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

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

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

Data-Independent Acquisition Shortens the Analytical Window of Single-Cell Proteomics to Fifteen Minutes in Capillary Electrophoresis Mass Spectrometry

Separation in single-cell mass spectrometry (MS) improves molecular coverage and quantification; however, it also elongates measurements, thus limiting analytical throughput to study large populations of cells. Here, we advance the speed of bottom-up proteomics by capillary electrophoresis (CE) high-resolution mass spectrometry (MS) for single-cell proteomics. We adjust the applied electrophoresis potential to readily control the duration of electrophoresis. On the HeLa proteome standard, shorter separation times curbed proteome detection using data-dependent acquisition (DDA) but not data-independent acquisition (DIA) on an Orbitrap analyzer. This DIA method identified 1161 proteins vs 401 proteins by the reference DDA within a 15 min effective separation from single HeLa-cell-equivalent (∼200 pg) proteome digests. Label-free quantification found these exclusively DIA-identified proteins in the lower domain of the concentration range, revealing sensitivity improvement. The approach also significantly advanced the reproducibility of quantification, where ∼76% of the DIA-quantified proteins had <20% coefficient of variation vs ∼43% by DDA. As a proof of principle, the method allowed us to quantify 1242 proteins in subcellular niches in a single, neural-tissue fated cell in the live Xenopus laevis (frog) embryo, including many canonical components of organelles. DIA integration enhanced throughput by ∼2-4 fold and sensitivity by a factor of ∼3 in single-cell (subcellular) CE-MS proteomics.

A critical evaluation of ultrasensitive single-cell proteomics strategies

Success of mass spectrometry characterization of the proteome of single cells allows us to gain a greater understanding than afforded by transcriptomics alone but requires clear understanding of the tradeoffs between analytical throughput and precision. Recent advances in mass spectrometry acquisition techniques, including updated instrumentation and sample preparation, have improved the quality of peptide signals obtained from single cell data. However, much of the proteome remains uncharacterized, and higher throughput techniques often come at the expense of reduced sensitivity and coverage, which diminish the ability to measure proteoform heterogeneity, including splice variants and post-translational modifications, in single cell data analysis. Here, we assess the growing body of ultrasensitive single-cell approaches and their tradeoffs as researchers try to balance throughput and precision in their experiments.

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.

An automated spray-capillary platform for the microsampling and CE-MS analysis of picoliter- and nanoliter-volume samples

Capillary electrophoresis mass spectrometry (CE-MS) is an emerging analytical tool for microscale biological sample analysis that offers high separation resolution, low detection limit, and low sample consumption. We recently developed a novel microsampling device, "spray-capillary," for quantitative low-volume sample extraction (as low as 15 pL/s) and online CE-MS analysis. This platform can efficiently analyze picoliter samples (e.g., single cells) with minimal sample loss and no additional offline sample-handling steps. However, our original spray-capillary-based experiments required manual manipulation of the sample inlet for sample collection and separation, which is time consuming and requires proficiency in device handling. To optimize the performance of spray-capillary CE-MS analysis, we developed an automated platform for robust, high-throughput analysis of picoliter samples using a commercially available CE autosampler. Our results demonstrated high reproducibility among 50 continuous runs using the standard peptide angiotensin II (Ang II), with an RSD of 14.70% and 0.62% with respect to intensity and elution time, respectively. We also analyzed Ang II using varying injection times to evaluate the capability of the spray-capillary to perform quantitative sampling and found high linearity for peptide intensity with respect to injection time (R2 > 0.99). These results demonstrate the capability of the spray-capillary sampling platform for high-throughput quantitative analysis of low-volume, low-complexity samples using pressure elution (e.g., direct injection). To further evaluate and optimize the automated spray-capillary platform to analyze complex biological samples, we performed online CE-MS analysis on Escherichia coli lysate digest spiked with Ang II using varying injection times. We maintained high linearity of intensity with respect to injection time for Ang II and E. coli peptides (R2 > 0.97 in all cases). Furthermore, we observed good CE separation and high reproducibility between automated runs. Overall, we demonstrated that the automated spray-capillary CE-MS platform can efficiently and reproducibly sample picoliter and nanoliter biological samples for high-throughput proteomics analysis.

