Microfluidic devices for high-throughput gene expression profiling of single hESC-derived neural stem cells

Revealing the molecular mechanism of central nervous system leukemia with single-cell technology

Central nervous system leukemia (CNSL) is a severe complication of acute leukemia, with serious consequences for life quality and expectancy. The molecular mechanism of CNSL is unclear at present. Thus, determining appropriate prevention and therapeutic strategies for CNSL remain challenging. Currently, inferences regarding gene functions are based on the measurement of average gene expression in a bulk lysate. However, leukemia cells are a heterogeneous population in which the expression of critical genes may be masked by many unrelated genes. Single-cell sequencing may therefore be the best way to explore the development of CNSL in the bone marrow and peripheral blood at diagnosis and subsequent time points, in order to detect potential targets and prevent the development of CNSL. In this review, we first discuss the possible mechanism of CNSL, then describe the heterogeneity of leukemia cells. Finally, we focus on the role of single-cell technology in preventing and treating CNSL.

Single-cell genomic analysis of head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) incidence or rates have increased dramatically recently with little improvement in patient outcomes. There is an unmet need in HNSCC to develop reliable molecular markers capable of evaluating patient risks and advising treatments. This review focuses on recent developments in single-cell molecular analysis of cancer, and its applications for HNSCC diagnosis and treatments. For proof of concept, we examined gene expression levels of 62 patients with HNSCC, and correlate the gene expression profiles to single-cell gene expression profiles obtained from a pilot single-cell study of CCR5-positive breast carcinoma cells. The single-cell molecular analyses complemented the lysate data and reveals heterogeneity of oncogenesis pathways with the cancer cell population. Our single-cell molecular analysis indicated that molecular heterogeneity exists in HNSCC and should be addressed in treatment strategy of HNSCC. Single-cell molecular technology can have significant impact on diagnosis, therapeutic decision making, and prognosis of HNSCC.

Single-cell transcriptome and epigenomic reprogramming of cardiomyocyte-derived cardiac progenitor cells

The molecular basis underlying the dedifferentiation of mammalian adult cardiomyocytes (ACMs) into myocyte-derived cardiac progenitor cells (mCPCs) during cardiac tissue regeneration is poorly understood. We present data integrating single-cell transcriptome and whole-genome DNA methylome analyses of mouse mCPCs to understand the epigenomic reprogramming governing their intrinsic cellular plasticity. Compared to parental cardiomyocytes, mCPCs display epigenomic reprogramming with many differentially-methylated regions, both hypermethylated and hypomethylated, across the entire genome. Correlating well with the methylome, our single-cell transcriptomic data show that the genes encoding cardiac structure and function proteins are remarkably down-regulated in mCPCs, while those for cell cycle, proliferation, and stemness are significantly up-regulated. In addition, implanting mCPCs into infarcted mouse myocardium improves cardiac function with augmented left ventricular ejection fraction. This dataset suggests that the cellular plasticity of mammalian cardiomyocytes is the result of a well-orchestrated epigenomic reprogramming and a subsequent global transcriptomic alteration. Understanding cardiomyocyte epigenomic reprogramming may enable the design of future clinical therapies that induce cardiac regeneration, and prevent heart failure.

Epigenomic Reprogramming of Adult Cardiomyocyte-Derived Cardiac Progenitor Cells

It has been believed that mammalian adult cardiomyocytes (ACMs) are terminally-differentiated and are unable to proliferate. Recently, using a bi-transgenic ACM fate mapping mouse model and an in vitro culture system, we demonstrated that adult mouse cardiomyocytes were able to dedifferentiate into cardiac progenitor-like cells (CPCs). However, little is known about the molecular basis of their intrinsic cellular plasticity. Here we integrate single-cell transcriptome and whole-genome DNA methylation analyses to unravel the molecular mechanisms underlying the dedifferentiation and cell cycle reentry of mouse ACMs. Compared to parental cardiomyocytes, dedifferentiated mouse cardiomyocyte-derived CPCs (mCPCs) display epigenomic reprogramming with many differentially-methylated regions, both hypermethylated and hypomethylated, across the entire genome. Correlated well with the methylome, our transcriptomic data showed that the genes encoding cardiac structure and function proteins are remarkably down-regulated in mCPCs, while those for cell cycle, proliferation, and stemness are significantly up-regulated. In addition, implantation of mCPCs into infarcted mouse myocardium improves cardiac function with augmented left ventricular ejection fraction. Our study demonstrates that the cellular plasticity of mammalian cardiomyocytes is the result of a well-orchestrated epigenomic reprogramming and a subsequent global transcriptomic alteration.

Microfluidic Organ/Body-on-a-Chip Devices at the Convergence of Biology and Microengineering

Recent advances in biomedical technologies are mostly related to the convergence of biology with microengineering. For instance, microfluidic devices are now commonly found in most research centers, clinics and hospitals, contributing to more accurate studies and therapies as powerful tools for drug delivery, monitoring of specific analytes, and medical diagnostics. Most remarkably, integration of cellularized constructs within microengineered platforms has enabled the recapitulation of the physiological and pathological conditions of complex tissues and organs. The so-called “organ-on-a-chip” technology, which represents a new avenue in the field of advanced in vitro models, with the potential to revolutionize current approaches to drug screening and toxicology studies. This review aims to highlight recent advances of microfluidic-based devices towards a body-on-a-chip concept, exploring their technology and broad applications in the biomedical field.

