ADAMTS12 promotes fibrosis by restructuring extracellular matrix to enable activation of injury-responsive fibroblasts.

Fibrosis represents the uncontrolled replacement of parenchymal tissue with extracellular matrix (ECM) produced by myofibroblasts. While genetic fate-tracing and single-cell RNA-Seq technologies have helped elucidate fibroblast heterogeneity and ontogeny beyond fibroblast to myofibroblast differentiation, newly identified fibroblast populations remain ill defined, with respect to both the molecular cues driving their differentiation and their subsequent role in fibrosis. Using an unbiased approach, we identified the metalloprotease ADAMTS12 as a fibroblast-specific gene that is strongly upregulated during active fibrogenesis in humans and mice. Functional in vivo KO studies in mice confirmed that Adamts12 was critical during fibrogenesis in both heart and kidney. Mechanistically, using a combination of spatial transcriptomics and expression of catalytically active or inactive ADAMTS12, we demonstrated that the active protease of ADAMTS12 shaped ECM composition and cleaved hemicentin 1 (HMCN1) to enable the activation and migration of a distinct injury-responsive fibroblast subset defined by aberrant high JAK/STAT signaling.

Spatial transcriptomic analysis of primary and metastatic pancreatic cancers highlights tumor microenvironmental heterogeneity.

Although the spatial, cellular and molecular landscapes of resected pancreatic ductal adenocarcinoma (PDAC) are well documented, the characteristics of its metastatic ecology remain elusive. By applying spatially resolved transcriptomics to matched primary and metastatic PDAC samples, we discovered a conserved continuum of fibrotic, metabolic and immunosuppressive spatial ecotypes across anatomical regions. We observed spatial tumor microenvironment heterogeneity spanning beyond that previously appreciated in PDAC. Through comparative analysis, we show that the spatial ecotypes exhibit distinct enrichment between primary and metastatic sites, implying adaptability to the local environment for survival and progression. The invasive border ecotype exhibits both pro-tumorigenic and anti-tumorigenic cell-type enrichment, suggesting a potential immunotherapy target. The ecotype heterogeneity across patients emphasizes the need to map individual patient landscapes to develop personalized treatment strategies. Collectively, our findings provide critical insights into metastatic PDAC biology and serve as a valuable resource for future therapeutic exploration and molecular investigations.

Generation of a conditional cellular senescence model using proximal tubule cells and fibroblasts from human kidneys.

Emerging evidence highlights cellular senescence's pivotal role in chronic kidney disease (CKD). Proximal tubule epithelial cells (PTECs) and fibroblasts are major players in CKD and serve as cellular sources of senescence. The generation of a conditionally immortalized human kidney cell model would allow to better understand the specific mechanisms and factors associated with cellular senescence in a controlled setting, devoid of potential confounding factors such as age and comorbidities. In addition, the availability of human kidney cell lines for preclinical research is sparse and most cell lines do not reflect their in vivo counterparts due to their altered behavior as immortalized cancer-like cells. In this study, PTECs and fibroblasts from human kidneys were isolated and transduced with doxycycline-inducible simian virus 40 large T antigen (SV40LT) vector. By comparing their gene expression with single-cell RNA sequencing data from human kidneys, the newly produced human kidney cell lines demonstrated significant resemblances to their in vivo counterparts. As predicted, PTECs showed functional activity and fibroblasts responded to injury with fibrosis. Withdrawal of the immortalizing factor doxycycline led to p21+ cell-cycle arrest and the key hallmarks of senescence. The obtained senescence gene set largely overlapped between both cell lines and with the previously published SenMayo set of senescence-associated genes. Furthermore, crosstalk experiments showed that senescent PTECs can cause a profibrotic response in fibroblasts by paracrine actions. In 76 human kidney sections, the number of p21+ cells correlated with the degree of fibrosis, age and reduced glomerular filtration, validating the role of senescence in CKD. In conclusion, we provide a novel cellular ex vivo model to study kidney senescence which can serve as a platform for large scale compounds testing.

