High-throughput, multiparameter analysis of single cells

Droplet Microfluidics for Current Cancer Research: From Single-Cell Analysis to 3D Cell Culture

Cancer is the second leading cause of death worldwide. Differences in drug resistance and treatment response caused by the heterogeneity of cancer cells are the primary reasons for poor cancer therapy outcomes in patients. In addition, current in vitro anticancer drug-screening methods rely on two-dimensional monolayer-cultured cancer cells, which cannot accurately predict drug behavior in vivo. Therefore, a powerful tool to study the heterogeneity of cancer cells and produce effective in vitro tumor models is warranted to leverage cancer research. Droplet microfluidics has become a powerful platform for the single-cell analysis of cancer cells and three-dimensional cell culture of in vitro tumor spheroids. In this review, we discuss the use of droplet microfluidics in cancer research. Droplet microfluidic technologies, including single- or double-emulsion droplet generation and passive- or active-droplet manipulation, are concisely discussed. Recent advances in droplet microfluidics for single-cell analysis of cancer cells, circulating tumor cells, and scaffold-free/based 3D cell culture of tumor spheroids have been systematically introduced. Finally, the challenges that must be overcome for the further application of droplet microfluidics in cancer research are discussed.

Single cell proteomics analysis of drug response shows its potential as a drug discovery platform

Single-cell analysis has clearly established itself in biology and biomedical fields as an invaluable tool that allows one to comprehensively understand the relationship between cells, including their types, states, transitions, trajectories, and spatial position. Scientific methods such as fluorescence labeling, nanoscale super-resolution microscopy, advances in single cell RNAseq and proteomics technologies, provide more detailed information about biological processes which were not evident with the analysis of bulk material. This new era of single-cell biology provides a better understanding of such complex biological systems as cancer, inflammation, immunity mechanism and aging processes, and opens the door into the field of drug response heterogeneity. The latest discoveries of cellular heterogeneity gives us a unique understanding of complex biological processes, such as disease mechanism, and will lead to new strategies for better and personalized treatment strategies. Recently, single-cell proteomics techniques that allow quantification of thousands of proteins from single mammalian cells have been introduced. Here we present an improved single-cell mass spectrometry-based proteomics platform called SCREEN (Single Cell pRotEomE aNalysis) for deep and high-throughput single-cell proteome coverage with high efficiency, less turnaround time and with an improved ability for protein quantitation across more cells than previously achieved. We applied this new platform to analyze the single-cell proteomic landscape under different drug treatment over time to uncover heterogeneity in cancer cell response, which for the first time, to our knowledge, has been achieved by mass spectrometry based analytical methods. We discuss challenges in single-cell proteomics, future improvements and general trends with the goal to encourage forthcoming technical developments.

Optofluidic Flow Cytometer with In-Plane Spherical Mirror for Signal Enhancement

Statistical analysis of the properties of single microparticles, such as cells, bacteria or plastic slivers, has attracted increasing interest in recent years. In this regard, field flow cytometry is considered the gold standard technique, but commercially available instruments are bulky, expensive, and not suitable for use in point-of-care (PoC) testing. Microfluidic flow cytometers, on the other hand, are small, cheap and can be used for on-site analyses. However, in order to detect small particles, they require complex geometries and the aid of external optical components. To overcome these limitations, here, we present an opto-fluidic flow cytometer with an integrated 3D in-plane spherical mirror for enhanced optical signal collection. As a result, the signal-to-noise ratio is increased by a factor of six, enabling the detection of particle sizes down to 1.5 µm. The proposed optofluidic detection scheme enables the simultaneous collection of particle fluorescence and scattering using a single optical fiber, which is crucial to easily distinguishing particle populations with different optical properties. The devices have been fully characterized using fluorescent polystyrene beads of different sizes. As a proof of concept for potential real-world applications, signals from fluorescent HEK cells and Escherichia coli bacteria were analyzed.

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.

