T cell fate and clonality inference from single-cell transcriptomes

Mapping human development at single-cell resolution

Human development is regulated by spatiotemporally restricted molecular programmes and is pertinent to many areas of basic biology and human medicine, such as stem cell biology, reproductive medicine and childhood cancer. Mapping human development has presented significant technological, logistical and ethical challenges. The availability of established human developmental biorepositories and the advent of cutting-edge single-cell technologies provide new opportunities to study human development. Here, we present a working framework for the establishment of a human developmental cell atlas exploiting single-cell genomics and spatial analysis. We discuss how the development atlas will benefit the scientific and clinical communities to advance our understanding of basic biology, health and disease.

An Efficient Single-Cell RNA-Seq Approach to Identify Neoantigen-Specific T Cell Receptors

The adoptive transfer of neoantigen-reactive tumor-infiltrating lymphocytes (TILs) can result in tumor regression in patients with metastatic cancer. To improve the efficacy of adoptive T cell therapy targeting these tumor-specific mutations, we have proposed a new therapeutic strategy, which involves the genetic modification of autologous T cells with neoantigen-specific T cell receptors (TCRs) and the transfer of these modified T cells back to cancer patients. However, the current techniques to isolate neoantigen-specific TCRs are labor intensive, time consuming, and technically challenging, not suitable for clinical applications. To facilitate this process, a new approach was developed, which included the co-culture of TILs with tandem minigene (TMG)-transfected or peptide-pulsed autologous antigen-presenting cells (APCs) and the single-cell RNA sequencing (RNA-seq) analysis of T cells to identify paired TCR sequences associated with cells expressing high levels of interferon-γ (IFN-γ) and interleukin-2 (IL-2). Following this new approach, multiple TCRs were identified, synthesized, cloned into a retroviral vector, and then transduced into donor T cells. These transduced T cells were shown to specifically recognize the neoantigens presented by autologous APCs. In conclusion, this approach provides an efficient procedure to isolate neoantigen-specific TCRs for clinical applications, as well as for basic and translational research.

Precursors of human CD4+ cytotoxic T lymphocytes identified by single-cell transcriptome analysis

CD4+ cytotoxic T lymphocytes (CD4-CTLs) have been reported to play a protective role in several viral infections. However, little is known in humans about the biology of CD4-CTL generation, their functional properties, and heterogeneity, especially in relation to other well-described CD4+ memory T cell subsets. We performed single-cell RNA sequencing in more than 9000 cells to unravel CD4-CTL heterogeneity, transcriptional profile, and clonality in humans. Single-cell differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the TEMRA (effector memory T cells expressing CD45RA) subset, which is highly enriched for CD4-CTLs, compared with CD4+ T cells in the central memory (TCM) and effector memory (TEM) subsets. Simultaneous T cell antigen receptor (TCR) analysis in single cells and bulk subsets revealed that CD4-TEMRA cells show marked clonal expansion compared with TCM and TEM cells and that most of CD4-TEMRA were dengue virus (DENV)-specific in donors with previous DENV infection. The profile of CD4-TEMRA was highly heterogeneous across donors, with four distinct clusters identified by the single-cell analysis. We identified distinct clusters of CD4-CTL effector and precursor cells in the TEMRA subset; the precursor cells shared TCR clonotypes with CD4-CTL effectors and were distinguished by high expression of the interleukin-7 receptor. Our identification of a CD4-CTL precursor population may allow further investigation of how CD4-CTLs arise in humans and, thus, could provide insights into the mechanisms that may be used to generate durable and effective CD4-CTL immunity.

HLA variation and disease

Fifty years since the first description of an association between HLA and human disease, HLA molecules have proven to be central to physiology, protective immunity and deleterious, disease-causing autoimmune reactivity. Technological advances have enabled pivotal progress in the determination of the molecular mechanisms that underpin the association between HLA genetics and functional outcome. Here, we review our current understanding of HLA molecules as the fundamental platform for immune surveillance and responsiveness in health and disease. We evaluate the scope for personalized antigen-specific disease prevention, whereby harnessing HLA-ligand interactions for clinical benefit is becoming a realistic prospect.

Single-Cell mRNA-Seq Using the Fluidigm C1 System and Integrated Fluidics Circuits

Single-cell mRNA-seq is a valuable tool to dissect expression profiles and to understand the regulatory network of genes. Microfluidics is well suited for single-cell analysis owing both to the small volume of the reaction chambers and easiness of automation. Here we describe the workflow of single-cell mRNA-seq using C1 IFC, which can isolate and process up to 96 cells. Both on-chip procedure (lysis, reverse transcription, and preamplification PCR) and off-chip sequencing library preparation protocols are described. The workflow generates full-length mRNA information, which is more valuable compared to 3' end counting method for many applications.