Modeling bi-modality improves characterization of cell cycle on gene expression in single cells

Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%–17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome.

Recent technological advances have enabled the measurement of gene expression in individual cells, revealing that there is substantial variability in expression, even within a homogeneous cell population. In this paper, we develop new analytical methods that account for the intrinsic, stochastic nature of single cell expression in order to characterize the effect of cell cycle on gene expression at the single-cell level. Applying these methods to populations of asynchronously cycling cells, we are able to identify large numbers of genes with cell cycle-associated expression patterns. By measuring and adjusting for cellular-level factors, we are able to derive estimates of co-expressing gene networks that more closely reflect cellular-level processes as opposed to sample-level processes. We find that cell cycle phase only accounts for a modest amount of the overall variability of gene expression within an individual cell. The analytical methods demonstrated in this paper are universally applicable to single cell expression data and represent a promising tool to the scientific community.

Investigating evolutionary perspective of carcinogenesis with single-cell transcriptome analysis

We developed phase-switch microfluidic devices for molecular profiling of a large number of single cells. Whole genome microarrays and RNA-sequencing are commonly used to determine the expression levels of genes in cell lysates (a physical mix of millions of cells) for inferring gene functions. However, cellular heterogeneity becomes an inherent noise in the measurement of gene expression. The unique molecular characteristics of individual cells, as well as the temporal and quantitative information of gene expression in cells, are lost when averaged among all cells in cell lysates. Our single-cell technology overcomes this limitation and enables us to obtain a large number of single-cell transcriptomes from a population of cells. A collection of single-cell molecular profiles allows us to study carcinogenesis from an evolutionary perspective by treating cancer as a diverse population of cells with abnormal molecular characteristics. Because a cancer cell population contains cells at various stages of development toward drug resistance, clustering similar single-cell molecular profiles could reveal how drug-resistant sub-clones evolve during cancer treatment. Here, we discuss how single-cell transcriptome analysis technology could enable the study of carcinogenesis from an evolutionary perspective and the development of drug-resistance in leukemia. The single-cell transcriptome analysis reported here could have a direct and significant impact on current cancer treatments and future personalized cancer therapies.

Molecular characterization of heterogeneous mesenchymal stem cells with single-cell transcriptomes

Mesenchymal stem cells (MSC) are heterogeneous cell populations with promising therapeutic potentials in regenerative medicine. The therapeutic values of MSC in various clinical situations have been reported. Clonal assays (expansion of MSC from a single cell) demonstrated that multiple types of cells with different developmental potential exist in a MSC population. Due to the heterogeneous nature of MSC, molecular characterization of MSC in the absence of known biomarkers is a challenge for cell therapy with MSC. Here, we review potential therapeutic applications of MSC and discuss a systematic approach for molecular characterization of heterogeneous cell population using single-cell transcriptome analysis. Differentiation/maturation of cells is orchestrated by sequential expression of a series of genes within a cell. Therefore, single-cell mRNA expression (transcriptome) profiles from consecutive developmental stages are more similar than those from disparate stages. Bioinformatic analysis can cluster single-cell transcriptome profiles from consecutive developmental stages into a dendrogram based on the similarity matrix of these profiles. Because a single-cell is an ultimately "pure" sample in expression profiling, these dendrograms can be used to classify individual cells into molecular subpopulations within a heterogeneous cell population without known biomarkers. This approach is especially powerful in studying cell populations with little molecular information and few known biomarkers, for example the MSC populations. The molecular understanding will provide novel targets for manipulating MSC differentiation with small molecules and other drugs to enable safer and more effective therapeutic applications of MSC.

An automated microfluidic device for assessment of mammalian cell genetic stability

Single-cell transcriptome contains reliable gene regulatory relationships because gene-gene interactions only happen within a mammalian cell. While the study of gene-gene interactions enables us to understand the molecular mechanism of cellular events and evaluate molecular characteristics of a mammalian cell population, its complexity requires an analysis of a large number of single-cells at various stages. However, many existing microfluidic platforms cannot process single-cells effectively for routine molecular analysis. To address these challenges, we develop an integrated system with individual controller for effective single-cell transcriptome analysis. In this paper, we report an integrated microfluidic approach to rapidly measure gene expression in individual cells for genetic stability assessment of a cell population. Inside this integrated microfluidic device, the cells are individually manipulated and isolated in an array using micro sieve structures, then transferred into different nanoliter reaction chambers for parallel processing of single-cell transcriptome analysis. This device enables us to manipulate individual single-cells into nanoliter reactor with high recovery rate. We have performed gene expression analysis for a large number of HeLa cells and 293T cells expanded from a single-cell. Our data shows that even the house-keeping genes are expressed at heterogeneous levels within a clone of cells. The heterogeneity of actin expression reflects the genetic stability, and the expression distribution is different between cancer cells (HeLa) and immortalized 293T cells. The result demonstrates that this platform has the potential for assessment of genetic stability in cancer diagnosis.

