Single-Cell Transcriptomics of a Human Kidney Allograft Biopsy Specimen Defines a Diverse Inflammatory Response

Caspase-1 and the inflammasome promote polycystic kidney disease progression

We and others have previously shown that the presence of renal innate immune cells can promote polycystic kidney disease (PKD) progression. In this study, we examined the influence of the inflammasome, a key part of the innate immune system, on PKD. The inflammasome is a system of molecular sensors, receptors, and scaffolds that responds to stimuli like cellular damage or microbes by activating Caspase-1, and generating critical mediators of the inflammatory milieu, including IL-1β and IL-18. We provide evidence that the inflammasome is primed in PKD, as multiple inflammasome sensors were upregulated in cystic kidneys from human ADPKD patients, as well as in kidneys from both orthologous (PKD1 RC/RC or RC/RC) and non-orthologous (jck) mouse models of PKD. Further, we demonstrate that the inflammasome is activated in female RC/RC mice kidneys, and this activation occurs in renal leukocytes, primarily in CD11c+ cells. Knock-out of Casp1, the gene encoding Caspase-1, in the RC/RC mice significantly restrained cystic disease progression in female mice, implying sex-specific differences in the renal immune environment. RNAseq analysis implicated the promotion of MYC/YAP pathways as a mechanism underlying the pro-cystic effects of the Caspase-1/inflammasome in females. Finally, treatment of RC/RC mice with hydroxychloroquine, a widely used immunomodulatory drug that has been shown to inhibit the inflammasome, protected renal function specifically in females and restrained cyst enlargement in both male and female RC/RC mice. Collectively, these results provide evidence for the first time that the activated Caspase-1/inflammasome promotes cyst expansion and disease progression in PKD, particularly in females. Moreover, the data suggest that this innate immune pathway may be a relevant target for therapy in PKD.

Single-cell analysis of senescent epithelia reveals targetable mechanisms promoting fibrosis

Progressive fibrosis and maladaptive organ repair result in significant morbidity and millions of premature deaths annually. Senescent cells accumulate with aging and after injury and are implicated in organ fibrosis, but the mechanisms by which senescence influences repair are poorly understood. Using 2 murine models of injury and repair, we show that obstructive injury generated senescent epithelia, which persisted after resolution of the original injury, promoted ongoing fibrosis, and impeded adaptive repair. Depletion of senescent cells with ABT-263 reduced fibrosis in reversed ureteric obstruction and after renal ischemia/reperfusion injury. We validated these findings in humans, showing that senescence and fibrosis persisted after relieved renal obstruction. We next characterized senescent epithelia in murine renal injury using single-cell RNA-Seq. We extended our classification to human kidney and liver disease and identified conserved profibrotic proteins, which we validated in vitro and in human disease. We demonstrated that increased levels of protein disulfide isomerase family A member 3 (PDIA3) augmented TGF-β-mediated fibroblast activation. Inhibition of PDIA3 in vivo significantly reduced kidney fibrosis during ongoing renal injury and as such represented a new potential therapeutic pathway. Analysis of the signaling pathways of senescent epithelia connected senescence to organ fibrosis, permitting rational design of antifibrotic therapies.

WARS1, TYMP and GBP1 display a distinctive microcirculation pattern by immunohistochemistry during antibody-mediated rejection in kidney transplantation

Antibody-mediated rejection (ABMR) is the leading cause of allograft failure in kidney transplantation. Defined by the Banff classification, its gold standard diagnosis remains a challenge, with limited inter-observer reproducibility of the histological scores and efficient immunomarker availability. We performed an immunohistochemical analysis of 3 interferon-related proteins, WARS1, TYMP and GBP1 in a cohort of kidney allograft biopsies including 17 ABMR cases and 37 other common graft injuries. Slides were interpreted, for an ABMR diagnosis, by four blinded nephropathologists and by a deep learning framework using convolutional neural networks. Pathologists identified a distinctive microcirculation staining pattern in ABMR with all three antibodies, displaying promising diagnostic performances and a substantial reproducibility. The deep learning analysis supported the microcirculation staining pattern and achieved similar diagnostic performance from internal validation, with a mean area under the receiver operating characteristic curve of 0.89 (± 0.02) for WARS1, 0.80 (± 0.04) for TYMP and 0.89 (± 0.04) for GBP1. The glomerulitis and peritubular capillaritis scores, the hallmarks of histological ABMR, were the most highly correlated Banff scores with the deep learning output, whatever the C4d status. These novel immunomarkers combined with a CNN framework could help mitigate current challenges in ABMR diagnosis and should be assessed in larger cohorts.

Gain-of-function TLR7 and loss-of-function A20 gene variants identify a novel pathway for Mendelian lupus and lupus nephritis

Systemic lupus erythematosus (SLE) is a chronic and inflammatory autoimmune disease of unknown origin that may cause kidney disease, i.e. lupus nephritis (LN). Within a wider trend towards an expanding field of genetic causes of kidney disease, two recent reports have emphasized the role of Mendelian autoimmune disorders in causing LN both in children and in young adults. Loss-of-function (LOF) variants of tumor necrosis factor alpha-induced protein 3 (TNFAIP3) and gain of function (GOF) variants of Toll-like receptor 7 (TLR7) cause SLE and LN, respectively. Interestingly, both genes regulate the same signaling route, as A20, the protein encoded by TNFAIP3, inhibits nuclear factor ĸB (NF-ĸB) activation while TLR7 promoted NF-ĸB activation. Moreover, TNFAIP3 and TLR7 variants are relatively frequent, potentially contributing to polygenic risk for LN. Finally, they both may be expressed by kidney cells, potentially contributing to the severity of kidney injury in persons who have already developed autoimmunity. The fact that both genes regulate the same pathway may lead to novel therapeutic approaches targeting the shared molecular pathway.

The cellular landscape of the normal kidney allograft: Main players balancing the alloimmune response

Despite recent advances made in short-term outcomes; minimal improvements have been observed in long-term kidney transplantation outcomes. Due to an imbalance between organ transplant availability and patient waiting list, expanding kidney allograft longevity is a critical need in the field. Prior studies have either focused on early ischemic and immunological conditions affecting kidney allografts (e.g., delayed graft function, acute rejection) or late stage chronic injury when interventions are no longer feasible. However, studies characterizing kidney allografts with normal function by its cellular distribution, cell-cell interactions, and associated molecular pathways are lacking. Herein, we used single nuclei RNA-sequencing to uncover the cellular landscape and transcriptome of the normal kidney allograft. We profiled 40,950 nuclei from seven human kidney biopsies (normal native, N = 3; normal allograft, N = 4); normal allograft protocol biopsies were collected ≥15-months post-transplant. A total of 17 distinct cell clusters were identified with proximal tubules (25.70 and 21.01%), distal tubules (15.22 and 18.20%), and endothelial cells (EC) (4.26 and 9.94%) constituting the major cell populations of normal native and normal allograft kidneys, respectively. A large proportion of cycling cells from normal native kidneys were in G1-phase (43.96%) whereas cells from normal allograft were predominantly in S-phase (32.69%). This result suggests that transcriptional differences between normal native and normal allograft biopsies are dependent on the new host environment, immunosuppression, and injury-affliction. In the normal allograft, EC-specific genes upregulated metabolism, the immune response, and cellular growth, emphasizing their role in maintaining homeostasis during the ongoing alloreactive stress response. Immune cells, including B (2.81%), macrophages (24.96%), monocytes (15.29%), natural killer (NK) (12.83%), neutrophils (8.44%), and T cells (14.41%, were increased in normal allografts despite lack of histological or clinical evidence of acute rejection. Phenotypic characterization of immune cell markers supported lymphocyte activation and proinflammatory cytokines signaling pathways (i.e., IL-15, IL-32). The activation of B, NK, and T cells reveals potential immune cells underlying subclinical inflammation and repair. These single nuclei analyses provide novel insights into kidney and immune cell associated signaling pathways that portray kidney grafts with normal allograft function beyond 2-years post-transplant, revealing a novel perspective in understanding long-term allograft graft survival.

