Microfluidic whole genome amplification device for single cell sequencing

Highly efficient cell-microbead encapsulation using dielectrophoresis-assisted dual-nanowell array

Recent advancements in micro/nanofabrication techniques have led to the development of portable devices for high-throughput single-cell analysis through the isolation of individual target cells, which are then paired with functionalized microbeads. Compared with commercially available benchtop instruments, portable microfluidic devices can be more widely and cost-effectively adopted in single-cell transcriptome and proteome analysis. The sample utilization and cell pairing rate (∼33%) of current stochastic-based cell-bead pairing approaches are fundamentally limited by Poisson statistics. Despite versatile technologies having been proposed to reduce randomness during the cell-bead pairing process in order to statistically beat the Poisson limit, improvement of the overall pairing rate of a single cell to a single bead is typically based on increased operational complexity and extra instability. In this article, we present a dielectrophoresis (DEP)-assisted dual-nanowell array (ddNA) device, which employs an innovative microstructure design and operating process that decouples the bead- and cell-loading processes. Our ddNA design contains thousands of subnanoliter microwell pairs specifically tailored to fit both beads and cells. Interdigitated electrodes (IDEs) are placed below the microwell structure to introduce a DEP force on cells, yielding high single-cell capture and pairing rates. Experimental results with human embryonic kidney cells confirmed the suitability and reproducibility of our design. We achieved a single-bead capture rate of >97% and a cell-bead pairing rate of >75%. We anticipate that our device will enhance the application of single-cell analysis in practical clinical use and academic research.

Whole Genome Amplification in Preimplantation Genetic Testing in the Era of Massively Parallel Sequencing

Successful whole genome amplification (WGA) is a cornerstone of contemporary preimplantation genetic testing (PGT). Choosing the most suitable WGA technique for PGT can be particularly challenging because each WGA technique performs differently in combination with different downstream processing and detection methods. The aim of this review is to provide insight into the performance and drawbacks of DOP-PCR, MDA and MALBAC, as well as the hybrid WGA techniques most widely used in PGT. As the field of PGT is moving towards a wide adaptation of comprehensive massively parallel sequencing (MPS)-based approaches, we especially focus our review on MPS parameters and detection opportunities of WGA-amplified material, i.e., mappability of reads, uniformity of coverage and its influence on copy number variation analysis, and genomic coverage and its influence on single nucleotide variation calling. The ability of MDA-based WGA solutions to better cover the targeted genome and the ability of PCR-based solutions to provide better uniformity of coverage are highlighted. While numerous comprehensive PGT solutions exploiting different WGA types and adjusted bioinformatic pipelines to detect copy number and single nucleotide changes are available, the ones exploiting MDA appear more advantageous. The opportunity to fully analyse the targeted genome is influenced by the MPS parameters themselves rather than the solely chosen WGA.

Leveraging single cell sequencing to unravel intra-tumour heterogeneity and tumour evolution in human cancers

Intra-tumour heterogeneity and tumour evolution are well-documented phenomena in human cancers. While the advent of next-generation sequencing technologies has facilitated the large-scale capture of genomic data, the field of single cell genomics is nascent but rapidly advancing and generating many new insights into the complex molecular mechanisms of tumour biology. In this review, we provide an overview of current single cell DNA sequencing technologies, exploring how recent methodological advancements have enumerated new insights into intra-tumour heterogeneity and tumour evolution. Areas highlighted include the potential power of single cell genome sequencing studies to explore evolutionary dynamics contributing to tumourigenesis through to progression, metastasis and therapy resistance. We also explore the use of in-situ sequencing technologies to study intra-tumour heterogeneity in a spatial context, as well as examining the use of single cell genomics to perform lineage tracing in both normal and malignant tissues. Finally, we consider the use of multi-modal single cell sequencing technologies. Taken together, it is hoped that these many facets of single cell genome sequencing will improve our understanding of tumourigenesis, progression and lethality in cancer leading to the development of novel therapies. This article is protected by copyright. All rights reserved.

Recent advances and application of whole genome amplification in molecular diagnosis and medicine

Whole genome amplification (WGA) is a technology for non-selective amplification of the whole genome sequence, first appearing in 1992. Its primary purpose is to amplify and reflect the whole genome of trace tissues and single cells without sequence bias and to provide sufficient DNA template for subsequent multigene and multilocus analysis, along with comprehensive genome research. WGA provides a method to obtain a large amount of genetic information from a small amount of DNA and provides a valuable tool for preserving limited samples in molecular biology. WGA technology is especially suitable for forensic identification and genetic disease research, along with new technologies such as next-generation sequencing (NGS). In addition, WGA is also widely used in single-cell sequencing. Due to the small amount of DNA in a single cell, it is often unable to meet the amount of samples needed for sequencing, so WGA is generally used to achieve the amplification of trace samples. This paper reviews WGA methods based on different principles, summarizes both amplification principle and amplification quality, and discusses the application prospects and challenges of WGA technology in molecular diagnosis and medicine.