Deletion of RFX6 impairs iPSC-derived islet organoid development and survival, with no impact on PDX1+/NKX6.1+ progenitors.

AIMS/HYPOTHESIS: Homozygous mutations in RFX6 lead to neonatal diabetes accompanied by a hypoplastic pancreas, whereas heterozygous mutations cause MODY. Recent studies have also shown RFX6 variants to be linked with type 2 diabetes. Despite RFX6's known function in islet development, its specific role in diabetes pathogenesis remains unclear. Here, we aimed to understand the mechanisms underlying the impairment of pancreatic islet development and subsequent hypoplasia due to loss-of-function mutations in RFX6. METHODS: We examined regulatory factor X6 (RFX6) expression during human embryonic stem cell (hESC) differentiation into pancreatic islets and re-analysed a single-cell RNA-seq dataset to identify RFX6-specific cell populations during islet development. Furthermore, induced pluripotent stem cell (iPSC) lines lacking RFX6 were generated using CRISPR/Cas9. Various approaches were then employed to explore the consequences of RFX6 loss across different developmental stages. Subsequently, we evaluated transcriptional changes resulting from RFX6 loss through RNA-seq of pancreatic progenitors (PPs) and endocrine progenitors (EPs). RESULTS: RFX6 expression was detected in PDX1+ cells in the hESC-derived posterior foregut (PF). However, in the PPs, RFX6 did not co-localise with pancreatic and duodenal homeobox 1 (PDX1) or NK homeobox 1 (NKX6.1) but instead co-localised with neurogenin 3, NK2 homeobox 2 and islet hormones in the EPs and islets. Single-cell analysis revealed high RFX6 expression levels in endocrine clusters across various hESC-derived pancreatic differentiation stages. Upon differentiating iPSCs lacking RFX6 into pancreatic islets, a significant decrease in PDX1 expression at the PF stage was observed, although this did not affect PPs co-expressing PDX1 and NKX6.1. RNA-seq analysis showed the downregulation of essential genes involved in pancreatic endocrine differentiation, insulin secretion and ion transport due to RFX6 deficiency. Furthermore, RFX6 deficiency resulted in the formation of smaller islet organoids due to increased cellular apoptosis, linked to reduced catalase expression, implying a protective role for RFX6. Overexpression of RFX6 reversed defective phenotypes in RFX6-knockout PPs, EPs and islets. CONCLUSIONS/INTERPRETATION: These findings suggest that pancreatic hypoplasia and reduced islet cell formation associated with RFX6 mutations are not due to alterations in PDX1+/NKX6.1+ PPs but instead result from cellular apoptosis and downregulation of pancreatic endocrine genes. DATA AVAILABILITY: RNA-seq datasets have been deposited in the Zenodo repository with accession link (DOI: https://doi.org/10.5281/zenodo.10656891 ).

The common p.Ile291Val variant of ERLIN1 enhances TM6SF2 function and is associated with protection against MASLD.

BACKGROUND: The ERLIN1 p.Ile291Val single-nucleotide polymorphism (rs2862954) is associated with protection from steatotic liver disease (SLD), but effects of this variant on metabolic phenotypes remain uncertain. METHODS: Metabolic phenotypes and outcomes associated with ERLIN1 p.Ile291Val were analyzed by using a genome-first approach in the UK Biobank (UKB), Penn Medicine BioBank (PMBB), and All of Us cohort. FINDINGS: ERLIN1 p.Ile291Val carriers exhibited significantly lower serum levels of alanine aminotransferase and aspartate aminotransferase as well as higher levels of triglycerides, low-density lipoprotein cholesterol, Apolipoprotein B, high-density lipoprotein cholesterol, and Apolipoprotein A1 in UKB, and these values were affected by ERLIN1 p.Ile291Val in an allele-dose-dependent manner. Homozygous ERLIN1 p.Ile291Val carriers had a significantly reduced risk of developing metabolic dysfunction-associated SLD (MASLD, adjusted odds ratio [aOR] = 0.92, 95% confidence interval [CI], 0.88-0.96). The protective effect of this variant was enhanced in patients with alcoholic liver disease. Our results were replicated in PMBB and the All of Us cohort. Strikingly, the protective effects of ERLIN1 p.Ile291Val were not apparent in individuals carrying the TM6SF2 p.Glu167Lys variant associated with increased risk of SLD. We analyzed the effects of predicted loss-of-function ERLIN1 variants and found that they had opposite effects, namely reduced plasma lipids, suggesting that ERLIN1 p.Ile291Val may be a gain-of-function variant. CONCLUSION: Our study contributes to a better understanding of ERLIN1 by investigating a coding variant that has emerged as a potential gain-of-function mutation with protective effects against MASLD development.