Improved single-cell genome amplification by a high-efficiency phi29 DNA polymerase

Single-cell genomic whole genome amplification (WGA) is a crucial step in single-cell sequencing, yet its low amplification efficiency, incomplete and uneven genome amplification still hinder the throughput and efficiency of single-cell sequencing workflows. Here we introduce a process called Improved Single-cell Genome Amplification (iSGA), in which the whole single-cell sequencing cycle is completed in a high-efficient and high-coverage manner, through phi29 DNA polymerase engineering and process engineering. By establishing a disulfide bond of F137C-A377C, the amplification ability of the enzyme was improved to that of single-cell. By further protein engineering and process engineering, a supreme enzyme named HotJa Phi29 DNA Polymerase was developed and showed significantly better coverage (99.75%) at a higher temperature (40°C). High single-cell genome amplification ability and high coverage (93.59%) were also achieved for commercial probiotic samples. iSGA is more efficient and robust than the wild-type phi29 DNA polymerase, and it is 2.03-fold more efficient and 10.89-fold cheaper than the commercial Thermo Scientific EquiPhi29 DNA Polymerase. These advantages promise its broad applications in large-scale single-cell sequencing.

Microfluidic flow cytometry for blood-based biomarker analysis

Flow cytometry has proven its capability for rapid and quantitative analysis of individual cells and the separation of targeted biological samples from others. The emerging microfluidics technology makes it possible to develop portable microfluidic diagnostic devices for point-of-care testing (POCT) applications. Microfluidic flow cytometry (MFCM), where flow cytometry and microfluidics are combined to achieve similar or even superior functionalities on microfluidic chips, provides a powerful single-cell characterisation and sorting tool for various biological samples. In recent years, researchers have made great progress in the development of the MFCM including focusing, detecting, and sorting subsystems, and its unique capabilities have been demonstrated in various biological applications. Moreover, liquid biopsy using blood can provide various physiological and pathological information. Thus, biomarkers from blood are regarded as meaningful circulating transporters of signal molecules or particles and have great potential to be used as non (or minimally)-invasive diagnostic tools. In this review, we summarise the recent progress of the key subsystems for MFCM and its achievements in blood-based biomarker analysis. Finally, foresight is offered to highlight the research challenges faced by MFCM in expanding into blood-based POCT applications, potentially yielding commercialisation opportunities.

From imaging a single cell to implementing precision medicine: an exciting new era

In the age of high-throughput, single-cell biology, single-cell imaging has evolved not only in terms of technological advancements but also in its translational applications. The synchronous advancements of imaging and computational biology have produced opportunities of merging the two, providing the scientific community with tools towards observing, understanding, and predicting cellular and tissue phenotypes and behaviors. Furthermore, multiplexed single-cell imaging and machine learning algorithms now enable patient stratification and predictive diagnostics of clinical specimens. Here, we provide an overall summary of the advances in single-cell imaging, with a focus on high-throughput microscopy phenomics and multiplexed proteomic spatial imaging platforms. We also review various computational tools that have been developed in recent years for image processing and downstream applications used in biomedical sciences. Finally, we discuss how harnessing systems biology approaches and data integration across disciplines can further strengthen the exciting applications and future implementation of single-cell imaging on precision medicine.

Single-cell transcriptomics allows novel insights into aging and circadian processes

Aging and circadian rhythms are two biological processes that affect an organism, although at different time scales. Nevertheless, due to the overlap of their actions, it was speculated that both interfere or interact with each other. However, to address this question, a much deeper insight into these processes is necessary, especially at the cellular level. New methods such as single-cell RNA-sequencing (scRNA-Seq) have the potential to close this gap in our knowledge. In this review, we analyze applications of scRNA-Seq from the aging and circadian rhythm fields and highlight new findings emerging from the analysis of single cells, especially in humans or rodents. Furthermore, we judge the potential of scRNA-Seq to identify common traits of both processes. Overall, this method offers several advantages over more traditional methods analyzing gene expression and will become an important tool to unravel the link between these biological processes.