Prototype for automatable, dielectrophoretically-accessed intracellular membrane-potential measurements by metal electrodes

Functional access to membrane proteins, for example, ion channels, of individual cells is an important prerequisite in drug discovery studies. The highly sophisticated patch-clamp method is widely used for electrogenic membrane proteins, but is demanding for the operator, and its automation remains challenging. The dielectrophoretically-accessed, intracellular membrane-potential measurement (DAIMM) method is a new technique showing high potential for automation of electrophysiological data recording in the whole-cell configuration. A cell suspension is brought between a mm-scaled planar electrode and a μm-scaled tip electrode, placed opposite to each other. Due to the asymmetric electrode configuration, the application of alternating electric fields (1-5 MHz) provokes a dielectrophoretic force acting on the target cell. As a consequence, the cell is accelerated and pierced by the tip electrode, hence functioning as the internal (working) electrode. We used the light-gated cation channel Channelrhodopsin-2 as a reporter protein expressed in HEK293 cells to characterize the DAIMM method in comparison with the patch-clamp technique.

Stem cells in microfluidics

Microfluidic techniques have been recently developed for cell-based assays. In microfluidic systems, the objective is for these microenvironments to mimic in vivo surroundings. With advantageous characteristics such as optical transparency and the capability for automating protocols, different types of cells can be cultured, screened, and monitored in real time to systematically investigate their morphology and functions under well-controlled microenvironments in response to various stimuli. Recently, the study of stem cells using microfluidic platforms has attracted considerable interest. Even though stem cells have been studied extensively using bench-top systems, an understanding of their behavior in in vivo-like microenvironments which stimulate cell proliferation and differentiation is still lacking. In this paper, recent cell studies using microfluidic systems are first introduced. The various miniature systems for cell culture, sorting and isolation, and stimulation are then systematically reviewed. The main focus of this review is on papers published in recent years studying stem cells by using microfluidic technology. This review aims to provide experts in microfluidics an overview of various microfluidic systems for stem cell research.

Microfluidic platform for controlling the differentiation of embryoid bodies

Embryonic stem (ES) cells are pluripotent cells, which can differentiate into any cell type. This cell type has often been implicated as an eminent source of renewable cells for tissue regeneration and cellular replacement therapies. Studies on manipulation of the various differentiation pathways have been at the forefront of research. There are many ways in which ES cells can be differentiated. One of the most common techniques is to initiate the development of embryoid bodies (EBs) by in vitro aggregation of ES cells. Thereafter, EBs can be induced to undergo differentiation into various cell lineages. In this article, we present a microfluidic platform using biocompatible materials, which is suitable for culturing EBs. The platform is based on a Y-channel device with two inlets for two different culturing media. An EB is located across both streams. Using the laminar characteristics at low Reynolds number and high Peclet numbers, we have induced cell differentiation on half of the EB while maintaining the other half in un-induced stages. The results prove the potential of using microfluidic technology for manipulation of EBs and ES cells in tissue engineering.

Stem cells in microfluidics

With the introduction of microtechnology and microfluidic platforms for cell culture, stem cell research can be put into a new context. Inside microfluidics, microenvironments can be more precisely controlled and their influence on cell fate studied. Microfluidic devices can be made transparent and the cells monitored real time by imaging, using fluorescence markers to probe cell functions and cell fate. This article gives a perspective on the yet untapped utility of microfluidic devices for stem cell research. It will guide the biologists through some basic microtechnology and the application of microfluidics to cell research, as well as highlight to the engineers the cell culture capabilities of microfluidics.

From the cellular perspective: exploring differences in the cellular baseline in macroscale and microfluidic cultures

Microfluidic devices for cell culture based assays provide new types of engineered microenvironments and new methods for controlling and quantifying cellular responses to these microenvironments. However, without an understanding of the effects of the microenvironments present in microdevices from a cellular perspective, it will be challenging to integrate work done in microdevices with biological data obtained via traditional methods. With the adaptation and validation of In Cell Westerns (ICWs) and in situ analysis techniques to microfluidic devices, we can begin to look at a variety of cellular responses to microcultures. Here we observe several differences in proliferation, glucose metabolism, signaling pathway activation and protein expression levels between cells cultured in traditional macroscale cultures and in microfluidic cultures. The issues of glucose starvation, growth factor restriction, volume density and effects of interactions with poly(dimethylsiloxane) (PDMS) were examined to determine the relative importance of each to cell behavior. Changes in glucose metabolism, insensitivity to volume density or media supplementation, and finally reduced proliferation as the exposure to PDMS increased, suggests that perhaps interactions between media/cells and this commonly employed polymer may be significant for some cell based assays. The differences between cells in macroscale and microfluidic cultures suggest that the cellular baseline may be substantially altered in microcultures due to both inherent differences in scale as well as material differences. The observations highlight the need to biologically validate micofluidic devices for cell based assays in order to accurately interpret the data obtained with them in the context of traditional macroculture data. Additional areas of study that will further characterize and validate microscale culture are discussed.