Activation of Interferon-Stimulated Transcriptomes and ACE2 Isoforms in Human Airway Epithelium Is Curbed by Janus Kinase Inhibitors

Activation of Interferon-Stimulated Transcriptomes and ACE2 Isoforms in Human Airway Epithelium Is Curbed by Janus Kinase Inhibitors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Activation of Interferon-Stimulated Transcriptomes and ACE2 Isoforms in Human Airway Epithelium Is Curbed by Janus Kinase Inhibitors Hye Kyung Lee, Olive Jung, Lothar Hennighausen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-119695/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Jun, 2021 Read the published version in Communications Biology → Version 1 posted You are reading this latest preprint version Abstract SARS-CoV-2 infection of human airway epithelium activates genetic programs that lead to progressive hyperinflammation in COVID-19 patients. Here we report on genetic programs activated by interferons and the suppression by Janus kinase (JAK) inhibitors. The angiotensin-converting enzyme 2 (ACE2) is the receptor for SARS-CoV-2 and deciphering its regulation is paramount for understanding the cell tropism of SARS-CoV-2 infection. We identified candidate regulatory elements in the ACE2 locus in human primary airway cells and lung tissue. Activating histone and promoter marks and Pol II loading characterize the intronic dACE2 and define novel candidate enhancers distal to the genuine ACE2 promoter and within additional introns. dACE2, and to a lesser extent ACE2, RNA levels increased in primary cells treated with interferons and this induction was mitigated by JAK inhibitors that are used therapeutically in COVID-19 patients. Our analyses provide insight into ACE2 regulatory elements and highlight JAK inhibitors as suitable tools to suppress interferon-activated genetic programs in bronchial cells. Physiology Bioinformatics Medical Genetics Cell Communication and Signaling COVID-19 ACE2 JAK Figures Figure 1 Figure 1 Figure 2 Figure 2 Figure 3 Figure 3 Figure 4 Figure 4 Figure 5 Figure 5 Introduction The angiotensin-converting enzyme 2 (ACE2) receptor is the gateway for SARS-CoV-2 to airway epithelium 1,2 and the strong inflammatory response after viral infection is a hallmark in COVID-19 patients. Single cell RNA sequencing (scRNA-seq) studies have revealed that ACE2 expression in type II pneumocytes is induced by interferons 3 , suggesting that the presence of an autoregulatory loop could result in increased viral infection. Recent studies 4,5 have identified a novel short form of ACE2, called dACE2, that originates from an intronic promoter activated by interferons, calling into question that transcription of the full length native ACE2 is under interferon control. Onabajo et al. 5 used ENCODE data for chromatin modification marks (H3K4me3, H3K4me1 and H3K27ac) as well as DNase I hypersensitive (DHS) sites in cell lines to label putative regulatory elements at the newly identified exon (ex1c) located within intron 9 of the ACE2 gene. However, no regulatory elements were detected in the vicinity of the 5’ end of the full-length transcript encoding biologically active ACE2, and in sequences distal to the genuine promoter. Since these data sets were obtained from a wide range of cell lines and not from human primary airway cells, the principal target of SARS-CoV-2, they might not present a comprehensive picture of the regulatory regions controlling expression of the dACE2 and the full-length ACE2 transcripts in bronchial tissue. Janus kinase (JAK) inhibitors suppress signal transduction pathways that lead to immune activation and inflammation and they are used therapeutically to harness cytokine storm in COVID-19 patients 6,7 . However, the genetic programs activated in airway cells by interferons and their response to JAK inhibitors remain to be elucidated. In this study we pursued two linked goals. We used genome-wide chromatin profiling and RNA-seq analyses to identify the regulation of ACE2 and dACE2 gene expression in human primary airway cells and we investigated the ability of JAK inhibitors to blunt interferon-activated genetic programs. Results Interferons regulate the ACE2 locus in human airways cells To comprehensively identify the genetic elements controlling the extended ACE2 locus, with an emphasis on its interferon response, we focused on human primary Small Airway Epithelial Cells (SAEC), which express a wide range of cytokine receptors and key mechanistic components of the executing JAK/STAT signal transduction pathway (Supplementary Table 1). We stimulated SAECs with interferon type I (IFNa and IFNb), type II (IFNg) and type III (IFNl) as well as with growth hormone (GH), Interleukin 6 (IL6) and IL7, followed by RNA-seq transcriptome analyses (Supplementary Tables 2–8). Increased ACE2 expression was obtained with the interferons but not with GH, IL6 and IL7 (Fig. 1a). However, the induction was less than that seen for classical interferon stimulated genes (ISG), such as STAT1 , ISG15 and ISG20 (Fig. 1b-c). In agreement with earlier studies 4,5 , we detected the novel dACE2 N-terminal exon (ex1c) within intron 9 of the ACE2 gene (Fig. 1d). To obtain additional information on the interferon response of the dACE2 and ACE2 promoters, we used RNA-seq and determined the respective read counts over the three alternative first exons (Fig. 1d-e). While the increase of RNA-seq reads induced by IFNa/b was highest (~ 25-fold) over ex1c, a lesser, yet significant, ~ 2-10-fold increase was detected over ex1a and ex1b, supporting the notion that expression of the full-length ACE2 transcript is also under interferon control. As an independent assay we used qRT-PCR and determined that IFN a/b stimulation led to an 8 to 15-fold increase of dACE2 (ex1c) and an approximately ~ 3-fold increase of ACE2 RNA (ex9) (Fig. 1f). However, the degree of induction of either form was lower than that seen for bona fide ISGs. Previous studies in normal human bronchial epithelium (NHBE) did not reveal an interferon response of the native ACE2 promoter 4,5 suggesting differences between cell types or growth conditions. The mouse Ace2 gene is also induced by cytokines through a STAT5-based enhancer in the second intron 8 and a DHS site is located in the equivalent location in the human ACE2 gene in SAEC and lung tissue. This suggests the presence of additional regulatory elements controlling expression of the full-length ACE2 mRNA. Interferons activate STAT enhancers in the ACE2 locus To identify candidate regulatory elements controlling the extended ACE2 locus, including ACE2 and dACE2 , in primary airway cells, we dug deeper and conducted ChIP-seq for the chromatin marks H3K27ac (activate loci), H3K4me1 (enhancers), H3K4me3 (promoters) and Polymerase II (Pol II) loading, both in the absence and presence of IFNb (Fig. 2). DNase I hypersensitive (DHS) sites from human lung tissues 9 and SAECs 10 served as bona fide predictors of regulatory regions. In addition to ACE2 , the neighboring TMEM27 gene, an ACE2 homologue, as well as BMX are activated by interferons (Fig. 2a) suggesting the possibility of jointly used regulatory elements. ACE2 and TMEM27 originated from a gene duplication and their response to interferon is equivalent. The positions of the chromatin boundary factor CTCF suggests that ACE2 and TMEM27 are located within a sub-TAD (Fig. 2a). In agreement with earlier studies 5 , we identified DHS sites at ex1c and in intron 17 (Fig. 2b). In addition, we identified DHS sites at ex1a, likely marking the genuine ACE2 promoter, a distal site marking a possible enhancer and in intron 15 coinciding with activate marks. The DHS site in intron 9 overlaps with strong H3K4me3 marks, identifying it as a genuine promoter region (Fig. 2b). This site is also decorated with H3K4me1 and H3K27ac marks and extensive Pol II loading, hallmarks of a complex promoter/enhancer. H3K27ac and Pol II loading was further induced by IFNb, reflecting increased ACE2 expression. IFNb activates the transcription factors STATs 1, 2 and 5 (Fig. 1b and Supplementary Table 3) and ChIP-seq experiments from K562 erythroid cells stimulated with IFNb 11 revealed preferential binding of STAT5 to the intronic promoter/enhancer (Fig. 2c) further supporting regulation through the JAK/STAT pathway. The STAT1 locus served as a control for the binding of STAT transcription factors (Fig. 2d). While the ACE2 promoter associated with ex1a is marked by a DHS site and H3K4me1 marks, there is little evidence of H3K4me3 and H3K27ac marks. However, it is well known that there is no direct relationship between gene activity and the presence of these marks. Based on the presence of DHS sites, activating chromatin marks and Pol II loading, either in combination or by themselves, we predict additional enhancers. A prominent candidate enhancer, marked by a DHS, H3K4me1 and Pol II loading is positioned approximately 16 kb distal of ex1a and additional putative regulatory regions are located with introns (Fig. 2b). Activating histone marks and DHS sites 9,10 are also present in the genuine ACE2 promoter and the distal region as well as the regulatory elements of ISG, such as STAT1 and ISG15, in human lung tissues (Fig. 3). JAK inhibitors suppress the IFNb-sensing enhancers in the ACE2 locus Interferons activate genetic programs through the JAK/STAT signaling pathway and JAK inhibitors are used clinically in COVID-19 patients in an effort to suppress the genomic consequences of cytokine storms 6,12,13 . To investigate if interferon-induced ACE2 expression is controlled by the JAK/STAT pathway, we cultured SAECs in the presence of IFNb and the JAK inhibitors, Baricitinib