Transcriptional profiling of cells sorted by RNA abundance

Single-cell transcriptional landscapes reveal HIV-1-driven aberrant host gene transcription as a potential therapeutic target

Understanding HIV-1-host interactions can identify the cellular environment supporting HIV-1 reactivation and mechanisms of clonal expansion. We developed HIV-1 SortSeq to isolate rare HIV-1-infected cells from virally suppressed, HIV-1-infected individuals upon early latency reversal. Single-cell transcriptome analysis of HIV-1 SortSeq⁺ cells revealed enrichment of nonsense-mediated RNA decay and viral transcription pathways. HIV-1 SortSeq⁺ cells up-regulated cellular factors that can support HIV-1 transcription (IMPDH1 and JAK1) or promote cellular survival (IL2 and IKBKB). HIV-1-host RNA landscape analysis at the integration site revealed that HIV-1 drives high aberrant host gene transcription downstream, but not upstream, of the integration site through HIV-1-to-host aberrant splicing, in which HIV-1 RNA splices into the host RNA and aberrantly drives host RNA transcription. HIV-1-induced aberrant transcription was driven by the HIV-1 promoter as shown by CRISPR-dCas9-mediated HIV-1-specific activation and could be suppressed by CRISPR-dCas9-mediated inhibition of HIV-1 5' long terminal repeat. Overall, we identified cellular factors supporting HIV-1 reactivation and HIV-1-driven aberrant host gene transcription as potential therapeutic targets to disrupt HIV-1 persistence.

Comparison of bias and resolvability in single-cell and single-transcript methods

Single-cell and single-transcript measurement methods have elevated our ability to understand and engineer biological systems. However, defining and comparing performance between methods remains a challenge, in part due to the confounding effects of experimental variability. Here, we propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is shared between methods. We demonstrate the utility of this framework by performing 12 different methods in parallel to measure the same underlying reference system for cellular response. We compare method performance using quantitative evaluations of bias and resolvability. We attribute differences in method performance to steps along the measurement process such as sample preparation, signal detection, and choice of measurand. Finally, we demonstrate how this framework can be used to benchmark different methods for single-transcript detection. The framework we present here provides a practical way to compare performance of any methods.

Microdroplet-based one-step RT-PCR for ultrahigh throughput single-cell multiplex gene expression analysis and rare cell detection

Gene expression analysis of individual cells enables characterization of heterogeneous and rare cell populations, yet widespread implementation of existing single-cell gene analysis techniques has been hindered due to limitations in scale, ease, and cost. Here, we present a novel microdroplet-based, one-step reverse-transcriptase polymerase chain reaction (RT-PCR) platform and demonstrate the detection of three targets simultaneously in over 100,000 single cells in a single experiment with a rapid read-out. Our customized reagent cocktail incorporates the bacteriophage T7 gene 2.5 protein to overcome cell lysate-mediated inhibition and allows for one-step RT-PCR of single cells encapsulated in nanoliter droplets. Fluorescent signals indicative of gene expressions are analyzed using a probabilistic deconvolution method to account for ambient RNA and cell doublets and produce single-cell gene signature profiles, as well as predict cell frequencies within heterogeneous samples. We also developed a simulation model to guide experimental design and optimize the accuracy and precision of the assay. Using mixtures of in vitro transcripts and murine cell lines, we demonstrated the detection of single RNA molecules and rare cell populations at a frequency of 0.1%. This low cost, sensitive, and adaptable technique will provide an accessible platform for high throughput single-cell analysis and enable a wide range of research and clinical applications.