Using Fluidigm C1 to Generate Single-Cell Full-Length cDNA Libraries for mRNA Sequencing

Single-cell RNA sequencing has evolved into a benchmark application to study cellular heterogeneity, advancing our understanding of cellular differentiation, disease progression, and gene regulation in a multitude of research areas. The generation of high-quality cDNA, an important step in the experimental workflow when generating sequence-ready libraries, is critical to maximizing data quality. Here we describe a strategy that uses a microfluidic device (i.e., the C1™ IFC) to synthesize full-length cDNA from single cells in a fully automated, nanoliter-scale format. The device also facilitates confirmation of the presence of a single, viable cell and recording of phenotypic information, quality control measures that are crucial for streamlining downstream data processing and enhancing overall data validity.

The Human Cell Atlas

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells

Single-cell RNA sequencing (scRNA-Seq) is rapidly becoming a powerful tool for high-throughput transcriptomic analysis of cell states and dynamics at the single cell level. Both the number and quality of scRNA-Seq datasets have dramatically increased recently. A database that can comprehensively collect, curate, and compare expression features of scRNA-Seq data in humans has not yet been built. Here, we present scRNASeqDB, a database that includes almost all the currently available human single cell transcriptome datasets (n = 38) covering 200 human cell lines or cell types and 13,440 samples. Our online web interface allows users to rank the expression profiles of the genes of interest across different cell types. It also provides tools to query and visualize data, including Gene Ontology and pathway annotations for differentially expressed genes between cell types or groups. The scRNASeqDB is a useful resource for single cell transcriptional studies. This database is publicly available at https://bioinfo.uth.edu/scrnaseqdb/.

The Human Cell Atlas

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Targeted reconstruction of T cell receptor sequence from single cell RNA-seq links CDR3 length to T cell differentiation state

The T cell compartment must contain diversity in both T cell receptor (TCR) repertoire and cell state to provide effective immunity against pathogens. However, it remains unclear how differences in the TCR contribute to heterogeneity in T cell state. Single cell RNA-sequencing (scRNA-seq) can allow simultaneous measurement of TCR sequence and global transcriptional profile from single cells. However, current methods for TCR inference from scRNA-seq are limited in their sensitivity and require long sequencing reads, thus increasing the cost and decreasing the number of cells that can be feasibly analyzed. Here we present TRAPeS, a publicly available tool that can efficiently extract TCR sequence information from short-read scRNA-seq libraries. We apply it to investigate heterogeneity in the CD8⁺ T cell response in humans and mice, and show that it is accurate and more sensitive than existing approaches. Coupling TRAPeS with transcriptome analysis of CD8⁺ T cells specific for a single epitope from Yellow Fever Virus (YFV), we show that the recently described ‘naive-like’ memory population have significantly longer CDR3 regions and greater divergence from germline sequence than do effector-memory phenotype cells. This suggests that TCR usage is associated with the differentiation state of the CD8⁺ T cell response to YFV.

Quantitative Characterization of the T Cell Receptor Repertoire of Naïve and Memory Subsets Using an Integrated Experimental and Computational Pipeline Which Is Robust, Economical, and Versatile

The T cell receptor (TCR) repertoire can provide a personalized biomarker for infectious and non-infectious diseases. We describe a protocol for amplifying, sequencing, and analyzing TCRs which is robust, sensitive, and versatile. The key experimental step is ligation of a single-stranded oligonucleotide to the 3' end of the TCR cDNA. This allows amplification of all possible rearrangements using a single set of primers per locus. It also introduces a unique molecular identifier to label each starting cDNA molecule. This molecular identifier is used to correct for sequence errors and for effects of differential PCR amplification efficiency, thus producing more accurate measures of the true TCR frequency within the sample. This integrated experimental and computational pipeline is applied to the analysis of human memory and naive subpopulations, and results in consistent measures of diversity and inequality. After error correction, the distribution of TCR sequence abundance in all subpopulations followed a power law over a wide range of values. The power law exponent differed between naïve and memory populations, but was consistent between individuals. The integrated experimental and analysis pipeline we describe is appropriate to studies of T cell responses in a broad range of physiological and pathological contexts.

T Cell Receptor Profiling in Type 1 Diabetes

PURPOSE OF REVIEW

The genetic susceptibility and dominant protection for type 1 diabetes (T1D) associated with human leukocyte antigen (HLA) haplotypes, along with minor risk variants, have long been thought to shape the T cell receptor (TCR) repertoire and eventual phenotype of autoreactive T cells that mediate β-cell destruction. While autoantibodies provide robust markers of disease progression, early studies tracking autoreactive T cells largely failed to achieve clinical utility.