Microfluidic single-cell transcriptomics: moving towards multimodal and spatiotemporal omics

Cells are the basic units of life with vast heterogeneity. Single-cell transcriptomics unveils cell-to-cell gene expression variabilities, discovers novel cell types, and uncovers the critical roles of cellular heterogeneity in biological processes. The recent advances in microfluidic technologies have greatly accelerated the development of single-cell transcriptomics with regard to throughput, sensitivity, cost, and automation. In this article, we review state-of-the-art microfluidic single-cell transcriptomics, with a focus on the methodologies. We first summarize six typical microfluidic platforms for isolation and transcriptomic analysis of single cells. Then the on-going trend of microfluidic transcriptomics towards multimodal omics, which integrates transcriptomics with other omics to provide more comprehensive pictures of gene expression networks, is discussed. We also highlight single-cell spatial transcriptomics and single-cell temporal transcriptomics that provide unprecedented spatiotemporal resolution to reveal transcriptomic dynamics in space and time, respectively. The emerging applications of microfluidic single-cell transcriptomics are also discussed. Finally, we discuss the current challenges to be tackled and provide perspectives on the future development of microfluidic single-cell transcriptomics.

Application of single cell genomics to focal epilepsies: A call to action

Focal epilepsies are the largest epilepsy subtype and associated with significant morbidity. Somatic variation is a newly recognized genetic mechanism underlying a subset of focal epilepsies, but little is known about the processes through which somatic mosaicism causes seizures, the cell types carrying the pathogenic variants, or their developmental origin. Meanwhile, the inception of single cell biology has completely revolutionized the study of neurological diseases and has the potential to answer some of these key questions. Focusing on single cell genomics, transcriptomics, and epigenomics in focal epilepsy research, circumvents the averaging artifact associated with studying bulk brain tissue and offers the kind of granularity that is needed for investigating the consequences of somatic mosaicism. Here we have provided a brief overview of some of the most developed single cell techniques and the major considerations around applying them to focal epilepsy research.

Methods and platforms for analysis of nucleic acids from single-cell based on microfluidics

Single-cell nucleic acid analysis aims at discovering the genetic differences between individual cells which is well known as the cellular heterogeneity. This technology facilitates cancer diagnosis, stem cell research, immune system analysis, and other life science applications. The conventional platforms for single-cell nucleic acid analysis more rely on manual operation or bulky devices. Recently, the emerging microfluidic technology has provided a perfect platform for single-cell nucleic acid analysis with the characteristic of accurate and automatic single-cell manipulation. In this review, we briefly summarized the procedure of single-cell nucleic acid analysis including single-cell isolation, single-cell lysis, nucleic acid amplification, and genetic analysis. And then, three representative microfluidic platforms for single-cell nucleic acid analysis are concluded as valve-, microwell-, and droplet-based platforms. Furthermore, we described the state-of-the-art integrated single-cell nucleic acid analysis systems based on the three platforms. Finally, the future development and challenges of microfluidics-based single-cell nucleic acid analysis are discussed as well.

Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics

Single-cell whole-genome sequencing (WGS) is critical for characterizing dynamic intercellular changes in DNA. Current sample preparation technologies for single-cell WGS are complex, expensive, and suffer from high amplification bias and errors. Here, we describe Digital-WGS, a sample preparation platform that streamlines high-performance single-cell WGS with automatic processing based on digital microfluidics. Using the method, we provide high single-cell capture efficiency for any amount and types of cells by a wetted hydrodynamic structure. The digital control of droplets in a closed hydrophobic interface enables the complete removal of exogenous DNA, sufficient cell lysis, and lossless amplicon recovery, achieving the low coefficient of variation and high coverage at multiple scales. The single-cell genomic variations profiling performs the excellent detection of copy number variants with the smallest bin of 150 kb and single-nucleotide variants with allele dropout rate of 5.2%, holding great promise for broader applications of single-cell genomics.

Comparison of Multiple Displacement Amplification (MDA) and Multiple Annealing and Looping-Based Amplification Cycles (MALBAC) in Limited DNA Sequencing Based on Tube and Droplet

Whole genome amplification (WGA) is crucial for whole genome sequencing to investigate complex genomic alteration at the single-cell or even single-molecule level. Multiple displacement amplification (MDA) and multiple annealing and looping based amplification cycles (MALBAC) are two most widely applied WGA methods, which have different advantages and disadvantages, dependent on research objectives. Herein, we compared the MDA and MALBAC to provide more information on their performance in droplets and tubes. We observed that the droplet method could dramatically reduce the amplification bias and retain the high accuracy of replication than the conventional tube method. Furthermore, the droplet method exhibited higher efficiency and sensitivity for both homozygous and heterozygous single nucleotide variants (SNVs) at the low sequencing depth. In addition, we also found that MALBAC offered a greater uniformity and reproducibility and MDA showed a better efficiency of genomic coverage and SNV detection. Our results provided insights that will allow future decision making.