Integrative and comparative single-cell analysis reveals transcriptomic difference between human tumefactive demyelinating lesion and glioma

Tumefactive demyelinating lesion (TDL) is an immune-mediated disease which can be misdiagnosed as glioma. At present, there is no study comparing difference between the two disorders at the cellular level. Here, we perform integrative and comparative single-cell RNA sequencing (ScRNA-seq) transcriptomic analysis on TDL and glioma lesions. At single-cell resolution, TDL is comprised primarily of immune cells, which is completely different from glioma. The integrated analysis reveals a TDL-specific microglial subset involving in B cell activation and proliferation. Comparative analysis highlights remyelination function of glial cells and demyelination function of T cells in TDL. Subclustering and pseudotime trajectory analysis of T cells in TDL reveal their heterogeneity and diverse functions involving in TDL pathogenesis and recovery process. Our study identifies substantial differences between TDL and glioma at single-cell resolution. The observed heterogeneity and potentially diverse functions of cells in TDL may be critical in disease progression.

Integrative and comparative single-cell analysis reveals transcriptomic difference between human tumefactive demyelinating lesion and glioma.

Essential role of Wtip in mouse development and maintenance of the glomerular filtration barrier

Wilms' tumor interacting protein (Wtip) has been implicated in cell junction assembly and cell differentiation and interacts with proteins in the podocyte slit diaphragm, where it regulates podocyte phenotype. To define Wtip expression and function in the kidney, we created a Wtip-deleted mouse model using β-galactosidase-neomycin (β-geo) gene trap technology. Wtip gene trap mice were embryonic lethal, suggesting additional developmental roles outside kidney function. Using β-geo heterozygous and normal mice, Wtip expression was identified in the developing kidneys, heart, and eyes. In the kidney, expression was restricted to podocytes, which appeared initially at the capillary loop stage coinciding with terminal podocyte differentiation. Heterozygous mice had an expected lifespan and showed no evidence of proteinuria or glomerular pathology. However, heterozygous mice were more susceptible to glomerular injury than wild-type littermates and developed more significant and prolonged proteinuria in response to lipopolysaccharide or adriamycin. In normal human kidneys, WTIP expression patterns were consistent with observations in mice and were lost in glomeruli concurrent with loss of synaptopodin expression in disease. Mechanistically, we identified the Rho guanine nucleotide exchange factor 12 (ARHGEF12) as a binding partner for WTIP. ARHGEF12 was expressed in human podocytes and formed high-affinity interactions through their LIM- and PDZ-binding domains. Our findings suggest that Wtip is essential for early murine embryonic development and maintaining normal glomerular filtration barrier function, potentially regulating slit diaphragm and foot process function through Rho effector proteins.NEW & NOTEWORTHY This study characterized dynamic expression patterns of Wilms' tumor interacting protein (Wtip) and demonstrates the novel role of Wtip in murine development and maintenance of the glomerular filtration barrier.

Single-cell and spatial mapping Identify cell types and signaling Networks in the human ureter

Tissue engineering offers a promising treatment strategy for ureteral strictures, but its success requires an in-depth understanding of the architecture, cellular heterogeneity, and signaling pathways underlying tissue regeneration. Here, we define and spatially map cell populations within the human ureter using single-cell RNA sequencing, spatial gene expression, and immunofluorescence approaches. We focus on the stromal and urothelial cell populations to enumerate the distinct cell types composing the human ureter and infer potential cell-cell communication networks underpinning the bi-directional crosstalk between these compartments. Furthermore, we analyze and experimentally validate the importance of the sonic hedgehog (SHH) signaling pathway in adult progenitor cell maintenance. The SHH-expressing basal cells support organoid generation in vitro and accurately predict the differentiation trajectory from basal progenitor cells to terminally differentiated umbrella cells. Our results highlight the essential processes involved in adult ureter tissue homeostasis and provide a blueprint for guiding ureter tissue engineering.

Practical Considerations for Single-Cell Genomics

The single-cell revolution in the field of genomics is in full bloom, with clever new molecular biology tricks appearing regularly that allow researchers to explore new modalities or scale up their projects to millions of cells and beyond. Techniques abound to measure RNA expression, DNA alterations, protein abundance, chromatin accessibility, and more, all with single-cell resolution and often in combination. Despite such a rapidly changing technology landscape, there are several fundamental principles that are applicable to the majority of experimental workflows to help users avoid pitfalls and exploit the advantages of the chosen platform. In this overview article, we describe a variety of popular single-cell genomics technologies and address some common questions pertaining to study design, sample preparation, quality control, and sequencing strategy. As the majority of relevant publications currently revolve around single-cell RNA-seq, we will prioritize this genomics modality in our discussion. © 2022 Wiley Periodicals LLC.

Intrarenal Single-Cell Sequencing of Hepatitis B Virus Associated Membranous Nephropathy

To date, the pathogenesis of hepatitis B virus (HBV)-associated membranous nephropathy (MN) remains elusive. This study aimed to decipher the etiopathogenesis of HBV-associated MN by performing single-cell RNA sequencing (scRNA-seq) of kidney biopsy specimens from a patient with HBV-associated MN and two healthy individuals. We generated 4,114 intrarenal single-cell transcriptomes from the HBV-associated MN patient by scRNA-seq. Compared to healthy individuals, podocytes in the HBV-associated MN patient showed an increased expression of extracellular matrix formation-related genes, including HSPA5, CTGF, and EDIL3. Kidney endothelial cells (ECs) in the HBV-associated MN were enriched in inflammatory pathways, including NF-kappa B signaling, IL-17 signaling, TNF signaling and NOD-like receptor signaling. Gene ontology (GO) functional enrichment analysis and Gene Set Variation Analysis (GSVA) further revealed that differentially expressed genes (DEGs) of ECs from the HBV-associated MN patients were enriched in apoptotic signaling pathway, response to cytokine and leukocyte cell-cell adhesion. The up-regulated DEGs in glomerular ECs of HBV-associated MN patients were involved in biological processes such as viral gene expression, and protein targeting to endoplasmic reticulum. We further verified that the overexpressed genes in ECs from HBV-associated MN were mainly enriched in regulation of protein targeting to endoplasmic reticulum, exocytosis, viral gene expression, IL-6 and IL-1 secretion when compared with anti-phospholipase A2 receptor (PLA2R)-positive idiopathic membranous nephropathy (IMN). The receptor-ligand crosstalk analysis revealed potential interactions between endothelial cells and other cells in HBV-associated-MN. These results offer new insight into the pathogenesis of HBV-associated MN and may identify new therapeutic targets for HBV-associated MN.

Single-cell analysis highlights differences in druggable pathways underlying adaptive or fibrotic kidney regeneration

The kidney has tremendous capacity to repair after acute injury, however, pathways guiding adaptive and fibrotic repair are poorly understood. We developed a model of adaptive and fibrotic kidney regeneration by titrating ischemic injury dose. We performed detailed biochemical and histological analysis and profiled transcriptomic changes at bulk and single-cell level (> 110,000 cells) over time. Our analysis highlights kidney proximal tubule cells as key susceptible cells to injury. Adaptive proximal tubule repair correlated with fatty acid oxidation and oxidative phosphorylation. We identify a specific maladaptive/profibrotic proximal tubule cluster after long ischemia, which expresses proinflammatory and profibrotic cytokines and myeloid cell chemotactic factors. Druggability analysis highlights pyroptosis/ferroptosis as vulnerable pathways in these profibrotic cells. Pharmacological targeting of pyroptosis/ferroptosis in vivo pushed cells towards adaptive repair and ameliorates fibrosis. In summary, our single-cell analysis defines key differences in adaptive and fibrotic repair and identifies druggable pathways for pharmacological intervention to prevent kidney fibrosis.