Analysis of naphthenic acids in produced water samples by capillary electrophoresis-mass spectrometry

A capillary electrophoresis-mass spectrometry method was used to analyze naphthenic acids in produced water samples. It was possible to detect cyclopentanecarboxylic, benzoic, cyclohexanebutyric, 1-naphthoic, decanoic, 3,5-dimethyladamantane-1-carboxylic, 9-anthracenecarboxylic, and pentadecanoic acids within ca. 13 min using a buffer composed of 40 mmol/L ammonium hydroxide, 32 mmol/L acetic acid and 20% v/v isopropyl alcohol, pH 8.6. The proposed method showed good repeatability, with relative standard deviation (RSD) values of 6.6% for the sum of the peak areas and less than 2% for the analysis time. In the interday analysis, the RSD values for the sum of the peak areas and migration time were 10.3% and 10%, respectively. The developed method demonstrated linear behavior in the concentration range between 5 and 50 mg/L for benzoic, decanoic, 3,5-dimethyladamantane-1-carboxylic and 9-anthracenecarboxylic acids, and between 10 and 50 mg/L for cyclopentanecarboxylic, cyclohexanebutyric, 1- naphthoic, and pentadecanoic acids. The detection limits values ranged from 0.31 to 1.64 mg/L. Six produced water samples were analyzed and it was possible to identify and quantify cyclopentanecarboxylic, benzoic, cyclohexanebutyric, and decanoic acids. The concentrations varied between 4.8 and 98.9 mg/L, proving effective in the application of complex samples.

Application of single-cell multi-omics approaches in horticulture research

Cell heterogeneity shapes the morphology and function of various tissues and organs in multicellular organisms. Elucidation of the differences among cells and the mechanism of intercellular regulation is essential for an in-depth understanding of the developmental process. In recent years, the rapid development of high-throughput single-cell transcriptome sequencing technologies has influenced the study of plant developmental biology. Additionally, the accuracy and sensitivity of tools used to study the epigenome and metabolome have significantly increased, thus enabling multi-omics analysis at single-cell resolution. Here, we summarize the currently available single-cell multi-omics approaches and their recent applications in plant research, review the single-cell based studies in fruit, vegetable, and ornamental crops, and discuss the potential of such approaches in future horticulture research.

Single-cell omic molecular profiling using capillary electrophoresis-mass spectrometry

Tissues and other cell populations are highly heterogeneous at the cellular level, owing to differences in expression and modifications of proteins, polynucleotides, metabolites, and lipids. The ability to assess this heterogeneity is crucial in understanding numerous biological phenomena, including various pathologies. Traditional analyses apply bulk-cell sampling, which masks the potentially subtle differences between cells that can be important in understanding of biological processes. These limitations due to cell heterogeneity inspired significant efforts and interest toward the analysis of smaller sample sizes, down to the level of individual cells. Among the emerging techniques, the unique capabilities of capillary electrophoresis coupled with mass spectrometry (CE-MS) made it a prominent technique for proteomics and metabolomics analysis at the single-cell level. In this review, we focus on the application of CE-MS in the proteomic and metabolomic profiling of single cells and highlight the recent advances in sample preparation, separation, MS acquisition, and data analysis.

