ADP-heptose attenuates Helicobacter pylori-induced dendritic cell activation.

Sophisticated immune evasion strategies enable Helicobacter pylori (H. pylori) to colonize the gastric mucosa of approximately half of the world's population. Persistent infection and the resulting chronic inflammation are a major cause of gastric cancer. To understand the intricate interplay between H. pylori and host immunity, spatial profiling was used to monitor immune cells in H. pylori infected gastric tissue. Dendritic cell (DC) and T cell phenotypes were further investigated in gastric organoid/immune cell co-cultures and mechanistic insights were acquired by proteomics of human DCs. Here, we show that ADP-heptose, a bacterial metabolite originally reported to act as a bona fide PAMP, reduces H. pylori-induced DC maturation and subsequent T cell responses. Mechanistically, we report that H. pylori uptake and subsequent DC activation by an ADP-heptose deficient H. pylori strain depends on TLR2. Moreover, ADP-heptose attenuates full-fledged activation of primary human DCs in the context of H. pylori infection by impairing type I IFN signaling. This study reveals that ADP-heptose mitigates host immunity during H. pylori infection.

JAK-STAT signaling maintains homeostasis in T cells and macrophages.

Immune cells need to sustain a state of constant alertness over a lifetime. Yet, little is known about the regulatory processes that control the fluent and fragile balance that is called homeostasis. Here we demonstrate that JAK-STAT signaling, beyond its role in immune responses, is a major regulator of immune cell homeostasis. We investigated JAK-STAT-mediated transcription and chromatin accessibility across 12 mouse models, including knockouts of all STAT transcription factors and of the TYK2 kinase. Baseline JAK-STAT signaling was detected in CD8+ T cells and macrophages of unperturbed mice-but abrogated in the knockouts and in unstimulated immune cells deprived of their normal tissue context. We observed diverse gene-regulatory programs, including effects of STAT2 and IRF9 that were independent of STAT1. In summary, our large-scale dataset and integrative analysis of JAK-STAT mutant and wild-type mice uncovered a crucial role of JAK-STAT signaling in unstimulated immune cells, where it contributes to a poised epigenetic and transcriptional state and helps prepare these cells for rapid response to immune stimuli.

Reliable interpretability of biology-inspired deep neural networks.

Deep neural networks display impressive performance but suffer from limited interpretability. Biology-inspired deep learning, where the architecture of the computational graph is based on biological knowledge, enables unique interpretability where real-world concepts are encoded in hidden nodes, which can be ranked by importance and thereby interpreted. In such models trained on single-cell transcriptomes, we previously demonstrated that node-level interpretations lack robustness upon repeated training and are influenced by biases in biological knowledge. Similar studies are missing for related models. Here, we test and extend our methodology for reliable interpretability in P-NET, a biology-inspired model trained on patient mutation data. We observe variability of interpretations and susceptibility to knowledge biases, and identify the network properties that drive interpretation biases. We further present an approach to control the robustness and biases of interpretations, which leads to more specific interpretations. In summary, our study reveals the broad importance of methods to ensure robust and bias-aware interpretability in biology-inspired deep learning.

In vivo screening characterizes chromatin factor functions during normal and malignant hematopoiesis.

Cellular differentiation requires extensive alterations in chromatin structure and function, which is elicited by the coordinated action of chromatin and transcription factors. By contrast with transcription factors, the roles of chromatin factors in differentiation have not been systematically characterized. Here, we combine bulk ex vivo and single-cell in vivo CRISPR screens to characterize the role of chromatin factor families in hematopoiesis. We uncover marked lineage specificities for 142 chromatin factors, revealing functional diversity among related chromatin factors (i.e. barrier-to-autointegration factor subcomplexes) as well as shared roles for unrelated repressive complexes that restrain excessive myeloid differentiation. Using epigenetic profiling, we identify functional interactions between lineage-determining transcription factors and several chromatin factors that explain their lineage dependencies. Studying chromatin factor functions in leukemia, we show that leukemia cells engage homeostatic chromatin factor functions to block differentiation, generating specific chromatin factor-transcription factor interactions that might be therapeutically targeted. Together, our work elucidates the lineage-determining properties of chromatin factors across normal and malignant hematopoiesis.

Cell-autonomous regulation of complement C3 by factor H limits macrophage efferocytosis and exacerbates atherosclerosis.

