A Public BCR Present in a Unique Dual-Receptor-Expressing Lymphocyte from Type 1 Diabetes Patients Encodes a Potent T Cell Autoantigen.

T and B cells are the two known lineages of adaptive immune cells. Here, we describe a previously unknown lymphocyte that is a dual expresser (DE) of TCR and BCR and key lineage markers of both B and T cells. In type 1 diabetes (T1D), DEs are predominated by one clonotype that encodes a potent CD4 T cell autoantigen in its antigen binding site. Molecular dynamics simulations revealed that this peptide has an optimal binding register for diabetogenic HLA-DQ8. In concordance, a synthetic version of the peptide forms stable DQ8 complexes and potently stimulates autoreactive CD4 T cells from T1D patients, but not healthy controls. Moreover, mAbs bearing this clonotype are autoreactive against CD4 T cells and inhibit insulin tetramer binding to CD4 T cells. Thus, compartmentalization of adaptive immune cells into T and B cells is not absolute, and violators of this paradigm are likely key drivers of autoimmune diseases.

CellNet: network biology applied to stem cell engineering.

Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering.

Hippo pathway activity influences liver cell fate.

The Hippo-signaling pathway is an important regulator of cellular proliferation and organ size. However, little is known about the role of this cascade in the control of cell fate. Employing a combination of lineage tracing, clonal analysis, and organoid culture approaches, we demonstrate that Hippo pathway activity is essential for the maintenance of the differentiated hepatocyte state. Remarkably, acute inactivation of Hippo pathway signaling in vivo is sufficient to dedifferentiate, at very high efficiencies, adult hepatocytes into cells bearing progenitor characteristics. These hepatocyte-derived progenitor cells demonstrate self-renewal and engraftment capacity at the single-cell level. We also identify the NOTCH-signaling pathway as a functional important effector downstream of the Hippo transducer YAP. Our findings uncover a potent role for Hippo/YAP signaling in controlling liver cell fate and reveal an unprecedented level of phenotypic plasticity in mature hepatocytes, which has implications for the understanding and manipulation of liver regeneration.

Dissecting engineered cell types and enhancing cell fate conversion via CellNet.

Engineering clinically relevant cells in vitro holds promise for regenerative medicine, but most protocols fail to faithfully recapitulate target cell properties. To address this, we developed CellNet, a network biology platform that determines whether engineered cells are equivalent to their target tissues, diagnoses aberrant gene regulatory networks, and prioritizes candidate transcriptional regulators to enhance engineered conversions. Using CellNet, we improved B cell to macrophage conversion, transcriptionally and functionally, by knocking down predicted B cell regulators. Analyzing conversion of fibroblasts to induced hepatocytes (iHeps), CellNet revealed an unexpected intestinal program regulated by the master regulator Cdx2. We observed long-term functional engraftment of mouse colon by iHeps, thereby establishing their broader potential as endoderm progenitors and demonstrating direct conversion of fibroblasts into intestinal epithelium. Our studies illustrate how CellNet can be employed to improve direct conversion and to uncover unappreciated properties of engineered cells.

Organogenetic transcriptomes of the Drosophila embryo at single cell resolution.

To gain insight into the transcription programs activated during the formation of Drosophila larval structures, we carried out single cell RNA sequencing during two periods of Drosophila embryogenesis: stages 10-12, when most organs are first specified and initiate morphological and physiological specialization; and stages 13-16, when organs achieve their final mature architectures and begin to function. Our data confirm previous findings with regards to functional specialization of some organs - the salivary gland and trachea - and clarify the embryonic functions of another - the plasmatocytes. We also identify two early developmental trajectories in germ cells and uncover a potential role for proteolysis during germline stem cell specialization. We identify the likely cell type of origin for key components of the Drosophila matrisome and several commonly used Drosophila embryonic cell culture lines. Finally, we compare our findings with other recent related studies and with other modalities for identifying tissue-specific gene expression patterns. These data provide a useful community resource for identifying many new players in tissue-specific morphogenesis and functional specialization of developing organs.

Origins and implications of pluripotent stem cell variability and heterogeneity.

Pluripotent stem cells constitute a platform to model disease and developmental processes and can potentially be used in regenerative medicine. However, not all pluripotent cell lines are equal in their capacity to differentiate into desired cell types in vitro. Genetic and epigenetic variations contribute to functional variability between cell lines and heterogeneity within clones. These genetic and epigenetic variations could 'lock' the pluripotency network resulting in residual pluripotent cells or alter the signalling response of developmental pathways leading to lineage bias. The molecular contributors to functional variability and heterogeneity in both embryonic stem (ES) cells and induced pluripotent stem (iPS) cells are only beginning to emerge, yet they are crucial to the future of the stem cell field.

Spatial transcriptomics reveals a role for sensory nerves in preserving cranial suture patency through modulation of BMP/TGF-ß signaling.

The patterning and ossification of the mammalian skeleton requires the coordinated actions of both intrinsic bone morphogens and extrinsic neurovascular signals, which function in a temporal and spatial fashion to control mesenchymal progenitor cell (MPC) fate. Here, we show the genetic inhibition of tropomyosin receptor kinase A (TrkA) sensory nerve innervation of the developing cranium results in premature calvarial suture closure, associated with a decrease in suture MPC proliferation and increased mineralization. In vitro, axons from peripheral afferent neurons derived from dorsal root ganglions (DRGs) of wild-type mice induce MPC proliferation in a spatially restricted manner via a soluble factor when cocultured in microfluidic chambers. Comparative spatial transcriptomic analysis of the cranial sutures in vivo confirmed a positive association between sensory axons and proliferative MPCs. SpatialTime analysis across the developing suture revealed regional-specific alterations in bone morphogenetic protein (BMP) and TGF-ß signaling pathway transcripts in response to TrkA inhibition. RNA sequencing of DRG cell bodies, following direct, axonal coculture with MPCs, confirmed the alterations in BMP/TGF-ß signaling pathway transcripts. Among these, the BMP inhibitor follistatin-like 1 (FSTL1) replicated key features of the neural-to-bone influence, including mitogenic and anti-osteogenic effects via the inhibition of BMP/TGF-ß signaling. Taken together, our results demonstrate that sensory nerve-derived signals, including FSTL1, function to coordinate cranial bone patterning by regulating MPC proliferation and differentiation in the suture mesenchyme.

Immune Checkpoint Molecule TIGIT Regulates Kidney T Cell Functions and Contributes to AKI.

SIGNIFICANCE STATEMENT: T cells mediate pathogenic and reparative processes during AKI, but the exact mechanisms regulating kidney T cell functions are unclear. This study identified upregulation of the novel immune checkpoint molecule, TIGIT, on mouse and human kidney T cells after AKI. TIGIT-expressing kidney T cells produced proinflammatory cytokines and had effector (EM) and central memory (CM) phenotypes. TIGIT-deficient mice had protection from both ischemic and nephrotoxic AKI. Single-cell RNA sequencing led to the discovery of possible downstream targets of TIGIT. TIGIT mediates AKI pathophysiology, is a promising novel target for AKI therapy, and is being increasingly studied in human cancer therapy trials. BACKGROUND: T cells play pathogenic and reparative roles during AKI. However, mechanisms regulating T cell responses are relatively unknown. We investigated the roles of the novel immune checkpoint molecule T cell immunoreceptor with Ig and immunoreceptor tyrosine-based inhibitory motif domains (TIGIT) in kidney T cells and AKI outcomes. METHODS: TIGIT expression and functional effects were evaluated in mouse kidney T cells using RNA sequencing (RNA-Seq) and flow cytometry. TIGIT effect on AKI outcomes was studied with TIGIT knockout (TIGIT-KO) mice in ischemia reperfusion (IR) and cisplatin AKI models. Human kidney T cells from nephrectomy samples and single cell RNA sequencing (scRNA-Seq) data from the Kidney Precision Medicine Project were used to assess TIGIT's role in humans. RESULTS: RNA-Seq and flow cytometry analysis of mouse kidney CD4+ T cells revealed increased expression of TIGIT after IR injury. Ischemic injury also increased TIGIT expression in human kidney T cells, and TIGIT expression was restricted to T/natural killer cell subsets in patients with AKI. TIGIT-expressing kidney T cells in wild type (WT) mice had an effector/central memory phenotype and proinflammatory profile at baseline and post-IR. Kidney regulatory T cells were predominantly TIGIT+ and significantly reduced post-IR. TIGIT-KO mice had significantly reduced kidney injury after IR and nephrotoxic injury compared with WT mice. scRNA-Seq analysis showed enrichment of genes related to oxidative phosphorylation and mTORC1 signaling in Th17 cells from TIGIT-KO mice. CONCLUSIONS: TIGIT expression increases in mouse and human kidney T cells during AKI, worsens AKI outcomes, and is a novel therapeutic target for AKI.

Gene regulation network inference using k-nearest neighbor-based mutual information estimation: revisiting an old DREAM.

BACKGROUND: A cell exhibits a variety of responses to internal and external cues. These responses are possible, in part, due to the presence of an elaborate gene regulatory network (GRN) in every single cell. In the past 20 years, many groups worked on reconstructing the topological structure of GRNs from large-scale gene expression data using a variety of inference algorithms. Insights gained about participating players in GRNs may ultimately lead to therapeutic benefits. Mutual information (MI) is a widely used metric within this inference/reconstruction pipeline as it can detect any correlation (linear and non-linear) between any number of variables (n-dimensions). However, the use of MI with continuous data (for example, normalized fluorescence intensity measurement of gene expression levels) is sensitive to data size, correlation strength and underlying distributions, and often requires laborious and, at times, ad hoc optimization. RESULTS: In this work, we first show that estimating MI of a bi- and tri-variate Gaussian distribution using k-nearest neighbor (kNN) MI estimation results in significant error reduction as compared to commonly used methods based on fixed binning. Second, we demonstrate that implementing the MI-based kNN Kraskov-Stoögbauer-Grassberger (KSG) algorithm leads to a significant improvement in GRN reconstruction for popular inference algorithms, such as Context Likelihood of Relatedness (CLR). Finally, through extensive in-silico benchmarking we show that a new inference algorithm CMIA (Conditional Mutual Information Augmentation), inspired by CLR, in combination with the KSG-MI estimator, outperforms commonly used methods. CONCLUSIONS: Using three canonical datasets containing 15 synthetic networks, the newly developed method for GRN reconstruction-which combines CMIA, and the KSG-MI estimator-achieves an improvement of 20-35% in precision-recall measures over the current gold standard in the field. This new method will enable researchers to discover new gene interactions or better choose gene candidates for experimental validations.

A single cell transcriptional atlas of early synovial joint development.

Synovial joint development begins with the formation of the interzone, a region of condensed mesenchymal cells at the site of the prospective joint. Recently, lineage-tracing strategies have revealed that Gdf5-lineage cells native to and from outside the interzone contribute to most, if not all, of the major joint components. However, there is limited knowledge of the specific transcriptional and signaling programs that regulate interzone formation and fate diversification of synovial joint constituents. To address this, we have performed single cell RNA-Seq analysis of 7329 synovial joint progenitor cells from the developing murine knee joint from E12.5 to E15.5. By using a combination of computational analytics, in situ hybridization and in vitro characterization of prospectively isolated populations, we have identified the transcriptional profiles of the major developmental paths for joint progenitors. Our freely available single cell transcriptional atlas will serve as a resource for the community to uncover transcriptional programs and cell interactions that regulate synovial joint development.

Single-Cell Transcriptomic Census of Endothelial Changes Induced by Matrix Stiffness and the Association with Atherosclerosis.

Vascular endothelial cell (EC) plasticity plays a critical role in the progression of atherosclerosis by giving rise to mesenchymal phenotypes in the plaque lesion. Despite the evidence for arterial stiffening as a major contributor to atherosclerosis, the complex interplay among atherogenic stimuli in vivo has hindered attempts to determine the effects of extracellular matrix (ECM) stiffness on endothelial-mesenchymal transition (EndMT). To study the regulatory effects of ECM stiffness on EndMT, an in vitro model is developed in which human coronary artery ECs are cultured on physiological or pathological stiffness substrates. Leveraging single-cell RNA sequencing, cell clusters with mesenchymal transcriptional features are identified to be more prevalent on pathological substrates than physiological substrates. Trajectory inference analyses reveal a novel mesenchymal-to-endothelial reverse transition, which is blocked by pathological stiffness substrates, in addition to the expected EndMT trajectory. ECs pushed to a mesenchymal character by pathological stiffness substrates are enriched in transcriptional signatures of atherosclerotic ECs from human and murine plaques. This study characterizes at single-cell resolution the transcriptional programs that underpin EC plasticity in both physiological or pathological milieus, and thus serves as a valuable resource for more precisely defining EndMT and the transcriptional programs contributing to atherosclerosis.

Multiple mechanisms disrupt the let-7 microRNA family in neuroblastoma.

Poor prognosis in neuroblastoma is associated with genetic amplification of MYCN. MYCN is itself a target of let-7, a tumour suppressor family of microRNAs implicated in numerous cancers. LIN28B, an inhibitor of let-7 biogenesis, is overexpressed in neuroblastoma and has been reported to regulate MYCN. Here we show, however, that LIN28B is dispensable in MYCN-amplified neuroblastoma cell lines, despite de-repression of let-7. We further demonstrate that MYCN messenger RNA levels in amplified disease are exceptionally high and sufficient to sponge let-7, which reconciles the dispensability of LIN28B. We found that genetic loss of let-7 is common in neuroblastoma, inversely associated with MYCN amplification, and independently associated with poor outcomes, providing a rationale for chromosomal loss patterns in neuroblastoma. We propose that let-7 disruption by LIN28B, MYCN sponging, or genetic loss is a unifying mechanism of neuroblastoma development with broad implications for cancer pathogenesis.

Understanding development and stem cells using single cell-based analyses of gene expression.

In recent years, genome-wide profiling approaches have begun to uncover the molecular programs that drive developmental processes. In particular, technical advances that enable genome-wide profiling of thousands of individual cells have provided the tantalizing prospect of cataloging cell type diversity and developmental dynamics in a quantitative and comprehensive manner. Here, we review how single-cell RNA sequencing has provided key insights into mammalian developmental and stem cell biology, emphasizing the analytical approaches that are specific to studying gene expression in single cells.

Deconstructing transcriptional heterogeneity in pluripotent stem cells.

Pluripotent stem cells (PSCs) are capable of dynamic interconversion between distinct substates; however, the regulatory circuits specifying these states and enabling transitions between them are not well understood. Here we set out to characterize transcriptional heterogeneity in mouse PSCs by single-cell expression profiling under different chemical and genetic perturbations. Signalling factors and developmental regulators show highly variable expression, with expression states for some variable genes heritable through multiple cell divisions. Expression variability and population heterogeneity can be influenced by perturbation of signalling pathways and chromatin regulators. Notably, either removal of mature microRNAs or pharmacological blockage of signalling pathways drives PSCs into a low-noise ground state characterized by a reconfigured pluripotency network, enhanced self-renewal and a distinct chromatin state, an effect mediated by opposing microRNA families acting on the Myc/Lin28/let-7 axis. These data provide insight into the nature of transcriptional heterogeneity in PSCs.

TGF-ß inhibitors stimulate red blood cell production by enhancing self-renewal of BFU-E erythroid progenitors.

Burst-forming unit erythroid progenitors (BFU-Es) are so named based on their ability to generate in methylcellulose culture large colonies of erythroid cells that consist of "bursts" of smaller erythroid colonies derived from the later colony-forming unit erythroid progenitor erythropoietin (Epo)-dependent progenitors. "Early" BFU-E cells forming large BFU-E colonies presumably have higher capacities for self-renewal than do "late" BFU-Es forming small colonies, but the mechanism underlying this heterogeneity remains unknown. We show that the type III transforming growth factor ß (TGF-ß) receptor (TßRIII) is a marker that distinguishes early and late BFU-Es. Transient elevation of TßRIII expression promotes TGF-ß signaling during the early BFU-E to late BFU-E transition. Blocking TGF-ß signaling using a receptor kinase inhibitor increases early BFU-E cell self-renewal and total erythroblast production, suggesting the usefulness of this type of drug in treating Epo-unresponsive anemias.

Chromatin-modifying enzymes as modulators of reprogramming.

Generation of induced pluripotent stem cells (iPSCs) by somatic cell reprogramming involves global epigenetic remodelling. Whereas several proteins are known to regulate chromatin marks associated with the distinct epigenetic states of cells before and after reprogramming, the role of specific chromatin-modifying enzymes in reprogramming remains to be determined. To address how chromatin-modifying proteins influence reprogramming, we used short hairpin RNAs (shRNAs) to target genes in DNA and histone methylation pathways, and identified positive and negative modulators of iPSC generation. Whereas inhibition of the core components of the polycomb repressive complex 1 and 2, including the histone 3 lysine 27 methyltransferase EZH2, reduced reprogramming efficiency, suppression of SUV39H1, YY1 and DOT1L enhanced reprogramming. Specifically, inhibition of the H3K79 histone methyltransferase DOT1L by shRNA or a small molecule accelerated reprogramming, significantly increased the yield of iPSC colonies, and substituted for KLF4 and c-Myc (also known as MYC). Inhibition of DOT1L early in the reprogramming process is associated with a marked increase in two alternative factors, NANOG and LIN28, which play essential functional roles in the enhancement of reprogramming. Genome-wide analysis of H3K79me2 distribution revealed that fibroblast-specific genes associated with the epithelial to mesenchymal transition lose H3K79me2 in the initial phases of reprogramming. DOT1L inhibition facilitates the loss of this mark from genes that are fated to be repressed in the pluripotent state. These findings implicate specific chromatin-modifying enzymes as barriers to or facilitators of reprogramming, and demonstrate how modulation of chromatin-modifying enzymes can be exploited to more efficiently generate iPSCs with fewer exogenous transcription factors.

Investigating monogenic and complex diseases with pluripotent stem cells.

Human genetic studies have revealed the molecular basis of countless monogenic diseases but have been less successful in associating phenotype to genotype in complex multigenic conditions. Pluripotent stem cells (PSCs), which can differentiate into any cell type, offer promise for defining the functional effects of genetic variation. Here, we recount the advantages and practical limitations of coupling PSCs to genome-wide analyses to probe complex genetics and discuss the ability to investigate epigenetic contributions to disease states. We also describe new ways of using mice and mouse embryonic stem cells (ESCs) in tandem with human stem cells to further define genotype-phenotype relationships.

A nontranscriptional role for Oct4 in the regulation of mitotic entry.

Rapid progression through the cell cycle and a very short G1 phase are defining characteristics of embryonic stem cells. This distinct cell cycle is driven by a positive feedback loop involving Rb inactivation and reduced oscillations of cyclins and cyclin-dependent kinase (Cdk) activity. In this setting, we inquired how ES cells avoid the potentially deleterious consequences of premature mitotic entry. We found that the pluripotency transcription factor Oct4 (octamer-binding transcription factor 4) plays an unappreciated role in the ES cell cycle by forming a complex with cyclin-Cdk1 and inhibiting Cdk1 activation. Ectopic expression of Oct4 or a mutant lacking transcriptional activity recapitulated delayed mitotic entry in HeLa cells. Reduction of Oct4 levels in ES cells accelerated G2 progression, which led to increased chromosomal missegregation and apoptosis. Our data demonstrate an unexpected nontranscriptional function of Oct4 in the regulation of mitotic entry.

Polycomb repressive complex 2 regulates normal development of the mouse heart.

RATIONALE: Epigenetic marks are crucial for organogenesis, but their role in heart development is poorly understood. Polycomb repressive complex 2 (PRC2) trimethylates histone H3 at lysine 27, which establishes H3K27me3 repressive epigenetic marks that promote tissue-specific differentiation by silencing ectopic gene programs. OBJECTIVE: We studied the function of PRC2 in murine heart development using a tissue-restricted conditional inactivation strategy. METHODS AND RESULTS: Inactivation of the PRC2 subunit Ezh2 by Nkx2-5(Cre) (Ezh2(NK)) caused lethal congenital heart malformations, namely, compact myocardial hypoplasia, hypertrabeculation, and ventricular septal defect. Candidate and genome-wide RNA expression profiling and chromatin immunoprecipitation analyses of Ezh2(NK) heart identified genes directly repressed by EZH2. Among these were the potent cell cycle inhibitors Ink4a/b (inhibitors of cyclin-dependent kinase 4 A and B), the upregulation of which was associated with decreased cardiomyocyte proliferation in Ezh2(NK). EZH2-repressed genes were enriched for transcriptional regulators of noncardiomyocyte expression programs such as Pax6, Isl1, and Six1. EZH2 was also required for proper spatiotemporal regulation of cardiac gene expression, because Hcn4, Mlc2a, and Bmp10 were inappropriately upregulated in ventricular RNA. PRC2 was also required later in heart development, as indicated by cardiomyocyte-restricted TNT-Cre inactivation of the PRC2 subunit Eed. However, Ezh2 inactivation by TNT-Cre did not cause an overt phenotype, likely because of functional redundancy with Ezh1. Thus, early Ezh2 inactivation by Nk2-5(Cre) caused later disruption of cardiomyocyte gene expression and heart development. CONCLUSIONS: Our study reveals a previously undescribed role of EZH2 in regulating heart formation and shows that perturbation of the epigenetic landscape early in cardiogenesis has sustained disruptive effects at later developmental stages.

OneSC: A computational platform for recapitulating cell state transitions.

Computational modelling of cell state transitions has been a great interest of many in the field of developmental biology, cancer biology and cell fate engineering because it enables performing perturbation experiments in silico more rapidly and cheaply than could be achieved in a wet lab. Recent advancements in single-cell RNA sequencing (scRNA-seq) allow the capture of high-resolution snapshots of cell states as they transition along temporal trajectories. Using these high-throughput datasets, we can train computational models to generate in silico 'synthetic' cells that faithfully mimic the temporal trajectories. Here we present OneSC, a platform that can simulate synthetic cells across developmental trajectories using systems of stochastic differential equations govern by a core transcription factors (TFs) regulatory network. Different from the current network inference methods, OneSC prioritizes on generating Boolean network that produces faithful cell state transitions and steady cell states that mimic real biological systems. Applying OneSC to real data, we inferred a core TF network using a mouse myeloid progenitor scRNA-seq dataset and showed that the dynamical simulations of that network generate synthetic single-cell expression profiles that faithfully recapitulate the four myeloid differentiation trajectories going into differentiated cell states (erythrocytes, megakaryocytes, granulocytes and monocytes). Finally, through the in-silico perturbations of the mouse myeloid progenitor core network, we showed that OneSC can accurately predict cell fate decision biases of TF perturbations that closely match with previous experimental observations.