Discovery of Oogenesis Biomarkers from Mouse Oocytes Using a Single-Cell Proteomics Approach

We established an efficient and simplified single-cell proteomics (ES-SCP) workflow to realize proteomics profiling at the single-oocyte level. With the ES-SCP workflow, we constructed a deep coverage proteome library during oocyte maturation, which contained more than 6000 protein groups, and identified and quantified more than 4000 protein groups from a pool of only 15 oocytes at germinal vesicle (GV), GV breakdown (GVBD), and metaphase II (MII) stages. More than 1500 protein groups can be identified from single oocytes. We found that marker proteins including maternal factors and mRNA regulators, such as ZAR1, TLE6, and BTG4, showed significant variations in abundance during oocyte maturation, and it was discovered that maternal mRNA degradation was indispensable during oocyte maturation. Proteomics analysis from single oocytes revealed that changes in antioxidant factors, maternal factors, mRNA stabilization, and energy metabolism were the factors that affect the oocyte quality during ovary aging. Our data laid the foundation for future innovations in assisted reproduction.

Recent advances in proteomics and metabolomics in plants

Over the past decade, systems biology and plant-omics have increasingly become the main stream in plant biology research. New developments in mass spectrometry and bioinformatics tools, and methodological schema to integrate multi-omics data have leveraged recent advances in proteomics and metabolomics. These progresses are driving a rapid evolution in the field of plant research, greatly facilitating our understanding of the mechanistic aspects of plant metabolisms and the interactions of plants with their external environment. Here, we review the recent progresses in MS-based proteomics and metabolomics tools and workflows with a special focus on their applications to plant biology research using several case studies related to mechanistic understanding of stress response, gene/protein function characterization, metabolic and signaling pathways exploration, and natural product discovery. We also present a projection concerning future perspectives in MS-based proteomics and metabolomics development including their applications to and challenges for system biology. This review is intended to provide readers with an overview of how advanced MS technology, and integrated application of proteomics and metabolomics can be used to advance plant system biology research.

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.

Mass Spectrometry Measurements of Neuropeptides: From Identification to Quantitation

Neuropeptides (NPs), a unique class of neuronal signaling molecules, participate in a variety of physiological processes and diseases. Quantitative measurements of NPs provide valuable information regarding how these molecules are differentially regulated in a multitude of neurological, metabolic, and mental disorders. Mass spectrometry (MS) has evolved to become a powerful technique for measuring trace levels of NPs in complex biological tissues and individual cells using both targeted and exploratory approaches. There are inherent challenges to measuring NPs, including their wide endogenous concentration range, transport and postmortem degradation, complex sample matrices, and statistical processing of MS data required for accurate NP quantitation. This review highlights techniques developed to address these challenges and presents an overview of quantitative MS-based measurement approaches for NPs, including the incorporation of separation methods for high-throughput analysis, MS imaging for spatial measurements, and methods for NP quantitation in single neurons.

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing (Frog) Embryo

Characterization of molecular events as cells give rise to tissues and organs raises a potential to better understand normal development and design efficient remedies for diseases. Technologies enabling accurate identification and quantification of diverse types and large numbers of proteins would provide still missing information on molecular mechanisms orchestrating tissue and organism development in space and time. Here, we present a mass spectrometry-based protocol that enables the measurement of thousands of proteins in identified cell lineages in Xenopus laevis (frog) embryos. The approach builds on reproducible cell-fate maps and established methods to identify, fluorescently label, track, and sample cells and their progeny (clones) from this model of vertebrate development. After collecting cellular contents using microsampling or isolating cells by dissection or fluorescence-activated cell sorting, proteins are extracted and processed for bottom-up proteomic analysis. Liquid chromatography and capillary electrophoresis are used to provide scalable separation for protein detection and quantification with high-resolution mass spectrometry (HRMS). Representative examples are provided for the proteomic characterization of neural-tissue fated cells. Cell-lineage-guided HRMS proteomics is adaptable to different tissues and organisms. It is sufficiently sensitive, specific, and quantitative to peer into the spatio-temporal dynamics of the proteome during vertebrate development.

