Interferons and viruses induce a novel primate-specific isoform dACE2 and not the SARS-CoV-2 receptor ACE2

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes COVID-19, utilizes angiotensin-converting enzyme 2 (ACE2) for entry into target cells. ACE2 has been proposed as an interferon-stimulated gene (ISG). Thus, interferon-induced variability in ACE2 expression levels could be important for susceptibility to COVID-19 or its outcomes. Here, we report the discovery of a novel, primate-specific isoform of ACE2, which we designate as deltaACE2 (dACE2). We demonstrate that dACE2, but not ACE2, is an ISG. In vitro, dACE2, which lacks 356 N-terminal amino acids, was non-functional in binding the SARS-CoV-2 spike protein and as a carboxypeptidase. Our results reconcile current knowledge on ACE2 expression and suggest that the ISG-type induction of dACE2 in IFN-high conditions created by treatments, inflammatory tumor microenvironment, or viral co-infections is unlikely to affect the cellular entry of SARS-CoV-2 and promote infection.


INTRODUCTION
Cells expressing ACE2 are potential targets of SARS-CoV-2 infection 1,2 . Studies based on single-cell RNA-sequencing (scRNA-seq) of lung cells have identified type II pneumocytes, ciliated cells, and transient secretory cells as the main types of ACE2-expressing cells 3,4 .
Furthermore, ACE2 was proposed to be an ISG, based on its inducible expression in cells treated with interferons (IFNs) or infected by viruses that induce IFN responses, such as influenza 4,5 .
These findings implied that the induction of ACE2 expression in IFN-high conditions could result in an amplified risk of SARS-CoV-2 infection 4,5 . Concerns could also be raised about possible ACE2-inducing side effects of IFN-based treatments proposed for COVID-19 [6][7][8][9] .
ACE2 plays multiple roles in normal physiological conditions and as part of host tissueprotective machinery during damaging conditions, including viral infections. As a terminal carboxypeptidase, ACE2 cleaves a single C-terminal residue from peptide hormones such as angiotensin II and des-Arg9-bradykinin. Angiotensin II is generated from its precursor angiotensin I by ACE, and is proteolytically converted into another biologically active peptide, angiotensin-(1-7) by ACE2 10,11 . ACE and ACE2 belong to the renin-angiotensin-aldosterone system, which regulates blood pressure and fluid-electrolyte balance; dysfunction of this system contributes to comorbidities in COVID-19 10,12 . des-Arg9-bradykinin is generated from bradykinin and belongs to the kallikrein-kinin system, which is critical in regulating vascular leakage and pulmonary edema, early signs of severe COVID-19 13,14 .
High plasma angiotensin II levels were found responsible for coronavirus-associated acute respiratory distress syndrome (ARDS), lung damage and high mortality in mouse models 15,16 and as a predictor of lethality in avian influenza in humans 17,18 . ACE2, which decreases the levels of angiotensin II, was identified as a protective factor in the same conditions. The hijacking of the normal host tissue-protective machinery guarded by ACE2 was suggested as a mechanism through which SARS-CoV could infect more cells 4,5 . Thus, it is critically important to identify factors affecting ACE2 expression in normal physiological processes and during viral infections and associated pathologies, such as in  Herein, aiming to explore the IFN-induced expression of ACE2 and its role in SARS-CoV-2 infection, we identified a novel, primate-specific isoform of ACE2, which we designate as deltaACE2 (dACE2). We then showed that dACE2, but not ACE2, is induced in various human and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07. 19.210955 doi: bioRxiv preprint cell types by IFNs and viruses; this information is important to consider for future therapeutic strategies and understanding susceptibility and outcomes of COVID-19.