Microfluidic Single-Cell Omics Analysis

The commonly existing cellular heterogeneity plays a critical role in biological processes such as embryonic development, cell differentiation, and disease progress. Single-cell omics-based heterogeneous studies have great significance for identifying different cell populations, discovering new cell types, revealing informative cell features, and uncovering significant interrelationships between cells. Recently, microfluidics has evolved to be a powerful technology for single-cell omics analysis due to its merits of throughput, sensitivity, and accuracy. Herein, the recent advances of microfluidic single-cell omics analysis, including different microfluidic platform designs, lysis strategies, and omics analysis techniques, are reviewed. Representative applications of microfluidic single-cell omics analysis in complex biological studies are then summarized. Finally, a few perspectives on the future challenges and development trends of microfluidic-assisted single-cell omics analysis are discussed.

Microfluidic single-cell analysis-Toward integration and total on-chip analysis

Various types of single-cell analyses are now extensively used to answer many biological questions, and with this growth in popularity, potential drawbacks to these methods are also becoming apparent. Depending on the specific application, workflows can be laborious, low throughput, and run the risk of contamination. Microfluidic designs, with their advantages of being high throughput, low in reaction volume, and compatible with bio-inert materials, have been widely used to improve single-cell workflows in all major stages of single-cell applications, from cell sorting to lysis, to sample processing and readout. Yet, designing an integrated microfluidic chip that encompasses the entire single-cell workflow from start to finish remains challenging. In this article, we review the current microfluidic approaches that cover different stages of processing in single-cell analysis and discuss the prospects and challenges of achieving a full integrated workflow to achieve total single-cell analysis in one device.

Injection Molded Microfluidics for Establishing High-Density Single Cell Arrays in an Open Hydrogel Format

Here, we develop an injection molded microfluidic approach for single cell analysis by making use of (1) rapidly curing injectable hydrogels, (2) a high density microfluidic weir trap array, and (3) reversibly bonded PDMS lids that are strong enough to withstand the injection molding process, but which can be peeled off after the hydrogel sets. This approach allows for single cell patterns to be created with densities exceeding 40 cells per mm2, is amenable to high speed imaging, and creates microfluidic devices that enable efficient nutrient and gas exchange and the delivery of specific biological and chemical reagents to individual cells. We show that it is possible to organize up to 10 000 single cells in a few minutes on the device, and we developed an image analysis program to automatically analyze the single-cell capture efficiency. The results show single cell trapping rates were better than 80%. We also demonstrate that the genomic DNA of the single cells trapped in the hydrogel can be amplified via localized, multiple displacement amplification in a massively parallel format, which offers a promising strategy for analyzing single cell genomes. Finally, we show the ability to perform selective staining of individual cells with a commercial bioprinter, providing proof of concept of its ability to deliver tailored reagents to specific cells in an array for future downstream analysis. This injection molded microfluidic approach leverages the benefits of both closed and open microfluidics, allows multiday single cell cultures, direct access to the trapped cells for genotypic end point studies.

Single-Cell Analysis Using Droplet Microfluidics

Droplet microfluidics has revolutionized the study of single cells. The ability to compartmentalize cells within picoliter droplets in microfluidic devices has opened up a wide range of strategies to extract information at the genomic, transcriptomic, proteomic, or metabolomic level from large numbers of individual cells. Studying the different molecular landscapes at single-cell resolution has provided the authors with a detailed picture of intracellular heterogeneity and the resulting changes in cellular phenotypes. In addition, these technologies have aided in the discovery of rare cells in tumors or in the immune system, and left the authors with a deeper understanding of the fundamental biological processes that determine cell fate. This review aims to provide a detailed overview of the various droplet microfluidic strategies reported in the literature, taking into account the sometimes subtle differences in workflow or reagents that enable or improve certain protocols. Specifically, approaches to targeted- and whole-genome analysis, as well as whole-transcriptome profiling techniques, are reviewed. In addition, an up-to-date overview of new methods to characterize and quantify single-cell protein levels, and of developments to screen secreted molecules such as antibodies, cytokines, or metabolites at the single-cell level, is provided.

Recent advances in microfluidic platforms for single-cell analysis in cancer biology, diagnosis and therapy

Understanding molecular, cellular, genetic and functional heterogeneity of tumors at the single-cell level has become a major challenge for cancer research. The microfluidic technique has emerged as an important tool that offers advantages in analyzing single-cells with the capability to integrate time-consuming and labour-intensive experimental procedures such as single-cell capture into a single microdevice at ease and in a high-throughput fashion. Single-cell manipulation and analysis can be implemented within a multi-functional microfluidic device for various applications in cancer research. Here, we present recent advances of microfluidic devices for single-cell analysis pertaining to cancer biology, diagnostics, and therapeutics. We first concisely introduce various microfluidic platforms used for single-cell analysis, followed with different microfluidic techniques for single-cell manipulation. Then, we highlight their various applications in cancer research, with an emphasis on cancer biology, diagnosis, and therapy. Current limitations and prospective trends of microfluidic single-cell analysis are discussed at the end.

