Microfluidic single-cell real-time PCR for comparative analysis of gene expression patterns

Human monocyte subtype expression of neuroinflammation and regeneration-related genes is linked to age and sex

Stroke is a leading cause of disability and the third cause of death. The immune system plays an essential role in post-stroke recovery. After an ischemic stroke, monocytes infiltrate the injured brain tissue and can exacerbate or mitigate the damage. Ischemic stroke is more prevalent in the aged population, and the aging brain exhibits an altered immune response. There are also sex disparities in ischemic stroke incidence, outcomes, and recovery, and these differences may be hormone-driven and determined by genetic and epigenetic factors. Here, we studied whether human peripheral blood monocyte subtype (classical, intermediate, and non-classical) expression of neuronal inflammation- and regeneration-related genes depends on age and sex. A FACS analysis of blood samples from 44 volunteers (male and female, aged 28 to 98) showed that in contrast to other immune cells, the proportion of natural killer cells increased in females. The proportion of B-cells decreased in both sexes with age, and subtypes of monocytes were not linked to age or sex. Gene expression analysis by qPCR identified several genes differentially correlating with age and sex within different monocyte subtypes. Interestingly, ANXA1 and CD36 showed a consistent increase with aging in all monocytes, specifically in intermediate (CD36) and intermediate and non-classical (ANXA1) subtypes. Other genes (IL-1β, S100A8, TNFα, CD64, CD33, TGFβ1, TLR8, CD91) were differentially changed in monocyte subtypes with increased aging. Most age-dependent gene changes were differentially expressed in female monocytes. Our data shed light on the nuanced interplay of age and sex in shaping the expression of inflammation- and regeneration-related genes within distinct monocyte subtypes. Understanding these dynamics could pave the way for targeted interventions and personalized approaches in post-stroke care, particularly for the aging population and individuals of different sexes.

Transcription Factor-Forced Astrocytic Differentiation Impairs Human Glioblastoma Growth In Vitro and In Vivo

Direct cellular reprogramming has recently gained attention of cancer researchers for the possibility to convert undifferentiated cancer cells into more differentiated, postmitotic cell types. While a few studies have attempted reprogramming of glioblastoma (GBM) cells toward a neuronal fate, this approach has not yet been used to induce differentiation into other lineages and in vivo data on reduction in tumorigenicity are limited. Here, we employ cellular reprogramming to induce astrocytic differentiation as a therapeutic approach in GBM. To this end, we overexpressed key transcriptional regulators of astroglial development in human GBM and GBM stem cell lines. Treated cells undergo a remarkable shift in structure, acquiring an astrocyte-like morphology with star-shaped bodies and radial branched processes. Differentiated cells express typical glial markers and show a marked decrease in their proliferative state. In addition, forced differentiation induces astrocytic functions such as induced calcium transients and ability to respond to inflammatory stimuli. Most importantly, forced differentiation substantially reduces tumorigenicity of GBM cells in an in vivo xenotransplantation model. The current study capitalizes on cellular plasticity with a novel application in cancer. We take advantage of the similarity between neural developmental processes and cancer hierarchy to mitigate, if not completely abolish, the malignant nature of tumor cells and pave the way for new intervention strategies.

Detection of MicroRNA Expression Dynamics Using LNA/DNA Nanobiosensor

The investigation of complex biological processes requires effective tools for probing the spatiotemporal dynamics of individual cells. Single-cell gene expression analysis, such as RNA in situ hybridization and single-cell PCR, has been demonstrated in various biological applications (Tautz and Pfeifle, Chromosoma 98(2):81-5, 1989; Stahlberg and Bengtsson, Methods 50(4):282-288, 2010; Sanchez-Freire et al., Nat Protoc 7(5):829-838, 2012). However, existing techniques require cell lysis or fixation. The dynamic information and spatiotemporal regulation of the biological process cannot be obtained with these methods. Real-time gene expression analysis in living cells remains an outstanding challenge in the field. Here, we described a single-cell gene expression analysis method in living mammalian cells using a locked nucleic acid/DNA (LNA/DNA) nanobiosensor. This LNA/DNA nanobiosensor consists of a fluorophore-labeled detecting strand and a quenching strand. The fluorophore-labeled LNA probe is designed to hybridize with the target microRNA (miRNA) specifically and displace from the quenching strand, allowing the fluorophore to fluorescence. Large-scale single-cell dynamic gene expression monitoring can be performed using time-lapse microscopy to study spatiotemporal distribution and heterogeneity in gene expression. Multiplex detection of miRNAs can be achieved using different fluorophore-labeled LNA/DNA nanobiosensors. This LNA/DNA protocol is fast, generally applicable, and easily accessible.

RNA cytometry of single-cells using semi-permeable microcapsules

Analytical tools for gene expression profiling of individual cells are critical for studying complex biological systems. However, the techniques enabling rapid measurements of gene expression on thousands of single-cells are lacking. Here, we report a high-throughput RNA cytometry for digital profiling of single-cells isolated in liquid droplets enveloped by a thin semi-permeable membrane (microcapsules). Due to the selective permeability of the membrane, the desirable enzymes and reagents can be loaded, or replaced, in the microcapsule at any given step by simply changing the reaction buffer in which the microcapsules are dispersed. Therefore, complex molecular biology workflows can be readily adapted to conduct nucleic acid analysis on encapsulated mammalian cells, or other biological species. The microcapsules support sequential multi-step enzymatic reactions and remain intact under different biochemical conditions, freezing, thawing, and thermocycling. Combining microcapsules with conventional FACS provides a high-throughput approach for conducting RNA cytometry of individual cells based on their digital gene expression signature.

