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

Shedding Light on Intracellular Proteins using Flow Cytometry

Intracellular protein abundance is routinely measured in mammalian cells using population-based techniques such as western blotting which fail to capture single cell protein levels or using fluorescence microscopy which is although suitable for single cell protein detection but not for rapid analysis of large no. of cells. Flow cytometry offers rapid, high-throughput, multiparameter-based analysis of intracellular protein expression in statistically significant no. of cells at single cell resolution. In past few decades, customized assays have been developed for flow cytometric detection of specific intracellular proteins. This review discusses the scope of flow cytometry for intracellular protein detection in mammalian cells along with specific applications. Technological advancements to overcome the limitations of traditional flow cytometry for the same are also discussed.

An Early Myelosuppression in the Acute Mouse Sepsis Is Partly Outcome-Dependent

Adult hematopoietic stem and progenitor cells (HSPCs) respond to bacterial infections by expansion to myeloid cells. Sepsis impairs this process by suppressing differentiation of stem cells subsequently contributing to an ineffective immune response. Whether the magnitude of HSPCs impairment in sepsis is severity-dependent remains unknown. This study investigated dynamics of the HSPC immune-inflammatory response in the bone marrow, splenic, and blood compartments in moribund and surviving septic mice. The 12-week-old outbred CD-1 female mice (n=65) were subjected to a cecal ligation and puncture (CLP) sepsis, treated with antibiotics and fluid resuscitation, and stratified into predicted-to-die (P-DIE) and predicted-to-survive (P-SUR) cohorts for analysis. CLP strongly reduced the common myeloid and multipotent progenitors, short- and long-term hematopoietic stem cell (HSC) counts in the bone marrow; lineage⁻ckit⁺Sca-1⁺ and short-term HSC suppression was greater in P-DIE versus P-SUR mice. A profound depletion of the common myeloid progenitors occurred in the blood (by 75%) and spleen (by 77%) of P-DIE. In P-SUR, most common circulating HSPCs subpopulations recovered to baseline by 72 h post-CLP. Analysis of activated caspase-1/-3/-7 revealed an increased apoptotic (by 30%) but not pyroptotic signaling in the bone marrow HSCs of P-DIE mice. The bone marrow from P-DIE mice revealed spikes of IL-6 (by 5-fold), CXCL1/KC (15-fold), CCL3/MIP-1α (1.7-fold), and CCL2/MCP-1 (2.8-fold) versus P-SUR and control (TNF, IFN-γ, IL-1β, -5, -10 remained unaltered). Summarizing, our findings demonstrate that an early sepsis-induced impairment of myelopoiesis is strongly outcome-dependent but varies among compartments. It is suggestive that the HSCPC loss is at least partly due to an increased apoptosis but not pyroptosis.

Computational strategies for single-cell multi-omics integration

Single-cell omics technologies are currently solving biological and medical problems that earlier have remained elusive, such as discovery of new cell types, cellular differentiation trajectories and communication networks across cells and tissues. Current advances especially in single-cell multi-omics hold high potential for breakthroughs by integration of multiple different omics layers. To pair with the recent biotechnological developments, many computational approaches to process and analyze single-cell multi-omics data have been proposed. In this review, we first introduce recent developments in single-cell multi-omics in general and then focus on the available data integration strategies. The integration approaches are divided into three categories: early, intermediate, and late data integration. For each category, we describe the underlying conceptual principles and main characteristics, as well as provide examples of currently available tools and how they have been applied to analyze single-cell multi-omics data. Finally, we explore the challenges and prospective future directions of single-cell multi-omics data integration, including examples of adopting multi-view analysis approaches used in other disciplines to single-cell multi-omics.

A Multiparameter Flow Cytometry Analysis Panel to Assess CD163 mRNA and Protein in Monocyte and Macrophage Populations in Hyperinflammatory Diseases

CD163 facilitates regulation and resolution of inflammation and removal of free hemoglobin and is highly expressed in myeloid cells from patients with inflammatory disorders, such as systemic juvenile idiopathic arthritis (SJIA) and macrophage activation syndrome (MAS). Our recent studies indicate that regulation of CD163 mRNA expression is a key functional property of polarized monocytes and macrophages and is mediated at the transcriptional and posttranscriptional level, including via microRNAs. The goal of the current study is to develop a multiparameter flow cytometry panel incorporating detection of CD163 mRNA for polarized monocyte and macrophage populations in disorders such as SJIA and MAS. THP-1 cells and CD14⁺ human monocytes were stained using fluorochrome-conjugated Abs to myeloid surface markers, along with CD163 mRNA. Staining for mRNA could reliably detect CD163 expression while simultaneously detecting different macrophage populations using Abs targeting CD14, CD64, CD80, CD163, and CD209. This approach was found to be highly sensitive for increased mRNA expression when macrophages were polarized with IL-10 [M(IL-10)], with a strong signal over a broad range of IL-10 concentrations, and showed distinct kinetics of CD163 mRNA and protein induction upon IL-10 stimulation. Finally, this panel demonstrated clear changes in polarization markers in unstimulated monocytes from patients with SJIA and MAS, including upregulated CD163 mRNA and increased CD64 expression. This approach represents a robust and sensitive system for RNA flow cytometry, useful for studying CD163 expression as part of a multimarker panel for human monocytes and macrophages, with broad applicability to the pathogenesis of hyperinflammatory diseases.

Single-cell Quantitation of mRNA and Surface Protein Expression in Simian Immunodeficiency Virus-infected CD4+ T Cells Isolated from Rhesus macaques

Single-cell analysis is an important tool for dissecting heterogeneous populations of cells. The identification and isolation of rare cells can be difficult. To overcome this challenge, a methodology combining indexed flow cytometry and high-throughput multiplexed quantitative polymerase chain reaction (qPCR) was developed. The objective was to identify and characterize simian immunodeficiency virus (SIV)-infected cells present within rhesus macaques. Through quantitation of surface protein by fluorescence-activated cell sorting (FACS) and mRNA by qPCR, virus-infected cells are identified by viral gene expression, which is combined with host gene and protein measurements to create a multidimensional profile. We term the approach, targeted Single-Cell Proteo-transcriptional Evaluation, or tSCEPTRE. To perform the method, viable cells are stained with fluorescent antibodies specific for surface markers used for FACS isolation of a cell subset and/or downstream phenotypic analysis. Single cells are sorted followed by immediate lysis, multiplex reverse transcription (RT), PCR pre-amplification, and high throughput qPCR of up to 96 transcripts. FACS measurements are recorded at the time of sorting and subsequently linked to the gene expression data by well position to create a combined protein and transcriptional profile. To study SIV-infected cells directly ex vivo, cells were identified by qPCR detection of multiple viral RNA species. The combination of viral transcripts and the quantity of each provide a framework for classifying cells into distinct stages of the viral life cycle (e.g., productive versus non-productive). Moreover, tSCEPTRE of SIV⁺ cells were compared to uninfected cells isolated from the same specimen to assess differentially expressed host genes and proteins. The analysis revealed previously unappreciated viral RNA expression heterogeneity among infected cells as well as in vivo SIV-mediated post-transcriptional gene regulation with single-cell resolution. The tSCEPTRE method is relevant for the analysis of any cell population amenable to identification by expression of surface protein marker(s), host or pathogen gene(s), or combinations thereof.

RNA Flow Cytometry Using the Branched DNA Technique

The systematic modulation of mRNA and proteins governs the complicated and intermingled biological functions of our cells. Traditionally, transcriptomic technologies such as DNA microarray and RNA-Seq have been used to identify, characterize, and profile gene expression data. These are, however, considered bulk methods as they are unable to measure gene expression at the single-cell level, unless the cells are pre-sorted. Branched DNA is a flow cytometry-based detection platform that has been developed recently to measure mRNA at the single-cell level. Originally adapted from microscopy, the current system has been modified to achieve compatibility with the detection of surface and intracellular antigens using monoclonal antibodies conjugated to fluorochromes, thus permitting simultaneous detection of mRNAs and proteins. The Branched DNA method offers a variety of advantages when compared to traditional or standard methods used for the quantification of mRNA, such as (a) the detection of specific mRNA on a per cell basis, (b) an alternate detection tool when the measurement of a protein is technically infeasible (i.e., no quality antibody exists) or the epitope is not assessable, and (c) correlate the analysis of mRNA with protein. Compared to earlier attempts at measuring nucleic acid by flow cytometry, the hybridization temperature applied in the Branched DNA assay is much lower, thus preserving the integrity of cellular structures for further characterization. It also has greatly increased specificity and sensitivity. Here, we provide detailed instruction for performing the Branched DNA method using it in a model system to correlate the expression of CD8 mRNA and CD8 protein by flow cytometry.

A Scalable Pipeline for High-Throughput Flow Cytometry

Flow cytometry (FC) provides high-content data for a variety of applications, including phenotypic analysis of cell surface and intracellular markers, characterization of cell supernatant or lysates, and gene expression analysis. Historically, sample preparation, acquisition, and analysis have presented as a bottleneck for running such types of assays at scale. This article will outline the solutions that have been implemented at Novartis which have allowed high-throughput FC to be successfully conducted and analyzed for a variety of cell-based assays. While these experiments were generally conducted to measure phenotypic responses from a well-characterized and information-rich small molecular probe library known as the Mechanism-of-Action (MoA) Box, they are broadly applicable to any type of test sample. The article focuses on application of automated methods for FC sample preparation in 384-well assay plates. It also highlights a pipeline for analyzing large volumes of FC data, covering a visualization approach that facilitates review of screen-level data by dynamically embedding FlowJo (FJ) workspace images for each sample into a Spotfire file, directly linking them to the metric being observed. Finally, an application of these methods to a screen for MHC-I expression upregulators is discussed.

Cancer-related mRNA expression analysis using a novel flow cytometry-based assay

BACKGROUND

Cancer-related gene expression data mostly originate from unfractionated bulk samples, leading to "expression averaging" of heterogeneous populations. Multicolor flow cytometry (FCM) may distinguish heterogeneous populations based on the phenotypic characterization of single-cells, but is not applicable for RNA targets. Here, we evaluated the PrimeFlow™ RNA assay, a novel FCM-based assay designed to measure gene expressions, in two cancer entities with high and low RNA target levels.

METHODS

Neuroblastoma (NB) cell lines were studied for MYCN gene expression by PrimeFlow™ and compared with the gold standard, RT-qPCR. Dilution series of NB cells (0.10-11%) were prepared to evaluate performance in small cell populations. Diagnostic material of de novo acute myeloid leukemia (AML) patients was used to measure Wilms' tumor 1 (WT1) expression in bulk leukemic cells and rare subsets, e.g. leukemic stem cells (LSCs). FCM analysis was performed on a FACSCanto II (BD Biosciences) using Infinicyt™ (Cytognos^® ) for data analysis. mRNA expression was reported by normalized mean fluorescence intensity (MFI) values and staining indices.

RESULTS

MYCN mRNA quantified by PrimeFlow™ significantly correlated with RT-qPCR and remained detectable in small (0.1%) populations. Using PrimeFlow^TM , WT1 levels were shown to be significantly higher in AML patient samples with WT1 overexpression, previously defined by RT-qPCR. Moreover, WT1 overexpression was distinguishable between heterogeneous cell populations and remained measurable in rare LSCs.

CONCLUSION

PrimeFlow™ is a sensitive technique to investigate mRNA expressions, with high concordance to RT-qPCR. High (MYCN) and subtle (WT1) overexpressed mRNA targets can be quantified in heterogeneous and rare subpopulations e.g. LSCs. © 2017 International Clinical Cytometry Society.

Germinal center B cell development has distinctly regulated stages completed by disengagement from T cell help

To reconcile conflicting reports on the role of CD40 signaling in germinal center (GC) formation, we examined the earliest stages of murine GC B cell differentiation. Peri-follicular GC precursors first expressed intermediate levels of BCL6 while co-expressing the transcription factors RelB and IRF4, the latter known to repress Bcl6 transcription. Transition of GC precursors to the BCL6^hi follicular state was associated with cell division, although the number of required cell divisions was immunogen dose dependent. Potentiating T cell help or CD40 signaling in these GC precursors actively repressed GC B cell maturation and diverted their fate towards plasmablast differentiation, whereas depletion of CD4+ T cells promoted this initial transition. Thus while CD40 signaling in B cells is necessary to generate the immediate precursors of GC B cells, transition to the BCL6^hi follicular state is promoted by a regional and transient diminution of T cell help.

DOI:http://dx.doi.org/10.7554/eLife.19552.001

Single-Cell Multiomics: Multiple Measurements from Single Cells

Single-cell sequencing provides information that is not confounded by genotypic or phenotypic heterogeneity of bulk samples. Sequencing of one molecular type (RNA, methylated DNA or open chromatin) in a single cell, furthermore, provides insights into the cell's phenotype and links to its genotype. Nevertheless, only by taking measurements of these phenotypes and genotypes from the same single cells can such inferences be made unambiguously. In this review, we survey the first experimental approaches that assay, in parallel, multiple molecular types from the same single cell, before considering the challenges and opportunities afforded by these and future technologies.

Unambiguous inference that a cellular phenotype is caused by a genotype can only be achieved by their measurement from the same single cell.

Estimating RNA and DNA copy number abundance in single cells is now possible using a variety of experimental approaches.

Parallel measurement of single-cell epigenomes and transcriptomes provides further insight into the regulation of cellular identity and phenotypes.

Parallel measurement of single-cell transcriptomes and protein abundance (by FACS, proximity ligation assays/PEA or mass cytometry) allows insight into expression dynamics.

Our understanding of cancer progression and diversity is likely to be advanced greatly by the multiomics investigation of single cells, as is our understanding of normal developmental and other disease processes.

Ongoing technological advances will see improvements in the coverage, sensitivity of multiomics approaches, as well the number of analytes that can be surveyed in parallel.

Flow cytometry what you see matters: Enhanced clinical detection using image-based flow cytometry

Image-based flow cytometry combines the throughput of traditional flow cytometry with the ability to visually confirm findings and collect novel data that would not be possible otherwise. Since image-based flow cytometry borrows measurement parameters and analysis techniques from microscopy, it is possible to collect unique measures (i.e. nuclear translocation, co-localization, cellular synapse, cellular endocytosis, etc.) that would not be possible with traditional flow cytometry. The ability to collect unique outcomes has led many researchers to develop novel assays for the monitoring and detection of a variety of clinical conditions and diseases. In many cases, investigators have innovated and expanded classical assays to provide new insight regarding clinical conditions and chronic disease. Beyond human clinical applications, image-based flow cytometry has been used to monitor marine biology changes, nano-particles for solar cell production, and particle quality in pharmaceuticals. This review article summarizes work from the major scientists working in the field of image-based flow cytometry.

Fluorescence In situ Hybridization: Cell-Based Genetic Diagnostic and Research Applications

Fluorescence in situ hybridization (FISH) is a macromolecule recognition technology based on the complementary nature of DNA or DNA/RNA double strands. Selected DNA strands incorporated with fluorophore-coupled nucleotides can be used as probes to hybridize onto the complementary sequences in tested cells and tissues and then visualized through a fluorescence microscope or an imaging system. This technology was initially developed as a physical mapping tool to delineate genes within chromosomes. Its high analytical resolution to a single gene level and high sensitivity and specificity enabled an immediate application for genetic diagnosis of constitutional common aneuploidies, microdeletion/microduplication syndromes, and subtelomeric rearrangements. FISH tests using panels of gene-specific probes for somatic recurrent losses, gains, and translocations have been routinely applied for hematologic and solid tumors and are one of the fastest-growing areas in cancer diagnosis. FISH has also been used to detect infectious microbias and parasites like malaria in human blood cells. Recent advances in FISH technology involve various methods for improving probe labeling efficiency and the use of super resolution imaging systems for direct visualization of intra-nuclear chromosomal organization and profiling of RNA transcription in single cells. Cas9-mediated FISH (CASFISH) allowed in situ labeling of repetitive sequences and single-copy sequences without the disruption of nuclear genomic organization in fixed or living cells. Using oligopaint-FISH and super-resolution imaging enabled in situ visualization of chromosome haplotypes from differentially specified single-nucleotide polymorphism loci. Single molecule RNA FISH (smRNA-FISH) using combinatorial labeling or sequential barcoding by multiple round of hybridization were applied to measure mRNA expression of multiple genes within single cells. Research applications of these single molecule single cells DNA and RNA FISH techniques have visualized intra-nuclear genomic structure and sub-cellular transcriptional dynamics of many genes and revealed their functions in various biological processes.