Single-cell RNA sequencing to explore immune c.pdf

From bacteria to humans,the diverse and adaptable nature of foreign threats has driven the evolution of a powerful and flexible defence response.To maintain its effectiveness,this socalled immune system has produced highly specialized(pathogenspecific)cell types that work together to prevent,retain a memory of and eliminate disease14.Singlecell resolution is therefore essential to understanding how the immune system gives rise to such a breadth of potential responses against many different pathogens5.Recently,new technologies have been developed that enable the profiling of single cells using nextgeneration sequencing,which offers an unbiased approach to studying immune cell diversity.In this Review,we present an overview of existing singlecell technologies and discuss their strengths and limitations(BOX1).We also explore ways in which these approaches can deepen our understanding of immunological responses and disease,and we examine cuttingedge trends and potential future innovations in thefield.Targeted single-cell profiling technologiesA large number of techniques have leveraged advances in microscopy,cytometry,molecular biology and,most recently,nextgeneration sequencing to profile single cells.Many of these approaches have been developed and optimized to be used in studies that aim to deconvolve immune cell heterogeneity,but they can differ by orders of magnitude in terms of the number of cells that can be analysed per experiment(the breadth of cellular profiling)and the number of genes per cell that can be detected(the depth of cellular profiling).Targeted technologies can assess a preselected set of molecular dimensions(preselected genes for mRNA expression studies and proteinlevel detection)across hundreds to millions of cells using known molecular baits such as fluorescently labelled oligonucleotide probes,fluorescent or metalconjugated antibodies,or PCR primers to profile genes or proteins with single cell resolution.For example,recent advances in flow cytometry6 have allowed for the routine and simultaneous profiling of up to 17 proteins per cell using fluorescent antibodies.By using metalconjugated antibodies to overcome the spectral limits of fluorescent proteins,mass cytometry7 can further extend profiling to the simultaneous detection of about 40 proteins per cell,with an order of magnitude increase in the number of cells that can be studied at one time8,9.These technologies have led to the discovery and characterization of major and minor cell types in the mammalian immune system10.However,their application is limited to a small number of parameters that are selected based on prior knowledge or guesswork(such as genes or surface proteins),and the profiling of these parameters depends on the availability of gene sequences for primer design or proteinspecific antibodies.As an alternative to cytometry,genespecific primers can be used to carry out quantitative PCR(qPCR)on single cells11,which allows for the fluorescent quantification of singlecell mRNA levels12,13.Singlecell qPCR(scqPCR)does not require sample library preparation or deep sequencing,and it therefore offers a rapid and highly quantitative assay for singlecell gene expression,particularly in the absence of specific antibodies.Commercial microfluidic approaches have been used to multiplex up to 1Center for Genomics and Systems Biology,New York University,New York,NY 100036688,USA.2New York Genome Center,New York,New York 10013,USA.Correspondence to R.S.rsatijanygenome.orgdoi:10.1038/nri.2017.76Published online 7 Aug 2017Flow cytometryLaser-based technology that allows for simultaneous quantification of the abundance of up to 17 cell surface proteins using fluorescently labelled antibodies.Mass cytometry(commercial name CyTOF).Mass spectrometry technique used as an alternative to flow cytometry that allows for the quantification of cellular protein levels by using isotopes that overcome problems associated with the spectral overlap of fluorophores.Single-cell RNA sequencing to explore immune cell heterogeneityEfthymia Papalexi1,2 and Rahul Satija1,2Abstract|Advances in single-cell RNA sequencing(scRNA-seq)have allowed for comprehensive analysis of the immune system.In this Review,we briefly describe the available scRNA-seq technologies together with their corresponding strengths and weaknesses.We discuss in depth how scRNA-seq can be used to deconvolve immune system heterogeneity by identifying novel distinct immune cell subsets in health and disease,characterizing stochastic heterogeneity within a cell population and building developmental trajectories for immune cells.Finally,we discuss future directions of the field and present integrated approaches to complement molecular information from a single cell with studies of the environment,epigenetic state and cell lineage.NATURE REVIEWS|IMMUNOLOGY ADVANCE ONLINE PUBLICATION|1REVIEWS 2017 Macmillan Publishers Limited,part of Springer Nature.All rights