RECENT FINDINGS

Advances in acquisition of pancreata and islets from T1D organ donors have facilitated studies of T cells isolated from the target tissues. Immunosequencing of TCR α/β-chain complementarity determining regions, along with transcriptional profiling, offers the potential to transform biomarker discovery. Herein, we review recent studies characterizing the autoreactive TCR signature in T1D, emerging technologies, and the challenges and opportunities associated with tracking TCR molecular profiles during the natural history of T1D.

Impact of sequencing depth and read length on single cell RNA sequencing data of T cells

Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% − 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.

Single-cell transcriptomics to explore the immune system in health and disease

The immune system varies in cell types, states, and locations. The complex networks, interactions, and responses of immune cells produce diverse cellular ecosystems composed of multiple cell types, accompanied by genetic diversity in antigen receptors. Within this ecosystem, innate and adaptive immune cells maintain and protect tissue function, integrity, and homeostasis upon changes in functional demands and diverse insults. Characterizing this inherent complexity requires studies at single-cell resolution. Recent advances such as massively parallel single-cell RNA sequencing and sophisticated computational methods are catalyzing a revolution in our understanding of immunology. Here we provide an overview of the state of single-cell genomics methods and an outlook on the use of single-cell techniques to decipher the adaptive and innate components of immunity.

High-dimension single-cell analysis applied to cancer

High-dimension single-cell technology is transforming our ability to study and understand cancer. Numerous studies and reviews have reported advances in technology development. The biological insights gleaned from single-cell technology about cancer biology are less reviewed. Here we focus on research studies that illustrate novel aspects of cancer biology that bulk analysis could not achieve, and discuss the fresh insights gained from the application of single-cell technology across basic and clinical cancer studies.

Systems immunology: just getting started

Systems-biology approaches in immunology take various forms, but here we review strategies for measuring a broad swath of immunological functions as a means of discovering previously unknown relationships and phenomena and as a powerful way of understanding the immune system as a whole. This approach has rejuvenated the field of vaccine development and has fostered hope that new ways will be found to combat infectious diseases that have proven refractory to classical approaches. Systems immunology also presents an important new strategy for understanding human immunity directly, taking advantage of the many ways the immune system of humans can be manipulated.

A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications

RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. RNA-seq has fueled much discovery and innovation in medicine over recent years. For practical reasons, the technique is usually conducted on samples comprising thousands to millions of cells. However, this has hindered direct assessment of the fundamental unit of biology-the cell. Since the first single-cell RNA-sequencing (scRNA-seq) study was published in 2009, many more have been conducted, mostly by specialist laboratories with unique skills in wet-lab single-cell genomics, bioinformatics, and computation. However, with the increasing commercial availability of scRNA-seq platforms, and the rapid ongoing maturation of bioinformatics approaches, a point has been reached where any biomedical researcher or clinician can use scRNA-seq to make exciting discoveries. In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation.

TIL 2.0: More effective and predictive T-cell products by enrichment for defined antigen specificities

Adoptive transfer of in vitro-expanded T cells derived from tumor-infiltrating lymphocytes (TILs) in melanoma patients started the era of tumor immunotherapy three decades ago. The approach has demonstrated remarkable clinical responses in several studies since. Reinfusion of TIL-derived T cells represents a highly personalized form of immunotherapy, taking into account the enormous interindividual tumor heterogeneity. However, despite its successes, TIL therapy does not lead to objective clinical responses in all cases. It is thus crucial to find out which tumor antigens are particularly valuable targets and to develop strategies to enhance the reactivity of T-cell products toward them. In this issue of the European Journal of Immunology, Kelderman et al. [Eur. J. Immunol. 2016. 46: 1351-1360] present a platform for the generation of antigen-specific TIL therapy. Combining recently developed technologies for clinical identification and enrichment of antigen-specific CD8(+) T cells, such as MHC Streptamers and UV-mediated peptide exchange, the authors could enrich T-cell populations with defined antigen specificities from melanoma-derived TILs. This T-cell product showed higher reactivity against autologous tumor cell lines than bulk TIL-derived T cells. The novel platform might enable the generation of more effective and predictable TIL-derived T-cell products for future clinical applications.

