Recent Advances in the Analysis of Single Cells

The isolation strategy and chemical analysis of oil cells from Asari Radix et Rhizoma

BACKGROUND

Single-cell analysis, a rapidly evolving field, encounters significant challenges in detecting individual cells within complex plant tissues, particularly oil cells (OCs). The intricate process of single-cell isolation, coupled with the inherent chemical volatility of oil cells, necessitates a comprehensive methodology.

RESULTS

This study presents a method for obtaining intact OC from Asari Radix et Rhizoma (ARR), a traditional herbal medicine. The developed approach facilitates both qualitative and quantitative analysis of diverse OCs. To determine the most reliable approach, four practical methods-laser capture microdissection, micromanipulation capturing, micromanipulation piping, and cell picking-were systematically compared and evaluated, unequivocally establishing cell picking as the most effective method for OC isolation and chemical analysis. Microscopic observations showed that OCs predominantly distribute in the cortex of adventitious and fibrous roots, as well as the pith and cortex of the rhizome, with distinct morphologies-oblong in roots and circular in rhizomes. Sixty-three volatile constituents were identified in OCs, with eighteen compounds exhibiting significant differences. Safrole, methyleugenol, and asaricin emerged as the most abundant constituents in OCs. Notably, cis-4-thujanol and tetramethylpyrazine were exclusive to rhizome OCs, while isoeugenol methyl ether was specific to fibrous root OCs based on the detections. ARR roots and rhizomes displayed marked disparities in OC distribution, morphology, and constituents.

CONCLUSION

The study highlights the efficacy of cell picking coupled with HS-SPME-GC-MS as a flexible, reliable, and sensitive method for OC isolation and chemical analysis, providing a robust methodology for future endeavors in single-cell analyses.

Morphological Stability for in silico Models of Avascular Tumors

The landscape of computational modeling in cancer systems biology is diverse, offering a spectrum of models and frameworks, each with its own trade-offs and advantages. Ideally, models are meant to be useful in refining hypotheses, to sharpen experimental procedures and, in the longer run, even for applications in personalized medicine. One of the greatest challenges is to balance model realism and detail with experimental data to eventually produce useful data-driven models. We contribute to this quest by developing a transparent, highly parsimonious, first principle in silico model of a growing avascular tumor. We initially formulate the physiological considerations and the specific model within a stochastic cell-based framework. We next formulate a corresponding mean-field model using partial differential equations which is amenable to mathematical analysis. Despite a few notable differences between the two models, we are in this way able to successfully detail the impact of all parameters in the stability of the growth process and on the eventual tumor fate of the stochastic model. This facilitates the deduction of Bayesian priors for a given situation, but also provides important insights into the underlying mechanism of tumor growth and progression. Although the resulting model framework is relatively simple and transparent, it can still reproduce the full range of known emergent behavior. We identify a novel model instability arising from nutrient starvation and we also discuss additional insight concerning possible model additions and the effects of those. Thanks to the framework's flexibility, such additions can be readily included whenever the relevant data become available.

Recent advances of nanopore technique in single cell analysis

Single cells and their dynamic behavior are closely related to biological research. Monitoring their dynamic behavior is of great significance for disease prevention. How to achieve rapid and non-destructive monitoring of single cells is a major issue that needs to be solved urgently. As an emerging technology, nanopores have been proven to enable non-destructive and label-free detection of single cells. The structural properties of nanopores enable a high degree of sensitivity and accuracy during analysis. In this article, we summarize and classify the different types of solid-state nanopores that can be used for single-cell detection and illustrate their specific applications depending on the size of the analyte. In addition, their research progress in material transport and microenvironment monitoring is also highlighted. Finally, a brief summary of existing research challenges and future trends in nanopore single-cell analysis is tentatively provided.

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.

Nanobead-based single-molecule pulldown for single cells

Investigation of cell-to-cell variability holds critical physiological and clinical implications. Thus, numerous new techniques have been developed for studying cell-to-cell variability, and these single-cell techniques can also be used to investigate rare cells. Moreover, for studying protein-protein interactions (PPIs) in single cells, several techniques have been developed based on the principle of the single-molecule pulldown (SiMPull) assay. However, the applicability of these single-cell SiMPull (sc-SiMPull) techniques is limited because of their high technical barrier and special requirements for target cells and molecules. Here, we report a highly innovative nanobead-based approach for sc-SiMPull that is based on our recently developed microbead-based, improved version of SiMPull for cell populations. In our sc-SiMPull method, single cells are captured in microwells and lysed in situ, after which commercially available, pre-surface-functionalized magnetic nanobeads are placed in the microwells to specifically capture proteins of interest together with their binding partners from cell extracts; subsequently, the PPIs are examined under a microscope at the single-molecule level. Relative to previously published methods, nanobead-based sc-SiMPull is considerably faster, easier to use, more reproducible, and more versatile for distinct cell types and protein molecules, and yet provides similar sensitivity and signal-to-background ratio. These crucial features should enable universal application of our method to the study of PPIs in single cells.

