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.

[1]  Aaron R Wheeler,et al.  Microfluidic device for single-cell analysis. , 2003, Analytical chemistry.

[2]  X. Xie,et al.  Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients , 2013, Proceedings of the National Academy of Sciences.

[3]  Ambrose Carr,et al.  Scalable microfluidics for single-cell RNA printing and sequencing , 2015, Genome Biology.

[4]  Björn Önfelt,et al.  A silicon-glass microwell platform for high-resolution imaging and high-content screening with single cell resolution , 2011, Biomedical microdevices.

[5]  Rona S. Gertner,et al.  Single cell RNA Seq reveals dynamic paracrine control of cellular variation , 2014, Nature.

[6]  Hakho Lee,et al.  Photocleavable DNA barcode-antibody conjugates allow sensitive and multiplexed protein analysis in single cells. , 2012, Journal of the American Chemical Society.

[7]  James R Heath,et al.  Quantitating cell-cell interaction functions with applications to glioblastoma multiforme cancer cells. , 2012, Nano letters.

[8]  Bo Huang,et al.  Counting Low-Copy Number Proteins in a Single Cell , 2007, Science.

[9]  Shuqiang Li,et al.  Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction , 2016, Genome Biology.

[10]  Cole Trapnell,et al.  The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells , 2014, Nature Biotechnology.

[11]  Jeff Mellen,et al.  High-Throughput Droplet Digital PCR System for Absolute Quantitation of DNA Copy Number , 2011, Analytical chemistry.

[12]  N. Neff,et al.  Reconstructing lineage hierarchies of the distal lung epithelium using single cell RNA-seq , 2014, Nature.

[13]  G. Whitesides The origins and the future of microfluidics , 2006, Nature.

[14]  Todd M. Allen,et al.  Antiviral CD8+ T Cells Restricted by Human Leukocyte Antigen Class II Exist during Natural HIV Infection and Exhibit Clonal Expansion , 2016, Immunity.

[15]  R. Zengerle,et al.  Proximity Ligation Assay for High-content Profiling of Cell Signaling Pathways on a Microfluidic Chip* , 2013, Molecular & Cellular Proteomics.

[16]  Nir Friedman,et al.  Monitoring the dynamics of primary T cell activation and differentiation using long term live cell imaging in microwell arrays. , 2012, Lab on a chip.

[17]  Nathan C. Sheffield,et al.  The accessible chromatin landscape of the human genome , 2012, Nature.

[18]  Alex A. Pollen,et al.  Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex , 2014, Nature Biotechnology.

[19]  P. Blainey The future is now: single-cell genomics of bacteria and archaea. , 2013, FEMS microbiology reviews.

[20]  R. Milo,et al.  Dynamic Proteomics of Individual Cancer Cells in Response to a Drug , 2008, Science.

[21]  Howard Y. Chang,et al.  Single-cell chromatin accessibility reveals principles of regulatory variation , 2015, Nature.

[22]  E V Koonin,et al.  Lineage-specific gene expansions in bacterial and archaeal genomes. , 2001, Genome research.

[23]  Jong Kyoung Kim,et al.  Corrigendum: Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression , 2015, Nature Communications.

[24]  Ralph Weissleder,et al.  Cancer Cell Profiling by Barcoding Allows Multiplexed Protein Analysis in Fine-Needle Aspirates , 2014, Science Translational Medicine.

[25]  Adrian W. Briggs,et al.  Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers , 2015, The ISME Journal.

[26]  Jeffrey W. Smith,et al.  Stochastic Gene Expression in a Single Cell , .

[27]  Ali Bashashati,et al.  Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates , 2016, Proceedings of the National Academy of Sciences.

[28]  Rong Fan,et al.  Single-cell proteomic chip for profiling intracellular signaling pathways in single tumor cells , 2011, Proceedings of the National Academy of Sciences.

[29]  Helene Andersson-Svahn,et al.  Analysis of transient migration behavior of natural killer cells imaged in situ and in vitro. , 2011, Integrative biology : quantitative biosciences from nano to macro.

[30]  Daniel L. Vera,et al.  Open chromatin reveals the functional maize genome , 2016, Proceedings of the National Academy of Sciences.

[31]  Stephen R Quake,et al.  Single-Cell DNA-Methylation Analysis Reveals Epigenetic Chimerism in Preimplantation Embryos , 2013, Science.