Bacterial Single Cell Whole Transcriptome Amplification in Microfluidic Platform Shows Putative Gene Expression Heterogeneity

Single cell RNA sequencing is a technology that provides the capability of analyzing the transcriptome of a single cell from a population. So far, single cell RNA sequencing has been focused mostly on human cells due to the larger starting amount of RNA template for subsequent amplification. One of the major challenges of applying single cell RNA sequencing to microbial cells is to amplify the femtograms of the RNA template to obtain sufficient material for downstream sequencing with minimal contamination. To achieve this goal, efforts have been focused on multiround RNA amplification, but would introduce additional contamination and bias. In this work, we for the first time coupled a microfluidic platform with multiple displacement amplification technology to perform single cell whole transcriptome amplification and sequencing of Porphyromonas somerae, a microbe of interest in endometrial cancer, as a proof-of-concept demonstration of using single cell RNA sequencing tool to unveil gene expression heterogeneity in single microbial cells. Our results show that the bacterial single-cell gene expression regulation is distinct across different cells, supporting widespread heterogeneity.

Somatic mutation load and spectra: A record of DNA damage and repair in healthy human cells

Somatic genome instability is a hallmark of cancer genomes and has been linked to aging and a variety of other pathologies. Large-scale cancer genome and exome sequencing have revealed that mutation load and spectra in cancers can be influenced by environmental exposures, the anatomical site of exposures, and tissue type. There is now an abundance of data favoring the hypothesis that a substantial portion of the mutations in cancers originate prior to carcinogenesis in stem cells of the healthy individual. Rapid advances in sequencing of noncancer cells from healthy humans have shown that their mutation loads and spectra resemble cancer data. Similar to cancer genomes, mutation profiles of healthy cells show marked intra-individual variation, thus providing a metric of the various factors-environmental and endogenous-involved in mutagenesis in these individuals. This review focuses on the current methodologies to measure mutation loads and to determine mutation signatures for evaluating the environmental and endogenous sources of DNA damage in human somatic cells. We anticipate that in future, such large-scale studies aimed at exploring the landscapes of somatic mutations across different cell types in healthy people would provide a valuable resource for designing personalized preventative strategies against diseases associated with somatic genome instability. Environ. Mol. Mutagen. 59:672-686, 2018. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Sequencing of human genomes extracted from single cancer cells isolated in a valveless microfluidic device

Sequencing the genomes of individual cells enables the direct determination of genetic heterogeneity amongst cells within a population. We have developed an injection-moulded valveless microfluidic device in which single cells from colorectal cancer derived cell lines (LS174T, LS180 and RKO) and fresh colorectal tumors have been individually trapped, their genomes extracted and prepared for sequencing using multiple displacement amplification (MDA). Ninety nine percent of the DNA sequences obtained mapped to a reference human genome, indicating that there was effectively no contamination of these samples from non-human sources. In addition, most of the reads are correctly paired, with a low percentage of singletons (0.17 ± 0.06%) and we obtain genome coverages approaching 90%. To achieve this high quality, our device design and process shows that amplification can be conducted in microliter volumes as long as the lysis is in sub-nanoliter volumes. Our data thus demonstrates that high quality whole genome sequencing of single cells can be achieved using a relatively simple, inexpensive and scalable device. Detection of genetic heterogeneity at the single cell level, as we have demonstrated for freshly obtained single cancer cells, could soon become available as a clinical tool to precisely match treatment with the properties of a patient's own tumor.

Optofluidic Single-Cell Genome Amplification of Sub-micron Bacteria in the Ocean Subsurface

Optofluidic single-cell genome amplification was used to obtain genome sequences from sub-micron cells collected from the euphotic and mesopelagic zones of the northwestern Sargasso Sea. Plankton cells were visually selected and manually sorted with an optical trap, yielding 20 partial genome sequences representing seven bacterial phyla. Two organisms, E01-9C-26 (Gammaproteobacteria), represented by four single cell genomes, and Opi.OSU.00C, an uncharacterized Verrucomicrobia, were the first of their types retrieved by single cell genome sequencing and were studied in detail. Metagenomic data showed that E01-9C-26 is found throughout the dark ocean, while Opi.OSU.00C was observed to bloom transiently in the nutrient-depleted euphotic zone of the late spring and early summer. The E01-9C-26 genomes had an estimated size of 4.76-5.05 Mbps, and contained "O" and "W"-type monooxygenase genes related to methane and ammonium monooxygenases that were previously reported from ocean metagenomes. Metabolic reconstruction indicated E01-9C-26 are likely versatile methylotrophs capable of scavenging C1 compounds, methylated compounds, reduced sulfur compounds, and a wide range of amines, including D-amino acids. The genome sequences identified E01-9C-26 as a source of "O" and "W"-type monooxygenase genes related to methane and ammonium monooxygenases that were previously reported from ocean metagenomes, but are of unknown function. In contrast, Opi.OSU.00C genomes encode genes for catabolizing carbohydrate compounds normally associated with eukaryotic phytoplankton. This exploration of optofluidics showed that it was effective for retrieving diverse single-cell bacterioplankton genomes and has potential advantages in microbiology applications that require working with small sample volumes or targeting cells by their morphology.

