Deep generative modeling for single-cell transcriptomics.

Single-cell transcriptome measurements can reveal unexplored biological diversity, but they suffer from technical noise and bias that must be modeled to account for the resulting uncertainty in downstream analyses. Here we introduce single-cell variational inference (scVI), a ready-to-use scalable framework for the probabilistic representation and analysis of gene expression in single cells ( https://github.com/YosefLab/scVI ). scVI uses stochastic optimization and deep neural networks to aggregate information across similar cells and genes and to approximate the distributions that underlie observed expression values, while accounting for batch effects and limited sensitivity. We used scVI for a range of fundamental analysis tasks including batch correction, visualization, clustering, and differential expression, and achieved high accuracy for each task

Selective Impairment of TH17-Differentiation and Protection against Autoimmune Arthritis after Overexpression of BCL2A1 in T Lymphocytes

The inhibition of apoptotic cell death in T cells through the dysregulated expression of BCL2 family members has been associated with the protection against the development of different autoimmune diseases. However, multiple mechanisms were proposed to be responsible for such protective effect. The purpose of this study was to explore the effect of the Tcell overexpression of BCL2A1, an anti-apoptotic BCL2 family member without an effect on cell cycle progression, in the development of collagen-induced arthritis. Our results demonstrated an attenuated development of arthritis in these transgenic mice. The protective effect was unrelated to the suppressive activity of regulatory T cells but it was associated with a defective activation of p38 mitogen-activated protein kinase in CD4+ cells after in vitro TCR stimulation. In addition, the in vitro and in vivo TH17 differentiation were impaired in BCL2A1 transgenic mice. Taken together, we demonstrated here a previously unknown role for BCL2A1 controlling the activation of CD4+ cells and their differentiation into pathogenic proinflammatory TH17 cells and identified BCL2A1 as a potential target in the control of autoimmune/inflammatory diseases

Stabilization of cytokine mRNAs in iNKT cells requires the serine-threonine kinase IRE1alpha

Activated invariant natural killer T (iNKT) cells rapidly produce large amounts of cytokines, but how cytokine mRNAs are induced, stabilized and mobilized following iNKT activation is still unclear. Here we show that an endoplasmic reticulum stress sensor, inositol-requiring enzyme 1α (IRE1α), links key cellular processes required for iNKT cell effector functions in specific iNKT subsets, in which TCR-dependent activation of IRE1α is associated with downstream activation of p38 MAPK and the stabilization of preformed cytokine mRNAs. Importantly, genetic deletion of IRE1α in iNKT cells reduces cytokine production and protects mice from oxazolone colitis. We therefore propose that an IRE1α-dependent signaling cascade couples constitutive cytokine mRNA expression to the rapid induction of cytokine secretion and effector functions in activated iNKT cells

The neuropeptide NMU amplifies ILC2-driven allergic lung inflammation

Type 2 innate lymphoid cells (ILC2s) both contribute to mucosal homeostasis and initiate pathologic inflammation in allergic asthma. However, the signals that direct ILC2s to promote homeostasis versus inflammation are unclear. To identify such molecular cues, we profiled mouse lung-resident ILCs using single-cell RNA sequencing at steady state and after in vivo stimulation with the alarmin cytokines IL-25 and IL-33. ILC2s were transcriptionally heterogeneous after activation, with subpopulations distinguished by expression of proliferative, homeostatic and effector genes. The neuropeptide receptor Nmur1 was preferentially expressed by ILC2s at steady state and after IL-25 stimulation. Neuromedin U (NMU), the ligand of NMUR1, activated ILC2s in vitro, and in vivo co-administration of NMU with IL-25 strongly amplified allergic inflammation. Loss of NMU-NMUR1 signalling reduced ILC2 frequency and effector function, and altered transcriptional programs following allergen challenge in vivo. Thus, NMUR1 signalling promotes inflammatory ILC2 responses, highlighting the importance of neuro-immune crosstalk in allergic inflammation at mucosal surfaces

JunB is essential for IL-23-dependent pathogenicity of Th17 cells

CD4+ T-helper cells producing interleukin-17 (IL-17), known as T-helper 17 (TH17) cells, comprise heterogeneous subsets that exhibit distinct pathogenicity. Although pathogenic and non-pathogenic TH17 subsets share a common RORγt-dependent TH17 transcriptional programme, transcriptional regulatory mechanisms specific to each of these subsets are mostly unknown. Here we show that the AP-1 transcription factor JunB is critical for TH17 pathogenicity. JunB, which is induced by IL-6, is essential for expression of RORγt and IL-23 receptor by facilitating DNA binding of BATF at the Rorc locus in IL-23-dependent pathogenic TH17 cells, but not in TGF-β1-dependent non-pathogenic TH17 cells. Junb-deficient T cells fail to induce TH17-mediated autoimmune encephalomyelitis and colitis. However, JunB deficiency does not affect the abundance of gut-resident non-pathogenic TH17 cells. The selective requirement of JunB for IL-23-dependent TH17 pathogenicity suggests that the JunB-dependent pathway may be a therapeutic target for autoimmune diseases

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

A freely available semi-automated method for quantifying retinal ganglion cells in entire retinal flatmounts

Glaucomatous optic neuropathies are characterized by progressive loss of retinal ganglion cells (RGCs), the neurons that connect the eye to the brain. Quantification of these RGCs is a cornerstone in experimental optic neuropathy research and commonly performed via manually quantifying parts of the retina. However, this is a time-consuming process subject to inter- and intra-observer variability. Here we present a freely available ImageJ script to semi-automatically quantify RGCs in entire retinal flatmounts after immunostaining for the RGC-specific transcription factor Brn3a. The blob-like signal of Brn3a-immunopositive RGCs is enhanced via eigenvalues of the Hessian matrix and the resulting local maxima are counted as RGCs. After the user has outlined the retinal flatmount area, the total RGC number and retinal area are reported and an isodensity map, showing the RGC density distribution across the retina, is created. The semi-automated quantification shows a very strong correlation (Pearson's r ≥ 0.99) with manual counts for both widefield and confocal images, thereby validating the data generated via the developed script. Moreover, application of this method in established glaucomatous optic neuropathy models such as N-methyl-D-aspartate-induced excitotoxicity, optic nerve crush and laser-induced ocular hypertension revealed RGC loss conform with literature. Compared to manual counting, the described automated quantification method is faster and shows user-independent consistency. Furthermore, as the script detects the RGC number in entire retinal flatmounts, the method allows detection of regional differences in RGC density. As such, it can help advance research investigating the degenerative mechanisms of glaucomatous optic neuropathies and the effectiveness of new neuroprotective treatments. Because the script is flexible and easy to optimize due to a low number of critical parameters, it can potentially be applied in combination with other tissues or alternative labeling protocols.publisher: Elsevier articletitle: A freely available semi-automated method for quantifying retinal ganglion cells in entire retinal flatmounts journaltitle: Experimental Eye Research articlelink: http://dx.doi.org/10.1016/j.exer.2016.04.010 content_type: article copyright: © 2016 Elsevier Ltd. All rights reserved.status: publishe

Geometry-dependent functional changes in iPSC-derived cardiomyocytes probed by functional imaging and RNA sequencing.

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) are a promising platform for cardiac studies in vitro, and possibly for tissue repair in humans. However, hiPSC-CM cells tend to retain morphology, metabolism, patterns of gene expression, and electrophysiology similar to that of embryonic cardiomyocytes. We grew hiPSC-CM in patterned islands of different sizes and shapes, and measured the effect of island geometry on action potential waveform and calcium dynamics using optical recordings of voltage and calcium from 970 islands of different sizes. hiPSC-CM in larger islands showed electrical and calcium dynamics indicative of greater functional maturity. We then compared transcriptional signatures of the small and large islands against a developmental time course of cardiac differentiation. Although island size had little effect on expression of most genes whose levels differed between hiPSC-CM and adult primary CM, we identified a subset of genes for which island size drove the majority (58%) of the changes associated with functional maturation. Finally, we patterned hiPSC-CM on islands with a variety of shapes to probe the relative contributions of soluble factors, electrical coupling, and direct cell-cell contacts to the functional maturation. Collectively, our data show that optical electrophysiology is a powerful tool for assaying hiPSC-CM maturation, and that island size powerfully drives activation of a subset of genes involved in cardiac maturation

Geometry-dependent functional changes in iPSC-derived cardiomyocytes probed by functional imaging and RNA sequencing

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) are a promising platform for cardiac studies in vitro, and possibly for tissue repair in humans. However, hiPSC-CM cells tend to retain morphology, metabolism, patterns of gene expression, and electrophysiology similar to that of embryonic cardiomyocytes. We grew hiPSC-CM in patterned islands of different sizes and shapes, and measured the effect of island geometry on action potential waveform and calcium dynamics using optical recordings of voltage and calcium from 970 islands of different sizes. hiPSC-CM in larger islands showed electrical and calcium dynamics indicative of greater functional maturity. We then compared transcriptional signatures of the small and large islands against a developmental time course of cardiac differentiation. Although island size had little effect on expression of most genes whose levels differed between hiPSC-CM and adult primary CM, we identified a subset of genes for which island size drove the majority (58%) of the changes associated with functional maturation. Finally, we patterned hiPSC-CM on islands with a variety of shapes to probe the relative contributions of soluble factors, electrical coupling, and direct cell-cell contacts to the functional maturation. Collectively, our data show that optical electrophysiology is a powerful tool for assaying hiPSC-CM maturation, and that island size powerfully drives activation of a subset of genes involved in cardiac maturation