Microfluidics Cell Loading-Dock System: Ordered Cellular Array for Dynamic Lymphocyte-Communication Study

It remains a great challenge to establish a high-throughput platform that can explore the interactions among multiple lymphocytes (>2 cells) and retrieve the interested cells for downstream analysis. This study demonstrates a microfluidics cell loading-dock system (Cell-Dock) to enclose multiple cells in 1D, 2D, and 3D chambers with high throughput and efficiency and single-cell accuracy. The loading efficiencies of 95%, 85%, and 74% for one-, three-, and five-cell systems are achieved, respectively. The Cell-Dock system provides precise and dynamic cell packing models to facilitate lymphocyte-interaction studies. The results demonstrate that individual natural killer (NK) cells may function independently rather than cooperate to lyse target cells in the defined microenvironment. Furthermore, the strong/weak NK cells are retrieved based on their on-chip cytotoxicity and mRNA sequencing is conducted to find the possible mechanisms for "serial killing," an important but unsolved issue. This study finds that the stronger NK cells overexpress multiple genes involved in cytotoxicity and adhesion molecules (including the well-known ICAM1 and seldom reported B4GALT1) might play important roles in the regulation of NK cytolysis.

Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing

Systematic interrogation of tumor-infiltrating lymphocytes is key to the development of immunotherapies and the prediction of their clinical responses in cancers. Here, we perform deep single-cell RNA sequencing on 5,063 single T cells isolated from peripheral blood, tumor, and adjacent normal tissues from six hepatocellular carcinoma patients. The transcriptional profiles of these individual cells, coupled with assembled T cell receptor (TCR) sequences, enable us to identify 11 T cell subsets based on their molecular and functional properties and delineate their developmental trajectory. Specific subsets such as exhausted CD8⁺ T cells and Tregs are preferentially enriched and potentially clonally expanded in hepatocellular carcinoma (HCC), and we identified signature genes for each subset. One of the genes, layilin, is upregulated on activated CD8⁺ T cells and Tregs and represses the CD8⁺ T cell functions in vitro. This compendium of transcriptome data provides valuable insights and a rich resource for understanding the immune landscape in cancers.

Overview of methodologies for T-cell receptor repertoire analysis

Background

The T-cell receptor (TCR), located on the surface of T cells, is responsible for the recognition of the antigen-major histocompatibility complex, leading to the initiation of an inflammatory response. Analysing the TCR repertoire may help to gain a better understanding of the immune system features and of the aetiology and progression of diseases, in particular those with unknown antigenic triggers. The extreme diversity of the TCR repertoire represents a major analytical challenge; this has led to the development of specialized methods which aim to characterize the TCR repertoire in-depth. Currently, next generation sequencing based technologies are most widely employed for the high-throughput analysis of the immune cell repertoire.

Results

Here, we report on the latest methodological advancements in the field by describing and comparing the available tools; from the choice of the starting material and library preparation method, to the sequencing technologies and data analysis.

Finally, we provide a practical example and our own experience by reporting some exemplary results from a small internal benchmark study, where current approaches from the literature and the market are employed and compared.

Conclusions

Several valid methods for clonotype identification and TCR repertoire analysis exist, however, a gold standard method for the field has not yet been identified. Depending on the purpose of the scientific study, some approaches may be more suitable than others. Finally, due to possible method specific biases, scientists must be careful when comparing results obtained using different methods.

Electronic supplementary material

The online version of this article (doi:10.1186/s12896-017-0379-9) contains supplementary material, which is available to authorized users.

Immune monitoring as prerequisite for transplantation tolerance trials

Ever since its first application in clinical medicine, scientists have been urged to induce tolerance towards foreign allogeneic transplants and thus avoid rejection by the recipient's immune system. This would circumvent chronic use of immunosuppressive drugs (IS) and thus avoid development of IS-induced side effects, which are contributing to the still unsatisfactory long-term graft and patient survival after solid organ transplantation. Although manifold strategies of tolerance induction have been described in preclinical models, only three therapeutic approaches have been utilized successfully in a still small number of patients. These approaches are based on (i) IS withdrawal in spontaneous operational tolerant (SOT) patients, (ii) induction of a mixed chimerism and (iii) adoptive transfer of regulatory cells. Results of clinical trials utilizing these approaches show that tolerance induction does not work in all patients. Thus, there is a need for reliable biomarkers, which can be used for patient selection and post-therapeutic immune monitoring of safety, success and failure. In this review, we summarize recent achievements in the identification and validation of such immunological assays and biomarkers, focusing mainly on kidney and liver transplantation. From the published findings so far, it has become clear that indicative biomarkers may vary between different therapeutic approaches applied and organs transplanted. Also, patient numbers studied so far are very small. This is the main reason why nearly all described parameters lack validation and reproducibility testing in large clinical trials, and are therefore not yet suitable for clinical practice.