Persistent transcriptional changes in cardiac adaptive immune cells following myocardial infarction: New evidence from the re-analysis of publicly available single cell and nuclei RNA-sequencing data sets.

INTRODUCTION: Chronic immunopathology contributes to the development of heart failure after a myocardial infarction. Both T and B cells of the adaptive immune system are present in the myocardium and have been suggested to be involved in post-MI immunopathology. METHODS: We analyzed the B and T cell populations isolated from previously published single cell RNA-sequencing data sets (PMID: 32130914, PMID: 35948637, PMID: 32971526 and PMID: 35926050), of the mouse and human heart, using differential expression analysis, functional enrichment analysis, gene regulatory inferences, and integration with autoimmune and cardiovascular GWAS. RESULTS: Already at baseline, mature effector B and T cells are present in the human and mouse heart, having increased activity in transcription factors maintaining tolerance (e.g. DEAF1, JDP2, SPI-B). Following MI, T cells upregulate pro-inflammatory transcript levels (e.g. Cd11, Gzmk, Prf1), while B cells upregulate activation markers (e.g. Il6, Il1rn, Ccl6) and collagen (e.g. Col5a2, Col4a1, Col1a2). Importantly, pro-inflammatory and fibrotic transcription factors (e.g. NFKB1, CREM, REL) remain active in T cells, while B cells maintain elevated activity in transcription factors related to immunoglobulin production (e.g. ERG, REL) in both mouse and human post-MI hearts. Notably, genes differentially expressed in post-MI T and B cells are associated with cardiovascular and autoimmune disease. CONCLUSION: These findings highlight the varied and time-dependent dynamic roles of post-MI T and B cells. They appear ready-to-go and are activated immediately after MI, thus participate in the acute wound healing response. However, they subsequently remain in a state of pro-inflammatory activation contributing to persistent immunopathology.

Harnessing Artificial Intelligence for Enhanced Renal Analysis: Automated Detection of Hydronephrosis and Precise Kidney Segmentation.

Background and objective: Hydronephrosis is essential in the diagnosis of renal colic. We automated the detection of hydronephrosis from ultrasound images to standardize the therapy and reduce the misdiagnosis of renal colic. Methods: Anonymously collected ultrasound images of human kidneys, both normal and hydronephrotic, were preprocessed for neural networks. Six "state of the art" models were trained and cross-validated for the detection of hydronephrosis, and two convolutional networks were used for kidney segmentation. In the testing phase, performance metrics included true positives, true negatives, false positives, false negatives, accuracy, and F1 score, while the evaluation of the segmentation task involved accuracy, precision, dice, jaccard, recall, and ASSD. Key findings and limitations: A total of 523 sonographic kidney images (423 nonhydronephrotic and 100 hydronephrotic) were collected from three different ultrasound devices. After training on this dataset, all models were used to evaluate 200 new ultrasound kidney images (142 nonhydronephrotic and 58 hydronephrotic kidneys). The highest validation accuracy (98.5%) was achieved by the AlexNet model (GoogLeNet 97%, AlexNet_v2 96%, ResNet50 96%, ResNet101 97.5%, and ResNet152 95%). The deeplabv3_resnet50 and deeplabv3_resnet101 reached a dice coefficient of 94.74% and 94.48%, respectively, on the task of automated kidney segmentation. The study is limited by analyzing only hydronephrosis, but this specific focus enabled high detection accuracy. Conclusions and clinical implications: We show that our automated ultrasound deep learning model can be trained and used to interpret and segmentate ultrasound images from different sources with high accuracy. This method will serve as an automated tool in the diagnostic algorithm of acute renal failure in the future. Patient summary: Hydronephrosis is crucial in the diagnosis of renal colic. Recent advances in artificial intelligence allow automated detection of hydronephrosis in ultrasound images with high accuracy. These methods will help standardize the diagnosis and treatment renal colic.

