Monodisperse Picoliter Droplets for Low-Bias and Contamination-Free Reactions in Single-Cell Whole Genome Amplification

Whole genome amplification (WGA) is essential for obtaining genome sequences from single bacterial cells because the quantity of template DNA contained in a single cell is very low. Multiple displacement amplification (MDA), using Phi29 DNA polymerase and random primers, is the most widely used method for single-cell WGA. However, single-cell MDA usually results in uneven genome coverage because of amplification bias, background amplification of contaminating DNA, and formation of chimeras by linking of non-contiguous chromosomal regions. Here, we present a novel MDA method, termed droplet MDA, that minimizes amplification bias and amplification of contaminants by using picoliter-sized droplets for compartmentalized WGA reactions. Extracted DNA fragments from a lysed cell in MDA mixture are divided into 10⁵ droplets (67 pL) within minutes via flow through simple microfluidic channels. Compartmentalized genome fragments can be individually amplified in these droplets without the risk of encounter with reagent-borne or environmental contaminants. Following quality assessment of WGA products from single Escherichia coli cells, we showed that droplet MDA minimized unexpected amplification and improved the percentage of genome recovery from 59% to 89%. Our results demonstrate that microfluidic-generated droplets show potential as an efficient tool for effective amplification of low-input DNA for single-cell genomics and greatly reduce the cost and labor investment required for determination of nearly complete genome sequences of uncultured bacteria from environmental samples.     

单细胞机械性能检测方法与应用研究进展

细胞机械性能与细胞的生理状态与功能存在密切联系。早期对于细胞机械性能的研究受制于技术条件,只能获得细胞群的弹性或剪切模量,使得少量异质细胞的机械表型被淹没。近年来,单细胞机械性能检测技术得到了蓬勃发展。原子力显微镜、微吸管技术、光镊与光学拉伸、磁扭转流变仪与磁镊等单细胞机械性能检测技术展现出非常高的检测精度,但检测通量相对较低。新型微流控高通量检测方法的出现使检测通量呈几何式增长,有望解决大样本快速检测的需求。本文首先综述原子力显微镜、微吸管、光镊与光学拉伸和磁扭转流变仪与磁镊等单细胞机械性能检测技术。在此基础上,重点介绍细胞过孔、剪切诱导细胞变形和拉伸诱导细胞变形3种新兴微流控高通量检测技术的工作原理及最新研究进展,探讨各类方法的优缺点。最后,本文展望单细胞机械性能检测技术的未来发展方向。     

Five-in-One: Simultaneous isolation of multiple major liver cell types from livers of normal and NASH mice

NASH is a chronic liver disease that affects 3%–6% of individuals and requires urgent therapeutic developments. Isolating the key cell types in the liver is a necessary step towards understanding their function and roles in disease pathogenesis. However, traditional isolation methods through gradient centrifugation can only collect one or a few cell types simultaneously and pose technical difficulties when applied to NASH livers. Taking advantage of identified cell surface markers from liver single-cell RNAseq, here we established the combination of gradient centrifugation and antibody-based cell sorting techniques to isolate five key liver cell types (hepatocytes, endothelial cells, stellate cells, macrophages and other immune cells) from a single mouse liver. This method yielded high purity of each cell type from healthy and NASH livers. Our five-in-one protocol simultaneously isolates key liver cell types with high purity under normal and NASH conditions, enabling for systematic and accurate exploratory experiments such as RNA sequencing.     

Single-cell analysis of yeast, mammalian cells, and fungal spores with a microfluidic pressure-driven chip-based system.

BACKGROUND: Cytomics aims at understanding the function of cellular systems by analysis of single cells. Recently, there has been a growing interest in single cell measurements being performed in microfluidic systems. These systems promise to integrate staining, measurement, and analysis in a single system. One important aspect is the limitation of allowable cell sizes due to microfluidic channel dimensions. Here we want to demonstrate the broad applicability of microfluidic chip technology for the analysis of many different cell types. METHODS: We have developed a microfluidic chip and measurement system that allows flow cytometric analysis of fluorescently stained cells from different organisms. In this setup, the cells are moved by pressure-driven flow inside a network of microfluidic channels and are analyzed individually by fluorescence detection. RESULTS: We have successfully applied the system to develop a methodology to detect viable and dead cells in yeast cell populations. Also, we have measured short interfering RNA (siRNA) mediated silencing of protein expression in mammalian cells. In addition, we have characterized the infection state of Magnaportae grisea fungal spores. CONCLUSIONS: Results obtained with the microfluidic system demonstrate a broad applicability of microfluidic flow cytometry to measurement of various cell types.     

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

Single-cell quantitative real-time PCR (qRT-PCR) combined with high-throughput arrays allows the analysis of gene expression profiles at a molecular level in approximately 11 h after cell sample collection. We present here a high-content microfluidic real-time platform as a powerful tool for comparatively investigating the regulation of developmental processes in single cells. This approach overcomes the limitations involving heterogeneous cell populations and sample amounts, and may shed light on differential regulation of gene expression in normal versus disease-related contexts. Furthermore, high-throughput single-cell qRT-PCR provides a standardized, comparative assay for in-depth analysis of the mechanisms underlying human pluripotent stem cell self-renewal and differentiation.     

Recent advances in single-cell analysis using capillary electrophoresis and microfluidic devices

Cells are the fundamental unit of life, and studies on cell contribute to reveal the mystery of life. However, since variability exists between individual cells even in the same kind of cells, increased emphasis has been put on the analysis of individual cells for getting better understanding on the organism functions. During the past two decades, various techniques have been developed for single-cell analysis. Capillary electrophoresis is an excellent technique for identifying and quantifying the contents of single cells. The microfluidic devices afford a versatile platform for single-cell analysis owing to their unique characteristics. This article provides a review on recent advances in single-cell analysis using capillary electrophoresis and microfluidic devices; focus areas to be covered include sampling techniques, detection methods and main applications in capillary electrophoresis, and cell culture, cell manipulation, chemical cytometry and cellular physiology on microfluidic devices.     

Purification of Specific Cell Population by Fluorescence Activated Cell Sorting (FACS)

Experimental and clinical studies often require highly purified cell populations. FACS is a technique of choice to purify cell populations of known phenotype. Other bulk methods of purification include panning, complement depletion and magnetic bead separation. However, FACS has several advantages over other available methods. FACS is the preferred method when very high purity of the desired population is required, when the target cell population expresses a very low level of the identifying marker or when cell populations require separation based on differential marker density. In addition, FACS is the only available purification technique to isolate cells based on internal staining or intracellular protein expression, such as a genetically modified fluorescent protein marker. FACS allows the purification of individual cells based on size, granularity and fluorescence. In order to purify cells of interest, they are first stained with fluorescently-tagged monoclonal antibodies (mAb), which recognize specific surface markers on the desired cell population (1). Negative selection of unstained cells is also possible. FACS purification requires a flow cytometer with sorting capacity and the appropriate software. For FACS, cells in suspension are passed as a stream in droplets with each containing a single cell in front of a laser. The fluorescence detection system detects cells of interest based on predetermined fluorescent parameters of the cells. The instrument applies a charge to the droplet containing a cell of interest and an electrostatic deflection system facilitates collection of the charged droplets into appropriate collection tubes (2). The success of staining and thereby sorting depends largely on the selection of the identifying markers and the choice of mAb. Sorting parameters can be adjusted depending on the requirement of purity and yield. Although FACS requires specialized equipment and personnel training, it is the method of choice for isolation of highly purified cell populations.     

Microfluidic single cell analysis: from promise to practice

Methods for single-cell analysis are critical to revealing cell-to-cell variability in biological systems, especially in cases where relevant minority cell populations can be obscured by population-averaged measurements. However, to date single cell studies have been limited by the cost and throughput required to examine large numbers of cells and the difficulties associated with analyzing small amounts of starting material. Microfluidic approaches are well suited to resolving these issues by providing increased senstitivity, economy of scale, and automation. After many years of development microfluidic systems are now finding traction in a variety of single-cell analytics including gene expression measurements, protein analysis, signaling response, and growth dynamics. With newly developed tools now being applied in fields ranging from human haplotyping and drug discovery to stem cell and cancer research, the long-heralded promise of microfluidic single cell analysis is now finally being realized.     

Cancer Cell Analyses at the Single Cell-Level Using Electroactive Microwell Array Device

Circulating tumor cells (CTCs), shed from primary tumors and disseminated into peripheral blood, are playing a major role in metastasis. Even after isolation of CTCs from blood, the target cells are mixed with a population of other cell types. Here, we propose a new method for analyses of cell mixture at the single-cell level using a microfluidic device that contains arrayed electroactive microwells. Dielectrophoretic (DEP) force, induced by the electrodes patterned on the bottom surface of the microwells, allows efficient trapping and stable positioning of single cells for high-throughput biochemical analyses. We demonstrated that various on-chip analyses including immunostaining, viability/apoptosis assay and fluorescent in situ hybridization (FISH) at the single-cell level could be conducted just by applying specific reagents for each assay. Our simple method should greatly help discrimination and analysis of rare cancer cells among a population of blood cells.     

Single-Cell Gene Expression Analysis: Implications for Neurodegenerative and Neuropsychiatric Disorders

Technical and experimental advances in microaspiration techniques, RNA amplification, quantitative real-time polymerase chain reaction (qPCR), and cDNA microarray analysis have led to an increase in the number of studies of single-cell gene expression. In particular, the central nervous system (CNS) is an ideal structure to apply single-cell gene expression paradigms. Unlike an organ that is composed of one principal cell type, the brain contains a constellation of neuronal and noneuronal populations of cells. A goal is to sample gene expression from similar cell types within a defined region without potential contamination by expression profiles of adjacent neuronal subpopulations and noneuronal cells. The unprecedented resolution afforded by single-cell RNA analysis in combination with cDNA microarrays and qPCR-based analyses allows for relative gene expression level comparisons across cell types under different experimental conditions and disease states. The ability to analyze single cells is an important distinction from global and regional assessments of mRNA expression and can be applied to optimally prepared tissues from animal models as well as postmortem human brain tissues. This focused review illustrates the potential power of single-cell gene expression studies within the CNS in relation to neurodegenerative and neuropsychiatric disorders such as Alzheimer's disease (AD) and schizophrenia, respectively.     

Integration of Droplet Microfluidic Tools for Single-cell Functional Metagenomics:An Engineering Head Start

Droplet microfluidic techniques have shown promising outcome to study single cells at high throughput. However, their adoption in laboratories studying"-omics"sciences is still irrelevant due to the complex and multi-disciplinary nature of the field. To facilitate their use, here we provide engineering details and organized protocols for integrating three droplet-based microfluidic technologies into the metagenomic pipeline to enable functional screening of bioproducts at high throughput. First, a device encapsulating single cells in droplets at a rate of～ 250 Hz is described considering droplet size and cell growth. Then, we expand on previously reported fluorescence-activated droplet sorting systems to integrate the use of 4 independent fluorescence-exciting lasers (i.e., 405, 488, 561, and 637 nm) in a single platform to make it compatible with different fluorescence-emitting biosensors. For this sorter, both hardware and software are provided and optimized for effortlessly sorting droplets at 60 Hz. Then, a passive droplet merger is also integrated into our pipeline to enable adding new reagents to already-made droplets at a rate of 200 Hz. Finally, we provide an optimized recipe for manufacturing these chips using silicon dry-etching tools. Because of the overall integration and the technical details presented here, our approach allows biologists to quickly use microfluidic technologies and achieve both single-cell resolution and high-throughput capability (>50,000 cells/day) for mining and bioprospecting metagenomic data.     

Single-Cell Genetic Analysis Using Automated Microfluidics to Resolve Somatic Mosaicism

Somatic mosaicism occurs throughout normal development and contributes to numerous disease etiologies, including tumorigenesis and neurological disorders. Intratumor genetic heterogeneity is inherent to many cancers, creating challenges for effective treatments. Unfortunately, analysis of bulk DNA masks subclonal phylogenetic architectures created by the acquisition and distribution of somatic mutations amongst cells. As a result, single-cell genetic analysis is becoming recognized as vital for accurately characterizing cancers. Despite this, methods for single-cell genetics are lacking. Here we present an automated microfluidic workflow enabling efficient cell capture, lysis, and whole genome amplification (WGA). We find that ~90% of the genome is accessible in single cells with improved uniformity relative to current single-cell WGA methods. Allelic dropout (ADO) rates were limited to 13.75% and variant false discovery rates (SNV FDR) were 4.11x10^-6, on average. Application to ER-/PR-/HER2+ breast cancer cells and matched normal controls identified novel mutations that arose in a subpopulation of cells and effectively resolved the segregation of known cancer-related mutations with single-cell resolution. Finally, we demonstrate effective cell classification using mutation profiles with 10X average exome coverage depth per cell. Our data demonstrate an efficient automated microfluidic platform for single-cell WGA that enables the resolution of somatic mutation patterns in single cells.     

Microgenomics: Identification of new expression profiles via small and single-cell sample analyses.

BACKGROUND: Since the sequencing of the human genome has been finished, microgenomics has been booming, employing highly sophisticated, high-throughput platforms. But these mainly chip-based methods can only generate biologically relevant data if the samples investigated consist of homogeneous cell populations, in which no unwanted cells of different specificity and/or developmental stage obscure the results. METHODS: Different sampling methods have been routinely applied to overcome the problem presented by heterogeneous samples, e.g., global surveys, cell cultures, and microdissection. Various methods of laser-assisted microdissection, employing either positive or negative selection of tissue areas or even single cells, are available. RESULTS: These laser-assisted microdissection methods allow for fast and precise procurement of extremely small samples. Through subsequent application of recently developed methods of linear mRNA amplification in a pool of isolated total RNA, it has now become possible to perform complex high-throughput RNA expression profiling by microdissecting and processing even single-cell samples. CONCLUSIONS: Studies using the tools and methods of microgenomics have shed light on how those new approaches will eventually aid in the development of a new generation of diagnostics, e.g., leading to new patient-specific drugs tailored to the requirements assessed by assaying only a few biopsy cells.     

A statistical framework for multiparameter analysis at the single-cell level

Phenotypic characterization of individual cells provides crucial insights into intercellular heterogeneity and enables access to information that is unavailable from ensemble averaged, bulk cell analyses. Single-cell studies have attracted significant interest in recent years and spurred the development of a variety of commercially available and research-grade technologies. To quantify cell-to-cell variability of cell populations, we have developed an experimental platform for real-time measurements of oxygen consumption (OC) kinetics at the single-cell level. Unique challenges inherent to these single-cell measurements arise, and no existing data analysis methodology is available to address them. Here we present a data processing and analysis method that addresses challenges encountered with this unique type of data in order to extract biologically relevant information. We applied the method to analyze OC profiles obtained with single cells of two different cell lines derived from metaplastic and dysplastic human Barrett's esophageal epithelium. In terms of method development, three main challenges were considered for this heterogeneous dynamic system: (i) high levels of noise, (ii) the lack of a priori knowledge of single-cell dynamics, and (iii) the role of intercellular variability within and across cell types. Several strategies and solutions to address each of these three challenges are presented. The features such as slopes, intercepts, breakpoint or change-point were extracted for every OC profile and compared across individual cells and cell types. The results demonstrated that the extracted features facilitated exposition of subtle differences between individual cells and their responses to cell-cell interactions. With minor modifications, this method can be used to process and analyze data from other acquisition and experimental modalities at the single-cell level, providing a valuable statistical framework for single-cell analysis.