Revealing the vectors of cellular identity with single-cell genomics

Single-cell genomics has now made it possible to create a comprehensive atlas of human cells. At the same time, it has reopened definitions of a cell's identity and of the ways in which identity is regulated by the cell's molecular circuitry. Emerging computational analysis methods, especially in single-cell RNA sequencing (scRNA-seq), have already begun to reveal, in a data-driven way, the diverse simultaneous facets of a cell's identity, from discrete cell types to continuous dynamic transitions and spatial locations. These developments will eventually allow a cell to be represented as a superposition of 'basis vectors', each determining a different (but possibly dependent) aspect of cellular organization and function. However, computational methods must also overcome considerable challenges-from handling technical noise and data scale to forming new abstractions of biology. As the scale of single-cell experiments continues to increase, new computational approaches will be essential for constructing and characterizing a reference map of cell identities.

Deep Sequencing in Infectious Diseases: Immune and Pathogen Repertoires for the Improvement of Patient Outcomes

The inaugural workshop “Deep Sequencing in Infectious Diseases: Immune and Pathogen Repertoires for the Improvement of Patient Outcomes” was held in Singapore on 13–14 October 2016. The aim of the workshop was to discuss the latest trends in using high-throughput sequencing, bioinformatics, and allied technologies to analyze immune and pathogen repertoires and their interplay within the host, bringing together key international players in the field and Singapore-based researchers and clinician-scientists. The focus was in particular on the application of these technologies for the improvement of patient diagnosis, prognosis and treatment, and for other broad public health outcomes. The presentations by scientists and clinicians showed the potential of deep sequencing technology to capture the coevolution of adaptive immunity and pathogens. For clinical applications, some key challenges remain, such as the long turnaround time and relatively high cost of deep sequencing for pathogen identification and characterization and the lack of international standardization in immune repertoire analysis.

Single-Cell RNA Sequencing Reveals Expanded Clones of Islet Antigen-Reactive CD4+ T Cells in Peripheral Blood of Subjects with Type 1 Diabetes

The significance of islet Ag-reactive T cells found in peripheral blood of type 1 diabetes (T1D) subjects is unclear, partly because similar cells are also found in healthy control (HC) subjects. We hypothesized that key disease-associated cells would show evidence of prior Ag exposure, inferred from expanded TCR clonotypes, and essential phenotypic properties in their transcriptomes. To test this, we developed single-cell RNA sequencing procedures for identifying TCR clonotypes and transcript phenotypes in individual T cells. We applied these procedures to analysis of islet Ag-reactive CD4⁺ memory T cells from the blood of T1D and HC individuals after activation with pooled immunodominant islet peptides. We found extensive TCR clonotype sharing in Ag-activated cells, especially from individual T1D subjects, consistent with in vivo T cell expansion during disease progression. The expanded clonotype from one T1D subject was detected at repeat visits spanning >15 mo, demonstrating clonotype stability. Notably, we found no clonotype sharing between subjects, indicating a predominance of "private" TCR specificities. Expanded clones from two T1D subjects recognized distinct IGRP peptides, implicating this molecule as a trigger for CD4⁺ T cell expansion. Although overall transcript profiles of cells from HC and T1D subjects were similar, profiles from the most expanded clones were distinctive. Our findings demonstrate that islet Ag-reactive CD4⁺ memory T cells with unique Ag specificities and phenotypes are expanded during disease progression and can be detected by single-cell analysis of peripheral blood.

Novel Approaches to Analyze Immunoglobulin Repertoires

Analysis of immunoglobulin (Ig) repertoires aims to comprehend Ig diversity with the goal of predicting humoral immune responses in the context of infection, vaccination, autoimmunity, and malignancies. The first next-generation sequencing (NGS) analyses of bulk B cell populations dramatically advanced sampling depth over previous low-throughput single-cell-based protocols, albeit at the expense of accuracy and loss of chain-pairing information. In recent years the field has substantially differentiated, with bulk analyses becoming more accurate while single-cell approaches have gained in throughput. Additionally, new platforms striving to combine high throughput and chain pairing have been developed as well as various computational tools for analysis. Here we review the developments of the past 4-5 years and discuss the open challenges.

Advances in single-cell RNA sequencing and its applications in cancer research

Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic analysis of an individual cell. Through the combination of high-throughput sequencing and bioinformatic tools, single-cell RNA-seq can detect more than 10,000 transcripts in one cell to distinguish cell subsets and dynamic cellular changes. After several years’ development, single-cell RNA-seq can now achieve massively parallel, full-length mRNA sequencing as well as in situ sequencing and even has potential for multi-omic detection. One appealing area of single-cell RNA-seq is cancer research, and it is regarded as a promising way to enhance prognosis and provide more precise target therapy by identifying druggable subclones. Indeed, progresses have been made regarding solid tumor analysis to reveal intratumoral heterogeneity, correlations between signaling pathways, stemness, drug resistance, and tumor architecture shaping the microenvironment. Furthermore, through investigation into circulating tumor cells, many genes have been shown to promote a propensity toward stemness and the epithelial-mesenchymal transition, to enhance anchoring and adhesion, and to be involved in mechanisms of anoikis resistance and drug resistance. This review focuses on advances and progresses of single-cell RNA-seq with regard to the following aspects:

1. Methodologies of single-cell RNA-seq

2. Single-cell isolation techniques

3. Single-cell RNA-seq in solid tumor research

4. Single-cell RNA-seq in circulating tumor cell research

5. Perspectives

Scaling single-cell genomics from phenomenology to mechanism

Three of the most fundamental questions in biology are how individual cells differentiate to form tissues, how tissues function in a coordinated and flexible fashion and which gene regulatory mechanisms support these processes. Single-cell genomics is opening up new ways to tackle these questions by combining the comprehensive nature of genomics with the microscopic resolution that is required to describe complex multicellular systems. Initial single-cell genomic studies provided a remarkably rich phenomenology of heterogeneous cellular states, but transforming observational studies into models of dynamics and causal mechanisms in tissues poses fresh challenges and requires stronger integration of theoretical, computational and experimental frameworks.

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.

Measuring Signaling and RNA-Seq in the Same Cell Links Gene Expression to Dynamic Patterns of NF-κB Activation

Signaling proteins display remarkable cell-to-cell heterogeneity in their dynamic responses to stimuli, but the consequences of this heterogeneity remain largely unknown. For instance, the contribution of the dynamics of the innate immune transcription factor nuclear factor κB (NF-κB) to gene expression output is disputed. Here we explore these questions by integrating live-cell imaging approaches with single-cell sequencing technologies. We used this approach to measure both the dynamics of lipopolysaccharide-induced NF-κB activation and the global transcriptional response in the same individual cell. Our results identify multiple, distinct cytokine expression patterns that are correlated with NF-κB activation dynamics, establishing a functional role for NF-κB dynamics in determining cellular phenotypes. Applications of this approach to other model systems and single-cell sequencing technologies have significant potential for discovery, as it is now possible to trace cellular behavior from the initial stimulus, through the signaling pathways, down to genome-wide changes in gene expression, all inside of a single cell.

Aging increases cell-to-cell transcriptional variability upon immune stimulation

Aging is characterized by progressive loss of physiological and cellular functions, but the molecular basis of this decline remains unclear. We explored how aging affects transcriptional dynamics using single-cell RNA sequencing of unstimulated and stimulated naïve and effector memory CD4+ T cells from young and old mice from two divergent species. In young animals, immunological activation drives a conserved transcriptomic switch, resulting in tightly controlled gene expression characterized by a strong up-regulation of a core activation program, coupled with a decrease in cell-to-cell variability. Aging perturbed the activation of this core program and increased expression heterogeneity across populations of cells in both species. These discoveries suggest that increased cell-to-cell transcriptional variability will be a hallmark feature of aging across most, if not all, mammalian tissues.

Are cells from a snowman realistic? Cryopreserved tissues as a source for single-cell RNA-sequencing experiments

A recently published study in Genome Biology shows that cells isolated from cryopreserved tissues are a reliable source of genetic material for single-cell RNA-sequencing experiments.Please see related Method article: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1171-9.

Writ large: Genomic dissection of the effect of cellular environment on immune response

Cells of the immune system routinely respond to cues from their local environment and feed back to their surroundings through transient responses, choice of differentiation trajectories, plastic changes in cell state, and malleable adaptation to their tissue of residence. Genomic approaches have opened the way for comprehensive interrogation of such orchestrated responses. Focusing on genomic profiling of transcriptional and epigenetic cell states, we discuss how they are applied to investigate immune cells faced with various environmental cues. We highlight some of the emerging principles on the role of dense regulatory circuitry, epigenetic memory, cell type fluidity, and reuse of regulatory modules in achieving and maintaining appropriate responses to a changing environment. These provide a first step toward a systematic understanding of molecular circuits in complex tissues.

A new mechanism shapes the naïve CD8+ T cell repertoire: the selection for full diversity

During thymic T cell differentiation, TCR repertoires are shaped by negative, positive and agonist selection. In the thymus and in the periphery, repertoires are also shaped by strong inter-clonal and intra-clonal competition to survive death by neglect. Understanding the impact of these events on the T cell repertoire requires direct evaluation of TCR expression in peripheral naïve T cells. Several studies have evaluated TCR diversity, with contradictory results. Some of these studies had intrinsic technical limitations since they used material obtained from T cell pools, preventing the direct evaluation of clonal sizes. Indeed with these approaches, identical TCRs may correspond to different cells expressing the same receptor, or to several amplicons from the same T cell. We here overcame this limitation by evaluating TCRB expression in individual naïve CD8⁺ T cells. Of the 2269 Tcrb sequences we obtained from 13 mice, 99% were unique. Mathematical analysis of the data showed that the average number of naïve peripheral CD8⁺ T cells expressing the same TCRB is 1.1 cell. Since TCRA co-expression studies could only increase repertoire diversity, these results reveal that the number of naïve T cells with unique TCRs approaches the number of naïve cells. Since thymocytes undergo multiple rounds of divisions after TCRB rearrangement and 3-5% of thymocytes survive thymic selection events the number of cells expressing the same TCRB was expected to be much higher. Thus, these results suggest a new repertoire selection mechanism, which strongly selects for full TCRB diversity.

Single-cell RNA-seq and computational analysis using temporal mixture modelling resolves Th1/Tfh fate bifurcation in malaria

Differentiation of naïve CD4+ T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to extensive heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a challenge for systematic dissection in vivo. By using single-cell transcriptomics and computational analysis using a temporal mixtures of Gaussian processes model, termed GPfates, we reconstructed the developmental trajectories of Th1 and Tfh cells during blood-stage Plasmodium infection in mice. By tracking clonality using endogenous TCR sequences, we first demonstrated that Th1/Tfh bifurcation had occurred at both population and single-clone levels. Next, we identified genes whose expression was associated with Th1 or Tfh fates, and demonstrated a T-cell intrinsic role for Galectin-1 in supporting a Th1 differentiation. We also revealed the close molecular relationship between Th1 and IL-10-producing Tr1 cells in this infection. Th1 and Tfh fates emerged from a highly proliferative precursor that upregulated aerobic glycolysis and accelerated cell cycling as cytokine expression began. Dynamic gene expression of chemokine receptors around bifurcation predicted roles for cell-cell in driving Th1/Tfh fates. In particular, we found that precursor Th cells were coached towards a Th1 but not a Tfh fate by inflammatory monocytes. Thus, by integrating genomic and computational approaches, our study has provided two unique resources, a database www.PlasmoTH.org, which facilitates discovery of novel factors controlling Th1/Tfh fate commitment, and more generally, GPfates, a modelling framework for characterizing cell differentiation towards multiple fates.

Single-cell transcriptome analysis of fish immune cells provides insight into the evolution of vertebrate immune cell types

The immune system of vertebrate species consists of many different cell types that have distinct functional roles and are subject to different evolutionary pressures. Here, we first analyzed conservation of genes specific for all major immune cell types in human and mouse. Our results revealed higher gene turnover and faster evolution of trans-membrane proteins in NK cells compared with other immune cell types, and especially T cells, but similar conservation of nuclear and cytoplasmic protein coding genes. To validate these findings in a distant vertebrate species, we used single-cell RNA sequencing of lck:GFP cells in zebrafish and obtained the first transcriptome of specific immune cell types in a nonmammalian species. Unsupervised clustering and single-cell TCR locus reconstruction identified three cell populations, T cells, a novel type of NK-like cells, and a smaller population of myeloid-like cells. Differential expression analysis uncovered new immune-cell-specific genes, including novel immunoglobulin-like receptors, and neofunctionalization of recently duplicated paralogs. Evolutionary analyses confirmed the higher gene turnover of trans-membrane proteins in NK cells compared with T cells in fish species, suggesting that this is a general property of immune cell types across all vertebrates.

Identifying T Cell Receptors from High-Throughput Sequencing: Dealing with Promiscuity in TCRα and TCRβ Pairing

Characterisation of the T cell receptors (TCR) involved in immune responses is important for the design of vaccines and immunotherapies for cancer and autoimmune disease. The specificity of the interaction between the TCR heterodimer and its peptide-MHC ligand derives largely from the juxtaposed hypervariable CDR3 regions on the TCRα and TCRβ chains, and obtaining the paired sequences of these regions is a standard for functionally defining the TCR. A brute force approach to identifying the TCRs in a population of T cells is to use high-throughput single-cell sequencing, but currently this process remains costly and risks missing small clones. Alternatively, CDR3α and CDR3β sequences can be associated using their frequency of co-occurrence in independent samples, but this approach can be confounded by the sharing of CDR3α and CDR3β across clones, commonly observed within epitope-specific T cell populations. The accurate, exhaustive, and economical recovery of TCR sequences from such populations therefore remains a challenging problem. Here we describe an algorithm for performing frequency-based pairing (alphabetr) that accommodates CDR3α- and CDR3β-sharing, cells expressing two TCRα chains, and multiple forms of sequencing error. The algorithm also yields accurate estimates of clonal frequencies.

Single-Cell Genomics: Approaches and Utility in Immunology

Single-cell genomics offers powerful tools for studying immune cells, which make it possible to observe rare and intermediate cell states that cannot be resolved at the population level. Advances in computer science and single-cell sequencing technology have created a data-driven revolution in immunology. The challenge for immunologists is to harness computing and turn an avalanche of quantitative data into meaningful discovery of immunological principles, predictive models, and strategies for therapeutics. Here, we review the current literature on computational analysis of single-cell RNA-sequencing data and discuss underlying assumptions, methods, and applications in immunology, and highlight important directions for future research.

Tissue distribution and clonal diversity of the T and B cell repertoire in type 1 diabetes

The adaptive immune repertoire plays a critical role in type 1 diabetes (T1D) pathogenesis. However, efforts to characterize B cell and T cell receptor (TCR) profiles in T1D subjects have been largely limited to peripheral blood sampling and restricted to known antigens. To address this, we collected pancreatic draining lymph nodes (pLN), "irrelevant" nonpancreatic draining lymph nodes, peripheral blood mononuclear cells (PBMC), and splenocytes from T1D subjects (n = 18) and control donors (n = 9) as well as pancreatic islets from 1 T1D patient; from these tissues, we collected purified CD4⁺ conventional T cells (Tconv), CD4⁺ Treg, CD8⁺ T cells, and B cells. By conducting high-throughput immunosequencing of the TCR β chain (TRB) and B cell receptor (BCR) immunoglobulin heavy chain (IGH) on these samples, we sought to analyze the molecular signature of the lymphocyte populations within these tissues and of T1D. Ultimately, we observed a highly tissue-restricted CD4⁺ repertoire, while up to 24% of CD8⁺ clones were shared among tissues. We surveyed our data set for previously described proinsulin- and glutamic acid decarboxylase 65-reactive (GAD65-reactive) receptors, and interestingly, we observed a TRB with homology to a known GAD65-reactive TCR (clone GAD4.13) present in 7 T1D donors (38.9%), representing >25% of all productive TRB within Tconv isolated from the pLN of 1 T1D subject. These data demonstrate diverse receptor signatures at the nucleotide level and enriched autoreactive clones at the amino acid level, supporting the utility of coupling immunosequencing data with knowledge of characterized autoreactive receptors.

Single-cell barcoding and sequencing using droplet microfluidics

Single-cell RNA sequencing has recently emerged as a powerful tool for mapping cellular heterogeneity in diseased and healthy tissues, yet high-throughput methods are needed for capturing the unbiased diversity of cells. Droplet microfluidics is among the most promising candidates for capturing and processing thousands of individual cells for whole-transcriptome or genomic analysis in a massively parallel manner with minimal reagent use. We recently established a method called inDrops, which has the capability to index >15,000 cells in an hour. A suspension of cells is first encapsulated into nanoliter droplets with hydrogel beads (HBs) bearing barcoding DNA primers. Cells are then lysed and mRNA is barcoded (indexed) by a reverse transcription (RT) reaction. Here we provide details for (i) establishing an inDrops platform (1 d); (ii) performing hydrogel bead synthesis (4 d); (iii) encapsulating and barcoding cells (1 d); and (iv) RNA-seq library preparation (2 d). inDrops is a robust and scalable platform, and it is unique in its ability to capture and profile >75% of cells in even very small samples, on a scale of thousands or tens of thousands of cells.

Human immune system variation

The human immune system is highly variable between individuals but relatively stable over time within a given person. Recent conceptual and technological advances have enabled systems immunology analyses, which reveal the composition of immune cells and proteins in populations of healthy individuals. The range of variation and some specific influences that shape an individual's immune system is now becoming clearer. Human immune systems vary as a consequence of heritable and non-heritable influences, but symbiotic and pathogenic microbes and other non-heritable influences explain most of this variation. Understanding when and how such influences shape the human immune system is key for defining metrics of immunological health and understanding the risk of immune-mediated and infectious diseases.

Exploring viral infection using single-cell sequencing

Single-cell sequencing (SCS) has emerged as a valuable tool to study cellular heterogeneity in diverse fields, including virology. By studying the viral and cellular genome and/or transcriptome, the dynamics of viral infection can be investigated at single cell level. Most studies have explored the impact of cell-to-cell variation on the viral life cycle from the point of view of the virus, by analyzing viral sequences, and from the point of view of the cell, mainly by analyzing the cellular host transcriptome. In this review, we will focus on recent studies that use single-cell sequencing to explore viral diversity and cell variability in response to viral replication.