Transplanted organoids empower human preclinical assessment of drug candidate for the clinic

Pharmacodynamic (PD) studies are an essential component of preclinical drug discovery. Current approaches for PD studies, including the analysis of novel kidney disease targeting therapeutic agents, are limited to animal models with unclear translatability to the human condition. To address this challenge, we developed a novel approach for PD studies using transplanted, perfused human kidney organoids. We performed pharmacokinetic (PK) studies with GFB-887, an investigational new drug now in phase 2 trials. Orally dosed GFB-887 to athymic rats that had undergone organoid transplantation resulted in measurable drug exposure in transplanted organoids. We established the efficacy of orally dosed GFB-887 in PD studies, where quantitative analysis showed significant protection of kidney filter cells in human organoids and endogenous rat host kidneys. This widely applicable approach demonstrates feasibility of using transplanted human organoids in preclinical PD studies with an investigational new drug, empowering organoids to revolutionize drug discovery.

Spatially Resolved Transcriptomes of Mammalian Kidneys Illustrate the Molecular Complexity and Interactions of Functional Nephron Segments

Available transcriptomes of the mammalian kidney provide limited information on the spatial interplay between different functional nephron structures due to the required dissociation of tissue with traditional transcriptome-based methodologies. A deeper understanding of the complexity of functional nephron structures requires a non-dissociative transcriptomics approach, such as spatial transcriptomics sequencing (ST-seq). We hypothesize that the application of ST-seq in normal mammalian kidneys will give transcriptomic insights within and across species of physiology at the functional structure level and cellular communication at the cell level. Here, we applied ST-seq in six mice and four human kidneys that were histologically absent of any overt pathology. We defined the location of specific nephron structures in the captured ST-seq datasets using three lines of evidence: pathologist's annotation, marker gene expression, and integration with public single-cell and/or single-nucleus RNA-sequencing datasets. We compared the mouse and human cortical kidney regions. In the human ST-seq datasets, we further investigated the cellular communication within glomeruli and regions of proximal tubules-peritubular capillaries by screening for co-expression of ligand-receptor gene pairs. Gene expression signatures of distinct nephron structures and microvascular regions were spatially resolved within the mouse and human ST-seq datasets. We identified 7,370 differentially expressed genes (p adj < 0.05) distinguishing species, suggesting changes in energy production and metabolism in mouse cortical regions relative to human kidneys. Hundreds of potential ligand-receptor interactions were identified within glomeruli and regions of proximal tubules-peritubular capillaries, including known and novel interactions relevant to kidney physiology. Our application of ST-seq to normal human and murine kidneys confirms current knowledge and localization of transcripts within the kidney. Furthermore, the generated ST-seq datasets provide a valuable resource for the kidney community that can be used to inform future research into this complex organ.

Comprehensive Network-Based Analyses Reveal Novel Renal Function-Related Targets in Acute Kidney Injury

Background: Acute kidney injury (AKI) is a common clinical syndrome with limited methods of treatment and diagnosis. Although several molecules associated with AKI have been discovered, molecular mechanisms underlying AKI still remain unclear. Weighted gene co-expression network analysis (WGCNA) is a novel method to uncover the relationship between co-expression genes and clinical traits at the system level.

Methods: First, by employing WGCNA in transcriptional data on 30 patients with well/poor functioning kidney graft, we identified two co-expression modules that were significantly related to serum creatinine (SCr). Second, based on the modules, potential small molecular compound candidates for developing targeted therapeutics were obtained by connectivity map analysis. Furthermore, multiple validations of expression in space/time were carried out with two classical AKI models in vivo and other five databases of over 152 samples.

Results: Two of the 14 modules were found to be closely correlated with SCr. Function enrichment analysis illustrated that one module was enriched in the immune system, while the other was in the metabolic process. Six key renal function-related genes (RFRGs) were finally obtained. Such genes performed well in cisplatin-induced or cecal ligation and puncture-induced AKI mouse models.

Conclusion: The analysis suggests that WGCNA is a proper method to connect clinical traits with genome data to find novel targets in AKI. The kidney tissue with worse renal function tended to develop a “high immune but low metabolic activity” expression pattern. Also, ACSM2A, GLYAT, CORO1A, DPEP1, ALDH7A1, and EPHX2 are potential targets of molecular diagnosis and treatment in AKI.

T Cells With Activated STAT4 Drive the High-Risk Rejection State to Renal Allograft Failure After Kidney Transplantation

In kidney transplantation, deteriorated progression of rejection is considered to be a leading course of postoperative mortality. However, the conventional histologic diagnosis is limited in reading the rejection status at the molecular level, thereby triggering mismatched pathogenesis with clinical phenotypes. Here, by applying uniform manifold approximation and projection and Leiden algorithms to 2,611 publicly available microarray datasets of renal transplantation, we uncovered six rejection states with corresponding signature genes and revealed a high-risk (HR) state that was essential in promoting allograft loss. By identifying cell populations from single-cell RNA sequencing data that were associated with the six rejection states, we identified a T-cell population to be the pathogenesis-triggering cells associated with the HR rejection state. Additionally, by constructing gene regulatory networks, we identified that activated STAT4, as a core transcription factor that was regulated by PTPN6 in T cells, was closely linked to poor allograft function and prognosis. Taken together, our study provides a novel strategy to help with the precise diagnosis of kidney allograft rejection progression, which is powerful in investigating the underlying molecular pathogenesis, and therefore, for further clinical intervention.

Kidney Development: Recent Insights from Technological Advances

The kidney is a complex organ, and how it forms is a fascinating process. New technologies, such as single-cell transcriptomics, and enhanced imaging modalities are offering new approaches to understand the complex and intertwined processes during embryonic kidney development.

Harnessing the Full Potential of Multi-Omic Analyses to Advance the Study and Treatment of Chronic Kidney Disease

Chronic kidney disease (CKD) was the 12th leading cause of death globally in 2017 with the prevalence of CKD estimated at ~9%. Early detection and intervention for CKD may improve patient outcomes, but standard testing approaches even in developed countries do not facilitate identification of patients at high risk of developing CKD, nor those progressing to end-stage kidney disease (ESKD). Recent advances in CKD research are moving towards a more personalised approach for CKD. Heritability for CKD ranges from 30% to 75%, yet identified genetic risk factors account for only a small proportion of the inherited contribution to CKD. More in depth analysis of genomic sequencing data in large cohorts is revealing new genetic risk factors for common diagnoses of CKD and providing novel diagnoses for rare forms of CKD. Multi-omic approaches are now being harnessed to improve our understanding of CKD and explain some of the so-called 'missing heritability'. The most common omic analyses employed for CKD are genomics, epigenomics, transcriptomics, metabolomics, proteomics and phenomics. While each of these omics have been reviewed individually, considering integrated multi-omic analysis offers considerable scope to improve our understanding and treatment of CKD. This narrative review summarises current understanding of multi-omic research alongside recent experimental and analytical approaches, discusses current challenges and future perspectives, and offers new insights for CKD.