Single-cell metabolomics by mass spectrometry: ready for primetime?

Single-cell metabolomics (SCMs) is a powerful tool for studying cellular heterogeneity by providing insight into the differences between individual cells. With the development of a set of promising SCMs pipelines, this maturing technology is expected to be widely used in biomedical research. However, before SCMs is ready for primetime, there are some challenges to overcome. In this review, we summarize the trends and challenges in the development of SCMs. We also highlight the latest methodologies, applications, and sketch the perspective for integration with other omics and imaging approaches.

Electrochemical Biosensors for Whole Blood Analysis: Recent Progress, Challenges, and Future Perspectives

Whole blood, as one of the most significant biological fluids, provides critical information for health management and disease monitoring. Over the past 10 years, advances in nanotechnology, microfluidics, and biomarker research have spurred the development of powerful miniaturized diagnostic systems for whole blood testing toward the goal of disease monitoring and treatment. Among the techniques employed for whole-blood diagnostics, electrochemical biosensors, as known to be rapid, sensitive, capable of miniaturization, reagentless and washing free, become a class of emerging technology to achieve the target detection specifically and directly in complex media, e.g., whole blood or even in the living body. Here we are aiming to provide a comprehensive review to summarize advances over the past decade in the development of electrochemical sensors for whole blood analysis. Further, we address the remaining challenges and opportunities to integrate electrochemical sensing platforms.

Parallel Dielectrophoretic Capture, Isolation, and Electrical Lysis of Individual Breast Cancer Cells to Assess Variability in Enzymatic Activity

Tumor cell heterogeneity drives disease progression and response to therapy, and therefore, there is a need for single-cell analysis methods. In this paper, we present an integrated, scalable method to analyze enzymatic activity in many individual cancer cells at once. The reported method uses dielectrophoresis (DEP) to selectively capture tumor cells at wireless electrodes aligned to an overlying array of cell-sized micropockets. Following hydrodynamic transfer of the captured cells into microfluidic chambers, the chambers are fluidically isolated and sealed with a hydrophobic ionic liquid, which possesses sufficient conductivity to allow for subsequent electrical lysis of the cells to access their contents for enzymatic assay. The wireless electrodes have an interlocking spiral design that ensures successful electrical lysis regardless of the location of the cell within the chamber. Here, breast cancer cells are assessed for β-galactosidase through its activation of a fluorogenic substrate. A key point is that the fluorogenic assay solution was optimized to allow for dielectrophoretic cell capture, thereby obviating the need for a solution exchange step. Our approach has several distinct advantages including a high rate of single-cell capture, a capture efficiency that is independent of the dimensions of the reaction chambers, no need for mechanical closure of reaction volumes, and no observed cross-talk. In this study, first, the steps of cell capture, transfer, and lysis are established on this platform in the presence of the optimized assay solution. We then quantify the increase in fluorescence intensity obtained over the duration of the enzymatic assay of individual cells. Finally, this method is applied to the analysis of β-galactosidase activity in 258 individual MDA-MB-231 breast cancer cells, revealing heterogeneity in expression of this enzyme in this cell line. We expect that the adaptability of this method will allow for expanded studies of single-cell enzymatic expression and activity. This will in turn open avenues of research into cancer cell heterogeneity in metabolism, invasiveness, and drug response. The ability to study these features of cancer at the single-cell level raises the possibility for treatment plans tailored to target the specific combinations of cell subpopulations present in tumors. Furthermore, we expect that this method can be adapted to uses outside of cancer research, such as studies of neuron metabolism, pathogenesis in bacteria, and stem cell development.

Stability of enzyme immobilized on the nanofluidic channel surface

The lifetime of an enzyme is critical to prevent system failure and optimize maintenance schedules in biological and analytical chemistry. The lifetime metrics of an enzyme can be evaluated from enzyme activity in terms of catalytic cycles per enzyme at various storage times. Trypsin, which is a gold-standard enzyme in proteomics, has been known to decrease activity due to self-digestion. To improve the activity of trypsin, enzyme reactors have developed by immobilizing in micro and nanospace. However, an evaluation method for the catalytic cycle has not been established due to major issues such as nonuniform space, unstable liquid transport, and self-digestion during immobilization in conventional work. To solve these issues, we have previously developed an ultra-fast enzyme reactor with a well-defined nanofabrication method, stable liquid transport, and partial enzyme modification. Here, we aimed to investigate catalytic cycles in a nanochannel. To extend enzyme lifetime efficiently, we have evaluated the optimal immobilization process and catalytic cycles of trypsin. As a result, immobilized enzyme densities by the trypsinogen immobilization process were increased at all concentrations compared to the trypsin immobilization process. To evaluate the lifetime of trypsin, the immobilized enzyme densities and activities were almost the same before and after 72 h of enzyme storage, and the calculated catalytic cycles were 1740. These results indicated that self-digestion of the immobilized enzyme was highly suppressed. Consequently, the reaction efficiency has been evaluated depending on the catalytic cycles from the substrate for the first time, while preventing self-digestion by trypsin.

