key: cord-1054190-92fa0hf4
authors: Nakayama, Tsuguhisa; Lee, Ivan T.; Jiang, Sizun; Matter, Matthias S.; Yan, Carol H.; Overdevest, Jonathan B.; Wu, Chien-Ting; Goltsev, Yury; Shih, Liang-Chun; Liao, Chun-Kang; Zhu, Bokai; Bai, Yunhao; Lidsky, Peter; Xiao, Yinghong; Zarabanda, David; Yang, Angela; Easwaran, Meena; Schürch, Christian M.; Chu, Pauline; Chen, Han; Stalder, Anna K.; McIlwain, David R.; Borchard, Nicole A.; Gall, Phil A.; Dholakia, Sachi S.; Le, Wei; Xu, Le; Tai, Chih-Jaan; Yeh, Te-Huei; Erickson-Direnzo, Elizabeth; Duran, Jason M.; Mertz, Kirsten D.; Hwang, Peter H.; Haslbauer, Jasmin D.; Jackson, Peter K.; Menter, Thomas; Andino, Raul; Canoll, Peter D.; DeConde, Adam S.; Patel, Zara M.; Tzankov, Alexandar; Nolan, Garry P.; Nayak, Jayakar V.
title: Determinants of SARS-CoV-2 entry and replication in airway mucosal tissue and susceptibility in smokers
date: 2021-09-28
journal: Cell Rep Med
DOI: 10.1016/j.xcrm.2021.100421
sha: 3a2530b59531167e9670bc606bd5a025a13c30bf
doc_id: 1054190
cord_uid: 92fa0hf4

Understanding viral tropism is an essential step towards reducing SARS-CoV-2 transmission, decreasing mortality from COVID-19, and limiting opportunities for mutant strains to arise. Currently, little is known about the extent to which distinct tissue sites in the human head & neck region and proximal respiratory tract selectively permit SARS-CoV-2 infection and replication. In this translational study, we discover key variabilities in the expression of ACE2 and TMPRSS2, essential SARS-CoV-2 entry factors, among the mucosal tissues of the human proximal airways. We show that SARS-CoV-2 infection is present in all examined head & neck tissues, with a notable tropism for the nasal cavity and tracheal mucosa. Finally, we uncover an association between smoking and higher SARS-CoV-2 viral infection in the human proximal airway, which may explain the increased susceptibility of smokers to developing severe COVID-19. This is at least partially explained by differences in IFN-β1 levels between smokers and non-smokers.

The causative agent of the Coronavirus Disease 2019 (COVID- 19) , SARS-CoV-2, infects host cells via initial attachment to angiotensin-converting enzyme 2 (ACE2) and subsequent priming by host entry factors including transmembrane serine protease 2 (TMPRSS2). 1 Mucosal surfaces of the head & neck, comprising the nasal and oral cavities and ocular conjunctiva, are the primary portals of entry for most respiratory viruses, including SARS-CoV-2. We and others have previously shown that nasal mucosal surfaces are a primary site for SARS-CoV-2 infection. 2, 3 On the other hand, the infectivity of SARS-CoV-2 in the oral mucosa is unknown. Although saliva specimens are widely used in diagnostic testing, it is uncertain whether detected viral RNA in the saliva originates from retro-nasal transit of secretions or from active viral replication within the oral epithelium. By contrast, ocular mucosa does not appear to be a major transmission route for SARS-CoV-2, given the limited viral loads and low rate of positive SARS-CoV-2 detection from conjunctival swabs, 4, 5 although inoculation through the nasolacrimal duct (ocular-to-nasal route) has been shown to result in SARS-CoV-2 infection in a limited number of non-human primates. 6 Understanding the tissue-specific tropism of SARS-CoV-2 for the distinct mucosal surfaces of the head & neck region is fundamental for both the prevention and treatment of viral infection. Firstly, knowledge of SARS-CoV-2 transmission dynamics has guided the use of non-pharmaceutical interventions such as face masks and physical distancing to a great effect. 7 Secondly, aspiration of SARS-CoV-2 from nasal and/or oral secretions into the lungs is the likely initiator of viral pathogenesis and subsequent acute lung injury, the primary cause of mortality in COVID-19. 2, 8 Reduction of viral transmission from the upper into the lower airway will likely improve clinical outcomes. Thirdly, variants of SARS-CoV-2 with more efficient transmission have arisen during the process of viral replication. Available evidence suggests that recent mutant strains, including the Delta variant, are associated with higher viral loads from nasal/oral swab specimens and increased efficiency of transmission. [9] [10] [11] Strategies to reduce viral replication at targeted anatomic sites will likely be effective in decreasing both SARS-CoV-2 mortality and transmission as viral load correlates with disease severity and infectivity. [12] [13] [14] Additionally, several antiviral intranasal 15, 16 , inhaled 17, 18 , and oral rinse 19, 20 formulations targeting the upper respiratory mucosa are currently under investigation and may become important measures to reduce COVID-19 disease burden/transmission.

In this study, we comparatively analyzed the expression of essential SARS-CoV-2 entry factors, ACE2 and TMPRSS2, across various normal human proximal mucosal tissues of the head & neck (nasal, oral, pharyngeal, laryngeal, tracheal, and ocular), to gain insight into the tissue tropism and host-viral interactions of SARS-CoV-2 (see graphical abstract). We next quantified the intracellular levels of SARS-CoV-2 viral infection in head & neck mucosal tissues from patients with COVID-19 and discovered that an array of distinct proximal airway tissues serves as infection sites for SARS-CoV-2. Notably, the nasal cavity and trachea were the most prominent sites of viral infection, harboring significant quantities of viral nucleic acids even after individuals succumbed to COVID-19. Finally, comparative analysis of SARS-CoV-2 infection among COVID-19 patients revealed clinical characteristics, such as smoking status, that were associated with heightened intracellular SARS-CoV-2 propagation.

ACE2 & TMPRSS2 are expressed in human nasal, oral, and ocular mucosal surfaces SARS-CoV-2 entry factors, ACE2 and TMPRSS2, have been previously reported to be expressed in human head & neck mucosal surfaces including the nasal cavity, 2,3,21 oral cavity, 22, 23 and eyes. 24 A comprehensive and comparative analysis of ACE2 and TMPRSS2 protein expression across these primary barrier tissues is lacking and of paramount importance in understanding the various mucosal routes of entry for SARS-CoV-2. We therefore defined the landscape of ACE2 and TMPRSS2 expression in head & neck mucosal tissues from normal controls and COVID-19 individuals ( Figure 1A ).