Probe-Seq: Method for RNA Sequencing of Specific Cell Types from Animal Tissue

Most organs and tissues are composed of many types of cells. To characterize cellular state, various transcription profiling approaches are currently available, including whole-tissue bulk RNA sequencing, single cell RNA sequencing (scRNA-Seq), and cell type-specific RNA sequencing. What is missing in this repertoire is a simple, versatile method for bulk transcriptional profiling of cell types for which cell type-specific genetic markers or antibodies are not readily available. We therefore developed Probe-Seq, which uses hybridization of gene-specific probes to RNA markers for isolation of specific types of cells, to enable downstream FACS isolation and bulk RNA sequencing. We show that this method can enable isolation and profiling of specific cell types from mouse retina, frozen human retina, Drosophila midgut, and developing chick retina, suggesting that it is likely useful for most organisms.

FIN-Seq: transcriptional profiling of specific cell types from frozen archived tissue of the human central nervous system

Thousands of frozen, archived tissue samples from the human central nervous system (CNS) are currently available in brain banks. As recent developments in RNA sequencing technologies are beginning to elucidate the cellular diversity present within the human CNS, it is becoming clear that an understanding of this diversity would greatly benefit from deeper transcriptional analyses. Single cell and single nucleus RNA profiling provide one avenue to decipher this heterogeneity. An alternative, complementary approach is to profile isolated, pre-defined cell types and use methods that can be applied to many archived human tissue samples that have been stored long-term. Here, we developed FIN-Seq (Frozen Immunolabeled Nuclei Sequencing), a method that accomplishes these goals. FIN-Seq uses immunohistochemical isolation of nuclei of specific cell types from frozen human tissue, followed by bulk RNA-Sequencing. We applied this method to frozen postmortem samples of human cerebral cortex and retina and were able to identify transcripts, including low abundance transcripts, in specific cell types.

Probe-Seq enables transcriptional profiling of specific cell types from heterogeneous tissue by RNA-based isolation

Recent transcriptional profiling technologies are uncovering previously-undefined cell populations and molecular markers at an unprecedented pace. While single cell RNA (scRNA) sequencing is an attractive approach for unbiased transcriptional profiling of all cell types, a complementary method to isolate and sequence specific cell populations from heterogeneous tissue remains challenging. Here, we developed Probe-Seq, which allows deep transcriptional profiling of specific cell types isolated using RNA as the defining feature. Dissociated cells are labeled using fluorescent in situ hybridization (FISH) for RNA, and then isolated by fluorescent activated cell sorting (FACS). We used Probe-Seq to purify and profile specific cell types from mouse, human, and chick retinas, as well as from Drosophila midguts. Probe-Seq is compatible with frozen nuclei, making cell types within archival tissue immediately accessible. As it can be multiplexed, combinations of markers can be used to create specificity. Multiplexing also allows for the isolation of multiple cell types from one cell preparation. Probe-Seq should enable RNA profiling of specific cell types from any organism.

Transcriptional Heterogeneity of Beta Cells in the Intact Pancreas

Pancreatic beta cells have been shown to be heterogeneous at multiple levels. However, spatially interrogating transcriptional heterogeneity in the intact tissue has been challenging. Here, we developed an optimized protocol for single-molecule transcript imaging in the intact pancreas and used it to identify a sub-population of "extreme" beta cells with elevated mRNA levels of insulin and other secretory genes. Extreme beta cells contain higher ribosomal and proinsulin content but lower levels of insulin protein in fasted states, suggesting they may be tuned for basal insulin secretion. They exhibit a distinctive intra-cellular polarization pattern, with elevated mRNA concentrations in an apical ER-enriched compartment, distinct from the localization of nascent and mature proteins. The proportion of extreme cells increases in db/db diabetic mice, potentially facilitating the required increase in basal insulin. Our results thus highlight a sub-population of beta cells that may carry distinct functional roles along physiological and pathological timescales.

