bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder.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
and is also made available for use under a CC0 license.
Interferons and viruses induce a novel primate-specific isoform dACE2 and not
the SARS-CoV-2 receptor ACE2
1,#
Olusegun O. Onabajo, 1,#A. Rouf Banday, 1Wusheng Yan, 1Adeola Obajemu, 2Megan L.
Stanifer, 3Deanna M. Santer,1Oscar Florez-Vargas, 4Helen Piontkivska, 1Joselin Vargas,
6,7
Carmon Kee, 3D. Lorne J. Tyrrell, 5Juan L. Mendoza, 6,7Steeve Boulant,
1
Ludmila Prokunina-Olsson
Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics,
National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
2
Department of Infectious Diseases, Molecular Virology, University Hospital Heidelberg,
Heidelberg, Germany
3
Li Ka Shing Institute of Virology and Department of Medical Microbiology and Immunology,
University of Alberta, Edmonton, Alberta, Canada.
4
Department of Biological Sciences and Brain Health Research Institute, Kent State University,
Kent, OH, USA
5
Pritzker School of Molecular Engineering and Department of Biochemistry and Molecular
Biology, University of Chicago, Chicago, IL, USA
6
Division of Cellular Polarity and Viral Infection, German Cancer Research Center (DKFZ),
Heidelberg, Germany
7
Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg,
Germany
#
these authors contributed equally and will list themselves first in their CVs.
1
* Corresponding author
Ludmila-Prokunina-Olsson, PhD
Laboratory of Translational Genomics,
Division of Cancer Epidemiology and Genetics,
National Cancer Institute,
9615 Medical Center Dr,
Bethesda, MD 20892-9776
Tel:+1-240-760-6531; Fax: +1 240-541-4442
E-mail: prokuninal@mail.nih.gov
Key words: ACE2, Interferon-stimulated gene, Interferon, SARS-CoV-2, COVID-19, immune
response
1
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder.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
and is also made available for use under a CC0 license.
ABSTRACT
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes COVID19, 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.
2
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
INTRODUCTION
Cells expressing ACE2 are potential targets of SARS-CoV-2 infection1,2. 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 cells3,4.
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 influenza4,5.
These findings implied that the induction of ACE2 expression in IFN-high conditions could
result in an amplified risk of SARS-CoV-2 infection4,5. Concerns could also be raised about
possible ACE2-inducing side effects of IFN-based treatments proposed for COVID-196-9.
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 ACE210,11. 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-1910,12. 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-1913,14.
High plasma angiotensin II levels were found responsible for coronavirus-associated acute
respiratory distress syndrome (ARDS), lung damage and high mortality in mouse models15,16 and
as a predictor of lethality in avian influenza in humans17,18. 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 cells4,5. 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 COVID-19.
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
3
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
cell types by IFNs and viruses; this information is important to consider for future therapeutic
strategies and understanding susceptibility and outcomes of COVID-19.
RESULTS
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 ISGs19-21.
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,
B).
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
4
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
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,
B).
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) cells22 and human intestinal (colon and ileum) organoid cultures23. 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 viruses – by 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
5
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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
and is also made available for use under a CC0 license.
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 infection4. 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 ISG4,5 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).
6
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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
and is also made available for use under a CC0 license.
Generally, dACE2 expression was enriched in squamous tumors representing epithelial tracts.
Squamous carcinomas of the lung (LUSC) and head and neck (HNSC) represent respiratory
tract, esophageal cancer (ESCA) - upper gastrointestinal, and bladder cancer (BLCA) and
cervical squamous carcinoma (CESC) - urogenital tract (Figure 4A). In each tumor type, dACE2
expression was significantly higher in squamous compared to non-squamous tumors and
adjacent-normal tissues (Figure 4B). Because tumors represent results of clonal expansion of
individual cells, this analysis highlighted the differential etiology (squamous vs. non-squamous)
of ACE2- and dACE2 expressing cells in various tissues.