We first integrated RNA expression from a number of published scRNA-seq datasets ( Figure 1B ). [25] [26] [27] [28] [29] [30] [31] We focused our analysis on epithelial cells given that this population is the most accessible and plausible initial target of viral entry, and also the most abundant cell population in head & neck mucosal tissues. 21, 32, 33 We annotated five major epithelial cell types using a number of well-established markers, including those described here ( Figure 1B , S1A and S1B). 34 ACE2 expression was generally sparse in the reported transcriptome datasets ( Figure  1C , D, and E), but was highly expressed when present in the ciliated and secretory epithelial cells of head & neck tissues ( Figure 1C ). We observed variable levels of ACE2 expression across the nasal, tracheal, and bronchial tissues with a subset of epithelial cells from each tissue type demonstrating elevated ACE2 RNA expression ( Figure 1D and E), although anatomy-specific comparisons were inconclusive due to the sparse expression of ACE2 RNA and the low percentage of ACE2 positive cells ( Figure 1C , D and E). Our analysis found TMPRSS2 expression to be more robustly expressed and detected in the epithelial cells, especially in ciliated cells, of these head & neck tissues ( Figure 1C , D, and E). Comparison of TMPRSS2 expression levels across these tissue types suggested higher expression in the nasal cavity, trachea, and bronchus but lower expression in the tongue ( Figure 1D ). We also analyzed the expression level of other putative SARS-CoV-2 entry factors, TMPRSS4, 35 transferrin receptor (TFRC), 36 and neuropilin1 (NRP1). 37, 38 TMPRSS4 was expressed in all epithelial cells, particularly secretory and basal cells of the nasal cavity. TFRC expression was highest in the tongue, and NRP1 was very sparsely expressed overall (Figure S1C, D, and E). These analyses were notably limited given that these RNA datasets largely derived from diseased tissues rather than healthy donor controls, and the limitations of detecting low abundance transcripts, such as ACE2, via single-cell transcriptomic studies.

Since proteins represent the functional product of RNA transcripts, we next investigated the protein expression of the two most established viral entry factors, ACE2 and TMPRSS2, across an array of normal human mucosal epithelia to further define the potential relevance of each tissue to SARS-CoV-2 transmission dynamics. We performed immunofluorescence staining of these tissues simultaneously using previously validated antibodies against ACE2 3 (see Figure 2A for further antibody validation), the epithelial marker pan-cytokeratin (panKRT), and the cilia marker acetylated α-tubulin (ACTUB). We observed robust ACE2 expression within the epithelia of all stained tissues ( Figure 3A and S2). Consistent with our prior findings, 3 this protein expression was prominent in the cilia organelle of the ciliated epithelial tissues in the nasal cavity, nasopharynx, and trachea/bronchus ( Figure 3A and S2). Quantitative analysis of this data showed ACE2 expression to be higher in the trachea/bronchus compared to the nasopharynx, oro/hypo-pharynx, and conjunctiva ( Figure 3B , p < 0.05). There were no statistical differences in ACE2 expression between the trachea/bronchus, nasal cavity, tongue, larynx, and esophagus ( Figure 3B ). We also did not observe any significant differences in ACE2 expression within the motile cilia of the analyzed ciliated tissues ( Figure 3C ). Overall, ACE2 is expressed among numerous mucosal surfaces of the head & neck with modest inter-regional variance.

Next, we evaluated TMPRSS2 expression within the epithelial cells and cilia of these mucosal tissues using validated antibodies against TMPRSS2 39 (see Figure 2B for antibody validation), panKRT, and ACTUB. Similar to ACE2 expression, TMPRSS2 protein expression was also observed in the epithelia and cilia organelles of the ciliated epithelium (when anatomically present) of all stained tissues ( Figure 3D and S3). However, we found TMPRSS2 expression to be significantly higher in the mucosa of the nasal cavity and trachea/bronchus compared to the tongue, oro/hypo-pharynx, esophagus, and conjunctiva ( Figure 3E , p < 0.05). Within the motile cilia, TMPRSS2 expression was notably elevated in the nasal cavity compared to the nasopharynx and trachea/bronchus ( Figure 3F , p < 0.01). These patterns of TMPRSS2 expression within the epithelia suggest that while proximal airway and ocular tissues are all susceptible to SARS-CoV-2, greater TMPRSS2 expression in the nasal cavity and trachea/bronchus may render these airway sites particularly conducive to SARS-CoV-2 infection and proliferation.

Diagnostic swab sampling of the nasal and oral cavities detects shedded SARS-CoV-2 virus in the respective mucus/saliva secretions and is the basis of most RNA-based COVID-19 testing methods. 40 However, nasal secretions physiologically drain into the oropharyngeal space, rendering infeasible the use of swab samples to localize the primary sites of major viral infection and intracellular replication. To test the hypothesis that SARS-CoV-2 infects and replicates intracellularly in multiple head & neck mucosal epithelial surfaces, we evaluated SARS-CoV-2-infected human proximal airway (nasal cavity, tongue, pharynx, larynx, trachea) tissues collected postmortem at autopsy from 27 patients with COVID-19 between March and July 2020. All 27 patients (n=18 male, n=9 female) were diagnosed with COVID-19 by a positive reverse transcription polymerase chain reaction (RT-PCR) test for SARS-CoV-2. The median age at death was 74.7 years (interquartile range, 66-82 years; range, 53 to 96 years), and the time from onset of known COVID-19 symptoms to death ranged from 4 to 44 days, with a median of 19 days (Table S1 ). Cases were not preselected with regard to clinical characteristics owing to the extreme challenges of tissue procurement in the pandemic setting. Due to potential for body disfigurement and unavailability of an ophthalmic pathologist during the time of autopsy, we were unable to obtain a meaningful number of ocular tissues from COVID-19 patients. Ocular tissues were obtained from 3 patients in our cohort, but only one specimen had detectable low levels of SARS-CoV-2 RNA. 41 We performed in situ hybridization (ISH) using a robustly validated SARS-CoV-2 Spike mRNA probe in combination with antibodies against panKRT and ACTUB on these proximal respiratory tract and oral tissues (see Figures S4A-C for independent SARS-CoV-2 probe validation). 42 The rationale for quantifying SARS-CoV-2 Spike RNA, rather than Spike protein, was to minimize confounding or artifactual signal due to partially degraded Spike protein fragments detected in the extracellular space or taken up by cells, leading to misrepresentation of SARS-CoV-2 localization. 43 Viral RNA also allows the additional benefit of being present as both part of the virion as well as an accurate indicator of viral replication and transcription in an infected cell. 44 As above, we focused on SARS-CoV-2 infection in the head & neck mucosal epithelium, which faces the airway lumen and is relevant to the dynamics of respiratory viral transmission. Interestingly, we observed SARS-CoV-2 viral RNA within the epithelia of all 5 distinct proximal airway tissue sites ( Figure 4A ). The olfactory cleft, part of the superior nasal cavity along the skull base, also stained positive for SARS-CoV-2 RNA ( Figure 5 ) as was similarly demonstrated by Meinhardt et al. 45 Comparatively, SARS-CoV-2 RNA was significantly more abundant in the nasal and tracheal epithelia compared to the lingual (tongue) epithelium, with respect to both infected surface area and copies of RNA within the infected area ( Figure 4B and C, p < 0.05). Intermediate levels of SARS-CoV-2 RNA transcripts were detected in the epithelia of the pharynx and larynx compared to the nasal cavity/trachea and the tongue ( Figure 4B and C). These results demonstrate that in COVID-19 patients, SARS-CoV-2 infects and propagates within multiple regions of the proximal respiratory tract from the nasal cavity to the tongue. Our findings further implicate the nose and the trachea as primary sites of SARS-CoV-2 infection amongst the mucosal surfaces of the head & neck region.

We next identified clinical characteristics that could potentially account for the variability in SARS-CoV-2 transcription noted amongst nasal and tracheal tissues from individual COVID-19 patients. Minimal inter-subject viral load variance was seen in the tongue, pharyngeal, and laryngeal tissues, thus only nasal and tracheal samples (n=24 patients) were compared ( Figure 4B and C). We first determined the extent to which epithelial SARS-CoV-2 RNA infection differs by age, gender, body mass index (BMI), smoking status, hypertension, and diabetescovariates reported to be associated with COVID-19 disease severity. Patient demographics and clinical comorbidities are listed in Table  S1 . Known coexisting medical conditions included obesity (n=9), diabetes mellitus (n=10), and hypertension (n=15).

We found no significant differences in SARS-CoV-2 RNA abundance based on age, gender, or BMI ( Figure S5A -C). There was also no correlation between SARS-CoV-2 RNA and duration of disease ( Figure S5D ; e.g. days between initial symptom onset and death), similar to the findings of a recent preprint. 46 Interestingly, SARS-CoV-2 RNA levels were significantly higher amongst smokers (both current and former) compared to non-smokers ( Figure 6A , p < 0.01). We also identified a trend towards higher SARS-CoV-2 RNA levels in patients with diabetes mellitus ( Figure 6B ), but these results were not statistically significant due to the low sample size. No significant differences were noted between patients with or without hypertension ( Figure 6C ). We then compared SARS-CoV-2 RNA levels between patients who received systemic steroids, antivirals, or interleukin-6 (IL-6) inhibitors during the course of their hospitalization for COVID-19. Not surprisingly, neither steroid nor tocilizumab intervention was associated with changes in SARS-CoV-2 RNA expression in the proximal airways ( Figure S5E and S5F), but paradoxically, patients who received antiviral medications displayed statistically significantly higher tissue levels of SARS-CoV-2 RNA ( Figure S5G ) (see discussion). Overall, these results indicate that smoking status (current or former) is associated with higher SARS-CoV-2 propagation in the proximal respiratory tract and may explain why smokers are at a higher risk for heightened severity of COVID-19 disease. 47, 48 Further studies with larger sample sizes will be necessary for validation.

To further elucidate potential mechanisms of elevated SARS-CoV-2 infection in smokers, we first assessed ACE2 and TMPRSS2 expression in these tissues as higher levels of entry factors may facilitate SARS-CoV-2 infection. Epithelial and ciliary ACE2 and TMPRSS2 protein expression were not significantly different between upper airway tissues of smokers and non-smokers ( Figure S6A and B). We also cultured human nasal epithelial cells (HNEpCs) in air liquid interface (ALI) and found no significant differences in ACE2 and TMPRSS2 expression between cigarette smoke extract (CSE) exposed and non-exposed controls ( Figure S6C ). We next compared interferon β1 (IFNB1) expression between upper airway tissues of smokers and non-smokers as cigarette smoke exposure has been shown to decrease Type 1 interferon signaling, 49 and IFN-β1 has been demonstrated to play an important role in abrogating SARS-CoV-2 infection in CS-exposed ALI cultures. 50 We performed in situ hybridization using probes against IFNB1 and another inflammatory cytokine, IL6, in combination with antibodies against CD45. IFNB1 expression within epithelial cells and CD45 + immune cells were significantly lower in upper airway tissues from smokers, but IL6 expression did not differ ( Figure 7A and S6E). Similarly, ex vivo, IFNB1 expression was significantly lower in CSE-exposed HNEpCs in ALI culture compared to controls ( Figure S6D ).

To show the causative effects of smoking on IFNB1 expression and subsequent increased susceptibility to SARS-CoV-2 infection, we exposed CSE to HNEpCs in ALI culture prior to infection with SARS-CoV-2 ex vivo ( Figure 7B ). We observed that CSE exposure significantly increased the number of cells productively infected by SARS-CoV-2 compared to non-exposed controls ( Figure 7C and D). Furthermore, the addition of recombinant IFN-β1 to the ALI culture abrogated the SARS-CoV-2 replication in both CSE exposed HNEpCs and controls ( Figure 7C and D). These results are consistent with prior findings of reduced interferon response after CS exposure and abrogation of SARS-CoV-2 infection by exogenous IFN-β1 in human bronchial/lung tissues. 50 Overall, our results suggest downregulation of IFN-β1 as a mechanism that at least partially explains higher SARS-CoV-2 infection in smokers.

We report here several notable discoveries in this human translational research study. First, we found that ACE2 and TMPRSS2, the primary entry factors of SARS-CoV-2, are expressed in a wide range of human mucosal surfaces of the head & neck including the tongue, pharynx, larynx, conjunctiva, and most prominently in the nasal cavity and trachea. Importantly, antibody-based protein staining has consistently yielded robust information compared to single-cell gene expression analyses, 3 which are likely confounded by the low expression levels of ACE2. Second, in line with these results, we observed that SARS-CoV-2 can infect and propagate in disparate head & neck mucosal tissues, and viral infection is particularly enriched in the nasal cavity and the trachea. This tissue tropism may be explained by our findings of enriched TMPRSS2 gene and protein expression in the epithelia of the nasal cavity and the trachea. Another nonmutually exclusive explanation is that the nasal cavity and trachea contain high proportions of ciliated epithelium, in contrast to the squamous and/or pseudostratified epithelium of the other mucosal tissues examined. We and others have previously shown that ciliated epithelial cells of the nose and trachea are the initial/early sites of entry for SARS-CoV-2, 2,3 in large part because ACE2 and TMPRSS2 show robust expression in the motile cilia of the airway lumen, compared to the epithelial cell body (Figure 3 ), 3 which is supported by the results of scRNA-seq in this study. Notably, since the head & neck tissue subsites shown herein were obtained at autopsy from patients who succumbed to COVID-19, the SARS-CoV-2 Spike RNA detected via ISH represents RNA replication throughout the course of the disease rather than early viral transmission. Given our results, it is possible that the degree of viral propagation is a consequence of early viral entry and sustained epithelial cell infection, as the nose and trachea are also early sites of infection. Finally, other entry factors such as TMPRSS4, TFRC, and NRP1 may also play a role in determining SARS-CoV-2 tissue tropism. Further studies are underway to further determine the protein expression of these entry factors within head & neck tissues.

