related diseases.

Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.

Microfluidics Coupled Mass Spectrometry for Single Cell Multi-Omics

Population-level analysis masks significant heterogeneity between individual cells, making it difficult to accurately reflect the true intricacies of life activities. Microfluidics is a technique that can manipulate individual cells effectively and is commonly coupled with a variety of analytical methods for single-cell analysis. Single-cell omics provides abundant molecular information at the single-cell level, fundamentally revealing differences in cell types and biological states among cell individuals, leading to a deeper understanding of cellular phenotypes and life activities. Herein, this work summarizes the microfluidic chips designed for single-cell isolation, manipulation, trapping, screening, and sorting, including droplet microfluidic chips, microwell arrays, hydrodynamic microfluidic chips, and microchips with microvalves. This work further reviews the studies on single-cell proteomics, metabolomics, lipidomics, and multi-omics based on microfluidics and mass spectrometry. Finally, the challenges and future application of single-cell multi-omics are discussed.

Non-Invasive Detection of Biomolecular Abundance from Fermentative Microorganisms via Raman Spectra Combined with Target Extraction and Multimodel Fitting

Biomolecular abundance detection of fermentation microorganisms is significant for the accurate regulation of fermentation, which is conducive to reducing fermentation costs and improving the yield of target products. However, the development of an accurate analytical method for the detection of biomolecular abundance still faces important challenges. Herein, we present a non-invasive biomolecular abundance detection method based on Raman spectra combined with target extraction and multimodel fitting. The high gain of the eXtreme Gradient Boosting (XGBoost) algorithm was used to extract the characteristic Raman peaks of metabolically active proteins and nucleic acids within E. coli and yeast. The test accuracy for different culture times and cell cycles of E. coli was 94.4% and 98.2%, respectively. Simultaneously, the Gaussian multi-peak fitting algorithm was exploited to calculate peak intensity from mixed peaks, which can improve the accuracy of biomolecular abundance calculations. The accuracy of Gaussian multi-peak fitting was above 0.9, and the results of the analysis of variance (ANOVA) measurements for the lag phase, log phase, and stationary phase of E. coli growth demonstrated highly significant levels, indicating that the intracellular biomolecular abundance detection was consistent with the classical cell growth law. These results suggest the great potential of the combination of microbial intracellular abundance, Raman spectra analysis, target extraction, and multimodel fitting as a method for microbial fermentation engineering.

Quantification of Nitric Oxide in Single Cells Using the Single-Probe Mass Spectrometry Technique

Nitric oxide (NO) is a small molecule that plays important roles in biological systems and human diseases. The abundance of intracellular NO is tightly related to numerous biological processes. Due to cell heterogeneity, the intracellular NO amounts significantly vary from cell to cell, and therefore, any meaningful studies need to be conducted at the single-cell level. However, measuring NO in single cells is very challenging, primarily due to the extremely small size of single cells and reactive nature of NO. In the current studies, the quantitative reaction between NO and amlodipine, a compound containing the Hantzsch ester group, was performed in live cells. The product dehydro amlodipine was then detected by the Single-probe single-cell mass spectrometry technique to quantify NO in single cells. The experimental results indicated heterogeneous distributions of intracellular NO amounts in single cells with the existence of subpopulations.

Application and outlook of electrochemical technology in single-cell analysis

Cellular heterogeneity, especially in some important diseased cells like tumor cells, acts as an invisible driver for disease development like cancer progression in the tumor ecosystem, contributing to differences in the macroscopic and microscopic detection of disease lesions like tumors. Traditional analysis techniques choose group information masked by the mean as the analysis sample, making it difficult to achieve precise diagnosis and target treatment, on which could be shed light via the single-cell level determination/bioanalysis. Hence, in this article we have reviewed the special characteristic differences among various kinds of typical single-cell bioanalysis strategies and electrochemical techniques, and then focused on the recent advance and special bio-applications of electrochemiluminescence and micro-nano electrochemical sensing mediated in single-cell bioimaging & bioanalysis. Especially, we have summarized the relevant research exploration of the possibility to establish the in-situ single-cell electrochemical methods to detect cell heterogeneity through determination of specific biomolecules and bioimaging of some important biological processes. Eventually, this review has explored some important advances of electrochemical single-cell detection techniques for the real-time cellular bioimaging and diagnostics of some disease lesions like tumors. It raises the possibility to provide the specific in-situ platform to exploit the versatile, sensitive, and high-resolution electrochemical single-cell analysis for the promising biomedical applications like rapid tracing of some disease lesions or in vivo bioimaging for precise cancer theranostics.

Recent developments in ionization techniques for single-cell mass spectrometry

The variation among individual cells plays a significant role in many biological functions. Single-cell analysis is advantageous for gaining insight into intricate biochemical mechanisms rarely accessible when studying tissues as a whole. However, measurement on a unicellular scale is still challenging due to unicellular complex composition, minute substance quantities, and considerable differences in compound concentrations. Mass spectrometry has recently gained extensive attention in unicellular analytical fields due to its exceptional sensitivity, throughput, and compound identification abilities. At present, single-cell mass spectrometry primarily concentrates on the enhancement of ionization methods. The principal ionization approaches encompass nanoelectrospray ionization (nano-ESI), laser desorption ionization (LDI), secondary ion mass spectrometry (SIMS), and inductively coupled plasma (ICP). This article summarizes the most recent advancements in ionization techniques and explores their potential directions within the field of single-cell mass spectrometry.

High-Throughput f-LAESI-IMS-MS for Mapping Biological Nitrogen Fixation One Cell at a Time

For the characterization of the metabolic heterogeneity of cell populations, high-throughput single-cell analysis platforms are needed. In this study, we utilized mass spectrometry (MS) enhanced with ion mobility separation (IMS) and coupled with an automated sampling platform, fiber-based laser ablation electrospray ionization (f-LAESI), for in situ high-throughput single-cell metabolomics in soybean (Glycine max) root nodules. By fully automating the in situ sampling platform, an overall sampling rate of 804 cells/h was achieved for high numbers (>500) of tissue-embedded plant cells. This is an improvement by a factor of 13 compared to the previous f-LAESI-MS configuration. By introducing IMS, the molecular coverage improved, and structural isomers were separated on a millisecond time scale. The enhanced f-LAESI-IMS-MS platform produced 259 sample-related peaks/cell, almost twice as much as the 131 sample-related peaks/cell produced by f-LAESI-MS without IMS. Using the upgraded system, two types of metabolic heterogeneity characterization methods became possible. For unimodal metabolite abundance distributions, the metabolic noise reported on the metabolite level variations within the cell population. For bimodal distributions, the presence of metabolically distinct subpopulations was established. Discovering these latent cellular phenotypes could be linked to the presence of different cell states, e.g., proliferating bacteria in partially occupied plant cells and quiescent bacteroids in fully occupied cells in biological nitrogen fixation, or spatial heterogeneity due to altered local environments.

Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics

Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.

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

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

Prospects of single-cell nuclear magnetic resonance spectroscopy with quantum sensors

Single-cell analysis can unravel functional heterogeneity within cell populations otherwise obscured by ensemble measurements. However, noninvasive techniques that probe chemical entities and their dynamics are still lacking. This challenge could be overcome by novel sensors based on nitrogen-vacancy (NV) centers in diamond, which enable nuclear magnetic resonance (NMR) spectroscopy on unprecedented sample volumes. In this perspective, we briefly introduce NV-based quantum sensing and review the progress made in microscale NV-NMR spectroscopy. Last, we discuss approaches to enhance the sensitivity of NV ensemble magnetometers to detect biologically relevant concentrations and provide a roadmap toward their application in single-cell analysis.

Ultrafast Subcellular Biolabeling and Bioresponsive Real-Time Monitoring for Targeting Cancer Theranostics

Cell heterogeneity poses a formidable challenge for tumor theranostics, requiring high-resolution strategies for intercellular bioanalysis between single cells. Nanoelectrode-based electrochemical analysis has attracted much attention due to its advantages of label-free characteristics, relatively low cost, and ultra-high resolution for single-cell analysis. Here, we have designed and developed a subcellular biolabeling and bioresponsive real-time monitoring strategy for precise bioimaging-guided cancer diagnosis and theranostics. Our observations revealed the apparent intracellular migration of biosynthetic Au nanoclusters (Au NCs) at different subcellular locations, i.e., from the mitochondria to the mitochondrion-free region in the cytoplasm, which may be helpful for controlling over the biosynthesis of Au NCs. Considering the precise biolabeling advantage of the intracellular biosynthetic Au NCs for biomedical imaging of cancers, it is important to realize the biosynthetic Au NC-enabled precise control in real-time theranostics of cancer cells. Therefore, this work raises the possibility to achieve subcellular monitoring of H2O2 for targeting cancer theranostics, thereby providing a new way to explore the underlying mechanism and imaging-guided tumor theranostics.

Metabolomics: A useful tool for ischemic stroke research

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

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

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

Advancements in ToF-SIMS imaging for life sciences

In the last 2 decades, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) has gained significant prominence as a powerful imaging technique in the field of life sciences. This comprehensive review provides an in-depth overview of recent advancements in ToF-SIMS instrument technology and its applications in metabolomics, lipidomics, and single-cell analysis. We highlight the use of ToF-SIMS imaging for studying lipid distribution, composition, and interactions in cells and tissues, and discuss its application in metabolomics, including the analysis of metabolic pathways. Furthermore, we review recent progress in single-cell analysis using ToF-SIMS, focusing on sample preparation techniques, in situ investigation for subcellular distribution of drugs, and interactions between drug molecules and biological targets. The high spatial resolution and potential for multimodal analysis of ToF-SIMS make it a promising tool for unraveling the complex molecular landscape of biological systems. We also discuss future prospects and potential advancements of ToF-SIMS in the research of life sciences, with the expectation of a significant impact in the field.

Exploring Single-Cell Exposomics by Mass Spectrometry

Single-cell exposomics, a revolutionary approach that investigates cell-environment interactions at cellular and subcellular levels, stands distinct from conventional bulk exposomics. Leveraging advancements in mass spectrometry, it provides a detailed perspective on cellular dynamics, interactions, and responses to environmental stimuli and their impacts on human health. This work delves into this innovative realm, highlighting the nuanced interplay between environmental stressors and biological responses at cellular and subcellular levels. The application of spatial mass spectrometry in single-cell exposomics is discussed, revealing the intricate spatial organization and molecular composition within individual cells. Cell-type-specific exposomics, shedding light on distinct susceptibilities and adaptive strategies of various cell types to environmental exposures, is also examined. The Perspective further emphasizes the integration with molecular and cellular biology approaches to validate hypotheses derived from single-cell exposomics in a comprehensive biological context. Looking toward the future, we anticipate continued technological advancements and convergence with other -omics approaches and discuss implications for environmental health research, disease progression studies, and precision medicine. The final emphasis is on the need for robust computational tools and interdisciplinary collaboration to fully leverage the potential of single-cell exposomics, acknowledging the complexities inherent to this paradigm.

Rapid, One-Step Sample Processing for Label-Free Single-Cell Proteomics

Sample preparation for single-cell proteomics is generally performed in a one-pot workflow with multiple dispensing and incubation steps. These hours-long processes can be labor intensive and lead to long sample-to-answer times. Here we report a sample preparation method that achieves cell lysis, protein denaturation, and digestion in 1 h using commercially available high-temperature-stabilized proteases with a single reagent dispensing step. Four different one-step reagent compositions were evaluated, and the mixture providing the highest proteome coverage was compared to the previously employed multistep workflow. The one-step preparation increases proteome coverage relative to the previous multistep workflow while minimizing labor input and the possibility of human error. We also compared sample recovery between previously used microfabricated glass nanowell chips and injection-molded polypropylene chips and found the polypropylene provided improved proteome coverage. Combined, the one-step sample preparation and the polypropylene substrates enabled the identification of an average of nearly 2400 proteins per cell using a standard data-dependent workflow with Orbitrap mass spectrometers. These advances greatly simplify sample preparation for single-cell proteomics and broaden accessibility with no compromise in terms of proteome coverage.

Proteomics mining of cancer hallmarks on a single-cell resolution

Dysregulated proteome is an essential contributor in carcinogenesis. Protein fluctuations fuel the progression of malignant transformation, such as uncontrolled proliferation, metastasis, and chemo/radiotherapy resistance, which severely impair therapeutic effectiveness and cause disease recurrence and eventually mortality among cancer patients. Cellular heterogeneity is widely observed in cancer and numerous cell subtypes have been characterized that greatly influence cancer progression. Population-averaged research may not fully reveal the heterogeneity, leading to inaccurate conclusions. Thus, deep mining of the multiplex proteome at the single-cell resolution will provide new insights into cancer biology, to develop prognostic biomarkers and treatments. Considering the recent advances in single-cell proteomics, herein we review several novel technologies with particular focus on single-cell mass spectrometry analysis, and summarize their advantages and practical applications in the diagnosis and treatment for cancer. Technological development in single-cell proteomics will bring a paradigm shift in cancer detection, intervention, and therapy.

Chemical Decrosslinking-Based Peptide Characterization of Formaldehyde-Fixed Rat Pancreas Using Fluorescence-Guided Single-Cell Mass Spectrometry

Approaches for the characterization of proteins/peptides in single cells of formaldehyde-fixed (FF) tissues via mass spectrometry (MS) are still under development. The lack of a general method for selectively eliminating formaldehyde-induced crosslinking is a major challenge. A workflow is shown for the high-throughput peptide profiling of single cells isolated from FF tissues, here the rodent pancreas, which possesses multiple peptide hormones from the islets of Langerhans. The heat treatment is enhanced by a collagen-selective multistep thermal process assisting efficient isolation of islets from the FF pancreas and, subsequently, their dissociation into single islet cells. Hydroxylamine-based chemical decrosslinking helped restore intact peptide signals from individual isolated cells. Subsequently, an acetone/glycerol-assisted cell dispersion was optimized for spatially resolved cell deposition onto glass slides, while a glycerol solution maintained the hydrated state of the cells. This sample preparation procedure allowed peptide profiling in FF single cells by fluorescence-guided matrix-assisted laser desorption ionization MS. Here, 2594 single islet cells were analyzed and 28 peptides were detected, including insulin C-peptides and glucagon. T-distributed stochastic neighbor embedding (t-SNE) data visualization demonstrated that cells cluster based on cell-specific pancreatic peptide hormones. This workflow expands the sample availability for single-cell MS characterization to a wide range of formaldehyde-treated tissue specimens stored in biobanks.

Pocket-Size Wireless Nanoelectrospray Ionization Mass Spectrometry for Metabolic Analysis of Salty Biofluids and Single Cells

Analysis of volume-limited biological samples such as single cells and biofluids not only benefits clinical purposes but also promotes fundamental research in life sciences. Detection of these samples, however, imposes strict requirements on measurement performance because of the minimal volume and concentrated salts of the samples. Herein, we developed a self-cleaning nanoelectrospray ionization device powered by a pocket-size "MasSpec Pointer" (MSP-nanoESI) for metabolic analysis of salty biological samples with limited volume. The self-cleaning effect induced by Maxwell-Wagner electric stress helps with keeping the borosilicate glass capillary tip free from clogging and thus increasing salt tolerance. This device possesses a high sample economy (about 0.1 μL per test) due to its pulsed high voltage supply, sampling method (dipping the nanoESI tip into analyte solution), and contact-free electrospray ionization (ESI) (the electrode does not touch the analyte solution during ESI). High repeatable results could be acquired by the device with a relative standard deviation (RSD) of 1.02% for voltage output and 12.94% for MS signals of caffeine standard. Single MCF-7 cells were metabolically analyzed directly from phosphate buffered saline, and two types of untreated cerebrospinal fluid from hydrocephalus patients were distinguished with 84% accuracy. MSP-nanoESI gets rid of the bulky apparatus and could be held in hand or put into one's pocket for transportation, and it could operate for more than 4 h without recharge. We believe this device will boost scientific research and clinical usage of volume-limited biological samples with high-concentration salts in a low-cost, convenient, and rapid manner.

Managing the Heterogeneity of Mesenchymal Stem Cells for Cartilage Regenerative Therapy: A Review

Articular cartilage defects commonly result from trauma and are associated with significant morbidity. Since cartilage is an avascular, aneural, and alymphatic tissue with a poor intrinsic healing ability, the regeneration of functional hyaline cartilage remains a difficult clinical problem. Mesenchymal stem cells (MSCs) are multipotent cells with multilineage differentiation potential, including the ability to differentiate into chondrocytes. Due to their availability and ease of ex vivo expansion, clinicians are increasingly applying MSCs in the treatment of cartilage lesions. However, despite encouraging pre-clinical and clinical data, inconsistencies in MSC proliferative and chondrogenic potential depending on donor, tissue source, cell subset, culture conditions, and handling techniques remain a key barrier to widespread clinical application of MSC therapy in cartilage regeneration. In this review, we highlight the strategies to manage the heterogeneity of MSCs ex vivo for more effective cartilage repair, including reducing the MSC culture expansion period, and selecting MSCs with higher chondrogenic potential through specific genetic markers, surface markers, and biophysical attributes. The accomplishment of a less heterogeneous population of culture-expanded MSCs may improve the scalability, reproducibility, and standardisation of MSC therapy for clinical application in cartilage regeneration.

Using mass spectrometry imaging to visualize age-related subcellular disruption

Metabolic homeostasis balances the production and consumption of energetic molecules to maintain active, healthy cells. Cellular stress, which disrupts metabolism and leads to the loss of cellular homeostasis, is important in age-related diseases. We focus here on the role of organelle dysfunction in age-related diseases, including the roles of energy deficiencies, mitochondrial dysfunction, endoplasmic reticulum (ER) stress, changes in metabolic flux in aging (e.g., Ca2+ and nicotinamide adenine dinucleotide), and alterations in the endoplasmic reticulum-mitochondria contact sites that regulate the trafficking of metabolites. Tools for single-cell resolution of metabolite pools and metabolic flux in animal models of aging and age-related diseases are urgently needed. High-resolution mass spectrometry imaging (MSI) provides a revolutionary approach for capturing the metabolic states of individual cells and cellular interactions without the dissociation of tissues. mass spectrometry imaging can be a powerful tool to elucidate the role of stress-induced cellular dysfunction in aging.

Advances in Mass Spectrometry-Based Single Cell Analysis

Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine.

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.

Applying multi-omics toward tumor microbiome research

Rather than a "short-term tenant," the tumor microbiome has been shown to play a vital role as a "permanent resident," affecting carcinogenesis, cancer development, metastasis, and cancer therapies. As the tumor microbiome has great potential to become a target for the early diagnosis and treatment of cancer, recent research on the relevance of the tumor microbiota has attracted a wide range of attention from various scientific fields, resulting in remarkable progress that benefits from the development of interdisciplinary technologies. However, there are still a great variety of challenges in this emerging area, such as the low biomass of intratumoral bacteria and unculturable character of some microbial species. Due to the complexity of tumor microbiome research (e.g., the heterogeneity of tumor microenvironment), new methods with high spatial and temporal resolution are urgently needed. Among these developing methods, multi-omics technologies (combinations of genomics, transcriptomics, proteomics, and metabolomics) are powerful approaches that can facilitate the understanding of the tumor microbiome on different levels of the central dogma. Therefore, multi-omics (especially single-cell omics) will make enormous impacts on the future studies of the interplay between microbes and tumor microenvironment. In this review, we have systematically summarized the advances in multi-omics and their existing and potential applications in tumor microbiome research, thus providing an omics toolbox for investigators to reference in the future.

Single-cell omics: A new direction for functional genetic research in human diseases and animal models

Over the past decade, with the development of high-throughput single-cell sequencing technology, single-cell omics has been emerged as a powerful tool to understand the molecular basis of cellular mechanisms and refine our knowledge of diverse cell states. They can reveal the heterogeneity at different genetic layers and elucidate their associations by multiple omics analysis, providing a more comprehensive genetic map of biological regulatory networks. In the post-GWAS era, the molecular biological mechanisms influencing human diseases will be further elucidated by single-cell omics. This review mainly summarizes the development and trend of single-cell omics. This involves single-cell omics technologies, single-cell multi-omics technologies, multiple omics data integration methods, applications in various human organs and diseases, classic laboratory cell lines, and animal disease models. The review will reveal some perspectives for elucidating human diseases and constructing animal models.

Microfluidic device integrating single-cell extraction and electrical lysis for mass spectrometry detection of intracellular compounds

Analysis of cellular composition and metabolism at a single-cell resolution allows gaining more information about complex relationships of cells within tissues or whole living organisms by resolving the variance stemming from the cellular heterogeneity. Mass spectrometry (MS) is a perfect analytical tool satisfying the demanding requirements of detecting and identifying compounds present in such ultralow-volume samples of high chemical complexity. However, the method of sampling and sample ionization is crucial in obtaining relevant information. In this work, we present a microfluidic sampling platform that integrates single-cell extraction from MS-incompatible media with electrical cell lysis and nanoESI-MS analysis of human erythrocytes. Hemoglobin alpha and beta chains (300 amol/cell) were successfully identified in mass spectra of single-erythrocyte lysates.

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.

Monitoring and modelling the dynamics of the cellular glycolysis pathway: A review and future perspectives

BACKGROUND

The dynamics of the cellular glycolysis pathway underpin cellular function and dysfunction, and therefore ultimately health, disease, diagnostic and therapeutic strategies. Evolving our understanding of this fundamental process and its dynamics remains critical.

SCOPE OF REVIEW

This paper reviews the medical relevance of glycolytic pathway in depth and explores the current state of the art for monitoring and modelling the dynamics of the process. The future perspectives of label free, vibrational microspectroscopic techniques to overcome the limitations of the current approaches are considered.

MAJOR CONCLUSIONS

Vibrational microspectroscopic techniques can potentially operate in the niche area of limitations of other omics technologies for non-destructive, real-time, in vivo label-free monitoring of glycolysis dynamics at a cellular and subcellular level.

Single-cell mass spectrometry

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

Heterogeneity of triple negative breast cancer: Current advances in subtyping and treatment implications

As the field of translational ‘omics has progressed, refined classifiers at both genomic and proteomic levels have emerged to decipher the heterogeneity of breast cancer in a clinically-applicable way. The integration of ‘omics knowledge at the DNA, RNA and protein levels is further expanding biologic understanding of breast cancer and opportunities for customized treatment, a particularly pressing need in clinically triple negative tumors. For this group of aggressive breast cancers, work from multiple groups has now validated at least four major biologically and clinically distinct omics-based subtypes. While to date most clinical trial designs have considered triple negative breast cancers as a single group, with an expanding arsenal of targeted therapies applicable to distinct biological pathways, survival benefits may be best realized by designing and analyzing clinical trials in the context of major molecular subtypes. While RNA-based classifiers are the most developed, proteomic classifiers proposed for triple negative breast cancer based on new technologies have the potential to more directly identify the most clinically-relevant biomarkers and therapeutic targets. Phospho-proteomic data further identify targetable signalling pathways in a unique subtype-specific manner. Single cell profiling of the tumor microenvironment represents a promising way to allow a better characterization of the heterogeneity of triple negative breast cancer which could be integrated in a spatially resolved context to build an ecosystem-based patient classification. Multi-omic data further allows in silico analysis of genetic and pharmacologic screens to map therapeutic vulnerabilities in a subtype-specific context. This review describes current knowledge about molecular subtyping of triple negative breast cancer, recent advances in omics-based genomics and proteomics diagnostics addressing the diversity of this disease, key advances made through single cell analysis approaches, and developments in treatments including targeted therapeutics being tested in major clinical trials.

Investigation on the binary ionization choices for large conjugated amines during electrospray ionization

RATIONALE

Generally, amines form protonated cations ([M + H]⁺ ) in positive polarity during electrospray ionization (ESI). However, it was found that large conjugated amines (LCAs) had binary ionization choices of generating either radical cations (M^•+ ) or [M + H]⁺ during ESI. Investigation on the mechanism would further our understanding of ESI.

METHODS

In this work, the binary ionization behavior of LCAs was reported and studied. Internal factors (functional groups and sizes of conjugated systems) and external factors (solvent type, flow rate, and electrode position) were systematically investigated and discussed.

RESULTS

For the internal factors, electron-donating groups and large conjugated structures of LCAs were conducive to the generation of M^•+ . For the external factors, aprotic solvent, higher flow rate, and shorter distance from the electrode to the spray cone facilitated the formation of M^•+ but hampered the generation of [M + H]⁺ .

CONCLUSION

The present study illustrated that the formations of M^•+ and [M + H]⁺ for LCAs were two independent processes. The M^•+ cations of LCAs were formed on the surface of the electrode through electrochemical oxidation, whereas the [M + H]⁺ cations were generated following the typical ESI evolution process. By regulating the external factors, the ionization results of LCAs could be well modulated.

Single-Cell Mass Spectrometry of Metabolites and Proteins for Systems and Functional Biology

Molecular composition is intricately intertwined with cellular function, and elucidation of this relationship is essential for understanding life processes and developing next-generational therapeutics. Technological innovations in capillary electrophoresis (CE) and liquid chromatography (LC) mass spectrometry (MS) provide previously unavailable insights into cellular biochemistry by allowing for the unbiased detection and quantification of molecules with high specificity. This chapter presents our validated protocols integrating ultrasensitive MS with classical tools of cell, developmental, and neurobiology to assess the biological function of important biomolecules. We use CE and LC MS to measure hundreds of metabolites and thousands of proteins in single cells or limited populations of tissues in chordate embryos and mammalian neurons, revealing molecular heterogeneity between identified cells. By pairing microinjection and optical microscopy, we demonstrate cell lineage tracing and testing the roles the dysregulated molecules play in the formation and maintenance of cell heterogeneity and tissue specification in frog embryos (Xenopus laevis). Electrophysiology extends our workflows to characterizing neuronal activity in sections of mammalian brain tissues. The information obtained from these studies mutually strengthen chemistry and biology and highlight the importance of interdisciplinary research to advance basic knowledge and translational applications forward.

Study on Ammonia Content and Distribution in the Microenvironment Based on Covalent Organic Framework Nanochannels

A crack-free micrometer-sized compact structure of 1,3,5-tris(4-aminophenyl)benzene-terephthaldehyde-covalent organic frameworks (TAPB-PDA-COFs) was constructed in situ at the tip of a theta micropipette (TMP). The COF-covered theta micropipette (CTP) then created a stable liquid-gas interface inside COF nanochannels, which was utilized to electrochemically analyze the content and distribution of ammonia gas in the microenvironments. The TMP-based electrochemical ammonia sensor (TEAS) shows a high sensing response, with current increasing linearly from 0 to 50,000 ppm ammonia, owing to the absorption of ammonia gas in the solvent meniscus that connects both barrels of the TEAS. The TEAS also exhibits a short response and recovery time of 5 ± 2 s and 6 ± 2 s, respectively. This response of the ammonia sensor is remarkably stable and repeatable, with a relative standard deviation of 6% for 500 ppm ammonia gas dispensing with humidity control. Due to its fast, reproducible, and stable response to ammonia gas, the TEAS was also utilized as a scanning electrochemical microscopy (SECM) probe for imaging the distribution of ammonia gas in a microspace. This study unlocks new possibilities for using a TMP in designing microscale probes for gas sensing and imaging.

Recent Advances in Single Cell Analysis by Electrochemiluminescence

Understanding biological mechanisms operating in cells is one of the major goals of biology. Since heterogeneity is the fundamental property of cellular systems, single cell measurements can provide more accurate information about the composition, dynamics, and regulatory circuits of cells than population-averaged assays. Electrochemiluminescence (ECL), the light emission triggered by electrochemical reactions, is an emerging approach for single cell analysis. Numerous analytes, ranging from small biomolecules such as glucose and cholesterol, proteins and nucleic acids to subcellular structures, have been determined in single cells by ECL, which yields new insights into cellular functions. This review aims to provide an overview of research progress on ECL principles and systems for single cell analysis in recent years. The ECL reaction mechanisms are briefly introduced, and then the advances and representative works in ECL single cell analysis are summarized. Finally, outlooks and challenges in this field are addressed.

Mass spectrometry imaging to explore molecular heterogeneity in cell culture

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

Single-cell quantitative proteomic analysis of human oocyte maturation revealed high heterogeneity in in vitro matured oocytes

Oocyte maturation is pertinent to the success of in vitro maturation (IVM), which is used to overcome female infertility, and produced over 5000 live births worldwide. However, the quality of human IVM oocytes has not been investigated at single-cell proteome level. Here, we quantified 2094 proteins in human oocytes during in vitro and in vivo maturation (IVO) by single-cell proteomic analysis and identified 176 differential proteins between IVO and germinal vesicle oocytes and 45 between IVM and IVO oocytes including maternal effect proteins, with potential contribution to the clinically observed decreased fertilization, implantation, and birth rates using human IVM oocytes. IVM and IVO oocytes showed separate clusters in principal component analysis, with higher inter-cell variability among IVM oocytes, and have little correlation between mRNA and protein changes during maturation. The patients with the most aberrantly expressed proteins in IVM oocytes had the lowest level of estradiol per mature follicle on trigger day. Our data provide a rich resource to evaluate effect of IVM on oocyte quality and study mechanism of oocyte maturation.

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Single-cell proteomic profiling of human oocytes matured in vitro and in vivo.

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Low correlation between protein and mRNA levels during human oocyte maturation.

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In vitro matured (IVM) oocytes exhibit higher heterogeneity at the proteome level.

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45 differentially expressed proteins between IVM and in vivo matured (IVO) oocytes.

Microanalysis of Brain Angiotensin Peptides Using Ultrasensitive Capillary Electrophoresis Trapped Ion Mobility Mass Spectrometry

While the role of the renin-angiotensin system (RAS) in peripheral circulation is well characterized, we still lack an in-depth understanding of its role within the brain. This knowledge gap is sustained by lacking technologies for trace-level angiotensin detection throughout tissues, such as the brain. To provide a bridging solution, we enhanced capillary electrophoresis (CE) nanoflow electrospray ionization (ESI) with large-volume sample stacking and employed trapped ion mobility time-of-flight (timsTOF) tandem HRMS detection. A dynamic pH junction helped stack approximately 10 times more of the sample than optimal using the field-amplified reference. In conjunction, the efficiency of ion generation was maximized by a cone-jet nanospray on a low sheath-flow tapered-tip nano-electrospray emitter. The platform provided additional peptide-dependent information, the collision cross section, to filter chemical noise and improve sequence identification and detection limits. The lower limit of detection reached sub-picomolar or ∼30 zmol (∼18,000 copies) level. All nine targeted angiotensin peptides in mouse tissue samples were detectable and quantifiable from the paraventricular nucleus (PVN) of the hypothalamus even after removal of circulatory blood components (perfusion). We anticipate CE-ESI with timsTOF HRMS to be broadly applicable for the ultrasensitive detection of brain peptidomes in pursuit of a better understanding of the brain.

Capillary microsampling-based single-cell metabolomics by mass spectrometry and its applications in medicine and drug discovery

Characterization of cellular metabolic states is a technical challenge in biomedicine. Cellular heterogeneity caused by inherent diversity in expression of metabolic enzymes or due to sensitivity of metabolic reactions to perturbations, necessitates single cell analysis of metabolism. Heterogeneity is typically seen in cancer and thus, single-cell metabolomics is expectedly useful in studying cancer progression, metastasis, and variations in cancer drug response. However, low sample volumes and analyte concentrations limit detection of critically important metabolites. Capillary microsampling-based mass spectrometry approaches are emerging as a promising solution for achieving single-cell omics. Herein, we focus on the recent advances in capillary microsampling-based mass spectrometry techniques for single-cell metabolomics. We discuss recent technical developments and applications to cancer medicine and drug discovery.