Nanocapillary sampling coupled to liquid chromatography mass spectrometry delivers single cell drug measurement and lipid fingerprints

This work describes the development of a new approach to measure drug levels and lipid fingerprints in single living mammalian cells. Nanocapillary sampling is an approach that enables the selection and isolation of single living cells under microscope observation. Here, live single cell nanocapillary sampling is coupled to liquid chromatography for the first time. This allows molecular species to be separated prior to ionisation and improves measurement precision of drug analytes. The efficiency of transferring analytes from the sampling capillary into a vial was optimised in this work. The analysis was carried out using standard flow liquid chromatography coupled to widely available mass spectrometry instrumentation, highlighting opportunities for widespread adoption. The method was applied to 30 living cells, revealing cell-to-cell heterogeneity in the uptake of different drug molecules. Using this system, we detected 14-158 lipid features per single cell, revealing the association between bedaquiline uptake and lipid fingerprints.

Multiplexed analysis of signalling proteins at the single-immune cell level

High numbers of tumour-associated macrophages (TAMs) in the tumour microenvironment are associated with a poor prognosis. However, the effect of TAMs on tumour progression depends on the proteins secreted by individual TAMs. Here, we developed a microfluidic platform to quantitatively measure the secreted proteins of individual macrophages as well as macrophages polarized by the culture medium derived from breast cancer cells. The macrophages were captured in hydrodynamic traps and isolated with pneumatically activated valves for single-cell analysis. Barcoded and functionalized magnetic beads were captured in specially designed traps to determine the secreted proteins by immunoassay. Individual bead trapping facilitated the recording of the protein concentration since all beads were geometrically constrained in the same focal plane, which is an important requirement for rapid and automated image analysis. By determining three signaling proteins, namely interleuking 10 (IL-10), vascular endothelial growth factor (VEGF), and tumour necrosis factor alpha (TNF-α), we successfully distinguished between differently polarized macrophages. The results indicate a heterogeneous pattern, with M2 macrophages characterized by a higher secretion of IL-10, while M1 macrophages secrete high levels of the inflammatory cytokine TNF-α. The macrophages treated with the supernatant from cancer cells show a similar signalling pattern to M2 macrophages with an increased secretion of the pro-tumoural cytokine VEGF. This microfluidic method resolves correlations in signaling protein expression at the single-cell level. Ultimately, single-macrophage analysis can contribute to the development of novel therapies aimed at reversing M2-like TAMs into M1-like TAMs.

Defining atherosclerotic plaque biology by mass spectrometry-based omics approaches

Atherosclerosis is the principal cause of vascular diseases and one of the leading causes of worldwide death. Even though several insights into its natural course, risk factors and interventions have been identified, it is still an ongoing global pandemic. Since the structure and biochemical composition of the plaques show high heterogeneity, a comprehensive understanding of the intraplaque composition, its microenvironment, and the mechanisms of the progression and instability across different vascular beds at their progression stages is crucial for better risk stratification and treatment modalities. Even though several cell-based studies, animal studies, and extensive multicentric population studies have been conducted concerning cardiovascular diseases for assessing the risk factors and plaque biology, the studies on human clinical samples are very limited. New novel approaches utilize samples from percutaneous coronary interventions, which could possibly gain more access to clinical samples at different stages of the diseases without complex invasive resections. As an emerging technological platform in disease discovery research, mass spectrometry-based omics technologies offer capabilities for a comprehensive understanding of the mechanisms linked to several vascular diseases. Here, we discuss the cellular and molecular processes of atherosclerosis, different mass spectrometry-based omics approaches, and the studies mostly done on clinical samples of atheroma plaque using mass spectrometry-based proteomics, metabolomics and lipidomics approaches.

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.

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.

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.

