A modular single-cell pipette microfluidic chip coupling to ETAAS and ICP-MS for single cell analysis

Accurate single-cell capture is a crucial step for single cell biological and chemical analysis. Conventional single-cell capturing often confront operational complexity, limited efficiency, cell damage, large scale but low accuracy, incompetence in the acquirement of nano-upgraded single-cell liquid. Flow cytometry has been widely used in large-scale single-cell detection, while precise single-cell isolation relies on both a precision operating platform and a microscope, which is not only extre...     

High-throughput single-cell quantification using simple microwell-based cell docking and programmable time-course live-cell imaging

Extracting single-cell information during cellular responses to external signals in a high-throughput manner is an essential step for quantitative single-cell analyses. Here, we have developed a simple yet robust microfluidic platform for measuring time-course single-cell response on a large scale. Our method combines a simple microwell-based cell docking process inside a patterned microfluidic channel, with programmable time-course live-cell imaging and software-aided fluorescent image processing. The budding yeast, Saccharomyces cerevisiae (S. cerevisiae), cells were individually captured in microwells by multiple sweeping processes, in which a cell-containing solution plug was actively migrating back and forth several times by a finger-pressure induced receding meniscus. To optimize cell docking efficiency while minimizing unnecessary flooding in subsequent steps, circular microwells of various channel dimensions (4-24 μm diameter, 8 μm depth) along with different densities of cell solution (1.5-6.0 × 10(9) cells per mL) were tested. It was found that the microwells of 8 μm diameter and 8 μm depth allowed for an optimal docking efficiency (>90%) without notable flooding issues. For quantitative single-cell analysis, time-course (time interval 15 minute, for 2 hours) fluorescent images of the cells stimulated by mating pheromone were captured using computerized fluorescence microscope and the captured images were processed using a commercially available image processing software. Here, real-time cellular responses of the mating MAPK pathway were monitored at various concentrations (1 nM-100 μM) of mating pheromone at single-cell resolution, revealing that individual cells in the population showed non-uniform signaling response kinetics.     

SCOUT: A new algorithm for the inference of pseudo-time trajectory using single-cell data

Single cell technology is a powerful tool to reveal intercellular heterogeneity and discover cellular developmental processes. When analyzing the complexity of cellular dynamics and variability, it is important to construct a pseudo-time trajectory using single-cell expression data to reflect the process of cellular development. Although a number of computational and statistical methods have been developed recently for single-cell analysis, more effective and efficient methods are still strongly needed. In this work we propose a new method named SCOUT for the inference of single-cell pseudo-time ordering with bifurcation trajectories. We first propose to use the fixed-radius near neighbors algorithms based on cell densities to find landmarks to represent the cell states, and employ the minimum spanning tree (MST) to determine the developmental branches. We then propose to use the projection of Apollonian circle or a weighted distance to determine the pseudo-time trajectories of single cells. The proposed algorithm is applied to one synthetic and two realistic single-cell datasets (including single-branching and multi-branching trajectories) and the cellular developmental dynamics is recovered successfully. Compared with other popular methods, numerical results show that our proposed method is able to generate more robust and accurate pseudo-time trajectories. The code of the method is implemented in Python and available at https://github.com/statway/SCOUT.     

基于质谱的单细胞蛋白质组学分析方法及应用

细胞是生命体的最小组成单位,遗传及外部环境等因素使单细胞异质性广泛存在于众多生物体中。传统的生物学实验获得的结果多是大量细胞的平均测量值,因此在单细胞层面开展研究对于精确理解细胞的生长发育以及疾病的诊断与治疗至关重要。而作为重要的细胞和生命活动的执行者,蛋白质由于其不具备扩增特性,且种类繁多、丰度低、动态分布范围宽,与核酸等其他生物大分子相比,其单细胞组学研究相对滞后。而在所有的检测手段中,荧光检测以及电化学分析方法具有极高的灵敏度,但是囿于其研究通量有限,以及电化学活性依赖,很难成为普适性的单细胞蛋白质组学研究方法。质谱分析作为传统蛋白质组学中最为核心的研究技术,由于其高灵敏、高通量、结构信息丰富等特点,在单细胞蛋白质组学研究中独树一帜。该文综述了近年来基于质谱的单细胞蛋白质组学研究中的代表性方法,根据质谱分析前蛋白质分离方式的差异,将其分为基于毛细管电泳分离、液相色谱分离和无分离手段的直接检测3类方法,在介绍研究现状的同时对这些方法在细胞通量、蛋白质鉴定数目、灵敏度以及方法应用方面进行了总结与比较。最后,基于目前研究中面临的挑战以及发展趋势对基于质谱的单细胞蛋白质组学的研究前景进行了展望。     