Multiple single cell screening and DNA MDA amplification chip for oncogenic mutation profiling

The oncogenic mutation heterogeneity of the cancer cell population has been proven to be essential for predicting both drug-response and drug-resistance of targeted therapies, such as tyrosine kinase inhibitors. It is necessary to accurately evaluate the mutation heterogeneity, oncogenic mutation and resistant mutation profiling at a single cell level. However, there are two major hurdles in the process. First, majority of the cells in tumor tissue are non-cancer cells, which cause background noise. Second, the work load and cost of next generation sequencing on dozens of single cells are prohibitive. To address both these issues, we developed a microfluidic chip for profiling of dozens of selected cells. With the help of a novel tri-states valve structure, which performs precise controlling of the cell/reagent movement, as well as active mixing of different reagents, trapping/identification/lysis and in situ MDA amplification was achieved at a single cell level on the same chip. Using a proof-of-concept assay mimicking EGFR targeting drug Gefitinib treatment of lung cancer cells, the new method was validated as capable of not only detecting the existence of multiple mutations, but also providing complete information of the mutation scenario at the single cell level by using cost-effective Sanger's sequencing.

Recent advances in the use of microfluidic technologies for single cell analysis

The inherent heterogeneity in cell populations has become of great interest and importance as analytical techniques have improved over the past decades. With the advent of personalized medicine, understanding the impact of this heterogeneity has become an important challenge for the research community. Many different microfluidic approaches with varying levels of throughput and resolution exist to study single cell activity. In this review, we take a broad view of the recent microfluidic developments in single cell analysis based on microwell, microchamber, and droplet platforms. We cover physical, chemical, and molecular biology approaches for cellular and molecular analysis including newly emerging genome-wide analysis.

A short review of variants calling for single-cell-sequencing data with applications

The field of single-cell sequencing is fleetly expanding, and many techniques have been developed in the past decade. With this technology, biologists can study not only the heterogeneity between two adjacent cells in the same tissue or organ, but also the evolutionary relationships and degenerative processes in a single cell. Calling variants is the main purpose in analyzing single cell sequencing (SCS) data. Currently, some popular methods used for bulk-cell-sequencing data analysis are tailored directly to be applied in dealing with SCS data. However, SCS requires an extra step of genome amplification to accumulate enough quantity for satisfying sequencing needs. The amplification yields large biases and thus raises challenge for using the bulk-cell-sequencing methods. In order to provide guidance for the development of specialized analyzed methods as well as using currently developed tools for SNS, this paper aims to bridge the gap. In this paper, we firstly introduced two popular genome amplification methods and compared their capabilities. Then we introduced a few popular models for calling single-nucleotide polymorphisms and copy-number variations. Finally, break-through applications of SNS were summarized to demonstrate its potential in researching cell evolution.

Towards Multiplex Molecular Diagnosis-A Review of Microfluidic Genomics Technologies

Highly sensitive and specific pathogen diagnosis is essential for correct and timely treatment of infectious diseases, especially virulent strains, in people. Point-of-care pathogen diagnosis can be a tremendous help in managing disease outbreaks as well as in routine healthcare settings. Infectious pathogens can be identified with high specificity using molecular methods. A plethora of microfluidic innovations in recent years have now made it increasingly feasible to develop portable, robust, accurate, and sensitive genomic diagnostic devices for deployment at the point of care. However, improving processing time, multiplexed detection, sensitivity and limit of detection, specificity, and ease of deployment in resource-limited settings are ongoing challenges. This review outlines recent techniques in microfluidic genomic diagnosis and devices with a focus on integrating them into a lab on a chip that will lead towards the development of multiplexed point-of-care devices of high sensitivity and specificity.