Fluorescence lifetime activated droplet sorting (FLADS) for label-free sorting of Synechocystis sp. PCC6803

This study presents the label-free sorting of cyanobacterial cells in droplets with single-cell sensitivity based on their fluorescence lifetime. We separated living and dead cyanobacteria (Synechocystis sp. PCC6803) using fluorescence lifetime signals of the photopigment autofluorescence to indicate their photosynthetic activity. We developed a setup and a chip design to achieve live/dead sorting accuracies of more than 97% at a droplet frequency of 100 Hz with a PDMS-based chip system and standard optics using fluorescence lifetime as the sorting criterion. The obtained sorting accuracies could be experimentally confirmed by cell plating and observing the droplet sorting process via a high-speed camera. The herein presented results demonstrate the capabilities of the developed system for studying the effects of stressors on cyanobacterial physiology and the subsequent deterministic sorting of different stress-response phenotypes. This technology eliminates the need for tedious staining of cyanobacterial cells, which makes it particularly attractive for its application in the field of phototrophic microbial bio(techno)logic and in the context of cell secretion studies.

Selective retrieval of antibody-secreting hybridomas in cell arrays based on the dielectrophoresis

A cascade of the formation of cell arrays, the discrimination of cells secreting specific molecules, and the selective retrieval of cells has been developed to harvest antibody-secreting hybridomas in heterogeneous cell populations simply and rapidly. The microwell array device consisted of three-dimensional microband electrodes by assembling both upper and lower substrates perpendicularly. Arrays of hybridomas secreting specific antibodies were prepared by aligning hybridomas in each microwell based on the attractive force of positive dielectrophoresis (p-DEP). Antibody secreted by the hybridomas in the microwells was recognized by the antigen immobilized on the microwells or the membrane surfaces of hybridomas to discriminate hybridomas with the secretion ability. Thereafter, a repulsive force of negative dielectrophoresis (n-DEP) was applied to release the target hybridomas from the microwell array. To harvest the target hybridoma, AC signals could be modulated in the n-DEP frequency region and applied to a pair of microband electrodes located above and below each microwell containing target hybridoma. Thus, the cell-based array system described in this study allowed selective retrieval of single target hybridomas by merely switching from p-DEP to n-DEP after selecting the antibody-secreting hybridomas trapped in each microwell. The development of this high-affinity device could be useful to recover hybridomas producing antibodies in large populations of cells rapidly and effectively.

High-Throughput, Living Single-Cell, Multiple Secreted Biomarker Profiling Using Microfluidic Chip and Machine Learning for Tumor Cell Classification

Secreted proteins provide abundant functional information on living cells and can be used as important tumor diagnostic markers, of which profiling at the single-cell level is helpful for accurate tumor cell classification. Currently, achieving living single-cell multi-index, high-sensitivity, and quantitative secretion biomarker profiling remains a great challenge. Here, a high-throughput living single-cell multi-index secreted biomarker profiling platform is proposed, combined with machine learning, to achieve accurate tumor cell classification. A single-cell culture microfluidic chip with self-assembled graphene oxide quantum dots (GOQDs) enables high-activity single-cell culture, ensuring normal secretion of biomarkers and high-throughput single-cell separation, providing sufficient statistical data for machine learning. At the same time, the antibody barcode chip with self-assembled GOQDs performs multi-index, highly sensitive, and quantitative detection of secreted biomarkers, in which each cell culture chamber covers a whole barcode array. Importantly, by combining the K-means strategy with machine learning, thousands of single tumor cell secretion data are analyzed, enabling tumor cell classification with a recognition accuracy of 95.0%. In addition, further profiling of the grouping results reveals the unique secretion characteristics of subgroups. This work provides an intelligent platform for high-throughput living single-cell multiple secretion biomarker profiling, which has broad implications for cancer investigation and biomedical research.

Controllable Fabrication of Small-Size Holding Pipets for the Nondestructive Manipulation of Suspended Living Single Cells

The capture and manipulation of single cells are an important premise and basis for intracellular delivery, which provides abundant molecular and omics information for biomedical development. However, for intracellular delivery of cargos into/from small-size suspended living single cells, the capture methods are limited by the lack of small-size holding pipets, poor cell activity, and the low spatial accuracy of intracellular delivery. To solve these problems, a method for the controllable fabrication of small-size holding pipets was proposed. A simple, homemade microforge instrument including an imaging device was built to cut and melt the glass capillary tip by controlling the heat production of a nichrome wire. The controllable fabrication of small-size holding pipets was realized by observing the fabrication process in real time. Combined with an electroosmotic drive system and a micromanipulation system with high spatial resolution, the holding pipet achieved the active capture, movement, and sampling of suspended living single cells. Moreover, solid-phase microextraction was performed on captured single pheochromocytoma cells, and the extracted dopamine was successfully detected using an electrochemical method. The homemade microforge instrument overcame the limitations of traditional microforges, resulting in holding pipets that were sufficiently small for small-size suspended single living cells (5-30 μm). This proactive capture method overcame the shortcomings of existing methods to achieve the multiangle, high-precision manipulation of single cells, thereby allowing the intracellular delivery of small-size single cells in suspension with high spatiotemporal resolution.