Functional Characterization and Phenotyping of Protoplasts on a Microfluidics-Based Flow Cytometry

A better understanding of the phenotypic heterogeneity of protoplasts requires a comprehensive analysis of the morphological and metabolic characteristics of many individual cells. In this study, we developed a microfluidic flow cytometry with fluorescence sensor for functional characterization and phenotyping of protoplasts to allow an unbiased assessment of the influence of environmental factors at the single cell level. First, based on the measurement of intracellular homeostasis of reactive oxygen species (ROS) with a DCFH-DA dye, the effects of various external stress factors such as H₂O₂, temperature, ultraviolet (UV) light, and cadmium ions on intracellular ROS accumulation in Arabidopsis mesophyll protoplasts were quantitatively investigated. Second, a faster and stronger oxidative burst was observed in Petunia protoplasts isolated from white petals than in those isolated from purple petals, demonstrating the photoprotective role of anthocyanins. Third, using mutants with different endogenous auxin, we demonstrated the beneficial effect of auxin during the process of primary cell wall regeneration. Moreover, UV-B irradiation has a similar accelerating effect by increasing the intracellular auxin level, as shown by double fluorescence channels. In summary, our work has revealed previously underappreciated phenotypic variability within a protoplast population and demonstrated the advantages of a microfluidic flow cytometry for assessing the in vivo dynamics of plant metabolic and physiological indices at the single-cell level.

Single cell multi-miRNAs quantification with hydrogel microbeads for liver cancer cell subtypes discrimination

The simultaneous quantification of multi-miRNAs in single cells reveals cellular heterogeneity, and benefits the subtypes discrimination of cancer cells . Though micro-droplet techniques enable successful single cell encapsulation, the isolated and restricted reaction space of microdroplets causes cross-reactions and inaccuracy for simultaneous multi-miRNAs quantification. Herein, we develop a hydrogel microbead based strategy for the simultaneous sensitive quantification of miRNA-21, 122 and 222 in single cells. Single cells are encapsulated and undergo cytolysis in hydrogel microbeads. The three target miRNAs are retained in the microbead by pre-immobilized capture probes, and activate rolling circle amplification (RCA) reactions. The RCA products are hybridized with corresponding dye labelled DNA reporters, and the respective fluorescence intensities are recorded for multi-miRNA quantification. The porous structure of the hydrogel microbeads allows the free diffusion of reactants and easy removal of unreacted DNA strands, which effectively avoids nonspecific cross-reactions. Clear differentiation of cellular heterogeneity and subpopulation discrimination are achieved for three kinds of liver cancer cells and one normal liver cell.

A single cell multi-miRNAs quantification strategy is reported. Single cells are encapsulated and undergo cytolysis in hydrogel microbeads, then the quantitative analysis of three miRNAs is used to achieve sub-populations discrimination for liver cells.

An ultrasensitive multivariate signal amplification strategy based on microchip platform tailored for simultaneous quantification of multiple microRNAs in single cell

MicroRNAs (miRNAs) play a very important regulatory role in life activities. Abnormal expression levels of miRNAs in cells are associated with various diseases, especially human cancer. Nevertheless, accurate detection of the copy numbers of various miRNA molecules in single cell is still a great challenge. In this study, an intracellular multivariate signal amplification strategy based on microchip platform was proposed, and an ultrasensitive single-cell analysis method was established for simultaneous quantification of absolute copy numbers of multiple miRNAs in a single cell. Using miRNA-21 and miRNA-141 as the analytical models of miRNAs, the detection limits of 1.0 and 2.0 fM were obtained. Based on the developed method, an analysis of 600 randomly acquired different types of cells was performed. The distribution of absolute copy numbers of miRNA-21 and miRNA-141 in six types of cells was obtained. It was found that the number of copies of miRNA-21 and miRNA-141 in different types of cancer cells showed different expression characteristics. The study results can help us more accurately understand cell-to-cell heterogeneity and the relationship between different miRNAs and different types of cancer at the single cell level.

Quantification of tumor heterogeneity: from data acquisition to metric generation

Tumors are unique and complex ecosystems, in which heterogeneous cell subpopulations with variable molecular profiles, aggressiveness, and proliferation potential coexist and interact. Understanding how heterogeneity influences tumor progression has important clinical implications for improving diagnosis, prognosis, and treatment response prediction. Several recent innovations in data acquisition methods and computational metrics have enabled the quantification of spatiotemporal heterogeneity across different scales of tumor organization. Here, we summarize the most promising efforts from a common experimental and computational perspective, discussing their advantages, shortcomings, and challenges. With personalized medicine entering a new era of unprecedented opportunities, our vision is that of future workflows integrating across modalities, scales, and dimensions to capture intricate aspects of the tumor ecosystem and to open new avenues for improved patient care.

Challenges and approaches to studying pore-forming proteins

Pore-forming proteins (PFPs) are a broad class of molecules that comprise various families, structural folds, and assembly pathways. In nature, PFPs are most often deployed by their host organisms to defend against other organisms. In humans, this is apparent in the immune system, where several immune effectors possess pore-forming activity. Furthermore, applications of PFPs are found in next-generation low-cost DNA sequencing, agricultural crop protection, pest control, and biosensing. The advent of cryoEM has propelled the field forward. Nevertheless, significant challenges and knowledge-gaps remain. Overcoming these challenges is particularly important for the development of custom, purpose-engineered PFPs with novel or desired properties. Emerging single-molecule techniques and methods are helping to address these unanswered questions. Here we review the current challenges, problems, and approaches to studying PFPs.

Deoxynivalenol in Fusarium graminearum: Evaluation of Cyproconazole Stereoisomers In Vitro and In Planta

Cyproconazole (CPZ), a representative chiral triazole fungicide, is widely used to control Fusarium head blight (FHB). In this study, the stereoselective efficiency of CPZ was investigated in vitro and in planta. Consistent results were observed between the in vitro bioassay and the in planta visual disease rating, with the control efficacy ordered RS-CPZ > RR-CPZ > SR-CPZ > SS-CPZ. Unexpectedly, the in planta deoxynivalenol level was in the order RR-CPZ > RS-CPZ > SS-CPZ > SR-CPZ, while RS-CPZ inhibited the deoxynivalenol production and ergosterol biosynthesis in Fusarium graminearum. We further investigated that the Tri genes were upregulated in Fusarium graminearum of the RS-CPZ group, and SR-CPZ preferentially degraded in wheat. An extra action mode of CPZ was inferred to stimulate the production of deoxynivalenol. These findings revealed the stereoselective efficiency of CPZ stereoisomers against FHB and provided new insights into the mechanism of action of triazole fungicides against FHB and deoxynivalenol.

