Introduction: why analyze single cells?

Dielectrophoretic Traps for Efficient Bead and Cell Trapping and Formation of Aggregates of Controlled Size and Composition

We present a microfluidic dielectrophoretic-actuated system designed to trap chosen single-cell and form controlled cell aggregates. A novel method is proposed to characterize the efficiency of the dielectrophoretic trapping, considering the flow speed but also the heat generated by the traps as limiting criteria in cell-safe manipulation. Two original designs with different manufacturing processes are experimentally compared. The most efficient design is selected and the cell membrane integrity is monitored by fluorescence imaging to guarantee a safe-cell trapping. Design rules are suggested to adapt the traps to multiple-cells trapping and are experimentally validated as we formed aggregates of controlled size and composition with two different types of cells. We provide hereby a simple manufactured tool allowing the controlled manipulation of particles for the composition of multicellular assemblies.

Sorting single-cell microcarriers using commercial flow cytometers

The scale of biological discovery is driven by the vessels in which we can perform assays and analyze results, from multi-well plates to microfluidic compartments. We report on the compatibility of sub-nanoliter single-cell containers or "nanovials" with commercial fluorescence activated cell sorters (FACS). This recent lab on a particle approach utilizes 3D structured microparticles to isolate cells and perform single-cell assays at scale with existing lab equipment. Use of flow cytometry led to detection of fluorescently labeled protein with dynamic ranges spanning 2-3 log and detection limits down to ∼10,000 molecules per nanovial, which was the lowest amount tested. Detection limits were improved compared to fluorescence microscopy measurements using a 20X objective and a cooled CMOS camera. Nanovials with diameters between 35-85 µm could also be sorted with purity from 99-93% on different commercial instruments at throughputs up to 800 events/second. Cell-loaded nanovials were found to have unique forward and side (or back) scatter signatures that enabled gating of cell-containing nanovials using scatter metrics alone. The compatibility of nanovials with widely-available commercial FACS instruments promises to democratize single-cell assays used in discovery of antibodies and cell therapies, by enabling analysis of single cells based on secreted products and leveraging the unmatched analytical capabilities of flow cytometers to sort important clones.

Magnetically Single-Cell Virus Stamping

Single-cell engineering via virus based genetic manipulation allows the possibility of understanding of complex tissues. However, current delivery methods for the genetic engineering of single cells via viral transduction suffer from limitations that restrict their application. Here I present a protocol describing a precise technique which can be used for the targeted virus infection of single cells in a monolayer of cells that is optically accessible. The protocol, demonstrated here by stamping cultured Hela cells with lentiviruses (LVs), completes in a few minutes and allows stable transgene expression within a few days, at success rates approaching 80%.

Development overview of Raman-activated cell sorting devoted to bacterial detection at single-cell level

Understanding the metabolic interactions between bacteria in natural habitat at the single-cell level and the contribution of individual cell to their functions is essential for exploring the dark matter of uncultured bacteria. The combination of Raman-activated cell sorting (RACS) and single-cell Raman spectra (SCRS) with unique fingerprint characteristics makes it possible for research in the field of microbiology to enter the single cell era. This review presents an overview of current knowledge about the research progress of recognition and assessment of single bacterium cell based on RACS and further research perspectives. We first systematically summarize the label-free and non-destructive RACS strategies based on microfluidics, microdroplets, optical tweezers, and specially made substrates. The importance of RACS platforms in linking target cell genotype and phenotype is highlighted and the approaches mentioned in this paper for distinguishing single-cell phenotype include surface-enhanced Raman scattering (SERS), biomarkers, stable isotope probing (SIP), and machine learning. Finally, the prospects and challenges of RACS in exploring the world of unknown microorganisms are discussed. KEY POINTS: • Analysis of single bacteria is essential for further understanding of the microbiological world. • Raman-activated cell sorting (RACS) systems are significant protocol for characterizing phenotypes and genotypes of individual bacteria.