and Ruxolitinib, followed by RNA-seq and qRT-PCR assays (Fig. 4a-c and Supplementary Tables 9–10) and ChIP-seq analyses (Fig. 4e-h). Both inhibitors suppressed the IFNb-induced increase of the full-length ACE2 (ex1a, ex1b and ex9) and the dACE2 (ex1c) transcripts (Fig. 4a-b), supporting that their respective promoters are under JAK/STAT control. The efficacy of the two inhibitors extended to a range of genetic programs activated through the pan JAK/STAT pathway (Figs. 4c) and induction of bona fide interferon stimulated genes (ISG), such as ISG15 , was suppressed (Fig. 4d). In ACE2 , as in other ISGs, Ruxolitinib treatment mitigated the establishment of activating H3K27ac marks and Pol II loading over distal and intronic regulatory elements (Fig. 4e-h). Gene Set Enrichment Analysis (GSEA) of RNA-seq profiles showed, depending on the interferon, between 17% and 26% of the induced genes were linked to immune responses, like IFNg/a response, TNFa signaling, inflammatory response, IL-JAK/STAT signaling, among others (Fig. 5a and Supplementary Table 2–5). Both JAK inhibitors led to a suppression of immune signaling pathways and IFNb-induced gene activation (Fig. 5b), including both forms of ACE2 transcripts (Fig. 4b). These data suggest that JAK inhibitors have the potential to relieve COVID-19 symptoms induced by interferon-STAT1 that contribute to the COVID-19 pathogenesis 14 . Discussion SARS-CoV-2 entry into cells is facilitated by ACE2 and deciphering the regulation of the ACE2 gene will aid our understanding of the viral tropism and also non-pulmonary pathology. Here, we have assessed the extended ACE2 locus for regulatory elements controlling gene expression induced by interferons and other, not yet defined, stimuli. We show that the intronic regulatory region bears promoter and enhancer marks and binds STAT transcription factors, thus constituting a complex regulatory element controlling interferon-induced dACE2 expression 5 . We also identified additional candidate regulatory elements throughout the locus that can be invoked in controlling transcription of the full-length transcripts yielding the biologically active ACE2. Regulation of the human and mouse ACE2 8 loci displays distinct differences, yet they share their response to cytokines and the JAK/STAT pathway, with the mouse Ace2 gene being activated in mammary tissue by cytokines through an intronic enhancer 8 . Further studies in tissues and primary cells are needed to better understand the complex, possibly cell-specific, regulation of the human ACE2 locus in organs with extrapulmonary manifestations of SARS-CoV-2 infection. Our demonstration that JAK inhibitors mitigate interferon-induced activation of inflammatory programs has practical implications for their use in treating COVID-19 patients. Methods Cell culture. Human small airway epithelial cells (SAEC) obtained from Lifeline Technology (FC-0016) were expanded using the complete BronchiaLife™ media kit (Lifeline Technology, LL-0023). All culture wares were pre-coated in 30 µγ/ml of Fibronectin (ThermoFisher Scientific, 33016015) for at least 1 h at room temperature. Calu-3 line (ATCC, HTB-55™) were cultured using Eagle’s Minimum Essential Medium (ATCC, 30-2003™) containing 10% fetal bovine serum (Cytiva, SH3007103) in 5% CO2 atmosphere at 37 °C. Cytokines (10 ng/ml; Human IFNb, 300-02BC; Human IFNg, 300-02; Human IL6, 200-06; Human IL7, 200-07; Human Growth hormone, 100 − 40, Peprotech; Human IFNa2b, 78077.1, Stem Cell Technologies; Human IFNl3, 5259-IL-025, R&D systems) were treated in respective culture media and the cells were incubated for 12hr in 5% CO2 atmosphere at 37 °C. The cells were washed with PBS (Gibco, 14190144) twice and harvested. Jak inhibitors, 10 µΜ of either Baricitinib (HY-15315A, MedChemExpress) or Ruxolitinib (HY-50856A, MedChemExpress), were added to BronchiLiafe™ media with or without IFNb. SAEC and incubated for 12hrs and then washed with PBS twice and harvested. RNA isolation and quantitative real-time PCR (qRT–PCR). Total RNA was extracted from the collected cells and purified using the PureLink RNA Mini Kit (Invitrogen) according to the manufacturer’s instructions. cDNA was synthesized from total RNA using Superscript II (Invitrogen). Quantitative real-time PCR (qRT-PCR) was performed using TaqMan probes (ACE2, Hs01085333_m1; STAT1 , Hs01013996_m1; GAPDH , Hs02786624_g1, Thermo Fisher scientific) on the CFX384 Real-Time PCR Detection System (Bio-Rad) according to the manufacturer's instructions. Exon9 and exon1c mRNA were measured with the following primers, that were used by Onabajo et al. 5 , using SYBR Green system: Forward, 5’-GGGCGACTTCAGGATCCTTAT-3’, Reverse, 5’-GGATATGCCCCATCTCATGATGG-3’; Forward, 5’-GGAAGCAGGCTGGGACAAA-3’, Reverse, 5’-AGCTGTCAGGAAGTCGTCCATTG-3’. PCR conditions were 95 °C for 30 s, 95 °C for 15 s, and 60 °C for 30 s for 40 cycles. All reactions were done in triplicate and normalized to the housekeeping gene GAPDH . Relative differences in PCR results were calculated using the comparative cycle threshold ( C T ) method. Total RNA sequencing (Total RNA-seq) and data analysis. Total RNA was extracted from the collected cells and purified using the PureLink RNA Mini Kit (Invitrogen) according to the manufacturer’s instructions. Ribosomal RNA was removed from 1 µg of total RNAs and cDNA was synthesized using SuperScript III (Invitrogen). Libraries for sequencing were prepared according to the manufacturer’s instructions with TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (Illumina, RS-122-2301) and paired-end sequencing was done with a HiSeq 3000 instrument (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/). Total RNA-seq read quality control was done using Trimmomatic 15 (version 0.36) and STAR RNA-seq 16 (version STAR 2.5.4a) using 50 bp paired-end mode was used to align the reads (hg19). HTSeq 17 (version 0.9.1) was to retrieve the raw counts and subsequently, R (https://www.R-project.org/), Bioconductor 18 and DESeq2 19 were used. Additionally, the RUVSeq 20 package was applied to remove confounding factors. The data were pre-filtered keeping only those genes, which have at least ten reads in total. The visualization was done using dplyr (https://CRAN.R-project.org/package=dplyr) and ggplot2 21 . Genes were categorized as significantly differentially expressed with an adjusted p-value (pAdj) below 0.05 and a fold change > 2 for up-regulated genes and a fold change of < -2 for down-regulated ones. Sequence read numbers were calculated using Samtools 22 software with sorted bam files. Chromatin immunoprecipitation sequencing (ChIP-seq) and data analysis. Chromatin was fixed with formaldehyde (1% final concentration) for 15 min at room temperature, and then quenched with glycine (0.125 M final concentration). Samples were processed as previously described 23 . The following antibodies were used for ChIP-seq: H3K27ac (Abcam, ab4729), RNA polymerase II (Abcam, ab5408), H3K4me1 (Active Motif, 39297) and H3K4me3 (Millipore, 07-473). Libraries for next-generation sequencing were prepared and sequenced with a HiSeq 3000 instrument (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/). Quality filtering and alignment of the raw reads was done using Trimmomatic 15 (version 0.36), Bowtie 24 (version 1.2.2) and Samtools 22 (version 1.8), with the parameter ‘-m 1’ to keep only uniquely mapped reads, using the reference genome mm10. Picard tools (Broad Institute. Picard, http://broadinstitute.github.io/picard/. 2016) was used to remove duplicates. Homer 25 (version 4.8.2) and DeepTools 26 (version 3.1.3) software was applied to generate bedGraph files, separately. Integrative Genomics Viewer 27 (version 2.5.3) was used for visualization. Each ChIP-seq experiment was conducted for more than two replicates. DeepTools was used to obtain the Pearson and Spearman correlation between the replicates. Statistical analysis. For comparison of samples, data were presented as standard deviation in each group and were evaluated with a two-way ANOVA followed by Tukey’s multiple comparisons test or a one-way ANOVA with Dunnett’s multiple comparisons test using PRISM 8 GraphPad (version 8.2.0). Statistical significance was obtained by comparing the measures from wild-type or control group, and each mutant group. A value of * P < 0.05, ** P < 0.001, *** P < 0.0001, **** P < 0.00001 was considered statistically significant. Declarations Data availability. All data were obtained or uploaded to Gene Expression Omnibus (GEO). ChIP-seq for STATs was obtained under GSE31477. ChIP-seq data for H3K27ac and H3K4me1 from human lung tissues were downloaded from GSE143115 and 142958. DNase I hypersensitive (DHS) data from human lung tissues and SAEC were obtained under GSE90364 and 29692, respectively. The RNA-seq data and ChIP-seq for SAECs in the presence of cytokines and the JAK inhibitors were uploaded to GSE161665 (ChIP-seq in GSE161663 and RNA-seq in GSE161664). Acknowledgments We thank Ilhan Akan, Sijung Yun and Harold Smith from the NIDDK genomics core for NGS and NCATS Chemical Genomics Center Team for the JAK inhibitors. This work utilized the computational resources of the NIH HPC Biowulf cluster ( http://hpc.nih.gov ). Funding This work was supported by the Intramural Research Programs (IRPs) of National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and National Center for Advancing Translational Sciences (NCATS). Author contribution HKL: project conception, experimental design and execution, data analysis, preparation of figures, writing manuscript; OJ: experimental design and execution; LH: project conception, experimental design, data analysis, preparation of figures, writing manuscript. Competing interests The authors declare no competing financial interests. References Hoffmann, M. et al. SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor. Cell 181 , 271-280 e8 (2020). Lukassen, S. et al. SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells. EMBO J , e105114 (2020). Ziegler, C.G.K. et al. SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues. Cell (2020). Ng, K.W. et al. Tissue-specific and interferon-inducible expression of nonfunctional ACE2 through endogenous retroelement co-option. 