Absolute Quantification of MicroRNAs in a Single Cell with Chemiluminescence Detection Based on Rolling Circle Amplification on a Microchip Platform

The absolute quantification of miRNAs in a single cell allows to better understand the heterogeneity of cells and the relationship between miRNAs and diseases. However, seldom methods for miRNA quantification in a single cell have been reported because the miRNA content in a single cell is very low. Herein, an ultrasensitive chemiluminescence assay strategy based on rolling circle amplification (RCA) on a microchip platform was proposed for the absolute quantification of miRNAs in a single cell. In this strategy, a ring probe with specificity was designed and synthesized, which could perform RCA for target miRNAs to improve the sensitivity and satisfy the need of absolute quantification of miRNAs in a single cell. The 20 liver cancer cells (HepG2) and 20 normal liver cells (HL-7702) were analyzed using this method; it is found that the miRNA-21 contents varied among cells, and miRNA-21 was overexpressed in HepG2 cells. Compared with traditional methods, the proposed strategy has many advantages such as low cost, simple operation, short analysis time, good specificity, and lower probability of false positives. This method is expected to be one of the powerful tools for the absolute quantification of miRNAs in a single cell.

Single-Cell Sequencing Methodologies: From Transcriptome to Multi-Dimensional Measurement

Cells are the basic building blocks of biological systems, with inherent unique molecular features and development trajectories. The study of single cells facilitates in-depth understanding of cellular diversity, disease processes, and organization of multicellular organisms. Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for the interrogation of gene expression patterns and the dynamics of single cells, allowing cellular heterogeneity to be dissected at unprecedented resolution. Nevertheless, measuring at only transcriptome level or 1D is incomplete; the cellular heterogeneity reflects in multiple dimensions, including the genome, epigenome, transcriptome, spatial, and even temporal dimensions. Hence, integrative single cell analysis is highly desired. In addition, the way to interpret sequencing data by virtue of bioinformatic tools also exerts critical roles in revealing differential gene expression. Here, a comprehensive review that summarizes the cutting-edge single-cell transcriptome sequencing methodologies, including scRNA-seq, spatial and temporal transcriptome profiling, multi-omics sequencing and computational methods developed for scRNA-seq data analysis is provided. Finally, the challenges and perspectives of this field are discussed.

Microdroplet-based one-step RT-PCR for ultrahigh throughput single-cell multiplex gene expression analysis and rare cell detection

Gene expression analysis of individual cells enables characterization of heterogeneous and rare cell populations, yet widespread implementation of existing single-cell gene analysis techniques has been hindered due to limitations in scale, ease, and cost. Here, we present a novel microdroplet-based, one-step reverse-transcriptase polymerase chain reaction (RT-PCR) platform and demonstrate the detection of three targets simultaneously in over 100,000 single cells in a single experiment with a rapid read-out. Our customized reagent cocktail incorporates the bacteriophage T7 gene 2.5 protein to overcome cell lysate-mediated inhibition and allows for one-step RT-PCR of single cells encapsulated in nanoliter droplets. Fluorescent signals indicative of gene expressions are analyzed using a probabilistic deconvolution method to account for ambient RNA and cell doublets and produce single-cell gene signature profiles, as well as predict cell frequencies within heterogeneous samples. We also developed a simulation model to guide experimental design and optimize the accuracy and precision of the assay. Using mixtures of in vitro transcripts and murine cell lines, we demonstrated the detection of single RNA molecules and rare cell populations at a frequency of 0.1%. This low cost, sensitive, and adaptable technique will provide an accessible platform for high throughput single-cell analysis and enable a wide range of research and clinical applications.

Ex uno, plures-From One Tissue to Many Cells: A Review of Single-Cell Transcriptomics in Cardiovascular Biology

Recent technological advances have revolutionized the study of tissue biology and garnered a greater appreciation for tissue complexity. In order to understand cardiac development, heart tissue homeostasis, and the effects of stress and injury on the cardiovascular system, it is essential to characterize the heart at high cellular resolution. Single-cell profiling provides a more precise definition of tissue composition, cell differentiation trajectories, and intercellular communication, compared to classical bulk approaches. Here, we aim to review how recent single-cell multi-omic studies have changed our understanding of cell dynamics during cardiac development, and in the healthy and diseased adult myocardium.

Pitfalls in Single Clone CRISPR-Cas9 Mutagenesis to Fine-map Regulatory Intervals

The majority of genetic variants affecting complex traits map to regulatory regions of genes, and typically lie in credible intervals of 100 or more SNPs. Fine mapping of the causal variant(s) at a locus depends on assays that are able to discriminate the effects of polymorphisms or mutations on gene expression. Here, we evaluated a moderate-throughput CRISPR-Cas9 mutagenesis approach, based on replicated measurement of transcript abundance in single-cell clones, by deleting candidate regulatory SNPs, affecting four genes known to be affected by large-effect expression Quantitative Trait Loci (eQTL) in leukocytes, and using Fluidigm qRT-PCR to monitor gene expression in HL60 pro-myeloid human cells. We concluded that there were multiple constraints that rendered the approach generally infeasible for fine mapping. These included the non-targetability of many regulatory SNPs, clonal variability of single-cell derivatives, and expense. Power calculations based on the measured variance attributable to major sources of experimental error indicated that typical eQTL explaining 10% of the variation in expression of a gene would usually require at least eight biological replicates of each clone. Scanning across credible intervals with this approach is not recommended.

Low-Cost Battery-Powered and User-Friendly Real-Time Quantitative PCR System for the Detection of Multigene

Real-time polymerase chain reaction (PCR) is the standard for nucleic acid detection and plays an important role in many fields. A new chip design is proposed in this study to avoid the use of expensive instruments for hydrophobic treatment of the surface, and a new injection method solves the issue of bubbles formed during the temperature cycle. We built a battery-powered real-time PCR device to follow polymerase chain reaction using fluorescence detection and developed an independently designed electromechanical control system and a fluorescence analysis software to control the temperature cycle, the photoelectric detection coupling, and the automatic analysis of the experimental data. The microchips and the temperature cycling system cost USD 100. All the elements of the device are available through open access, and there are no technical barriers. The simple structure and manipulation allows beginners to build instruments and perform PCR tests after only a short tutorial. The device is used for analysis of the amplification curve and the melting curve of multiple target genes to demonstrate that our instrument has the same accuracy and stability as a commercial instrument.