dACE2 is a novel inducible and primate-specific isoform of ACE2
To address the extent to which IFNs induce the expression of ACE2 in human cells, we used our existing RNA-seq dataset (NCBI SRA: PRJNA512015) of a breast cancer cell line T47D infected with Sendai virus (SeV), known to be a strong inducer of IFNs and ISGs [19][20][21] .
Accordingly, no IFNs were expressed in T47D cells at baseline, but SeV strongly induced IFNB1, a type I IFN and all type III IFNs (IFNL1, 2, 3, and 4). Several well-known ISGs (ISG15, MX1 and IFIT1) were moderately expressed at baseline but were strongly induced by SeV (Table S1). ACE2 was not expressed at baseline but was strongly induced by SeV, exclusively as an isoform initiated from a novel first exon in intron 9 of the full-length ACE2 gene (Figure 1A, RNA-seq analysis in additional cell lines demonstrated that ACE2 exists as two full-length transcripts initiated from two independent first exons, which we designated as Ex1a and Ex1b (the latter is shared between these transcripts). Additionally, a truncated transcript was initiated from this novel first exon in intron 9, which we designated as Ex1c ( Figure 1B). The combination of ENCODE chromatin modification marks (H3K4me1, H3K4me3, H3K27ac, and a cluster of DNase I hypersensitivity sites, Figure 1A) suggests that Ex1c, but not Ex1a and Ex1b, is located within a putative regulatory region that might affect gene expression. Analysis of corresponding promoters for binding motifs for transcription factors relevant for IFN signaling predicted multiple motifs within the promoter of ACE2-Ex1c (P3) (Figure S1). In contrast, no ISG-type motifs were predicted in promoters of ACE2-Ex1a (P1) and Ex1b (P2), and only one ISG-type motif was predicted within the 5'UTR of Ex1b ( Figure S1).
The novel ACE2 isoform at 5p22.2 locus of human chromosome X is predicted to encode a protein of 459 aa, in which Ex1c encodes the first 10 aa, which are unique. Compared to the fulllength ACE2 protein of 805 aa, the truncation eliminates 17 aa of the signal peptide (SigP) and 339 aa of the N-terminal peptidase domain (PD, Figure 1C). We designate this novel transcript and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint as deltaACE2 (dACE2, NCBI GenBank accession number MT505392). Of the 100 vertebrate species with genomic sequences available through the UCSC Genome Browser, the 140-bp sequence of dACE2-Ex1c is highly conserved only in primates ( Figure 1D, E and Figure S2A,

dACE2 is induced by in vitro treatment with IFNs
We confirmed the SeV-induced expression of the full-length dACE2 by RT-PCR (Figure 2A, B) and verified the corresponding PCR products by Sanger-sequencing. Using custom-designed assays, we explored ACE2 and dACE2 expression in multiple cell lines ( Figure 2C, Table S2A).
In most cell lines tested, dACE2 but not ACE2 was strongly upregulated by SeV infection ( Figure 2B, C). To directly address whether IFN was responsible for the induced expression of dACE2, we performed expression analysis in primary normal human bronchial epithelial (NHBE) cells 22 and human intestinal (colon and ileum) organoid cultures 23 . In NHBE cells from 5 healthy donors, baseline expression levels of dACE2 and ACE2 were comparable, but only dACE2 was significantly induced by treatment with IFN-α or IFN-λ3 ( Figure 2D, Table S2B).
In contrast, ACE2 was highly expressed already at baseline both in colon and ileum organoid cultures, while the expression of dACE2 was very low. Treatments with IFN-β or a cocktail of IFNλ1-3 significantly induced only expression of dACE2 and not ACE2 ( Figure 2E, Table   S2C). In both cell models, the expression pattern of dACE2 was similar to that of the known ISGs -MX1 ( Figure 2D, Table S2B) and IFIT1 ( Figure 2E, Table S2C).

dACE2 is induced in virally infected human respiratory epithelial cells
To investigate whether dACE2 expression is induced by RNA viruses, which are potent inducers of the IFN response, we de novo quantified the expression of ACE2-Ex1a, Ex1b, and the newly annotated dACE2-Ex1c in several public RNA-seq datasets of virally infected human respiratory epithelial cells. In an RNA-seq dataset of human nasal airway epithelial cells from asthmatic patients ex-vivo infected with respiratory rhinovirus strains RV-A16 and RV-C15 (NCBI SRA: PRJNA627860), both ACE2 and dACE2 were expressed ( Figure 3A). Compared to uninfected cells, dACE2-Ex1c expression was strongly induced by both virusesby RV-A16 (2.58-fold; P = 2.52E-13) and RV-C15 (2.42-fold; P = 2.52E-12), while expression of ACE2-Ex1b was weakly induced only by RV-C15 (1.13-fold; P = 0.032) ( Figure 3B). Only dACE2 expression strongly correlated with multiple ISGs and IFNs ( Figure 3C). Similarly, in human lung explants infected and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint with influenza A/H3N2 virus (NCBI SRA: PRJNA557257), only dACE2 was induced by infection, and its expression correlated with the levels of IFNs and ISG (Figure 3D, E).
It was reported that in contrast to ACE2 expression in human cells, Ace2 was not induced in primary mouse tracheal basal cells in response to in vitro and in vivo IFN-stimulation, and upon in vivo viral infection 4 . To explore this further, we analyzed a dataset for human and mouse lung cells infected with the respiratory syncytial virus (RSV, NCBI SRA: PRJNA588982). Indeed, we did not observe induction of Ace2 in mouse lung cells (Figure S3A), while dACE2 but not ACE2 was induced in RSV-infected human pulmonary carcinoma cell line (H292) (Figure S3B). These results illustrate that the identification of ACE2 as an ISG 4,5 was likely based on the detection of inducible expression of dACE2, since 3'-scRNA-seq would detect both ACE2 and dACE2. The significant differences between the human and mouse sequences corresponding to dACE2-Ex1c and corresponding promoters might be responsible for the lack of ISG-type ACE2 expression in the mouse ( Figure 1D, Figure S2A, B).