Capillary Electrophoresis Mass Spectrometry for Scalable Single-Cell Proteomics

Understanding the biochemistry of the cell requires measurement of all the molecules it produces. Single-cell proteomics recently became possible through advances in microanalytical sample preparation, separation by nano-flow liquid chromatography (nanoLC) and capillary electrophoresis (CE), and detection using electrospray ionization (ESI) high-resolution mass spectrometry (HRMS). Here, we demonstrate capillary microsampling CE-ESI-HRMS to be scalable to proteomics across broad cellular dimensions. This study established proof-of-principle using giant, ∼250-µm-diameter cells from embryos of the frog Xenopus laevis and small, ∼35-µm-diameter neurons in culture from the mouse hippocampus. From ∼18 ng, or ∼0.2% of the total cellular proteome, subcellular analysis of the ventral-animal midline (V11) and equatorial (V12) cells identified 1,133 different proteins in a 16-cell embryo. CE-HRMS achieved ∼20-times higher sensitivity and doubled the speed of instrumental measurements compared to nanoLC, the closest neighboring single-cell technology of choice. Microanalysis was scalable to 722 proteins groups from ∼5 ng of cellular protein digest from identified left dorsal-animal midline cell (D11), supporting sensitivity for smaller cells. Capillary microsampling enabled the isolation and transfer of individual neurons from the culture, identifying 37 proteins between three different cells. A total of 224 proteins were detected from 500 pg of neuronal protein digest, which estimates to a single neuron. Serial dilution returned 157 proteins from sample amounts estimating to about half a cell (250 pg protein) and 70 proteins from ca. a quarter of a neuron (125 pg protein), suggesting sufficient sensitivity for subcellular proteomics. CE-ESI-HRMS complements nanoLC proteomics with scalability, sensitivity, and speed across broad cellular dimensions.

Multi-Omics Prognostic Signatures Based on Lipid Metabolism for Colorectal Cancer

Background: The potential biological processes and laws of the biological components in malignant tumors can be understood more systematically and comprehensively through multi-omics analysis. This study elaborately explored the role of lipid metabolism in the prognosis of colorectal cancer (CRC) from the metabonomics and transcriptomics.

Methods: We performed K-means unsupervised clustering algorithm and t test to identify the differential lipid metabolites determined by liquid chromatography tandem mass spectrometry (LC-MS/MS) in the serum of 236 CRC patients of the First Hospital of Jilin University (JLUFH). Cox regression analysis was used to identify prognosis-associated lipid metabolites and to construct multi-lipid-metabolite prognostic signature. The composite nomogram composed of independent prognostic factors was utilized to individually predict the outcome of CRC patients. Glycerophospholipid metabolism was the most significant enrichment pathway for lipid metabolites in CRC, whose related hub genes (GMRHGs) were distinguished by gene set variation analysis (GSVA) and weighted gene co-expression network analysis (WGCNA). Cox regression and least absolute shrinkage and selection operator (LASSO) regression analysis were utilized to develop the prognostic signature.

Results: Six-lipid-metabolite and five-GMRHG prognostic signatures were developed, indicating favorable survival stratification effects on CRC patients. Using the independent prognostic factors as variables, we established a composite nomogram to individually evaluate the prognosis of CRC patients. The AUCs of one-, three-, and five-year ROC curves were 0.815, 0.815, and 0.805, respectively, showing auspicious prognostic accuracy. Furthermore, we explored the potential relationship between tumor microenvironment (TME) and immune infiltration. Moreover, the mutational frequency of TP53 in the high-risk group was significantly higher than that in the low-risk group (p < 0.001), while in the coordinate mutational status of TP53, the overall survival of CRC patients in the high-risk group was significantly lower than that in low-risk group with statistical differences.

Conclusion: We identified the significance of lipid metabolism for the prognosis of CRC from the aspects of metabonomics and transcriptomics, which can provide a novel perspective for promoting individualized treatment and revealing the potential molecular biological characteristics of CRC. The composite nomogram including a six-lipid-metabolite prognostic signature is a promising predictor of the prognosis of CRC patients.

