Single cell RNA Seq reveals dynamic paracrine control of cellular variation

Nature (Impact Factor: 41.46). 06/2014; 510(7505). DOI: 10.1038/nature13437
Source: PubMed


High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis and function of gene expression variation between seemingly identical cells. Here we sequence single-cell RNA-seq libraries prepared from over 1,700 primary mouse bone-marrow-derived dendritic cells spanning several experimental conditions. We find substantial variation between identically stimulated dendritic cells, in both the fraction of cells detectably expressing a given messenger RNA and the transcript's level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a 'core' module of antiviral genes is expressed very early by a few 'precocious' cells in response to uniform stimulation with a pathogenic component, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analysing dendritic cells from knockout mice, and modulating secretion and extracellular signalling, we show that this response is coordinated by interferon-mediated paracrine signalling from these precocious cells. Notably, preventing cell-to-cell communication also substantially reduces variability between cells in the expression of an early-induced 'peaked' inflammatory module, suggesting that paracrine signalling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations can use to establish complex dynamic responses.

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    • "Notably, N-glycosylation and ER stress were previously shown to interact with the TLR pathway (Komura et al., 2013; Martinon et al., 2010); however, direct involvement of OSTc was not shown. The LPS response in DCs has been previously characterized (Shalek et al., 2014) by three distinct co-expression signatures: (1) anti-viral genes (''anti-viral''), (2) inflammatory genes, including Tnf, whose expression peaks at 2 hr (''peaked inflammatory''), and (3) inflammatory genes with sustained expression within the 6 hr timescale (''sustained inflammatory''). While several of the mutants in the known TLR pathway genes were defective in activating all three signatures (Figures 5C–5E), targeting OSTc members reduced the inflammatory signatures (sustained: p = 0.01; peaked: p = 0.01, t test), but not the anti-viral signature (p = 0.24, t test) (Figures 4B–4E and 5C– 5E), suggesting a specific rather than global effect on the Tlr4 response. "
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    ABSTRACT: Finding the components of cellular circuits and determining their functions systematically remains a major challenge in mammalian cells. Here, we introduced genome-wide pooled CRISPR-Cas9 libraries into dendritic cells (DCs) to identify genes that control the induction of tumor necrosis factor (Tnf) by bacterial lipopolysaccharide (LPS), a key process in the host response to pathogens, mediated by the Tlr4 pathway. We found many of the known regulators of Tlr4 signaling, as well as dozens of previously unknown candidates that we validated. By measuring protein markers and mRNA profiles in DCs that are deficient in known or candidate genes, we classified the genes into three functional modules with distinct effects on the canonical responses to LPS and highlighted functions for the PAF complex and oligosaccharyltransferase (OST) complex. Our findings uncover new facets of innate immune circuits in primary cells and provide a genetic approach for dissection of mammalian cell circuits. Copyright © 2015 Elsevier Inc. All rights reserved.
    Cell 07/2015; DOI:10.1016/j.cell.2015.06.059 · 32.24 Impact Factor
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    • "The use of cellular barcodes allows processing of multiple cells in single reaction tubes and has increased throughput to thousands of cells (Islam et al, 2011; Jaitin et al, 2014), while the use of microfluidics, especially in combination with molecular barcodes, has considerably decreased technical noise (Islam et al, 2013; Wu et al, 2014). Single-cell transcriptomics is therefore increasingly being used to chart the diversity of cell types within tissues (Jaitin et al, 2014; Treutlein et al, 2014) and during developmental transitions (Shalek et al, 2014), but investigation of heterogeneity within developmentally homogeneous cell populations has only recently started (Kumar et al, 2014). Following the availability of methods to determine the use of exons in single cells (Ramsköld et al, 2012), a recent study has investigated splice isoform heterogeneity in single dendritic cells (Shalek et al, 2013). "
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    ABSTRACT: Cell-to-cell variability in gene expression is important for many processes in biology, including embryonic development and stem cell homeostasis. While heterogeneity of gene expression levels has been extensively studied, less attention has been paid to mRNA polyadenylation isoform choice. 3' untranslated regions regulate mRNA fate, and their choice is tightly controlled during development, but how 3' isoform usage varies within genetically and developmentally homogeneous cell populations has not been explored. Here, we perform genome-wide quantification of polyadenylation site usage in single mouse embryonic and neural stem cells using a novel single-cell transcriptomic method, BATSeq. By applying BATBayes, a statistical framework for analyzing single-cell isoform data, we find that while the developmental state of the cell globally determines isoform usage, single cells from the same state differ in the choice of isoforms. Notably this variation exceeds random selection with equal preference in all cells, a finding that was confirmed by RNA FISH data. Variability in 3' isoform choice has potential implications on functional cell-to-cell heterogeneity as well as utility in resolving cell populations. © 2015 The Authors. Published under the terms of the CC BY 4.0 license.
    Molecular Systems Biology 06/2015; 11(6). DOI:10.15252/msb.20156198 · 10.87 Impact Factor
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    • "With scRNA-seq, cell-to-cell variation in all expressed genes in a given population can in theory be quantified. Heterogeneity in gene expression levels across cells can suggest the existence of new underlying subpopulations, as well as providing insights into a gene's function (Shalek et al., 2014). In a homogeneous population, heterogeneity in gene expression will likely arise from stochastic gene expression as well as nonsynchronous cellular processes such as the cell cycle or circadian rhythm (Buettner et al., 2015). "
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    ABSTRACT: The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications. Copyright © 2015 Elsevier Inc. All rights reserved.
    Molecular cell 05/2015; 58(4):610-620. DOI:10.1016/j.molcel.2015.04.005 · 14.02 Impact Factor
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