Discovery of YAP1/TAZ pathway inhibitors through phenotypic screening with potent anti-tumor activity via blockade of Rho-GTPase signaling.

This study describes the identification and target deconvolution of small molecule inhibitors of oncogenic Yes-associated protein (YAP1)/TAZ activity with potent anti-tumor activity in vivo. A high-throughput screen (HTS) of 3.8 million compounds was conducted using a cellular YAP1/TAZ reporter assay. Target deconvolution studies identified the geranylgeranyltransferase-I (GGTase-I) complex as the direct target of YAP1/TAZ pathway inhibitors. The small molecule inhibitors block the activation of Rho-GTPases, leading to subsequent inactivation of YAP1/TAZ and inhibition of cancer cell proliferation in vitro. Multi-parameter optimization resulted in BAY-593, an in vivo probe with favorable PK properties, which demonstrated anti-tumor activity and blockade of YAP1/TAZ signaling in vivo.

The role of desmoglein-2 in kidney disease.

Desmosomes are multi-protein cell-cell adhesion structures supporting cell stability and mechanical stress resilience of tissues, best described in skin and heart. The kidney is exposed to various mechanical stimuli and stress, yet little is known about kidney desmosomes. In healthy kidneys, we found desmosomal proteins located at the apical-junctional complex in tubular epithelial cells. In four different animal models and patient biopsies with various kidney diseases, desmosomal components were significantly upregulated and partly miss-localized outside of the apical-junctional complexes along the whole lateral tubular epithelial cell membrane. The most upregulated component was desmoglein-2 (Dsg2). Mice with constitutive tubular epithelial cell-specific deletion of Dsg2 developed normally, and other desmosomal components were not altered in these mice. When challenged with different types of tubular epithelial cell injury (unilateral ureteral obstruction, ischemia-reperfusion, and 2,8-dihydroxyadenine crystal nephropathy), we found increased tubular epithelial cell apoptosis, proliferation, tubular atrophy, and inflammation compared to wild-type mice in all models and time points. In vitro, silencing DSG2 via siRNA weakened cell-cell adhesion in HK-2 cells and increased cell death. Thus, our data show a prominent upregulation of desmosomal components in tubular cells across species and diseases and suggest a protective role of Dsg2 against various injurious stimuli.

Matrix Metalloproteinase-7 in Urinary Extracellular Vesicles Identifies Rapid Disease Progression in Autosomal Dominant Polycystic Kidney Disease.