Technological Advances in Multiscale Analysis of Single Cells in Biomedicine

Single-cell analysis has recently received significant attention in biomedicine. With the advances in super-resolution microscopy, fluorescence labeling, and nanoscale biosensing, new information may be obtained for the design of cancer diagnosis and therapeutic interventions. The discovery of cellular heterogeneity further stresses the importance of single-cell analysis to improve our understanding of disease mechanism and to develop new strategies for disease treatment. To this end, many studies are exploited at the single-cell level for high throughput, highly parallel, and quantitative analysis. Technically, microfluidics are also designed to facilitate single-cell isolation and enrichment for downstream detection and manipulation in a robust, sensitive, and automated manner. Further achievements are made possible by consolidating optically label-free, electrical, and molecular sensing techniques. Moreover, these technologies are coupled with computing algorithms for high throughput and automated quantitative analysis with a short turnaround time. To reflect on how the technological developments have advanced single-cell analysis, this mini-review is aimed to offer readers an introduction to single-cell analysis with a brief historical development and the recent progresses that have enabled multiscale analysis of single-cells in the last decade. The challenges and future trends are also discussed with the view to inspire forthcoming technical developments.

Novel computational model of gastrula morphogenesis to identify spatial discriminator genes by self-organizing map (SOM) clustering

Deciphering the key mechanisms of morphogenesis during embryonic development is crucial to understanding the guiding principles of the body plan and promote applications in biomedical research fields. Although several computational tissue reconstruction methods using cellular gene expression data have been proposed, those methods are insufficient with regard to arranging cells in their correct positions in tissues or organs unless spatial information is explicitly provided. Here, we report SPRESSO, a new in silico three-dimensional (3D) tissue reconstruction method using stochastic self-organizing map (stochastic-SOM) clustering, to estimate the spatial domains of cells in tissues or organs from only their gene expression profiles. With only five gene sets defined by Gene Ontology (GO), we successfully demonstrated the reconstruction of a four-domain structure of mid-gastrula mouse embryo (E7.0) with high reproducibility (success rate = 99%). Interestingly, the five GOs contain 20 genes, most of which are related to differentiation and morphogenesis, such as activin A receptor and Wnt family member genes. Further analysis indicated that Id2 is the most influential gene contributing to the reconstruction. SPRESSO may provide novel and better insights on the mechanisms of 3D structure formation of living tissues via informative genes playing a role as spatial discriminators.

From observing to predicting single-cell structure and function with high-throughput/high-content microscopy

In the past 15 years, cell-based microscopy has evolved its focus from observing cell function to aiming to predict it. In particular-powered by breakthroughs in computer vision, large-scale image analysis and machine learning-high-throughput and high-content microscopy imaging have enabled to uniquely harness single-cell information to systematically discover and annotate genes and regulatory pathways, uncover systems-level interactions and causal links between cellular processes, and begin to clarify and predict causal cellular behaviour and decision making. Here we review these developments, discuss emerging trends in the field, and describe how single-cell 'omics and single-cell microscopy are imminently in an intersecting trajectory. The marriage of these two fields will make possible an unprecedented understanding of cell and tissue behaviour and function.

Recent advances in single-cell analysis by mass spectrometry

Cells are the most basic structural units that play vital roles in the functioning of living organisms. Analysis of the chemical composition and content of a single cell plays a vital role in ensuring precise investigations of cellular metabolism, and is a crucial aspect of lipidomic and proteomic studies. In addition, structural knowledge provides a better understanding of cell behavior as well as the cellular and subcellular mechanisms. However, single-cell analysis can be very challenging due to the very small size of each cell as well as the large variety and extremely low concentrations of substances found in individual cells. On account of its high sensitivity and selectivity, mass spectrometry holds great promise as an effective technique for single-cell analysis. Numerous mass spectrometric techniques have been developed to elucidate the molecular profiles at the cellular level, including electrospray ionization mass spectrometry (ESI-MS), secondary ion mass spectrometry (SIMS), laser-based mass spectrometry and inductively coupled plasma mass spectrometry (ICP-MS). In this review, the recent advances in single-cell analysis by mass spectrometry are summarized. The strategies of different ionization modes to achieve single-cell analysis are classified and discussed in detail.

True one cell chemical analysis: a review

The constantly growing field of True One Cell (TOC) analysis has provided important information on the direct chemical composition of various cells and cellular components.

New advances in microfluidic flow cytometry

In recent years, researchers are paying the increasing attention to the development of portable microfluidic diagnostic devices including microfluidic flow cytometry for the point-of-care testing. Microfluidic flow cytometry, where microfluidics and flow cytometry work together to realize novel functionalities on the microchip, provides a powerful tool for measuring the multiple characteristics of biological samples. The development of a portable, low-cost, and compact flow cytometer can benefit the health care in underserved areas such as Africa or Asia. In this article, we review recent advancements of microfluidics including sample pumping, focusing and sorting, novel detection approaches, and data analysis in the field of flow cytometry. The challenge of microfluidic flow cytometry is also examined briefly.

Coarse-graining bacteria colonies for modelling critical solute distributions in picolitre bioreactors for bacterial studies on single-cell level

Microfluidic single‐cell bioreactors have found widespread application to investigate growth and gene expression of microbial model organisms, but yet there are few attempts to systematically characterize different design and cultivation concepts. Quantitative measurements of critical solute concentrations, e.g. limiting nutrients, are not yet feasible within the typical volumes in the range of picolitres. A way to gain new insights about the mass transport within those volumes is by simulation, but the complex geometry resulting from the multitude of cells within a colony leads to time and resource consuming computational challenges. In this work, six different concepts for the model representation of cellular microcolonies within microfluidic monolayer growth chamber devices are compared. The Gini coefficient is proposed as new measure for inhomogeneity within cellular colonies. An example cell colony is represented by a single point source, a cylindrical volume with homogeneous reaction rates with and without adjusted diffusion coefficient, as point sources for each single cell and as rod‐shaped, diffusion blocking, three‐dimensional cells with varying shapes. Simulated concentration profiles across the chambers depended strongly on the chosen cell representation. The representation with the lowest degree of abstraction, three‐dimensional cells, leads to complex geometries and high computational effort, but also gives a conservative and therefore preferable estimate for the cultivation conditions within a given cultivation chamber geometry. Interestingly, the cylindrical volume with adjusted diffusion coefficient gives similar results but requires far less computational effort. Therefore, it is proposed to use the three‐dimensional cells for detailed studies and to determine parameters for the cylindrical volume with adjusted diffusion coefficient, which can then be used for experimental design, screening of parameter spaces, and similar applications.

Microfluidic Platform for Parallel Single Cell Analysis for Diagnostic Applications

Cell populations are heterogeneous: they can comprise different cell types or even cells at different stages of the cell cycle and/or of biological processes. Furthermore, molecular processes taking place in cells are stochastic in nature. Therefore, cellular analysis must be brought down to the single cell level to get useful insight into biological processes, and to access essential molecular information that would be lost when using a cell population analysis approach. Furthermore, to fully characterize a cell population, ideally, information both at the single cell level and on the whole cell population is required, which calls for analyzing each individual cell in a population in a parallel manner. This single cell level analysis approach is particularly important for diagnostic applications to unravel molecular perturbations at the onset of a disease, to identify biomarkers, and for personalized medicine, not only because of the heterogeneity of the cell sample, but also due to the availability of a reduced amount of cells, or even unique cells. This chapter presents a versatile platform meant for the parallel analysis of individual cells, with a particular focus on diagnostic applications and the analysis of cancer cells. We first describe one essential step of this parallel single cell analysis protocol, which is the trapping of individual cells in dedicated structures. Following this, we report different steps of a whole analytical process, including on-chip cell staining and imaging, cell membrane permeabilization and/or lysis using either chemical or physical means, and retrieval of the cell molecular content in dedicated channels for further analysis. This series of experiments illustrates the versatility of the herein-presented platform and its suitability for various analysis schemes and different analytical purposes.