Our findings of robust SARS-CoV-2 transcription in the nasal cavity supports the idea that the nasal epithelium is not only an early site of entry 2,3 but also a prominent site of ongoing SARS-CoV-2 replication. In line with our findings, the loss of sense of smell termed anosmia is a common and long-lasting symptom of COVID-19, 51 and has been attributed to SARS-CoV-2 infection of the olfactory cleft in the nasal cavity. 45, 52 Ageusia, the loss of taste, is another symptom frequently associated with COVID-19 51 with possible mechanisms being viral damage of gustatory receptors in the tongue or as a secondary consequence of anosmia, as olfaction strongly contributes to taste perception. Our findings of relatively lower levels of SARS-CoV-2 infection in the tongue, in contrast to the nose ( Figure 4B and C) , suggest the latter hypothesis as the more likely mechanism for dysgeusia, and would be an interesting future area of research.

The observation in this study that SARS-CoV-2 can infect and replicate in the oropharynx and the tongue suggests that the oral mucosa can serve as an additional reservoir, or an indicator for host SARS-CoV-2 infection status. Recent studies have reported that both saliva and nasopharyngeal viral load correlate with COVID-19 disease severity, with saliva viral loads as a potentially better indicator for cumulative viral load due to admixed secretions from the nose and the lower respiratory tract. [12] [13] [14] 46 J o u r n a l P r e -p r o o f Whether SARS-CoV-2 directly infects the oral cavity upon aerosol/droplet exposure, or indirectly via the nasal-to-oral route is uncertain. Nasal secretions drain into the pharynx, larynx, oral cavity, and even trachea, allowing viral particles from the nasal cavity to potentially seed the remaining downstream mucosal tissues, and prime the oral route of transmission to new hosts. Our finding of relatively lower SARS-CoV-2 transcription in the tongue, compared to the nose, is in support of an indirect route of oral tissue infection via the nose. However, in a recent study of the influenza virus using a ferret model, throat swabs of flu-infected ferrets sometimes tested positive for influenza before nose swabs, suggesting that viral deposition and infection can also be initiated in the oropharyngeal cavity for other respiratory viruses. 53 Studies of SARS-CoV-2 in animal models are needed to deduce the mechanisms of viral replication and deposition in the oral mucosa, which will have important implications for understanding and prevention of transmission dynamics of COVID-19.

Notably, in the present study, we found that current and former smokers have higher SARS-CoV-2 infection in the proximal respiratory tract. This result is supported by findings that cigarette smoke exposure increases the number of SARS-CoV-2 infected airway epithelial cells ex vivo ( Figure 7D ). 50 Although meta-analyses and our own data herein suggest that smokers may not be at a higher risk for SARS-CoV-2 initial infection given the absence of ACE2 and TMPRSS2 upregulation in smokers ( Figure S6A , B, and C), 3, 47, 48 once infected with the virus, smokers are at an increased risk of severe COVID-19 outcome. 47, 48 Our findings of reduced IFN-β1 expression in both upper airway tissues from smokers and CSE exposed HNEpCs, as well as the abrogation of SARS-CoV-2 infection by recombinant IFN-β1 suggest that a defective interferon response from cigarette smoking 49 may compromise cellular antiviral defense, leading to higher viral replication. Alternatively, impairments in mucociliary clearance in the proximal airway, seen in both current and former smokers, 54,55 may perpetuate local infection of neighboring cells from infected cells, leading to overall greater or sustained SARS-CoV-2 replication, which in turn leads to higher susceptibility to severe COVID-19 disease. Indeed, of all clinical characteristics available for our analyses, smoking is the only variable that directly impacts the airway tissue. In this study, we also observed a tendency towards higher SARS-CoV-2 infection in the airway of patients with diabetes ( Figure 6B ). Although statistical significance was not achieved, this finding is consistent with a recent study demonstrating a trend of prolonged viral shedding in the lungs of diabetics. 56 Additionally, we unexpectedly found that patients who had received antiviral therapy had higher SARS-CoV-2 infection in the proximal airway ( Figure S5G ). Aside from the small sample size of this patient cohort, one major caveat is that 4 of the 5 patients in this group had only received a 2-day course of either remdesivir or lopinavirritonavir in the 2 days preceding death, and one of the patients received remdesivir very late into the disease course (20 days following symptom onset). Although early trials of lopinavir-ritonavir and remdesivir did not demonstrate a reduction in viral load from upper airway swab specimens, 57,58 more recent larger trials have not provided viral load data. 59, 60 Whether a complete and earlier course of antiviral treatment may decrease SARS-CoV-2 replication in the proximal airways is not established. It also remains to be seen whether antivirals can decrease viremia (regardless of their clinical efficacy). We caution against overinterpretation of our findings due to these possible confounders as well as study limitations discussed below. Lastly, our findings that the use of steroids or tocilizumab was not associated with higher SARS-CoV-2 infection in the proximal airway is consistent with recent studies measuring viral load from nasopharyngeal swabs. 61, 62 Limitations of the Study This study has expected limitations in the setting of the ongoing pandemic. The sample size of our COVID-19 patient cohort has been constrained by the logistical challenges and precautions required when harvesting SARS-CoV-2 infected head & neck tissues. Similarly, the sample size of our HNEpCs was also limited by tissue availability and challenges of conducting experiments under Biosafety Level 3 (BSL3). Our study was likely underpowered to detect statistically significant differences in SARS-CoV-2 infection in patients with diabetes, hypertension, and obesitycomorbidities that may predispose to higher SARS-CoV-2 viral replication given their association with greater disease severity. However, the patient cohort presented here contains the largest published collection of head & neck and proximal airway tissues from COVID-19 patients to date. An additional limitation is that, as is the case with any observational study, we cannot infer a causal relationship between SARS-CoV-2 infection and clinical characteristics including smoking and antiviral usage. There may be potential confounders that can independently influence levels of viral replication in these individuals. Treatment selection bias, such as the use of antivirals in patients deemed to have more severe disease, is possible. Additionally, because we analyzed only tissues procured at autopsy from patients who died of COVID-19, we are unable to associate viral replication with clinical outcome, nor derive a more mechanistic understanding of SARS-CoV-2 pathogenesis. Regardless of the differing amounts of SARS-CoV-2 replication present, all of these patients had succumbed to COVID-19. However, it is conceivable that a therapeutic intervention that was unavailable earlier in the pandemic would have prevented their death. The REGN-COV2 antibody cocktail, for example, has been shown to be more effective in outpatients with a higher baseline viral load. 63 Finally, although SARS-CoV-2 has been infrequently isolated from conjunctival swabs or tears, 4,5 we were unfortunately unable to comparatively assess SARS-CoV-2 propagation in ocular tissues. Likewise, we confined our analysis to head & neck and proximal airway tissues, and did not examine lung tissues.

In summary, we describe here how the diverse human head & neck mucosal tissues, particularly the nasal cavity and trachea, serve as active sites of SARS-CoV-2 infection. Measures directed at reducing SARS-CoV-2 propagation in these anatomic regions will likely not only reduce mortality and transmission but also limit opportunities for SARS-CoV-2 mutant strains to arise. There is emerging evidence that novel SARS-CoV-2 variants can arise from the upper respiratory tract of immunocompromised hosts. 64, 65 Therapeutics administered through the upper airway have the potential to hamper SARS-CoV-2 evolution, especially in persistently infected individuals. Nasally administered povidone-iodine, 16 inhaled ciclesonide, 17 

I.T.L. is currently an employee and shareholder of Moderna although this work was conducted prior to or independent of his employment. I.T.L. had also received research support unrelated to this study from Genentech (Roche). Moderna did not fund nor participate in any form in this study. All other authors declare no competing interests relevant to this work.

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Jayakar V. Nayak (jnayak@stanford.edu).

This study did not generate new unique reagents.

This paper analyzes existing, publicly available RNA datasets. The accession numbers for these datasets are listed in the key resources table. The analysis codes used to support additional findings of this study were minimally modified from previously published codes 3 and are available at: https://github.com/bmyury/membrane_ACE2_quantitation. Additional data reported in this paper will be shared by the Lead Contact upon reasonable request.

Normal human tissue specimen collection. Normal tissues from the nasal cavity and the paranasal sinuses (collectively termed "nasal" tissues) were collected from healthy control donors (range 12-82 years; n=4 male and n=7 female) from the Stanford Sinus Center within the Stanford University School of Medicine. These controls were patients without history, endoscopic, or radiographic evidence of sinus disease, but underwent sinus procedures for surgical treatment of adjacent anatomic sites, such as for repair of cerebrospinal fluid leaks at the skull base. All tissue specimens were collected under approved Institutional Review Board (IRB) protocols in accordance with the regulations of the Research Compliance Office (protocol ID #18981 at Stanford University). All subjects provided informed consent. Following surgical excision, sinonasal specimens were placed in physiologic saline, immediately transported to the lab, and placed in 10% neutral buffered formalin for 24-48 h before paraffin embedding. Sinonasal tissues that contain bone were placed into EDTA for bone decalcification prior to embedding into tissue blocks. Normal formalin-fixed, paraffin-embedded (FFPE) human tissues of the nasopharynx (range 21-67 years; n=3 male and n=4 female), oro/hypo-pharynx (range 38-71, n=6 male and n=4 female), trachea/bronchus (range 19-68 years; n=12 male and n=9 female), and conjunctiva (range 52-85 years; n=4 male and n=0 female) were selected from Stanford University Pathology archives based on specific notation of disease absence and normal histology. Additional utilized tissue sections include normal human tissue microarrays obtained from US Biolab XHN801 (tongue) and XHN803 (tongue) as well as US Biomax OR208a (tongue) (range 22-73 years; n=12 male and n=4 female), BN1002b (esophagus) (range 22-42 years; n=4 male and n=1 female), and LP208 (Larynx (range 16-48 years; n=3 male and n=1 female), oro/hypo-pharynx (range 15-43 years; n=2 male and n=2 female)). Normal histology was independently confirmed again by board-certified pathologists, M.S.M., C.M.S., and A.T., using H&E stained images for evaluation.

SARS-CoV-2 infected proximal respiratory tract tissues were obtained during autopsy at the University Hospital Basel Switzerland, University of California San Diego, California, and Columbia University School of Medicine, New York City. Tissues were processed in a similar manner as previously described, 68 and collection was approved by the ethics commission of Northern Switzerland (EKNZ; study ID #2020-00969) and the Institutional Review Board (IRB) in accordance with the regulations of the Research Compliance Office (protocol ID #200485X at University of California San Diego, #AAAT0689 at Columbia University School of Medicine). All COVID-19 patients or their relatives consented to the use of tissue for research purposes. Smoking status (current/former/never) was defined based on self-reports in the electronic medical record. Patients were considered to have hypertension and/or diabetes mellitus based on documented pre-existing medical history and the use of medications for hypertension and/or diabetes mellitus on admission. Patients whose co-morbidities or use of medications could not be confirmed were excluded from data analyses in Fig. 6 and S5 (see Table S1 ).

Publicly available single cell RNA-seq datasets pertaining to nasal tissues, [25] [26] [27] bronchial tissues, 25, 29 trachea, 28 and tongue 30 were downloaded and processed with Seurat 31 , where the data was processed in parallel by normalization with the NormalizeData() function, followed by variable feature identification with FindVariableFeatures(), and data scaling subsequently with ScaleData().

Automated cell type annotation was performed with SingleR 69 using the Human Primary Cell Atlas data in celldex, 69, 70 with the primary focus of isolating epithelial cells. Since the datasets were of different library preparation methods and tissue sources, we performed data integration in Seurat using the FindIntegrationAnchors() and IntegrateData() functions, as previously described. 31 Five major epithelial cell types identified here, namely secretory cells (SCGB1A1, KRT15, LYPD2, KRT4, KRT13), basal cells (KRT5, DAPL1, TP64), ciliated cells (FOXJ1, CCDC153, CCDC113, MLF1, LZTFL1), ionocytes (FOXI1, CFTR, ASCL3), and others. We refer readers to a more detailed annotation list described here. 34 Plots were generated in Seurat or ggplot directly. 71

Sections were cut to 4 µm thickness and mounted on frosted glass slides. Deparaffinization, rehydration, and heat-induced epitope retrieval (HIER) were performed on a ST4020 small linear stainer (Leica). For deparaffinization, slides were baked at 70 °C for 1-1.5 h, followed by rehydration in descending concentrations of ethanol (100% twice, 95% twice, 80%, 70%, ddH2O twice; each step for 30 s). Washes were performed using a Leica ST4020 Linear Stainer (Leica Biosystems, Wetzlar, Germany) programmed to three dips per wash for 30 seconds each. HIER was performed in a Lab VisionTM PT module (Thermo Fisher) using Dako Target Retrieval Solution, pH 9 (S236784-2, DAKO Agilent) at 97 °C for 10 min and cooled down to 65 °C. After further cooling to room temperature for 30 min, slides were washed for 10 min three times in Tris-Buffered Saline (TBS), containing 0.1% Tween 20 (Cell Marque; TBS-T). Sections were then blocked in 5% normal donkey serum in TBS-T at room temperature for 1 h, followed by incubation with primary antibodies in the blocking solution. After one overnight incubation of primary antibodies in 4°C, sections were washed three times with TBS-T and stained with the appropriate secondary antibodies in PBS with 3% bovine serum albumin, 0.4% saponin, and 0.02% sodium azide at room temperature for 1 hour. Following this, sections were washed three times with TBS-T and mounted with ProLong Gold Antifade mounting medium (Invitrogen). Hoechst (33342, Thermo) was also used in the second to last TBS-T wash for nuclear staining. The primary antibodies and final titrations used were rabbit anti-ACE2 (1:100; Abcam ab15348), mouse anti-TMPRSS2 (1:50; Millipore MABF2158), mouse anti-acetylated α Tubulin (1:300; Santa Cruz sc-23950; for immunofluorescence staining with anti-ACE2), rabbit anti-acetylated α Tubulin (1:800, CST 5335S; for immunofluorescence staining with anti-TMPRSS2), guinea pig anti-pan-cytokeratin (1:250; LifeSpan Biosciences LS-B16812-50), mouse anti-Tubulin β3 (TUBB3) Antibody (1:500; Biolegend 801202), mouse anti-CD45 (1:100; Abcam ab781; PD7/26 + 2B11), and mouse anti-SARS-CoV-2 spike (1:1000, Genetex 1A9). Secondary antibodies include highly cross-adsorbed donkey anti-rabbit Alexa Fluor Plus 647 (1:500; Thermo A32795), highly cross-adsorbed donkey anti-mouse Alexa Fluor Plus 555 (1:500; Thermo A32773), highly crossadsorbed goat anti-guinea pig Alexa Fluor 488 (1:500; Thermo A11073). Phalloidin (Sigma-Aldrich 65906) was used to stain actin filaments. Fluorescence-immunolabeled images were acquired using an Andor Dragonfly 302 Spinning Disk Confocal (Oxford Instruments) attached to a Nikon Eclipse Ti microscope and a Keyence BZ-X710 microscope. Post-imaging processing was performed using FIJI package of ImageJ 1.52t. Figures were organized using Adobe Illustrator.

Using peptide sequences generously provided by the manufacturers of anti-ACE2 (Abcam ab15348) and anti-TMPRSS2 (Millipore MABF2158) antibodies, we custom synthesized the immunizing ACE2 and TMPRSS2 peptides, respectively, through GenScript. The sequence of the synthesized immunizing ACE2 peptide is: KGENNPGFQNTDDVQTSF. The sequence of the synthesized immunizing TMPRSS2 peptide was provided in confidence by the manufacturer. Prior to primary antibody staining, the primary antibody was mixed and incubated with a 20-fold molar excess of immunizing peptide or an unrelated mock peptide for 3 hours at room temperature. Other staining procedures were performed as described above.

Rehydration and HIER of tissue sections were performed as described above and in Lee et al. 2020 . After cooling to room temperature, slides were washed for 2 × 2 min with ddH 2 O before a 15 min H 2 O 2 block at 40°C (322335, Bio-Techne). Slides were then washed for 2 × 2 min ddH 2 O before an overnight hybridization at 40°C with probes against the SARS-CoV-2 Spike mRNA (848561, Bio-Techne), IFNB1 (417071, Bio-Techne), and IL6 (310371, Bio-Techne). Amplification of the ISH probes was performed the next day according to manufacturer's protocol (323100, Bio-Techne), with the final deposition of Cyanine 3 (NEL744001KT, Akoya Biosciences) or Cyanine 5 (NEL745001KT, Akoya Biosciences). Slides were then processed as described above for IF IHC staining.

Validation of assay specificity was performed using control slides in parallel to the experimental slides. The control slides contained either 1) Vero E6 cells infected with SARS-CoV-2 or mock infected (generated in-house and also via a generous gift from Dr. Xiankun Zeng), or 2) COVID-19 lung or non-COVID-19 lung autopsy samples, or 3) COVID-19 nasal or non-COVID-19 nasal autopsy samples. These autopsy samples were also subject to qRT-PCR validation to confirm viral presence.

3.3 x 10 4 human nasal epithelial cells (HNEpCs) were seeded in 24-well 6.5mm Transwell inserts (StemCell technologies) with PneumaCult-EX Plus Medium. After confluence was reached, PneumaCult-ALI Maintenance Medium was added to the basal chamber only and maintained 21-28 days to achieve differentiation into pseudostratified mucociliary epithelium. Media was changed every other day and cultures were maintained at 37°C and 5% CO 2 .

The clinical SARS-CoV-2 isolate of the pandemic D614G variant (SARS-CoV-2/human/USA/CA-UCSF-0001C/2020) was kindly provided by Sara Sunshine and Dr. Joe DeRisi. 100 μl of SARS-CoV-2 suspension (5-10x10^6 PFU per ml) was added to the top chamber of the ALI-cultured HNEpCs for ex vivo infection. Media containing the virus were removed after 2 hours of inoculation, and the ALI cultures were incubated at 37°C for the indicated time.

Cigarette smoke extract (CSE) treatment CSE was made by bubbling the cigarette smoke using 3R4F University of Kentucky standard reference cigarettes with 9.4 mg tar/0.726 mg nicotine (University of Kentucky, Lexington, KY) through 40 ml of normal saline. A 35 ml cigarette puff drawn at 1L/min over 2 seconds was delivered to normal saline, followed by 58 seconds of filtered air at 2L/min rate, every minute, as per FTC/ISO protocol. A single cigarette was consumed in 9 puffs and thus combusted for a total of 9 minutes. The saline was exposed to 4 cigarettes in the inExpose smoking system (SCIREQ, Montreal, QB, Canada), and then filtered through a 0.22 μm filter. CSE was diluted with the medium to 5% final concentration. The cells were treated with CSE 1 hour per day for 3 days before the SARS-CoV-2 inoculation.

Interferon-β1 (200 ng/ml) (Peprotech) was added to the ALI cultures 1 hour before the SARS-CoV-2 infection. Vehicle was added to controls at the same time point in parallel.

At 48 hours post infection, the cells were fixed or lysed for the immunofluorescence staining and gene expression level analysis. Cells were lysed in TRIzol (Invitrogen) and total RNA was isolated using RNeasy Lipid Tissue Kit (QIAGEN) and cDNA was synthesized using M-MLV Reverse Transcriptase (Invitrogen, 28025-013). qPCR was performed using TaqMan Probes (Invitrogen) and the TaqMan Gene Expression Master Mix (Applied Biosystems, 4369016) in 96-well Micro Amp Optical reaction plates (Applied Biosystems, N8010560). Life Technologies TaqMan probe: ACE2: Hs00222343_m1, TMPRSS2: Hs00237175_m1, IFNB1: Hs01077958_s1.

Samples within each cohort for comparative analysis were stained simultaneously using the same master mixes, washes, and identical incubation times under staining conditions described above. Exposure times under confocal microscopy were identical for samples within the same cohort. Quantification was performed using a custom script developed in the FIJI package of ImageJ as previously described. 3 Briefly, a binary mask was created by thresholding the pan-cytokeratin (Pan-KRT) and acetylated α-Tubulin (ACTUB) channels using selected cutoff values to generate a comprehensive outline of each channel. Pan-KRT-and ACTUB-positive regions were segmented using continuity of high signal regions on a binary mask. The signal within the segmented areas was computed for fluorescent channels that represent ACE2 or TMPRSS2 protein expression. For the sake of cross-sample normalization for ACE2 and TMPRSS2, the ratio of the ACE2 or TMPRSS2 signal divided by the epithelial Pan-KRT ( Fig. 3B and E) or cilia ACTUB signal (Fig. 3C or F ; "normalized ACE2" or "normalized TMPRSS2") for each tissue sample was used for further comparative analysis. For SARS-CoV-2 mRNA, the area and intensity within the areas segmented by thresholding SARS-CoV-2 signal (within the Pan-KRT positive area) was used in quantitative analyses.

Images of in situ hybridization of IFNB1 and IL6 in SARS-CoV-2 infected autopsy samples were collected using a Keyence BZ-X710 with Nikon PlanFluor 40x NA 1.3 oil immersion lens. Since the expression levels of IFNB1 and IL6 were lower compared to the expression of SARS-CoV-2 Spike mRNA, we applied the 40X objective lens to count the dots where a single dot represents a single copy of RNA. The number of dots was counted by thresholding the IFNB1 and IL6 signals into binary masks using the FIJI Analyze Particles function within regions of cell segmentation. To segment out the CD45 + immune cells, Mesmer, a deep learning-based algorithm utilizing the DeepCell J o u r n a l P r e -p r o o f library (deepcell-tf 0.6.0) was locally implemented to firstly segment out all the cells. 72, 73 The prediction was performed with the multiplex_segmentation.py within deepcell-tf, and the neural network weights were imported from https://deepcell-data.s3-us-west-1.amazonaws.com/model-weights/Multiplex_Segmentation_20200908_2_head.h5. Signals from the nuclear hoechst channel were firstly capped at the 99.7 th percentile, then input as the nuclear channel for all the FOVs, while a dummy all-zero image was generated and used as the membrane channel. model_mpp = 0.6 was used in the multiplex_segmentation.py script for all FOVs to generate the nuclear segmentation.

To remove confounding RBC background, segmented cells with an area smaller than 200 pixels were first excluded. Next, the signal ratio between hoechst and CD45 were calculated for each cell, and the cells with a number smaller than 0.15 were excluded, as RBCs do not contain nuclei. To further remove confounding non-specific CD45 signals, Otsu's thresholding was applied to the distances between the cell centroids and their CD45 signal weighted centroids.

Analyses were performed with GraphPad Prism 6.0 (GraphPad Software, La Jolla, CA) and IBM SPSS Statistics version 23 (IBM, Armonk, NY) software. Detailed information on the statistical analysis used can be found in figure legends. A p-value of < 0.05 was considered statistically significant. Datasets were derived from a variety of tissues from healthy patients, [25] [26] [27] 29 patients with chronic rhinosinusitis, 26, 27 head and neck squamous cell carcinoma (HNSCC), 30 and unclear disease history. 28 See also Figure S1 .

antibody staining in the cilia and epithelia (A) ACE2 protein expression in the cilia and epithelia (mock-treated) is abolished when anti-ACE2 antibody is pre-incubated with the immunizing peptide prior to immunofluorescence staining. Acetylated α-tubulin (ACTUB) is a marker of the motile cilia. The nuclei were stained using Hoechst (blue) as a counterstain. (B) TMPRSS2 protein expression in the cilia and epithelia (mock-treated) is abolished when anti-TMPRSS2 antibody is pre-incubated with the immunizing peptide prior to immunofluorescence staining. Acetylated α-tubulin (ACTUB) is a marker of the motile cilia. The nuclei were stained using Hoechst (blue) as a counterstain. Scale bars: 50 μm and 20 μm (inset images).

Representative immunofluorescence staining of ACE2, the epithelial marker pancytokeratin (panKRT), and the cilia marker acetylated α-tubulin (ACTUB) on normal human nasal cavity tissue (upper row) and bronchus tissue (lower row). Note colocalization of ACE2 and panKRT/ACTUB staining in the epithelia/cilia, respectively. Nuclei were stained using Hoechst (blue) as a counterstain. (B) Quantification of ACE2 in the epithelia of normal human mucosal tissues of the head and neck. ACE2 protein expression was statistically significantly higher in the trachea/bronchus (0.93 ± 0.07; n=21) compared to nasopharynx (0.82 ± 0.03; n=7), 

SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

SARS-CoV-2 Reverse Genetics Reveals a Variable Infection Gradient in the Respiratory Tract

ACE2 localizes to the respiratory cilia and is not increased by ACE inhibitors or ARBs

Evaluation of coronavirus in tears and conjunctival secretions of patients with SARS-CoV-2 infection

SARS-CoV-2 may be related to conjunctivitis but not necessarily spread through the conjunctiva SARS-CoV-2 and conjunctiva

Ocular conjunctival inoculation of SARS-CoV-2 can cause mild COVID-19 in rhesus macaques

Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and metaanalysis

The central role of the nasal microenvironment in the transmission, modulation, and clinical progression of SARS-CoV-2 infection

Emergence and rapid spread of a new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) lineage with multiple spike mutations in South Africa. medRxiv

Transmission of SARS-CoV-2 Lineage B. 1.1. 7 in England: Insights from linking epidemiological and genetic data