Free convective PCR: From principle study to commercial applications-A critical review

Polymerase chain reaction (PCR) is an extremely important tool for molecular diagnosis, as it can specifically amplify nucleic acid templates for sensitive detection. As another division of PCR, free convective PCR was invented in 2001, which can be performed in a capillary tube pseudo-isothermally within a significantly short time. Convective PCR thermal cycling is implemented by inducing thermal convection inside the capillary tube, which stratifies the reaction into spatially separate and stable melting, annealing, and extension zones created by the temperature gradient. Convective PCR is a promising tool that can be used for nucleic acid diagnosis as a point-of-care test (POCT) due to the significantly simplified heating strategy, reduced cost, and shortened detection time without sacrificing sensitivity and accuracy. Here, we review the history of free convective PCR from its invention to development and its commercial applications.

Towards Predicting Progression to Severe Dengue

There is an urgent need for prognostic assays to predict progression to severe dengue infection, which is a major global threat. While the majority of symptomatic dengue patients experience an acute febrile illness, 5-20% progress to severe infection associated with significant morbidity and mortality. Early monitoring and administration of supportive care reduce mortality and clinically usable biomarkers to predict severe dengue are needed. Here, we review recent discoveries of gene sets, anti-dengue antibody properties, and inflammatory markers with potential utility as predictors of disease progression. Upon larger scale validation and development of affordable sample-to-answer technologies, some of these biomarkers may be utilized to develop the first prognostic assay for improving patient care and allocating healthcare resources more effectively in dengue endemic countries.

Multivariate patterning of human pluripotent cells under perfusion reveals critical roles of induced paracrine factors in kidney organoid development

Creating complex multicellular kidney organoids from pluripotent stem cells shows great promise. Further improvements in differentiation outcomes, patterning, and maturation of specific cell types are, however, intrinsically limited by standard tissue culture approaches. We describe a novel full factorial microbioreactor array-based methodology to achieve rapid interrogation and optimization of this complex multicellular differentiation process in a facile manner. We successfully recapitulate early kidney tissue patterning events, exploring more than 1000 unique conditions in an unbiased and quantitative manner, and define new media combinations that achieve near-pure renal cell type specification. Single-cell resolution identification of distinct renal cell types within multilayered kidney organoids, coupled with multivariate analysis, defined the definitive roles of Wnt, fibroblast growth factor, and bone morphogenetic protein signaling in their specification, exposed retinoic acid as a minimal effector of nephron patterning, and highlighted critical contributions of induced paracrine factors on cell specification and patterning.

A cluster robustness score for identifying cell subpopulations in single cell gene expression datasets from heterogeneous tissues and tumors

MOTIVATION

A major aim of single cell biology is to identify important cell types such as stem cells in heterogeneous tissues and tumors. This is typically done by isolating hundreds of individual cells and measuring expression levels of multiple genes simultaneously from each cell. Then, clustering algorithms are used to group together similar single-cell expression profiles into clusters, each representing a distinct cell type. However, many of these clusters result from overfitting, meaning that rather than representing biologically meaningful cell types, they describe the intrinsic 'noise' in gene expression levels due to limitations in experimental precision or the intrinsic randomness of biochemical cellular processes. Consequentially, these non-meaningful clusters are most sensitive to noise: a slight shift in gene expression levels due to a repeated measurement will rearrange the grouping of data points such that these clusters break up.

RESULTS

To identify the biologically meaningful clusters we propose a 'cluster robustness score': We add increasing amounts of noise (zero mean and increasing variance) and check which clusters are most robust in the sense that they do not mix with their neighbors up to high levels of noise. We show that biologically meaningful cell clusters that were manually identified in previously published single cell expression datasets have high robustness scores. These scores are higher than what would be expected in corresponding randomized homogeneous datasets having the same expression level statistics. We believe that this scoring system provides a more automated way to identify cell types in heterogeneous tissues and tumors.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Droplets as Carriers for Flexible Electronic Devices

Coupling soft bodies and dynamic motions with multifunctional flexible electronics is challenging, but is essential in satisfying the urgent and soaring demands of fully soft and comprehensive robotic systems that can perform tasks in spite of rigorous spatial constraints. Here, the mobility and adaptability of liquid droplets with the functionality of flexible electronics, and techniques to use droplets as carriers for flexible devices are combined. The resulting active droplets (ADs) with volumes ranging from 150 to 600 µL can conduct programmable functions, such as sensing, actuation, and energy harvesting defined by the carried flexible devices and move under the excitation of gravitational force or magnetic force. They work in both dry and wet environments, and adapt to the surrounding environment through reversible shape shifting. These ADs can achieve controllable motions at a maximum velocity of 226 cm min-1 on a dry surface and 32 cm min-1 in a liquid environment. The conceptual system may eventually lead to individually addressable ADs that offer sophisticated functions for high-throughput molecule analysis, drug assessment, chemical synthesis, and information collection.

Patient-derived pancreas-on-a-chip to model cystic fibrosis-related disorders

Cystic fibrosis (CF) is a genetic disorder caused by defective CF Transmembrane Conductance Regulator (CFTR) function. Insulin producing pancreatic islets are located in close proximity to the pancreatic duct and there is a possibility of impaired cell-cell signaling between pancreatic ductal epithelial cells (PDECs) and islet cells as causative in CF. To study this possibility, we present an in vitro co-culturing system, pancreas-on-a-chip. Furthermore, we present an efficient method to micro dissect patient-derived human pancreatic ducts from pancreatic remnant cell pellets, followed by the isolation of PDECs. Here we show that defective CFTR function in PDECs directly reduced insulin secretion in islet cells significantly. This uniquely developed pancreatic function monitoring tool will help to study CF-related disorders in vitro, as a system to monitor cell-cell functional interaction of PDECs and pancreatic islets, characterize appropriate therapeutic measures and further our understanding of pancreatic function.

Defective CFTR protein, responsible for Cystic Fibrosis (CF), is highly expressed in pancreatic ductal epithelial cells (PDECs) but their impact on insulin secreting pancreatic islets is not fully understood. Here the authors develop a non-CF and CF patient derived pancreas-on-a-chip model to study how CF affects insulin secretion.

Proteasome-Dependent Regulation of Distinct Metabolic States During Long-Term Culture of Human iPSC-Derived Cardiomyocytes

RATIONALE

The immature presentation of human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) is currently a challenge for their application in disease modeling, drug screening, and regenerative medicine. Long-term culture is known to achieve partial maturation of iPSC-CMs. However, little is known about the molecular signaling circuitries that govern functional changes, metabolic output, and cellular homeostasis during long-term culture of iPSC-CMs.