SU-8 free-standing microfluidic probes

We present a process for fabrication of free-standing SU-8 probes, with a dry, mechanical release of the final micro-devices. The process utilizes the thermal release tape, a commonly used cleanroom material, for facile heat-release from the sacrificial layer. For characterization of the SU-8 microfluidic probes, two liquid interfaces were designed: a disposable interface with integrated wells and an interface with external liquid reservoirs. The versatility of the fabrication and the release procedures was illustrated by further developing the process to functionalize the SU-8 probes for impedance sensing, by integrating metal thin-film electrodes. An additional interface scheme which contains electronic components for impedance measurements was developed. We investigated the possibilities of introducing perforations in the SU-8 device by photolithography, for solution sampling predominantly by diffusion. The SU-8 processes described here allow for a convenient batch production of versatile free-standing microfluidic devices with well-defined tip-geometry.

Single Cell Isolation and Analysis

Individual cell heterogeneity within a population can be critical to its peculiar function and fate. Subpopulations studies with mixed mutants and wild types may not be as informative regarding which cell responds to which drugs or clinical treatments. Cell to cell differences in RNA transcripts and protein expression can be key to answering questions in cancer, neurobiology, stem cell biology, immunology, and developmental biology. Conventional cell-based assays mainly analyze the average responses from a population of cells, without regarding individual cell phenotypes. To better understand the variations from cell to cell, scientists need to use single cell analyses to provide more detailed information for therapeutic decision making in precision medicine. In this review, we focus on the recent developments in single cell isolation and analysis, which include technologies, analyses and main applications. Here, we summarize the historical background, limitations, applications, and potential of single cell isolation technologies.

Development of Droplet Microfluidics Enabling High-Throughput Single-Cell Analysis

This article reviews recent developments in droplet microfluidics enabling high-throughput single-cell analysis. Five key aspects in this field are included in this review: (1) prototype demonstration of single-cell encapsulation in microfluidic droplets; (2) technical improvements of single-cell encapsulation in microfluidic droplets; (3) microfluidic droplets enabling single-cell proteomic analysis; (4) microfluidic droplets enabling single-cell genomic analysis; and (5) integrated microfluidic droplet systems enabling single-cell screening. We examine the advantages and limitations of each technique and discuss future research opportunities by focusing on key performances of throughput, multifunctionality, and absolute quantification.

AirLab: a cloud-based platform to manage and share antibody-based single-cell research

Single-cell analysis technologies are essential tools in research and clinical diagnostics. These methods include flow cytometry, mass cytometry, and other microfluidics-based technologies. Most laboratories that employ these methods maintain large repositories of antibodies. These ever-growing collections of antibodies, their multiple conjugates, and the large amounts of data generated in assays using specific antibodies and conditions makes a dedicated software solution necessary. We have developed AirLab, a cloud-based tool with web and mobile interfaces, for the organization of these data. AirLab streamlines the processes of antibody purchase, organization, and storage, antibody panel creation, results logging, and antibody validation data sharing and distribution. Furthermore, AirLab enables inventory of other laboratory stocks, such as primers or clinical samples, through user-controlled customization. Thus, AirLab is a mobile-powered and flexible tool that harnesses the capabilities of mobile tools and cloud-based technology to facilitate inventory and sharing of antibody and sample collections and associated validation data.

