key: cord-1053427-sez5ez34 authors: Jankowski, Jakub; Lee, Hye Kyung; Wilflingseder, Julia; Hennighausen, Lothar title: JAK inhibitors dampen activation of interferon-activated transcriptomes and the SARS-CoV-2 receptor ACE2 in human renal proximal tubules date: 2021-07-30 journal: iScience DOI: 10.1016/j.isci.2021.102928 sha: 9bfd2a065d825bf557f185af4ca54d7fe969bdae doc_id: 1053427 cord_uid: sez5ez34 SARS-CoV-2 infections initiate cytokine storms and activate genetic programs leading to progressive hyperinflammation in multiple organs of COVID-19 patients. While it is known that COVID-19 impacts kidney function, leading to increased mortality, cytokine response of renal epithelium has not been studied in detail. Here, we report on the genetic programs activated in Human Primary Proximal Tubule (HPPT) cells by interferons and their suppression by ruxolitinib, a Janus kinase (JAK) inhibitor used in COVID-19 treatment. Integration of our data with those form acute kidney injury and COVID-19 patients, as well as other tissues, permitted the identification of kidney-specific interferon responses. Additionally, we investigated the regulation of the recently discovered isoform (dACE2) of the angiotensin-converting enzyme 2 (ACE2), the SARS-CoV-2 receptor. Using ChIP-seq, we identified candidate interferon-activated enhancers controlling the ACE2 locus, including the intronic dACE2 promoter. Taken together, our study provides an in-depth understanding of genetic programs activated in kidney cells. A form of acute respiratory distress syndrome (ARDS) caused by SARS-CoV-2 is a major contributor to the death toll of COVID-19. (Gibson et al., 2020) ARDS is closely linked to cytokine storm, an unrestrained release of proinflammatory cytokines and chemokines. (Kim et al., 2021) This, in turn, may result in multi-organ failure (Mokhtari et al., 2020) and coagulopathies (Vinayagam and Sattu, 2020) , affecting, amongst others, the kidney. (Ahmadian et al., 2021) Acute kidney injury (AKI), potentially resulting from cytokine storm (Chong and Saha, 2021) , is a known complication of COVID-19 and it has also been proposed that decline in renal function in hospitalized patients is caused by the virus itself. (Lynch and Tang, 2020) Even before the SARS-CoV-2 pandemic, AKI was a significant medical and socioeconomic burden, with estimated one in three intensive care patients suffering from decline in kidney function. (Hoste et al., 2018) In addition to other mechanisms, SARS-CoV-2 was shown to able to infect kidney epithelium, directly contributing to organ damage. (Braun et al., 2020; Peng et al., 2020; Su et al., 2020; Sun et al., 2020) It is known, that its infectivity depends on a receptor, Angiotensin-Converting Enzyme 2 (ACE2). (Hoffmann et al., 2020) Physiologically, ACE2 serves as an element of Renin-Angiotensin-Aldosterone system and Bradykinin system. (Donoghue et al., 2000; Tipnis et al., 2000) In SARS-CoV-2 infection, the viral spike protein binds ACE2 and facilitates viral entry into cells. ACE2 expression has been detected in the kidney (Sungnak et al., 2020) and proximal tubules via single cell transcriptome analysis. He et al., 2020) However, transcriptional regulation of ACE2 and its expression pattern in the kidney are poorly understood. Human studies indicate, that changes in ACE2 expression are linked to type 2 diabetic J o u r n a l P r e -p r o o f nephropathy (Mizuiri et al., 2008) , IgA nephropathy (Mizuiri et al., 2011) , hypertension (Koka et al., 2008) and nephrosclerosis. (Wang et al., 2010) Usually, decrease in ACE2 is associated with disease, which may dysregulate ACE/ACE2 ratio, though both ACE and ACE2 may be regulated by independent pathways. (Mizuiri and Ohashi, 2015) Recently, a new isoform of ACE2, deltaACE2 (dACE2) was identified in several cell types. (Blume et al., 2020; Fignani et al., 2020; Lee et al., 2021; Ng et al., 2020; Onabajo et al., 2020) Contrary to earlier reports (Ziegler et al., 2020) , where ACE2 was suggested to be an interferon stimulated gene (ISG), it's dACE2 expression that appears to be significantly regulated by cytokine or viral stimulation. In fact, in some cells, like pancreatic β-cells, dACE2 may be the prevalent isoform even at the baseline. (Fignani et al., 2020) Usually, decrease in ACE2 expression is linked with disease progression, however, it is unknown whether dACE2 has an impact on these readouts, as methods used to this date assessed ACE2 without discerning between