MAGNETOPHORETIC CIRCUIT BIOCOMPATIBILITY

Recently, we introduced magnetophoretic circuits, composed of overlaid magnetic and metallic layers, as a novel single-cell analysis (SCA) tool. We showed the ability of these circuits in organizing large single-particle and particle-pair arrays. Assembling the cells in microarrays is performed with the ultimate goal of running temporal phenotypic analyses. However, for long-term studies, a suitable microenvironment for the cells to normally grow and differentiate is needed. Towards this goal, in this study, we run required biocompatibility tests, based on which we make the magnetophoretic-based microchip a suitable home for the cells to grow. The results confirm the ability of these chips in cell handling and show no unwanted cell behavior alteration due to the applied shear stress on them, the magnetic labeling, or the microenvironment. After this achievement, this tool would be ready for running important single-cell studies in oncology, virology, and medicine.

Automated image analysis system for studying cardiotoxicity in human pluripotent stem cell-Derived cardiomyocytes

BACKGROUND

Cardiotoxicity, characterized by severe cardiac dysfunction, is a major problem in patients treated with different classes of anticancer drugs. Development of predictable human-based models and assays for drug screening are crucial for preventing potential drug-induced adverse effects. Current animal in vivo models and cell lines are not always adequate to represent human biology. Alternatively, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) show great potential for disease modelling and drug-induced toxicity screenings. Fully automated high-throughput screening of drug toxicity on hiPSC-CMs by fluorescence image analysis is, however, very challenging, due to clustered cell growth patterns and strong intracellular and intercellular variation in the expression of fluorescent markers.

RESULTS

In this paper, we report on the development of a fully automated image analysis system for quantification of cardiotoxic phenotypes from hiPSC-CMs that are treated with various concentrations of anticancer drugs doxorubicin or crizotinib. This high-throughput system relies on single-cell segmentation by nuclear signal extraction, fuzzy C-mean clustering of cardiac α-actinin signal, and finally nuclear signal propagation. When compared to manual segmentation, it generates precision and recall scores of 0.81 and 0.93, respectively.

CONCLUSIONS

Our results show that our fully automated image analysis system can reliably segment cardiomyocytes even with heterogeneous α-actinin signals.

Technologies for the Directed Evolution of Cell Therapies

The next generation of therapies is moving beyond the use of small molecules and proteins to using whole cells. Compared with the interactions of small-molecule drugs with biomolecules, which can largely be understood through chemistry, cell therapies act in a chemical and physical world and can actively adapt to that world, amplifying complexity but also the potential for truly breakthrough impact. Although there has been success in introducing targeting proteins into cells to achieve a therapeutic effect, for example, chimeric antigen receptor (CAR) T cells, our ability to engineer cells is generally limited to introducing proteins, but not modulating large-scale traits or structures of cellular "machines," which play critical roles in disease. Example traits include the ability to secrete compounds, deform through tissue, adhere to surrounding cells, apply force to phagocytose targets, or move through extracellular matrix. There is an opportunity to increase the efficacy of cell therapies through the use of quantitative automation tools, to analyze, sort, and select rare cells with beneficial traits. Combined with methods of genetic or epigenetic mutagenesis to create diversity, such approaches can enable the directed cellular evolution of new therapeutically optimal populations of cells and uncover genetic underpinnings of these optimal traits.

Profiling Single Cancer Cells with Volatolomics Approach

Single-cell analysis is a rapidly evolving to characterize molecular information at the individual cell level. Here, we present a new approach with the potential to overcome several key challenges facing the currently available techniques. The approach is based on the identification of volatile organic compounds (VOCs), viz. organic compounds having relatively high vapor pressure, emitted to the cell's headspace. This concept is demonstrated using lung cancer cells with various p53 genetic status and normal lung cells. The VOCs were analyzed by gas chromatography combined with mass spectrometry. Among hundreds of detected compounds, 18 VOCs showed significant changes in their concentration levels in tumor cells versus control. The composition of these VOCs was found to depend, also, on the sub-molecular structure of the p53 genetic status. Analyzing the VOCs offers a complementary way of querying the molecular mechanisms of cancer as well as of developing new generation(s) of biomedical approaches for personalized screening and diagnosis.