[32]  Francisco Feijó Delgado,et al.  High-throughput measurement of single-cell growth rates using serial microfluidic mass sensor arrays , 2016, Nature Biotechnology.

[33]  L. Hood,et al.  Integrated barcode chips for rapid, multiplexed analysis of proteins in microliter quantities of blood , 2008, Nature Biotechnology.

[34]  C. Ponting,et al.  G&T-seq: parallel sequencing of single-cell genomes and transcriptomes , 2015, Nature Methods.

[35]  N. Navin,et al.  Clonal Evolution in Breast Cancer Revealed by Single Nucleus Genome Sequencing , 2014, Nature.

[36]  Zhi Zhu,et al.  Highly sensitive and quantitative detection of rare pathogens through agarose droplet microfluidic emulsion PCR at the single-cell level. , 2012, Lab on a chip.

[37]  Grace X. Y. Zheng,et al.  Massively parallel digital transcriptional profiling of single cells , 2016, bioRxiv.

[38]  J. Stenvang,et al.  Homogenous 96-Plex PEA Immunoassay Exhibiting High Sensitivity, Specificity, and Excellent Scalability , 2014, PloS one.

[39]  D. Weitz,et al.  Droplet microfluidics for high-throughput biological assays. , 2012, Lab on a chip.

[40]  George Georgiou,et al.  High-throughput sequencing of the paired human immunoglobulin heavy and light chain repertoire , 2013, Nature Biotechnology.

[41]  Yaniv Lubling,et al.  Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell , 2015, Nature Protocols.

[42]  Stephen R Quake,et al.  Whole-genome molecular haplotyping of single cells , 2011, Nature Biotechnology.

[43]  Peter Kuhn,et al.  Site-specific DNA-antibody conjugates for specific and sensitive immuno-PCR , 2012, Proceedings of the National Academy of Sciences.

[44]  Monika S. Kowalczyk,et al.  Single-cell RNA-seq reveals changes in cell cycle and differentiation programs upon aging of hematopoietic stem cells , 2015, Genome research.

[45]  Shawn M. Gillespie,et al.  Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma , 2014, Science.

[46]  E. Lander Initial impact of the sequencing of the human genome , 2011, Nature.

[47]  S. Manalis,et al.  Weighing of biomolecules, single cells and single nanoparticles in fluid , 2007, Nature.

[48]  J Christopher Love,et al.  Single-cell analysis of the dynamics and functional outcomes of interactions between human natural killer cells and target cells. , 2012, Integrative biology : quantitative biosciences from nano to macro.

[49]  W. Koh,et al.  Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics , 2014, Proceedings of the National Academy of Sciences.

[50]  I. Hellmann,et al.  Comparative Analysis of Single-Cell RNA Sequencing Methods , 2016, bioRxiv.

[51]  William H. Grover,et al.  Using buoyant mass to measure the growth of single cells , 2010, Nature Methods.

[52]  Kun Zhang,et al.  Massively parallel polymerase cloning and genome sequencing of single cells using nanoliter microwells , 2013, Nature Biotechnology.

[53]  Richard Novak,et al.  High-performance single cell genetic analysis using microfluidic emulsion generator arrays. , 2010, Analytical chemistry.

[54]  J. Schug,et al.  Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes , 2016, Molecular metabolism.

[55]  Christopher M. Hindson,et al.  Absolute quantification by droplet digital PCR versus analog real-time PCR , 2013, Nature Methods.

[56]  Carlos A Aguilar,et al.  Micro- and nanoscale devices for the investigation of epigenetics and chromatin dynamics. , 2013, Nature nanotechnology.

[57]  Mario Roederer,et al.  Single-cell technologies for monitoring immune systems , 2014, Nature Immunology.

[58]  J Christopher Love,et al.  Cell-surface sensors for real-time probing of cellular environments. , 2011, Nature nanotechnology.

[59]  A. Regev,et al.  Spatial reconstruction of single-cell gene expression data , 2015 .

[60]  Hans Clevers,et al.  Single-cell messenger RNA sequencing reveals rare intestinal cell types , 2015, Nature.

[61]  B. Bernstein,et al.  Epigenetic Reprogramming in Cancer , 2013, Science.

[62]  Ramesh Ramakrishnan,et al.  Single-Cell Genetic Analysis Using Automated Microfluidics to Resolve Somatic Mosaicism , 2015, PloS one.

