Pooled multicolour tagging for visualizing subcellular protein dynamics

Imaging-based methods are widely used for studying the subcellular localization of proteins in living cells. While routine for individual proteins, global monitoring of protein dynamics following perturbation typically relies on arrayed panels of fluorescently tagged cell lines, limiting throughput and scalability. Here, we describe a strategy that combines high-throughput microscopy, computer vision and machine learning to detect perturbation-induced changes in multicolour tagged visual proteomics cell (vpCell) pools. We use genome-wide and cancer-focused intron-targeting sgRNA libraries to generate vpCell pools and a large, arrayed collection of clones each expressing two different endogenously tagged fluorescent proteins. Individual clones can be identified in vpCell pools by image analysis using the localization patterns and expression level of the tagged proteins as visual barcodes, enabling simultaneous live-cell monitoring of large sets of proteins. To demonstrate broad applicability and scale, we test the effects of antiproliferative compounds on a pool with cancer-related proteins, on which we identify widespread protein localization changes and new inhibitors of the nuclear import/export machinery. The time-resolved characterization of changes in subcellular localization and abundance of proteins upon perturbation in a pooled format highlights the power of the vpCell approach for drug discovery and mechanism-of-action studies.

Transcriptomic signatures of progressive and regressive liver fibrosis and portal hypertension

Persistent liver injury triggers a fibrogenic program that causes pathologic remodeling of the hepatic microenvironment (i.e., liver fibrosis) and portal hypertension. The dynamics of gene regulation during liver disease progression and early regression remain understudied. Here, we generated hepatic transcriptome profiles in two well-established liver disease models at peak fibrosis and during spontaneous regression after the removal of the inducing agents. We linked the dynamics of key disease readouts, such as portal pressure, collagen area, and transaminase levels, to differentially expressed genes, enabling the identification of transcriptomic signatures of progressive vs. regressive liver fibrosis and portal hypertension. These candidate biomarkers (e.g., Tcf4, Mmp7, Trem2, Spp1, Scube1, Islr) were validated in RNA sequencing datasets of patients with cirrhosis and portal hypertension, and those cured from hepatitis C infection. Finally, deconvolution identified major cell types and suggested an association of macrophage and portal hepatocyte signatures with portal hypertension and fibrosis area.

Mapping human natural killer cell development in pediatric tonsil by imaging mass cytometry and high-resolution microscopy

Natural killer (NK) cells develop from CD34+ progenitors in a stage-specific manner defined by changes in cell surface receptor expression and function. Secondary lymphoid tissues, including tonsil, are sites of human NK cell development. Here we present new insights into human NK cell development in pediatric tonsil using cyclic immunofluorescence and imaging mass cytometry. We show that NK cell subset localization and interactions are dependent on NK cell developmental stage and tissue residency. NK cell progenitors are found in the interfollicular domain in proximity to cytokine-expressing stromal cells that promote proliferation and maturation. Mature NK cells are primarily found in the T-cell rich parafollicular domain engaging in cell-cell interactions that differ depending on their stage and tissue residency. The presence of local inflammation results in changes in NK cell interactions, abundance, and localization. This study provides the first comprehensive atlas of human NK cell development in secondary lymphoid tissue.

Epigenetic memory of coronavirus infection in innate immune cells and their progenitors

Inflammation can trigger lasting phenotypes in immune and non-immune cells. Whether and how human infections and associated inflammation can form innate immune memory in hematopoietic stem and progenitor cells (HSPC) has remained unclear. We found that circulating HSPC, enriched from peripheral blood, captured the diversity of bone marrow HSPC, enabling investigation of their epigenomic reprogramming following coronavirus disease 2019 (COVID-19). Alterations in innate immune phenotypes and epigenetic programs of HSPC persisted for months to 1 year following severe COVID-19 and were associated with distinct transcription factor (TF) activities, altered regulation of inflammatory programs, and durable increases in myelopoiesis. HSPC epigenomic alterations were conveyed, through differentiation, to progeny innate immune cells. Early activity of IL-6 contributed to these persistent phenotypes in human COVID-19 and a mouse coronavirus infection model. Epigenetic reprogramming of HSPC may underlie altered immune function following infection and be broadly relevant, especially for millions of COVID-19 survivors.