Simultaneous determination of glutathione and reactive oxygen species in individual cells by microchip electrophoresis

A microchip electrophoresis method was developed for simultaneous determination of reactive oxygen species (ROS) and reduced glutathione (GSH) in the individual erythrocyte cell. In this method, cell sampling, single-cell loading, docking, lysing, and capillary electrophoretic separation with LIF detection were integrated on a microfluidic chip with crossed channels. ROS was labeled with dihydrorhodamine 123 in the intact cell, while GSH was on-chip labeled with 2,3-naphthalene-dicarboxaldehyde, which was included in the separation medium. On-chip electrical lysis, characterized by extremely fast disruption of the cellular membrane (<40 ms), was exploited to minimize enzymatic effects on analyte concentrations during the determination. The microfluidic network was optimized to prevent cell leaking from the sample reservoir (S) into separation during the separation phase. The structure of the S was modified to avoid blockage of its outlet by deposited cells. Detection limits of 0.5 and 6.9 amol for ROS and GSH, respectively, were achieved. The average cell throughput was 25 cells/h. The effectiveness of the method was demonstrated in the simultaneous determination of GSH and ROS in individual cells and the variations of cellular GSH and ROS contents in response to external stimuli.     

Intact living-cell electrolaunching ionization mass spectrometry for single-cell metabolomics

While single-cell mass spectrometry can reveal cellular heterogeneity and the molecular mechanisms of intracellular biochemical reactions, its application is limited by the insufficient detection sensitivity resulting from matrix interference and sample dilution. Herein, we propose an intact living-cell electrolaunching ionization mass spectrometry (ILCEI-MS) method. A capillary emitter with a narrow-bore, constant-inner-diameter ensures that the entire living cell enters the MS ion-transfer tube. Inlet ionization improves sample utilization, and no solvent is required, preventing sample dilution and matrix interference. Based on these features, the detection sensitivity is greatly improved, and the average signal-to-noise (S/N) ratio is about 20 : 1 of single-cell peaks in the TIC of ILCEI-MS. A high detection throughput of 51 cells per min was achieved by ILCEI-MS for the single-cell metabolic profiling of multiple cell lines, and 368 cellular metabolites were identified. Further, more than 4000 primary single cells digested from the fresh multi-organ tissues of mice were detected by ILCEI-MS, demonstrating its applicability and reliability.

A novel living-cell mass spectrometry method allows a whole cell to enter entirely into the MS inlet and ionize with almost no sample dilution and matrix interference, which greatly improves the sensitivity of single-cell metabolite detection.     

微流控进样阿达玛变换显微荧光成像单细胞分析

将微流控芯片用于单细胞进样,以自制阿达玛变换显微荧光成像分析系统进行成像检测,讨论了影响单细胞进样和荧光成像的主要因素,并对花粉细胞DNA含量进行定量分析。结果表明：微流控进样技术与HT显微成像技术相结合,可有效可靠地应用于单细胞分析中,所测定的三个玉帘花粉的DNA含量分别为124．4、123．9和62．9pg。     

Development of a microfluidic platform for single-cell secretion analysis using a direct photoactive cell-attaching method

A precise understanding of individual cellular processes is essential to meet the expectations of most advanced cell biology. Therefore single-cell analysis is considered to be one of possible approach to overcome any misleading of cell characteristics by averaging large groups of cells in bulk conditions. In the present work, we modified a newly designed microchip for single-cell analysis and regulated the cell-adhesive area inside a cell-chamber of the microfluidic system. By using surface-modification techniques involving a silanization compound, a photo-labile linker and the 2-methacryloyloxyethyl phosphorylcholine (MPC) polymer were covalently bonded on the surface of a microchannel. The MPC polymer was utilized as a non-biofouling compound for inhibiting non-specific binding of the biological samples inside the microchannel, and was selectively removed by a photochemical reaction that controlled the cell attachment. To achieve the desired single-macrophage patterning and culture in the cell-chamber of the microchannel, the cell density and flow rate of the culture medium were optimized. We found that a cell density of 2.0 × 10(6) cells/ml was the appropriate condition to introduce a single cell in each cell chamber. Furthermore, the macrophage was cultured in a small size of the cell chamber in a safe way for 5 h at a flow rate of 0.2 μl/min under the medium condition. This strategy can be a powerful tool for broadening new possibilities in studies of individual cellular processes in a dynamic microfluidic device.     