Massively parallel whole genome amplification for single-cell sequencing using droplet microfluidics

Massively parallel single-cell genome sequencing is required to further understand genetic diversities in complex biological systems. Whole genome amplification (WGA) is the first step for single-cell sequencing, but its throughput and accuracy are insufficient in conventional reaction platforms. Here, we introduce single droplet multiple displacement amplification (sd-MDA), a method that enables massively parallel amplification of single cell genomes while maintaining sequence accuracy and specificity. Tens of thousands of single cells are compartmentalized in millions of picoliter droplets and then subjected to lysis and WGA by passive droplet fusion in microfluidic channels. Because single cells are isolated in compartments, their genomes are amplified to saturation without contamination. This enables the high-throughput acquisition of contamination-free and cell specific sequence reads from single cells (21,000 single-cells/h), resulting in enhancement of the sequence data quality compared to conventional methods. This method allowed WGA of both single bacterial cells and human cancer cells. The obtained sequencing coverage rivals those of conventional techniques with superior sequence quality. In addition, we also demonstrate de novo assembly of uncultured soil bacteria and obtain draft genomes from single cell sequencing. This sd-MDA is promising for flexible and scalable use in single-cell sequencing.

Single-Cell-Based Platform for Copy Number Variation Profiling through Digital Counting of Amplified Genomic DNA Fragments

We develop a novel single-cell-based platform through digital counting of amplified genomic DNA fragments, named multifraction amplification (mfA), to detect the copy number variations (CNVs) in a single cell. Amplification is required to acquire genomic information from a single cell, while introducing unavoidable bias. Unlike prevalent methods that directly infer CNV profiles from the pattern of sequencing depth, our mfA platform denatures and separates the DNA molecules from a single cell into multiple fractions of a reaction mix before amplification. By examining the sequencing result of each fraction for a specific fragment and applying a segment-merge maximum likelihood algorithm to the calculation of copy number, we digitize the sequencing-depth-based CNV identification and thus provide a method that is less sensitive to the amplification bias. In this paper, we demonstrate a mfA platform through multiple displacement amplification (MDA) chemistry. When performing the mfA platform, the noise of MDA is reduced; therefore, the resolution of single-cell CNV identification can be improved to 100 kb. We can also determine the genomic region free of allelic drop-out with mfA platform, which is impossible for conventional single-cell amplification methods.

Scaling by shrinking: empowering single-cell 'omics' with microfluidic devices

Recent advances in cellular profiling have demonstrated substantial heterogeneity in the behaviour of cells once deemed 'identical', challenging fundamental notions of cell 'type' and 'state'. Not surprisingly, these findings have elicited substantial interest in deeply characterizing the diversity, interrelationships and plasticity among cellular phenotypes. To explore these questions, experimental platforms are needed that can extensively and controllably profile many individual cells. Here, microfluidic structures - whether valve-, droplet- or nanowell-based - have an important role because they can facilitate easy capture and processing of single cells and their components, reducing labour and costs relative to conventional plate-based methods while also improving consistency. In this article, we review the current state-of-the-art methodologies with respect to microfluidics for mammalian single-cell 'omics' and discuss challenges and future opportunities.

SAG-QC: quality control of single amplified genome information by subtracting non-target sequences based on sequence compositions

Background

Whole genome amplification techniques have enabled the analysis of unexplored genomic information by sequencing of single-amplified genomes (SAGs). Whole genome amplification of single bacteria is currently challenging because contamination often occurs in experimental processes. Thus, to increase the confidence in the analyses of sequenced SAGs, bioinformatics approaches that identify and exclude non-target sequences from SAGs are required. Since currently reported approaches utilize sequence information in public databases, they have limitations when new strains are the targets of interest. Here, we developed a software SAG-QC that identify and exclude non-target sequences independent of database.

Results

In our method, “no template control” sequences acquired during WGA were used. We calculated the probability that a sequence was derived from contaminants by comparing k-mer compositions with the no template control sequences. Based on the results of tests using simulated SAG datasets, the accuracy of our method for predicting non-target sequences was higher than that of currently reported techniques. Subsequently, we applied our tool to actual SAG datasets and evaluated the accuracy of the predictions.

Conclusions

Our method works independently of public sequence information for distinguishing SAGs from non-target sequences. This method will be effective when employed against SAG sequences of unexplored strains and we anticipate that it will contribute to the correct interpretation of SAGs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1572-5) contains supplementary material, which is available to authorized users.

Microfluidics for genome-wide studies involving next generation sequencing

Next-generation sequencing (NGS) has revolutionized how molecular biology studies are conducted. Its decreasing cost and increasing throughput permit profiling of genomic, transcriptomic, and epigenomic features for a wide range of applications. Microfluidics has been proven to be highly complementary to NGS technology with its unique capabilities for handling small volumes of samples and providing platforms for automation, integration, and multiplexing. In this article, we review recent progress on applying microfluidics to facilitate genome-wide studies. We emphasize on several technical aspects of NGS and how they benefit from coupling with microfluidic technology. We also summarize recent efforts on developing microfluidic technology for genomic, transcriptomic, and epigenomic studies, with emphasis on single cell analysis. We envision rapid growth in these directions, driven by the needs for testing scarce primary cell samples from patients in the context of precision medicine.