ClampFISH detects individual nucleic acid molecules using click chemistry-based amplification

Methods for detecting single nucleic acids in cell and tissues, such as fluorescence in situ hybridization (FISH), are limited by relatively low signal intensity and nonspecific probe binding. Here we present click-amplifying FISH (clampFISH), a method for fluorescence detection of nucleic acids that achieves high specificity and high-gain (>400-fold) signal amplification. ClampFISH probes form a 'C' configuration upon hybridization to the sequence of interest in a double helical manner. The ends of the probes are ligated together using bio-orthogonal click chemistry, effectively locking the probes around the target. Iterative rounds of hybridization and click amplify the fluorescence intensity. We show that clampFISH enables the detection of RNA species with low-magnification microscopy and in RNA-based flow cytometry. Additionally, we show that the modular design of clampFISH probes allows multiplexing of RNA and DNA detection, that the locking mechanism prevents probe detachment in expansion microscopy, and that clampFISH can be applied in tissue samples.

Single molecule approaches for studying gene regulation in metabolic tissues

Gene expression in metabolic tissues can be regulated at multiple levels, ranging from the control of promoter accessibilities, transcription rates, mRNA degradation rates and mRNA localization. Modulating these processes can differentially affect important performance criteria of cells. These include precision, cellular economy, rapid response and maintenance of DNA integrity. In this review we will describe how distinct strategies of gene regulation impact the trade-offs between the cells' performance criteria. We will highlight tools based on single molecule visualization of transcripts that can be used to measure promoter states, transcription rates and mRNA degradation rates in intact tissues. These approaches revealed surprising recurrent patterns in mammalian tissues, that include transcriptional bursting, nuclear retention of mRNA, and coordination of mRNA lifetimes to facilitate rapid adaptation to changing metabolic inputs. The ability to characterize gene expression at the single molecule level can uncover the design principles of gene regulation in metabolic tissues such as the liver and the pancreas.

Systematic identification of factors mediating accelerated mRNA degradation in response to changes in environmental nitrogen

Cellular responses to changing environments frequently involve rapid reprogramming of the transcriptome. Regulated changes in mRNA degradation rates can accelerate reprogramming by clearing or stabilizing extant transcripts. Here, we measured mRNA stability using 4-thiouracil labeling in the budding yeast Saccharomyces cerevisiae during a nitrogen upshift and found that 78 mRNAs are subject to destabilization. These transcripts include Nitrogen Catabolite Repression (NCR) and carbon metabolism mRNAs, suggesting that mRNA destabilization is a mechanism for targeted reprogramming of the transcriptome. To explore the molecular basis of destabilization we implemented a SortSeq approach to screen the pooled deletion collection library for trans factors that mediate rapid GAP1 mRNA repression. We combined low-input multiplexed Barcode sequencing with branched-DNA single-molecule mRNA FISH and Fluorescence-activated cell sorting (BFF) to identify the Lsm1-7p/Pat1p complex and general mRNA decay machinery as important for GAP1 mRNA clearance. We also find that the decapping modulators EDC3 and SCD6, translation factor eIF4G2, and the 5' UTR of GAP1 are factors that mediate rapid repression of GAP1 mRNA, suggesting that translational control may impact the post-transcriptional fate of mRNAs in response to environmental changes.

Cholesterol signaling in single cells: lessons from STAR and sm-FISH

Cholesterol is an important regulator of cell signaling, both through direct impacts on cell membranes and through oxy-metabolites that activate specific receptors (steroids, hydroxy-cholesterols, bile acids). Cholesterol moves slowly through and between cell membranes with the assistance of specific binding proteins and transfer processes. The prototype cholesterol regulator is the Steroidogenesis Acute Regulatory (STAR), which moves cholesterol into mitochondria, where steroid synthesis is initiated by cytochrome P450 11A1 in multiple endocrine cell types. CYP27A1 generates hydroxyl cholesterol metabolites that activate LXR nuclear receptors to control cholesterol homeostatic and transport mechanisms. LXR regulation of cholesterol transport and storage as cholesterol ester droplets is shared by both steroid-producing cells and macrophage. This cholesterol signaling is crucial to brain neuron regulation by astrocytes and microglial macrophage, mediated by ApoE and sensitive to disruption by β-amyloid plaques. sm-FISH delivers appreciable insights into signaling in single cells, by resolving single RNA molecules as mRNA and by quantifying pre-mRNA at gene loci. sm-FISH has been applied to problems in physiology, embryo development and cancer biology, where single cell features have critical impacts. sm-FISH identifies novel features of STAR transcription in adrenal and testis cells, including asymmetric expression at individual gene loci, delayed splicing and 1:1 association of mRNA with mitochondria. This may represent a functional unit for the translation-dependent cholesterol transfer directed by STAR, which integrates into mitochondrial fusion dynamics. Similar cholesterol dynamics repeat with different players in the cycling of cholesterol between astrocytes and neurons in the brain, which may be abnormal in neurodegenerative diseases.

Isolation of intact RNA from murine CD4+ T cells after intracellular cytokine staining and fluorescence-activated cell sorting

Intracellular cytokine staining (ICS) is a powerful method for identifying functionally distinct lymphocyte subsets, and for isolating these by fluorescence activated cell sorting (FACS). Although transcriptomic analysis of cells sorted on the basis of ICS has many potential applications, this is rarely performed because of the difficulty in isolating intact RNA from cells processed using standard fixation and permeabilization buffers for ICS. To address this issue, we compared three buffers shown previously to preserve RNA in nonhematopoietic cells subjected to intracellular staining for their effects on RNA isolated from T lymphocytes processed for ICS. Our results showed that buffers containing the recombinant ribonuclease inhibitor RNasin or high molar concentrations of salt yielded intact RNA from fixed and permeabilized T cells. As proof of principle, we successfully used the buffer containing RNasin to isolate intact RNA from CD4⁺ T cells that were sorted by FACS on the basis of specific cytokine production, thus demonstrating the potential of this approach for coupling ICS with transcriptomic analysis.

Transcriptome Analysis of Mycobacteria-Specific CD4+ T Cells Identified by Activation-Induced Expression of CD154

Analysis of Ag-specific CD4⁺ T cells in mycobacterial infections at the transcriptome level is informative but technically challenging. Although several methods exist for identifying Ag-specific T cells, including intracellular cytokine staining, cell surface cytokine-capture assays, and staining with peptide:MHC class II multimers, all of these have significant technical constraints that limit their usefulness. Measurement of activation-induced expression of CD154 has been reported to detect live Ag-specific CD4⁺ T cells, but this approach remains underexplored and, to our knowledge, has not previously been applied in mycobacteria-infected animals. In this article, we show that CD154 expression identifies adoptively transferred or endogenous Ag-specific CD4⁺ T cells induced by Mycobacterium bovis bacillus Calmette-Guérin vaccination. We confirmed that Ag-specific cytokine production was positively correlated with CD154 expression by CD4⁺ T cells from bacillus Calmette-Guérin-vaccinated mice and show that high-quality microarrays can be performed from RNA isolated from CD154⁺ cells purified by cell sorting. Analysis of microarray data demonstrated that the transcriptome of CD4⁺ CD154⁺ cells was distinct from that of CD154^- cells and showed major enrichment of transcripts encoding multiple cytokines and pathways of cellular activation. One notable finding was the identification of a previously unrecognized subset of mycobacteria-specific CD4⁺ T cells that is characterized by the production of IL-3. Our results support the use of CD154 expression as a practical and reliable method to isolate live Ag-specific CD4⁺ T cells for transcriptomic analysis and potentially for a range of other studies in infected or previously immunized hosts.

Cerebral cortical neuron diversity and development at single-cell resolution

Over a century of efforts to categorize the astonishing diversity of cortical neurons has relied on criteria of morphology, electrophysiology, ontology, and the expression of a few transcripts and proteins. The rapid development of single-cell RNA sequencing (scRNA-seq) adds genome-wide gene expression patterns to this list of criteria, and promises to reveal new insights into the transitions that establish neuronal identity during development, differentiation, activity, and disease. Comparing single neuron data to reference atlases constructed from hundreds of thousands of single-cell transcriptomes will be critical to understanding these transitions and the molecular mechanisms that drive them. We review early efforts, and discuss future challenges and opportunities, in applying scRNA-seq to the elucidation of neuronal subtypes and their development.

RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures

BACKGROUND

Rare cell subtypes can profoundly impact the course of human health and disease, yet their presence within a sample is often missed with bulk molecular analysis. Single-cell analysis tools such as FACS, FISH-FC and single-cell barcode-based sequencing can investigate cellular heterogeneity; however, they have significant limitations that impede their ability to identify and transcriptionally characterize many rare cell subpopulations.

RESULTS

PCR-activated cell sorting (PACS) is a novel cytometry method that uses single-cell TaqMan PCR reactions performed in microfluidic droplets to identify and isolate cell subtypes with high-throughput. Here, we extend this method and demonstrate that PACS enables high-dimensional molecular profiling on TaqMan-targeted cells. Using a random priming RNA-Seq strategy, we obtained high-fidelity transcriptome measurements following PACS sorting of prostate cancer cells from a heterogeneous population. The sequencing data revealed prostate cancer gene expression profiles that were obscured in the unsorted populations. Single-cell expression analysis with PACS was subsequently used to confirm a number of the differentially expressed genes identified with RNA sequencing.

CONCLUSIONS

PACS requires minimal sample processing, uses readily available TaqMan assays and can isolate cell subtypes with high sensitivity. We have now validated a method for performing next-generation sequencing on mRNA obtained from PACS isolated cells. This capability makes PACS well suited for transcriptional profiling of rare cells from complex populations to obtain maximal biological insight into cell states and behaviors.

Simultaneous, Single-Cell Measurement of Messenger RNA, Cell Surface Proteins, and Intracellular Proteins

Nucleic acid content can be quantified by flow cytometry through the use of intercalating compounds; however, measuring the presence of specific sequences has hitherto been difficult to achieve by this methodology. The primary obstacle to detecting discrete nucleic acid sequences by flow cytometry is their low quantity and the presence of high background signals, rendering the detection of hybridized fluorescent probes challenging. Amplification of nucleic acid sequences by molecular techniques such as in situ PCR have been applied to single-cell suspensions, but these approaches have not been easily adapted to conventional flow cytometry. An alternative strategy implements a Branched DNA technique, comprising target-specific probes and sequentially hybridized amplification reagents, resulting in a theoretical 8,000- to 16,000-fold increase in fluorescence signal amplification. The Branched DNA technique allows for the quantification of native and unmanipulated mRNA content with increased signal detection and reduced background. This procedure utilizes gentle fixation steps with low hybridization temperatures, leaving the assayed cells intact to permit their concomitant immunophenotyping. This technology has the potential to advance scientific discovery by correlating potentially small quantities of mRNA with many biological measurements at the single-cell level.

Pooled shRNA Screening in Mammalian Cells as a Functional Genomic Discovery Platform

Functional genomic screens using shRNA technology are a great tool in biomedical research. As more labs gain access to the necessary reagents and technology to perform such screens, some may lack in-depth knowledge on the difficulties often encountered. With this protocol, we aim to point out the most important caveats of performing shRNA based screens and provide a streamlined workflow that can be easily adapted to meet the specific needs of any particular screening project.

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.

Fixed single-cell transcriptomic characterization of human radial glial diversity

The human neocortex is created from diverse intermixed progenitors in the prenatal germinal zones. These progenitors have been difficult to characterize since progenitors—particularly radial glia (RG)—are rare, and are defined by a combination of intracellular markers, position and morphology. To circumvent these problems we developed a method called FRISCR for transcriptome profiling of individual fixed, stained and sorted cells. After validation of FRISCR using human embryonic stem cells, we profiled primary human RG that constitute only 1% of the mid-gestation cortex. These RG could be classified into ventricular zone-enriched RG (vRG) that express ANXA1 and CRYAB, and outer subventricular zone-localized RG (oRG) that express HOPX. Our study identifies the first markers and molecular profiles of vRG and oRG cells, and provides an essential step for understanding molecular networks driving the lineage of human neocortical progenitors. Furthermore, FRISCR allows targeted single-cell transcriptomic profiling of tissues that lack live-cell markers.

Functional footprinting of regulatory DNA

Regulatory regions harbor multiple transcription factor (TF) recognition sites; however, the contribution of individual sites to regulatory function remains challenging to define. We describe an approach that exploits the error-prone nature of genome editing-induced double-strand break repair to map functional elements within regulatory DNA at nucleotide resolution. We demonstrate the approach on a human erythroid enhancer, revealing single TF recognition sites that gate the majority of downstream regulatory function.

The developmental potential of iPSCs is greatly influenced by reprogramming factor selection

Induced pluripotent stem cells (iPSCs) are commonly generated by transduction of Oct4, Sox2, Klf4, and Myc (OSKM) into cells. Although iPSCs are pluripotent, they frequently exhibit high variation in terms of quality, as measured in mice by chimera contribution and tetraploid complementation. Reliably high-quality iPSCs will be needed for future therapeutic applications. Here, we show that one major determinant of iPSC quality is the combination of reprogramming factors used. Based on tetraploid complementation, we found that ectopic expression of Sall4, Nanog, Esrrb, and Lin28 (SNEL) in mouse embryonic fibroblasts (MEFs) generated high-quality iPSCs more efficiently than other combinations of factors including OSKM. Although differentially methylated regions, transcript number of master regulators, establishment of specific superenhancers, and global aneuploidy were comparable between high- and low-quality lines, aberrant gene expression, trisomy of chromosome 8, and abnormal H2A.X deposition were distinguishing features that could potentially also be applicable to human.

Development of a novel cell sorting method that samples population diversity in flow cytometry

Flow cytometry based electrostatic cell sorting is an important tool in the separation of cell populations. Existing instruments can sort single cells into multi-well collection plates, and keep track of cell of origin and sorted well location. However currently single sorted cell results reflect the population distribution and fail to capture the population diversity. Software was designed that implements a novel sorting approach, "Slice and Dice Sorting," that links a graphical representation of a multi-well plate to logic that ensures that single cells are sampled and sorted from all areas defined by the sort region/s. Therefore the diversity of the total population is captured, and the more frequently occurring or rarer cell types are all sampled. The sorting approach was tested computationally, and using functional cell based assays. Computationally we demonstrate that conventional single cell sorting can sample as little as 50% of the population diversity dependant on the population distribution, and that Slice and Dice sorting samples much more of the variety present within a cell population. We then show by sorting single cells into wells using the Slice and Dice sorting method that there are cells sorted using this method that would be either rarely sorted, or not sorted at all using conventional single cell sorting approaches. The present study demonstrates a novel single cell sorting method that samples much more of the population diversity than current methods. It has implications in clonal selection, stem cell sorting, single cell sequencing and any areas where population heterogeneity is of importance.

Systems cell biology

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology.

Single-cell RNA-seq: advances and future challenges

Phenotypically identical cells can dramatically vary with respect to behavior during their lifespan and this variation is reflected in their molecular composition such as the transcriptomic landscape. Single-cell transcriptomics using next-generation transcript sequencing (RNA-seq) is now emerging as a powerful tool to profile cell-to-cell variability on a genomic scale. Its application has already greatly impacted our conceptual understanding of diverse biological processes with broad implications for both basic and clinical research. Different single-cell RNA-seq protocols have been introduced and are reviewed here—each one with its own strengths and current limitations. We further provide an overview of the biological questions single-cell RNA-seq has been used to address, the major findings obtained from such studies, and current challenges and expected future developments in this booming field.