微流控芯片测定单细胞内化学组分的进展

细胞是生命的基本单元。由于细胞的个体差异,传统分析群体细胞的方法难以得到单细胞的重要信息。准确可靠地测定单细胞内化学组分的含量能大大提高从正常细胞中辨别不正常细胞的能力,为进一步研究和发展生物化学、医学和临床检验等领域奠定基础。近年来,用微流控芯片进行单细胞分析已引起广泛的兴趣。微流控芯片可以集成单细胞进样、溶膜、电泳分离胞内化学组分和高灵敏度测定等一系列操作步骤,为分析单细胞内的化学组分提供了新的技术平台。本文主要综述了近年来微流控芯片测定单细胞内化学组分的进展。重点在于利用电渗流、压力结合电渗流和激光镊子等技术操控单细胞在微流控芯片上完成单细胞进样、溶膜、细胞内化学组分的电泳分离和高灵敏度测定等一系列操作步骤。对在微流控芯片上的衍生技术也做了较为详细的阐述。     

Single-cell recording and stimulation with a 16k micro-nail electrode array integrated on a 0.18 μm CMOS chip

To cope with the growing needs in research towards the understanding of cellular function and network dynamics, advanced micro-electrode arrays (MEAs) based on integrated complementary metal oxide semiconductor (CMOS) circuits have been increasingly reported. Although such arrays contain a large number of sensors for recording and/or stimulation, the size of the electrodes on these chips are often larger than a typical mammalian cell. Therefore, true single-cell recording and stimulation remains challenging. Single-cell resolution can be obtained by decreasing the size of the electrodes, which inherently increases the characteristic impedance and noise. Here, we present an array of 16,384 active sensors monolithically integrated on chip, realized in 0.18 μm CMOS technology for recording and stimulation of individual cells. Successful recording of electrical activity of cardiac cells with the chip, validated with intracellular whole-cell patch clamp recordings are presented, illustrating single-cell readout capability. Further, by applying a single-electrode stimulation protocol, we could pace individual cardiac cells, demonstrating single-cell addressability. This novel electrode array could help pave the way towards solving complex interactions of mammalian cellular networks.     

Recent advances in capillary electrophoretic analysis of individual cells

Because variability exists within populations of cells, single-cell analysis has become increasingly important for probing complex cellular environments. Capillary electrophoresis (CE) is an excellent technique for identifying and quantifying the contents of single cells owing to its small volume requirements and fast, efficient separations with highly sensitive detection. Recent progress in both whole-cell and subcellular sampling has allowed researchers to study cellular function in the areas of neuroscience, oncology, enzymology, immunology, and gene expression.      

Analysis of single mammalian cells on-chip

A goal of modern biology is to understand the molecular mechanisms underlying cellular function. The ability to manipulate and analyze single cells is crucial for this task. The advent of microengineering is providing biologists with unprecedented opportunities for cell handling and investigation on a cell-by-cell basis. For this reason, lab-on-a-chip (LOC) technologies are emerging as the next revolution in tools for biological discovery. In the current discussion, we seek to summarize the state of the art for conventional technologies in use by biologists for the analysis of single, mammalian cells, and then compare LOC devices engineered for these same single-cell studies. While a review of the technical progress is included, a major goal is to present the view point of the practicing biologist and the advances that might increase adoption by these individuals. The LOC field is expanding rapidly, and we have focused on areas of broad interest to the biology community where the technology is sufficiently far advanced to contemplate near-term application in biological experimentation. Focus areas to be covered include flow cytometry, electrophoretic analysis of cell contents, fluorescent-indicator-based analyses, cells as small volume reactors, control of the cellular microenvironment, and single-cell PCR.     

Dynamic metabolic change of cancer cells induced by natural killer cells at the single-cell level studied by label-free mass cytometry

Natural killer cells (NK cells) are important immune cells which have attracted increasing attention in cancer immunotherapy. Due to the heterogeneity of cells, individual cancer cells show different resistance to NK cytotoxicity, which has been revealed by flow cytometry. Here we used label-free mass cytometry (CyESI-MS) as a new tool to analyze the metabolites in Human Hepatocellular Carcinoma (HepG2) cells at the single-cell level after the interaction with different numbers of NK92 MI cells. A large amount of chemical information from individual HepG2 cells was obtained showing the process of cell apoptosis induced by NK cells. Nineteen metabolites which consecutively change during cell apoptosis were revealed by calculating their average relative intensity. Four metabolic pathways were impacted during cell apoptosis which hit 4 metabolites including glutathione (GSH), creatine, glutamic acid and taurine. We found that the HepG2 cells could be divided into two phenotypes after co-culturing with NK cells according to the bimodal distribution of concentration of these 4 metabolites. The correlation between metabolites and different apoptotic pathways in the early apoptosis cell group was established by the 4 metabolites at the single-cell level. This is a new idea of using single-cell specific metabolites to reveal the metabolic heterogeneity in cell apoptosis which would be a powerful means for evaluating the cytotoxicity of NK cells.