Single cell studies of mouse embryonic stem cell (mESC) differentiation by electrical impedance measurements in a microfluidic device

Biological populations of cells show considerable cell-to-cell variability. Study of single cells and analysis of cell heterogeneity are considered to be critical in understanding biological processes such as stem cell differentiation and cancer development. Recent advances in lab-on-a-chip techniques have allowed single-cell capture in microfluidic channels with the possibility of precise environmental control and high throughput of experiments with minimal usage of samples and reagents. In recent years, label-free techniques such as electrical impedance spectroscopy have emerged as a non-invasive approach to studying cell properties. In this study, we have designed and fabricated a microfluidic device that combines hydrodynamic trapping of single cells in pre-defined locations with the capability of running electrical impedance measurements within the same device. We have measured mouse embryonic stem cells (mESCs) at different states during differentiation (t=0h, 24h and 48h) and quantitatively analysed the changes in electrical parameters of cells during differentiation. A marked increase in the magnitude of the cell impedance is found during cell differentiation, which can be attributed to an increase in cell size. The analysis of the measurements shows that the nucleus-to-cytoplasm ratio decreases during this process. The degree of cell heterogeneity is observed to be the highest when the cells are at the transition state (24h), compare with cells at undifferentiated (0h) and fully differentiated (48h) states. The device enables highly efficient single cell trapping and provides sensitive, label-free electrical impedance measurements of individual cells, enabling the possibility of quantitatively analysing their physical state as well as studying the associated heterogeneity of a cell population.

Tools for Single-Cell Kinetic Analysis of Virus-Host Interactions

Measures of cellular gene expression or behavior, when performed on individual cells, inevitably reveal a diversity of behaviors and outcomes that can correlate with normal or diseased states. For virus infections, the potential diversity of outcomes are pushed to an extreme, where measures of infection reflect features of the specific infecting virus particle, the individual host cell, as well as interactions between viral and cellular components. Single-cell measures, while revealing, still often rely on specialized fluid handling capabilities, employ end-point measures, and remain labor-intensive to perform. To address these limitations, we consider a new microwell-based device that uses simple pipette-based fluid handling to isolate individual cells. Our design allows different experimental conditions to be implemented in a single device, permitting easier and more standardized protocols. Further, we utilize a recently reported dual-color fluorescent reporter system that provides dynamic readouts of viral and cellular gene expression during single-cell infections by vesicular stomatitis virus. In addition, we develop and show how free, open-source software can enable streamlined data management and batch image analysis. Here we validate the integration of the device and software using the reporter system to demonstrate unique single-cell dynamic measures of cellular responses to viral infection.

Three-dimensional hydrodynamic focusing microfluidic emitter: a strategy to inhibit sample ion expansion in nanoelectrospray ionization

A proposed 3D HFNE was used to generate a wrapped electrospray to achieve the inhibition of sample ion expansion, thus restraining injection loss in electrospray ionization.

Au@pNIPAM SERRS Tags for Multiplex Immunophenotyping Cellular Receptors and Imaging Tumor Cells

Detection technologies employing optically encoded particles have gained much interest toward clinical diagnostics and drug discovery, but the portfolio of available systems is still limited. The fabrication and characterization of highly stable surface-enhanced resonance Raman scattering (SERRS)-encoded colloids for the identification and imaging of proteins expressed in cells are reported. These plasmonic nanostructures are made of gold octahedra coated with poly(N-isopropylacrylamide) microgels and can be readily encoded with Raman active dyes while retaining high colloidal stability in biofluids. A layer-by-layer polyelectrolyte coating is used to seal the outer surface of the encoded particles and to provide a reactive surface for covalent conjugation with antibodies. The targeted multiplexing capabilities of the SERRS tags are demonstrated by the simultaneous detection and imaging of three tumor-associated surface biomarkers: epidermal growth factor receptor (EGFR), epithelial cell adhesion molecule (EpCAM), and homing cell adhesion molecule (CD44) by SERRS spectroscopy. The plasmonic microgels are able to discriminate tumor A431 (EGFR+/EpCAM+/CD44+) and nontumor 3T3 2.2 (EGFR-/EpCAM-/CD44+) cells while cocultured in vitro.