Accelerated protein digestion and separation with picoliter volume utilizing nanofluidics

Single cell analyses can provide critical biological insight into cellular heterogeneity. In particular, the proteome, which governs cell functions, is much more difficult to analyze because it is principally impossible to amplify proteins compared to nucleic acids. The most promising approach to single cell proteomics is based on the liquid chromatography mass spectrometry (LC-MS) platform. However, pretreatments before MS detection have two critical issues for single cell analysis: analyte loss as a result of adsorption and artifacts due to the duration of analysis. This is a serious problem because single cells have a limited number of protein molecules and a small volume. To solve these issues, we developed an integrated nanofluidic device to manipulate samples on a femtoliter to picoliter (fL-pL) scale to achieve high-throughput analysis via suppressing analyte loss. This device can perform tryptic digestion, chromatographic separation, and non-labeled detection with high consistency. In addition, we introduced an open/close valve by physical deformation of glass on a nanometer scale to independently modify the nanochannel surfaces and control sample aliquots. The injection system equipped with this valve achieved an injection volume of 1.0 ± 0.1 pL. By using this integrated device, we found that the chromatogram of bulk-digestion for 12 hours resembled that of 15 min-digestion in the nanochannel, which indicated that these conditions reached a similar state of digestion. Therefore, an integrated device for ultra-fast protein analysis was developed on a 1 pL scale for the first time.

Prototype Smartphone-Based Device for Flow Cytometry with Immunolabeling via Supra-nanoparticle Assemblies of Quantum Dots

Methods for the detection, enumeration, and typing of cells are important in many areas of research and healthcare. In this context, flow cytometers are a widely used research and clinical tool but are also an example of a large and expensive instrument that is limited to specialized laboratories. Smartphones have been shown to have excellent potential to serve as portable and lower-cost platforms for analyses that would normally be done in a laboratory. Here, we developed a prototype smartphone-based flow cytometer (FC). This compact 3D-printed device incorporated a laser diode and a microfluidic flow cell and used the built-in camera of a smartphone to track immunofluorescently labeled cells in suspension and measure their color. This capability was enabled by high-brightness supra-nanoparticle assemblies of colloidal semiconductor quantum dots (SiO₂@QDs) as well as a support vector machine (SVM) classification algorithm. The smartphone-based FC device detected and enumerated target cells against a background of other cells, simultaneously and selectively counted two different cell types in a mixture, and used multiple colors of SiO₂@QD-antibody conjugates to screen for and identify a particular cell type. The potential limits of multicolor detection are discussed alongside ideas for further development. Our results suggest that innovations in materials and engineering should enable eventual smartphone-based FC assays for clinical applications.

Integrated Microfluidic Handheld Cell Sorter for High-Throughput Label-Free Malignant Tumor Cell Sorting

Handheld sample preparation devices are urgently required for point-of-care diagnosis in resource-limited settings. In this paper, we develop a novel handheld sorter with a multifunction integrated microfluidic chip. The integrated microfluidic handheld sorter (μHCS) is composed of three units, including cartridges, shells, and core integrated microchip. The integrated microchip contains two flow regulators for achieving the on-chip regulation of the input flows generated by a low-cost diaphragm pump to the desired flow rates and a spiral inertial microfluidic channel for size-based cell separation. After introducing the conceptual design of our μHCS system, the performances of the separate spiral channel and flow regulator are systematically characterized and optimized, respectively. Finally, the prototype of the μHCS is successfully assembled to separate the malignant tumor cells from the clinical pleural effusions. Our μHCS is simple to use, inexpensive, portable, and compact and can be used for high-throughput label-free separation of rare cells from large volume samples in resource-limited areas.

Recent progress of microfluidic technology for pharmaceutical analysis

In recent years, the progress of microfluidic technology has provided new tools for pharmaceutical analysis and the proposal of pharm-lab-on-a-chip is appealing for its great potential to integrate pharmaceutical test and pharmacological test in a single chip system. Here, we summarize and highlight recent advances of chip-based principles, techniques and devices for pharmaceutical test and pharmacological/toxicological test focusing on the separation and analysis of drug molecules on a chip and the construction of pharmacological models on a chip as well as their demonstrative applications in quality control, drug screening and precision medicine. The trend and challenge of microfluidic technology for pharmaceutical analysis are also discussed and prospected. We hope this review would update the insight and development of pharm-lab-on-a-chip.

Recent Advances in Electrical Impedance Sensing Technology for Single-Cell Analysis

Cellular heterogeneity is of significance in cell-based assays for life science, biomedicine and clinical diagnostics. Electrical impedance sensing technology has become a powerful tool, allowing for rapid, non-invasive, and label-free acquisition of electrical parameters of single cells. These electrical parameters, i.e., equivalent cell resistance, membrane capacitance and cytoplasm conductivity, are closely related to cellular biophysical properties and dynamic activities, such as size, morphology, membrane intactness, growth state, and proliferation. This review summarizes basic principles, analytical models and design concepts of single-cell impedance sensing devices, including impedance flow cytometry (IFC) to detect flow-through single cells and electrical impedance spectroscopy (EIS) to monitor immobilized single cells. Then, recent advances of both electrical impedance sensing systems applied in cell recognition, cell counting, viability detection, phenotypic assay, cell screening, and other cell detection are presented. Finally, prospects of impedance sensing technology in single-cell analysis are discussed.

A Microfluidic Platform for Sequential Assembly and Separation of Synthetic Cell Models

Cell-sized vesicles like giant unilamellar vesicles (GUVs) are established as a promising biomimetic model for studying cellular phenomena in isolation. However, the presence of residual components and byproducts, generated during vesicles preparation and manipulation, severely limits the utility of GUVs in applications like synthetic cells. Therefore, with the rapidly growing field of synthetic biology, there is an emergent demand for techniques that can continuously purify cell-like vesicles from diverse residues, while GUVs are being simultaneously synthesized and manipulated. We have developed a microfluidic platform capable of purifying GUVs through stream bifurcation, where a vesicles suspension is partitioned into three fractions: purified GUVs, residual components, and a washing solution. Using our purification approach, we show that giant vesicles can be separated from various residues—which range in size and chemical composition—with a very high efficiency (e = 0.99), based on size and deformability of the filtered objects. In addition, by incorporating the purification module with a microfluidic-based GUV-formation method, octanol-assisted liposome assembly (OLA), we established an integrated production-purification microfluidic unit that sequentially produces, manipulates, and purifies GUVs. We demonstrate the applicability of the integrated device to synthetic biology through sequentially fusing SUVs with freshly prepared GUVs and separating the fused GUVs from extraneous SUVs and oil droplets at the same time.

Two-photon fluorescence lifetime for label-free microfluidic droplet sorting

Microfluidic droplet sorting systems facilitate automated selective micromanipulation of compartmentalized micro- and nano-entities in a fluidic stream. Current state-of-the-art droplet sorting systems mainly rely on fluorescence detection in the visible range with the drawback that pre-labeling steps are required. This limits the application range significantly, and there is a high demand for alternative, label-free methods. Therefore, we introduce time-resolved two-photon excitation (TPE) fluorescence detection with excitation at 532 nm as a detection technique in droplet microfluidics. This enables label-free in-droplet detection of small aromatic compounds that only absorb in a deep-UV spectral region. Applying time-correlated single-photon counting, compounds with similar emission spectra can be distinguished due to their fluorescence lifetimes. This information is then used to trigger downstream dielectrophoretic droplet sorting. In this proof-of-concept study, we developed a polydimethylsiloxane-fused silica (FS) hybrid chip that simultaneously provides a very high optical transparency in the deep-UV range and suitable surface properties for droplet microfluidics. The herein developed system incorporating a 532-nm picosecond laser, time-correlated single-photon counting (TCSPC), and a chip-integrated dielectrophoretic pulsed actuator was exemplarily applied to sort droplets containing serotonin or propranolol. Furthermore, yeast cells were screened using the presented platform to show its applicability to study cells based on their protein autofluorescence via TPE fluorescence lifetime at 532 nm.

Detection of the effect of polydopamine (PDA)-coated polydimethylsiloxane (PDMS) substrates on the release of H2O2 from a single HeLa cell

Endogenous H₂O₂ generated by a single HeLa cell that was adhered on the PDA-coated PDMS substrates under 25 mM glucose culture conditions was detected using a home-built photoelectric dual detection platform. With PMA as the stimulus, the cell released a small amount of H₂O₂ and its mitochondrial membrane potential (MMP) decrease was smaller, compared with that on the PDMS substrates.

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

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

Single Cell Metabolite Detection Using Inertial Microfluidics-Assisted Ion Mobility Mass Spectrometry

Single-cell metabolite measurement remains highly challenging due to difficulties related to single cell isolation, metabolite detection, and identification of low levels of metabolites. Here, as a first step of the technological development, we propose a novel strategy integrating spiral inertial microfluidics and ion mobility mass spectrometry (IM-MS) for single-cell metabolite detection and identification. Cells in methanol suspension are inertially focused into a single stream in the spiral microchannel. This stream of separated cells is delivered to the nanoelectrospray needle to be lysed and ionized and subsequently analyzed in real time by IM-MS. This analytical system enables six to eight single-cell metabolic fingerprints to be collected per minute, including gas-phase collisional cross section (CCS) measurements as an additional molecular descriptor, giving increased confidence in metabolite identification. As a proof of concept, the metabolic profiles of three types of cancer cells (U2OS, HepG2, and HepG2.215) were successfully screened, and 19 distinct lipids species were identified with CCS value filtering. Furthermore, principal component analysis (PCA) showed differentiation of the three cancer cell lines, mainly due to cellular surface phospholipids. Taken together, our technology platform offers a simple and efficient method for single-cell lipid profiling, with additional ion mobility separation of lipids significantly improving the confidence toward identification of metabolites.

Following de novo triglyceride dynamics in ovaries of Aedes aegypti during the previtellogenic stage

Understanding the molecular and biochemical basis of egg development is a central topic in mosquito reproductive biology. Lipids are a major source of energy and building blocks for the developing ovarian follicles. Ultra-High Resolution Mass Spectrometry (UHRMS) combined with in vivo metabolic labeling of follicle lipids with deuterated water (²H₂O) can provide unequivocal identification of de novo lipid species during ovarian development. In the present study, we followed de novo triglyceride (TG) dynamics during the ovarian previtellogenic (PVG) stage (2-7 days post-eclosion) of female adult Aedes aegypti. The incorporation of stable isotopes from the diet was evaluated using liquid chromatography (LC) in tandem with the high accuracy (< 0.3 ppm) and high mass resolution (over 1 M) of a 14.5 T Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (14.5 T FT-ICR MS) equipped with hexapolar detection. LC-UHRMS provides effective lipid class separation and chemical formula identification based on the isotopic fine structure. The monitoring of stable isotope incorporation into de novo incorporated TGs suggests that ovarian lipids are consumed or recycled during the PVG stage, with variable time dynamics. These results provide further evidence of the complexity of the molecular mechanism of follicular lipid dynamics during oogenesis in mosquitoes.

A microscopy-compatible temperature regulation system for single-cell phenotype analysis - demonstrated by thermoresponse mapping of microalgae

This work describes a programmable heat-stage compatible with in situ microscopy for the accurate provision of spatiotemporally defined temperatures to different microfluidic devices. The heat-stage comprises an array of integrated thin-film Joule heaters and resistance temperature detectors (RTDs). External programming of the heat-stage is provided by a custom software program connected to temperature controllers and heater-sensor pairs. Biologically relevant (20-40 °C) temperature profiles can be supplied to cells within microfluidic devices as spatial gradients (0.5-1.5 °C mm-1) or in a time-varying approach via e.g. step-wise or sinusoidally varying profiles with negligible temperature over-shoot. Demonstration of the device is achieved by exposing two strains of the coral symbiont Symbiodinium to different temperature profiles while monitoring their single-cell photophysiology via chlorophyll fluorometry. This revealed that photophysiological responses to temperature depended on the exposure duration, exposure magnitude and strain background. Moreover, thermal dose analysis suggested that cell acclimatisation occurs under longer temperature (6 h) exposures but not under shorter temperature exposures (15 min). As the thermal sensitivity of Symbiodinium mediates the thermal tolerance in corals, our versatile technology now provides unique possibilities to research this interdependency at single cell resolution. Our results also show the potential of this heat-stage for further applications in fields such as biotechnology and ecotoxicology.

Selective Trapping and Retrieval of Single Cells Using Microwell Array Devices Combined with Dielectrophoresis

We proposed selective manipulation techniques for retrieving and retaining target cells arrayed in microwells based on dielectrophoresis (DEP). The upper substrate with microband electrodes was mounted on the lower substrate with microwells based on the same design of microband electrodes by 90 degree relative to the lower substrate. A repulsive force of negative dielectrophoresis (n-DEP) was employed to retrieve the target cells from the microwell array selectively. Furthermore, the target cells were retained in the microwells after other cells were removed by n-DEP. Thus, the system described in this study could make it possible to retrieve and recover single target cells from a microwell array after determining the function of cells trapped in each microwell.

Opening up the Single-Cell Toolbox for Microbial Natural Products Research

The diverse microbes that produce natural products represent an important source of novel therapeutics, drug leads, and scientific tools. However, the vast majority have not been grown in axenic culture and are members of complex communities. While meta-'omic methods such as metagenomics, -transcriptomics, and -proteomics reveal collective molecular features of this "microbial dark matter", the study of individual microbiome members can be challenging. To address these limits, a number of techniques with single-bacterial resolution have been developed in the last decade and a half. While several of these are embraced by microbial ecologists, there has been less use by researchers interested in mining microbes for natural products. In this review, we discuss the available and emerging techniques for targeted single-cell analysis with a particular focus on applications to the discovery and study of natural products.