[63]  Irving L. Weissman,et al.  Association of reactive oxygen species levels and radioresistance in cancer stem cells , 2009, Nature.

[64]  Rhonda Bacher,et al.  Design and computational analysis of single-cell RNA-sequencing experiments , 2016, Genome Biology.

[65]  Victor Guryev,et al.  Single-cell whole genome sequencing reveals no evidence for common aneuploidy in normal and Alzheimer’s disease neurons , 2016, Genome Biology.

[66]  Rong Fan,et al.  A Clinical Microchip for Evaluation of Single Immune Cells Reveals High Functional Heterogeneity in Phenotypically Similar T Cells Nih Public Access Author Manuscript Design Rationale and Detection Limit of the Scbc Online Methods Microchip Fabrication On-chip Secretion Profiling Supplementary Mater , 2022 .

[67]  Howard Y. Chang,et al.  Lineage-specific and single cell chromatin accessibility charts human hematopoiesis and leukemia evolution , 2016, Nature Genetics.

[68]  D. Pe’er,et al.  Highly multiplexed profiling of single-cell effector functions reveals deep functional heterogeneity in response to pathogenic ligands , 2015, Proceedings of the National Academy of Sciences.

[69]  Jong Wook Hong,et al.  Integrated nanoliter systems , 2003, Nature Biotechnology.

[70]  Stephen R. Quake,et al.  Genome-wide Single-Cell Analysis of Recombination Activity and De Novo Mutation Rates in Human Sperm , 2012, Cell.

[71]  H. S. Rho,et al.  Parallel Single Cancer Cell Whole Genome Amplification Using Button-Valve Assisted Mixing in Nanoliter Chambers , 2014, PloS one.

[72]  J. C. Love,et al.  Single-Cell Detection of Secreted Aβ and sAPPα from Human IPSC-Derived Neurons and Astrocytes , 2016, The Journal of Neuroscience.

[73]  Meng Zhang,et al.  Quantitative assessment of single-cell whole genome amplification methods for detecting copy number variation using hippocampal neurons , 2015, Scientific Reports.

[74]  Stephen R Quake,et al.  Single-cell multimodal profiling reveals cellular epigenetic heterogeneity , 2016, Nature Methods.

[75]  I. Amit,et al.  Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq , 2016, Cell.

[76]  Sridhar Ramaswamy,et al.  RNA sequencing of pancreatic circulating tumour cells implicates WNT signaling in metastasis , 2012, Nature.

[77]  J. Herschkowitz,et al.  Stand-Sit Microchip for High-Throughput, Multiplexed Analysis of Single Cancer Cells , 2016, Scientific Reports.

[78]  Michael W. Sneddon,et al.  Single-cell quantification of IL-2 response by effector and regulatory T cells reveals critical plasticity in immune response , 2010, Molecular systems biology.

[79]  A. Regev,et al.  A Generic and Cell-Type-Specific Wound Response Precedes Regeneration in Planarians. , 2015, Developmental cell.

[80]  Pradeep S Rajendran,et al.  Single-cell dissection of transcriptional heterogeneity in human colon tumors , 2011, Nature Biotechnology.

[81]  Lior Pachter,et al.  Sequence Analysis , 2020, Definitions.

[82]  Thomas M. Norman,et al.  A Multiplexed Single-Cell CRISPR Screening Platform Enables Systematic Dissection of the Unfolded Protein Response , 2016, Cell.

[83]  W. Koh,et al.  Single-cell genome sequencing: current state of the science , 2016, Nature Reviews Genetics.

[84]  T. Mikkelsen,et al.  Genome-wide maps of chromatin state in pluripotent and lineage-committed cells , 2007, Nature.

[85]  U. Landegren,et al.  Protein detection using proximity-dependent DNA ligation assays , 2002, Nature Biotechnology.

[86]  S. P. Fodor,et al.  Combinatorial labeling of single cells for gene expression cytometry , 2015, Science.

[87]  Samuel L. Wolock,et al.  A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure. , 2016, Cell systems.

[88]  J Christopher Love,et al.  Development of a High-Throughput Functional Screen Using Nanowell-Assisted Cell Patterning. , 2015, Small.

[89]  O. Stegle,et al.  Single-Cell Genome-Wide Bisulfite Sequencing for Assessing Epigenetic Heterogeneity , 2014, Nature Methods.

[90]  J. C. Love,et al.  Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput , 2017, Nature Methods.