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Measurement of VOCs was achieved at the single-cell level

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Genetic changes influence the emitted volatiles of single and bulk cancer cells

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Single-cell VOC analysis measures population heterogeneity in initial stage of tumors

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Volatolomics research can promote non-invasive, simple, and cost-effective diagnostics

Label-Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy

Characterization of single cell metabolism is imperative for understanding subcellular functional and biochemical changes associated with healthy tissue development and the progression of numerous diseases. However, single-cell analysis often requires the use of fluorescent tags and cell lysis followed by genomic profiling to identify the cellular heterogeneity. Identifying individual cells in a noninvasive and label-free manner is crucial for the detection of energy metabolism which will discriminate cell types and most importantly critical for maintaining cell viability for further analysis. Here, we have developed a robust assay using the droplet microfluidic technology together with the phasor approach to fluorescence lifetime imaging microscopy to study cell heterogeneity within and among the leukemia cell lines (K-562 and Jurkat). We have extended these techniques to characterize metabolic differences between proliferating and quiescent cells-a critical step toward label-free single cancer cell dormancy research. The result suggests a droplet-based noninvasive and label-free method to distinguish individual cells based on their metabolic states, which could be used as an upstream phenotypic platform to correlate with genomic statistics. © 2018 International Society for Advancement of Cytometry.

Biomedical Applications of Untethered Mobile Milli/Microrobots

Untethered robots miniaturized to the length scale of millimeter and below attract growing attention for the prospect of transforming many aspects of health care and bioengineering. As the robot size goes down to the order of a single cell, previously inaccessible body sites would become available for high-resolution in situ and in vivo manipulations. This unprecedented direct access would enable an extensive range of minimally invasive medical operations. Here, we provide a comprehensive review of the current advances in biome dical untethered mobile milli/microrobots. We put a special emphasis on the potential impacts of biomedical microrobots in the near future. Finally, we discuss the existing challenges and emerging concepts associated with designing such a miniaturized robot for operation inside a biological environment for biomedical applications.

Self-folding single cell grippers

Given the heterogeneous nature of cultures, tumors, and tissues, the ability to capture, contain, and analyze single cells is important for genomics, proteomics, diagnostics, therapeutics, and surgery. Moreover, for surgical applications in small conduits in the body such as in the cardiovascular system, there is a need for tiny tools that approach the size of the single red blood cells that traverse the blood vessels and capillaries. We describe the fabrication of arrayed or untethered single cell grippers composed of biocompatible and bioresorbable silicon monoxide and silicon dioxide. The energy required to actuate these grippers is derived from the release of residual stress in 3-27 nm thick films, did not require any wires, tethers, or batteries, and resulted in folding angles over 100° with folding radii as small as 765 nm. We developed and applied a finite element model to predict these folding angles. Finally, we demonstrated the capture of live mouse fibroblast cells in an array of grippers and individual red blood cells in untethered grippers which could be released from the substrate to illustrate the potential utility for in vivo operations.

Continuous-flow cytomorphological staining and analysis

Cells suspended in bodily fluids are routinely analyzed by cytopathologists as a means of diagnosing malignancies and other diseases. The physical and morphological properties of these suspended cells are evaluated in making diagnostic decisions, which often requires manual concentration, staining, and washing procedures to extract information about intracellular architecture. The need to manually prepare slides for analysis by a cytopathologist is a labor-intensive process, which is ripe for additional automation to reduce costs but also to potentially provide more repeatable and improved accuracy in diagnoses. We have developed a microfluidic system to perform several steps in the preparation of samples for cytopathology that (i) automates colorimetric staining on-chip, and (ii) images cells in flow, as well as provides (iii) additional quantitative analyses of captured images to aid cytopathologists. A flow-through approach provides benefits by allowing staining and imaging to be performed in a continuous, integrated manner, which also overcomes previous challenges with in-suspension colorimetric staining. We envision such a tool may reduce costs and aid cytopathologists in identifying rare or characteristic cells of interest by providing isolated images along with quantitative metrics on single cells from various rotational angles, allowing efficient determination of disease etiology.

Nuclear mechanics in cancer

Despite decades of research, cancer metastasis remains an incompletely understood process that is as complex as it is devastating. In recent years, there has been an increasing push to investigate the biomechanical aspects of tumorigenesis, complementing the research on genetic and biochemical changes. In contrast to the high genetic variability encountered in cancer cells, almost all metastatic cells are subject to the same physical constraints as they leave the primary tumor, invade surrounding tissues, transit through the circulatory system, and finally infiltrate new tissues. Advances in live cell imaging and other biophysical techniques, including measurements of subcellular mechanics, have yielded stunning new insights into the physics of cancer cells. While much of this research has been focused on the mechanics of the cytoskeleton and the cellular microenvironment, it is now emerging that the mechanical properties of the cell nucleus and its connection to the cytoskeleton may play a major role in cancer metastasis, as deformation of the large and stiff nucleus presents a substantial obstacle during the passage through the dense interstitial space and narrow capillaries. Here, we present an overview of the molecular components that govern the mechanical properties of the nucleus, and we discuss how changes in nuclear structure and composition observed in many cancers can modulate nuclear mechanics and promote metastatic processes. Improved insights into this interplay between nuclear mechanics and metastatic progression may have powerful implications in cancer diagnostics and therapy and may reveal novel therapeutic targets for pharmacological inhibition of cancer cell invasion.

Mechanical stiffness as an improved single-cell indicator of osteoblastic human mesenchymal stem cell differentiation

Although it has been established that cellular stiffness can change as a stem cell differentiates, the precise relationship between cell mechanics and other phenotypic properties remains unclear. Inherent cell heterogeneity and asynchronous differentiation complicate population analysis; therefore, single-cell analysis was employed to determine how changes in cell stiffness correlate with changes in molecular biomarkers during differentiation. Design of a custom gridded tissue culture dish facilitated single-cell comparisons between cell mechanics and other differentiation biomarkers by enabling sequential measurement of cell mechanics and protein biomarker expression at the single cell level. The Young's modulus of mesenchymal stem cells was shown not only to decrease during chemically-induced osteoblast differentiation, but also to correlate more closely with the day of differentiation than did the relative expression of the traditional osteoblast differentiation markers, bone sialoprotein and osteocalcin. Therefore, cell stiffness, a measurable property of individual cells, may serve as an improved indicator of single-cell osteoblast differentiation compared to traditional biological markers. Revelation of additional osteoblast differentiation indicators, such as cell stiffness, can improve identification and collection of starting cell populations, with applications to mesenchymal stem cell therapies and stem cell-based tissue engineering.

Ultrasound assisted particle and cell manipulation on-chip

Ultrasonic fields are able to exert forces on cells and other micron-scale particles, including microbubbles. The technology is compatible with existing lab-on-chip techniques and is complementary to many alternative manipulation approaches due to its ability to handle many cells simultaneously over extended length scales. This paper provides an overview of the physical principles underlying ultrasonic manipulation, discusses the biological effects relevant to its use with cells, and describes emerging applications that are of interest in the field of drug development and delivery on-chip.

Detection of low abundance RNA molecules in individual cells by flow cytometry

A variety of RNA analysis technologies are available for the detection of RNA transcripts from bulk cell populations. However, the techniques for RNA detection from individual cells have been limited. Here we adapt a novel in situ signal amplification method (the RNAScope® detection platform) for the analysis of intracellular RNAs in individual cells by flow cytometry. Using novel target-specific probes that were designed to suppress background signals, we demonstrate the specific detection of HIV gag RNAs in HIV-infected cellular samples, in addition to bcr and abl mRNAs in the K562 cell line. This method was capable of distinguishing cells expressing low abundance RNA transcripts and correlated well with quantitative imaging analysis. Furthermore, multiple distinct RNA targets were simultaneously detected with a high specificity without interference. Overall, the sensitivity and specificity of this method will be useful for the analysis of functionally important RNA species from individual cells, even at very low copy numbers.