isoforms. Additionally, increased ACE2 levels were found in several animal models of kidney disease, and contribution of dACE2 to these changes remains to be assessed. (Moon et al., 2008) Here, for the first time, we show global transcriptional regulation in cytokine-stimulated human primary proximal tubule (HPPT) cells. We assess overlaps between responses to IFNα, IFNβ and IFNγ, we compare IFN-stimulated genetic programs to available AKI and COVID-19 datasets to investigate shared pathways in renal response to injury. We show interferoninducible genetic pathways unique for the kidney and shared with other human tissues. We assess interferon stimulated gene downregulation by JAK inhibitor ruxolitinib, and, finally, describe in detail ACE2 locus in renal proximal tubule cells. J o u r n a l P r e -p r o o f 4 These findings provide in depth understanding of interferon-mediated immune responses in the kidney, especially in context of ACE2 activation observed in SARS-CoV-2 infection and may serve as a basis for better understanding of the commonalities and differences between cytokine stimulation of various tissues. J o u r n a l P r e -p r o o f To investigate renal cytokine-induced genetic programs, we conducted unbiased RNA-seq analyses from HPPT cells treated for 12 hours with IFN, IFNβ, IFN or IL-1β. 746 genes were significantly induced by IFN, 1169 by IFNβ, 1280 by IFN and 2190 by IL-1β (Tables S1-2). Next, we investigated the degree of interferon response overlap. IFN induced expression of 58 unique genes, while IFNβ and IFN induced 482 and 710 genes, respectively ( Figure 1A ). The overlap between all three interferons (320 genes) was enriched for interferon response genes ( Figure 1B and Table S3 ), while gene sets unique for IFNβ, and IFN were more diverse ( Figure 1C , D). Next, we focused on IFNβ. It statistically significantly altered the most diverse signaling pathways as identified by GSEA (Table S3) , it is also a known antiviral used against COVID-19. Additionally, several public transcriptomic data sets from cells treated with IFNβ are available to help elucidate interferon-regulated genetic programs specific for renal epithelium. First, we compared whether expression patterns in acute kidney injury (Park et al., 2020) and severe COVID-19 (Desai et al., 2020) patients bear resemblance to those stimulated in HPPT by IFN. To our knowledge, only one RNA-seq dataset with human ischemia-reperfusion AKI data is publicly available. (Park et al., 2020) Similarly, only one renal dataset from COVID-19 patients could be found for our comparison, differentiating between severe and non-severe disease. (Desai et al., 2020) IFNβ stimulation of HPPT resulted in upregulation of 981 unique genes compared to other conditions (Figure 2A, B) . Acute kidney injury resulted in increased expression of 2566 genes including 156 that were shared with IFNβ-stimulated HPPT (Figure 2A , C; Table S3 ). Expression of 35 genes was induced in both severe COVID-19 and IFNβ-treated HPPT ( Table S3 ). Although more genes were shared between IFNβ-HTTP and AKI than between IFNβ-J o u r n a l P r e -p r o o f 6 HPPT and COVID-19, genes involved in the interferon signaling pathways were preferentially activated in IFNβ-HPPT and COVID-19 than in IFNβ-HPPT and AKI ( Figure 2C , D). We also visualized the genes identified as involved in interferon-signaling pathway and overlapping between conditions to see whether similar fold increases in expression can be observed ( Figure 2E , F). The degree of gene induction varied between datasets, possibly reflecting differences in sample type and technical preparation. Next, to elucidate cell-specific and common genes induced by IFNβ in multiple cell lines, we compared our HPPT data (12-hour in vitro IFNβ treatment) with similarly treated human primary lung epithelium Table S2 ). Extended GSEA analyses for all data presented here can be found in Table S3 . Recent research (Blume et al., 2020; Lee et al., 2021; Ng et al., 2020; Onabajo et al., 2020) revealed the presence of an alternative promoter expressing deltaACE2 (dACE2), a short isoform of ACE2, within intron 9 of the ACE2 gene. Although some studies found the presence of dACE2 RNA in healthy kidney tissue and tumors (Ng et al., 2020; Onabajo et al., 2020) , its structure, function and the presence of regulatory elements, as well as cytokine-inducibility in kidney cells have not been investigated. First, we assessed the expression levels of ACE2 