dACE2 expression is IFN-γ-inducible
In addition to cell type origin, the observed enrichment of dACE2 expression in some tumors
might reflect persistent IFN exposure due to an inflammatory tumor microenvironment or
underlying infection. IFN-γ-induced signature emerged as a prominent feature in airway
epithelial cells of COVID-19 patients, and this signature was linked with enrichment of cytotoxic
T lymphocytes (CTLs)5. Unlike normal tissues, tumors are extensively infiltrated by immune
cells, making TCGA dataset particularly informative for the analysis of IFN signatures. IFNG
was the most commonly expressed IFN in TCGA tumors (with 61% of all tumors expressing
IFNG at RSEM ≥ 1, mean RSEM = 19.8), while other IFNs were poorly expressed (mean RSEM
≤ 1.3, Figure S8A). dACE2-Ex1c levels significantly correlated (P ≤ 0.01, r ≥ 0.2) with IFNG
expression in 8 out of 32 tumor types tested (Figure S8B), while ACE2-Ex1b showed only
moderate and predominantly negative correlations with IFNG expression in some tumor types
(Figure S8C). Furthermore, in vitro treatment with IFN-γ significantly induced dACE2, but not
ACE2 (Figure S8D). Thus, in addition to type I and type III IFNs (Figure 2E-G), dACE2
expression might be partly driven by IFN-γ contributed by tumor-infiltrating immune cells or
inflamed virally infected tissues.
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 ISGs24, 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
7
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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 RTPCR 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 cells23. Specifically, dACE2 was most strongly induced in
Caco-2 cells, in which over 80% of cells were infected by 24 hrs, moderately induced in T84
cells (20% of infected cells), and not induced in Calu3 cells (10% of infected cells). A similar
expression pattern was observed for an ISG IFIT1 except for Calu3 cells, in which IFIT1 was
significantly induced (Figure 5A, 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 tumors25, we detected human-specific peptides matching the 10 aa
8
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and is also made available for use under a CC0 license.
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 infection4,5 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
9
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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
and is also made available for use under a CC0 license.
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.
Suppression of IFN signaling by SARS-CoV-2 has been reported by several studies26,27, possibly
explaining only a moderate effect of SARS-CoV-2 infection on dACE2 induction in our
experiments. While type I and type III IFNs are barely detectable in COVID-19 patients28,29, high
levels of IFN-γ have been reported29,30. Specifically, a 3’-scRNA-seq analysis showed ACE2
induction by SARS-CoV-2 infection in ciliated epithelia, where high levels of IFN-γ producing
immune cells were also detected5. Our results strongly suggest that the induction of dACE2 and
not ACE2 was detected in these COVID-19 patients.
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 mice – because 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 evolution31 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
10
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and is also made available for use under a CC0 license.
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-CoV2 infection, ACE2 deficiency rather than overexpression is discussed as a major factor
contributing to COVID-19 morbidity12-14,32. Functional ACE2 deficiency occurs due to
internalization of the SARS-CoV-2 -ACE2 complex2,33, which restricts ACE2 from performing
its physiological functions, including its role as carboxypeptidase for angiotensin II and desArg9-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 population34,35 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
outcomes34. 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 disease10. 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
11
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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.
MATERIALS AND METHODS
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 described22 normal human bronchial
epithelial cells (NHBE) were isolated from normal lungs that were not used for transplantation.
The lungs were obtained from 5 de-identified donors via a tissue retrieval service (International
Institute for the Advancement of Medicine, Edison, NJ) with ethical approval from the Conjoint
Health Research Ethics Board of the University of Calgary and the Internal Ethics Board of the
International Institute for the Advancement of Medicine. Anonymized human tissue from colon
resections was obtained from the University Hospital Heidelberg, in accordance with the
recommendations of the University Hospital Heidelberg and written informed consent obtained
from all subjects in accordance with the Declaration of Helsinki. The protocol (S-443/2017) was
approved by the Ethics Commission of the University Hospital Heidelberg. Organoids were
generated from these tissues as previously described23.
Viral infections
Stocks of Sendai virus (SeV) Cantell strain were purchased from Charles River Laboratories.
Cells listed in Table S3 were infected in duplicates or triplicates with SeV (7.5×105 CEID50/ml)
for 12 or 24 hrs as previously described19-21.
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 described23. Briefly, the
infections were performed using the MOI=1 for cell lines. Organoids were infected with 3x105
FFU of the virus, based on titers in Vero E6 cells. Culture media was removed from
12
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
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-ACMyc-DDK (Origene) were used as controls.
Treatments with IFNs
All IFNs used are listed in Table S5. The IFN-treated NHBE cells were previously described22.
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 described23. 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.