Spinning micropipette liquid emulsion generator for single cell whole genome amplification

Many on-chip approaches that use flow-focusing to pinch the continuous aqueous phase into droplets have become the most popular methods that provide monodisperse emulsion droplets. However, not every lab can easily adapt a microfluidic workflow into their familiar protocols. We develop an off-chip approach, spinning micro-pipette liquid emulsion (SiMPLE) generator, to produce highly stable monodisperse water-in-oil emulsions using a moving micropipette to disperse the aqueous phase in an oil-filled microcentrifuge tube. This method provides a simple way to produce picoliter-size droplets in situ with no dead volume during emulsification. With SiMPLE, single-cell emulsion whole genome amplification was performed to demonstrate that this novel method can seamlessly be integrated with experimental operations and supplies that most researchers are familiar with. The SiMPLE generator has effectively lowered the technical difficulties in applications relying on emulsion droplets.

Reality of Single Circulating Tumor Cell Sequencing for Molecular Diagnostics in Pancreatic Cancer

To understand the potential and limitations of circulating tumor cell (CTC) sequencing for molecular diagnostics, we investigated the feasibility of identifying the ubiquitous KRAS mutation in single CTCs from pancreatic cancer (PC) patients. We used the NanoVelcro/laser capture microdissection CTC platform, combined with whole genome amplification and KRAS Sanger sequencing. We assessed both KRAS codon-12 coverage and the degree that allele dropout during whole genome amplification affected the detection of KRAS mutations from single CTCs. We isolated 385 single cells, 163 from PC cell lines and 222 from the blood of 12 PC patients, and obtained KRAS sequence coverage in 218 of 385 single cells (56.6%). For PC cell lines with known KRAS mutations, single mutations were detected in 67% of homozygous cells but only 37.4% of heterozygous single cells, demonstrating that both coverage and allele dropout are important causes of mutation detection failure from single cells. We could detect KRAS mutations in CTCs from 11 of 12 patients (92%) and 33 of 119 single CTCs sequenced, resulting in a KRAS mutation detection rate of 27.7%. Importantly, KRAS mutations were never found in the 103 white blood cells sequenced. Sequencing of groups of cells containing between 1 and 100 cells determined that at least 10 CTCs are likely required to reliably assess KRAS mutation status from CTCs.

Nonspecific Organelle-Targeting Strategy with Core-Shell Nanoparticles of Varied Lipid Components/Ratios

We report a nonspecific organelle-targeting strategy through one-step microfluidic fabrication and screening of a library of surface charge- and lipid components/ratios-varied lipid shell-polymer core nanoparticles. Different from the common strategy relying on the use of organelle-targeted moieties conjugated onto the surface of nanoparticles, here, we program the distribution of hybrid nanoparticles in lysosomes or mitochondria by tuning the lipid components/ratios in shell. Hybrid nanoparticles with 60% 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) and 20% 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) can intracellularly target mitochondria in both in vitro and in vivo models. While replacing DOPE with the same amount of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), the nanoparticles do not show mitochondrial targeting, indicating an incremental effect of cationic and fusogenic lipids on lysosomal escape which is further studied by molecular dynamics simulations. This work unveils the lipid-regulated subcellular distribution of hybrid nanoparticles in which target moieties and complex synthetic steps are avoided.

Innovative Tools and Technology for Analysis of Single Cells and Cell-Cell Interaction

Heterogeneity in single-cell responses and intercellular interactions results from complex regulation of cell-intrinsic and environmental factors. Single-cell analysis allows not only detection of individual cellular characteristics but also correlation of genetic content with phenotypic traits in the same cell. Technological advances in micro- and nanofabrication have benefited single-cell analysis by allowing precise control of the localized microenvironment, cell manipulation, and sensitive detection capabilities. Additionally, microscale techniques permit rapid, high-throughput, multiparametric screening that has become essential for -omics research. This review highlights innovative applications of microscale platforms in genetic, proteomic, and metabolic detection in single cells; cell sorting strategies; and heterotypic cell-cell interaction. We discuss key design aspects of single-cell localization and isolation in microfluidic systems, dynamic and endpoint analyses, and approaches that integrate highly multiplexed detection of various intracellular species.

Single-cell genome sequencing: current state of the science

The field of single-cell genomics is advancing rapidly and is generating many new insights into complex biological systems, ranging from the diversity of microbial ecosystems to the genomics of human cancer. In this Review, we provide an overview of the current state of the field of single-cell genome sequencing. First, we focus on the technical challenges of making measurements that start from a single molecule of DNA, and then explore how some of these recent methodological advancements have enabled the discovery of unexpected new biology. Areas highlighted include the application of single-cell genomics to interrogate microbial dark matter and to evaluate the pathogenic roles of genetic mosaicism in multicellular organisms, with a focus on cancer. We then attempt to predict advances we expect to see in the next few years.

A microfluidic approach to parallelized transcriptional profiling of single cells

The ability to correlate single-cell genetic information with cellular phenotypes is of great importance to biology and medicine, as it holds the potential to gain insight into disease pathways that is unavailable from ensemble measurements. We present a microfluidic approach to parallelized, rapid, quantitative analysis of messenger RNA from single cells via RT-qPCR. The approach leverages an array of single-cell RT-qPCR analysis units formed by a set of parallel microchannels concurrently controlled by elastomeric pneumatic valves, thereby enabling parallelized handling and processing of single cells in a drastically simplified operation procedure using a relatively small number of microvalves. All steps for single-cell RT-qPCR, including cell isolation and immobilization, cell lysis, mRNA purification, reverse transcription and qPCR, are integrated on a single chip, eliminating the need for off-chip manual cell and reagent transfer and qPCR amplification as commonly used in existing approaches. Additionally, the approach incorporates optically transparent microfluidic components to allow monitoring of single-cell trapping without the need for molecular labeling that can potentially alter the targeted gene expression and utilizes a polycarbonate film as a barrier against evaporation to minimize the loss of reagents at elevated temperatures during the analysis. We demonstrate the utility of the approach by the transcriptional profiling for the induction of the cyclin-dependent kinase inhibitor 1a and the glyceraldehyde 3-phosphate dehydrogenase in single cells from the MCF-7 breast cancer cell line. Furthermore, the methyl methanesulfonate is employed to allow measurement of the expression of the genes in individual cells responding to a genotoxic stress.

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.

Uniform and accurate single-cell sequencing based on emulsion whole-genome amplification

Whole-genome amplification (WGA) for next-generation sequencing has seen wide applications in biology and medicine when characterization of the genome of a single cell is required. High uniformity and fidelity of WGA is needed to accurately determine genomic variations, such as copy number variations (CNVs) and single-nucleotide variations (SNVs). Prevailing WGA methods have been limited by fluctuation of the amplification yield along the genome, as well as false-positive and -negative errors for SNV identification. Here, we report emulsion WGA (eWGA) to overcome these problems. We divide single-cell genomic DNA into a large number (10(5)) of picoliter aqueous droplets in oil. Containing only a few DNA fragments, each droplet is led to reach saturation of DNA amplification before demulsification such that the differences in amplification gain among the fragments are minimized. We demonstrate the proof-of-principle of eWGA with multiple displacement amplification (MDA), a popular WGA method. This easy-to-operate approach enables simultaneous detection of CNVs and SNVs in an individual human cell, exhibiting significantly improved amplification evenness and accuracy.

Comparison of variations detection between whole-genome amplification methods used in single-cell resequencing

BACKGROUND

Single-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed.

RESULTS

We systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2).

CONCLUSIONS

Our findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level.

Comparison of variations detection between whole-genome amplification methods used in single-cell resequencing

BACKGROUND

Single-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed.

RESULTS

We systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2).

CONCLUSIONS

Our findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level.

Development of nanotoxicology: implications for drug delivery and medical devices

Current nanotoxicology research suffers from suboptimal in vitro models, lack of in vitro–in vivo correlations, variability within in vitro protocols, deficits in both material purity and physicochemical characterization. Reliable nanomaterial toxicity and mechanistic insights are required for health and toxicity risk assessments. Much in vitro toxicological data is inconclusive in designating whether nanomaterials for drug delivery and medical device implants are truly safe. A critique is presented to analyze the interface between toxicology and nanopharmaceuticals. Deficiencies of existing practices in toxicology are reviewed and useful emerging techniques (e.g., lab-on-a-chip, tissue engineering, atomic force microscopy, high-content analysis) are highlighted. Cross-fertilization between disciplines will aid development of biocompatible delivery and implant platforms while improvements are being suggested for better translation of nanotoxicology.

Quantitative assessment of single-cell whole genome amplification methods for detecting copy number variation using hippocampal neurons

Single-cell genomic analysis has grown rapidly in recent years and finds widespread applications in various fields of biology, including cancer biology, development, immunology, pre-implantation genetic diagnosis, and neurobiology. To date, the amplification bias, amplification uniformity and reproducibility of the three major single cell whole genome amplification methods (GenomePlex WGA4, MDA and MALBAC) have not been systematically investigated using mammalian cells. In this study, we amplified genomic DNA from individual hippocampal neurons using three single-cell DNA amplification methods, and sequenced them at shallow depth. We then systematically evaluated the GC-bias, reproducibility, and copy number variations among individual neurons. Our results showed that single-cell genome sequencing results obtained from the MALBAC and WGA4 methods are highly reproducible and have a high success rate. The MALBAC displays significant biases towards high GC content. We then attempted to correct the GC bias issue by developing a bioinformatics pipeline, which allows us to call CNVs in single cell sequencing data, and chromosome level and sub-chromosomal level CNVs among individual neurons can be detected. We also proposed a metric to determine the CNV detection limits. Overall, MALBAC and WGA4 have better performance than MDA in detecting CNVs.