dACE2 is enriched in squamous epithelial tumors
We explored the expression patterns of dACE2 in various human tissues. In a dataset of 95 normal human tissues of 27 types, dACE2-Ex1c was detectable in select tissues but at very low levels (≤ 10 RNA-seq reads), while ACE2-Ex1b expression was common ( Figure S4). In the Genotype-Tissue Expression (GTEx) set of normal human tissues, only total gene expression was available for ACE2, with the highest expression observed in the testes and small intestine ( Figure S5). We hypothesized that as an ISG, dACE2 might be absent or expressed at low levels in normal tissues, but could be induced by the inflammatory tissue microenvironment. We explored the data from The Cancer Genome Atlas (TCGA), which represents the largest collection of tumors and tumor-adjacent normal tissues. Expression of both ACE2 and dACE2 was detectable in many tumor-adjacent normal tissues ( Figure 4A, Figure S6). In the set of 10,185 TCGA tumors of 33 types, ACE2-Ex1a, Ex1b and dACE2-Ex1c were expressed in 12.6%, 38.0% and 16.8% of tumors, respectively, with ≥5 RNA-seq reads/sample. dACE2 was most expressed in the sets of head and neck squamous carcinoma (HNSC) and lung squamous carcinoma (LUSC), which represent oral and bronchial mucosal epithelial surfaces, while ACE2 was most expressed in kidney tumors ( Figure S7). and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. However, in TCGA-LUSC dataset (n=501), which represents ACE2-and dACE2-expressing tumors of bronchial origin (Figure 4B), IFNG expression did not correlate with dACE2 ( Figure   S8B). Using a curated list of 270 ISGs 24 , we used an unsupervised machine learning approach to assign all LUSC tumors to 6 clusters based on their ISG expression profiles (Figure S9A, B). A set of ISGs (n=100) that most strongly contributed to the definition of these clusters was used for correlation analysis. The analysis in a cluster that included 114 LUSC tumors with the highest and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint ISG expression showed that dACE2 was strongly and significantly (FDR p-value < 0.05) correlated with expression of 20 ISGs and ACE2 -with 5 ISGs (Figure S9C, D). Thus, in LUSC tumors, dACE2 was expressed as an ISG but unlikely driven by IFN-γ, suggesting multiple factors might be contributing to this expression.

dACE2 is induced by SARS-CoV-2 in vitro
Once we established that dACE2 is an ISG in multiple human cells under various conditions, we tested whether its expression could also be induced by SARS-CoV-2. There was a noticeable difference in baseline expression levels of ACE2 and dACE2 in three cell lines tested (Calu3, Caco-2 and T84). Expression of ACE2 and dACE2 was much higher in a lung adenocarcinoma cell line Calu3 compared to both colon adenocarcinoma cell lines Caco2 and T84 ( Figure 5A, Table S2D). Baseline dACE2 expression in T84 was higher than in Caco-2, in line with the RT-PCR results ( Figure 1B). All cell lines were successfully infected with SARS-CoV-2 ( Figure   5B, Table S2D), but ACE2 expression was not affected by infection in any cell line tested ( Figure 5A, Table S2D). Induction of dACE2 expression tracked with previously reported SARS-CoV-2 infectivity rates in these cells 23 Table S2D). We performed a similar analysis in human colon and ileum organoid cultures derived from two donors. There was more variability in expression of the three genes tested but, overall, the expression of dACE2 and IFIT1 but not ACE2 was significantly induced by SARS-CoV-2 infection ( Figure 5C, Table S2E), despite comparable SARS-CoV-2 infection load ( Figure 5D, Table S2E), and a similar infection rate (10% of the cells) 23 . These results confirm that dACE2 is inducible by SARS-CoV-2 infection.

dACE2 is non-functional as SARS-CoV-2 receptor and carboxypeptidase
Despite the strong induction of dACE2 mRNA expression, we were unable to detect endogenous dACE2 in SeV-infected cell lines by Western blotting with commercial ACE2 antibodies (data not shown). However, in the proteome database of mass spectrometry data available for breast, colon, and ovarian TCGA tumors 25 , we detected human-specific peptides matching the 10 aa and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint encoded by the dACE2-Ex1c (Figure S10), suggesting that dACE2 protein could be expressed in some conditions. The substantial N-terminal truncation by 356 aa in the peptidase domain of the putative dACE2 protein is expected to have significant functional consequences compared to the activity of the full-length ACE2 protein of 805 aa. For example, decreased or no binding by the SARS-CoV-2 spike receptor-binding domain (RBD) would be expected for dACE2. Indeed, when we treated cells overexpressing GFP or Myc-DDK-tagged dACE2 or ACE2 with biotinylated spike protein RBD ( Figure 6A), dACE2 failed to bind and internalize the RBD (Figure 6B, C) or affect the RBD binding by ACE2 (Figure 6D-F). The N-terminal truncation is also predicted to affect carboxypeptidase activity of dACE2, which is important for its ability to cleave angiotensin II, des-Arg9-bradykinin, and other substrates of ACE2. Indeed, we observed carboxypeptidase activity in lysates of cells transfected with ACE2-GFP but not dACE2-GFP (Figure 6G, H).
Thus, the main activities that involve the peptidase domain of ACE2 appear to be abrogated in dACE2.

DISCUSSION
ACE2 was recently proposed to be an ISG due to its induction in IFN-high conditions, raising concerns about its potential role in increasing SARS-CoV-2 infection 4,5 and the safety of IFNbased treatments proposed for COVID-19. Our discovery of dACE2, a primate-specific version of ACE2, demonstrates that it is dACE2 and not ACE2 that is induced by IFNs and viruses, including SARS-CoV-2. dACE2, however, did not appear to bind SARS-CoV-2 spike protein or affect the binding of ACE2 in our in vitro experiments, thus assuring that ISG-type induction of dACE2 would not increase viral entry.
Our findings highlight that in the presence of dACE2, ACE2 expression is likely to be misinterpreted when detected by methods such as 3'-scRNA-seq and gene-based assays that target shared dACE2 and ACE2 sequences. However, in non-primate species or in human cells that do not express dACE2, the same detection methods would correctly quantify Ace2 (ACE2), but not finding it is an ISG. These considerations are also important when using non-primate and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint species to study SARS-CoV-2 infection and COVID-19 because any possible effects contributed by dACE2 will not be captured in these animal models. By analyses in multiple human cell types and tissues, we showed that expression of dACE2, but not ACE2, is inducible by IFNs (type I, II and III) and viruses that induce IFN responses. IFN-γ-driven ISG signatures are contributed by immune cells that infiltrate tumors and inflamed virally infected tissues. We could not study the involvement of dACE2 in these signatures in cell culture models because they lack the immune component; in tissues by 3'-scRNA-seq because this method does not differentiate ACE2 and dACE2; and in micebecause they lack dAce2.
Instead, we explored the extensive TCGA dataset of more than 10,000 tumors in which we denovo quantified dACE2 expression based on RNA-seq data. We believe the conclusions of these analyses can be extended to inflamed virally infected tissues, for which comparable RNA-seq data is limited by small sample sets; low percentage of mappable reads due to substantially degraded input RNA, or raw data is not provided due to patient privacy restrictions.
Although all IFNs (type I, II and III) appeared to be potent inducers of dACE2 expression in vitro, IFN-γ might be an important driver of dACE2 expression in tissues with significant infiltration by immune cells, such as in tumors or virally infected tissues. Furthermore, the expression patterns observed in TCGA indicated that dACE2 expression might be intrinsically enriched in squamous epithelial cells, which give rise to corresponding tumors of the respiratory, gastrointestinal, and urogenital tracts.
While our experiments did not yet identify a clear functional role for dACE2, the absence in nonprimate species and the high degree of dACE2-Ex1c sequence conservation over 43 million years of primate evolution 31 argues for a potentially important role of dACE2. Endogenous dACE2 was not detected in cell lines by Western blotting with anti-ACE2 antibodies and may require the and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint development of dACE2-specific antibodies. However, the detection of dACE2-specific peptides in some TCGA tumors suggests that the protein production occurs, but might require some specific conditions or better detection tools. However, based on our in vitro data, it is unlikely that dACE2 protein would affect the binding and cellular access of SARS-CoV-2.
Although possible ISG-type ACE2 induction was considered as a risk for increasing SARS-CoV-2 infection, ACE2 deficiency rather than overexpression is discussed as a major factor contributing to COVID-19 morbidity [12][13][14]32 . Functional ACE2 deficiency occurs due to internalization of the SARS-CoV-2 -ACE2 complex 2,33 , which restricts ACE2 from performing its physiological functions, including its role as carboxypeptidase for angiotensin II and des-Arg9-bradykinin and other peptide hormones. ACE2 deficiency might also be created due to its regulation at the mRNA level, which needs to be explored.
Cancer patients are considered to be at a higher risk of more severe COVID-19 outcomes compared to the general population 34,35 due to older age, comorbidities and effects of cancer and cancer treatments. Lung cancer patients are at a specifically increased risk of severe COVID-19 outcomes 34 . In our analysis, dACE2 expression was common in tumors and particularly enriched in lung tumors of bronchial origin (LUSC), where the proper function of ACE2 is essential for protection from virus-induced tissue damage. The possible role of dACE2 expression and COVID-19 outcomes, specifically in cancer patients, should be further explored. ACE inhibitors (ACEIs) and angiotensin-receptor blockers (ARBs) are widely used to control hypertension and treat heart disease and chronic kidney disease 10 . Significant concerns were raised that ACEIs and ARBs could induce ACE2 expression, leading to increased SARS-CoV-2 infection and possibly accounting for COVID-19 severity and high mortality in those who are likely to use these medications -the elderly and patients with cardiovascular disease. We demonstrated that ACE2 expression is not inducible by IFNs, but it would be important to explore the effects of ACEIs and ARBs on dACE2 expression to properly assess this risk. The effects of other factors, such as smoking on dACE2 expression, should also be considered.
In conclusion, we present the first report of the discovery and functional annotation of dACE2, an IFN-inducible isoform of ACE2. The existence of two functionally distinct ACE2 isoforms reconciles several biological properties previously attributed to ACE2, with dACE2 being an ISG, and ACE2 acting as the SARS-CoV-2 entry receptor and carboxypeptidase, without being and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint regulated by IFNs. While our understanding of the functional role of dACE2 is still unfolding, we believe these insights will clarify our knowledge on ACE2 and provide new research leads in understanding COVID-19 susceptibility, mechanisms, and outcomes.

Cells
All cell lines and primary cells used are listed in Table S3. Cell lines were either used within 6 months after purchase or were periodically authenticated by microsatellite fingerprinting (AmpFLSTR Identifiler, Thermo Fisher) by the Cancer Genomics Research Laboratory/NCI).
All cell lines were regularly tested for mycoplasma contamination using the MycoAlert Mycoplasma Detection kit (Lonza). The previously described 22  approved by the Ethics Commission of the University Hospital Heidelberg. Organoids were generated from these tissues as previously described 23 .

Cells listed in
Infections with SARS-CoV-2 in colon cancer cell lines (Caco2 and T84) and lung cancer cell line (Calu3) and colon and ileum organoid cultures were previously described 23 . Briefly, the infections were performed using the MOI=1 for cell lines. Organoids were infected with 3x10 5 FFU of the virus, based on titers in Vero E6 cells. Culture media was removed from and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint cells/organoids and the virus was added for 1 hr at 37°C. After virus removal, cells were washed 1x with PBS, and media was added back to the cells. Viral replication and ISG induction were monitored for 24 hrs post-infection. The percentage of infected cells was determined by immunofluorescence staining and quantification of the number of nuclei vs. the number of infected cells. It was determined that infection rates were 80% in Caco2 cells, ~20% in T84 cells, ~10% in Calu3 cells, and 10% in organoids.

PCR, cloning and Sanger sequencing
cDNA was synthesized from 250 ng of total RNA per 20 µl reactions using the RT2 First-Strand cDNA kit and random hexamers (Qiagen). PCR for the full-length dACE2 was performed using primers and conditions listed in Table S4. PCR-amplified products were resolved on 1% agarose gel, cut, purified, and Sanger-sequenced. After cDNA sequences were validated, constructs for dACE2 with C-terminal Myc-DDK and GFP tags cloned in pcDNA3.4 vector were customsynthesized by Thermo Fisher. ACE2 with C-terminal GFP-tag (RG208442) and Myc-DDK tag (RC208442) were purchased from Origene. Empty vectors pMax-GFP (Lonza) and pCMV6-AC-Myc-DDK (Origene) were used as controls.

Treatments with IFNs
All IFNs used are listed in Table S5. The IFN-treated NHBE cells were previously described 22 .
Briefly, the cells were cultured in BEGM with supplements (Lonza), plated in 6-well plates and utilized at ~70% confluence (typically after 10-11 days with media change every 2 days). Cells were left untreated or treated with IFN-α2b (INTRON A, Merck, 100 IU/ml) or IFN-λ3 (R&D Systems, 100ng/ml) for 24 hrs. Cells were washed with PBS, resuspended in TRIzol (Thermo Fisher) and stored at -80°C for future RNA isolation. Total RNA was extracted with Direct-zol mini RNA isolation kits (Zymo Research). The IFN treatment of human colon and ileum organoids was previously described 23 . Briefly, cells were seeded 24 hrs prior to IFN treatment to reach a confluency of 70% at the time of treatment. Media was removed from cells and replaced with a cocktail of IFN-λ1-3 (100ng/mL of each for a total of 300ng/mL). Media was removed 24 hrs post-treatment, and RNA was extracted using the RNAeasy kit (Qiagen). 250ng of RNA was used to prepare cDNA using iSCRIPT (BioRad) and qRT-PCR was performed using iTaq SYBR Green (BioRad). T84 and Caco-2 cells were treated with IFN-γ (2 ng/ml) for 48 hrs, followed by cell harvesting, RNA extraction and expression analysis. and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020.  Table S4). The expression of target genes was normalized by geometric means of endogenous controls (GAPDH, HPRT1, TBP or ACTB, as indicated in Table S2), and presented as dCt values relative to endogenous controls (log2 scale).

RNA sequencing (RNA-seq) of T47D and RT4 cells
Total RNA was extracted from T47D and RT4 cells using RNeasy Mini Kit with an on-column

Estimation of RNA-seq read counts for ACE2 exons
and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint RNA-seq reads corresponding to the three first exons, ACE2-Ex1a and Ex1b and dACE2-Ex1c, were counted by processing RNA-seq BAM slices using R package ASpli version 1.5.1 with default settings. Genomic coordinates were manually curated in the GTF file and the 'counts' function was used to generate and export RNA-seq reads for the selected exons in a tab file format. The reads were normalized by dividing by the exon length (Table S7)

Unsupervised clustering and correlation analyses in TCGA
Gene expression Z-scores in the lung squamous cell carcinoma (TCGA-LUSC, n=501) dataset were calculated for 270 ISGs from a previously curated list 24 . ISGs with low expression values, (below 10 reads), or expressed in less than 5% of tumors were excluded. The data was used for self-organizing maps (SOM) clustering, which is an unsupervised machine learning approach enabling data dimensionality reduction without relying on any assumption about the data structure 37,38 . The SOM algorithm was iterated 100,000 times with Euclidean distance, linearly decreasing the learning rate from 0.05 to 0.01 using the "Kohonen" R package. The ISG expression patterns were projected onto a two-dimensional 10x10 hexagonal map. Thus, each node in this map is an expression profile representing a subset of the samples. SOM output, trained based on 100,000 iterations, was used to estimate the contribution of each ISG to and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint defining the clusters as a variance weighted according to the size of each node. A total of 6 clusters were estimated by kmeans algorithm and used to generate an expression heatmap.
Expression Z-scores of the top 100 ISGs ranked based on their contribution to defining the clusters were plotted using the "pheatmap" R package. Pearson correlation coefficients and corresponding FDR-adjusted p-values were calculated between Z-scores for the top 100 ISGs and both ACE2 and dACE2 in cluster 5, which included 114 tumors with the highest ISG expression. The analysis was performed using the "Hmisc" R package.

In silico analysis of promoter regulatory elements relevant for IFN signaling
Promoters were defined within the -800 bp/+100 bp window from the corresponding transcription start sites (TSS). The window was limited by 800 bp, based on the intronic distance between TSS of Ex1c and its upstream exon. Promoters of ACE2-Ex1a (P1) and Ex1b (P2) and dACE2-Ex1c (P3) were analyzed using Nsite tool 39 from online bioinformatics gateway Softberry (www. softberry.com) to predict transcription factor binding sites. The search was set against the ooTFD (Object-oriented Transcription Factors Database) of human and animal transcription factor binding sites largely curated according to the functional data from the literature. The parameters were set to allow a maximum of 1 or 2 mismatches with the known motifs. ISG-type motifs were manually curated from ~300 predicted and annotated motifs per promoter.

Mining of proteomics datasets
Mass-spectrometry datasets generated for TCGA colon, breast and ovarian tumors (http://www.pepquery.org/) were mined for matches to the 36-aa fragment of dACE2, including the unique 10 aa encoded by dACE2-Ex1c. The analysis was done with PepQuery peptide-centric search engine 25 , using the following parameters: MS dataset of a specific cancer type; target event as protein; scoring algorithm as Hyperscore and not selecting for Unrestricted modification filtering. The identified peptides for each cancer type were exported as CSV files and manually analyzed for further assessment of peptide quality.

Transient transfections
Transient transfections were performed with Lipofectamine 3000 (Thermo Fisher). Unless specified, bladder cancer cells (T24), in which no baseline expression of ACE2 or dACE2 was and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint detected (Table S2), were used for transfections at 70-90% confluency in 12-or 6-well plates for 24 hrs.

Western blot
Cells were lysed with RIPA buffer (Sigma) supplemented with protease inhibitor cocktail (Promega) and PhosSTOP (Roche) and placed on ice for 30 min, with vortexing every 10 min.
Lysates were pulse-sonicated for 30 sec, with 10-s burst-cooling cycles, at 4°C, boiled in reducing sample buffer for 5 min and resolved on 4-12% Bis-Tris Bolt gels and transferred using an iBlot 2 (Thermo Fisher). Blots were blocked in 2.5% milk in 1% TBS-Tween before staining with antibodies ( Table S5)

Flow cytometry analysis of SARS-CoV-2 spike protein-RBD binding
T24 cells were transiently transfected with ACE2-GFP, dACE2-Myc-DDK, or co-transfected with both constructs in 12-well plates (1x10 5 cells/well). After 24 hrs, cells were stained with recombinant biotinylated spike protein RBD as described above and analyzed with and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint multiparametric flow cytometry on a FACS Aria III (BD Biosciences) and FlowJo.v10 software (BD Biosciences).

Peptidase activity assays
T24 cells were transiently transfected with ACE2-GFP, dACE2-GFP, or empty GFP-vector in triplicates. After 24 hrs, cells were pelleted and lysed with 400 μl of Lysis Buffer provided with the ACE2 activity kit (#K897, BioVision). Cell lysates were analyzed by Western blots with Cterminal anti-ACE2 antibody (Abcam), and the amounts of recombinant ACE2-GFP and dACE2-GFP proteins in lysates were quantified by densitometry analysis (Imagelab, BD Biosciences) of Western blots. The amounts of ACE2 and dACE2 lysates to be used in protease assays were determined based on protein quantification. Protein lysates were processed in duplicates using the kit reagents and according to protocol. The activity was measured as fluorescence (Ex/Em = 365/410-460 nm) using Promega GlowMax plate reader for two time points between 30 mins and 2 hrs after adding the corresponding substrate mix and normalizing for baseline level. Positive control was provided by the kit.

Statistical analysis
Expression of ACE2-Ex1a and Ex1b and dACE2-Ex1c between groups of samples was evaluated by the non-parametric Mann-Whitney U test. Student's T-test was used for small groups of samples. Statistical tests for other analyses are indicated in corresponding sections. FDR adjustment was applied when indicated. P-values <0.05 were considered significant.

Computational resources
We used the NIH Biowulf supercomputing cluster and specific packages for R version 3.6.2. was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105

R21AG064479-01 and a Brain
The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint and is also made available for use under a CC0 license. was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint Figure 1. dACE2 is a novel primate-specific and virally-induced isoform of ACE2. A) UCSC genome browser view of the human ACE2 region (chrX:15,560,521-15,602,580, GRCh38/hg38) showing alternative first exons ACE2-Ex1a and Ex1b and a novel Ex1c that creates a short isoform designated as deltaACE2 (dACE2). ENCODE epigenetic markers (H3K4me1, H3K4me3, H3K27ac, and cluster of DNase I hypersensitivity sites) indicate that dACE2-Ex1c is located within a putative regulatory region that can affect gene expression. B) RNA-seq Sashimi plots depict splicing patterns defining ACE2 and dACE2 isoforms in SeV/mock-infected T47D cells and uninfected RT-4 cells. C) ACE2 is a single-span and is also made available for use under a CC0 license.

FIGURES
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint transmembrane protein with a signal peptide (SigP) of 17 aa and four functional domainspeptidase domain (PD, aa 18-615), collectrin-like domain (CLD, aa 616-740), transmembrane domain (TM, aa 741-761), and intracellular domain (ICD, aa 762-805). In dACE2, no signal peptide is predicted; the extracellular domain (ECD) starts from aa R357; the first 356 aa are replaced by 10 aa of a unique protein sequence; * and ** -cleavage sites by membrane-bound proteases ADAM17 and TMPRSS2, respectively. D) Alignments of the dACE2 5'UTRs in primates. E) Alignments of protein sequences encoded by dACE2-Ex1c and part of the downstream exon. dACE2 is not predicted to be encoded in any non-primate species. and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020.  and is also made available for use under a CC0 license. was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020.  and is also made available for use under a CC0 license. was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint and is also made available for use under a CC0 license. was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint A). Bubble plot showing mean expression levels (RNA-seq read counts) and proportions of samples (%) with dACE2-Ex1c in TCGA tumor-adjacent normal (AN) tissues and 33 tumor types. dACE2-Ex1c is expressed at relatively high levels and in many tumors of the bladder (BLCA), cervix (CESC), esophagus (ESCA), head and neck (HNSC), and lung squamous carcinoma (LUSC). B) RNA-seq counts of ACE2-Ex1a and Ex1b and dACE2-Ex1c in tumoradjacent normal (AN), squamous tumors (SQ) and non-squamous tumors (NSQ). Expression of dACE2 is significantly higher in SQ compared to NSQ tumors of the same tissue origin and corresponding AN tissues. Specifically -dACE2-Ex1c is expressed similarly in AN tissues adjacent to LUSC and LUAD, while it is significantly higher in corresponding tumors and higher in LUSC than in LUAD, due to clonal origin of these tumors from cells with differential expression of dACE2. P-values are for the nonparametric Mann-Whitney U test. and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint and is also made available for use under a CC0 license. was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint Figure 6. dACE2 is non-functional for binding SARS-CoV-2 spike protein RBD and as a carboxypeptidase. and is also made available for use under a CC0 license. was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint A) Representative confocal images of T24 cells transiently overexpressing dACE2-Myc (white), ACE2-GFP (green) and treated with receptor-binding domain (RBD) of SARS-CoV-2 spike protein (red), nuclei (DAPI)-blue; bars=20µM. B-D) Representative flow cytometry histogram B) and mean fluorescence intensity (MFI) values from 3 biological replicates C) of spike-RBD binding to the surface of ACE2-GFP but not dACE2-Myc expressing T24 cells. D) Representative flow cytometry plot showing gates for T24 cells co-transfected with dACE2-Myc and ACE2-GFP. Gates were drawn to identify cells expressing dACE2-Myc, ACE2-GFP, or both proteins. E) Histogram and F) plot depicting MFI of spike protein-RBD binding in gated cells from plot E, based on 3 biological replicates. Data represent one of two independent experiments. G) A representative Western blot showing detection of ACE2-GFP and dACE-GFP in protein lysates of T24 cells transfected with equal amounts of plasmids. Based on Western blot densitometry, equal estimated amounts of ACE2 and dACE2 proteins were used in peptidase activity assays in H. Results are based on 3 biological replicates. and is also made available for use under a CC0 license.
was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 The copyright holder for this preprint (which this version posted July 20, 2020. . https://doi.org/10.1101/2020.07.19.210955 doi: bioRxiv preprint