SIGNIFICANCE STATEMENT: There is an unmet need for biomarkers of disease progression in autosomal dominant polycystic kidney disease (ADPKD). This study investigated urinary extracellular vesicles (uEVs) as a source of such biomarkers. Proteomic analysis of uEVs identified matrix metalloproteinase 7 (MMP-7) as a biomarker predictive of rapid disease progression. In validation studies, MMP-7 was predictive in uEVs but not in whole urine, possibly because uEVs are primarily secreted by tubular epithelial cells. Indeed, single-nucleus RNA sequencing showed that MMP-7 was especially increased in proximal tubule and thick ascending limb cells, which were further characterized by a profibrotic phenotype. Together, these data suggest that MMP-7 is a biologically plausible and promising uEV biomarker for rapid disease progression in ADPKD. BACKGROUND: In ADPKD, there is an unmet need for early markers of rapid disease progression to facilitate counseling and selection for kidney-protective therapy. Our aim was to identify markers for rapid disease progression in uEVs. METHODS: Six paired case-control groups ( n =10-59/group) of cases with rapid disease progression and controls with stable disease were formed from two independent ADPKD cohorts, with matching by age, sex, total kidney volume, and genetic variant. Candidate uEV biomarkers were identified by mass spectrometry and further analyzed using immunoblotting and an ELISA. Single-nucleus RNA sequencing of healthy and ADPKD tissue was used to identify the cellular origin of the uEV biomarker. RESULTS: In the discovery proteomics experiments, the protein abundance of MMP-7 was significantly higher in uEVs of patients with rapid disease progression compared with stable disease. In the validation groups, a significant >2-fold increase in uEV-MMP-7 in patients with rapid disease progression was confirmed using immunoblotting. By contrast, no significant difference in MMP-7 was found in whole urine using ELISA. Compared with healthy kidney tissue, ADPKD tissue had significantly higher MMP-7 expression in proximal tubule and thick ascending limb cells with a profibrotic phenotype. CONCLUSIONS: Among patients with ADPKD, rapid disease progressors have higher uEV-associated MMP-7. Our findings also suggest that MMP-7 is a biologically plausible biomarker for more rapid disease progression.

Sublethal necroptosis signaling promotes inflammation and liver cancer.

It is currently not well known how necroptosis and necroptosis responses manifest in vivo. Here, we uncovered a molecular switch facilitating reprogramming between two alternative modes of necroptosis signaling in hepatocytes, fundamentally affecting immune responses and hepatocarcinogenesis. Concomitant necrosome and NF-κB activation in hepatocytes, which physiologically express low concentrations of receptor-interacting kinase 3 (RIPK3), did not lead to immediate cell death but forced them into a prolonged "sublethal" state with leaky membranes, functioning as secretory cells that released specific chemokines including CCL20 and MCP-1. This triggered hepatic cell proliferation as well as activation of procarcinogenic monocyte-derived macrophage cell clusters, contributing to hepatocarcinogenesis. In contrast, necrosome activation in hepatocytes with inactive NF-κB-signaling caused an accelerated execution of necroptosis, limiting alarmin release, and thereby preventing inflammation and hepatocarcinogenesis. Consistently, intratumoral NF-κB-necroptosis signatures were associated with poor prognosis in human hepatocarcinogenesis. Therefore, pharmacological reprogramming between these distinct forms of necroptosis may represent a promising strategy against hepatocellular carcinoma.

MASI enables fast model-free standardization and integration of single-cell transcriptomics data.

Single-cell transcriptomics datasets from the same anatomical sites generated by different research labs are becoming increasingly common. However, fast and computationally inexpensive tools for standardization of cell-type annotation and data integration are still needed in order to increase research inclusivity. To standardize cell-type annotation and integrate single-cell transcriptomics datasets, we have built a fast model-free integration method, named MASI (Marker-Assisted Standardization and Integration). We benchmark MASI with other well-established methods and demonstrate that MASI outperforms other methods, in terms of integration, annotation, and speed. To harness knowledge from single-cell atlases, we demonstrate three case studies that cover integration across biological conditions, surveyed participants, and research groups, respectively. Finally, we show MASI can annotate approximately one million cells on a personal laptop, making large-scale single-cell data integration more accessible. We envision that MASI can serve as a cheap computational alternative for the single-cell research community.

IL-6 in the infarcted heart is preferentially formed by fibroblasts and modulated by purinergic signaling.

Plasma IL-6 is elevated after myocardial infarction (MI) and is associated with increased morbidity and mortality. Which cardiac cell type preferentially contributes to IL-6 expression and how its production is regulated are largely unknown. Here, we studied the cellular source and purinergic regulation of IL-6 formation in a murine MI model. We found that IL-6, measured in various cell types in post-MI hearts at the protein level and by quantitative PCR and RNAscope, was preferentially formed by cardiac fibroblasts (CFs). Single-cell RNA-Seq (scRNA-Seq) in infarcted mouse and human hearts confirmed this finding. We found that adenosine stimulated fibroblast IL-6 formation via the adenosine receptor A2bR in a Gq-dependent manner. CFs highly expressed Adora2b and rapidly degraded extracellular ATP to AMP but lacked CD73. In mice and humans, scRNA-Seq revealed that Adora2B was also mainly expressed by fibroblasts. We assessed global IL-6 production in isolated hearts from mice lacking CD73 on T cells (CD4-CD73-/-), a condition known to be associated with adverse cardiac remodeling. The ischemia-induced release of IL-6 was strongly attenuated in CD4-CD73-/- mice, suggesting adenosine-mediated modulation. Together, these findings demonstrate that post-MI IL-6 was mainly derived from activated CFs and was controlled by T cell-derived adenosine. We show that purinergic metabolic cooperation between CFs and T cells is a mechanism that modulates IL-6 formation by the heart and has therapeutic potential.

Fast model-free standardization and integration of single-cell transcriptomics data.

Single-cell transcriptomics datasets from the same anatomical sites generated by different research labs are becoming increasingly common. However, fast and computationally inexpensive tools for standardization of cell-type annotation and data integration are still needed in order to increase research inclusivity. To standardize cell-type annotation and integrate single-cell transcriptomics datasets, we have built a fast model-free integration method, named MASI (Marker-Assisted Standardization and Integration). MASI first identifies putative cell-type markers from reference data through an ensemble approach. Then, it converts gene expression matrix to cell-type score matrix with the identified putative cell-type markers for the purpose of cell-type annotation and data integration. Because of integration through cell-type markers instead of model inference, MASI can annotate approximately one million cells on a personal laptop, which provides a cheap computational alternative for the single-cell community. We benchmark MASI with other well-established methods and demonstrate that MASI outperforms other methods based on speed. Its performance for both tasks of data integration and cell-type annotation are comparable or even superior to these existing methods. To harness knowledge from single-cell atlases, we demonstrate three case studies that cover integration across biological conditions, surveyed participants, and research groups, respectively.

Targeting Immune-Fibroblast Crosstalk in Myocardial Infarction and Cardiac Fibrosis.

Inflammation and tissue fibrosis co-exist and are causally linked to organ dysfunction. However, the molecular mechanisms driving immune-fibroblast crosstalk in human cardiac disease remains unexplored and there are currently no therapeutics to target fibrosis. Here, we performed multi-omic single-cell gene expression, epitope mapping, and chromatin accessibility profiling in 38 donors, acutely infarcted, and chronically failing human hearts. We identified a disease-associated fibroblast trajectory marked by cell surface expression of fibroblast activator protein (FAP), which diverged into distinct myofibroblasts and pro-fibrotic fibroblast populations, the latter resembling matrifibrocytes. Pro-fibrotic fibroblasts were transcriptionally similar to cancer associated fibroblasts and expressed high levels of collagens and periostin (POSTN), thymocyte differentiation antigen 1 (THY-1), and endothelin receptor A (EDNRA) predicted to be driven by a RUNX1 gene regulatory network. We assessed the applicability of experimental systems to model tissue fibrosis and demonstrated that 3 different in vivo mouse models of cardiac injury were superior compared to cultured human heart and dermal fibroblasts in recapitulating the human disease phenotype. Ligand-receptor analysis and spatial transcriptomics predicted that interactions between C-C chemokine receptor type 2 (CCR2) macrophages and fibroblasts mediated by interleukin 1 beta (IL-1ß) signaling drove the emergence of pro-fibrotic fibroblasts within spatially defined niches. This concept was validated through in silico transcription factor perturbation and in vivo inhibition of IL-1ß signaling in fibroblasts where we observed reduced pro-fibrotic fibroblasts, preferential differentiation of fibroblasts towards myofibroblasts, and reduced cardiac fibrosis. Herein, we show a subset of macrophages signal to fibroblasts via IL-1ß and rewire their gene regulatory network and differentiation trajectory towards a pro-fibrotic fibroblast phenotype. These findings highlight the broader therapeutic potential of targeting inflammation to treat tissue fibrosis and restore organ function.

[Artificial intelligence in urology-opportunities and possibilities]. / Künstliche Intelligenz in der Urologie ­ Chancen und Möglichkeiten.

The use of artificial intelligence (AI) in urology can contribute to a significant improvement with regard to individualization of diagnostics and therapy as well as healthcare cost reduction. The potential applications and advantages of AI in medicine are often underestimated or incompletely understood. This makes it difficult to conceptually solve relevant medical problems using AI. With current advances in computer science, multiple, highly complex nonmedical processes have already been studied and optimized in an automated fashion. The development of AI models, if applied correctly, can lead to more effective processing and analysis of patient-related data and correspondingly optimized diagnosis and therapy of urological patients. In this review, the current status on the application of AI in medicine and its opportunities and possibilities in urology are presented from a conceptual perspective using practical examples.

Platelet-instructed SPP1+ macrophages drive myofibroblast activation in fibrosis in a CXCL4-dependent manner.

Fibrosis represents the common end stage of chronic organ injury independent of the initial insult, destroying tissue architecture and driving organ failure. Here we discover a population of profibrotic macrophages marked by expression of Spp1, Fn1, and Arg1 (termed Spp1 macrophages), which expands after organ injury. Using an unbiased approach, we identify the chemokine (C-X-C motif) ligand 4 (CXCL4) to be among the top upregulated genes during profibrotic Spp1 macrophage differentiation. In vitro and in vivo studies show that loss of Cxcl4 abrogates profibrotic Spp1 macrophage differentiation and ameliorates fibrosis after both heart and kidney injury. Moreover, we find that platelets, the most abundant source of CXCL4 in vivo, drive profibrotic Spp1 macrophage differentiation. Single nuclear RNA sequencing with ligand-receptor interaction analysis reveals that macrophages orchestrate fibroblast activation via Spp1, Fn1, and Sema3 crosstalk. Finally, we confirm that Spp1 macrophages expand in both human chronic kidney disease and heart failure.

Single-nucleus RNA sequencing in ischemic cardiomyopathy reveals common transcriptional profile underlying end-stage heart failure.

Ischemic cardiomyopathy (ICM) is the leading cause of heart failure worldwide, yet the cellular and molecular signature of this disease is largely unclear. Using single-nucleus RNA sequencing (snRNA-seq) and integrated computational analyses, we profile the transcriptomes of over 99,000 human cardiac nuclei from the non-infarct region of the left ventricle of 7 ICM transplant recipients and 8 non-failing (NF) controls. We find the cellular composition of the ischemic heart is significantly altered, with decreased cardiomyocytes and increased proportions of lymphatic, angiogenic, and arterial endothelial cells in patients with ICM. We show that there is increased LAMININ signaling from endothelial cells to other cell types in ICM compared with NF. Finally, we find that the transcriptional changes that occur in ICM are similar to those in hypertrophic and dilated cardiomyopathies and that the mining of these combined datasets can identify druggable genes that could be used to target end-stage heart failure.

Adult human kidney organoids originate from CD24+ cells and represent an advanced model for adult polycystic kidney disease.

Adult kidney organoids have been described as strictly tubular epithelia and termed tubuloids. While the cellular origin of tubuloids has remained elusive, here we report that they originate from a distinct CD24+ epithelial subpopulation. Long-term-cultured CD24+ cell-derived tubuloids represent a functional human kidney tubule. We show that kidney tubuloids can be used to model the most common inherited kidney disease, namely autosomal dominant polycystic kidney disease (ADPKD), reconstituting the phenotypic hallmark of this disease with cyst formation. Single-cell RNA sequencing of CRISPR-Cas9 gene-edited PKD1- and PKD2-knockout tubuloids and human ADPKD and control tissue shows similarities in upregulation of disease-driving genes. Furthermore, in a proof of concept, we demonstrate that tolvaptan, the only approved drug for ADPKD, has a significant effect on cyst size in tubuloids but no effect on a pluripotent stem cell-derived model. Thus, tubuloids are derived from a tubular epithelial subpopulation and represent an advanced system for ADPKD disease modeling.