Complement factor H (CFH) negatively regulates consumption of complement component 3 (C3), thereby restricting complement activation. Genetic variants in CFH predispose to chronic inflammatory disease. Here, we examined the impact of CFH on atherosclerosis development. In a mouse model of atherosclerosis, CFH deficiency limited plaque necrosis in a C3-dependent manner. Deletion of CFH in monocyte-derived inflammatory macrophages propagated uncontrolled cell-autonomous C3 consumption without downstream C5 activation and heightened efferocytotic capacity. Among leukocytes, Cfh expression was restricted to monocytes and macrophages, increased during inflammation, and coincided with the accumulation of intracellular C3. Macrophage-derived CFH was sufficient to dampen resolution of inflammation, and hematopoietic deletion of CFH in atherosclerosis-prone mice promoted lesional efferocytosis and reduced plaque size. Furthermore, we identified monocyte-derived inflammatory macrophages expressing C3 and CFH in human atherosclerotic plaques. Our findings reveal a regulatory axis wherein CFH controls intracellular C3 levels of macrophages in a cell-autonomous manner, evidencing the importance of on-site complement regulation in the pathogenesis of inflammatory diseases.

Single-cell transcriptomics and epigenomics unravel the role of monocytes in neuroblastoma bone marrow metastasis.

Metastasis is the major cause of cancer-related deaths. Neuroblastoma (NB), a childhood tumor has been molecularly defined at the primary cancer site, however, the bone marrow (BM) as the metastatic niche of NB is poorly characterized. Here we perform single-cell transcriptomic and epigenomic profiling of BM aspirates from 11 subjects spanning three major NB subtypes and compare these to five age-matched and metastasis-free BM, followed by in-depth single cell analyses of tissue diversity and cell-cell interactions, as well as functional validation. We show that cellular plasticity of NB tumor cells is conserved upon metastasis and tumor cell type composition is NB subtype-dependent. NB cells signal to the BM microenvironment, rewiring via macrophage mgration inhibitory factor and midkine signaling specifically monocytes, which exhibit M1 and M2 features, are marked by activation of pro- and anti-inflammatory programs, and express tumor-promoting factors, reminiscent of tumor-associated macrophages. The interactions and pathways characterized in our study provide the basis for therapeutic approaches that target tumor-to-microenvironment interactions.

Comparative analysis of genome-scale, base-resolution DNA methylation profiles across 580 animal species.

Methylation of cytosines is a prototypic epigenetic modification of the DNA. It has been implicated in various regulatory mechanisms across the animal kingdom and particularly in vertebrates. We mapped DNA methylation in 580 animal species (535 vertebrates, 45 invertebrates), resulting in 2443 genome-scale DNA methylation profiles of multiple organs. Bioinformatic analysis of this large dataset quantified the association of DNA methylation with the underlying genomic DNA sequence throughout vertebrate evolution. We observed a broadly conserved link with two major transitions-once in the first vertebrates and again with the emergence of reptiles. Cross-species comparisons focusing on individual organs supported a deeply conserved association of DNA methylation with tissue type, and cross-mapping analysis of DNA methylation at gene promoters revealed evolutionary changes for orthologous genes. In summary, this study establishes a large resource of vertebrate and invertebrate DNA methylomes, it showcases the power of reference-free epigenome analysis in species for which no reference genomes are available, and it contributes an epigenetic perspective to the study of vertebrate evolution.

Stress signaling boosts interferon-induced gene transcription in macrophages.

Promoters of antimicrobial genes function as logic boards, integrating signals of innate immune responses. One such set of genes is stimulated by interferon (IFN) signaling, and the expression of these genes [IFN-stimulated genes (ISGs)] can be further modulated by cell stress-induced pathways. Here, we investigated the global effect of stress-induced p38 mitogen-activated protein kinase (MAPK) signaling on the response of macrophages to IFN. In response to cell stress that coincided with IFN exposure, the p38 MAPK-activated transcription factors CREB and c-Jun, in addition to the IFN-activated STAT family of transcription factors, bound to ISGs. In addition, p38 MAPK signaling induced activating histone modifications at the loci of ISGs and stimulated nuclear translocation of the CREB coactivator CRTC3. These actions synergistically enhanced ISG expression. Disrupting this synergy with p38 MAPK inhibitors improved the viability of macrophages infected with Listeria monocytogenes. Our findings uncover a mechanism of transcriptional synergism and highlight the biological consequences of coincident stress-induced p38 MAPK and IFN-stimulated signal transduction.

Multi-omics profiling predicts allograft function after lung transplantation.