OBJECTIVE

We aimed to identify and characterize critical signaling events that control functional and metabolic transitions of cardiac cells during developmental progression, as recapitulated by long-term culture of iPSC-CMs.

METHODS AND RESULTS

We combined transcriptomic sequencing with pathway network mapping in iPSC-CMs that were cultured until a late time point, day 200, in comparison to a medium time point, day 90, and an early time point, day 30. Transcriptomic landscapes of long-term cultured iPSC-CMs allowed mapping of distinct metabolic stages during development of maturing iPSC-CMs. Temporally divergent control of mitochondrial metabolism was found to be regulated by cAMP/PKA (protein kinase A)- and proteasome-dependent signaling events. The PKA/proteasome-dependent signaling cascade was mediated downstream by Hsp90 (heat shock protein 90), which in turn modulated mitochondrial respiratory chain proteins and their metabolic output. During long-term culture, this circuitry was found to initiate upregulation of iPSC-CM metabolism, resulting in increased cell contractility that reached a maximum at the day 200 time point.

CONCLUSIONS

Our results reveal a PKA/proteasome- and Hsp90-dependent signaling pathway that regulates mitochondrial respiratory chain proteins and determines cardiomyocyte energy production and functional output. These findings provide deeper insight into signaling circuitries governing metabolic homeostasis in iPSC-CMs during developmental progression.

Segmented Filamentous Bacteria Induce Divergent Populations of Antigen-Specific CD4 T Cells in the Small Intestine

CD4 T cells differentiate into RORγt/IL-17A-expressing cells in the small intestine following colonization by segmented filamentous bacteria (SFB). However, it remains unclear whether SFB-specific CD4 T cells can differentiate directly from naïve precursors, and whether their effector differentiation is solely directed towards the Th17 lineage. In this study, we used adoptive T cell transfer experiments and showed that naïve CD4 T cells can migrate to the small intestinal lamina propria (sLP) and differentiate into effector T cells that synthesize IL-17A in response to SFB colonization. Using single cell RT-PCR analysis, we showed that the progenies of SFB responding T cells are not uniform but composed of transcriptionally divergent populations including Th1, Th17 and follicular helper T cells. We further confirmed this finding using in vitro culture of SFB specific intestinal CD4 T cells in the presence of cognate antigens, which also generated heterogeneous population with similar features. Collectively, these findings indicate that a single species of intestinal bacteria can generate a divergent population of antigen-specific effector CD4 T cells, rather than it provides a cytokine milieu for the development of a particular effector T cell subset.

Gradient in the electric field for particle position detection in microfluidic channels

In this work, a new method to track particles in microfluidic channels is presented. Particle position tracking in microfluidic systems is crucial to characterize sorting systems or to improve the analysis of cells in impedance flow cytometry studies. By developing an electric field gradient in a two parallel electrode array the position of the particles can be tracked in one axis by impedance analysis. This method can track the particle's position at lower frequencies and measure the conductivity of the system at higher frequencies. A 3-D simulation was performed showing particle position detection and conductivity analysis. To experimentally validate the technique, a microfluidic chip that develops a gradient in the electric field was fabricated and used to detect the position of polystyrene particles in one axis and measure their conductivity at low and high frequencies, respectively.

A brief review of single-cell transcriptomic technologies

In recent years, there has been an effort to develop new technologies for measuring gene expression and sequence information from thousands of individual cells. Large data sets that were obtained using these 'single cell' technologies have allowed scientists to address fundamental questions in biomedicine ranging from stems cells and development to cancer and immunology. Here, we provide a brief review of recent developments in single-cell technology. Our intention is to provide a quick background for newcomers to the field as well as a deeper description of some of the leading technologies to date.

Single Cell Gene Expression to Understand the Dynamic Architecture of the Heart

The recent development of single cell gene expression technologies, and especially single cell transcriptomics, have revolutionized the way biologists and clinicians investigate organs and organisms, allowing an unprecedented level of resolution to the description of cell demographics in both healthy and diseased states. Single cell transcriptomics provide information on prevalence, heterogeneity, and gene co-expression at the individual cell level. This enables a cell-centric outlook to define intracellular gene regulatory networks and to bridge toward the definition of intercellular pathways otherwise masked in bulk analysis. The technologies have developed at a fast pace producing a multitude of different approaches, with several alternatives to choose from at any step, including single cell isolation and capturing, lysis, RNA reverse transcription and cDNA amplification, library preparation, sequencing, and computational analyses. Here, we provide guidelines for the experimental design of single cell RNA sequencing experiments, exploring the current options for the crucial steps. Furthermore, we provide a complete overview of the typical data analysis workflow, from handling the raw sequencing data to making biological inferences. Significantly, advancements in single cell transcriptomics have already contributed to outstanding exploratory and functional studies of cardiac development and disease models, as summarized in this review. In conclusion, we discuss achievable outcomes of single cell transcriptomics' applications in addressing unanswered questions and influencing future cardiac clinical applications.

Validation of a quantitative PCR based detection system for indoor mold exposure assessment in bioaerosols

Determination and assessment of airborne fungal particles is complex and results of different sampling and analytical strategies are hard to compare due to limitations of each of the techniques. Here, an indoor mold detection system based on quantitative polymerase chain reaction (qPCR) is described and validated for its reliability and stability to identify airborne fungal particles collected. Data obtained from testing the system with fungal DNA, spore suspensions and bioaerosols indicated a need for spiking and normalization of measurements due to material loss and assay specific bias. Considering the loss of material during sample processing, detection limits defined for suspensions of Tritirachium oryzae spores were roughly 18 spores per sample. Detection of fungal spore mixtures nebulized under controlled conditions in a bioaerosol chamber showed generally 2-3 times higher normalized values measured with the molecular system compared to cultivation. Data obtained from a mold infested indoor sampling site and its corresponding outdoor reference measurement showed good correlations between qPCR and high-throughput sequencing (rho = 0.83, p < 0.01), if Cladosporium species were excluded. Taking necessary data normalization into account, the described qPCR detection system shows great potential to complement commonly used culture based approaches with the aim to improve the precision of indoor mold assessments. In contrast to already available qPCR assays that detect certain molds on a species level, this system covers a broad range of relevant fungal communities, serving as a promising alternative to high-throughput sequencing to identify indoor molds.