reserved.Quantitative PCR(qPCR).Polymerase chain reaction used to quantify gene expression levels using fluorescently labelled nucleotides and by tracking fluorescence levels during amplification cycles.Microfluidic approachesSingle-cell RNA-sequencing techniques that use microfluidic devices for single-cell isolation.MicroarraysTechnique used to detect gene expression levels of many genes simultaneously.Microarrays use gene-specific probes that can be hybridized to complementary fluorescently labelled cDNA molecules.The fluorescence intensity is used to quantify gene expression.96 primer pairs together in a single assay,and indeed,these approaches were shown to be extremely promising in deconvolving the molecular heterogeneity of the developing immune system14,15.However,similarly to cytometrybased approaches,qPCR assays also require measurement of a preselected pool of genes,which introduces bias and limits the potential for discovery of new genes and proteins of interest.As a result,there has been substantial interest around new methods that are capable of unbiased molecular profiling of single cells by leveraging new techniques based on nextgeneration sequencing.The development of singlecell RNA sequencing(scRNAseq)approaches has allowed for unbiased singlecell transcriptome profiling to enable the discovery of new cellular states,the profiling of genetic heterogeneity ranging from single nucleotide polymorphisms to diverse immunoglobulin sequences,and the study of the transcriptomes of nonmodel organisms.Towards unbiased single-cell profilingThe first protocols for bulk RNAseq offered an unbiased alternative to microarrays1618 but required millions of cells(1 g of total mRNA transcripts)19.Whereas some of the first immunological studies used abundant leukocyte cell populations20,21,the need to study rare cell populations and to discover new cellular states necessitated the development of RNAseq protocols with a lower cell input22,23.Particularly in the field of immunology,these new RNAseq proto cols,in combination with microarray data,allowed for the profiling of various rare cell populations with the use of only 1 ng of RNA isolated from 1001,000 immune cells.This led to the generation of large collaborative databases,including the Illumina Body Map Expression Atlas24;the Differentiation Map(DMAP)project25,which profiled 39 distinct human immune cell types;and the Immunological Genome Project,which profiled murine immune cell subsets.These databases are powerful community resources to identify modules of coregulated genes across many cell types and conditions for cellular subsets with welldefined markers.The development of lowinput RNAseq protocols paved the way for further optimization down to the single cell level,culminating in an explosion of new scRNAseq platforms.With the large number of methods available,each with distinct strengths and weaknesses,it is often unclear which option is most suitable for addressing a specific research question.Here,we review many of the available options and discuss how they differ in terms of workflow(FIG.1),sensitivity and data quality,in addition to outlining their ideally suited biological applications(BOX1).FACSCyTOFqPCRPlate-based protocols(STRT-seq,SMART-seq,SMART-seq2)Fluidigm C1Pooled approaches(CEL-seq,MARS-seq,SCRB-seq,CEL-seq2)Massively parallel approaches(Drop-seq,InDrop)Cell capture methodLaserMass cytometryMicropipettesFACSMicrofluidicsFACSMicrodropletsNumber of cells per experimentMillionsMillions3001,0005050048965002,0005,00010,000Cost$0.05 per cell$35 per cell$1 per cell$36 per well$35 per cell$36 per well$0.05 per cellSensitivityUp to 17 markersUp to 40 markers1030 genes per cell7,00010,000 genes per cell for cell lines;2,0006,000 genes per cell for primary cells6,0009,00 genes per cell for cell lines;1,0005,000 genes per cell for primary cells7,00010,000 genes per cell for cell lines;2,0006,000 genes per cell for primary cells5,000 genes per cell for cell lines;1,0003,000 genes per cell for primary cellsCEL-seq,cell expression by linear amplification and sequencing;CyTOF,cytometry by time of flight(mass cytometry);FACS,fluorescence-activated cell sorting;InDrop,indexing droplets sequencing;MARS-seq,massively parallel single-cell RNA sequencing;qPCR,quantitative PCR;SCRB-seq,single-cell RNA barcoding and sequencing;STRT-seq,single-cell tagged reverse transcription sequencing.Box 1|Summary of current single-cell profiling technologiesThe available technologies for single-cell RNA sequencing(scRNA-seq)have unique strengths and weaknesses(see table).Before choosing which technology to use for a particular study,it is important to consider the scale of the experiment,the cost and sensitivity of each method and the biological question to be answered.Advances in droplet microfluidics3335 now enable routine profiling of thousands of cells in a single experiment.These methods are ideally suited for discovering rare cell types or deconvolving highly heterogeneous populations such as whole tissue or organ samples.However,these technologies have reduced sensitivity per cell,and they may not be able to identify subtle transcriptional differences between cells.Alternative technologies,such as plate-based protocols2932 or commercial microfluidics solutions(Fluidigm C1),are capable of deep profiling of single cells but at a substantially increased cost.These technologies are better suited to study stochastic variability between single cells or to deconvolve subtle transcriptomic differences in homogeneous populations.In addition,plate-based methods that use index-sorting for cell isolation enable the recording of cellular immunophenotypes alongside the transcriptome,and the Fluidigm C1 allows for cells to be individually imaged before sequencing.As these technologies mature,they suggest a powerful complementary approach,whereby complex tissues are first atlased using high-breadth droplet-based technologies to identify new populations of interest and associated markers.Subsequently,these markers can be used for enrichment and deep sequencing using high-depth,plate-based approaches.REVIEWS2|ADVANCE ONLINE PUBLICATION 2017 Macmillan Publishers Limited,part of Springer Nature.All rights reserved.Fluidigm C1FACS sorterPhysical separation of cells on microfluidic chipPhysical separation of cells into 96-well platesCells trapped inside hydrogel dropletsSMART-seqSMART-seq2STRT-seqCEL-seqMARS-seqSCRB-seqCEL-seq2Drop-seqInDropIndividual cell amplificationFull-length sequencingDetect gene expression,splicing variants and BCR and TCR repertoire diversity53533 sequencingDetect gene expressionPooled PCR amplification5353ApplicationSequencingmethodAmplificationmethodCell isolationPopulation APopulation BA123456789101112BCDEFGHA123456789101112BCDEFGHLaserReverse transcriptionConversion of a mRNA molecule to complementary DNA(cDNA)using reverse transcriptase enzymes isolated from RNA viruses.Plate-based protocols.Most 96well protocols,such as singlecell tagged reverse transcription(STRT)sequencing(STRTseq),SMARTseq and SMARTseq2 (REFS23,2628),use micropipettes or fluorescence activated cell sorting(FACS)to place individual cells into wells containing lysis buffer.These platforms offer a fast and efficient way to analyse 50 to 500 single cells in one experiment.Single cells can be stored in plates longterm before analysis,allowing for a flexible experimental setup with optional pause points when time is limited.However,reverse transcription is carried out on individual wells,which requires additional pipetting steps that can slow down the process and introduce technical noise in the samples.In addition,the early versions of these platforms had low sensitivity and were quite costly.Subsequent studies optimized this platform to increase accuracy,sensitivity and throughput,as well as to decrease processing time.Moreover,these protocols are amenable to automation with liquidhandling robotics.These methods are generalizable,as they offer the opportunity to profile any cell,independent of size and type,that can pass through a micropipette or FACS sorter machine.Overall,they have high sensitivity and can measure 5,00010,000 genes per singlecell.Fluidigm C1.In 2012,Fluidigm introduced the C1,an automated microfluidic platform for scRNAseq that can individually capture up to 96 cells at a time on a single microfluidic chip.Downstream molecular steps are automated and parallelized in nanolitresized volumes.In addition,this platform offers the option to evaluate the captured cells under the microscope before the reverse transcription and amplification steps of the protocol.At least 10,000 cells are required as input,which suggests that this platform is not ideal for rare cell populations.To avoid introducing selection bias,it is required that cells be of similar size and shape.The sensitivity of the Fluidigm C1 is similar to that of platebased protocols,Figure 1|Overview of scRNA-seq technologies.Single-cell RNA sequencing(scRNA-seq)technologies use many different methods for cell isolation and transcript amplification.Whereas some technologies capture cells using microfluidic devices that trap cells inside hydrogel droplets,other technologies rely on methods(such as fluorescence-activated cell sorting(FACS)into 96-well plates and the microfluidic chips used by Fluidigm C1)that physically separate one cell from another in wells.Once cells are lysed,reverse transcription and PCR amplification are carried out.Droplet-based approaches,and some plate-based approaches,allow for pooled PCR amplification using cellular barcoding techniques,which decreases the cost as only one PCR reaction is required per experiment or plate.In other plate-based approaches and for Fluidigm C1,the number of PCR amplification reactions is equal to the number of cells that are being profiled,which makes these approaches expensive.PCR products are further processed to prepare samples for sequencing.Some approaches that use sequencing of the 3 end of eac