[91]  J. C. Love,et al.  Functional analysis of single cells identifies a rare subset of circulating tumor cells with malignant traits. , 2014, Integrative biology : quantitative biosciences from nano to macro.

[92]  J. C. Love,et al.  A microengraving method for rapid selection of single cells producing antigen-specific antibodies , 2006, Nature Biotechnology.

[93]  Mustafa Khammash,et al.  Digital Quantification of Proteins and mRNA in Single Mammalian Cells. , 2016, Molecular cell.

[94]  Funda Meric-Bernstam,et al.  Punctuated Copy Number Evolution and Clonal Stasis in Triple-Negative Breast Cancer , 2016, Nature Genetics.

[95]  Richard A. Olshen,et al.  Diversity and clonal selection in the human T-cell repertoire , 2014, Proceedings of the National Academy of Sciences.

[96]  S. Linnarsson,et al.  Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq , 2015, Science.

[97]  Thomas M. Norman,et al.  Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens , 2016, Cell.

[98]  Anneliese O. Speak,et al.  T cell fate and clonality inference from single cell transcriptomes , 2016, Nature Methods.

[99]  Peter A. Sims,et al.  An Automated Microwell Platform for Large-Scale Single Cell RNA-Seq , 2016, Scientific Reports.

[100]  D. Weitz,et al.  Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state , 2015, Nature Biotechnology.

[101]  Navin Varadarajan,et al.  Rapid, efficient functional characterization and recovery of HIV-specific human CD8+ T cells using microengraving , 2012, Proceedings of the National Academy of Sciences.

[102]  A. K. Singh,et al.  Mobile genes in the human microbiome are structured from global to individual scales , 2016, Nature.

[103]  Burak Dura,et al.  Profiling lymphocyte interactions at the single-cell level by microfluidic cell pairing , 2015, Nature Communications.

[104]  David Bryder,et al.  Transcription factor profiling in individual hematopoietic progenitors by digital RT-PCR , 2006, Proceedings of the National Academy of Sciences.

[105]  Douglas A. Lauffenburger,et al.  Polyfunctional responses by human T cells result from sequential release of cytokines , 2011, Proceedings of the National Academy of Sciences.

[106]  L. Christophorou Science , 2018, Emerging Dynamics: Science, Energy, Society and Values.

[107]  D. Steege Emerging features of mRNA decay in bacteria. , 2000, RNA.

[108]  Sijia Lu,et al.  Microfluidic whole genome amplification device for single cell sequencing. , 2014, Analytical chemistry.

[109]  Voichita D. Marinescu,et al.  Simultaneous Multiplexed Measurement of RNA and Proteins in Single Cells , 2015, Cell reports.

[110]  Evan Z. Macosko,et al.  Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets , 2015, Cell.

[111]  Ulf Landegren,et al.  Opportunities for sensitive plasma proteome analysis. , 2012, Analytical chemistry.

[112]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[113]  Allon M. Klein,et al.  Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells , 2015, Cell.

[114]  Maxwell R. Mumbach,et al.  Dynamic profiling of the protein life cycle in response to pathogens , 2015, Science.

[115]  Victor Guryev,et al.  Erratum to: Single-cell whole genome sequencing reveals no evidence for common aneuploidy in normal and Alzheimer’s disease neurons , 2016, Genome Biology.

[116]  Karen Sachs,et al.  Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators , 2012, Nature Biotechnology.

[117]  Charles H. Yoon,et al.  Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq , 2016, Science.

[118]  Scott A. Rifkin,et al.  Imaging individual mRNA molecules using multiple singly labeled probes , 2008, Nature Methods.

[119]  Sijia Lu,et al.  Uniform and accurate single-cell sequencing based on emulsion whole-genome amplification , 2015, Proceedings of the National Academy of Sciences.

[120]  Matt Thomson,et al.  Low Dimensionality in Gene Expression Data Enables the Accurate Extraction of Transcriptional Programs from Shallow Sequencing. , 2016, Cell systems.

[121]  Rona S. Gertner,et al.  Single-Cell Genomics Unveils Critical Regulators of Th17 Cell Pathogenicity , 2015, Cell.

[122]  Tanja Woyke,et al.  Reconstructing each cell's genome within complex microbial communities—dream or reality? , 2014, Front. Microbiol..

[123]  N. Friedman,et al.  Stochastic protein expression in individual cells at the single molecule level , 2006, Nature.

[124]  Nathan C. Sheffield,et al.  Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics , 2015, Cell reports.

[125]  Fabian J Theis,et al.  Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells , 2015, Nature Biotechnology.

[126]  J. V. Moran,et al.  Initial sequencing and analysis of the human genome. , 2001, Nature.

[127]  Paul J. Choi,et al.  Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells , 2010, Science.

[128]  Åsa K. Björklund,et al.  The heterogeneity of human CD127+ innate lymphoid cells revealed by single-cell RNA sequencing , 2016, Nature Immunology.

[129]  Sean C. Bendall,et al.  Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum , 2011, Science.

[130]  Aleksandra A. Kolodziejczyk,et al.  Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression , 2015, Nature Communications.

[131]  Alex K. Shalek,et al.  Heterogeneity in immune responses: from populations to single cells. , 2014, Trends in immunology.

[132]  Olivier Elemento,et al.  Single-cell TCRseq: paired recovery of entire T-cell alpha and beta chain transcripts in T-cell receptors from single-cell RNAseq , 2016, Genome Medicine.

[133]  P. Wen,et al.  Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate , 2016, Nature Biotechnology.

[134]  Niels W. Hanson,et al.  A programmable droplet-based microfluidic device applied to multiparameter analysis of single microbes and microbial communities , 2012, Proceedings of the National Academy of Sciences.

[135]  Amy E. Herr,et al.  Single-cell western blotting , 2014, Nature Methods.

[136]  Chaoyong James Yang,et al.  High-throughput single copy DNA amplification and cell analysis in engineered nanoliter droplets. , 2008, Analytical chemistry.

[137]  Sean C. Bendall,et al.  Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development , 2014, Cell.

[138]  A. Tanay,et al.  Single cell Hi-C reveals cell-to-cell variability in chromosome structure , 2013, Nature.

[139]  A. Abate,et al.  Ultrahigh-throughput screening in drop-based microfluidics for directed evolution , 2010, Proceedings of the National Academy of Sciences.

[140]  Qingge Li,et al.  Multicolor Combinatorial Probe Coding for Real-Time PCR , 2011, PloS one.

[141]  J. McLean,et al.  Single cell genomics of bacterial pathogens: outlook for infectious disease research , 2014, Genome Medicine.

[142]  Tejal A Desai,et al.  Programmed synthesis of three-dimensional tissues , 2015, Nature Methods.

[143]  Aviv Regev,et al.  Whole exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer , 2014, Nature Biotechnology.

[144]  M. Gerstein,et al.  Comparing protein abundance and mRNA expression levels on a genomic scale , 2003, Genome Biology.

[145]  B. Williams,et al.  From single-cell to cell-pool transcriptomes: Stochasticity in gene expression and RNA splicing , 2014, Genome research.

[146]  J. Radich,et al.  Single-cell genotyping demonstrates complex clonal diversity in acute myeloid leukemia , 2015, Science Translational Medicine.

[147]  Samuel Aparicio,et al.  High-throughput microfluidic single-cell RT-qPCR , 2011, Proceedings of the National Academy of Sciences.

[148]  Bing Sun,et al.  Mechanistic evaluation of the pros and cons of digital RT-LAMP for HIV-1 viral load quantification on a microfluidic device and improved efficiency via a two-step digital protocol. , 2013, Analytical chemistry.

[149]  A. Regev,et al.  Revealing the vectors of cellular identity with single-cell genomics , 2016, Nature Biotechnology.

[150]  Thomas P. Burg,et al.  Suspended microchannel resonators for biomolecular detection , 2003 .

[151]  Kim Sneppen,et al.  DNA methylation in human epigenomes depends on local topology of CpG sites , 2016, Nucleic acids research.

[152]  Rickard Sandberg,et al.  Single-cell sequencing of the small-RNA transcriptome , 2016, Nature Biotechnology.

[153]  F. Tang,et al.  Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing , 2013, Genome research.

[154]  Marius Wernig,et al.  Comprehensive qPCR profiling of gene expression in single neuronal cells , 2011, Nature Protocols.

[155]  Paul C. Blainey,et al.  A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages , 2016, Nature Communications.

[156]  Rona S. Gertner,et al.  Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells , 2013, Nature.

[157]  Chaoyong James Yang,et al.  Massively parallel single-molecule and single-cell emulsion reverse transcription polymerase chain reaction using agarose droplet microfluidics. , 2012, Analytical chemistry.