Exploring quantitative cellular bioimaging and assessment of CdSe/ZnS quantum dots cellular uptake in single cells, using ns-LA-ICP-SFMS

Quantitative bioimaging of Quantum Dots (QDs) uptake in single cells by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is a challenging task due to the high sensitivity and high spatial resolution required, and to the lack of matrix-matched reference materials. In this work, high spatially resolved quantitative bioimaging of CdSe/ZnS QDs uptake in single HT22 mouse hippocampal neuronal cells and in single HeLa human cervical carcinoma cells is novelty investigated combining: (a) the use of a ns-LA-ICP-Sector Field (SF)MS unit with mono-elemental fast and sensitive single pulse response for ¹¹⁴Cd⁺; and (b) the spatially resolved analysis of dried pL-droplets from a solution with a known concentration of these QDs to obtain a response factor that allows quantification of elemental bioimages. Single cells and dried pL-droplets are morphologically characterized by Atomic Force Microscopy (AFM) to determine their volume and thickness distribution. Moreover, operating conditions (e.g. spot size, energy per laser pulse, etc.) are optimized to completely ablate the cells and pL droplets at high spatial resolution. Constant operating conditions for the analysis of the single cells and calibrating samples is employed to reduce potential fractionation effects related to mass load effects in the ICP. A number concentration of CdSe/ZnS QDs between 3.5 10⁴ and 48 10⁴ is estimated to be uptaken by several selected single HT22 and HeLa cells, after being incubated in the presence of a QDs suspension added to a standard cell culture medium. Mono-elemental bioimaging at subcellular resolution seems to show a higher number concentration of the CdSe/ZnS QDs in the cytosol around the cell nucleus.

A nontargeted approach to determine the authenticity of Ginkgo biloba L. plant materials and dried leaf extracts by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemometrics

The lack of stringent regulations regarding raw materials for herbal supplements used for medicinal purposes has been a constant challenge in the industry. Ginkgo biloba L. leaf extracts attract consumers because of the supposed positive effect on mental performance and memory. Supplements are produced using dried leaf materials and standardized leaf extracts such as EGb 761. Adulteration of Ginkgo biloba L. plants and extracts are becoming more and more common practice due to economically driven motivation from increasing demand in the market and the high cost of raw materials and production. Reinforcement in quality control (QC) to avoid adulterations is necessary to ensure the efficacy of the supplements. In this study, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) was used with principal component analysis (PCA) as an unsupervised exploratory method to analyze, identify, and evaluate the adulterated Ginkgo biloba L. plant materials and dried leaf extracts using the PCA scores and loadings obtained and compound identification.

Analysis of biomolecular condensates and protein phase separation with microfluidic technology

An increasing body of evidence shows that membraneless organelles are key components in cellular organization. These observations open a variety of outstanding questions about the physico-chemical rules underlying their assembly, disassembly and functions. Some molecular determinants of biomolecular condensates are challenging to probe and understand in complex in vivo systems. Minimalistic in vitro reconstitution approaches can fill this gap, mimicking key biological features, while maintaining sufficient simplicity to enable the analysis of fundamental aspects of biomolecular condensates. In this context, microfluidic technologies are highly attractive tools for the analysis of biomolecular phase transitions. In addition to enabling high-throughput measurements on small sample volumes, microfluidic tools provide for exquisite control of self-assembly in both time and space, leading to accurate quantitative analysis of biomolecular phase transitions. Here, with a specific focus on droplet-based microfluidics, we describe the advantages of microfluidic technology for the analysis of several aspects of phase separation. These include phase diagrams, dynamics of assembly and disassembly, rheological and surface properties, exchange of materials with the surrounding environment and the coupling between compartmentalization and biochemical reactions. We illustrate these concepts with selected examples, ranging from simple solutions of individual proteins to more complex mixtures of proteins and RNA, which represent synthetic models of biological membraneless organelles. Finally, we discuss how this technology may impact the bottom-up fabrication of synthetic artificial cells and for the development of synthetic protein materials in biotechnology.

Deep Profiling of Cellular Heterogeneity by Emerging Single-Cell Proteomic Technologies

The ability to comprehensively profile cellular heterogeneity in functional proteome is crucial in advancing the understanding of cell behavior, organism development, and disease mechanisms. Conventional bulk measurement by averaging the biological responses across a population often loses the information of cellular variations. Single-cell proteomic technologies are becoming increasingly important to understand and discern cellular heterogeneity. The well-established methods for single-cell protein analysis based on flow cytometry and fluorescence microscopy are limited by the low multiplexing ability owing to the spectra overlap of fluorophores for labeling antibodies. Recent advances in mass spectrometry (MS), microchip, and reiterative staining-based techniques for single-cell proteomics have enabled the evaluation of cellular heterogeneity with high throughput, increased multiplexity, and improved sensitivity. In this review, the principles, developments, advantages, and limitations of these advanced technologies in analysis of single-cell proteins, along with their biological applications to study cellular heterogeneity, are described. At last, the remaining challenges, possible strategies, and future opportunities that will facilitate the improvement and broad applications of single-cell proteomic technologies in cell biology and medical research are discussed.