Spatial omics technologies at multimodal and single cell/subcellular level

Spatial omics technologies enable a deeper understanding of cellular organizations and interactions within a tissue of interest. These assays can identify specific compartments or regions in a tissue with differential transcript or protein abundance, delineate their interactions, and complement other methods in defining cellular phenotypes. A variety of spatial methodologies are being developed and commercialized; however, these techniques differ in spatial resolution, multiplexing capability, scale/throughput, and coverage. Here, we review the current and prospective landscape of single cell to subcellular resolution spatial omics technologies and analysis tools to provide a comprehensive picture for both research and clinical applications.

Unsupervised discovery of tissue architecture in multiplexed imaging

Multiplexed imaging and spatial transcriptomics enable highly resolved spatial characterization of cellular phenotypes, but still largely depend on laborious manual annotation to understand higher-order patterns of tissue organization. As a result, higher-order patterns of tissue organization are poorly understood and not systematically connected to disease pathology or clinical outcomes. To address this gap, we developed an approach called UTAG to identify and quantify microanatomical tissue structures in multiplexed images without human intervention. Our method combines information on cellular phenotypes with the physical proximity of cells to accurately identify organ-specific microanatomical domains in healthy and diseased tissue. We apply our method to various types of images across healthy and disease states to show that it can consistently detect higher-level architectures in human tissues, quantify structural differences between healthy and diseased tissue, and reveal tissue organization patterns at the organ scale.

Persistent alveolar type 2 dysfunction and lung structural derangement in post-acute COVID-19

SARS-CoV-2 infection can manifest as a wide range of respiratory and systemic symptoms well after the acute phase of infection in over 50% of patients. Key questions remain on the long-term effects of infection on tissue pathology in recovered COVID-19 patients. To address these questions we performed multiplexed imaging of post-mortem lung tissue from 12 individuals who died post-acute COVID-19 (PC) and compare them to lung tissue from patients who died during the acute phase of COVID-19, or patients who died with idiopathic pulmonary fibrosis (IPF), and otherwise healthy lung tissue. We find evidence of viral presence in the lung up to 359 days after the acute phase of disease, including in patients with negative nasopharyngeal swab tests. The lung of PC patients are characterized by the accumulation of senescent alveolar type 2 cells, fibrosis with hypervascularization of peribronchial areas and alveolar septa, as the most pronounced pathophysiological features. At the cellular level, lung disease of PC patients, while distinct, shares pathological features with the chronic pulmonary disease of IPF. which may help rationalize interventions for PC patients. Altogether, this study provides an important foundation for the understanding of the long-term effects of SARS-CoV-2 pulmonary infection at the microanatomical, cellular, and molecular level.

Sensing of SARS-CoV-2 by pDCs and their subsequent production of IFN-I contribute to macrophage-induced cytokine storm during COVID-19

Lung-infiltrating macrophages create a marked inflammatory milieu in a subset of patients with COVID-19 by producing a cytokine storm, which correlates with increased lethality. However, these macrophages are largely not infected by SARS-CoV-2, so the mechanism underlying their activation in the lung is unclear. Type I interferons (IFN-I) contribute to protecting the host against SARS-CoV-2 but may also have some deleterious effect, and the source of IFN-I in the lungs of infected patients is not well defined. Plasmacytoid dendritic cells (pDCs), a key cell type involved in antiviral responses, can produce IFN-I in response to SARS-CoV-2. We observed the infiltration of pDCs in the lungs of SARS-CoV-2-infected patients, which correlated with strong IFN-I signaling in lung macrophages. In patients with severe COVID-19, lung macrophages expressed a robust inflammatory signature, which correlated with persistent IFN-I signaling at the single-cell level. Hence, we observed the uncoupling in the kinetics of the infiltration of pDCs in the lungs and the associated IFN-I signature, with the cytokine storm in macrophages. We observed that pDCs were the dominant IFN-α-producing cells in response to the virus in the blood, whereas macrophages produced IFN-α only when in physical contact with infected epithelial cells. We also showed that IFN-α produced by pDCs, after the sensing of SARS-CoV-2 by TLR7, mediated changes in macrophages at both transcriptional and epigenetic levels, which favored their hyperactivation by environmental stimuli. Together, these data indicate that the priming of macrophages can result from the response by pDCs to SARS-CoV-2, leading to macrophage activation in patients with severe COVID-19.

System-wide transcriptome damage and tissue identity loss in COVID-19 patients

The molecular mechanisms underlying the clinical manifestations of coronavirus disease 2019 (COVID-19), and what distinguishes them from common seasonal influenza virus and other lung injury states such as acute respiratory distress syndrome, remain poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match these data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue-compartment-specific damage wrought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, evident as a function of varying viral loads during the clinical course of infection and tissue-type-specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections.

Metabolic and Immune Markers for Precise Monitoring of COVID-19 Severity and Treatment

Deep understanding of the SARS-CoV-2 effects on host molecular pathways is paramount for the discovery of early biomarkers of outcome of coronavirus disease 2019 (COVID-19) and the identification of novel therapeutic targets. In that light, we generated metabolomic data from COVID-19 patient blood using high-throughput targeted nuclear magnetic resonance (NMR) spectroscopy and high-dimensional flow cytometry. We find considerable changes in serum metabolome composition of COVID-19 patients associated with disease severity, and response to tocilizumab treatment. We built a clinically annotated, biologically-interpretable space for precise time-resolved disease monitoring and characterize the temporal dynamics of metabolomic change along the clinical course of COVID-19 patients and in response to therapy. Finally, we leverage joint immuno-metabolic measurements to provide a novel approach for patient stratification and early prediction of severe disease. Our results show that high-dimensional metabolomic and joint immune-metabolic readouts provide rich information content for elucidation of the host's response to infection and empower discovery of novel metabolic-driven therapies, as well as precise and efficient clinical action.

Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects

Background

Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, metadata formats from a data provider are often incompatible with requirements of a processing tool. There is no broadly accepted standard to organize metadata across biological projects and bioinformatics tools, restricting the portability and reusability of both annotated datasets and analysis software.

Results

To address this, we present the Portable Encapsulated Project (PEP) specification, a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many biological samples. In addition to standardization, the PEP specification provides descriptors and modifiers for project-level and sample-level metadata, which improve portability across both computing environments and data processing tools. PEPs include a schema validator framework, allowing formal definition of required metadata attributes for data analysis broadly. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata.

Conclusions

The PEP specification is an important step toward unifying data annotation and processing tools in data-intensive biological research projects. Links to tools and documentation are available at http://pep.databio.org/.

Hyperglycemia Induces Trained Immunity in Macrophages and Their Precursors and Promotes Atherosclerosis

BACKGROUND

Cardiovascular risk in diabetes remains elevated despite glucose-lowering therapies. We hypothesized that hyperglycemia induces trained immunity in macrophages, promoting persistent proatherogenic characteristics.

METHODS

Bone marrow-derived macrophages from control mice and mice with diabetes were grown in physiological glucose (5 mmol/L) and subjected to RNA sequencing (n=6), assay for transposase accessible chromatin sequencing (n=6), and chromatin immunoprecipitation sequencing (n=6) for determination of hyperglycemia-induced trained immunity. Bone marrow transplantation from mice with (n=9) or without (n=6) diabetes into (normoglycemic) Ldlr-/- mice was used to assess its functional significance in vivo. Evidence of hyperglycemia-induced trained immunity was sought in human peripheral blood mononuclear cells from patients with diabetes (n=8) compared with control subjects (n=16) and in human atherosclerotic plaque macrophages excised by laser capture microdissection.

RESULTS

In macrophages, high extracellular glucose promoted proinflammatory gene expression and proatherogenic functional characteristics through glycolysis-dependent mechanisms. Bone marrow-derived macrophages from diabetic mice retained these characteristics, even when cultured in physiological glucose, indicating hyperglycemia-induced trained immunity. Bone marrow transplantation from diabetic mice into (normoglycemic) Ldlr-/- mice increased aortic root atherosclerosis, confirming a disease-relevant and persistent form of trained innate immunity. Integrated assay for transposase accessible chromatin, chromatin immunoprecipitation, and RNA sequencing analyses of hematopoietic stem cells and bone marrow-derived macrophages revealed a proinflammatory priming effect in diabetes. The pattern of open chromatin implicated transcription factor Runt-related transcription factor 1 (Runx1). Similarly, transcriptomes of atherosclerotic plaque macrophages and peripheral leukocytes in patients with type 2 diabetes were enriched for Runx1 targets, consistent with a potential role in human disease. Pharmacological inhibition of Runx1 in vitro inhibited the trained phenotype.

CONCLUSIONS

Hyperglycemia-induced trained immunity may explain why targeting elevated glucose is ineffective in reducing macrovascular risk in diabetes and suggests new targets for disease prevention and therapy.

A molecular single-cell lung atlas of lethal COVID-19

Respiratory failure is the leading cause of death in patients with severe SARS-CoV-2 infection^1,2, but the host response at the lung tissue level is poorly understood. Here we performed single-nucleus RNA sequencing of about 116,000 nuclei from the lungs of nineteen individuals who died of COVID-19 and underwent rapid autopsy and seven control individuals. Integrated analyses identified substantial alterations in cellular composition, transcriptional cell states, and cell-to-cell interactions, thereby providing insight into the biology of lethal COVID-19. The lungs from individuals with COVID-19 were highly inflamed, with dense infiltration of aberrantly activated monocyte-derived macrophages and alveolar macrophages, but had impaired T cell responses. Monocyte/macrophage-derived interleukin-1β and epithelial cell-derived interleukin-6 were unique features of SARS-CoV-2 infection compared to other viral and bacterial causes of pneumonia. Alveolar type 2 cells adopted an inflammation-associated transient progenitor cell state and failed to undergo full transition into alveolar type 1 cells, resulting in impaired lung regeneration. Furthermore, we identified expansion of recently described CTHRC1⁺ pathological fibroblasts³ contributing to rapidly ensuing pulmonary fibrosis in COVID-19. Inference of protein activity and ligand-receptor interactions identified putative drug targets to disrupt deleterious circuits. This atlas enables the dissection of lethal COVID-19, may inform our understanding of long-term complications of COVID-19 survivors, and provides an important resource for therapeutic development.

Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing

Cell atlas projects and high-throughput perturbation screens require single-cell sequencing at a scale that is challenging with current technology. To enable cost-effective single-cell sequencing for millions of individual cells, we developed 'single-cell combinatorial fluidic indexing' (scifi). The scifi-RNA-seq assay combines one-step combinatorial preindexing of entire transcriptomes inside permeabilized cells with subsequent single-cell RNA-seq using microfluidics. Preindexing allows us to load several cells per droplet and computationally demultiplex their individual expression profiles. Thereby, scifi-RNA-seq massively increases the throughput of droplet-based single-cell RNA-seq, and provides a straightforward way of multiplexing thousands of samples in a single experiment. Compared with multiround combinatorial indexing, scifi-RNA-seq provides an easy and efficient workflow. Compared to cell hashing methods, which flag and discard droplets containing more than one cell, scifi-RNA-seq resolves and retains individual transcriptomes from overloaded droplets. We benchmarked scifi-RNA-seq on various human and mouse cell lines, validated it for primary human T cells and applied it in a highly multiplexed CRISPR screen with single-cell transcriptome readout of T cell receptor activation.

Multimodal analysis of cell-free DNA whole-genome sequencing for pediatric cancers with low mutational burden

Sequencing of cell-free DNA in the blood of cancer patients (liquid biopsy) provides attractive opportunities for early diagnosis, assessment of treatment response, and minimally invasive disease monitoring. To unlock liquid biopsy analysis for pediatric tumors with few genetic aberrations, we introduce an integrated genetic/epigenetic analysis method and demonstrate its utility on 241 deep whole-genome sequencing profiles of 95 patients with Ewing sarcoma and 31 patients with other pediatric sarcomas. Our method achieves sensitive detection and classification of circulating tumor DNA in peripheral blood independent of any genetic alterations. Moreover, we benchmark different metrics for cell-free DNA fragmentation analysis, and we introduce the LIQUORICE algorithm for detecting circulating tumor DNA based on cancer-specific chromatin signatures. Finally, we combine several fragmentation-based metrics into an integrated machine learning classifier for liquid biopsy analysis that exploits widespread epigenetic deregulation and is tailored to cancers with low mutation rates. Clinical associations highlight the potential value of cfDNA fragmentation patterns as prognostic biomarkers in Ewing sarcoma. In summary, our study provides a comprehensive analysis of circulating tumor DNA beyond recurrent genetic aberrations, and it renders the benefits of liquid biopsy more readily accessible for childhood cancers.

The spatial landscape of lung pathology during COVID-19 progression

Recent studies have provided insights into the pathology of and immune response to COVID-191-8. However, a thorough investigation of the interplay between infected cells and the immune system at sites of infection has been lacking. Here we use high-parameter imaging mass cytometry9 that targets the expression of 36 proteins to investigate the cellular composition and spatial architecture of acute lung injury in humans (including injuries derived from SARS-CoV-2 infection) at single-cell resolution. These spatially resolved single-cell data unravel the disordered structure of the infected and injured lung, alongside the distribution of extensive immune infiltration. Neutrophil and macrophage infiltration are hallmarks of bacterial pneumonia and COVID-19, respectively. We provide evidence that SARS-CoV-2 infects predominantly alveolar epithelial cells and induces a localized hyperinflammatory cell state that is associated with lung damage. We leverage the temporal range of fatal outcomes of COVID-19 in relation to the onset of symptoms, which reveals increased macrophage extravasation and increased numbers of mesenchymal cells and fibroblasts concomitant with increased proximity between these cell types as the disease progresses-possibly as a result of attempts to repair the damaged lung tissue. Our data enable us to develop a biologically interpretable landscape of lung pathology from a structural, immunological and clinical standpoint. We use this landscape to characterize the pathophysiology of the human lung from its macroscopic presentation to the single-cell level, which provides an important basis for understanding COVID-19 and lung pathology in general.

Profiling of immune dysfunction in COVID-19 patients allows early prediction of disease progression

With a rising incidence of COVID-19-associated morbidity and mortality worldwide, it is critical to elucidate the innate and adaptive immune responses that drive disease severity. We performed longitudinal immune profiling of peripheral blood mononuclear cells from 45 patients and healthy donors. We observed a dynamic immune landscape of innate and adaptive immune cells in disease progression and absolute changes of lymphocyte and myeloid cells in severe versus mild cases or healthy controls. Intubation and death were coupled with selected natural killer cell KIR receptor usage and IgM+ B cells and associated with profound CD4 and CD8 T-cell exhaustion. Pseudo-temporal reconstruction of the hierarchy of disease progression revealed dynamic time changes in the global population recapitulating individual patients and the development of an eight-marker classifier of disease severity. Estimating the effect of clinical progression on the immune response and early assessment of disease progression risks may allow implementation of tailored therapies.

Longitudinal immune profiling of mild and severe COVID-19 reveals innate and adaptive immune dysfunction and provides an early prediction tool for clinical progression

With a rising incidence of COVID-19-associated morbidity and mortality worldwide, it is critical to elucidate the innate and adaptive immune responses that drive disease severity. We performed longitudinal immune profiling of peripheral blood mononuclear cells from 45 patients and healthy donors. We observed a dynamic immune landscape of innate and adaptive immune cells in disease progression and absolute changes of lymphocyte and myeloid cells in severe versus mild cases or healthy controls. Intubation and death were coupled with selected natural killer cell KIR receptor usage and IgM+ B cells and associated with profound CD4 and CD8 T cell exhaustion. Pseudo-temporal reconstruction of the hierarchy of disease progression revealed dynamic time changes in the global population recapitulating individual patients and the development of an eight-marker classifier of disease severity. Estimating the effect of clinical progression on the immune response and early assessment of disease progression risks may allow implementation of tailored therapies.

Structural cells are key regulators of organ-specific immune responses

The mammalian immune system implements a remarkably effective set of mechanisms for fighting pathogens¹. Its main components are haematopoietic immune cells, including myeloid cells that control innate immunity, and lymphoid cells that constitute adaptive immunity². However, immune functions are not unique to haematopoietic cells, and many other cell types display basic mechanisms of pathogen defence^3-5. To advance our understanding of immunology outside the haematopoietic system, here we systematically investigate the regulation of immune genes in the three major types of structural cells: epithelium, endothelium and fibroblasts. We characterize these cell types across twelve organs in mice, using cellular phenotyping, transcriptome sequencing, chromatin accessibility profiling and epigenome mapping. This comprehensive dataset revealed complex immune gene activity and regulation in structural cells. The observed patterns were highly organ-specific and seem to modulate the extensive interactions between structural cells and haematopoietic immune cells. Moreover, we identified an epigenetically encoded immune potential in structural cells under tissue homeostasis, which was triggered in response to systemic viral infection. This study highlights the prevalence and organ-specific complexity of immune gene activity in non-haematopoietic structural cells, and it provides a high-resolution, multi-omics atlas of the epigenetic and transcriptional networks that regulate structural cells in the mouse.

Microbiota-Derived Metabolites Suppress Arthritis by Amplifying Aryl-Hydrocarbon Receptor Activation in Regulatory B Cells

The differentiation of IL-10-producing regulatory B cells (Bregs) in response to gut-microbiota-derived signals supports the maintenance of tolerance. However, whether microbiota-derived metabolites can modulate Breg suppressive function remains unknown. Here, we demonstrate that rheumatoid arthritis (RA) patients and arthritic mice have a reduction in microbial-derived short-chain fatty acids (SCFAs) compared to healthy controls and that in mice, supplementation with the SCFA butyrate reduces arthritis severity. Butyrate supplementation suppresses arthritis in a Breg-dependent manner by increasing the level of the serotonin-derived metabolite 5-Hydroxyindole-3-acetic acid (5-HIAA), which activates the aryl-hydrocarbon receptor (AhR), a newly discovered transcriptional marker for Breg function. Thus, butyrate supplementation via AhR activation controls a molecular program that supports Breg function while inhibiting germinal center (GC) B cell and plasmablast differentiation. Our study demonstrates that butyrate supplementation may serve as a viable therapy for the amelioration of systemic autoimmune disorders.

Chromatin mapping and single-cell immune profiling define the temporal dynamics of ibrutinib response in CLL

The Bruton tyrosine kinase (BTK) inhibitor ibrutinib provides effective treatment for patients with chronic lymphocytic leukemia (CLL), despite extensive heterogeneity in this disease. To define the underlining regulatory dynamics, we analyze high-resolution time courses of ibrutinib treatment in patients with CLL, combining immune-phenotyping, single-cell transcriptome profiling, and chromatin mapping. We identify a consistent regulatory program starting with a sharp decrease of NF-κB binding in CLL cells, which is followed by reduced activity of lineage-defining transcription factors, erosion of CLL cell identity, and acquisition of a quiescence-like gene signature. We observe patient-to-patient variation in the speed of execution of this program, which we exploit to predict patient-specific dynamics in the response to ibrutinib based on the pre-treatment patient samples. In aggregate, our study describes time-dependent cellular, molecular, and regulatory effects for therapeutic inhibition of B cell receptor signaling in CLL, and it establishes a broadly applicable method for epigenome/transcriptome-based treatment monitoring.

Ibrutinib, a Bruton tyrosine kinase inhibitor, provides effective treatment for chronic lymphocytic leukemia (CLL). Here, the authors describe time-dependent molecular changes to malignant cells and to the immune system in patients undergoing ibrutinib therapy, with can be used for therapy monitoring.

Aryl Hydrocarbon Receptor Contributes to the Transcriptional Program of IL-10-Producing Regulatory B Cells

Regulatory B cells (Bregs) play a critical role in the control of autoimmunity and inflammation. IL-10 production is the hallmark for the identification of Bregs. However, the molecular determinants that regulate the transcription of IL-10 and control the Breg developmental program remain unknown. Here, we demonstrate that aryl hydrocarbon receptor (AhR) regulates the differentiation and function of IL-10-producing CD19+CD21hiCD24hiBregs and limits their differentiation into B cells that contribute to inflammation. Chromatin profiling and transcriptome analyses show that loss of AhR in B cells reduces expression of IL-10 by skewing the differentiation of CD19+CD21hiCD24hiB cells into a pro-inflammatory program, under Breg-inducing conditions. B cell AhR-deficient mice develop exacerbated arthritis, show significant reductions in IL-10-producing Bregs and regulatory T cells, and show an increase in T helper (Th) 1 and Th17 cells compared with B cell AhR-sufficient mice. Thus, we identify AhR as a relevant contributor to the transcriptional regulation of Breg differentiation.

Combined chemosensitivity and chromatin profiling prioritizes drug combinations in CLL

The Bruton tyrosine kinase (BTK) inhibitor ibrutinib has substantially improved therapeutic options for chronic lymphocytic leukemia (CLL). Although ibrutinib is not curative, it has a profound effect on CLL cells and may create new pharmacologically exploitable vulnerabilities. To identify such vulnerabilities, we developed a systematic approach that combines epigenome profiling (charting the gene-regulatory basis of cell state) with single-cell chemosensitivity profiling (quantifying cell-type-specific drug response) and bioinformatic data integration. By applying our method to a cohort of matched patient samples collected before and during ibrutinib therapy, we identified characteristic ibrutinib-induced changes that provide a starting point for the rational design of ibrutinib combination therapies. Specifically, we observed and validated preferential sensitivity to proteasome, PLK1, and mTOR inhibitors during ibrutinib treatment. More generally, our study establishes a broadly applicable method for investigating treatment-specific vulnerabilities by integrating the complementary perspectives of epigenetic cell states and phenotypic drug responses in primary patient samples.

Functional Dissection of the Enhancer Repertoire in Human Embryonic Stem Cells

Enhancers are genetic elements that regulate spatiotemporal gene expression. Enhancer function requires transcription factor (TF) binding and correlates with histone modifications. However, the extent to which TF binding and histone modifications functionally define active enhancers remains unclear. Here, we combine chromatin immunoprecipitation with a massively parallel reporter assay (ChIP-STARR-seq) to identify functional enhancers in human embryonic stem cells (ESCs) genome-wide in a quantitative unbiased manner. Although active enhancers associate with TFs, only a minority of regions marked by NANOG, OCT4, H3K27ac, and H3K4me1 function as enhancers, with activity markedly changing under naive versus primed culture conditions. We identify an enhancer set associated with functions extending to non-ESC-specific processes. Moreover, although transposable elements associate with putative enhancers, only some exhibit activity. Similarly, within super-enhancers, large tracts are non-functional, with activity restricted to small sub-domains. This catalog of validated enhancers provides a valuable resource for further functional dissection of the regulatory genome.

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Massively parallel reporter assay assessed over 350,000 genome regions

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ChIP-STARR-seq catalogs functional enhancers in primed and naive hESCs

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Identification of transcription factors and transposable elements linked to enhancers

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ChIP-STARR-seq dissects super-enhancers into small functional units

Malondialdehyde epitopes are sterile mediators of hepatic inflammation in hypercholesterolemic mice

Diet-related health issues such as nonalcoholic fatty liver disease and cardiovascular disorders are known to have a major inflammatory component. However, the exact pathways linking diet-induced changes (e.g., hyperlipidemia) and the ensuing inflammation have remained elusive so far. We identified biological processes related to innate immunity and oxidative stress as prime response pathways in livers of low-density lipoprotein receptor-deficient mice on a Western-type diet using RNA sequencing and in silico functional analyses of transcriptome data. The observed changes were independent of the presence of microbiota and thus indicative of a role for sterile triggers. We further show that malondialdehyde (MDA) epitopes, products of lipid peroxidation and markers for enhanced oxidative stress, are detectable in hepatic inflammation predominantly on dying cells and stimulate cytokine secretion as well as leukocyte recruitment in vitro and in vivo. MDA-induced cytokine secretion in vitro was dependent on the presence of the scavenger receptors CD36 and MSR1. Moreover, in vivo neutralization of endogenously generated MDA epitopes by intravenous injection of a specific MDA antibody results in decreased hepatic inflammation in low-density lipoprotein receptor-deficient mice on a Western-type diet.

CONCLUSION

Accumulation of MDA epitopes plays a major role during diet-induced hepatic inflammation and can be ameliorated by administration of an anti-MDA antibody. (Hepatology 2017;65:1181-1195).

Pooled CRISPR screening with single-cell transcriptome readout

CRISPR-based genetic screens are accelerating biological discovery, but current methods have inherent limitations. Widely used pooled screens are restricted to simple readouts including cell proliferation and sortable marker proteins. Arrayed screens allow for comprehensive molecular readouts such as transcriptome profiling, but at much lower throughput. Here we combine pooled CRISPR screening with single-cell RNA sequencing into a broadly applicable workflow, directly linking guide RNA expression to transcriptome responses in thousands of individual cells. Our method for CRISPR droplet sequencing (CROP-seq) enables pooled CRISPR screens with single-cell transcriptome resolution, which will facilitate high-throughput functional dissection of complex regulatory mechanisms and heterogeneous cell populations.

Chromatin accessibility maps of chronic lymphocytic leukaemia identify subtype-specific epigenome signatures and transcription regulatory networks

Chronic lymphocytic leukaemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, here we present genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients measured by the ATAC-seq assay. We also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting data set, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status-which distinguishes the two major subtypes of CLL-was accurately predicted by the chromatin profiles and gene regulatory networks inferred for IGHV-mutated versus IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukaemia and demonstrated the feasibility of large-scale chromatin accessibility mapping in cancer cohorts and clinical research.

ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to map histone marks and transcription factor binding throughout the genome. Here we present ChIPmentation, a method that combines chromatin immunoprecipitation with sequencing library preparation by Tn5 transposase (“tagmentation”). ChIPmentation introduces sequencing-compatible adapters in a single-step reaction directly on bead-bound chromatin, which reduces time, cost, and input requirements, thus providing a convenient and broadly useful alternative to existing ChIP-seq protocols.

Evolutionary conservation of the eumetazoan gene regulatory landscape

Despite considerable differences in morphology and complexity of body plans among animals, a great part of the gene set is shared among Bilateria and their basally branching sister group, the Cnidaria. This suggests that the common ancestor of eumetazoans already had a highly complex gene repertoire. At present it is therefore unclear how morphological diversification is encoded in the genome. Here we address the possibility that differences in gene regulation could contribute to the large morphological divergence between cnidarians and bilaterians. To this end, we generated the first genome-wide map of gene regulatory elements in a nonbilaterian animal, the sea anemone Nematostella vectensis. Using chromatin immunoprecipitation followed by deep sequencing of five chromatin modifications and a transcriptional cofactor, we identified over 5000 enhancers in the Nematostella genome and could validate 75% of the tested enhancers in vivo. We found that in Nematostella, but not in yeast, enhancers are characterized by the same combination of histone modifications as in bilaterians, and these enhancers preferentially target developmental regulatory genes. Surprisingly, the distribution and abundance of gene regulatory elements relative to these genes are shared between Nematostella and bilaterian model organisms. Our results suggest that complex gene regulation originated at least 600 million yr ago, predating the common ancestor of eumetazoans.