High-throughput imaging of mRNA at the single-cell level in human primary immune cells.

Measurement of gene expression at the single-cell level has advanced the study of transcriptional regulation programs in healthy and disease states. In particular, single-cell approaches have shed light on the high level of transcriptional heterogeneity of individual cells, both at baseline and in response to experimental or environmental perturbations. We have developed a method for high-content imaging (HCI)-based quantification of relative changes in transcript abundance at the single-cell level in human primary immune cells and have validated its performance under multiple experimental conditions to demonstrate its general applicability. This method, named hcHCR, combines the sensitivity of the hybridization chain reaction (HCR) for the visualization of RNA in single cells, with the speed, scalability, and reproducibility of HCI. We first tested eight cell attachment substrates for short-term culture of primary human B cells, T cells, monocytes, or neutrophils. We then miniaturized HCR in 384-well format and documented the ability of the method to detect changes in transcript abundance at the single-cell level in thousands of cells for each experimental condition by HCI. Furthermore, we demonstrated the feasibility of multiplexing gene expression measurements by simultaneously assaying the abundance of three transcripts per cell at baseline and in response to an experimental stimulus. Finally, we tested the robustness of the assay to technical and biological variation. We anticipate that hcHCR will be suitable for low- to medium-throughput chemical or functional genomics screens in primary human cells, with the possibility of performing screens on cells obtained from patients with a specific disease.

Single-Cell Analysis Reveals the Range of Transcriptional States of Circulating Human Neutrophils.

Neutrophils are the most abundant leukocytes in human blood and are essential components of innate immunity. Until recently, neutrophils were considered homogeneous and transcriptionally inactive cells, but both concepts are being challenged. Single-cell RNA sequencing (scRNA-seq) offers an unbiased view of cells along a continuum of transcriptional states. However, the use of scRNA-seq to characterize neutrophils has proven technically difficult, explaining in part the paucity of published single-cell data on neutrophils. We have found that modifications to the data analysis pipeline, rather than to the existing scRNA-seq chemistries, can significantly increase the detection of human neutrophils in scRNA-seq. We have then applied a modified pipeline to the study of human peripheral blood neutrophils. Our findings indicate that circulating human neutrophils are transcriptionally heterogeneous cells, which can be classified into one of four transcriptional clusters that are reproducible among healthy human subjects. We demonstrate that peripheral blood neutrophils shift from relatively immature (Nh0) cells, through a transitional phenotype (Nh1), into one of two end points defined by either relative transcriptional inactivity (Nh2) or high expression of type I IFN-inducible genes (Nh3). Transitions among states are characterized by the expression of specific transcription factors. By simultaneously measuring surface proteins and intracellular transcripts at the single-cell level, we show that these transcriptional subsets are independent of the canonical surface proteins that are commonly used to define and characterize human neutrophils. These findings provide a new view of human neutrophil heterogeneity, with potential implications for the characterization of neutrophils in health and disease.

Sex differences in neutrophil biology modulate response to type I interferons and immunometabolism.

Differences between female and male immunity may contribute to variations in response to infections and predisposition to autoimmunity. We previously reported that neutrophils from reproductive-age males are more immature and less activated than their female counterparts. To further characterize the mechanisms that drive differential neutrophil phenotypes, we performed RNA sequencing on circulating neutrophils from healthy adult females and males. Female neutrophils displayed significant up-regulation of type I IFN (IFN)-stimulated genes (ISGs). Single-cell RNA-sequencing analysis indicated that these differences are neutrophil specific, driven by a distinct neutrophil subset and related to maturation status. Neutrophil hyperresponsiveness to type I IFNs promoted enhanced responses to Toll-like receptor agonists. Neutrophils from young adult males had significantly increased mitochondrial metabolism compared to those from females and this was modulated by estradiol. Assessment of ISGs and neutrophil maturation genes in Klinefelter syndrome (47, XXY) males and in prepubescent children supported that differences in neutrophil phenotype between adult male and female neutrophils are hormonally driven and not explained by X chromosome gene dosage. Our results indicate that there are distinct sex differences in neutrophil biology related to responses to type I IFNs, immunometabolism, and maturation status that may have prominent functional and pathogenic implications.

Glucocorticoid-induced eosinopenia results from CXCR4-dependent bone marrow migration.

Glucocorticoids are considered first-line therapy in a variety of eosinophilic disorders. They lead to a transient, profound decrease in circulating human eosinophils within hours of administration. The phenomenon of glucocorticoid-induced eosinopenia has been the basis for the use of glucocorticoids in eosinophilic disorders, and it has intrigued clinicians for 7 decades, yet its mechanism remains unexplained. To investigate, we first studied the response of circulating eosinophils to in vivo glucocorticoid administration in 3 species and found that the response in rhesus macaques, but not in mice, closely resembled that in humans. We then developed an isolation technique to purify rhesus macaque eosinophils from peripheral blood and performed live tracking of zirconium-89-oxine-labeled eosinophils by serial positron emission tomography/computed tomography imaging, before and after administration of glucocorticoids. Glucocorticoids induced rapid bone marrow homing of eosinophils. The kinetics of glucocorticoid-induced eosinopenia and bone marrow migration were consistent with those of the induction of the glucocorticoid-responsive chemokine receptor CXCR4, and selective blockade of CXCR4 reduced or eliminated the early glucocorticoid-induced reduction in blood eosinophils. Our results indicate that glucocorticoid-induced eosinopenia results from CXCR4-dependent migration of eosinophils to the bone marrow. These findings provide insight into the mechanism of action of glucocorticoids in eosinophilic disorders, with implications for the study of glucocorticoid resistance and the development of more targeted therapies. The human study was registered at ClinicalTrials.gov as #NCT02798523.

A Deep Learning Pipeline for Nucleus Segmentation.

Deep learning is rapidly becoming the technique of choice for automated segmentation of nuclei in biological image analysis workflows. In order to evaluate the feasibility of training nuclear segmentation models on small, custom annotated image datasets that have been augmented, we have designed a computational pipeline to systematically compare different nuclear segmentation model architectures and model training strategies. Using this approach, we demonstrate that transfer learning and tuning of training parameters, such as the composition, size, and preprocessing of the training image dataset, can lead to robust nuclear segmentation models, which match, and often exceed, the performance of existing, off-the-shelf deep learning models pretrained on large image datasets. We envision a practical scenario where deep learning nuclear segmentation models trained in this way can be shared across a laboratory, facility, or institution, and continuously improved by training them on progressively larger and varied image datasets. Our work provides computational tools and a practical framework for deep learning-based biological image segmentation using small annotated image datasets. Published [2020]. This article is a U.S. Government work and is in the public domain in the USA.

hcHCR: High-Throughput Single-Cell Imaging of RNA in Human Primary Immune Cells.

Functional genomics and chemical screens can identify and characterize novel cellular factors regulating signaling networks and chemical tools to modulate their function for the treatment of disease. Screening methods have relied primarily on immortalized and/or transformed cancer cell lines, which can limit the generalization of results to more physiologically relevant systems. Most have also relied on immunofluorescence, or on stably expressed recombinant fluorescent proteins, to detect specific protein markers using high-content imaging readouts. In comparison, high-throughput methods to visualize and measure RNA species have been less explored. To address this, we have adapted an isothermal signal amplification chemistry for RNA FISH known as hybridization chain reaction (HCR) to an automated, high-content imaging assay format. We present a detailed protocol for this technique, which we have named high-content HCR (hcHCR). The protocol focuses on the measurement of changes in mRNA abundance at the single-cell level in human primary cells, but it can be applied to a variety of primary cell types and perturbing agents. We anticipate that hcHCR will be most suitable for low- to medium-throughput screening experiments in which changes in transcript abundance are the desired output measure.

Topical Steroid Withdrawal is a Targetable Excess of Mitochondrial NAD.

Background: Topical corticosteroids (TCS) are first-line therapies for numerous skin conditions. Topical Steroid Withdrawal (TSW) is a controversial diagnosis advocated by patients with prolonged TCS exposure who report severe systemic reactions upon treatment cessation. However, to date there have been no systematic clinical or mechanistic studies to distinguish TSW from other eczematous disorders. Methods: A re-analysis of a previous survey with eczematous skin disease was performed to evaluate potential TSW distinguishing symptoms. We subsequently conducted a pilot study of 16 patients fitting the proposed diagnostic criteria. We then performed: tissue metabolomics, transcriptomics, and immunostaining on skin biopsies; serum metabolomics and cytokine assessments; shotgun metagenomics on microbiome skin swabs; genome sequencing; followed by functional, mechanistic studies using human skin cell lines and mice. Results: Clinically distinct TSW symptoms included burning, flushing, and thermodysregulation. Metabolomics and transcriptomics both implicated elevated NAD+ oxidation stemming from increased expression of mitochondrial complex I and conversion of tryptophan into kynurenine metabolites. These abnormalities were induced by glucocorticoid exposure both in vitro and in a cohort of healthy controls (N=19) exposed to TCS. Targeting complex I via either metformin or the herbal compound berberine improved outcomes in both cell culture and in an open-label case series for patients with TSW. Conclusion: Taken together, our results suggest that TSW has a distinct dermatopathology. While future studies are needed to validate these results in larger cohorts, this work provides the first mechanistic evaluation into TSW pathology, and offers insights into clinical identification, pharmacogenomic candidates, and directed therapeutic strategies.

GCgx: transcriptome-wide exploration of the response to glucocorticoids.

Glucocorticoids are the cornerstone of immunosuppressive and anti-inflammatory therapy in humans, yet the mechanisms of glucocorticoid immunoregulation and toxicity remain unclear. The response to glucocorticoids is highly cell type-dependent, so translating results from different experimental systems into a better understanding of glucocorticoid effects in humans would benefit from rapid access to high-quality data on the response to glucocorticoids by different cell types. We introduce GCgx, a web application that allows investigators to quickly visualize changes in transcript abundance in response to glucocorticoids in a variety of cells and species. The tool is designed to grow by the addition of datasets based on input from the user community. GCgx is implemented in R and HTML and packaged as a Docker image. The tool and its source code are publicly available.

Immune regulation by glucocorticoids can be linked to cell type-dependent transcriptional responses.

Glucocorticoids remain the most widely used immunosuppressive and anti-inflammatory drugs, yet substantial gaps exist in our understanding of glucocorticoid-mediated immunoregulation. To address this, we generated a pathway-level map of the transcriptional effects of glucocorticoids on nine primary human cell types. This analysis revealed that the response to glucocorticoids is highly cell type dependent, in terms of the individual genes and pathways affected, as well as the magnitude and direction of transcriptional regulation. Based on these data and given their importance in autoimmunity, we conducted functional studies with B cells. We found that glucocorticoids impair upstream B cell receptor and Toll-like receptor 7 signaling, reduce transcriptional output from the three immunoglobulin loci, and promote significant up-regulation of the genes encoding the immunomodulatory cytokine IL-10 and the terminal-differentiation factor BLIMP-1. These findings provide new mechanistic understanding of glucocorticoid action and emphasize the multifactorial, cell-specific effects of these drugs, with potential implications for designing more selective immunoregulatory therapies.

Transcript- and protein-level analyses of the response of human eosinophils to glucocorticoids.

Glucocorticoids are first-line agents for the treatment of many eosinophil-associated disorders; however, their effects on human eosinophils remain poorly understood. To gain an unbiased, genome-wide view of the early transcriptional effects of glucocorticoids on human eosinophils in vivo, RNA sequencing was performed on purified blood eosinophils obtained before and 30, 60, and 120 minutes after administration of a single dose of oral prednisone (1 mg/kg) to three unrelated healthy subjects with hypereosinophilia of unknown significance. The resulting dataset is of high quality and suitable for differential expression analysis. Flow cytometry and qPCR were then performed on three additional cohorts of human subjects, to validate the key findings at the transcript and protein levels. The resulting datasets provide a resource for understanding the response of circulating human eosinophils to glucocorticoid administration.

Postnatal epigenetic regulation of intestinal stem cells requires DNA methylation and is guided by the microbiome.

BACKGROUND: DNA methylation is an epigenetic mechanism central to development and maintenance of complex mammalian tissues, but our understanding of its role in intestinal development is limited. RESULTS: We use whole genome bisulfite sequencing, and find that differentiation of mouse colonic intestinal stem cells to intestinal epithelium is not associated with major changes in DNA methylation. However, we detect extensive dynamic epigenetic changes in intestinal stem cells and their progeny during the suckling period, suggesting postnatal epigenetic development in this stem cell population. We find that postnatal DNA methylation increases at 3' CpG islands (CGIs) correlate with transcriptional activation of glycosylation genes responsible for intestinal maturation. To directly test whether 3' CGI methylation regulates transcription, we conditionally disrupted two major DNA methyltransferases, Dnmt1 or Dnmt3a, in fetal and adult intestine. Deficiency of Dnmt1 causes severe intestinal abnormalities in neonates and disrupts crypt homeostasis in adults, whereas Dnmt3a loss was compatible with intestinal development. These studies reveal that 3' CGI methylation is functionally involved in the regulation of transcriptional activation in vivo, and that Dnmt1 is a critical regulator of postnatal epigenetic changes in intestinal stem cells. Finally, we show that postnatal 3' CGI methylation and associated gene activation in intestinal epithelial cells are significantly altered by germ-free conditions. CONCLUSIONS: Our results demonstrate that the suckling period is critical for epigenetic development of intestinal stem cells, with potential important implications for lifelong gut health, and that the gut microbiome guides and/or facilitates these postnatal epigenetic processes.

Targeted p16(Ink4a) epimutation causes tumorigenesis and reduces survival in mice.

Cancer has long been viewed as a genetic disease; however, epigenetic silencing as the result of aberrant promoter DNA methylation is frequently associated with cancer development, suggesting an epigenetic component to the disease. Nonetheless, it has remained unclear whether an epimutation (an aberrant change in epigenetic regulation) can induce tumorigenesis. Here, we exploited a functionally validated cis-acting regulatory element and devised a strategy to induce developmentally regulated genomic targeting of DNA methylation. We used this system to target DNA methylation within the p16(Ink4a) promoter in mice in vivo. Engineered p16(Ink4a) promoter hypermethylation led to transcriptional suppression in somatic tissues during aging and increased the incidence of spontaneous cancers in these mice. Further, mice carrying a germline p16(Ink4a) mutation in one allele and a somatic epimutation in the other had accelerated tumor onset and substantially shortened tumor-free survival. Taken together, these results provide direct functional evidence that p16(Ink4a) epimutation drives tumor formation and malignant progression and validate a targeted methylation approach to epigenetic engineering.

Developmentally programmed 3' CpG island methylation confers tissue- and cell-type-specific transcriptional activation.

During development, a small but significant number of CpG islands (CGIs) become methylated. The timing of developmentally programmed CGI methylation and associated mechanisms of transcriptional regulation during cellular differentiation, however, remain poorly characterized. Here, we used genome-wide DNA methylation microarrays to identify epigenetic changes during human embryonic stem cell (hESC) differentiation. We discovered a group of CGIs associated with developmental genes that gain methylation after hESCs differentiate. Conversely, erasure of methylation was observed at the identified CGIs during subsequent reprogramming to induced pluripotent stem cells (iPSCs), further supporting a functional role for the CGI methylation. Both global gene expression profiling and quantitative reverse transcription-PCR (RT-PCR) validation indicated opposing effects of CGI methylation in transcriptional regulation during differentiation, with promoter CGI methylation repressing and 3' CGI methylation activating transcription. By studying diverse human tissues and mouse models, we further confirmed that developmentally programmed 3' CGI methylation confers tissue- and cell-type-specific gene activation in vivo. Importantly, luciferase reporter assays provided evidence that 3' CGI methylation regulates transcriptional activation via a CTCF-dependent enhancer-blocking mechanism. These findings expand the classic view of mammalian CGI methylation as a mechanism for transcriptional silencing and indicate a functional role for 3' CGI methylation in developmental gene regulation.