and dACE2 mRNA after cytokine treatment using qRT-PCR ( Figure 5 , Figure S1 ). We analyzed the expression of total ACE2, serine protease TMPRSS2 (which primes viral S protein) and the transcription factor STAT1 to investigate JAK/STAT pathway activation ( Figure 5A -C, Figure S1 ). While ACE2 mRNA was increased 6-and 13-fold by IFNα and IFNβ respectively, expression of the serine protease TMPRSS2 was not affected by them, but rather was elevated by IL-1β, indicating its regulation by an independent pathway. Expression of STAT1 was strongly upregulated after interferon treatment. To examine the expression changes of full length dACE2 (flACE2) and dACE2 by IFNs, we performed qRT-PCR with isoform-specific primers ( Figure 5D , E). While flACE2 was elevated 3-fold, a 300-, 590-and 27-fold upregulation of dACE2 was detected upon IFNα, IFNβ and IFNγ treatments, respectively. Similar increase in gene expression was observed in the studies cited above (Table S4) . To investigate whether flACE2 and dACE2 are regulated through the JAK/STAT pathway by interferon signaling, we used the JAK inhibitor ruxolitinib ( Figure 5F -G, Figure S1 ). dACE2 and J o u r n a l P r e -p r o o f STAT1 levels elevated by IFNβ were ablated by ruxolitinib treatment, while no significant changes to full length ACE2 expression were observed. To understand the regulation of the ACE2 locus by IFNβ, and to identify putative genetic control elements of dACE2 in human primary proximal tubules, we conducted ChIP-seq ( Figure 6A -E) for H3K27ac (active chromatin), H3K4me1 (enhancers), H3K4me3 (promoter marks) and RNA polymerase II loading (Pol II), as well as used available DNase hypersensitive sites (DHS) dataset. (Thurman et al., 2012) Candidate regulatory elements were identified at upstream and intronic regions of the ACE2 locus ( Figure 6A -C). H3K27ac marks and Pol II loading were enriched in the alternative exon 1c in intron 9, the first coding exon of dACE2. An increase in RNA-seq reads was detected posttreatment, supporting the potential for presence of a regulatory element ( Figure 6C , F, Figure S2 ). In contrast, full length ACE2 promoter marks, which seem to be more pronounced in the kidney than in the lung , were reduced by IFNβ stimulation. The STAT1 locus served as a control for the ChIP-seq and after interferon treatment increased H3K4me3 promoter marks and Polymerase II binding can be seen, reflecting gene activation ( Figure 6D ). To confirm the presence of dACE2, we amplified and sequenced the novel dACE2 transcript and confirmed that exon 1c is spliced to exon 10 of ACE2 (Ng et al., 2020; Onabajo et al., 2020) ( Figure S2A ). Two TATA-box like sequences were identified, suggesting the presence of more than one TSS associated with the intronic promoter ( Figure S2B ). Additionally, strong H3K27ac marks induced by IFN were detected around exon 11 of ACE2. These marks are less pronounced in lung cells. In turn, two putative enhancer elements reported at the site corresponding to 3' end of ACE2 gene in lung cells seem to be weaker in the kidney. RNA-seq analyses J o u r n a l P r e -p r o o f 9 demonstrated 5-fold IFNβ-induced expression of exon 1c, compared to exon 1a, which harbors the first methionine of the full length ACE2 ( Figure 6F , Figure S2C ). Finally, in addition to the ACE2 and TMEM27 promoters, a candidate enhancer element can be seen between the two genes, as indicated by H3K4me1 marks. Additionally, an analysis of the extended ACE2 locus revealed that ACE2 and TMEM27 are under similar interferon regulation and are bordered by CTCF chromatin boundaries suggesting that they are part of a regulatory unit ( Figure S3 ). The TMEM27 locus displayed increased H3K27ac and H3K4me3 promoter marks indicating gene activation after IFNβ treatment ( Figure 6E ). Our study presents a broad overview of genetic programs stimulated by interferons in renal proximal tubules and compare them to other transcriptomic data. We show robust cytokine response with 1169 genes significantly induced by IFNβ and efficient quenching of gene expression by JAK inhibitor ruxolitinib. Some of those genes are known regulators of renal injury, belonging to divergent pathways, either driving inflammation like IRF1 or TLR4 (Wang et al., 2009; Wu et al., 2007) or attenuating it like IL4 and IL15 signaling. (Eini et al., 2010; Zhang et al., 2017) There is evidence that type I interferons may contribute to renal damage after ischemic AKI, suggesting that common pathways between IFN treated HPPT and AKI could be found. (Freitas et al., 2011) Conversely, we expected only a small overlap with SARS-CoV-2 -induced genes, as IFNβ has antiviral activity. While we indeed found that interferon stimulation and AKI shared more upregulated genes, interferon-treated cells and COVID-19 samples shared more genes identified as interferon signaling-related by GSEA analysis. This may not reflect overall trend due to diversity of AKI and only suggest the degree of similarity with ischemia-reperfusion. We also show uniqueness of renal response when compared to lung and liver, with over half of the genes upregulated in the kidney being tissue specific. We didn't observe significant regulation of TMPRSS2, protease involved in SARS-CoV-2 infection, by interferons. Instead, we saw upregulation of TMPRSS2 expression after IL-1β treatment. Both IL-1β and TMPRSS2 were reported to be downregulated in nasal basal epithelium after azithromycin treatment (Renteria et al., 2020) , reinforcing potential for the link between them. Our study of ACE2 locus revealed co-regulation of ACE2 and TMEM27, which may have additional significance for the kidney, as While our study demonstrates that dACE2 expression is activated by interferon treatment, further work is needed to identify whether viral infection enhances dACE2 expression in the kidney. Although several studies have identified dACE2 after SARS-CoV-2 infection in vitro, its biological role remains unknown. Based on lung epithelium cell data, it is proposed that its extracellular enzymatic and viral spike protein-binding domains are truncated, resulting in partial loss of its carboxypeptidase function. The dACE2 promoter may be a remnant of a retroviral ISG. (Ng et al., 2020) Blume (Blume et al., 2020) report lack of increase of ACE2 or dACE2 after SARS-CoV-2 stimulated BCi-NS1.1 lung cells. Onabajo (Onabajo et al., 2020) similarly show lack of their upregulation in lung Calu3 cell line, but colon cancer Caco-2 and T84 lines exhibited slightly increased dACE2 expression after SARS-CoV-2 exposure. This may in part be due to tissue-specific cytokine regulation of ACE2 and dACE2. Standardized and validated detection method of both ACE2 isoforms, as well as understanding of regulatory elements present in ACE2 locus is necessary to forward this topic. This is especially true for studies at the protein level, as detection methods such as Western blot are contradictory between reports. (Blume et al., 2020; Ng et al., 2020) In our attempts to investigate protein levels of dACE2 using Western blot, we were able to observe a 50 kDa band, however its presence and intensity was not consistent between various anti-ACE2 antibodies (data not shown). We summarized current knowledge on factors causing dACE2 upregulation in Table S4 . In our study, we present an in-depth analysis and comparison of interferon-stimulated human proximal tubule cells and other experimental datasets, providing insight into genetic pathways driving response to stimuli affecting renal health. In addition, by comparing our datasets to other, similarly treated cells, we show unique renal regulation of interferon response. We also identified several putative regulatory elements controlling ACE2, as well as confirmed the presence of dACE2 in renal epithelium. We describe reliance of dACE2 expression on the JAK/STAT pathway, which may be of clinical importance, as JAK inhibitors are currently used to treat COVID-19. (Cao et al., 2020) Our study strengthens current knowledge about cytokine signaling in renal epithelium and we believe that it can become a basis for further transcriptomic studies reaching beyond the current efforts to thwart and understand the COVID-19 pandemic. CXCL chemokine family and (H) Janus kinase 2 measured by RNA-seq. Individual data points as well as mean ± SEM of independent biological replicates (n = 3-6) are shown. Significance was analyzed with one-way ANOVA followed by Tukey's multiple comparisons test. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. See also Tables S1-3. inhibitor ruxolitinib or vehicle, alone or together with IFNß. Individual data points as well as mean ± SEM of independent biological replicates (n = 3) are shown. One-or two-way ANOVA followed by Tukey's multiple comparisons test was used to evaluate the statistical significance of differences relative to untreated cells. ****P < 0.0001. See also Figures S1-2. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Lothar Hennighausen (lotharh@nih.gov). This study did not generate new unique reagents. The original RNA-seq and ChIP-seq data from human primary proximal tubule cells were and GSE68976, respectively. RNA-seq data for IFNβ-stimulated lung and liver cell were obtained from GSE161665 and GSE115198. Human AKI and COVID-19 data was found under GSE142077 and GSE150316 respectively. Hi-C data from human adrenal gland tissues was obtained from Hi-C data browser (http://3dgenome.fsm.northwestern.edu/view.php). Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request. Cells were obtained at passage 2, cultured according to manufacturer's instructions and used between passages 4 and 6. In addition to characteristic cobblestone growth pattern when confluent, cells were confirmed to express several proximal tubule markers including yglutamyltransferase-1 and SLC3a1 as assessed with RNA-seq. (Lee et al., 2015) Method Details Cells were stimulated with IFNα (Stem Cell Technologies), IFNβ, IFNγ, TNFα, IL-6 and IL-1β (all obtained from Peprotech) for 12 hours in concentration of 10 ng/ml. Cells were treated with ruxolitinib (Peprotech) at 10 µM for 12 hours together with IFNβ. At least three biological replicates were prepared for all experiments. After cytokine stimulation, cells were washed twice with PBS before RNA isolation to remove medium and debris. mRNA was isolated using PureLink™ RNA Mini Kit (Invitrogen) and 500 ng was transcribed into cDNA using SuperScript™ III First-Strand Synthesis SuperMix (Invitrogen). ACE2 PCR was performed with cDNA obtained as described above. 50ng of cDNA was used in the following reaction: initial denaturation -3 minutes, 98 o C and 35 cycles of denaturation -30 seconds at 98 o C, annealing -30 seconds at 58 o C, extension -72 o C for 2 minutes, ending with final extension of 72 o C for 10 minutes. Amplified fragments were run on a 1.5% agarose in 1xTAE gel with 100 kb DNA ladder to assess product size. Bands were cut out and PCR products cleaned with MinElute Gel Extraction Kit (Quiagen) and Sanger sequenced by Quintara Biosciences. Primers used: dACE2 forward: 5'-TGTGAGAGCCTTAGGTTGGATTCC-3', dACE2 reverse: 5'-TCTCTCCTTGGCCATGTTGT-3'. (Onabajo et al., 2020) RNA-seq library preparation and data analysis J o u r n a l P r e -p r o o f mRNA was prepared as described above and quality assessed with Bioanalyzer 2100 (Aligent). Prep Kit according to manufacturer's instructions. Libraries were pooled in equimolar amounts and sequenced with HiSeq 2000 (Illumina). The raw data were subjected to QC analyses using the FastQC tool (version 0.11.9) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Trimmomatic (version 0.36) (Bolger et al., 2014) was used to assess total RNA-seq read quality and STAR RNA-seq (version 2.5.4a) (Dobin et al., 2013) using 50bp paired-end mode was used to align the reads (hg19). HTSeq was used to retrieve the raw counts and R package DESeq2 Love et al., 2014) was used to normalize data. Additionally, the RUVSeq (Risso et al., 2014) package was applied to remove confounding factors. Minimum of five reads was an additional basis for filtering artifacts. The visualization was done using dplyr (https://CRAN.Rproject.org/package=dplyr) and ggplot2. (Risso et al., 2014) Significantly differential expressed genes with an adjusted p-value (pAdj, FDR) below 0.05 and a fold change > 2 for up-regulated genes were categorized using GSEA (https://www.gsea-msigdb.org/gsea/msigdb). Sequence read numbers were calculated using Samtools (Li et al., 2009 ) software with sorted bam files. Cells were washed twice with PBS and fixed with 0.75% formaldehyde in DMEM for 10 minutes in room temperature. Next, glycine was added to quench fixation in a final concentration of 125 mM and plates were incubated in room temperature for another 10 minutes. Cells were then scraped and centrifuged at 4 o C, 1 minute, 3000 rpm, then washed twice with cold PBS. Pellets J o u r n a l P r e -p r o o f were re-suspended in 2 ml Farnham Lysis Buffer with protease inhibitors and incubated on ice for 10 minutes. Then, the cells were pelleted again at 4 o C, 5 minutes, 3500 rpm, and resuspended in TE buffer with protease inhibitors. Chromatin was sonicated for 3 minutes with a probe sonicator (Active Motif). Finally, after centrifugation at 4 o C, 13000 g for 10 minutes, supernatant was used for immunoprecipitation. Briefly, 600-1000 µg chromatin was incubated with antibody-coated Dynabeads™ Protein (Thorvaldsdottir et al., 2013) was used for visualization. Statistical analysis of data was performed with Prism 8. First, normal distribution of data was assessed. Next, statistical significance was evaluated with 1-way or 2-way AVOVA followed by Tukey's multiple comparisons, or a T-test, depending on experimental setup. n and points on a graph always represent biological replicates -seeded wells of a 6-well culture plate. Values of: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 were considered statistically significant. Figures 1-3 as well as ruxolitinib treatment data. The authors declare no competing interests. Covid-19 and kidney injury: Pathophysiology and molecular mechanisms HTSeq--a Python framework to work with high-throughput sequencing data A novel isoform of ACE2 is expressed in human nasal and bronchial respiratory epithelia and is upregulated in response to RNA respiratory virus infection. bioRxiv Trimmomatic: a flexible trimmer for Illumina sequence data SARS-CoV-2 renal tropism associates with acute kidney injury Ruxolitinib in treatment of severe coronavirus disease 2019 (COVID-19): A multicenter, singleblind, randomized controlled trial Localization of Cell Receptor-Related Genes of SARS-CoV-2 in the Kidney through Single-Cell Transcriptome Analysis Relationship Between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and the Etiology of Acute Kidney Injury (AKI) Temporal and spatial heterogeneity of host response to SARS-CoV-2 pulmonary infection STAR: ultrafast universal RNA-seq aligner A novel angiotensin-converting enzyme-related carboxypeptidase (ACE2) converts angiotensin I to angiotensin 1-9 SARS-CoV-2 receptor Angiotensin I-Converting Enzyme type 2 (ACE2) is expressed in human pancreatic β-cells and in the human pancreas microvasculature. bioRxiv Type I interferon pathway mediates renal ischemia/reperfusion injury COVID-19 acute respiratory distress syndrome (ARDS): clinical features and differences from typical pre-COVID-19 ARDS Single-cell RNA sequencing analysis of human kidney reveals the presence of ACE2 receptor: A potential pathway of COVID-19 infection. Molecular genetics & genomic medicine Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor Global epidemiology and outcomes of acute kidney injury Orchestrating high-throughput genomic analysis with Bioconductor Immunopathogenesis and treatment of cytokine storm in COVID-19 Angiotensin II upregulates angiotensin I-converting enzyme (ACE), but down-regulates ACE2 via the AT1-ERK/p38 MAP kinase pathway Ultrafast and memory-efficient alignment of short DNA sequences to the human genome JAK inhibitors dampen activation of interferonstimulated transcription of ACE2 isoforms in human airway epithelial cells Deep Sequencing in Microdissected Renal Tubules Identifies Nephron Segment-Specific Transcriptomes The Sequence Alignment/Map format and SAMtools Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 COVID-19 and Kidney Injury Increased ACE and decreased ACE2 expression in kidneys from patients with IgA nephropathy Expression of ACE and ACE2 in individuals with diabetic kidney disease and healthy controls ACE and ACE2 in kidney disease COVID-19 and multiorgan failure: A narrative review on potential mechanisms Renal ACE and ACE2 expression in early diabetic rats Tissue-specific and interferon-inducible expression of nonfunctional ACE2 through endogenous retroelement co-option Interferons and viruses induce a novel truncated ACE2 isoform and not the full-length SARS-CoV-2 receptor RNA-Seq identifies condition-specific biological signatures of ischemia-reperfusion injury in the human kidney SARS-CoV-2 can be detected in urine, blood, anal swabs, and oropharyngeal swabs specimens Normalization of RNA-seq data using factor analysis of control genes or samples Renal histopathological analysis of 26 postmortem findings of patients with COVID-19 in China Isolation of infectious SARS-CoV-2 from urine of a COVID-19 patient SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes Integrative Genomics Viewer (IGV): highperformance genomics data visualization and exploration The accessible chromatin landscape of the human genome A human homolog of angiotensin-converting enzyme. Cloning and functional expression as a captopril-insensitive carboxypeptidase SARS-CoV-2 and coagulation disorders in different organs Intrarenal expression of miRNAs in patients with hypertensive nephrosclerosis SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues