Villification of the intestinal epithelium is driven by Foxl1.

The primitive gut tube of mammals initially forms as a simple cylinder consisting of the endoderm-derived, pseudostratified epithelium and the mesoderm-derived surrounding mesenchyme. During mid-gestation a dramatic transformation occurs in which the epithelium is both restructured into its final cuboidal form and simultaneously folded and refolded to create intestinal villi and intervillus regions, the incipient crypts. Here we show that the mesenchymal winged helix transcription factor Foxl1, itself induced by epithelial hedgehog signaling, controls villification by activating BMP and PDGFRα as well as planar cell polarity genes in epithelial-adjacent telocyte progenitors, both directly and in a feed-forward loop with Foxo3.

Diurnal retinal and choroidal gene expression patterns support a role for circadian biology in myopia pathogenesis.

The prevalence of myopia (nearsightedness) is increasing to alarming levels, but its etiology remains poorly understood. Because both laboratory and clinical findings suggest an etiologic role for circadian rhythms in myopia development, we assayed gene expression by RNA-Seq in retina and choroid at the onset of unilateral experimental myopia in chick, isolating tissues every 4 h during a single 24-h period from myopic and contralateral control eyes. Occluded versus open eye gene expression differences varied considerably over the 24-h sampling period, with some occurring at multiple times of day but with others showing differences at only a single investigated timepoint. Some of the genes identified in retina or choroid of chick myopia were previously identified as candidate genes for common human myopia. Like differentially expressed genes, pathways identified by Gene Set Enrichment Analysis also varied dramatically by sampling time. Considered with other laboratory data, human genetic and epidemiology data, these findings further implicate circadian events in myopia pathogenesis. The present results emphasize a need to include time of day in mechanistic studies of myopia and to assess circadian biology directly in trying to understand better the origin of myopia and to develop more effective therapies.

Mu-opioid receptor-expressing neurons in the paraventricular thalamus modulate chronic morphine-induced wake alterations.

Disrupted sleep is a symptom of many psychiatric disorders, including substance use disorders. Most drugs of abuse, including opioids, disrupt sleep. However, the extent and consequence of opioid-induced sleep disturbance, especially during chronic drug exposure, is understudied. We have previously shown that sleep disturbance alters voluntary morphine intake. Here, we examine the effects of acute and chronic morphine exposure on sleep. Using an oral self-administration paradigm, we show that morphine disrupts sleep, most significantly during the dark cycle in chronic morphine, with a concomitant sustained increase in neural activity in the Paraventricular Nucleus of the Thalamus (PVT). Morphine binds primarily to Mu Opioid Receptors (MORs), which are highly expressed in the PVT. Translating Ribosome Affinity Purification (TRAP)-Sequencing of PVT neurons that express MORs showed significant enrichment of the circadian entrainment pathway. To determine whether MOR + cells in the PVT mediate morphine-induced sleep/wake properties, we inhibited these neurons during the dark cycle while mice were self-administering morphine. This inhibition decreased morphine-induced wakefulness but not general wakefulness, indicating that MORs in the PVT contribute to opioid-specific wake alterations. Overall, our results suggest an important role for PVT neurons that express MORs in mediating morphine-induced sleep disturbance.

Computational workflow and interactive analysis of single-cell expression profiling of islets generated by the Human Pancreas Analysis Program.

Type 1 and Type 2 diabetes are distinct genetic diseases of the pancreas which are defined by the abnormal level of blood glucose. Understanding the initial molecular perturbations that occur during the pathogenesis of diabetes is of critical importance in understanding these disorders. The inability to biopsy the human pancreas of living donors hampers insights into early detection, as the majority of diabetes studies have been performed on peripheral leukocytes from the blood, which is not the site of pathogenesis. Therefore, efforts have been made by various teams including the Human Pancreas Analysis Program (HPAP) to collect pancreatic tissues from deceased organ donors with different clinical phenotypes. HPAP is designed to define the molecular pathogenesis of islet dysfunction by generating detailed datasets of functional, cellular, and molecular information in pancreatic tissues of clinically well-defined organ donors with Type 1 and Type 2 diabetes. Moreover, data generated by HPAP continously become available through a centralized database, PANC-DB, thus enabling the diabetes research community to access these multi-dimensional data prepublication. Here, we present the computational workflow for single-cell RNA-seq data analysis of 258,379 high-quality cells from the pancreatic islets of 67 human donors generated by HPAP, the largest existing scRNA-seq dataset of human pancreatic tissues. We report various computational steps including preprocessing, doublet removal, clustering and cell type annotation across single-cell RNA-seq data from islets of four distintct classes of organ donors, i.e. non-diabetic control, autoantibody positive but normoglycemic, Type 1 diabetic, and Type 2 diabetic individuals. Moreover, we present an interactive tool, called CellxGene developed by the Chan Zuckerberg initiative, to navigate these high-dimensional datasets. Our data and interactive tools provide a reliable reference for singlecell pancreatic islet biology studies, especially diabetes-related conditions.

A LAMP sequencing approach for high-throughput co-detection of SARS-CoV-2 and influenza virus in human saliva.

The COVID-19 pandemic has created an urgent need for rapid, effective, and low-cost SARS-CoV-2 diagnostic testing. Here, we describe COV-ID, an approach that combines RT-LAMP with deep sequencing to detect SARS-CoV-2 in unprocessed human saliva with a low limit of detection (5-10 virions). Based on a multi-dimensional barcoding strategy, COV-ID can be used to test thousands of samples overnight in a single sequencing run with limited labor and laboratory equipment. The sequencing-based readout allows COV-ID to detect multiple amplicons simultaneously, including key controls such as host transcripts and artificial spike-ins, as well as multiple pathogens. Here, we demonstrate this flexibility by simultaneous detection of 4 amplicons in contrived saliva samples: SARS-CoV-2, influenza A, human STATHERIN, and an artificial SARS calibration standard. The approach was validated on clinical saliva samples, where it showed excellent agreement with RT-qPCR. COV-ID can also be performed directly on saliva absorbed on filter paper, simplifying collection logistics and sample handling.

Single-cell multi-omics analysis of human pancreatic islets reveals novel cellular states in type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease in which immune cells destroy insulin-producing beta cells. The aetiology of this complex disease is dependent on the interplay of multiple heterogeneous cell types in the pancreatic environment. Here, we provide a single-cell atlas of pancreatic islets of 24 T1D, autoantibody-positive and nondiabetic organ donors across multiple quantitative modalities including ~80,000 cells using single-cell transcriptomics, ~7,000,000 cells using cytometry by time of flight and ~1,000,000 cells using in situ imaging mass cytometry. We develop an advanced integrative analytical strategy to assess pancreatic islets and identify canonical cell types. We show that a subset of exocrine ductal cells acquires a signature of tolerogenic dendritic cells in an apparent attempt at immune suppression in T1D donors. Our multimodal analyses delineate cell types and processes that may contribute to T1D immunopathogenesis and provide an integrative procedure for exploration and discovery of human pancreatic function.

Evaluating whole-genome expression differences in idiopathic and diabetic adhesive capsulitis.

BACKGROUND: Diabetic patients have a greater incidence of adhesive capsulitis (AC) and a more protracted disease course than patients with idiopathic AC. The purpose of this study was to compare gene expression differences between AC with diabetes mellitus and AC without diabetes mellitus. METHODS: Shoulder capsule samples were prospectively obtained from diabetic or nondiabetic patients who presented with shoulder dysfunction and underwent arthroscopy (N = 16). Shoulder samples of AC with and without diabetes (n = 8) were compared with normal shoulder samples with and without diabetes as the control group (n = 8). Shoulder capsule samples were subjected to whole-transcriptome RNA sequencing, and differential expression was analyzed with EdgeR. Only genes with a false discovery rate < 5% were included for further functional enrichment analysis. RESULTS: The sample population had a mean age of 47 years (range, 24-62 years), and the mean hemoglobin A1c level for nondiabetic and diabetic patients was 5.18% and 8.71%, respectively. RNA-sequencing analysis revealed that 66 genes were differentially expressed between diabetic patients and nondiabetic patients with AC whereas only 3 genes were differentially expressed when control patients with and without diabetes were compared. Furthermore, 286 genes were differentially expressed in idiopathic AC patients, and 61 genes were differentially expressed in diabetic AC patients. On gene clustering analysis, idiopathic AC was enriched with multiple structural and muscle-related pathways, such as muscle filament sliding, whereas diabetic AC included a greater number of hormonal and inflammatory signaling pathways, such as cellular response to corticotropin-releasing factor. CONCLUSIONS: Whole-transcriptome expression profiles demonstrate a fundamentally different underlying pathophysiology when comparing diabetic AC with idiopathic AC, suggesting that these conditions are distinct clinical entities. The new genes expressed explain the differences in the disease course and suggest new therapeutic targets that may lead to different treatment paradigms in these 2 subsets.

Single-cell analysis of the human pancreas in type 2 diabetes using multi-spectral imaging mass cytometry.

Type 2 diabetes mellitus (T2D) is a chronic age-related disorder characterized by hyperglycemia due to the failure of pancreatic beta cells to compensate for increased insulin demand. Despite decades of research, the pathogenic mechanisms underlying T2D remain poorly defined. Here, we use imaging mass cytometry (IMC) with a panel of 34 antibodies to simultaneously quantify markers of pancreatic exocrine, islet, and immune cells and stromal components. We analyze over 2 million cells from 16 pancreata obtained from donors with T2D and 13 pancreata from age-similar non-diabetic controls. In the T2D pancreata, we observe significant alterations in islet architecture, endocrine cell composition, and immune cell constituents. Thus, both HLA-DR-positive CD8 T cells and macrophages are enriched intra-islet in the T2D pancreas. These efforts demonstrate the utility of IMC for investigating complex events at the cellular level in order to provide insights into the pathophysiology of T2D.

CAMPAREE: a robust and configurable RNA expression simulator.

BACKGROUND: The accurate interpretation of RNA-Seq data presents a moving target as scientists continue to introduce new experimental techniques and analysis algorithms. Simulated datasets are an invaluable tool to accurately assess the performance of RNA-Seq analysis methods. However, existing RNA-Seq simulators focus on modeling the technical biases and artifacts of sequencing, rather than on simulating the original RNA samples. A first step in simulating RNA-Seq is to simulate RNA. RESULTS: To fill this need, we developed the Configurable And Modular Program Allowing RNA Expression Emulation (CAMPAREE), a simulator using empirical data to simulate diploid RNA samples at the level of individual molecules. We demonstrated CAMPAREE's use for generating idealized coverage plots from real data, and for adding the ability to generate allele-specific data to existing RNA-Seq simulators that do not natively support this feature. CONCLUSIONS: Separating input sample modeling from library preparation/sequencing offers added flexibility for both users and developers to mix-and-match different sample and sequencing simulators to suit their specific needs. Furthermore, the ability to maintain sample and sequencing simulators independently provides greater agility to incorporate new biological findings about transcriptomics and new developments in sequencing technologies. Additionally, by simulating at the level of individual molecules, CAMPAREE has the potential to model molecules transcribed from the same genes as a heterogeneous population of transcripts with different states of degradation and processing (splicing, editing, etc.). CAMPAREE was developed in Python, is open source, and freely available at https://github.com/itmat/CAMPAREE .

Highly Multiplexed Image Analysis of Intestinal Tissue Sections in Patients With Inflammatory Bowel Disease.

BACKGROUND & AIMS: Significant progress has been made since the first report of inflammatory bowel disease (IBD) in 1859, after decades of research that have contributed to the understanding of the genetic and environmental factors involved in IBD pathogenesis. Today, a range of treatments is available for directed therapy, mostly targeting the overactive immune response. However, the mechanisms by which the immune system contributes to disease pathogenesis and progression are not fully understood. One challenge hindering IBD research is the heterogeneous nature of the disease and the lack of understanding of how immune cells interact with one another in the gut mucosa. Introduction of a technology that enables expansive characterization of the inflammatory environment of human IBD tissues may address this gap in knowledge. METHODS: We used the imaging mass cytometry platform to perform highly multiplex image analysis of IBD and healthy deidentified intestine sections (6 Crohn's disease compared to 6 control ileum; 6 ulcerative colitis compared to 6 control colon). The acquired images were graded for inflammation severity by analysis of adjacent H&E tissue sections. We assigned more than 300,000 cells to unique cell types and performed analyses of tissue integrity, epithelial activity, and immune cell composition. RESULTS: The intestinal epithelia of patients with IBD exhibited increased proliferation rates and expression of HLA-DR compared to control tissues, and both features were positively correlated with the severity of inflammation. The neighborhood analysis determined enrichment of regulatory T cell interactions with CD68+ macrophages, CD4+ T cells, and plasma cells in both forms of IBD, whereas activated lysozyme C+ macrophages were preferred regulatory T cell neighbors in Crohn's disease but not ulcerative colitis. CONCLUSIONS: Altogether, our study shows the power of imaging mass cytometry and its ability to both quantify immune cell types and characterize their spatial interactions within the inflammatory environment by a single analysis platform.

FoxA-dependent demethylation of DNA initiates epigenetic memory of cellular identity.

Tissue-specific DNA methylation patterns are created by transcription factors that recruit methylation and demethylation enzymes to cis-regulatory elements. To date, it is not known whether transcription factors are needed to continuously maintain methylation profiles in development and mature tissues or whether they only establish these marks during organ development. We queried the role of the pioneer factor FoxA in generating hypomethylated DNA at liver enhancers. We discovered a set of FoxA-binding sites that undergo regional, FoxA-dependent demethylation during organ development. Conditional ablation of FoxA genes in the adult liver demonstrated that continued FoxA presence was not required to maintain the hypomethylated state, even when massive cell proliferation was induced. This study provides strong evidence for the stable, epigenetic nature of tissue-specific DNA methylation patterns directed by lineage-determining transcription factors during organ development.

Highly multiplexed 2-dimensional imaging mass cytometry analysis of HBV-infected liver.

Studies of human hepatitis B virus (HBV) immune pathogenesis are hampered by limited access to liver tissues and technologies for detailed analyses. Here, utilizing imaging mass cytometry (IMC) to simultaneously detect 30 immune, viral, and structural markers in liver biopsies from patients with hepatitis B e antigen+ (HBeAg+) chronic hepatitis B, we provide potentially novel comprehensive visualization, quantitation, and phenotypic characterizations of hepatic adaptive and innate immune subsets that correlated with hepatocellular injury, histological fibrosis, and age. We further show marked correlations between adaptive and innate immune cell frequencies and phenotype, highlighting complex immune interactions within the hepatic microenvironment with relevance to HBV pathogenesis.

Paternal Exercise Improves the Metabolic Health of Offspring via Epigenetic Modulation of the Germline.

BACKGROUND/AIMS: Epigenetic regulation is considered the main molecular mechanism underlying the developmental origin of health and disease's (DOHAD) hypothesis. Previous studies that have investigated the role of paternal exercise on the metabolic health of the offspring did not control for the amount and intensity of the training or possible effects of adaptation to exercise and produced conflicting results regarding the benefits of parental exercise to the next generation. We employed a precisely regulated exercise regimen to study the transgenerational inheritance of improved metabolic health. METHODS: We subjected male mice to a well-controlled exercise -training program to investigate the effects of paternal exercise on glucose tolerance and insulin sensitivity in their adult progeny. To investigate the molecular mechanisms of epigenetic inheritance, we determined chromatin markers in the skeletal muscle of the offspring and the paternal sperm. RESULTS: Offspring of trained male mice exhibited improved glucose homeostasis and insulin sensitivity. Paternal exercise modulated the DNA methylation profile of PI3Kca and the imprinted H19/Igf2 locus at specific differentially methylated regions (DMRs) in the skeletal muscle of the offspring, which affected their gene expression. Remarkably, a similar DNA methylation profile at the PI3Kca, H19, and Igf2 genes was present in the progenitor sperm indicating that exercise-induced epigenetic changes that occurred during germ cell development contributed to transgenerational transmission. CONCLUSION: Paternal exercise might be considered as a strategy that could promote metabolic health in the offspring as the benefits can be inherited transgenerationally.

Single-cell transcriptomics of human islet ontogeny defines the molecular basis of ß-cell dedifferentiation in T2D.

OBJECTIVE: Dedifferentiation of pancreatic ß-cells may reduce islet function in type 2 diabetes (T2D). However, the prevalence, plasticity and functional consequences of this cellular state remain unknown. METHODS: We employed single-cell RNAseq to detail the maturation program of α- and ß-cells during human ontogeny. We also compared islets from non-diabetic and T2D individuals. RESULTS: Both α- and ß-cells mature in part by repressing non-endocrine genes; however, α-cells retain hallmarks of an immature state, while ß-cells attain a full ß-cell specific gene expression program. In islets from T2D donors, both α- and ß-cells have a less mature expression profile, de-repressing the juvenile genetic program and exocrine genes and increasing expression of exocytosis, inflammation and stress response signalling pathways. These changes are consistent with the increased proportion of ß-cells displaying suboptimal function observed in T2D islets. CONCLUSIONS: These findings provide new insights into the molecular program underlying islet cell maturation during human ontogeny and the loss of transcriptomic maturity that occurs in islets of type 2 diabetics.

A negative reciprocal regulatory axis between cyclin D1 and HNF4α modulates cell cycle progression and metabolism in the liver.

Hepatocyte nuclear factor 4α (HNF4α) is a master regulator of liver function and a tumor suppressor in hepatocellular carcinoma (HCC). In this study, we explore the reciprocal negative regulation of HNF4α and cyclin D1, a key cell cycle protein in the liver. Transcriptomic analysis of cultured hepatocyte and HCC cells found that cyclin D1 knockdown induced the expression of a large network of HNF4α-regulated genes. Chromatin immunoprecipitation-sequencing (ChIP-seq) demonstrated that cyclin D1 inhibits the binding of HNF4α to thousands of targets in the liver, thereby diminishing the expression of associated genes that regulate diverse metabolic activities. Conversely, acute HNF4α deletion in the liver induces cyclin D1 and hepatocyte cell cycle progression; concurrent cyclin D1 ablation blocked this proliferation, suggesting that HNF4α maintains proliferative quiescence in the liver, at least, in part, via repression of cyclin D1. Acute cyclin D1 deletion in the regenerating liver markedly inhibited hepatocyte proliferation after partial hepatectomy, confirming its pivotal role in cell cycle progression in this in vivo model, and enhanced the expression of HNF4α target proteins. Hepatocyte cyclin D1 gene ablation caused markedly increased postprandial liver glycogen levels (in a HNF4α-dependent fashion), indicating that the cyclin D1-HNF4α axis regulates glucose metabolism in response to feeding. In AML12 hepatocytes, cyclin D1 depletion led to increased glucose uptake, which was negated if HNF4α was depleted simultaneously, and markedly elevated glycogen synthesis. To summarize, mutual repression by cyclin D1 and HNF4α coordinately controls the cell cycle machinery and metabolism in the liver.

A High-Content Screen Identifies MicroRNAs That Regulate Liver Repopulation After Injury in Mice.

BACKGROUND & AIMS: Liver regeneration is impaired in mice with hepatocyte-specific deficiencies in microRNA (miRNA) processing, but it is not clear which miRNAs regulate this process. We developed a high-throughput screen to identify miRNAs that regulate hepatocyte repopulation after toxic liver injury using fumarylacetoacetate hydrolase-deficient mice. METHODS: We constructed plasmid pools encoding more than 30,000 tough decoy miRNA inhibitors (hairpin nucleic acids designed to specifically inhibit interactions between miRNAs and their targets) to target hepatocyte miRNAs in a pairwise manner. The plasmid libraries were delivered to hepatocytes in fumarylacetoacetate hydrolase-deficient mice at the time of liver injury via hydrodynamic tail-vein injection. Integrated transgene-containing transposons were quantified after liver repopulation via high-throughput sequencing. Changes in polysome-bound transcripts after miRNA inhibition were determined using translating ribosome affinity purification followed by high-throughput sequencing. RESULTS: Analyses of tough decoy abundance in hepatocyte genomic DNA and input plasmid pools identified several thousand miRNA inhibitors that were significantly depleted or increased after repopulation. We classified a subset of miRNA binding sites as those that have strong effects on liver repopulation, implicating the targeted hepatocyte miRNAs as regulators of this process. We then generated a high-content map of pairwise interactions between 171 miRNA-binding sites and identified synergistic and redundant effects. CONCLUSIONS: We developed a screen to identify miRNAs that regulate liver repopulation after injury in live mice.

miRNA142-3p targets Tet2 and impairs Treg differentiation and stability in models of type 1 diabetes.

In type 1 diabetes, the appearance of islet autoantibodies indicates the onset of islet autoimmunity, often many years before clinical symptoms arise. While T cells play a major role in the destruction of pancreatic beta cells, molecular underpinnings promoting aberrant T cell activation remain poorly understood. Here, we show that during islet autoimmunity an miR142-3p/Tet2/Foxp3 axis interferes with the efficient induction of regulatory T (Treg) cells, resulting in impaired Treg stability in mouse and human. Specifically, we demonstrate that miR142-3p is induced in islet autoimmunity and that its inhibition enhances Treg induction and stability, leading to reduced islet autoimmunity in non-obese diabetic mice. Using various cellular and molecular approaches we identify Tet2 as a direct target of miR142-3p, thereby linking high miR142-3p levels to epigenetic remodeling in Tregs. These findings offer a mechanistic model where during islet autoimmunity miR142-3p/Tet2-mediated Treg instability contributes to autoimmune activation and progression.

Comparative evaluation of RNA-Seq library preparation methods for strand-specificity and low input.

Library preparation is a key step in sequencing. For RNA sequencing there are advantages to both strand specificity and working with minute starting material, yet until recently there was no kit available enabling both. The Illumina TruSeq stranded mRNA Sample Preparation kit (TruSeq) requires abundant starting material while the Takara Bio SMART-Seq v4 Ultra Low Input RNA kit (V4) sacrifices strand specificity. The SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Pico) by Takara Bio claims to overcome these limitations. Comparative evaluation of these kits is important for selecting the appropriate protocol. We compared the three kits in a realistic differential expression analysis. We prepared and sequenced samples from two experimental conditions of biological interest with each of the three kits. We report differences between the kits at the level of differential gene expression; for example, the Pico kit results in 55% fewer differentially expressed genes than TruSeq. Nevertheless, the agreement of the observed enriched pathways suggests that comparable functional results can be obtained. In summary we conclude that the Pico kit sufficiently reproduces the results of the other kits at the level of pathway analysis while providing a combination of options that is not available in the other kits.