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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
and is also made available for use under a CC0 license.
qRT-PCR
cDNA was synthesized from the total RNA with the RT2 First Strand Kit (Qiagen), Superscript
VILO IV (Thermo Fisher), or iSCRIPT cDNA kit (BioRad), always with an additional DNase I
treatment step. qRT-PCR assays were performed in technical duplicates in 96- or 384-well plates
on QuantStudio 7 (Life Technologies) or Bio-Rad CFX 96 instrument, with RT² SYBR Green
(Qiagen), POWER SYBR (Thermo Fisher), iTaq SYBR (BioRad) or TaqMan (Thermo Fisher)
expression assays (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
DNase digestion (Qiagen) and treated with Ribo-Zero (Illumina). RNA-seq libraries were
prepared from high-quality RNA samples (RIN scores >9.0) with KAPA Stranded RNA-seq Kit
with RiboErase (Roche). Paired 150-bp reads (21.2 - 118.8 million reads per sample) were
generated with HiSeq 2500 (Illumina) by the Cancer Genomics Laboratory (DCEG/NCI). The
reads were aligned with STAR alignment tool version 7.1.2a (21) using the GRChg37/hg19
genome assembly and visualized using the Integrative Genomics Viewer (IGV).
RNA-seq analysis of data from NCBI Sequence Read Archive (SRA) and TCGA
RNA-seq datasets (Table S6) were downloaded from NCBI SRA using SRA tools. The FASTQ
files were compressed using GZIP and aligned with STAR version 7.1.3a to the GRChg38/hg38
genome assembly. BAM files with less than 80% of mappable reads were excluded. BAM files
were indexed and sliced using SAM tools to include 51.6 Kb of the ACE2 genomic region
(chrX:15,556,393-15,608,016, hg38). For mouse RNA-seq data sets, the alignment was done
with reference genome mm10. For TCGA STAR-aligned RNA-seq data, BAM slices for the
ACE2 region were acquired for 11, 041 TCGA samples (10,328 tumors and 713 tumor-adjacent
normal tissues) through the NCI Genomics Data Commons (GDC) portal accessed on May 12,
2020, using workflow https://docs.gdc.cancer.gov/API/Users_Guide/BAM_Slicing/.
Estimation of RNA-seq read counts for ACE2 exons
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bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
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) and multiplying
by the geometric mean of the total reads of the three exons (Ex1a, Ex1b and Ex1c) across all
samples as a scaling factor to adjust for variability in sequencing coverage between samples. The
analysis of exon expression patterns within tissue subtypes was based on log 2-transformed raw
reads for each exon. Correlation analysis of normalized expression of ACE2-Ex1a and Ex1b and
dACE2-Ex1c with TPMs of IFNs, STATs, IRFs and select ISG controls (ISG15 and ISG20) was
performed in R using package dplyr.
Expression values for all IFN genes for all tumors in TCGA PanCancer Atlas were downloaded
as RSEM values from cBioPortal for Cancer Genomics (https://www.cbioportal.org/).
Expression of IFNL4, a most recently discovered IFN36, was not available in TCGA dataset
based on hg19/GRCh37 reference. Because IFNG was expressed in most samples compared to
other IFN genes (Figure S8A), it was used for further analysis. Correlation analyses of the
normalized expression of ACE2-Ex1b and dACE2-Ex1c were performed with log2(RSEM+1)
values for IFNG. Correlation patterns between IFNG and ACE2-Ex1a were similar to those
between IFNG and ACE2-Ex1b (data not shown).
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 list24. 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
structure37,38. 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
15
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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
and is also made available for use under a CC0 license.
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 tool39 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 engine25, 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
16
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and is also made available for use under a CC0 license.
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). The signals were detected with HyGLO Quick Spray (Denville
Scientific) or SuperSignal West Femto Maximum Sensitivity Substrate (Thermo Fisher) and
viewed on a ChemiDoc Touch Imager with Image Lab 5.2 software (BioRad).
Confocal microscopy
T24 cells were transiently transfected with ACE2-GFP, dACE2-Myc-DDK, or co-transfected
with both constructs in 4-well chambered slides (2x104 cells/well, LabTek). After 24 hrs, cells
were treated with 2 ng/ml of recombinant biotinylated SARS-CoV-2 spike protein RBD (spike
protein-RBD, Sino Biological) for 1 hour at 37°C. Cells were washed twice with media and then
stained with 5µg/ml streptavidin PE (Thermo Fisher) for 30 min at 37°C. Cells were then washed
twice with PBS and fixed with 4% paraformaldehyde (BD Biosciences) for 30 min. After rinsing
twice in PBS and permeabilization buffer (BD Biosciences), cells were incubated with
permeabilization buffer for 1hr. Fixed cells were incubated with rabbit anti-FLAG antibody
(1:250 dilution, Thermo Fisher) overnight, washed and then stained with anti-rabbit Alexa Fluor
680 (1:500 dilution, Thermo Fisher). Slides were mounted with antifade mounting media with
DAPI (Thermo Fisher) and imaged at 40X magnification on an LSM700 confocal laser scanning
microscope (Carl Zeiss) using an inverted oil lens.
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 (1x105 cells/well). After 24 hrs, cells were stained with
recombinant biotinylated spike protein RBD as described above and analyzed with
17
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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
and is also made available for use under a CC0 license.
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.
Acknowledgments
We thank Nathan Cole (DCEG/NCI) for help with the acquisition of TCGA sliced BAM files
and Dr. David Proud (University of Calgary) for providing NHBE cells. We thank the
CGR/DCEG/NCI for help with RNA-sequencing and authentication of cell lines by Identifiler
profiling. The results are partially based on data generated by TCGA Research Network. The
project was supported by the Intramural Research Program of the Division of Cancer
Epidemiology and Genetics, National Cancer Institute; HP was supported by the NIH grant
18
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
R21AG064479-01 and a Brain Health Research Institute Pilot Award from Kent State
University; SB and MS received financial support from the Deutsche Forschungsgemeinschaft
(DFG) project number 240245660 (SFB1129) 415089553 (Heisenberg) and 272983813
(TRR179) to SB and project number 416072091 to MS. DMS and DLJT received financial
support from the Li Ka Shing Institute of Virology.
NCBI GenBank accession number for dACE2: MT505392
URLs:
UCSC Genome Browser: https://genome.ucsc.edu/
TCGA Research Network: https://www.cancer.gov/tcga
Conflict of interest statement
Authors declare no competing interests
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bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
FIGURES
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
22
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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
and is also made available for use under a CC0 license.
transmembrane protein with a signal peptide (SigP) of 17 aa and four functional domains –
peptidase 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.
23
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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
and is also made available for use under a CC0 license.
Figure 2. dACE2 is induced by IFNs in vitro.
A) Schematic representation of ACE2 and dACE2 transcripts and the position of the forward (F)
and reverse (R) PCR primers to generate full-length dACE2 amplicons. B) Agarose gel showing
an RT-PCR product of 1535 bp corresponding to full-length dACE2 in several cell lines
with/without SeV infection. C) Heatmap of ACE2 and dACE2 expression and a positive control
ISG (ISG15) measured by TaqMan expression assays in human cell lines infected with SeV for
12 hrs; colors represent expression differences as ddCt (log2) normalized by endogenous
controls (GAPDH and ACTB) and comparing SeV-infected to uninfected samples. D) Expression
of ACE2 and dACE2 and the positive control ISG MX1 in primary normal human bronchial
epithelial (NHBE) cells treated with IFNα or IFN-λ3 for 24 hrs vs. untreated cells. E) Expression
of ACE2 and dACE2 and the positive control ISG IFIT1 in colon and ileum organoid cultures
from one donor; the organoids were treated with IFNβ or a cocktail of IFN-λ1-3 for 24 hrs. Pvalues are for Student’s T-test.
24
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
Figure 3. dACE2 is induced in virally infected human respiratory cells.
Expression patterns of ACE2, represented by Ex1a and Ex1b and dACE2, represented by Ex1c in
A-C) mock (ctrl) and rhinovirus (RV)-infected human nasal epithelial cells and D-E) in
uninfected (ctrl) and influenza H5N2-infected cells from human lung explants. A) RNA-seq
Sashimi plots B) Expression levels C) Correlation coefficients with select ISGs and IFNs in the
full dataset of 90 samples. D) Expression levels E) Correlation coefficients with select ISGs and
IFNs in the full dataset of 20 samples. FC – fold change compared to mock. P-values are for the
non-parametric Mann–Whitney U test.
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bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
Figure 4. Expression of dACE2 is enriched in squamous epithelial tumors.
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bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
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.
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bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
Figure 5. dACE2 is induced by SARS-CoV-2 in human cell lines and organoid cultures.
Expression of ACE2, dACE2 and a control ISG IFIT1 in A) colon cancer cell lines Caco2 and
T84 and a lung cancer cell line Calu3 and C) colon and ileum organoid cultures derived from
two donors; B and D) SARS-CoV-2 viral loads in corresponding cells. P-values are for Student’s
T-test.
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bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
Figure 6. dACE2 is non-functional for binding SARS-CoV-2 spike protein RBD and as a
carboxypeptidase.
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bioRxiv preprint doi: https://doi.org/10.1101/2020.07.19.210955. this version posted July 20, 2020. The copyright holder for this preprint (which
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
and is also made available for use under a CC0 license.
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.
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