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Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell 38 , 576-89 (2010). Ramirez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res 44 , W160-5 (2016). Thorvaldsdottir, H., Robinson, J.T. & Mesirov, J.P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14 , 178-92 (2013). Supplemental Information Supplementary Table legends. Supplementary Table 1. mRNA levels of genes associated with the pan JAK-STAT pathway in SAEC. Supplementary Table 2. List of all genes with normalized read counts in each replicate at Control and IFNa treated SAEC, log 2 (fold change), p -value and adjusted p -value as well as upregulated gene list and GSEA analysis. Supplementary Table 3. List of all genes with normalized read counts in each replicate at Control and IFNb treated SAEC, log 2 (fold change), p -value and adjusted p -value as well as upregulated gene list and GSEA analysis. Supplementary Table 4. List of all genes with normalized read counts in each replicate at Control and IFNg treated SAEC, log 2 (fold change), p -value and adjusted p -value as well as upregulated gene list and GSEA analysis. Supplementary Table 5. List of all genes with normalized read counts in each replicate at Control and IFNl3 treated SAEC, log 2 (fold change), p -value and adjusted p -value as well as upregulated gene list and GSEA analysis. Supplementary Table 6. List of all genes with normalized read counts in each replicate at Control and IL6 treated SAEC, log 2 (fold change), p -value and adjusted p -value as well as upregulated gene list and GSEA analysis. Supplementary Table 7. List of all genes with normalized read counts in each replicate at Control and IL7 treated SAEC, log 2 (fold change), p -value and adjusted p -value as well as upregulated gene list and GSEA analysis. Supplementary Table 8. List of all genes with normalized read counts in each replicate at Control and GH treated SAEC, log 2 (fold change), p -value and adjusted p -value as well as upregulated gene list and GSEA analysis. Supplementary Table 9. List of all genes with normalized read counts in each replicate at IFNb and Baricitinib with IFNb, treated SAEC, log 2 (fold change), p -value and adjusted p -value as well as upregulated gene list and GSEA analysis. Supplementary Table 10. List of all genes with normalized read counts in each replicate at IFNb and Ruxolitinib with IFNb, treated SAEC, log 2 (fold change), p -value and adjusted p -value as well as upregulated gene list and GSEA analysis. Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryTable1.xlsx SupplementaryTable1.xlsx SupplementaryTable10IFNbvsIFNbRuxolitinib.xlsx SupplementaryTable10IFNbvsIFNbRuxolitinib.xlsx SupplementaryTable2ConvsIFNa.xlsx SupplementaryTable2ConvsIFNa.xlsx SupplementaryTable3ConvsIFNb.xlsx SupplementaryTable3ConvsIFNb.xlsx SupplementaryTable4ConvsIFNg.xlsx SupplementaryTable4ConvsIFNg.xlsx SupplementaryTable1.xlsx Supplementary Table 1 SupplementaryTable1.xlsx Supplementary Table 1 SupplementaryTable5ConvsIFNl3.xlsx SupplementaryTable5ConvsIFNl3.xlsx SupplementaryTable2ConvsIFNa.xlsx Supplementary Table 2 SupplementaryTable2ConvsIFNa.xlsx Supplementary Table 2 SupplementaryTable6ConvsIL6.xlsx SupplementaryTable6ConvsIL6.xlsx SupplementaryTable3ConvsIFNb.xlsx Supplementary Table 3 SupplementaryTable3ConvsIFNb.xlsx Supplementary Table 3 SupplementaryTable4ConvsIFNg.xlsx Supplementary Table 4 SupplementaryTable4ConvsIFNg.xlsx Supplementary Table 4 SupplementaryTable7ConvsIL7.xlsx SupplementaryTable7ConvsIL7.xlsx SupplementaryTable5ConvsIFNl3.xlsx Supplementary Table 5 SupplementaryTable5ConvsIFNl3.xlsx Supplementary Table 5 SupplementaryTable8ConvsGH.xlsx SupplementaryTable8ConvsGH.xlsx SupplementaryTable9IFNbvsIFNbBaricitinib.xlsx SupplementaryTable9IFNbvsIFNbBaricitinib.xlsx SupplementaryTable6ConvsIL6.xlsx Supplementary Table 6 SupplementaryTable6ConvsIL6.xlsx Supplementary Table 6 SupplementaryTable7ConvsIL7.xlsx Supplementary Table 7 SupplementaryTable7ConvsIL7.xlsx Supplementary Table 7 SupplementaryTable8ConvsGH.xlsx Supplementary Table 8 SupplementaryTable8ConvsGH.xlsx Supplementary Table 8 SupplementaryTable9IFNbvsIFNbBaricitinib.xlsx Supplementary Table 9 SupplementaryTable9IFNbvsIFNbBaricitinib.xlsx Supplementary Table 9 SupplementaryTable10IFNbvsIFNbRuxolitinib.xlsx Supplementary Table 10 SupplementaryTable10IFNbvsIFNbRuxolitinib.xlsx Supplementary Table 10 Cite Share Download PDF Status: Published Journal Publication published 02 Jun, 2021 Read the published version in Communications Biology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-119695","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":6175014,"identity":"77ad4801-aa36-4394-a6bd-78fb820c648b","order_by":0,"name":"Hye Kyung Lee","email":"","orcid":"https://orcid.org/0000-0002-7785-5942","institution":"National Institute of Diabetes and Digestive and Kidney Diseases","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hye","middleName":"Kyung","lastName":"Lee","suffix":""},{"id":6175015,"identity":"d9f34ddb-89a4-4f2d-a8bf-ff545e497ec1","order_by":1,"name":"Olive Jung","email":"","orcid":"","institution":"National Institutes of Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Olive","middleName":"","lastName":"Jung","suffix":""},{"id":6175016,"identity":"b4384caa-436c-4cd4-bad8-f1af3cfc9af4","order_by":2,"name":"Lothar Hennighausen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBACPgYGNiB1QI6BgbHxAAODRAJBLWwMzGAtxkAtDaRpSWwAkUBMhBb2/mMPfu65k762/XDDAcYdFnkM/IuPSeDVwnOY3bDn2bPcbWcSgVrOSBQzSDxLw69FIplNgufA4dxtB0Ba2iQSGyTOGBsQ0iL558DhdLPzD0nQIg20JcHsBswW/h7DBwT8YiYtc+Cw4bYbQFsSgVraJNgS8WrhZ298JvnmwGF5s/PpDx98bKtL7Oc/fOAAPi2oIAHs1ATiNcAsJsGOUTAKRsEoGBEAAPNNT9hEqol6AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-8319-9841","institution":"National Institute of Diabetes and Digestive and Kidney Diseases","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Lothar","middleName":"","lastName":"Hennighausen","suffix":""}],"badges":[],"createdAt":"2020-12-01 16:45:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-119695/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-119695/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s42003-021-02167-1","type":"published","date":"2021-06-02T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":4198183,"identity":"7d11b2e7-9f6e-4b63-a27f-f89331baaefd","added_by":"auto","created_at":"2020-12-11 16:43:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1109066,"visible":true,"origin":"","legend":"Expression of ACE2 isoforms is induced by interferons. a-c. ACE2, and STAT1 and ISGs mRNA levels from control cells and cells treated with different cytokines were measured by RNA-seq. Results are shown as the means ± s.e.m. of independent biological replicates (n = 3). One-way ANOVA followed by Dunnett’s multiple comparisons test was used to evaluate the statistical significance of differences. d. RNA-seq reads are matched with exons. e. SAECs were cultured in the absence and presence of interferon alpha (IFNα) and beta (IFNβ) followed by RNA-seq analyses. The reads covering key exons (1a, 1b, 9, 1c and 10) are shown. f. mRNA levels of exon9 and exon1c were measured using qRT-PCR. Results are shown as the means ± s.e.m. of independent biological replicates (Control and IFNα, n = 9; IFNβ, n = 3). Two-way ANOVA with followed by Tukey’s multiple comparisons test was used to evaluate the statistical significance of differences.","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/0612976fe514c8fdb53c4586.jpg"},{"id":4198145,"identity":"447680b0-c646-4a56-80c9-7d27a66a816e","added_by":"auto","created_at":"2020-12-11 16:43:20","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1109066,"visible":true,"origin":"","legend":"Expression of ACE2 isoforms is induced by interferons. a-c. ACE2, and STAT1 and ISGs mRNA levels from control cells and cells treated with different cytokines were measured by RNA-seq. Results are shown as the means ± s.e.m. of independent biological replicates (n = 3). One-way ANOVA followed by Dunnett’s multiple comparisons test was used to evaluate the statistical significance of differences. d. RNA-seq reads are matched with exons. e. SAECs were cultured in the absence and presence of interferon alpha (IFNα) and beta (IFNβ) followed by RNA-seq analyses. The reads covering key exons (1a, 1b, 9, 1c and 10) are shown. f. mRNA levels of exon9 and exon1c were measured using qRT-PCR. Results are shown as the means ± s.e.m. of independent biological replicates (Control and IFNα, n = 9; IFNβ, n = 3). Two-way ANOVA with followed by Tukey’s multiple comparisons test was used to evaluate the statistical significance of differences.","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/d0fcd4665f40fb268a4eb4e7.jpg"},{"id":4198184,"identity":"2d9c366b-6597-4c4b-9afb-1b117ae49765","added_by":"auto","created_at":"2020-12-11 16:43:26","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1823401,"visible":true,"origin":"","legend":"Structure of the extended ACE2 locus and regulation of the ACE2 locus in primary airway epithelium. a. Regulatory marks in the 600 kb locus including ACE2 and neighboring genes in SAECs. mRNA levels in the absence and presence of IFNβ were measured by RNA-seq. ChIP-seq for H3K4me1, H3K27ac, H3K4me3 and Pol II was conducted in SAECs in the absence and presence of IFNβ. CTCF and STAT5 ChIP-seq data and DHS data are from ENCODE. b. ChIP-seq experiments for the histone marks H3K4me3 (promoter), H3K4me1 (enhancers), H3K27ac (active genes) and Pol II loading. The DHS data were obtained from ENCODE9,10. Yellow shade, candidate enhancers and blue shade, predicted promoter. The P/E region within intron 9 probably constitutes a combined promoter/enhancer. The BCL6 severed as ChIP-seq. Solid arrows indicate the orientation of genes. c. Putative STAT5 enhancer in the ACE2 gene was identified using ChIP-seq data from IFNb treated K562 cells11. d. ChIP-seq data for STAT transcription factors, histone marks and RNA Pol II on the STAT1 locus.","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/83925bbf6f31d6d0698bcdae.jpg"},{"id":4198146,"identity":"7085bb6c-e60c-49f5-9ad7-3985023a9c52","added_by":"auto","created_at":"2020-12-11 16:43:20","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1823401,"visible":true,"origin":"","legend":"Structure of the extended ACE2 locus and regulation of the ACE2 locus in primary airway epithelium. a. Regulatory marks in the 600 kb locus including ACE2 and neighboring genes in SAECs. mRNA levels in the absence and presence of IFNβ were measured by RNA-seq. ChIP-seq for H3K4me1, H3K27ac, H3K4me3 and Pol II was conducted in SAECs in the absence and presence of IFNβ. CTCF and STAT5 ChIP-seq data and DHS data are from ENCODE. b. ChIP-seq experiments for the histone marks H3K4me3 (promoter), H3K4me1 (enhancers), H3K27ac (active genes) and Pol II loading. The DHS data were obtained from ENCODE9,10. Yellow shade, candidate enhancers and blue shade, predicted promoter. The P/E region within intron 9 probably constitutes a combined promoter/enhancer. The BCL6 severed as ChIP-seq. Solid arrows indicate the orientation of genes. c. Putative STAT5 enhancer in the ACE2 gene was identified using ChIP-seq data from IFNb treated K562 cells11. d. ChIP-seq data for STAT transcription factors, histone marks and RNA Pol II on the STAT1 locus.","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/e95e94ca6ad8be01d699fb1b.jpg"},{"id":4198185,"identity":"fbbd93a9-add3-4ec1-bb54-c73b48d10aec","added_by":"auto","created_at":"2020-12-11 16:43:26","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":516800,"visible":true,"origin":"","legend":"Activating histone marks at the ACE2 locus in lung tissue. ChIP-seq and DHS from human lung tissues and DHS from SAECs display regulatory elements at the ACE2 (a), STAT1 (b) and ISG15 (c) loci.","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/e8a1d07f2b50231c275b1b77.jpg"},{"id":4198147,"identity":"a22c5261-8ed4-456f-9518-35b5f1980ede","added_by":"auto","created_at":"2020-12-11 16:43:20","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":516800,"visible":true,"origin":"","legend":"Activating histone marks at the ACE2 locus in lung tissue. ChIP-seq and DHS from human lung tissues and DHS from SAECs display regulatory elements at the ACE2 (a), STAT1 (b) and ISG15 (c) loci.","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/86e8fd96d02619eaac773b79.jpg"},{"id":4198186,"identity":"6edc96a5-245a-47a6-9b76-31a2f576e6f8","added_by":"auto","created_at":"2020-12-11 16:43:26","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1410772,"visible":true,"origin":"","legend":"JAK inhibitors mitigated activation of IFNβ-stimulated genes. a-b. SAECs were cultured in the presence of IFNβ and JAK inhibitors, either Baricitinib or Ruxolitinib followed by RNA-seq analyses and qRT-PCR. Reads covering key exons are displayed. qRT-PCR results are shown as the means ± s.e.m. of independent biological replicates (Control and IFNb, n = 9; IFNb+JAK inhibitors, n = 3). Two-way ANOVA with followed by Tukey’s multiple comparisons test was used to evaluate the statistical significance of differences. c-d. STAT1 and ISG15 mRNA levels from control and experimental cells were measured by RNA-seq. Results are shown as the means ± s.e.m. of independent biological replicates (n = 3). One-way ANOVA with followed by Dunnett’s multiple comparisons test was used to evaluate the statistical significance of differences. e-h. H3K27ac marks, and Pol II loading at the ACE2, STAT1 and ISG15 loci in SAECs in the absence and presence of IFNβ and the JAK inhibitor, Ruxolitinib.","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/9b9bf0352099136069530844.jpg"},{"id":4198148,"identity":"4ff3c6db-0a5a-4bdd-9202-553690352b1d","added_by":"auto","created_at":"2020-12-11 16:43:20","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1410772,"visible":true,"origin":"","legend":"JAK inhibitors mitigated activation of IFNβ-stimulated genes. a-b. SAECs were cultured in the presence of IFNβ and JAK inhibitors, either Baricitinib or Ruxolitinib followed by RNA-seq analyses and qRT-PCR. Reads covering key exons are displayed. qRT-PCR results are shown as the means ± s.e.m. of independent biological replicates (Control and IFNb, n = 9; IFNb+JAK inhibitors, n = 3). Two-way ANOVA with followed by Tukey’s multiple comparisons test was used to evaluate the statistical significance of differences. c-d. STAT1 and ISG15 mRNA levels from control and experimental cells were measured by RNA-seq. Results are shown as the means ± s.e.m. of independent biological replicates (n = 3). One-way ANOVA with followed by Dunnett’s multiple comparisons test was used to evaluate the statistical significance of differences. e-h. H3K27ac marks, and Pol II loading at the ACE2, STAT1 and ISG15 loci in SAECs in the absence and presence of IFNβ and the JAK inhibitor, Ruxolitinib.","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/d13ca185ade023d9624ee3c6.jpg"},{"id":4198187,"identity":"398551c3-66aa-444f-8771-c1e20eb62f7c","added_by":"auto","created_at":"2020-12-11 16:43:26","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":386254,"visible":true,"origin":"","legend":"Activation of immune response genes by Interferons in human primary airway epithelium (SAEC) is mitigated by JAK inhibitors. a. Genes induced significantly by IFNα, β, γ and λ3 were significantly enriched in Hallmark Gene Sets (FDR q-value \u003c 0.005). Immune response genes accounted for 18.4%, 26.3%, 20.1% and 17% of the upregulated genes. b. Expression of immune pathway genes induced by IFNβ was mitigated by the JAK inhibitors Ruxolitinib and Baricitinib.","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/cc5cb05bcfe4186343af81ae.jpg"},{"id":4198149,"identity":"e22a3c2a-2ec5-44fd-adbe-7b2da48e2857","added_by":"auto","created_at":"2020-12-11 16:43:21","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":386254,"visible":true,"origin":"","legend":"Activation of immune response genes by Interferons in human primary airway epithelium (SAEC) is mitigated by JAK inhibitors. a. Genes induced significantly by IFNα, β, γ and λ3 were significantly enriched in Hallmark Gene Sets (FDR q-value \u003c 0.005). Immune response genes accounted for 18.4%, 26.3%, 20.1% and 17% of the upregulated genes. b. Expression of immune pathway genes induced by IFNβ was mitigated by the JAK inhibitors Ruxolitinib and Baricitinib.","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/c44ebe728d5e16987fa0ca15.jpg"},{"id":15782256,"identity":"15b244cd-ac8b-4cfa-b4f2-b980773e40b4","added_by":"auto","created_at":"2021-11-22 15:47:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1519466,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/3ecf9484-fd30-4202-843f-cca33b3d2f9d.pdf"},{"id":4198188,"identity":"fc4722a6-248e-491d-bd1d-8ac76d7a4e4b","added_by":"auto","created_at":"2020-12-11 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16:43:28","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":3303660,"visible":true,"origin":"","legend":"Supplementary Table 2","description":"","filename":"SupplementaryTable2ConvsIFNa.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/90ddb50fca208ef02fac4cfe.xlsx"},{"id":4198156,"identity":"f1f18071-f034-44ea-be85-83d97cd657d7","added_by":"auto","created_at":"2020-12-11 16:43:23","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":3303660,"visible":true,"origin":"","legend":"Supplementary Table 2","description":"","filename":"SupplementaryTable2ConvsIFNa.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/078255a00221faec7ebb51bb.xlsx"},{"id":4198197,"identity":"7f180ea9-3bc3-4070-82d4-9542ef7f9992","added_by":"auto","created_at":"2020-12-11 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16:43:28","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":3293533,"visible":true,"origin":"","legend":"Supplementary Table 3","description":"","filename":"SupplementaryTable3ConvsIFNb.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/ccb0fab282708b596561a2f0.xlsx"},{"id":4198158,"identity":"ec9dea72-d66d-4b5b-a0d9-d2a3354b31e2","added_by":"auto","created_at":"2020-12-11 16:43:23","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":3293533,"visible":true,"origin":"","legend":"Supplementary Table 3","description":"","filename":"SupplementaryTable3ConvsIFNb.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/b1ba84e30bc6ca807fdf0775.xlsx"},{"id":4198198,"identity":"32c52e83-797a-4cd7-ab5a-78624a0907b2","added_by":"auto","created_at":"2020-12-11 16:43:29","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":3295761,"visible":true,"origin":"","legend":"Supplementary Table 4","description":"","filename":"SupplementaryTable4ConvsIFNg.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/821802f4531d93312a349416.xlsx"},{"id":4198160,"identity":"ea0940b3-cf87-4af3-abbc-97850c1606dd","added_by":"auto","created_at":"2020-12-11 16:43:24","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":3295761,"visible":true,"origin":"","legend":"Supplementary Table 4","description":"","filename":"SupplementaryTable4ConvsIFNg.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/6c65b02b16280b982beb509d.xlsx"},{"id":4198199,"identity":"be982670-d968-487f-9c09-cfd2ffcb4dc7","added_by":"auto","created_at":"2020-12-11 16:43:29","extension":"xlsx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":3319618,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable7ConvsIL7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/2f51632f0c8e7cbb202fc960.xlsx"},{"id":4198161,"identity":"1becc182-f258-4993-b31c-537d830f13ff","added_by":"auto","created_at":"2020-12-11 16:43:24","extension":"xlsx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":3319618,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable7ConvsIL7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/21276a3be1fbec1285f45a15.xlsx"},{"id":4198200,"identity":"d646ac6c-16ad-43b7-b747-2a8cf86d45bd","added_by":"auto","created_at":"2020-12-11 16:43:29","extension":"xlsx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":3285914,"visible":true,"origin":"","legend":"Supplementary Table 5","description":"","filename":"SupplementaryTable5ConvsIFNl3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/f7467802ada0ed388855adc0.xlsx"},{"id":4198162,"identity":"d47d6d34-7fd4-4c21-ae95-1f477339f926","added_by":"auto","created_at":"2020-12-11 16:43:25","extension":"xlsx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":3285914,"visible":true,"origin":"","legend":"Supplementary Table 5","description":"","filename":"SupplementaryTable5ConvsIFNl3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/854de0eb39412f81a723ce91.xlsx"},{"id":4198201,"identity":"3942fa37-f6ce-466c-ac6b-78682973e789","added_by":"auto","created_at":"2020-12-11 16:43:30","extension":"xlsx","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":3321578,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable8ConvsGH.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/9f67276cca450f415c64b20c.xlsx"},{"id":4198163,"identity":"0befa6c8-a8fe-465e-86bf-2c21bd928895","added_by":"auto","created_at":"2020-12-11 16:43:25","extension":"xlsx","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":3321578,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable8ConvsGH.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/4e83aa41a77a8dc90b24a384.xlsx"},{"id":4198203,"identity":"72dbc61a-bbd4-4605-8186-f3bb953a9c82","added_by":"auto","created_at":"2020-12-11 16:43:30","extension":"xlsx","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":3075890,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable9IFNbvsIFNbBaricitinib.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/d11dbf1134f836442d3235f2.xlsx"},{"id":4198165,"identity":"bdc13b71-2e26-42b9-a34f-4ec83d24fec4","added_by":"auto","created_at":"2020-12-11 16:43:26","extension":"xlsx","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":3075890,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable9IFNbvsIFNbBaricitinib.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/391e06d0e90e0f59f5e42b95.xlsx"},{"id":4198202,"identity":"c151bff4-4b5c-4f48-b197-06f819a9f3df","added_by":"auto","created_at":"2020-12-11 16:43:30","extension":"xlsx","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":3300915,"visible":true,"origin":"","legend":"Supplementary Table 6","description":"","filename":"SupplementaryTable6ConvsIL6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/5052c838f9c5fb4b7d444ebf.xlsx"},{"id":4198164,"identity":"f374fdd8-d2b4-4743-b712-bc5a058ada34","added_by":"auto","created_at":"2020-12-11 16:43:25","extension":"xlsx","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":3300915,"visible":true,"origin":"","legend":"Supplementary Table 6","description":"","filename":"SupplementaryTable6ConvsIL6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/c1d316a9115a2978543e13af.xlsx"},{"id":4198204,"identity":"6000c537-452c-4ba2-91e4-20662ac3e3dc","added_by":"auto","created_at":"2020-12-11 16:43:31","extension":"xlsx","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":3319618,"visible":true,"origin":"","legend":"Supplementary Table 7","description":"","filename":"SupplementaryTable7ConvsIL7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/05afa1ab6aff5e61920d34b6.xlsx"},{"id":4198166,"identity":"9a14b81c-fc14-435f-8740-2b2597371576","added_by":"auto","created_at":"2020-12-11 16:43:26","extension":"xlsx","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":3319618,"visible":true,"origin":"","legend":"Supplementary Table 7","description":"","filename":"SupplementaryTable7ConvsIL7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/22f85b2a06ed7c47f05c6b96.xlsx"},{"id":4198205,"identity":"4760bdcf-ce7c-46c0-92b7-ead6376e41e7","added_by":"auto","created_at":"2020-12-11 16:43:31","extension":"xlsx","order_by":18,"title":"","display":"","copyAsset":false,"role":"supplement","size":3321578,"visible":true,"origin":"","legend":"Supplementary Table 8","description":"","filename":"SupplementaryTable8ConvsGH.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/cbbae945ed6ab05a007817b7.xlsx"},{"id":4198167,"identity":"3573015d-a7c6-4289-995e-f4b67b4c0400","added_by":"auto","created_at":"2020-12-11 16:43:26","extension":"xlsx","order_by":18,"title":"","display":"","copyAsset":false,"role":"supplement","size":3321578,"visible":true,"origin":"","legend":"Supplementary Table 8","description":"","filename":"SupplementaryTable8ConvsGH.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/7d7f800b71ef8dcea37e8289.xlsx"},{"id":4198206,"identity":"c54975c5-7eb4-4fa1-93e0-999da59af964","added_by":"auto","created_at":"2020-12-11 16:43:31","extension":"xlsx","order_by":19,"title":"","display":"","copyAsset":false,"role":"supplement","size":3075890,"visible":true,"origin":"","legend":"Supplementary Table 9","description":"","filename":"SupplementaryTable9IFNbvsIFNbBaricitinib.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/09528e525f83cae4bc7f97d0.xlsx"},{"id":4198168,"identity":"f5c51681-7906-4ca5-b725-076de442eadc","added_by":"auto","created_at":"2020-12-11 16:43:27","extension":"xlsx","order_by":19,"title":"","display":"","copyAsset":false,"role":"supplement","size":3075890,"visible":true,"origin":"","legend":"Supplementary Table 9","description":"","filename":"SupplementaryTable9IFNbvsIFNbBaricitinib.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/76877150315ffb71fbc57be1.xlsx"},{"id":4198207,"identity":"8993b20a-18e1-4fe3-b064-0b2ce30d27df","added_by":"auto","created_at":"2020-12-11 16:43:31","extension":"xlsx","order_by":20,"title":"","display":"","copyAsset":false,"role":"supplement","size":3073409,"visible":true,"origin":"","legend":"Supplementary Table 10","description":"","filename":"SupplementaryTable10IFNbvsIFNbRuxolitinib.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/67a551d46baa68d5713d4d1d.xlsx"},{"id":4198169,"identity":"fd96fcf4-165d-4ff3-81b5-87d1fd5ca51a","added_by":"auto","created_at":"2020-12-11 16:43:27","extension":"xlsx","order_by":20,"title":"","display":"","copyAsset":false,"role":"supplement","size":3073409,"visible":true,"origin":"","legend":"Supplementary Table 10","description":"","filename":"SupplementaryTable10IFNbvsIFNbRuxolitinib.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-119695/v1/04a882c18fe701daaf0938f3.xlsx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"\u003cp\u003eActivation of Interferon-Stimulated Transcriptomes and \u003cem\u003eACE2 \u003c/em\u003eIsoforms in Human Airway Epithelium Is Curbed by Janus Kinase Inhibitors\u003c/p\u003e","fulltext":[{"header":"Introduction","content":" \u003cp\u003eThe angiotensin-converting enzyme 2 (ACE2) receptor is the gateway for SARS-CoV-2 to airway epithelium\u003csup\u003e1,2\u003c/sup\u003e and the strong inflammatory response after viral infection is a hallmark in COVID-19 patients. Single cell RNA sequencing (scRNA-seq) studies have revealed that \u003cem\u003eACE2\u003c/em\u003e expression in type II pneumocytes is induced by interferons\u003csup\u003e3\u003c/sup\u003e, suggesting that the presence of an autoregulatory loop could result in increased viral infection. Recent studies\u003csup\u003e4,5\u003c/sup\u003e have identified a novel short form of ACE2, called dACE2, that originates from an intronic promoter activated by interferons, calling into question that transcription of the full length native \u003cem\u003eACE2\u003c/em\u003e is under interferon control. Onabajo et al.\u003csup\u003e5\u003c/sup\u003e used ENCODE data for chromatin modification marks (H3K4me3, H3K4me1 and H3K27ac) as well as DNase I hypersensitive (DHS) sites in cell lines to label putative regulatory elements at the newly identified exon (ex1c) located within intron 9 of the \u003cem\u003eACE2\u003c/em\u003e gene. However, no regulatory elements were detected in the vicinity of the 5\u0026rsquo; end of the full-length transcript encoding biologically active ACE2, and in sequences distal to the genuine promoter. Since these data sets were obtained from a wide range of cell lines and not from human primary airway cells, the principal target of SARS-CoV-2, they might not present a comprehensive picture of the regulatory regions controlling expression of the \u003cem\u003edACE2\u003c/em\u003e and the full-length \u003cem\u003eACE2\u003c/em\u003e transcripts in bronchial tissue.\u003c/p\u003e \u003cp\u003eJanus kinase (JAK) inhibitors suppress signal transduction pathways that lead to immune activation and inflammation and they are used therapeutically to harness cytokine storm in COVID-19 patients\u003csup\u003e6,7\u003c/sup\u003e. However, the genetic programs activated in airway cells by interferons and their response to JAK inhibitors remain to be elucidated. In this study we pursued two linked goals. We used genome-wide chromatin profiling and RNA-seq analyses to identify the regulation of \u003cem\u003eACE2\u003c/em\u003e and \u003cem\u003edACE2\u003c/em\u003e gene expression in human primary airway cells and we investigated the ability of JAK inhibitors to blunt interferon-activated genetic programs.\u003c/p\u003e "},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eInterferons regulate the\u003c/strong\u003eACE2\u003cstrong\u003elocus in human airways cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo comprehensively identify the genetic elements controlling the extended \u003cem\u003eACE2\u003c/em\u003e locus, with an emphasis on its interferon response, we focused on human primary Small Airway Epithelial Cells (SAEC), which express a wide range of cytokine receptors and key mechanistic components of the executing JAK/STAT signal transduction pathway (Supplementary Table\u0026nbsp;1). We stimulated SAECs with interferon type I (IFNa and IFNb), type II (IFNg) and type III (IFNl) as well as with growth hormone (GH), Interleukin 6 (IL6) and IL7, followed by RNA-seq transcriptome analyses (Supplementary Tables\u0026nbsp;2\u0026ndash;8). Increased \u003cem\u003eACE2\u003c/em\u003e expression was obtained with the interferons but not with GH, IL6 and IL7 (Fig.\u0026nbsp;1a). However, the induction was less than that seen for classical interferon stimulated genes (ISG), such as \u003cem\u003eSTAT1\u003c/em\u003e, \u003cem\u003eISG15\u003c/em\u003e and \u003cem\u003eISG20\u003c/em\u003e (Fig.\u0026nbsp;1b-c). In agreement with earlier studies\u003csup\u003e4,5\u003c/sup\u003e, we detected the novel \u003cem\u003edACE2\u003c/em\u003e N-terminal exon (ex1c) within intron 9 of the \u003cem\u003eACE2\u003c/em\u003e gene (Fig.\u0026nbsp;1d). To obtain additional information on the interferon response of the \u003cem\u003edACE2\u003c/em\u003e and \u003cem\u003eACE2\u003c/em\u003e promoters, we used RNA-seq and determined the respective read counts over the three alternative first exons (Fig.\u0026nbsp;1d-e). While the increase of RNA-seq reads induced by IFNa/b was highest (~\u0026thinsp;25-fold) over ex1c, a lesser, yet significant, ~\u0026thinsp;2-10-fold increase was detected over ex1a and ex1b, supporting the notion that expression of the full-length \u003cem\u003eACE2\u003c/em\u003e transcript is also under interferon control. As an independent assay we used qRT-PCR and determined that IFN a/b stimulation led to an 8 to 15-fold increase of \u003cem\u003edACE2\u003c/em\u003e (ex1c) and an approximately\u0026thinsp;~\u0026thinsp;3-fold increase of \u003cem\u003eACE2\u003c/em\u003e RNA (ex9) (Fig.\u0026nbsp;1f). However, the degree of induction of either form was lower than that seen for \u003cem\u003ebona fide\u003c/em\u003e ISGs. Previous studies in normal human bronchial epithelium (NHBE) did not reveal an interferon response of the native \u003cem\u003eACE2\u003c/em\u003e promoter\u003csup\u003e4,5\u003c/sup\u003e suggesting differences between cell types or growth conditions. The mouse \u003cem\u003eAce2\u003c/em\u003e gene is also induced by cytokines through a STAT5-based enhancer in the second intron\u003csup\u003e8\u003c/sup\u003e and a DHS site is located in the equivalent location in the human \u003cem\u003eACE2\u003c/em\u003e gene in SAEC and lung tissue. This suggests the presence of additional regulatory elements controlling expression of the full-length \u003cem\u003eACE2\u003c/em\u003e mRNA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterferons activate STAT enhancers in the\u003c/strong\u003eACE2\u003cstrong\u003elocus\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify candidate regulatory elements controlling the extended \u003cem\u003eACE2\u003c/em\u003e locus, including \u003cem\u003eACE2\u003c/em\u003e and \u003cem\u003edACE2\u003c/em\u003e, in primary airway cells, we dug deeper and conducted ChIP-seq for the chromatin marks H3K27ac (activate loci), H3K4me1 (enhancers), H3K4me3 (promoters) and Polymerase II (Pol II) loading, both in the absence and presence of IFNb (Fig.\u0026nbsp;2). DNase I hypersensitive (DHS) sites from human lung tissues\u003csup\u003e9\u003c/sup\u003e and SAECs\u003csup\u003e10\u003c/sup\u003e served as \u003cem\u003ebona fide\u003c/em\u003e predictors of regulatory regions. In addition to \u003cem\u003eACE2\u003c/em\u003e, the neighboring \u003cem\u003eTMEM27\u003c/em\u003e gene, an \u003cem\u003eACE2\u003c/em\u003e homologue, as well as \u003cem\u003eBMX\u003c/em\u003e are activated by interferons (Fig.\u0026nbsp;2a) suggesting the possibility of jointly used regulatory elements. \u003cem\u003eACE2\u003c/em\u003e and \u003cem\u003eTMEM27\u003c/em\u003e originated from a gene duplication and their response to interferon is equivalent. The positions of the chromatin boundary factor CTCF suggests that \u003cem\u003eACE2\u003c/em\u003e and \u003cem\u003eTMEM27\u003c/em\u003e are located within a sub-TAD (Fig.\u0026nbsp;2a).\u003c/p\u003e\n\u003cp\u003eIn agreement with earlier studies\u003csup\u003e5\u003c/sup\u003e, we identified DHS sites at ex1c and in intron 17 (Fig.\u0026nbsp;2b). In addition, we identified DHS sites at ex1a, likely marking the genuine \u003cem\u003eACE2\u003c/em\u003e promoter, a distal site marking a possible enhancer and in intron 15 coinciding with activate marks. The DHS site in intron 9 overlaps with strong H3K4me3 marks, identifying it as a genuine promoter region (Fig.\u0026nbsp;2b). This site is also decorated with H3K4me1 and H3K27ac marks and extensive Pol II loading, hallmarks of a complex promoter/enhancer. H3K27ac and Pol II loading was further induced by IFNb, reflecting increased \u003cem\u003eACE2\u003c/em\u003e expression. IFNb activates the transcription factors STATs 1, 2 and 5 (Fig.\u0026nbsp;1b and Supplementary Table\u0026nbsp;3) and ChIP-seq experiments from K562 erythroid cells stimulated with IFNb\u003csup\u003e11\u003c/sup\u003e revealed preferential binding of STAT5 to the intronic promoter/enhancer (Fig.\u0026nbsp;2c) further supporting regulation through the JAK/STAT pathway. The STAT1 locus served as a control for the binding of STAT transcription factors (Fig.\u0026nbsp;2d). While the \u003cem\u003eACE2\u003c/em\u003e promoter associated with ex1a is marked by a DHS site and H3K4me1 marks, there is little evidence of H3K4me3 and H3K27ac marks. However, it is well known that there is no direct relationship between gene activity and the presence of these marks.\u003c/p\u003e\n\u003cp\u003eBased on the presence of DHS sites, activating chromatin marks and Pol II loading, either in combination or by themselves, we predict additional enhancers. A prominent candidate enhancer, marked by a DHS, H3K4me1 and Pol II loading is positioned approximately 16\u0026nbsp;kb distal of ex1a and additional putative regulatory regions are located with introns (Fig.\u0026nbsp;2b). Activating histone marks and DHS sites\u003csup\u003e9,10\u003c/sup\u003e are also present in the genuine \u003cem\u003eACE2\u003c/em\u003e promoter and the distal region as well as the regulatory elements of ISG, such as STAT1 and ISG15, in human lung tissues (Fig.\u0026nbsp;3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJAK inhibitors suppress the IFNb-sensing enhancers in the\u003c/strong\u003eACE2\u003cstrong\u003elocus\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInterferons activate genetic programs through the JAK/STAT signaling pathway and JAK inhibitors are used clinically in COVID-19 patients in an effort to suppress the genomic consequences of cytokine storms\u003csup\u003e6,12,13\u003c/sup\u003e. To investigate if interferon-induced \u003cem\u003eACE2\u003c/em\u003e expression is controlled by the JAK/STAT pathway, we cultured SAECs in the presence of IFNb and the JAK inhibitors, Baricitinib and Ruxolitinib, followed by RNA-seq and qRT-PCR assays (Fig.\u0026nbsp;4a-c and Supplementary Tables\u0026nbsp;9\u0026ndash;10) and ChIP-seq analyses (Fig.\u0026nbsp;4e-h). Both inhibitors suppressed the IFNb-induced increase of the full-length \u003cem\u003eACE2\u003c/em\u003e (ex1a, ex1b and ex9) and the \u003cem\u003edACE2\u003c/em\u003e (ex1c) transcripts (Fig.\u0026nbsp;4a-b), supporting that their respective promoters are under JAK/STAT control. The efficacy of the two inhibitors extended to a range of genetic programs activated through the pan JAK/STAT pathway (Figs.\u0026nbsp;4c) and induction of \u003cem\u003ebona fide\u003c/em\u003e interferon stimulated genes (ISG), such as \u003cem\u003eISG15\u003c/em\u003e, was suppressed (Fig.\u0026nbsp;4d). In \u003cem\u003eACE2\u003c/em\u003e, as in other ISGs, Ruxolitinib treatment mitigated the establishment of activating H3K27ac marks and Pol II loading over distal and intronic regulatory elements (Fig.\u0026nbsp;4e-h).\u003c/p\u003e\n\u003cp\u003eGene Set Enrichment Analysis (GSEA) of RNA-seq profiles showed, depending on the interferon, between 17% and 26% of the induced genes were linked to immune responses, like IFNg/a response, TNFa signaling, inflammatory response, IL-JAK/STAT signaling, among others (Fig.\u0026nbsp;5a and Supplementary Table\u0026nbsp;2\u0026ndash;5). Both JAK inhibitors led to a suppression of immune signaling pathways and IFNb-induced gene activation (Fig.\u0026nbsp;5b), including both forms of \u003cem\u003eACE2\u003c/em\u003e transcripts (Fig.\u0026nbsp;4b). These data suggest that JAK inhibitors have the potential to relieve COVID-19 symptoms induced by interferon-STAT1 that contribute to the COVID-19 pathogenesis\u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Discussion","content":" \u003cp\u003eSARS-CoV-2 entry into cells is facilitated by ACE2 and deciphering the regulation of the \u003cem\u003eACE2\u003c/em\u003e gene will aid our understanding of the viral tropism and also non-pulmonary pathology. Here, we have assessed the extended \u003cem\u003eACE2\u003c/em\u003e locus for regulatory elements controlling gene expression induced by interferons and other, not yet defined, stimuli. We show that the intronic regulatory region bears promoter and enhancer marks and binds STAT transcription factors, thus constituting a complex regulatory element controlling interferon-induced \u003cem\u003edACE2\u003c/em\u003e expression\u003csup\u003e5\u003c/sup\u003e. We also identified additional candidate regulatory elements throughout the locus that can be invoked in controlling transcription of the full-length transcripts yielding the biologically active ACE2. Regulation of the human and mouse \u003cem\u003eACE2\u003c/em\u003e\u003csup\u003e8\u003c/sup\u003e loci displays distinct differences, yet they share their response to cytokines and the JAK/STAT pathway, with the mouse \u003cem\u003eAce2\u003c/em\u003e gene being activated in mammary tissue by cytokines through an intronic enhancer\u003csup\u003e8\u003c/sup\u003e. Further studies in tissues and primary cells are needed to better understand the complex, possibly cell-specific, regulation of the human \u003cem\u003eACE2\u003c/em\u003e locus in organs with extrapulmonary manifestations of SARS-CoV-2 infection. Our demonstration that JAK inhibitors mitigate interferon-induced activation of inflammatory programs has practical implications for their use in treating COVID-19 patients.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eCell culture.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman small airway epithelial cells (SAEC) obtained from Lifeline Technology (FC-0016) were expanded using the complete BronchiaLife\u0026trade; media kit (Lifeline Technology, LL-0023). All culture wares were pre-coated in 30\u0026nbsp;\u0026micro;\u0026gamma;/ml of Fibronectin (ThermoFisher Scientific, 33016015) for at least 1\u0026nbsp;h at room temperature. Calu-3 line (ATCC, HTB-55\u0026trade;) were cultured using Eagle\u0026rsquo;s Minimum Essential Medium (ATCC, 30-2003\u0026trade;) containing 10% fetal bovine serum (Cytiva, SH3007103) in 5% CO2 atmosphere at 37\u0026nbsp;\u0026deg;C.\u003c/p\u003e\n\u003cp\u003eCytokines (10\u0026nbsp;ng/ml; Human IFNb, 300-02BC; Human IFNg, 300-02; Human IL6, 200-06; Human IL7, 200-07; Human Growth hormone, 100\u0026thinsp;\u0026minus;\u0026thinsp;40, Peprotech; Human IFNa2b, 78077.1, Stem Cell Technologies; Human IFNl3, 5259-IL-025, R\u0026amp;D systems) were treated in respective culture media and the cells were incubated for 12hr in 5% CO2 atmosphere at 37\u0026nbsp;\u0026deg;C. The cells were washed with PBS (Gibco, 14190144) twice and harvested.\u003c/p\u003e\n\u003cp\u003eJak inhibitors, 10\u0026nbsp;\u0026micro;\u0026Mu; of either Baricitinib (HY-15315A, MedChemExpress) or Ruxolitinib (HY-50856A, MedChemExpress), were added to BronchiLiafe\u0026trade; media with or without IFNb. SAEC and incubated for 12hrs and then washed with PBS twice and harvested.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA isolation and quantitative real-time PCR (qRT\u0026ndash;PCR).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from the collected cells and purified using the PureLink RNA Mini Kit (Invitrogen) according to the manufacturer\u0026rsquo;s instructions. cDNA was synthesized from total RNA using Superscript II (Invitrogen). Quantitative real-time PCR (qRT-PCR) was performed using TaqMan probes (ACE2, Hs01085333_m1; \u003cem\u003eSTAT1\u003c/em\u003e, Hs01013996_m1; \u003cem\u003eGAPDH\u003c/em\u003e, Hs02786624_g1, Thermo Fisher scientific) on the CFX384 Real-Time PCR Detection System (Bio-Rad) according to the manufacturer's instructions. Exon9 and exon1c mRNA were measured with the following primers, that were used by Onabajo et al.\u003csup\u003e5\u003c/sup\u003e, using SYBR Green system: Forward, 5\u0026rsquo;-GGGCGACTTCAGGATCCTTAT-3\u0026rsquo;, Reverse, 5\u0026rsquo;-GGATATGCCCCATCTCATGATGG-3\u0026rsquo;; Forward, 5\u0026rsquo;-GGAAGCAGGCTGGGACAAA-3\u0026rsquo;, Reverse, 5\u0026rsquo;-AGCTGTCAGGAAGTCGTCCATTG-3\u0026rsquo;. PCR conditions were 95\u0026nbsp;\u0026deg;C for 30\u0026nbsp;s, 95\u0026nbsp;\u0026deg;C for 15\u0026nbsp;s, and 60\u0026nbsp;\u0026deg;C for 30\u0026nbsp;s for 40 cycles. All reactions were done in triplicate and normalized to the housekeeping gene \u003cem\u003eGAPDH\u003c/em\u003e. Relative differences in PCR results were calculated using the comparative cycle threshold (\u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003eT\u003c/em\u003e\u003c/sub\u003e) method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTotal RNA sequencing (Total RNA-seq) and data analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from the collected cells and purified using the PureLink RNA Mini Kit (Invitrogen) according to the manufacturer\u0026rsquo;s instructions. Ribosomal RNA was removed from 1\u0026nbsp;\u0026micro;g of total RNAs and cDNA was synthesized using SuperScript III (Invitrogen). Libraries for sequencing were prepared according to the manufacturer\u0026rsquo;s instructions with TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (Illumina, RS-122-2301) and paired-end sequencing was done with a HiSeq 3000 instrument (Illumina).\u003c/p\u003e\n\u003cp\u003eThe raw data were subjected to QC analyses using the FastQC tool (version 0.11.9) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Total RNA-seq read quality control was done using Trimmomatic\u003csup\u003e15\u003c/sup\u003e (version 0.36) and STAR RNA-seq\u003csup\u003e16\u003c/sup\u003e (version STAR 2.5.4a) using 50\u0026nbsp;bp paired-end mode was used to align the reads (hg19). HTSeq\u003csup\u003e17\u003c/sup\u003e (version 0.9.1) was to retrieve the raw counts and subsequently, R (https://www.R-project.org/), Bioconductor\u003csup\u003e18\u003c/sup\u003e and DESeq2\u003csup\u003e19\u003c/sup\u003e were used. Additionally, the RUVSeq\u003csup\u003e20\u003c/sup\u003e package was applied to remove confounding factors. The data were pre-filtered keeping only those genes, which have at least ten reads in total. The visualization was done using dplyr (https://CRAN.R-project.org/package=dplyr) and ggplot2\u003csup\u003e21\u003c/sup\u003e. Genes were categorized as significantly differentially expressed with an adjusted p-value (pAdj) below 0.05 and a fold change\u0026thinsp;\u0026gt;\u0026thinsp;2 for up-regulated genes and a fold change of \u0026lt; -2 for down-regulated ones. Sequence read numbers were calculated using Samtools\u003csup\u003e22\u003c/sup\u003e software with sorted bam files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChromatin immunoprecipitation sequencing (ChIP-seq) and data analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChromatin was fixed with formaldehyde (1% final concentration) for 15\u0026nbsp;min at room temperature, and then quenched with glycine (0.125\u0026nbsp;M final concentration). Samples were processed as previously described\u003csup\u003e23\u003c/sup\u003e. The following antibodies were used for ChIP-seq: H3K27ac (Abcam, ab4729), RNA polymerase II (Abcam, ab5408), H3K4me1 (Active Motif, 39297) and H3K4me3 (Millipore, 07-473). Libraries for next-generation sequencing were prepared and sequenced with a HiSeq 3000 instrument (Illumina).\u003c/p\u003e\n\u003cp\u003eThe raw data were subjected to QC analyses using the FastQC tool (version 0.11.9) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Quality filtering and alignment of the raw reads was done using Trimmomatic\u003csup\u003e15\u003c/sup\u003e (version 0.36), Bowtie\u003csup\u003e24\u003c/sup\u003e (version 1.2.2) and Samtools\u003csup\u003e22\u003c/sup\u003e (version 1.8), with the parameter \u0026lsquo;-m 1\u0026rsquo; to keep only uniquely mapped reads, using the reference genome mm10. Picard tools (Broad Institute. Picard, http://broadinstitute.github.io/picard/. 2016) was used to remove duplicates. Homer\u003csup\u003e25\u003c/sup\u003e (version 4.8.2) and DeepTools\u003csup\u003e26\u003c/sup\u003e (version 3.1.3) software was applied to generate bedGraph files, separately. Integrative Genomics Viewer\u003csup\u003e27\u003c/sup\u003e (version 2.5.3) was used for visualization. Each ChIP-seq experiment was conducted for more than two replicates. DeepTools was used to obtain the Pearson and Spearman correlation between the replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor comparison of samples, data were presented as standard deviation in each group and were evaluated with a two-way ANOVA followed by Tukey\u0026rsquo;s multiple comparisons test or a one-way ANOVA with Dunnett\u0026rsquo;s multiple comparisons test using PRISM 8 GraphPad (version 8.2.0). Statistical significance was obtained by comparing the measures from wild-type or control group, and each mutant group. A value of *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, ***\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, ****\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.00001 was considered statistically significant.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability. \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data were obtained or uploaded to Gene Expression Omnibus (GEO). ChIP-seq for STATs was obtained under GSE31477. ChIP-seq data for H3K27ac and H3K4me1 from human lung tissues were downloaded from GSE143115 and 142958. DNase I hypersensitive (DHS) data from human lung tissues and SAEC were obtained under GSE90364 and 29692, respectively. The RNA-seq data and ChIP-seq for SAECs in the presence of cytokines and the JAK inhibitors were uploaded to GSE161665 (ChIP-seq in GSE161663 and RNA-seq in GSE161664).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Ilhan Akan, Sijung Yun and Harold Smith from the NIDDK genomics core for NGS and NCATS Chemical Genomics Center\u0026nbsp;Team for the JAK inhibitors. This work utilized the computational resources of the NIH HPC Biowulf cluster (\u003ca href=\"http://hpc.nih.gov\"\u003ehttp://hpc.nih.gov\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Intramural Research Programs (IRPs) of National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and National Center for Advancing Translational Sciences (NCATS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHKL: project conception, experimental design and execution, data analysis, preparation of figures, writing manuscript; OJ: experimental design and execution; LH: project conception, experimental design, data analysis, preparation of figures, writing manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHoffmann, M.\u003cem\u003e et al.\u003c/em\u003e SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor. \u003cem\u003eCell\u003c/em\u003e\u003cstrong\u003e181\u003c/strong\u003e, 271-280 e8 (2020).\u003c/li\u003e\n\u003cli\u003eLukassen, S.\u003cem\u003e et al.\u003c/em\u003e SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells. \u003cem\u003eEMBO J\u003c/em\u003e, e105114 (2020).\u003c/li\u003e\n\u003cli\u003eZiegler, C.G.K.\u003cem\u003e et al.\u003c/em\u003e SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues. \u003cem\u003eCell\u003c/em\u003e (2020).\u003c/li\u003e\n\u003cli\u003eNg, K.W.\u003cem\u003e et al.\u003c/em\u003e Tissue-specific and interferon-inducible expression of nonfunctional ACE2 through endogenous retroelement co-option. \u003cem\u003eNat Genet\u003c/em\u003e (2020).\u003c/li\u003e\n\u003cli\u003eOnabajo, O.O.\u003cem\u003e et al.\u003c/em\u003e Interferons and viruses induce a novel truncated ACE2 isoform and not the full-length SARS-CoV-2 receptor. \u003cem\u003eNat Genet\u003c/em\u003e (2020).\u003c/li\u003e\n\u003cli\u003eLa Rosee, F.\u003cem\u003e et al.\u003c/em\u003e The Janus kinase 1/2 inhibitor ruxolitinib in COVID-19 with severe systemic hyperinflammation. \u003cem\u003eLeukemia\u003c/em\u003e\u003cstrong\u003e34\u003c/strong\u003e, 1805-1815 (2020).\u003c/li\u003e\n\u003cli\u003eSpinelli, F.R., Conti, F. \u0026amp; Gadina, M. 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Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. \u003cem\u003eBrief Bioinform\u003c/em\u003e\u003cstrong\u003e14\u003c/strong\u003e, 178-92 (2013).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Supplemental Information","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Table legends.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 1.\u003c/strong\u003e mRNA levels of genes associated with the pan JAK-STAT pathway in SAEC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 2.\u003c/strong\u003e List of all genes with normalized read counts in each replicate at Control and IFNa treated SAEC, log\u003csub\u003e2\u003c/sub\u003e (fold change), \u003cem\u003ep\u003c/em\u003e-value and adjusted \u003cem\u003ep\u003c/em\u003e-value as well as upregulated gene list and GSEA analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 3.\u003c/strong\u003e List of all genes with normalized read counts in each replicate at Control and IFNb treated SAEC, log\u003csub\u003e2\u003c/sub\u003e (fold change), \u003cem\u003ep\u003c/em\u003e-value and adjusted \u003cem\u003ep\u003c/em\u003e-value as well as upregulated gene list and GSEA analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 4.\u003c/strong\u003e List of all genes with normalized read counts in each replicate at Control and IFNg treated SAEC, log\u003csub\u003e2\u003c/sub\u003e (fold change), \u003cem\u003ep\u003c/em\u003e-value and adjusted \u003cem\u003ep\u003c/em\u003e-value as well as upregulated gene list and GSEA analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 5.\u003c/strong\u003e List of all genes with normalized read counts in each replicate at Control and IFNl3 treated SAEC, log\u003csub\u003e2\u003c/sub\u003e (fold change), \u003cem\u003ep\u003c/em\u003e-value and adjusted \u003cem\u003ep\u003c/em\u003e-value as well as upregulated gene list and GSEA analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 6.\u003c/strong\u003e List of all genes with normalized read counts in each replicate at Control and IL6 treated SAEC, log\u003csub\u003e2\u003c/sub\u003e (fold change), \u003cem\u003ep\u003c/em\u003e-value and adjusted \u003cem\u003ep\u003c/em\u003e-value as well as upregulated gene list and GSEA analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 7.\u003c/strong\u003e List of all genes with normalized read counts in each replicate at Control and IL7 treated SAEC, log\u003csub\u003e2\u003c/sub\u003e (fold change), \u003cem\u003ep\u003c/em\u003e-value and adjusted \u003cem\u003ep\u003c/em\u003e-value as well as upregulated gene list and GSEA analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 8.\u003c/strong\u003e List of all genes with normalized read counts in each replicate at Control and GH treated SAEC, log\u003csub\u003e2\u003c/sub\u003e (fold change), \u003cem\u003ep\u003c/em\u003e-value and adjusted \u003cem\u003ep\u003c/em\u003e-value as well as upregulated gene list and GSEA analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 9.\u003c/strong\u003e List of all genes with normalized read counts in each replicate at IFNb and Baricitinib with IFNb, treated SAEC, log\u003csub\u003e2\u003c/sub\u003e (fold change), \u003cem\u003ep\u003c/em\u003e-value and adjusted \u003cem\u003ep\u003c/em\u003e-value as well as upregulated gene list and GSEA analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 10.\u003c/strong\u003e List of all genes with normalized read counts in each replicate at IFNb and Ruxolitinib with IFNb, treated SAEC, log\u003csub\u003e2\u003c/sub\u003e (fold change), \u003cem\u003ep\u003c/em\u003e-value and adjusted \u003cem\u003ep\u003c/em\u003e-value as well as upregulated gene list and GSEA analysis.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"COVID-19, ACE2, JAK","lastPublishedDoi":"10.21203/rs.3.rs-119695/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-119695/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSARS-CoV-2 infection of human airway epithelium activates genetic programs that lead to progressive hyperinflammation in COVID-19 patients. Here we report on genetic programs activated by interferons and the suppression by Janus kinase (JAK) inhibitors. The angiotensin-converting enzyme 2 (ACE2) is the receptor for SARS-CoV-2 and deciphering its regulation is paramount for understanding the cell tropism of SARS-CoV-2 infection. We identified candidate regulatory elements in the \u003cem\u003eACE2\u003c/em\u003e locus in human primary airway cells and lung tissue. Activating histone and promoter marks and Pol II loading characterize the intronic \u003cem\u003edACE2\u003c/em\u003e and define novel candidate enhancers distal to the genuine \u003cem\u003eACE2\u003c/em\u003e promoter and within additional introns. \u003cem\u003edACE2,\u003c/em\u003e and to a lesser extent \u003cem\u003eACE2,\u003c/em\u003e RNA levels increased in primary cells treated with interferons and this induction was mitigated by JAK inhibitors that are used therapeutically in COVID-19 patients. Our analyses provide insight into \u003cem\u003eACE2\u003c/em\u003e regulatory elements and highlight JAK inhibitors as suitable tools to suppress interferon-activated genetic programs in bronchial cells.\u003c/p\u003e","manuscriptTitle":"Activation of Interferon-Stimulated Transcriptomes and ACE2 Isoforms in Human Airway Epithelium Is Curbed by Janus Kinase Inhibitors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-12-11 16:43:18","doi":"10.21203/rs.3.rs-119695/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-biology","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsbio","sideBox":"Learn more about [Communications Biology](http://www.nature.com/commsbio/)","snPcode":"","submissionUrl":"","title":"Communications Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2f8a9db4-d790-4c2c-9487-84b8b362a5e7","owner":[],"postedDate":"December 11th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":1428843,"name":"Physiology"},{"id":1428844,"name":"Bioinformatics"},{"id":1428845,"name":"Medical Genetics"},{"id":1428846,"name":"Cell Communication and Signaling"}],"tags":[],"updatedAt":"2021-11-22T15:42:18+00:00","versionOfRecord":{"articleIdentity":"rs-119695","link":"https://doi.org/10.1038/s42003-021-02167-1","journal":{"identity":"communications-biology","isVorOnly":false,"title":"Communications Biology"},"publishedOn":"2021-06-02 04:00:00","publishedOnDateReadable":"June 2nd, 2021"},"versionCreatedAt":"2020-12-11 16:43:18","video":"","vorDoi":"10.1038/s42003-021-02167-1","vorDoiUrl":"https://doi.org/10.1038/s42003-021-02167-1","workflowStages":[]},"version":"v1","identity":"rs-119695","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-119695","identity":"rs-119695","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}