Patch-Clamp Proteomics of Single Neurons in Tissue Using Electrophysiology and Subcellular Capillary Electrophoresis Mass Spectrometry

Understanding of the relationship between cellular function and molecular composition holds a key to next-generation therapeutics but requires measurement of all types of molecules in cells. Developments in sequencing enabled semiroutine measurement of single-cell genomes and transcriptomes, but analytical tools are scarce for detecting diverse proteins in tissue-embedded cells. To bridge this gap for neuroscience research, we report the integration of patch-clamp electrophysiology with subcellular shot-gun proteomics by high-resolution mass spectrometry (HRMS). Recording of electrical activity permitted identification of dopaminergic neurons in the substantia nigra pars compacta. Ca. 20-50% of the neuronal soma content, containing an estimated 100 pg of total protein, was aspirated into the patch pipette filled with ammonium bicarbonate. About 1 pg of somal protein, or ∼0.25% of the total cellular proteome, was analyzed on a custom-built capillary electrophoresis (CE) electrospray ionization platform using orbitrap HRMS for detection. A series of experiments were conducted to systematically enhance detection sensitivity through refinements in sample processing and detection, allowing us to quantify ∼275 different proteins from somal aspirate-equivalent protein digests from cultured neurons. From single neurons, patch-clamp proteomics of the soma quantified 91, 80, and 95 different proteins from three different dopaminergic neurons or 157 proteins in total. Quantification revealed detectable proteomic differences between the somal protein samples. Analysis of canonical knowledge predicted rich interaction networks between the observed proteins. The integration of patch-clamp electrophysiology with subcellular CE-HRMS proteomics expands the analytical toolbox of neuroscience.

Recent developments in capillary and microchip electroseparations of peptides (2019-mid 2021)

The review provides a comprehensive overview of developments and applications of high performance capillary and microchip electroseparation methods (zone electrophoresis, isotachophoresis, isoelectric focusing, affinity electrophoresis, electrokinetic chromatography, and electrochromatography) for analysis, microscale isolation, and physicochemical characterization of peptides from 2019 up to approximately the middle of 2021. Advances in the investigation of electromigration properties of peptides and in the methodology of their analysis, such as sample preparation, sorption suppression, EOF control, and detection, are presented. New developments in the individual CE and CEC methods are demonstrated and several types of their applications are shown. They include qualitative and quantitative analysis, determination in complex biomatrices, monitoring of chemical and enzymatic reactions and physicochemical changes, amino acid, sequence, and chiral analyses, and peptide mapping of proteins. In addition, micropreparative separations and determination of significant physicochemical parameters of peptides by CE and CEC methods are described.

Mass spectrometry based proteomics for developmental neurobiology in the amphibian Xenopus laevis

The South African clawed frog (Xenopus laevis), a prominent vertebrate model in cell and developmental biology, has been instrumental in studying molecular mechanisms of neural development and disease. Recently, high-resolution mass spectrometry (HRMS), a bioanalytical technology, has expanded the molecular toolbox of protein detection and characterization (proteomics). This chapter overviews the characteristics, advantages, and challenges of this biological model and technology. Discussions are offered on their combined use to aid studies on cell differentiation and development of neural tissues. Finally, the emerging integration of proteomics and other 'omic technologies is reflected on to generate new knowledge, drive and test new hypotheses, and ultimately, advance the understanding of neural development during states of health and disease.

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.

[Methods and applications of single-cell proteomics analysis based on mass spectrometry]

The cell is the smallest unit of living organisms. Although cells often assemble to serve a common function, intercellular heterogeneity often exists due to different genetic and environmental effects. Therefore, single-cell analysis has been regarded as an indispensable means to investigate cell heterogeneity, especially when researching cell differentiation, disease diagnosis, and therapy. As the chief factors influencing cell and biological activities, proteins have long been a major concern in biochemistry. However, due to their intrinsic lack of amplification characteristics, wide species variety, low abundance, and wide dynamic range, proteins are scarcely studied in single-cell research when compared with other biological macromolecules. Therefore, ultra-sensitive single-cell proteomics analysis methods are urgently required. Among all general measurement techniques, fluorescence methods possess high sensitivity and a capability of dynamic tracing, but low target numbers impose restrictions on their broad application in real "proteomic" studies. Similarly, electrochemical methods adapt to electrochemically active molecules, which miss the majority of proteins. Mass spectrometry (MS), as the core approach of proteomic studies, provides high-sensitivity and high-throughput analysis of proteins together with abundant structural information, which is unique in all the analytical instruments and has made great progress in single-cell proteomic research. Herein, the representative research methods for single-cell proteomics based on MS are reviewed. According to the different protein separation methods used prior to MS analysis, they are divided into three categories, including capillary electrophoresis (CE), liquid chromatography (LC), and direct infusion without the need for separation. First, CE has been widely used in the separation and analysis of complex biological samples owing to its low cost, high analysis speed, and high separation efficiency. Its unique feature is the extraction and transfer of contents from cellular or subcellular regions using capillaries smaller than a single cell size. This sampling method also offers less substrate interference and negligible oxidative damage to the cells. Nonetheless, single-cell analysis based on CE-MS mainly focuses on proteomic studies of large cells because of the considerable sample loss, interface instability, and reproducibility issues. Compared with CE, LC, especially nanoLC, is more widely used in single-cell proteomic research, which mainly depends on its good reproducibility, nanoliter injection volume, low flow rate, low sample loss, and good compatibility with mass spectrometry. In recent years, it has been increasingly applied in the study of large-volume embryos, germ cells, and even somatic cells. More than 1000 proteins have been identified in single HeLa cells using this state-of-the-art single-cell proteomics method. It is worth noting that the single-cell sampling volume based on LC gradually reduces to the nanoliter level, and that the sample loss can be reduced by integrating a series of proteomic sampling processes into small volumes, setting sealing conditions, and reducing washing steps. However, the adequacy of cell lysis, the completeness and efficiency of protein pretreatment, and the labeling of peptide segments are important factors affecting the number and types of protein identification. Compared with protein separation using CE or LC prior to MS analysis, the direct MS analysis, assisted by labelling and signal transformation, eliminates complicated sample pretreatment and simplifies the operation by reducing enzymatic hydrolysis and separation. It also renders higher resolution as well as multi-omics compatibility. So far, the number of proteins detected using this method is limited due to the complexity of the samples. In conclusion, the aspects of throughput, sensitivity, identified protein species, and applications are summarized for each method mentioned above, and the prospect of single-cell proteomic research based on MS in the future is also discussed.

Past, present, and future developments in enantioselective analysis using capillary electromigration techniques

Enantioseparation of chiral products has become increasingly important in a large diversity of academic and industrial applications. The separation of chiral compounds is inherently challenging and thus requires a suitable analytical technique that can achieve high resolution and sensitivity. In this context, CE has shown remarkable results so far. Chiral CE offers an orthogonal enantioselectivity and is typically considered less costly than chromatographic techniques, since only minute amounts of chiral selectors are needed. Several CE approaches have been developed for chiral analysis, including chiral EKC and chiral CEC. Enantioseparations by EKC benefit from the wide variety of possible pseudostationary phases that can be employed. Chiral CEC, on the other hand, combines chromatographic separation principles with the bulk fluid movement of CE, benefitting from reduced band broadening as compared to pressure-driven systems. Although UV detection is conventionally used for these approaches, MS can also be considered. CE-MS represents a promising alternative due to the increased sensitivity and selectivity, enabling the chiral analysis of complex samples. The potential contamination of the MS ion source in EKC-MS can be overcome using partial-filling and counter-migration techniques. However, chiral analysis using monolithic and open-tubular CEC-MS awaits additional method validation and a dedicated commercial interface. Further efforts in chiral CE are expected toward the improvement of existing techniques, the development of novel pseudostationary phases, and establishing the use of chiral ionic liquids, molecular imprinted polymers, and metal-organic frameworks. These developments will certainly foster the adoption of CE(-MS) as a well-established technique in routine chiral analysis.