Label-free mass cytometry is utilized to study the dynamic metabolic change during apoptosis in HepG2 cells induced by NK92 MI cells at the single-cell level. The metabolic heterogeneity of individual HepG2 cells during apoptosis was revealed.     

Capillary sodium dodecyl sulfate-DALT electrophoresis of proteins in a single human cancer cell.

Capillary Sodium dodlecyl sulfate (SDS)-DALT an (abbreviation for Dalton) electrophoresis was applied to analysis of proteins in single HT29 human colon adenocarcinoma cells. A vacuum pulse was employed to introduce a single cell into the coated capillary. Once the cell was lysed, proteins were denatured with SDS, fluorescantly labeled with 3-(2-furoyl)-quinoline-2-carboxaldehyde (FQ), and then separated by using 8% pullulan as the sieving matrix. This method offers a few advantages for single-cell protein analysis. First, it provides reproducible separation of single-cell proteins according to their size. Based on comparison with the migration time of standard proteins, most components from a single HT29 cancer cell have molecular masses within the range of 10-100 kDa. Second, as a one-dimensional separation method, it gives fairly good resolution for proteins. Typically, around 30 protein components of a single HT29 cell were resolved, indicating that this method has similar peak capacity to SDS-polyacrylamide gel electrophoresis (PAGE). Third, this method shows high detection sensitivity and wide dynamic range, which is important because of the wide range of protein expression in living systems. Detection limits for standard proteins ranged from 10(-10) to 10(-11) M. Finally, this method provides much higher speed than classical gel electrophoresis methods, and it provides automated anlysis of cellular proteins at the single-cell level; the separation is complete in 30 min and the entire analysis takes approximately 45 min.     

Nanoelectrochemical architectures for high-spatial-resolution single cell analysis

The analysis of single cells instead of cell populations is important for characterizing cellular heterogeneity and elucidating the cellular signalling pathways. Nanoelectrodes have emerged as an increasingly important tool for biomolecule analyses at the single-cell level with high spatial or temporal resolution. Various electrochemical methods, such as amperometry and scanning electrochemical microscopy(SECM), have been applied. Research to date has focused on the development of new nanoelectrochemical architectures, such as arrays, to achieve higher spatial resolution and faster analysis rates for single-cell analysis. In this review, the fabrication of these new nanoelectrochemical architectures and their applications in high spatial resolution single-cell analyses are discussed. The recent progress of Chinese researchers is highlighted.     

Effective single-cell clustering through ensemble feature selection and similarity measurements

Single-cell RNA sequencing technologies have revolutionized biomedical research by providing an effective means to profile gene expressions in individual cells. One of the first fundamental steps to perform the in-depth analysis of single-cell sequencing data is cell type classification and identification. Computational methods such as clustering algorithms have been utilized and gaining in popularity because they can save considerable resources and time for experimental validations. Although selecting the optimal features (i.e., genes) is an essential process to obtain accurate and reliable single-cell clustering results, the computational complexity and dropout events that can introduce zero-inflated noise make this process very challenging. In this paper, we propose an effective single-cell clustering algorithm based on the ensemble feature selection and similarity measurements. We initially identify the set of potential features, then measure the cell-to-cell similarity based on the subset of the potentials through multiple feature sampling approaches. We construct the ensemble network based on cell-to-cell similarity. Finally, we apply a network-based clustering algorithm to obtain single-cell clusters. We evaluate the performance of our proposed algorithm through multiple assessments in real-world single-cell RNA sequencing datasets with known cell types. The results show that our proposed algorithm can identify accurate and consistent single-cell clustering. Moreover, the proposed algorithm takes relative expression as input, so it can easily be adopted by existing analysis pipelines. The source code has been made publicly available at https://github.com/jeonglab/scCLUE.     

Exploring the feasibility of bioaerosol analysis as a novel fingerprinting technique

The purpose of this review is to investigate the feasibility of bioaerosol fingerprinting based on current understanding of cellular debris (with emphasis on human-emitted particulates) in aerosols and arguments regarding sampling, sensitivity, separations, and detection schemes. Target aerosol particles include cellular material and proteins emitted by humans, animals, and plants and can be regarded as information-rich packets that carry biochemical information specific to the living organisms present where the sample is collected. In this work we discuss sampling and analysis techniques that can be integrated with molecular (e.g. protein)-detection procedures to properly assess the aerosolized cellular material of interest. Developing a detailed understanding of bioaerosol molecular profiles in different environments suggests exciting possibilities of bioaerosol analysis with applications ranging from military defense to medical diagnosis and wildlife identification