RATIONALE: Lung transplantation is the ultimate treatment option for patients with end-stage respiratory diseases but bears the highest mortality rate among all solid organ transplantations due to chronic lung allograft dysfunction (CLAD). The mechanisms leading to CLAD remain elusive due to an insufficient understanding of the complex post-transplant adaptation processes. OBJECTIVES: To better understand these lung adaptation processes after transplantation and to investigate their association with future changes in allograft function. METHODS: We performed an exploratory cohort study of bronchoalveolar lavage samples from 78 lung recipients and donors. We analysed the alveolar microbiome using 16S rRNA sequencing, the cellular composition using flow cytometry, as well as metabolome and lipidome profiling. MEASUREMENTS AND MAIN RESULTS: We established distinct temporal dynamics for each of the analysed data sets. Comparing matched donor and recipient samples, we revealed that recipient-specific as well as environmental factors, rather than the donor microbiome, shape the long-term lung microbiome. We further discovered that the abundance of certain bacterial strains correlated with underlying lung diseases even after transplantation. A decline in forced expiratory volume during the first second (FEV1) is a major characteristic of lung allograft dysfunction in transplant recipients. By using a machine learning approach, we could accurately predict future changes in FEV1 from our multi-omics data, whereby microbial profiles showed a particularly high predictive power. CONCLUSION: Bronchoalveolar microbiome, cellular composition, metabolome and lipidome show specific temporal dynamics after lung transplantation. The lung microbiome can predict future changes in lung function with high precision.

The molecular and phenotypic makeup of fetal human skin T lymphocytes.

The adult human skin contains a vast number of T cells that are essential for skin homeostasis and pathogen defense. T cells are first observed in the skin at the early stages of gestation; however, our understanding of their contribution to early immunity has been limited by their low abundance and lack of comprehensive methodologies for their assessment. Here, we describe a new workflow for isolating and expanding significant amounts of T cells from fetal human skin. Using multiparametric flow cytometry and in situ immunofluorescence, we found a large population with a naive phenotype and small populations with a memory and regulatory phenotype. Their molecular state was characterized using single-cell transcriptomics and TCR repertoire profiling. Importantly, culture of total fetal skin biopsies facilitated T cell expansion without a substantial impact on their phenotype, a major prerequisite for subsequent functional assays. Collectively, our experimental approaches and data advance the understanding of fetal skin immunity and potential use in future therapeutic interventions.

Spontaneously Resolved Atopic Dermatitis Shows Melanocyte and Immune Cell Activation Distinct From Healthy Control Skin.

Atopic dermatitis (AD) typically starts in infancy or early childhood, showing spontaneous remission in a subset of patients, while others develop lifelong disease. Despite an increased understanding of AD, factors guiding its natural course are only insufficiently elucidated. We thus performed suction blistering in skin of adult patients with stable, spontaneous remission from previous moderate-to-severe AD during childhood. Samples were compared to healthy controls without personal or familial history of atopy, and to chronic, active AD lesions. Skin cells and tissue fluid obtained were used for single-cell RNA sequencing and proteomic multiplex assays, respectively. We found overall cell composition and proteomic profiles of spontaneously healed AD to be comparable to healthy control skin, without upregulation of typical AD activity markers (e.g., IL13, S100As, and KRT16). Among all cell types in spontaneously healed AD, melanocytes harbored the largest numbers of differentially expressed genes in comparison to healthy controls, with upregulation of potentially anti-inflammatory markers such as PLA2G7. Conventional T-cells also showed increases in regulatory markers, and a general skewing toward a more Th1-like phenotype. By contrast, gene expression of regulatory T-cells and keratinocytes was essentially indistinguishable from healthy skin. Melanocytes and conventional T-cells might thus contribute a specific regulatory milieu in spontaneously healed AD skin.

αßγδ T cells play a vital role in fetal human skin development and immunity.

T cells in human skin play an important role in the immune defense against pathogens and tumors. T cells are present already in fetal skin, where little is known about their cellular phenotype and biological function. Using single-cell analyses, we identified a naive T cell population expressing αß and γδ T cell receptors (TCRs) that was enriched in fetal skin and intestine but not detected in other fetal organs and peripheral blood. TCR sequencing data revealed that double-positive (DP) αßγδ T cells displayed little overlap of CDR3 sequences with single-positive αß T cells. Gene signatures, cytokine profiles and in silico receptor-ligand interaction studies indicate their contribution to early skin development. DP αßγδ T cells were phosphoantigen responsive, suggesting their participation in the protection of the fetus against pathogens in intrauterine infections. Together, our analyses unveil a unique cutaneous T cell type within the native skin microenvironment and point to fundamental differences in the immune surveillance between fetal and adult human skin.

Persistence of mature dendritic cells, TH2A, and Tc2 cells characterize clinically resolved atopic dermatitis under IL-4Rα blockade.

Therapeutic options for autoimmune diseases typically consist of broad and targeted immunosuppressive agents. However, sustained clinical benefit is rarely achieved, as the disease phenotype usually returns after cessation of treatment. To better understand tissue-resident immune memory in human disease, we investigated patients with atopic dermatitis (AD) who underwent short-term or long-term treatment with the IL-4Rα blocker dupilumab. Using multi-omics profiling with single-cell RNA sequencing and multiplex proteomics, we found significant decreases in overall skin immune cell counts and normalization of transcriptomic dysregulation in keratinocytes consistent with clearance of disease. However, we identified specific immune cell populations that persisted for up to a year after clinical remission while being absent from healthy controls. These populations included LAMP3 + CCL22+ mature dendritic cells, CRTH2 + CD161 + T helper ("TH2A") cells, and CRTAM + cytotoxic T cells, which expressed high levels of CCL17 (dendritic cells) and IL13 (T cells). TH2A cells showed a characteristic cytokine receptor constellation with IL17RB, IL1RL1 (ST2), and CRLF2 expression, suggesting that these cells are key responders to the AD-typical epidermal alarmins IL-25, IL-33, and TSLP, respectively. We thus identified disease-linked immune cell populations in resolved AD indicative of a persisting disease memory, facilitating a rapid response system of epidermal-dermal cross-talk between keratinocytes, dendritic cells, and T cells. This observation may help to explain the disease recurrence upon termination of immunosuppressive treatments in AD, and it identifies potential disease memory-linked cell types that may be targeted to achieve a more sustained therapeutic response.

Distributed changes of the functional connectome in patients with glioblastoma.

Glioblastoma might have widespread effects on the neural organization and cognitive function, and even focal lesions may be associated with distributed functional alterations. However, functional changes do not necessarily follow obvious anatomical patterns and the current understanding of this interrelation is limited. In this study, we used resting-state functional magnetic resonance imaging to evaluate changes in global functional connectivity patterns in 15 patients with glioblastoma. For six patients we followed longitudinal trajectories of their functional connectome and structural tumour evolution using bi-monthly follow-up scans throughout treatment and disease progression. In all patients, unilateral tumour lesions were associated with inter-hemispherically symmetric network alterations, and functional proximity of tumour location was stronger linked to distributed network deterioration than anatomical distance. In the longitudinal subcohort of six patients, we observed patterns of network alterations with initial transient deterioration followed by recovery at first follow-up, and local network deterioration to precede structural tumour recurrence by two months. In summary, the impact of focal glioblastoma lesions on the functional connectome is global and linked to functional proximity rather than anatomical distance to tumour regions. Our findings further suggest a relevance for functional network trajectories as a possible means supporting early detection of tumour recurrence.

Single-Cell RNA Sequencing Analysis Reveals a Crucial Role for CTHRC1 (Collagen Triple Helix Repeat Containing 1) Cardiac Fibroblasts After Myocardial Infarction.

BACKGROUND: Cardiac fibroblasts (CFs) have a central role in the ventricular remodeling process associated with different types of fibrosis. Recent studies have shown that fibroblasts do not respond homogeneously to heart injury. Because of the limited set of bona fide fibroblast markers, a proper characterization of fibroblast population heterogeneity in response to cardiac damage is lacking. The purpose of this study was to define CF heterogeneity during ventricular remodeling and the underlying mechanisms that regulate CF function. METHODS: Collagen1α1-GFP (green fluorescent protein)-positive CFs were characterized after myocardial infarction (MI) by single-cell and bulk RNA sequencing, assay for transposase-accessible chromatin sequencing, and functional assays. Swine and patient samples were studied using bulk RNA sequencing. RESULTS: We identified and characterized a unique CF subpopulation that emerges after MI in mice. These activated fibroblasts exhibit a clear profibrotic signature, express high levels of Cthrc1 (collagen triple helix repeat containing 1), and localize into the scar. Noncanonical transforming growth factor-ß signaling and different transcription factors including SOX9 are important regulators mediating their response to cardiac injury. Absence of CTHRC1 results in pronounced lethality attributable to ventricular rupture. A population of CFs with a similar transcriptome was identified in a swine model of MI and in heart tissue from patients with MI and dilated cardiomyopathy. CONCLUSIONS: We report CF heterogeneity and their dynamics during the course of MI and redefine the CFs that respond to cardiac injury and participate in myocardial remodeling. Our study identifies CTHRC1 as a novel regulator of the healing scar process and a target for future translational studies.

Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data.

BACKGROUND: Deep learning has emerged as a versatile approach for predicting complex biological phenomena. However, its utility for biological discovery has so far been limited, given that generic deep neural networks provide little insight into the biological mechanisms that underlie a successful prediction. Here we demonstrate deep learning on biological networks, where every node has a molecular equivalent, such as a protein or gene, and every edge has a mechanistic interpretation, such as a regulatory interaction along a signaling pathway. RESULTS: With knowledge-primed neural networks (KPNNs), we exploit the ability of deep learning algorithms to assign meaningful weights in multi-layered networks, resulting in a widely applicable approach for interpretable deep learning. We present a learning method that enhances the interpretability of trained KPNNs by stabilizing node weights in the presence of redundancy, enhancing the quantitative interpretability of node weights, and controlling for uneven connectivity in biological networks. We validate KPNNs on simulated data with known ground truth and demonstrate their practical use and utility in five biological applications with single-cell RNA-seq data for cancer and immune cells. CONCLUSIONS: We introduce KPNNs as a method that combines the predictive power of deep learning with the interpretability of biological networks. While demonstrated here on single-cell sequencing data, this method is broadly relevant to other research areas where prior domain knowledge can be represented as networks.

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 defence3-5. 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.

Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets.

BACKGROUND: Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. This application requires high levels of precision, robustness, and quantitative accuracy-beyond those achievable with existing methods for mainly qualitative single-cell analysis. Here, we establish the use of standardized reference cells as spike-in controls for accurate and robust dissection of single-cell drug responses. RESULTS: We find that contamination by cell-free RNA can constitute up to 20% of reads in human primary tissue samples, and we show that the ensuing biases can be removed effectively using a novel bioinformatics algorithm. Applying our method to both human and mouse pancreatic islets treated ex vivo, we obtain an accurate and quantitative assessment of cell-specific drug effects on the transcriptome. We observe that FOXO inhibition induces dedifferentiation of both alpha and beta cells, while artemether treatment upregulates insulin and other beta cell marker genes in a subset of alpha cells. In beta cells, dedifferentiation and insulin repression upon artemether treatment occurs predominantly in mouse but not in human samples. CONCLUSIONS: This new method for quantitative, error-correcting, scRNA-seq data normalization using spike-in reference cells helps clarify complex cell-specific effects of pharmacological perturbations with single-cell resolution and high quantitative accuracy.

Single-cell transcriptomics combined with interstitial fluid proteomics defines cell type-specific immune regulation in atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD) is the most common chronic inflammatory skin disease, but its complex pathogenesis is only insufficiently understood, resulting in still limited treatment options. OBJECTIVE: We sought to characterize AD on both transcriptomic and proteomic levels in humans. METHODS: We used skin suction blistering, a painless and nonscarring procedure that can simultaneously sample skin cells and interstitial fluid. We then compared results with conventional biopsies. RESULTS: Suction blistering captured epidermal and most immune cells equally well as biopsies, except for mast cells and nonmigratory CD163+ macrophages that were only present in biopsy isolates. Using single-cell RNA sequencing, we found comparable transcriptional profiles of key inflammatory pathways between blister and biopsy AD, but suction blistering was superior in cell-specific resolution for high-abundance transcripts (KRT1/KRT10, KRT16/KRT6A, S100A8/S100A9), which showed some background signals in biopsy isolates. Compared with healthy controls, we found characteristic upregulation of AD-typical cytokines such as IL13 and IL22 in Th2 and Th22 cells, respectively, but we also discovered these mediators in proliferating T cells and natural killer T cells, that also expressed the antimicrobial cytokine IL26. Overall, not T cells, but myeloid cells were most strongly enriched in AD, and we found dendritic cell (CLEC7A, amphiregulin/AREG, EREG) and macrophage products (CCL13) among the top upregulated proteins in AD blister fluid proteomic analyses. CONCLUSION: These data show that by using cutting-edge technology, suction blistering offers several advantages over conventional biopsies, including better transcriptomic resolution of skin cells, combined with proteomic information from interstitial fluid, unraveling novel inflammatory players that shape the cellular and proteomic microenvironment of AD.

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.