Biological applications of microchip electrophoresis with amperometric detection: in vivo monitoring and cell analysis

Microchip electrophoresis with amperometric detection (ME-EC) is a useful tool for the determination of redox active compounds in complex biological samples. In this review, a brief background on the principles of ME-EC is provided, including substrate types, electrode materials, and electrode configurations. Several different detection approaches are described, including dual-channel systems for dual-electrode detection and electrochemistry coupled with fluorescence and chemiluminescence. The application of ME-EC to the determination of catecholamines, adenosine and its metabolites, and reactive nitrogen and oxygen species in microdialysis samples and cell lysates is also detailed. Lastly, approaches for coupling of ME-EC with microdialysis sampling to create separation-based sensors that can be used for near real-time monitoring of drug metabolism and neurotransmitters in freely roaming animals are provided. Graphical abstract.

Analytical techniques for metabolomic studies: a review

Metabolomics is the comprehensive study of small-molecule metabolites. Obtaining a wide coverage of the metabolome is challenging because of the broad range of physicochemical properties of the small molecules. To study the compounds of interest spectroscopic (NMR), spectrometric (MS) and separation techniques (LC, GC, supercritical fluid chromatography, CE) are used. The choice for a given technique is influenced by the sample matrix, the concentration and properties of the metabolites, and the amount of sample. This review discusses the most commonly used analytical techniques for metabolomic studies, including their advantages, drawbacks and some applications.

Capillary zone electrophoresis-mass spectrometry for top-down proteomics

Mass spectrometry (MS)-based top-down proteomics characterizes complex proteomes at the intact proteoform level and provides an accurate picture of protein isoforms and protein post-translational modifications in the cell. The progress of top-down proteomics requires novel analytical tools with high peak capacity for proteoform separation and high sensitivity for proteoform detection. The requirements have made capillary zone electrophoresis (CZE)-MS an attractive approach for advancing large-scale top-down proteomics. CZE has achieved a peak capacity of 300 for separation of complex proteoform mixtures. CZE-MS has shown drastically better sensitivity than commonly used reversed-phase liquid chromatography (RPLC)-MS for proteoform detection. The advanced CZE-MS identified 6,000 proteoforms of nearly 1,000 proteoform families from a complex proteome sample, which represents one of the largest top-down proteomic datasets so far. In this review, we focus on the recent progress in CZE-MS-based top-down proteomics and provide our perspectives about its future directions.

Evolution of multi-functional capillary electrophoresis for high-efficiency selection of aptamers

Aptamers have drawn considerable attention as newly emerging molecular recognition elements in clinical diagnostics, drug delivery, therapeutics, environmental monitoring, and food safety analyses. As the in vitro screening antibody analogs, aptamers are enabled to recognize various types of targets with high affinity and specificity like or even superior to antibodies. However, the restrictions and inefficiency of selection have been hampering their wider application. Among various modified systematic evolution of ligands by exponential enrichment (SELEX) methods, capillary electrophoresis (CE)-SELEX holds multiple functions and advantages with the powerful qualitative and quantitative analysis capabilities, less consumption of sample and analytical reagent, natural binding environment, higher screening efficiency, and availability in multiple modes. This review summarizes the key developments in the area of CE-SELEX by leading research groups, including our teams' ten years of research and experience to help researchers fully understand and utilize CE-SELEX. Aptamers' history, applications, as well as the SELEX developments, have been briefly described; the advantages of CE-SELEX are highlighted compared with the conventional SELEX methods. Further, we describe some essential CE-SELEX models and provide an overview of the CE-SELEX, including the targets and ssDNA library, every technical point in the selection process, and post-SELEX protocol. We expect this review will inspire more researchers to have insight into the screening problems from CE-SELEX viewpoint and will help to improve the selection efficiency and probability of success to meet the growing needs of aptamers' discovery in bioanalytical and medical fields.

The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution

Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan.