Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

Recent molecular studies have shown that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels and phenotypic output1, 2, 3, 4, 5, with important functional consequences4, 5. Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs1, 2 or proteins5, 6 simultaneously, because genomic profiling methods3 could not be applied to single cells until very recently7, 8, 9, 10. Here we use single-cell RNA sequencing to investigate heterogeneity in the response of mouse bone-marrow-derived dendritic cells (BMDCs) to lipopolysaccharide. We find extensive, and previously unobserved, bimodal variation in messenger RNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit, involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.National Institutes of Health (U.S.) (NIH Postdoctoral Fellowship (1F32HD075541-01))Charles H. Hood Foundation (Postdoctoral Fellowship)National Institutes of Health (U.S.) (NIH grant U54 AI057159)National Institutes of Health (U.S.) (NIH New Innovator Award (DP2 OD002230))National Institutes of Health (U.S.) (NIH CEGS Award (1P50HG006193-01))National Institutes of Health (U.S.) (NIH Pioneer Awards (5DP1OD003893-03))National Institutes of Health (U.S.) (NIH Pioneer Awards (DP1OD003958-01))Broad Institute of MIT and HarvardBroad Institute of MIT and Harvard (Klarman Cell Observatory

Single-cell RNA-seq reveals dynamic paracrine control of cellular variation

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.National Human Genome Research Institute (U.S.). Centers of Excellence in Genomic Science (1P50HG006193-01)National Institutes of Health (U.S.). Pioneer Award (DP1OD003958-01)Howard Hughes Medical InstituteBroad Institute of MIT and Harvard. Klarman Cell Observator

Single cell RNA Seq reveals dynamic paracrine control of cellular variation

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 (DCs) spanning several experimental conditions. We find substantial variation between identically stimulated DCs, in both the fraction of cells detectably expressing a given mRNA 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, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analyzing DCs from knockout mice, and modulating secretion and extracellular signaling, we show that this response is coordinated via interferon-mediated paracrine signaling. Surprisingly, preventing cell-to-cell communication also substantially reduces variability in the expression of an early-induced “peaked” inflammatory module, suggesting that paracrine signaling 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 use to establish complex dynamic responses

Single-Cell Genomics Unveils Critical Regulators of Th17 Cell Pathogenicity

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or differentiated in vitro under either pathogenic or non-pathogenic polarization conditions. Computational analysis relates a spectrum of cellular states in vivo to in vitro differentiated Th17 cells, and unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four new genes: Gpr65, Plzp, Toso and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity, and can identify targets for selective suppression of pathogenic Th17 cells while potentially sparing non-pathogenic tissue-protective onesNational Institutes of Health (U.S.) (Grant P50 HG006193)National Cancer Institute (U.S.) (David H. Koch Institute for Integrative Cancer Research at MIT. Grant P30-CA14051)Klarman Cell Observator

Vertical silicon nanowires as a universal platform for delivering biomolecules into living cells

A generalized platform for introducing a diverse range of biomolecules into living cells in high-throughput could transform how complex cellular processes are probed and analyzed. Here, we demonstrate spatially localized, efficient, and universal delivery of biomolecules into immortalized and primary mammalian cells using surface-modified vertical silicon nanowires. The method relies on the ability of the silicon nanowires to penetrate a cell’s membrane and subsequently release surface-bound molecules directly into the cell’s cytosol, thus allowing highly efficient delivery of biomolecules without chemical modification or viral packaging. This modality enables one to assess the phenotypic consequences of introducing a broad range of biological effectors (DNAs, RNAs, peptides, proteins, and small molecules) into almost any cell type. We show that this platform can be used to guide neuronal progenitor growth with small molecules, knock down transcript levels by delivering siRNAs, inhibit apoptosis using peptides, and introduce targeted proteins to specific organelles. We further demonstrate codelivery of siRNAs and proteins on a single substrate in a microarray format, highlighting this technology’s potential as a robust, monolithic platform for high-throughput, miniaturized bioassays

Nuclear magnetic resonance detection and spectroscopy of single proteins using quantum logic

Nuclear magnetic resonance spectroscopy is a powerful tool for the structural analysis of organic compounds and biomolecules but typically requires macroscopic sample quantities. We use a sensor, which consists of two quantum bits corresponding to an electronic spin and an ancillary nuclear spin, to demonstrate room temperature magnetic resonance detection and spectroscopy of multiple nuclear species within individual ubiquitin proteins attached to the diamond surface. Using quantum logic to improve readout fidelity and a surface-treatment technique to extend the spin coherence time of shallow nitrogen-vacancy centers, we demonstrate magnetic field sensitivity sufficient to detect individual proton spins within 1 second of integration. This gain in sensitivity enables high-confidence detection of individual proteins and allows us to observe spectral features that reveal information about their chemical composition.Physic

A semiconductor 96-microplate platform for electrical-imaging based high-throughput phenotypic screening

Abstract High-content imaging for compound and genetic profiling is popular for drug discovery but limited to endpoint images of fixed cells. Conversely, electronic-based devices offer label-free, live cell functional information but suffer from limited spatial resolution or throughput. Here, we introduce a semiconductor 96-microplate platform for high-resolution, real-time impedance imaging. Each well features 4096 electrodes at 25 µm spatial resolution and a miniaturized data interface allows 8× parallel plate operation (768 total wells) for increased throughput. Electric field impedance measurements capture >20 parameter images including cell barrier, attachment, flatness, and motility every 15 min during experiments. We apply this technology to characterize 16 cell types, from primary epithelial to suspension cells, and quantify heterogeneity in mixed co-cultures. Screening 904 compounds across 13 semiconductor microplates reveals 25 distinct responses, demonstrating the platform’s potential for mechanism of action profiling. The scalability and translatability of this semiconductor platform expands high-throughput mechanism of action profiling and phenotypic drug discovery applications