Microfluidic-Based Single-Cell Study: Current Status and Future Perspective

Investigation of cell behavior under different environments and manual operations can give information in specific cellular processes. Among all cell-based analysis, single-cell study occupies a peculiar position, while it can avoid the interaction effect within cell groups and provide more precise information. Microfluidic devices have played an increasingly important role in the field of single-cell study owing to their advantages: high efficiency, easy operation, and low cost. In this review, the applications of polymer-based microfluidics on cell manipulation, cell treatment, and cell analysis at single-cell level are detailed summarized. Moreover, three mainly types of manufacturing methods, i.e., replication, photodefining, and soft lithography methods for polymer-based microfluidics are also discussed.

Ultrahigh-throughput droplet microfluidic device for single-cell miRNA detection with isothermal amplification

Analysis of microRNA (miRNA), a pivotal primary regulator of fundamental cellular processes, at the single-cell level is essential to elucidate regulated gene expression precisely. Most single-cell gene sequencing methods use the polymerase chain reaction (PCR) to increase the concentration of the target gene for detection, thus requiring a barcoding process for cell identification and creating a challenge for real-time, large-scale screening of sequences in cells to rapidly profile physiological samples. In this study, a rapid, PCR-free, single-cell miRNA assay is developed from a continuous-flow microfluidic process employing a DNA hybridization chain reaction to amplify the target miRNA signal. Individual cells are encapsulated with DNA amplifiers in water-in-oil droplets and then lysed. The released target miRNA interacts with the DNA amplifiers to trigger hybridization reactions, producing fluorescence signals. Afterward, the target sequences are recycled to trigger a cyclic cascade reaction and significantly amplify the fluorescence signals without using PCR thermal cycling. Multiple DNA amplifiers with distinct fluorescence signals can be encapsulated simultaneously in a droplet to measure multiple miRNAs from a single cell simultaneously. Moreover, this process converts the lab bench PCR assay to a real-time droplet assay with the post-reaction fluorescence signal as a readout to allow flow cytometry-like continuous-flow measurement of sequences in a single cell with an ultrahigh throughput (300-500 cells per minute) for rapid biomedical identification.

Simple paired heavy- and light-chain antibody repertoire sequencing using endoplasmic reticulum microsomes

Existing methods for paired antibody heavy- and light-chain repertoire sequencing rely on specialized equipment and are limited by their commercial availability and high costs. Here, we report a novel simple and cost-effective emulsion-based single-cell paired antibody repertoire sequencing method that employs only basic laboratory equipment. We performed a proof-of-concept using mixed mouse hybridoma cells and we also showed that our method can be used for discovery of novel antigen-specific monoclonal antibodies by sequencing human CD19⁺ B cell IgM and IgG repertoires isolated from peripheral whole blood before and seven days after Td (Tetanus toxoid/Diphtheria toxoid) booster immunization. We anticipate broad applicability of our method for providing insights into adaptive immune responses associated with various diseases, vaccinations, and cancer immunotherapies.

Using single-cell genomics to understand developmental processes and cell fate decisions

High-throughput -omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision-making is inherently a unicellular process to which "bulk" -omics techniques are poorly suited, as they capture ensemble averages of cell states. Recently developed single-cell methods bridge this gap, allowing high-throughput molecular surveys of individual cells. In this review, we cover core concepts of analysis of single-cell gene expression data and highlight areas of developmental biology where single-cell techniques have made important contributions. These include understanding of cell-to-cell heterogeneity, the tracing of differentiation pathways, quantification of gene expression from specific alleles, and the future directions of cell lineage tracing and spatial gene expression analysis.

Highly multiplexed single-cell quantitative PCR

We present a microfluidic device for rapid gene expression profiling in single cells using multiplexed quantitative polymerase chain reaction (qPCR). This device integrates all processing steps, including cell isolation and lysis, complementary DNA synthesis, pre-amplification, sample splitting, and measurement in twenty separate qPCR reactions. Each of these steps is performed in parallel on up to 200 single cells per run. Experiments performed on dilutions of purified RNA establish assay linearity over a dynamic range of at least 10⁴, a qPCR precision of 15%, and detection sensitivity down to a single cDNA molecule. We demonstrate the application of our device for rapid profiling of microRNA expression in single cells. Measurements performed on a panel of twenty miRNAs in two types of cells revealed clear cell-to-cell heterogeneity, with evidence of spontaneous differentiation manifested as distinct expression signatures. Highly multiplexed microfluidic RT-qPCR fills a gap in current capabilities for single-cell analysis, providing a rapid and cost-effective approach for profiling panels of marker genes, thereby complementing single-cell genomics methods that are best suited for global analysis and discovery. We expect this approach to enable new studies requiring fast, cost-effective, and precise measurements across hundreds of single cells.

Single-Cell RT-PCR in Microfluidic Droplets with Integrated Chemical Lysis

Droplet microfluidics can identify and sort cells using digital reverse transcription polymerase chain reaction (RT-PCR) signals from individual cells. However, current methods require multiple microfabricated devices for enzymatic cell lysis and PCR reagent addition, making the process complex and prone to failure. Here, we describe a new approach that integrates all components into a single device. The method enables controlled exposure of isolated single cells to a high pH buffer, which lyses cells and inactivates reaction inhibitors but can be instantly neutralized with RT-PCR buffer. Using our chemical lysis approach, we distinguish individual cells' gene expression with data quality equivalent to more complex two-step workflows. Our system accepts cells and produces droplets ready for amplification, making single-cell droplet RT-PCR faster and more reliable.

Construction of developmental lineage relationships in the mouse mammary gland by single-cell RNA profiling

The mammary epithelium comprises two primary cellular lineages, but the degree of heterogeneity within these compartments and their lineage relationships during development remain an open question. Here we report single-cell RNA profiling of mouse mammary epithelial cells spanning four developmental stages in the post-natal gland. Notably, the epithelium undergoes a large-scale shift in gene expression from a relatively homogeneous basal-like program in pre-puberty to distinct lineage-restricted programs in puberty. Interrogation of single-cell transcriptomes reveals different levels of diversity within the luminal and basal compartments, and identifies an early progenitor subset marked by CD55. Moreover, we uncover a luminal transit population and a rare mixed-lineage cluster amongst basal cells in the adult mammary gland. Together these findings point to a developmental hierarchy in which a basal-like gene expression program prevails in the early post-natal gland prior to the specification of distinct lineage signatures, and the presence of cellular intermediates that may serve as transit or lineage-primed cells.

Label-free analysis of the characteristics of a single cell trapped by acoustic tweezers

Single-cell analysis is essential to understand the physical and functional characteristics of cells. The basic knowledge of these characteristics is important to elucidate the unique features of various cells and causative factors of diseases and determine the most effective treatments for diseases. Recently, acoustic tweezers based on tightly focused ultrasound microbeam have attracted considerable attention owing to their capability to grab and separate a single cell from a heterogeneous cell sample and to measure its physical cell properties. However, the measurement cannot be performed while trapping the target cell, because the current method uses long ultrasound pulses for grabbing one cell and short pulses for interrogating the target cell. In this paper, we demonstrate that short ultrasound pulses can be used for generating acoustic trapping force comparable to that with long pulses by adjusting the pulse repetition frequency (PRF). This enables us to capture a single cell and measure its physical properties simultaneously. Furthermore, it is shown that short ultrasound pulses at a PRF of 167 kHz can trap and separate either one red blood cell or one prostate cancer cell and facilitate the simultaneous measurement of its integrated backscattering coefficient related to the cell size and mechanical properties.

Mammalian Transcription Factor Networks: Recent Advances in Interrogating Biological Complexity

Transcription factor (TF) networks are a key determinant of cell fate decisions in mammalian development and adult tissue homeostasis and are frequently corrupted in disease. However, our inability to experimentally resolve and interrogate the complexity of mammalian TF networks has hampered the progress in this field. Recent technological advances, in particular large-scale genome-wide approaches, single-cell methodologies, live-cell imaging, and genome editing, are emerging as important technologies in TF network biology. Several recent studies even suggest a need to re-evaluate established models of mammalian TF networks. Here, we provide a brief overview of current and emerging methods to define mammalian TF networks. We also discuss how these emerging technologies facilitate new ways to interrogate complex TF networks, consider the current open questions in the field, and comment on potential future directions and biomedical applications.

In situ mRNA isolation from a microfluidic single-cell array using an external AFM nanoprobe

We present an in situ mRNA extraction platform to quantify marker-genes' expression levels of single target cells within high-density microfluidic trapping arrays. This platform enables single-cell transcriptomic analysis to reveal in-depth information of cellular mechanisms and population heterogeneity. Although microfluidic technology enables the automation of single-cell sorting, trapping and identification, most developed microfluidic devices are closed off and prevent single-cell access by external analytical equipment. Besides, cell lysing is usually required for mRNA extraction. In our platform, cells are trapped individually in a microwell array sealed by a 1 μm-thick polydimethylsiloxane (PDMS) membrane, and a modified atomic force microscopy (AFM) probe-a dielectrophoretic nanotweezer (DENT)-penetrates through the membrane and extracts mRNA molecules from a single cell by dielectrophoresis. The single-cellular expression levels of 3 housekeeping genes from HeLa cells were analyzed quantitatively based on the quantification of the extracted mRNAs, and the probed cells remained viable when the applied alternating-current (AC) voltage was lower than 1.5 V_pp during mRNA probing. We also performed in situ mRNA isolation from a mixture of SK-BR-3 and U937 cells, mimicking a blood sample that underwent primary enrichment of circulating tumor cells (CTCs), and evaluated various marker-genes' expressions. This integrated platform combines the non-destructive and precise-control of a single-cell mRNA probe with sealed microfluidic systems' capability of upstream sample processing and downstream multifunctional analysis to enable a versatile and powerful tool for biomedical research.

Partial Reprogramming of Pluripotent Stem Cell-Derived Cardiomyocytes into Neurons

Direct reprogramming of somatic cells has been demonstrated, however, it is unknown whether electrophysiologically-active somatic cells derived from separate germ layers can be interconverted. We demonstrate that partial direct reprogramming of mesoderm-derived cardiomyocytes into neurons is feasible, generating cells exhibiting structural and electrophysiological properties of both cardiomyocytes and neurons. Human and mouse pluripotent stem cell-derived CMs (PSC-CMs) were transduced with the neurogenic transcription factors Brn2, Ascl1, Myt1l and NeuroD. We found that CMs adopted neuronal morphologies as early as day 3 post-transduction while still retaining a CM gene expression profile. At week 1 post-transduction, we found that reprogrammed CMs expressed neuronal markers such as Tuj1, Map2, and NCAM. At week 3 post-transduction, mature neuronal markers such as vGlut and synapsin were observed. With single-cell qPCR, we temporally examined CM gene expression and observed increased expression of neuronal markers Dcx, Map2, and Tubb3. Patch-clamp analysis confirmed the neuron-like electrophysiological profile of reprogrammed CMs. This study demonstrates that PSC-CMs are amenable to partial neuronal conversion, yielding a population of cells exhibiting features of both neurons and CMs.

Categorizing Cells on the Basis of their Chemical Profiles: Progress in Single-Cell Mass Spectrometry

The chemical differences between individual cells within large cellular populations provide unique information on organisms' homeostasis and the development of diseased states. Even genetically identical cell lineages diverge due to local microenvironments and stochastic processes. The minute sample volumes and low abundance of some constituents in cells hinder our understanding of cellular heterogeneity. Although amplification methods facilitate single-cell genomics and transcriptomics, the characterization of metabolites and proteins remains challenging both because of the lack of effective amplification approaches and the wide diversity in cellular constituents. Mass spectrometry has become an enabling technology for the investigation of individual cellular metabolite profiles with its exquisite sensitivity, large dynamic range, and ability to characterize hundreds to thousands of compounds. While advances in instrumentation have improved figures of merit, acquiring measurements at high throughput and sampling from large populations of cells are still not routine. In this Perspective, we highlight the current trends and progress in mass-spectrometry-based analysis of single cells, with a focus on the technologies that will enable the next generation of single-cell measurements.

Strategies for the acquisition of transcriptional and epigenetic information in single cells

As the basic unit of living organisms, each single cell has unique molecular signatures and functions. Our ability to uncover the transcriptional and epigenetic signature of single cells has been hampered by the lack of tools to explore this area of research. The advent of microfluidic single cell technology along with single cell genome-wide DNA amplification methods had greatly improved our understanding of the expression variation in single cells. Transcriptional expression profile by multiplex qPCR or genome-wide RNA sequencing has enabled us to examine genes expression in single cells in different tissues. With the new tools, the identification of new cellular heterogeneity, novel marker genes, unique subpopulations, and spatial locations of each single cell can be acquired successfully. Epigenetic modifications for each single cell can also be obtained via similar methods. Based on single cell genome sequencing, single cell epigenetic information including histone modifications, DNA methylation, and chromatin accessibility have been explored and provided valuable insights regarding gene regulation and disease prognosis. In this article, we review the development of strategies to obtain single cell transcriptional and epigenetic data. Furthermore, we discuss ways in which single cell studies may help to provide greater understanding of the mechanisms of basic cardiovascular biology that will eventually lead to improvement in our ability to diagnose disease and develop new therapies.

Single-neuron identification of chemical constituents, physiological changes, and metabolism using mass spectrometry

The use of single-cell assays has emerged as a cutting-edge technique during the past decade. Although single-cell mass spectrometry (MS) has recently achieved remarkable results, deep biological insights have not yet been obtained, probably because of various technical issues, including the unavoidable use of matrices, the inability to maintain cell viability, low throughput because of sample pretreatment, and the lack of recordings of cell physiological activities from the same cell. In this study, we describe a patch clamp/MS-based platform that enables the sensitive, rapid, and in situ chemical profiling of single living neurons. This approach integrates modified patch clamp technique and modified MS measurements to directly collect and detect nanoliter-scale samples from the cytoplasm of single neurons in mice brain slices. Abundant possible cytoplasmic constituents were detected in a single neuron at a relatively fast rate, and over 50 metabolites were identified in this study. The advantages of direct, rapid, and in situ sampling and analysis enabled us to measure the biological activities of the cytoplasmic constituents in a single neuron, including comparing neuron types by cytoplasmic chemical constituents; observing changes in constituent concentrations as the physiological conditions, such as age, vary; and identifying the metabolic pathways of small molecules.

Human Amniocytes Are Receptive to Chemically Induced Reprogramming to Pluripotency

Restoring pluripotency using chemical compounds alone would be a major step forward in developing clinical-grade pluripotent stem cells, but this has not yet been reported in human cells. We previously demonstrated that VPA_AFS cells, human amniocytes cultivated with valproic acid (VPA) acquired functional pluripotency while remaining distinct from human embryonic stem cells (hESCs), questioning the relationship between the modulation of cell fate and molecular regulation of the pluripotency network. Here, we used single-cell analysis and functional assays to reveal that VPA treatment resulted in a homogeneous population of self-renewing non-transformed cells that fulfill the hallmarks of pluripotency, i.e., a short G1 phase, a dependence on glycolytic metabolism, expression of epigenetic modifications on histones 3 and 4, and reactivation of endogenous OCT4 and downstream targets at a lower level than that observed in hESCs. Mechanistic insights into the process of VPA-induced reprogramming revealed that it was dependent on OCT4 promoter activation, which was achieved independently of the PI3K (phosphatidylinositol 3-kinase)/AKT/mTOR (mammalian target of rapamycin) pathway or GSK3β inhibition but was concomitant with the presence of acetylated histones H3K9 and H3K56, which promote pluripotency. Our data identify, for the first time, the pluripotent transcriptional and molecular signature and metabolic status of human chemically induced pluripotent stem cells.

Single cell digital polymerase chain reaction on self-priming compartmentalization chip

Single cell analysis provides a new framework for understanding biology and disease, however, an absolute quantification of single cell gene expression still faces many challenges. Microfluidic digital polymerase chain reaction (PCR) provides a unique method to absolutely quantify the single cell gene expression, but only limited devices are developed to analyze a single cell with detection variation. This paper describes a self-priming compartmentalization (SPC) microfluidic digital polymerase chain reaction chip being capable of performing single molecule amplification from single cell. The chip can be used to detect four single cells simultaneously with 85% of sample digitization. With the optimized protocol for the SPC chip, we first tested the ability, precision, and sensitivity of our SPC digital PCR chip by assessing β-actin DNA gene expression in 1, 10, 100, and 1000 cells. And the reproducibility of the SPC chip is evaluated by testing 18S rRNA of single cells with 1.6%-4.6% of coefficient of variation. At last, by detecting the lung cancer related genes, PLAU gene expression of A549 cells at the single cell level, the single cell heterogeneity was demonstrated. So, with the power-free, valve-free SPC chip, the gene copy number of single cells can be quantified absolutely with higher sensitivity, reduced labor time, and reagent. We expect that this chip will enable new studies for biology and disease.

Use of high-throughput RT-qPCR to assess modulations of gene expression profiles related to genomic stability and interactions by cadmium

Predictive test systems to assess the mode of action of chemical carcinogens are urgently required. Within the present study, we applied the Fluidigm dynamic array on the BioMark™ HD System for quantitative high-throughput RT-qPCR analysis of 95 genes and 96 samples in parallel, selecting genes crucial for maintaining genomic stability, including stress response as well as DNA repair, cell cycle control, apoptosis and mitotic signaling. The specificity of each individually designed sequence-specific primer pair and their respective target amplicons were evaluated via melting curve analysis as part of qPCR and size verification via agarose gel electrophoresis. For each gene, calibration curves displayed high efficiencies and correlation coefficients in the identified linear dynamic range as well as low intra-assay variations. Data were processed via Fluidigm real-time PCR analysis and GenEx software, and results were depicted as relative gene expression according to the ΔΔC q method. Subsequently, gene expression analyses were conducted in cadmium-treated adenocarcinoma A549 and epithelial bronchial BEAS-2B cells. They revealed distinct dose- and time-dependent and also cell-type-specific gene expression patterns, including the induction of genes coding for metallothioneins, the oxidative stress response, cell cycle control, mitotic signaling and apoptosis. Interestingly, while genes coding for the DNA damage response were induced, distinct DNA repair genes were down-regulated at the transcriptional level. Thus, this approach provided a comprehensive overview on the interaction by cadmium with distinct signaling pathways, also reflecting molecular modes of action in cadmium-induced carcinogenicity. Therefore, the test system appears to be a promising tool for toxicological risk assessment.