A reference tissue atlas for the human kidney

Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

Detection of infiltrating fibroblasts by single-cell transcriptomics in human kidney allografts

We tested the hypothesis that single-cell RNA-sequencing (scRNA-seq) analysis of human kidney allograft biopsies will reveal distinct cell types and states and yield insights to decipher the complex heterogeneity of alloimmune injury. We selected 3 biopsies of kidney cortex from 3 individuals for scRNA-seq and processed them fresh using an identical protocol on the 10x Chromium platform; (i) HK: native kidney biopsy from a living donor, (ii) AK1: allograft kidney with transplant glomerulopathy, tubulointerstitial fibrosis, and worsening graft function, and (iii) AK2: allograft kidney after successful treatment of active antibody-mediated rejection. We did not study T-cell-mediated rejections. We generated 7217 high-quality single cell transcriptomes. Taking advantage of the recipient-donor sex mismatches revealed by X and Y chromosome autosomal gene expression, we determined that in AK1 with fibrosis, 42 months after transplantation, more than half of the kidney allograft fibroblasts were recipient-derived and therefore likely migratory and graft infiltrative, whereas in AK2 without fibrosis, 84 months after transplantation, most fibroblasts were donor-organ-derived. Furthermore, AK1 was enriched for tubular progenitor cells overexpressing profibrotic extracellular matrix genes. AK2, eight months after successful treatment of rejection, contained plasmablast cells with high expression of immunoglobulins, endothelial cell elaboration of T cell chemoattractant cytokines, and persistent presence of cytotoxic T cells. In addition to these key findings, our analysis revealed unique cell types and states in the kidney. Altogether, single-cell transcriptomics yielded novel mechanistic insights, which could pave the way for individualizing the care of transplant recipients.

Urinary Proteomics Identifies Cathepsin D as a Biomarker of Rapid eGFR Decline in Type 1 Diabetes

OBJECTIVE

Understanding mechanisms underlying rapid estimated glomerular filtration rate (eGFR) decline is important to predict and treat kidney disease in type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

We performed a case-control study nested within four T1D cohorts to identify urinary proteins associated with rapid eGFR decline. Case and control subjects were categorized based on eGFR decline ≥3 and <1 mL/min/1.73 m2/year, respectively. We used targeted liquid chromatography-tandem mass spectrometry to measure 38 peptides from 20 proteins implicated in diabetic kidney disease. Significant proteins were investigated in complementary human cohorts and in mouse proximal tubular epithelial cell cultures.

RESULTS

The cohort study included 1,270 participants followed a median 8 years. In the discovery set, only cathepsin D peptide and protein were significant on full adjustment for clinical and laboratory variables. In the validation set, associations of cathepsin D with eGFR decline were replicated in minimally adjusted models but lost significance with adjustment for albuminuria. In a meta-analysis with combination of discovery and validation sets, the odds ratio for the association of cathepsin D with rapid eGFR decline was 1.29 per SD (95% CI 1.07-1.55). In complementary human cohorts, urine cathepsin D was associated with tubulointerstitial injury and tubulointerstitial cathepsin D expression was associated with increased cortical interstitial fractional volume. In mouse proximal tubular epithelial cell cultures, advanced glycation end product-BSA increased cathepsin D activity and inflammatory and tubular injury markers, which were further increased with cathepsin D siRNA.

CONCLUSIONS

Urine cathepsin D is associated with rapid eGFR decline in T1D and reflects kidney tubulointerstitial injury.

Where Are They Now: Spatial and Molecular Diversity of Tissue-Resident Macrophages in the Kidney

Kidney resident macrophages (KRMs) are involved in homeostasis, phagocytosis, defense against infectious agents, response to insults, inflammation, and tissue repair. They also play critical roles in the pathogenesis and recovery from many kidney diseases such as acute kidney injury. KRMs historically have been studied as one homogenous population, but the wide-ranging roles and phenotypes observed suggest that there is greater heterogeneity than previously understood. Advancements in RNA sequencing technologies (single-cell RNA sequencing and spatial transcriptomics) have identified specific subsets of KRMs that are molecularly, functionally, and spatially distinct with dynamic changes after kidney injury. Multiple studies have identified unique markers that represent these subpopulations, permitting further characterization of the function and roles they play in the kidney. Understanding the diversity of KRM subpopulations will be key in the development of novel therapies used in treating kidney diseases and promoting kidney health.

A Novel Machine Learning 13-Gene Signature: Improving Risk Analysis and Survival Prediction for Clear Cell Renal Cell Carcinoma Patients

Simple Summary

Clear cell renal cell carcinoma is a type of kidney cancer which comprises the majority of all renal cell carcinomas. Many efforts have been made to identify biomarkers which could help healthcare professionals better treat this kind of cancer. With extensive public data available, we conducted a machine learning study to determine a gene signature that could indicate patient survival with high accuracy. Through the min-Redundancy and Max-Relevance algorithm we generated a signature of 13 genes highly correlated with patient outcomes. These findings reveal potential strategies for personalized medicine in the clinical practice.

Abstract

Patients with clear cell renal cell carcinoma (ccRCC) have poor survival outcomes, especially if it has metastasized. It is of paramount importance to identify biomarkers in genomic data that could help predict the aggressiveness of ccRCC and its resistance to drugs. Thus, we conducted a study with the aims of evaluating gene signatures and proposing a novel one with higher predictive power and generalization in comparison to the former signatures. Using ccRCC cohorts of the Cancer Genome Atlas (TCGA-KIRC) and International Cancer Genome Consortium (ICGC-RECA), we evaluated linear survival models of Cox regression with 14 signatures and six methods of feature selection, and performed functional analysis and differential gene expression approaches. In this study, we established a 13-gene signature (AR, AL353637.1, DPP6, FOXJ1, GNB3, HHLA2, IL4, LIMCH1, LINC01732, OTX1, SAA1, SEMA3G, ZIC2) whose expression levels are able to predict distinct outcomes of patients with ccRCC. Moreover, we performed a comparison between our signature and others from the literature. The best-performing gene signature was achieved using the ensemble method Min-Redundancy and Max-Relevance (mRMR). This signature comprises unique features in comparison to the others, such as generalization through different cohorts and being functionally enriched in significant pathways: Urothelial Carcinoma, Chronic Kidney disease, and Transitional cell carcinoma, Nephrolithiasis. From the 13 genes in our signature, eight are known to be correlated with ccRCC patient survival and four are immune-related. Our model showed a performance of 0.82 using the Receiver Operator Characteristic (ROC) Area Under Curve (AUC) metric and it generalized well between the cohorts. Our findings revealed two clusters of genes with high expression (SAA1, OTX1, ZIC2, LINC01732, GNB3 and IL4) and low expression (AL353637.1, AR, HHLA2, LIMCH1, SEMA3G, DPP6, and FOXJ1) which are both correlated with poor prognosis. This signature can potentially be used in clinical practice to support patient treatment care and follow-up.

Single-Cell RNA Sequencing Identifies Intra-Graft Population Heterogeneity in Acute Heart Allograft Rejection in Mouse

Transplant rejection remains a major barrier to graft survival and involves a diversity of cell types. However, the heterogeneity of each cell type in the allograft remains poorly defined. In the present study, we used single-cell RNA sequencing technology to analyze graft-infiltrating cells to describe cell types and states associated with acute rejection in a mouse heart transplant model. Unsupervised clustering analysis revealed 21 distinct cell populations. Macrophages formed five cell clusters: two resident macrophage groups, two infiltrating macrophage groups and one dendritic cell-like monocyte group. Infiltrating macrophages were predominantly from allogeneic grafts. Nevertheless, only one infiltrating macrophage cluster was in an active state with the upregulation of CD40, Fam26f and Pira2, while the other was metabolically silent. Re-clustering of endothelial cells identified five subclusters. Interestingly, one of the endothelial cell populations was almost exclusively from allogeneic grafts. Further analysis of this population showed activation of antigen processing and presentation pathway and upregulation of MHC class II molecules. In addition, Ubiquitin D was specifically expressed in such endothelial cell population. The upregulation of Ubiquitin D in rejection was validated by staining of mouse heart grafts and human kidney biopsy specimens. Our findings present a comprehensive analysis of intra-graft cell heterogeneity, describe specific macrophage and endothelial cell populations which mediate rejection, and provide a potential predictive biomarker for rejection in the clinic.

Single-Nucleus Transcriptional Profiling of Chronic Kidney Disease after Cisplatin Nephrotoxicity

Cisplatin induces both acute and chronic nephrotoxicity during chemotherapy in patients with cancer. Presented here is the first study of single-nucleus RNA sequencing (snRNA-seq) of cisplatin-induced nephrotoxicity. Repeated low-dose cisplatin treatment (RLDC) led to decreases in renal function and kidney weight in mice at 9 weeks. The kidneys of these mice showed tubular degeneration and dilation. snRNA-seq identified 16 cell types and 17 cell clusters in these kidneys. Cluster-by-cluster comparison demonstrated cell type-specific changes in gene expression and identified a unique proximal tubule (PT) injury/repair cluster that co-expressed the injury marker kidney injury molecule-1 (Kim1) and the proliferation marker Ki-67. Compared with control, post-RLDC kidneys had 424 differentially expressed genes in PT cells, including tubular transporters and cytochrome P450 enzymes involved in lipid metabolism. snRNA-seq also revealed transcriptional changes in potential PT injury markers (Krt222, Eda2r, Ltbp2, and Masp1) and repair marker (Bex4). RLDC induced inflammation and proinflammatory cytokines (RelB, TNF-α, Il7, Ccl2, and Cxcl2) and the expression of fibrosis markers (fibronectin, collagen I, connective tissue growth factor, vimentin, and α-smooth muscle actin). Together, these results provide new insights into RLDC-induced transcriptional changes at the single-cell level that may contribute to the development of chronic kidney problems in patients with cancer after cisplatin chemotherapy.

A road map for happiness: The psychological factors related cell types in various parts of human body from single cell RNA-seq data analysis

Massive evidence from all sources including zoology, neurobiology and immunology has confirmed that psychological factors can raise remarkable physiological effects. Researchers have long been aware of the potential value of these effects and wanted to harness them in the development of new drugs and therapies, for which the mechanism study is a necessary prerequisite. However, most of these studies are restricted to neuroscience, or starts with blood sample and fall into the area of immunity. In this study, we choose to focus on the psychological factor of happiness, mining existing publicly available single cell RNA sequencing (scRNA-seq) data for the expression of happiness-related genes collected from various sources of literature in all types of cells in the samples, finding that the expression of these genes is not restricted within neuro-regulated cells or tissue-resident immune cells, on the opposite, cell types that are unique to tissue and organ without direct regulation from nervous system account for the majority to express the happiness-related genes. Our research is a preliminary exploration of where our body respond to our mind at cell level, and lays the foundation for more detailed mechanism research.

Glomerular endothelial cell-podocyte stresses and crosstalk in structurally normal kidney transplants

Increased podocyte detachment begins immediately after kidney transplantation and is associated with long-term allograft failure. We hypothesized that cell-specific transcriptional changes in podocytes and glomerular endothelial cells after transplantation would offer mechanistic insights into the podocyte detachment process. To test this, we evaluated cell-specific transcriptional profiles of glomerular endothelial cells and podocytes from 14 patients of their first-year surveillance biopsies with normal histology from low immune risk recipients with no post-transplant complications and compared these to biopsies of 20 healthy living donor controls. Glomerular endothelial cells from these surveillance biopsies were enriched for genes related to fluid shear stress, angiogenesis, and interferon signaling. In podocytes, pathways were enriched for genes in response to growth factor signaling and actin cytoskeletal reorganization but also showed evidence of podocyte stress as indicated by reduced nephrin (adhesion protein) gene expression. In parallel, transcripts coding for proteins required to maintain podocyte adherence to the underlying glomerular basement membrane were downregulated, including the major glomerular podocyte integrin α3 and the actin cytoskeleton-related gene synaptopodin. The reduction in integrin α3 protein expression in surveillance biopsies was confirmed by immunoperoxidase staining. The combined growth and stress response of patient allografts post-transplantation paralleled similar changes in a rodent model of nephrectomy-induced glomerular hypertrophic stress that progress to develop proteinuria and glomerulosclerosis with shortened kidney life span. Thus, even among patients with apparently healthy allografts with no detectable histologic abnormality including alloimmune injury, transcriptomic changes reflecting cell stresses are already set in motion that could drive hypertrophy-associated glomerular disease progression.

A novel renal perivascular mesenchymal cell subset gives rise to fibroblasts distinct from classic myofibroblasts

Perivascular mesenchymal cells (PMCs), which include pericytes, give rise to myofibroblasts that contribute to chronic kidney disease progression. Several PMC markers have been identified; however, PMC heterogeneity and functions are not fully understood. Here, we describe a novel subset of renal PMCs that express Meflin, a glycosylphosphatidylinositol-anchored protein that was recently identified as a marker of fibroblasts essential for cardiac tissue repair. Tracing the lineage of Meflin⁺ PMCs, which are found in perivascular and periglomerular areas and exhibit renin-producing potential, showed that they detach from the vasculature and proliferate under disease conditions. Although the contribution of Meflin⁺ PMCs to conventional α-SMA⁺ myofibroblasts is low, they give rise to fibroblasts with heterogeneous α-SMA expression patterns. Genetic ablation of Meflin⁺ PMCs in a renal fibrosis mouse model revealed their essential role in collagen production. Consistent with this, human biopsy samples showed that progressive renal diseases exhibit high Meflin expression. Furthermore, Meflin overexpression in kidney fibroblasts promoted bone morphogenetic protein 7 signals and suppressed myofibroblastic differentiation, implicating the roles of Meflin in suppressing tissue fibrosis. These findings demonstrate that Meflin marks a PMC subset that is functionally distinct from classic pericytes and myofibroblasts, highlighting the importance of elucidating PMC heterogeneity.

Immunomodulation by endothelial cells - partnering up with the immune system?

Blood vessel endothelial cells (ECs) have long been known to modulate inflammation by regulating immune cell trafficking, activation status and function. However, whether the heterogeneous EC populations in various tissues and organs differ in their immunomodulatory capacity has received insufficient attention, certainly with regard to considering them for alternative immunotherapy. Recent single-cell studies have identified specific EC subtypes that express gene signatures indicative of phagocytosis or scavenging, antigen presentation and immune cell recruitment. Here we discuss emerging evidence suggesting a tissue-specific and vessel type-specific immunomodulatory role for distinct subtypes of ECs, here collectively referred to as 'immunomodulatory ECs' (IMECs). We propose that IMECs have more important functions in immunity than previously recognized, and suggest that these might be considered as targets for new immunotherapeutic approaches.

Modeling injury and repair in kidney organoids reveals that homologous recombination governs tubular intrinsic repair

Kidneys have the capacity for intrinsic repair, preserving kidney architecture with return to a basal state after tubular injury. When injury is overwhelming or repetitive, however, that capacity is exceeded and incomplete repair results in fibrotic tissue replacing normal kidney parenchyma. Loss of nephrons correlates with reduced kidney function, which defines chronic kidney disease (CKD) and confers substantial morbidity and mortality to the worldwide population. Despite the identification of pathways involved in intrinsic repair, limited treatments for CKD exist, partly because of the limited throughput and predictivity of animal studies. Here, we showed that kidney organoids can model the transition from intrinsic to incomplete repair. Single-nuclear RNA sequencing of kidney organoids after cisplatin exposure identified 159 differentially expressed genes and 29 signal pathways in tubular cells undergoing intrinsic repair. Homology-directed repair (HDR) genes including Fanconi anemia complementation group D2 (FANCD2) and RAD51 recombinase (RAD51) were transiently up-regulated during intrinsic repair but were down-regulated in incomplete repair. Single cellular transcriptomics in mouse models of obstructive and hemodynamic kidney injury and human kidney samples of immune-mediated injury validated HDR gene up-regulation during tubular repair. Kidney biopsy samples with tubular injury and varying degrees of fibrosis confirmed loss of FANCD2 during incomplete repair. Last, we performed targeted drug screening that identified the DNA ligase IV inhibitor, SCR7, as a therapeutic candidate that rescued FANCD2/RAD51-mediated repair to prevent the progression of CKD in the cisplatin-induced organoid injury model. Our findings demonstrate the translational utility of kidney organoids to identify pathologic pathways and potential therapies.

Multiplexed droplet single-cell sequencing (Mux-Seq) of normal and transplant kidney

Maintenance of systemic homeostasis by kidney requires the coordinated response of diverse cell types. The use of single-cell RNA sequencing (scRNAseq) for patient tissue samples remains fraught with difficulties with cell isolation, purity, and experimental bias. The ability to characterize immune and parenchymal cells during transplant rejection will be invaluable in defining transplant pathology where tissue availability is restricted to needle biopsy fragments. Herein, we present feasibility data for multiplexing approach for droplet scRNAseq (Mux-Seq). Mux-Seq has the potential to minimize experimental batch bias and variation even with very small sample input. In this first proof-of-concept study for this approach, explant tissues from six normal and two transplant recipients after multiple early post-transplant rejection episodes leading to nephrectomy due to aggressive antibody mediated rejection, were pooled for Mux-Seq. A computational tool, Demuxlet was applied for demultiplexing the individual cells from the pooled experiment. Each sample was also applied individually in a single microfluidic run (singleplex) to correlate results with the pooled data from the same sample. Our applied protocol demonstrated that data from Mux-Seq correlated highly with singleplex (Pearson coefficient 0.982) sequencing results, with the ability to identify many known and novel kidney cell types including different infiltrating immune cells. Trajectory analysis of proximal tubule and endothelial cells demonstrated separation between healthy and injured kidney from transplant explant suggesting evolving stages of cell- specific differentiation in alloimmune injury. This study provides the technical groundwork for understanding the pathogenesis of alloimmune injury and host tissue response in transplant rejection and normal human kidney and provides a protocol for optimized processing precious and low input human kidney biopsy tissue for larger scale studies.

Cellular and molecular interrogation of kidney biopsy specimens

PURPOSE OF REVIEW

Traditional histopathology of the kidney biopsy specimen has been an essential and successful tool for the diagnosis and staging of kidney diseases. However, it is likely that the full potential of the kidney biopsy has not been tapped so far. Indeed, there is now a concerted worldwide effort to interrogate kidney biopsy samples at the cellular and molecular levels with unprecedented rigor and depth. This review examines these novel approaches to study kidney biopsy specimens and highlights their potential to refine our understanding of the pathophysiology of kidney disease and lead to precision-based diagnosis and therapy.

RECENT FINDINGS

Several consortia are now active at studying kidney biopsy samples from various patient cohorts with state-of-the art cellular and molecular techniques. These include advanced imaging approaches as well as deep molecular interrogation with tools such as epigenetics, transcriptomics, proteomics and metabolomics. The emphasis throughout is on rigor, reproducibility and quality control.

SUMMARY

Although these techniques to study kidney biopsies are complementary, each on its own can yield novel ways to define and classify kidney disease. Therefore, great efforts are needed in order to generate an integrated output that can propel the diagnosis and treatment of kidney disease into the realm of precision medicine.

Macrophages in the kidney in health, injury and repair

Macrophages are a key component of the renal mononuclear phagocyte system, playing a major role in defense against infection, renal injury and repair. Yolk sac macrophage precursors seed the early embryonic kidney and are important for renal development. Later, renal macrophages are derived from hematopoietic stem cells and in adult life, there is a significant contribution from circulating monocytes, which is enhanced in response to infection or injury. Macrophages are highly plastic and can alter their phenotype in response to cues from parenchymal renal cells. Danger-associated molecules released from injured kidney cells may activate macrophages toward a pro-inflammatory phenotype, mediating further recruitment of inflammatory cells, exacerbating renal injury and activating renal fibroblasts to promote scarring. In acute kidney injury, once the injury stimulus has abated, macrophages may adopt a more reparative phenotype, dampening the immune response and promoting repair of renal tissue. However, in chronic kidney disease ongoing activation of pro-inflammatory monocytes and persistence of reparative macrophages leads to glomerulosclerosis and tubulointerstitial fibrosis, the hallmarks of end-stage kidney disease. Several strategies to inhibit the recruitment, activation and secretory products of pro-inflammatory macrophages have proven beneficial in pre-clinical models and are now undergoing clinical trials in patients with kidney disease. In addition, macrophages may be utilized in cell therapy as a "Trojan Horse" to deliver targeted therapies to the kidney. Single-cell RNA sequencing has identified a previously unappreciated spectrum of macrophage phenotypes, which may be selectively present in injury or repair, and ongoing functional analyses of these subsets may identify more specific targets for therapeutic intervention.

DevKidCC allows for robust classification and direct comparisons of kidney organoid datasets

BACKGROUND

While single-cell transcriptional profiling has greatly increased our capacity to interrogate biology, accurate cell classification within and between datasets is a key challenge. This is particularly so in pluripotent stem cell-derived organoids which represent a model of a developmental system. Here, clustering algorithms and selected marker genes can fail to accurately classify cellular identity while variation in analyses makes it difficult to meaningfully compare datasets. Kidney organoids provide a valuable resource to understand kidney development and disease. However, direct comparison of relative cellular composition between protocols has proved challenging. Hence, an unbiased approach for classifying cell identity is required.

METHODS

The R package, scPred, was trained on multiple single cell RNA-seq datasets of human fetal kidney. A hierarchical model classified cellular subtypes into nephron, stroma and ureteric epithelial elements. This model, provided in the R package DevKidCC ( github.com/KidneyRegeneration/DevKidCC ), was then used to predict relative cell identity within published kidney organoid datasets generated using distinct cell lines and differentiation protocols, interrogating the impact of such variations. The package contains custom functions for the display of differential gene expression within cellular subtypes.

RESULTS

DevKidCC was used to directly compare between distinct kidney organoid protocols, identifying differences in relative proportions of cell types at all hierarchical levels of the model and highlighting variations in stromal and unassigned cell types, nephron progenitor prevalence and relative maturation of individual epithelial segments. Of note, DevKidCC was able to distinguish distal nephron from ureteric epithelium, cell types with overlapping profiles that have previously confounded analyses. When applied to a variation in protocol via the addition of retinoic acid, DevKidCC identified a consequential depletion of nephron progenitors.

CONCLUSIONS

The application of DevKidCC to kidney organoids reproducibly classifies component cellular identity within distinct single-cell datasets. The application of the tool is summarised in an interactive Shiny application, as are examples of the utility of in-built functions for data presentation. This tool will enable the consistent and rapid comparison of kidney organoid protocols, driving improvements in patterning to kidney endpoints and validating new approaches.

DevKidCC allows for robust classification and direct comparisons of kidney organoid datasets

Background

While single-cell transcriptional profiling has greatly increased our capacity to interrogate biology, accurate cell classification within and between datasets is a key challenge. This is particularly so in pluripotent stem cell-derived organoids which represent a model of a developmental system. Here, clustering algorithms and selected marker genes can fail to accurately classify cellular identity while variation in analyses makes it difficult to meaningfully compare datasets. Kidney organoids provide a valuable resource to understand kidney development and disease. However, direct comparison of relative cellular composition between protocols has proved challenging. Hence, an unbiased approach for classifying cell identity is required.

Methods

The R package, scPred, was trained on multiple single cell RNA-seq datasets of human fetal kidney. A hierarchical model classified cellular subtypes into nephron, stroma and ureteric epithelial elements. This model, provided in the R package DevKidCC (github.com/KidneyRegeneration/DevKidCC), was then used to predict relative cell identity within published kidney organoid datasets generated using distinct cell lines and differentiation protocols, interrogating the impact of such variations. The package contains custom functions for the display of differential gene expression within cellular subtypes.

Results

DevKidCC was used to directly compare between distinct kidney organoid protocols, identifying differences in relative proportions of cell types at all hierarchical levels of the model and highlighting variations in stromal and unassigned cell types, nephron progenitor prevalence and relative maturation of individual epithelial segments. Of note, DevKidCC was able to distinguish distal nephron from ureteric epithelium, cell types with overlapping profiles that have previously confounded analyses. When applied to a variation in protocol via the addition of retinoic acid, DevKidCC identified a consequential depletion of nephron progenitors.

Conclusions

The application of DevKidCC to kidney organoids reproducibly classifies component cellular identity within distinct single-cell datasets. The application of the tool is summarised in an interactive Shiny application, as are examples of the utility of in-built functions for data presentation. This tool will enable the consistent and rapid comparison of kidney organoid protocols, driving improvements in patterning to kidney endpoints and validating new approaches.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01023-z.

How Many Cell Types Are in the Kidney and What Do They Do?

The kidney maintains electrolyte, water, and acid-base balance, eliminates foreign and waste compounds, regulates blood pressure, and secretes hormones. There are at least 16 different highly specialized epithelial cell types in the mammalian kidney. The number of specialized endothelial cells, immune cells, and interstitial cell types might even be larger. The concerted interplay between different cell types is critical for kidney function. Traditionally, cells were defined by their function or microscopical morphological appearance. With the advent of new single-cell modalities such as transcriptomics, epigenetics, metabolomics, and proteomics we are entering into a new era of cell type definition. This new technological revolution provides new opportunities to classify cells in the kidney and understand their functions.

Urine Single-Cell RNA Sequencing in Focal Segmental Glomerulosclerosis Reveals Inflammatory Signatures

INTRODUCTION

Individuals with focal segmental glomerular sclerosis (FSGS) typically undergo kidney biopsy only once, which limits the ability to characterize kidney cell gene expression over time.

METHODS

We used single-cell RNA sequencing (scRNA-seq) to explore disease-related molecular signatures in urine cells from subjects with FSGS. We collected 17 urine samples from 12 FSGS subjects and captured these as 23 urine cell samples. The inflammatory signatures from renal epithelial and immune cells were evaluated in bulk gene expression data sets of FSGS and minimal change disease (MCD) (The Nephrotic Syndrome Study Network [NEPTUNE] study) and an immune single-cell data set from lupus nephritis (Accelerating Medicines Partnership).

RESULTS

We identified immune cells, predominantly monocytes, and renal epithelial cells in the urine. Further analysis revealed 2 monocyte subtypes consistent with M1 and M2 monocytes. Shed podocytes in the urine had high expression of marker genes for epithelial-to-mesenchymal transition (EMT). We selected the 16 most highly expressed genes from urine immune cells and 10 most highly expressed EMT genes from urine podocytes as immune signatures and EMT signatures, respectively. Using kidney biopsy transcriptomic data from NEPTUNE, we found that urine cell immune signature and EMT signature genes were more highly expressed in FSGS biopsies compared with MCD biopsies.

CONCLUSION

The identification of monocyte subsets and podocyte expression signatures in the urine samples of subjects with FSGS suggests that urine cell profiling might serve as a diagnostic and prognostic tool in nephrotic syndrome. Furthermore, this approach may aid in the development of novel biomarkers and identifying personalized therapies targeting particular molecular pathways in immune cells and podocytes.

Single-Cell RNA Sequencing of Urinary Cells Reveals Distinct Cellular Diversity in COVID-19-Associated AKI

Background

AKI is a common sequela of infection with SARS-CoV-2 and contributes to the severity and mortality from COVID-19. Here, we tested the hypothesis that kidney alterations induced by COVID-19-associated AKI could be detected in cells collected from urine.

Methods

We performed single-cell RNA sequencing (scRNAseq) on cells recovered from the urine of eight hospitalized patients with COVID-19 with (n=5) or without AKI (n=3) as well as four patients with non-COVID-19 AKI (n=4) to assess differences in cellular composition and gene expression during AKI.

Results

Analysis of 30,076 cells revealed a diverse array of cell types, most of which were kidney, urothelial, and immune cells. Pathway analysis of tubular cells from patients with AKI showed enrichment of transcripts associated with damage-related pathways compared with those without AKI. ACE2 and TMPRSS2 expression was highest in urothelial cells among cell types recovered. Notably, in one patient, we detected SARS-CoV-2 viral RNA in urothelial cells. These same cells were enriched for transcripts associated with antiviral and anti-inflammatory pathways.

Conclusions

We successfully performed scRNAseq on urinary sediment from hospitalized patients with COVID-19 to noninvasively study cellular alterations associated with AKI and established a dataset that includes both injured and uninjured kidney cells. Additionally, we provide preliminary evidence of direct infection of urinary bladder cells by SARS-CoV-2. The urinary sediment contains a wealth of information and is a useful resource for studying the pathophysiology and cellular alterations that occur in kidney diseases.

Functional role of histamine receptors in the renal cortical collecting duct cells

Histamine is an important immunomodulator, as well as a regulator of allergic inflammation, gastric acid secretion, and neurotransmission. Although substantial histamine level has been reported in the kidney, renal pathological and physiological effects of this compound have not been clearly defined. The goal of this study was to provide insight into the role of histamine-related pathways in the kidney, with emphasis on the collecting duct (CD), a distal part of the nephron important for the regulation of blood pressure. We report that all four histamine receptors (HRs) as well as enzymes responsible for histamine metabolism and synthesis are expressed in cultured mouse mpkCCD_cl4 cells, and histamine evokes a dose-dependent transient increase in intracellular Ca²⁺ in these cells. Furthermore, we observed a dose-dependent increase in cAMP in the CD cells in response to histamine. Short-circuit current studies aimed at measuring Na⁺ reabsorption via ENaC (epithelial Na⁺ channel) demonstrated inhibition of ENaC-mediated currents by histamine after a 4-hr incubation, and single-channel patch-clamp analysis revealed similar ENaC open probability before and after acute histamine application. The long-term (4 hr) effect on ENaC was corroborated in immunocytochemistry and qPCR, which showed a decrease in protein and gene expression for αENaC upon histamine treatment. In summary, our data highlight the functional importance of HRs in the CD cells and suggest potential implications of histamine in inflammation-related renal conditions. Further research is required to discern the molecular pathways downstream of HRs and assess the role of specific receptors in renal pathophysiology.

Integration of single cell data by disentangled representation learning

Recent developments of single cell RNA-sequencing technologies lead to the exponential growth of single cell sequencing datasets across different conditions. Combining these datasets helps to better understand cellular identity and function. However, it is challenging to integrate different datasets from different laboratories or technologies due to batch effect, which are interspersed with biological variances. To overcome this problem, we have proposed Single Cell Integration by Disentangled Representation Learning (SCIDRL), a domain adaption-based method, to learn low-dimensional representations invariant to batch effect. This method can efficiently remove batch effect while retaining cell type purity. We applied it to thirteen diverse simulated and real datasets. Benchmark results show that SCIDRL outperforms other methods in most cases and exhibits excellent performances in two common situations: (i) effective integration of batch-shared rare cell types and preservation of batch-specific rare cell types; (ii) reliable integration of datasets with different cell compositions. This demonstrates SCIDRL will offer a valuable tool for researchers to decode the enigma of cell heterogeneity.

Single-cell chromatin accessibility landscape in kidney identifies additional cell-of-origin in heterogenous papillary renal cell carcinoma

Papillary renal cell carcinoma (pRCC) is the most heterogenous renal cell carcinoma. Patient survival varies and no effective therapies for advanced pRCC exist. Histological and molecular characterization studies have highlighted the heterogeneity of pRCC tumours. Recent studies identified the proximal tubule (PT) cell as a cell-of-origin for pRCC. However, it remains elusive whether other pRCC subtypes have different cell-of-origin. Here, by obtaining genome-wide chromatin accessibility profiles of normal human kidney cells using single-cell transposase-accessible chromatin-sequencing and comparing the profiles with pRCC samples, we discover that besides PT cells, pRCC can also originate from kidney collecting duct principal cells. We show pRCCs with different cell-of-origin exhibit different molecular characteristics and clinical behaviors. Further, metabolic reprogramming appears to mediate the progression of pRCC to the advanced state. Here, our results suggest that determining cell-of-origin and monitoring origin-dependent metabolism could potentially be useful for early diagnosis and treatment of pRCC.

Using Imaging Mass Cytometry to Define Cell Identities and Interactions in Human Tissues

In the evolving landscape of highly multiplexed imaging techniques that can be applied to study complex cellular microenvironments, this review characterizes the use of imaging mass cytometry (IMC) to study the human kidney. We provide technical details for antibody validation, cell segmentation, and data analysis specifically tailored to human kidney samples, and elaborate on phenotyping of kidney cell types and novel insights that IMC can provide regarding pathophysiological processes in the injured or diseased kidney. This review will provide the reader with the necessary background to understand both the power and the limitations of IMC and thus support better perception of how IMC analysis can improve our understanding of human disease pathogenesis and can be integrated with other technologies such as single cell sequencing and proteomics to provide spatial context to cellular data.

Emerging Technologies to Study the Glomerular Filtration Barrier

Kidney disease is characterized by loss of glomerular function with clinical manifestation of proteinuria. Identifying the cellular and molecular changes that lead to loss of protein in the urine is challenging due to the complexity of the filtration barrier, constituted by podocytes, glomerular endothelial cells, and glomerular basement membrane. In this review, we will discuss how technologies like single cell RNA sequencing and bioinformatics-based spatial transcriptomics, as well as in vitro systems like kidney organoids and the glomerulus-on-a-chip, have contributed to our understanding of glomerular pathophysiology. Knowledge gained from these studies will contribute toward the development of personalized therapeutic approaches for patients affected by proteinuric diseases.

How Times Have Changed! A Cornucopia of Antigens for Membranous Nephropathy

The identification of the major target antigen phospholipase A2 receptor (PLA2R) in the majority of primary (idiopathic) cases of membranous nephropathy (MN) has been followed by the rapid identification of numerous minor antigens that appear to define phenotypically distinct forms of disease. This article serves to review all the known antigens that have been shown to localize to subepithelial deposits in MN, as well as the distinctive characteristics associated with each subtype of MN. We will also shed light on the novel proteomic approaches that have allowed identification of the most recent antigens. The paradigm of an antigen normally expressed on the podocyte cell surface leading to in-situ immune complex formation, complement activation, and subsequent podocyte injury will be discussed and challenged in light of the current repertoire of multiple MN antigens. Since disease phenotypes associated with each individual target antigens can often blur the distinction between primary and secondary disease, we encourage the use of antigen-based classification of membranous nephropathy.

Myeloid Heterogeneity in Kidney Disease as Revealed through Single-Cell RNA Sequencing

Kidney disease represents a global health burden of increasing prevalence and is an independent risk factor for cardiovascular disease. Myeloid cells are a major cellular compartment of the immune system; they are found in the healthy kidney and in increased numbers in the damaged and/or diseased kidney, where they act as key players in the progression of injury, inflammation, and fibrosis. They possess enormous plasticity and heterogeneity, adopting different phenotypic and functional characteristics in response to stimuli in the local milieu. Although this inherent complexity remains to be fully understood in the kidney, advances in single-cell genomics promise to change this. Specifically, single-cell RNA sequencing (scRNA-seq) has had a transformative effect on kidney research, enabling the profiling and analysis of the transcriptomes of single cells at unprecedented resolution and throughput, and subsequent generation of cell atlases. Moving forward, combining scRNA- and single-nuclear RNA-seq with greater-resolution spatial transcriptomics will allow spatial mapping of kidney disease of varying etiology to further reveal the patterning of immune cells and nonimmune renal cells. This review summarizes the roles of myeloid cells in kidney health and disease, the experimental workflow in currently available scRNA-seq technologies, and published findings using scRNA-seq in the context of myeloid cells and the kidney.

Urine Proteomics and Renal Single Cell Transcriptomics Implicate IL-16 in Lupus Nephritis

OBJECTIVES

Current treatments are effective only in 30% of lupus nephritis patients emphasizing the need for novel therapeutic strategies. To develop mechanistic hypotheses and explore novel biomarkers, we analyzed the longitudinal urinary proteomic profiles in patients with lupus nephritis undergoing treatment.

METHODS

We quantified 1,000 urinary proteins in 30 patients with lupus nephritis at the time of the diagnostic renal biopsy and after 3, 6, and 12 months. The proteins and molecular pathways detected in the urine proteome were then analyzed with respect to baseline clinical features and longitudinal trajectories. The intrarenal expression of candidate biomarkers was evaluated using single cell transcriptomics of renal biopsies from lupus nephritis patients.

RESULTS

Our analysis revealed multiple biological pathways including chemotaxis, neutrophil activation, platelet degranulation, and extracellular matrix organization that could be noninvasively quantified and monitored in the urine. We identified 237 urinary biomarkers associated with lupus nephritis as compared to controls without SLE. IL-16, CD163, and TGF-β mirrored intrarenal nephritis activity. Response to treatment was paralleled by a reduction of urinary IL-16, a CD4 ligand with proinflammatory and chemotactic properties. Single cell RNA sequencing independently demonstrated that IL16 is the second most expressed cytokine by most infiltrating immune cells in lupus nephritis kidneys. IL-16 producing cells were found at key sites of kidney injury.

CONCLUSION

Urine proteomics may profoundly change the diagnosis and management of lupus nephritis by noninvasively monitor active intrarenal biological pathways. These findings implicate IL-16 in lupus nephritis pathogenesis designating it as a potentially treatable target and biomarker.

Advanced Genomics-Based Approaches for Defining Allograft Rejection With Single Cell Resolution

Solid organ transplant recipients require long-term immunosuppression for prevention of rejection. Calcineurin inhibitor (CNI)-based immunosuppressive regimens have remained the primary means for immunosuppression for four decades now, yet little is known about their effects on graft resident and infiltrating immune cell populations. Similarly, the understanding of rejection biology under specific types of immunosuppression remains to be defined. Furthermore, development of innovative, rationally designed targeted therapeutics for mitigating or preventing rejection requires a fundamental understanding of the immunobiology that underlies the rejection process. The established use of microarray technologies in transplantation has provided great insight into gene transcripts associated with allograft rejection but does not characterize rejection on a single cell level. Therefore, the development of novel genomics tools, such as single cell sequencing techniques, combined with powerful bioinformatics approaches, has enabled characterization of immune processes at the single cell level. This can provide profound insights into the rejection process, including identification of resident and infiltrating cell transcriptomes, cell-cell interactions, and T cell receptor α/β repertoires. In this review, we discuss genomic analysis techniques, including microarray, bulk RNAseq (bulkSeq), single-cell RNAseq (scRNAseq), and spatial transcriptomic (ST) techniques, including considerations of their benefits and limitations. Further, other techniques, such as chromatin analysis via assay for transposase-accessible chromatin sequencing (ATACseq), bioinformatic regulatory network analyses, and protein-based approaches are also examined. Application of these tools will play a crucial role in redefining transplant rejection with single cell resolution and likely aid in the development of future immunomodulatory therapies in solid organ transplantation.