Viral infection and transmission in a large well-traced outbreak caused by the Delta SARS-CoV-2 variant

Impact of Severe Acute Respiratory Syndrome Coronavirus 2 Viral Load on Risk of Intubation and Mortality Among Hospitalized Patients With Coronavirus Disease

SARS-CoV-2 Viral Load Predicts Mortality in Patients with and without Cancer Who Are Hospitalized with COVID-19

Viral dynamics in mild and severe cases of COVID-19

Interim analysis of an open-label randomized controlled trial evaluating nasal irrigations in non-hospitalized patients with coronavirus disease

International Forum of Allergy & Rhinology

Vitro Efficacy of a Povidone-Iodine Nasal Antiseptic for Rapid Inactivation of SARS-CoV

The Inhaled Steroid Ciclesonide Blocks SARS-CoV-2 RNA Replication by Targeting the Viral Replication-Transcription Complex in Cultured Cells

Safety and efficacy of inhaled nebulised interferon beta-1a (SNG001) for treatment of SARS-CoV-2 infection: a randomised, double-blind, placebo-controlled, phase 2 trial [Internet]. The Lancet Respiratory Medicine

Antiviral Activity of Reagents in Mouth Rinses against SARS-CoV-2

A quadruple blind, randomised controlled trial of gargling agents in reducing intraoral viral load among hospitalised COVID-19 patients: A structured summary of a study protocol for a

SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes [Internet]. Nature Medicine

Existence of SARS-CoV-2 Entry Molecules in the Oral Cavity

High expression of ACE2 receptor of 2019-nCoV on the epithelial cells of oral mucosa

ACE2 and TMPRSS2 are expressed on the human ocular surface, suggesting susceptibility to SARS-CoV-2 infection

A cellular census of human lungs identifies novel cell states in health and in asthma

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues

Allergic inflammatory memory in human respiratory epithelial progenitor cells

Dissecting the cellular specificity of smoking effects and reconstructing lineages in the human airway epithelium

SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells

Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Head and Neck Cancer

Comprehensive Integration of Single-Cell Data

Infection of human Nasal Epithelial Cells with SARS-CoV-2 and a 382-nt deletion isolate lacking ORF8 reveals similar viral kinetics and host transcriptional profiles

PLOS Pathogens. 2020. p. e1009130

Gene expression and in situ protein profiling of candidate SARS-CoV-2 receptors in human airway epithelial cells and lung tissue

Single-cell longitudinal analysis of SARS-CoV-2 infection in human airway epithelium identifies target cells, alterations in gene expression, and cell state changes

TMPRSS2 and TMPRSS4 promote SARS-CoV-2 infection of human small intestinal enterocytes

Transferrin receptor is another receptor for SARS-CoV-2 entry

Neuropilin-1 facilitates SARS-CoV-2 cell entry and infectivity

Neuropilin-1 is a host factor for SARS-CoV-2 infection

The androgen-regulated type II serine protease TMPRSS2 is differentially expressed and mislocalized in prostate adenocarcinoma

Special Issue on Diagnostic Testing for Severe Acute Respiratory Syndrome Coronavirus 2 and Lessons from This Pandemic

Ocular pathology and occasionally detectable intraocular SARS-CoV-2 RNA in five fatal COVID-19 cases

Molecular detection of SARS-CoV-2 in formalin-fixed, paraffin-embedded specimens

JCI Insight

Discordant anti-SARS-CoV-2 spike protein and RNA staining in cutaneous perniotic lesions suggests endothelial deposition of cleaved spike protein

A contemporary view of coronavirus transcription

Olfactory transmucosal SARS-CoV-2 invasion as a port of central nervous system entry in individuals with COVID-19

Saliva viral load is a dynamic unifying correlate of COVID-19 severity and mortality. medRxiv

The effect of smoking on COVID-19 severity: A systematic review and meta-analysis

Current smoking, former smoking, and adverse outcome among hospitalized COVID-19 patients: a systematic review and meta-analysis

Cigarette smoking products suppress anti-viral effects of Type I interferon via phosphorylation-dependent downregulation of its receptor

Direct Exposure to SARS-CoV-2 and Cigarette Smoke Increases Infection Severity and Alters the Stem Cell-Derived Airway Repair Response

Smell and Taste Dysfunction in Patients With COVID-19: A Systematic Review and Metaanalysis

Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system underlying COVID-19-associated anosmia

Influenza A viruses are transmitted via the air from the nasal respiratory epithelium of ferrets

Impairment of nasal mucociliary clearance in former smokers with stable chronic obstructive pulmonary disease relates to the presence of a chronic bronchitis phenotype

Effects of cigarette smoking intensity on the mucociliary clearance of active smokers. Respiration

Diabetes mellitus is a risk factor for prolonged SARS-CoV-2 viral shedding in lower respiratory tract samples of critically ill patients

A Trial of Lopinavir-Ritonavir in Adults Hospitalized with Severe Covid-19

Remdesivir in adults with severe COVID-19: a randomised, double-blind, placebo-controlled, multicentre trial

Remdesivir for the Treatment of Covid-19 -Final Report

Lopinavirritonavir in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Impact of interleukin-6 blockade with tocilizumab on SARS-CoV-2 viral kinetics and antibody responses in patients with COVID-19: A prospective cohort study. EBioMedicine

Viral clearance after early corticosteroid treatment in patients with moderate or severe covid-19. Sci Rep

REGN-COV2, a Neutralizing Antibody Cocktail, in Outpatients with Covid-19

Case Study: Prolonged Infectious SARS-CoV-2 Shedding from an Asymptomatic Immunocompromised Individual with Cancer

Persistence and Evolution of SARS-CoV-2 in an Immunocompromised Host

SARS-CoV-2 Neutralizing Antibody LY-CoV555 in Outpatients with Covid-19

Human recombinant soluble ACE2 in severe COVID-19. The Lancet Respiratory Medicine

Postmortem examination of COVID-19 patients reveals diffuse alveolar damage with severe capillary congestion and variegated findings in lungs and other organs suggesting vascular dysfunction

Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage

An expression atlas of human primary cells: inference of gene function from coexpression networks

Elegant Graphics for Data Analysis

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments

Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning

Dunn's multiple comparison post-hoc test

Quantification of ACE2 within the cilia of normal human mucosal tissues of the head and neck. No significant differences in ACE2 expression was detected between cilia of the nose (n=11), nasopharynx (n=7), and trachea/bronchus (n=21). (Kruskal-Wallis test, p = 0.0624). The larynx tissue used in Figure 3B did not contain cilia

Representative immunofluorescence staining of TMPRSS2, panKRT, and ACTUB in normal human nasal (upper row) and bronchial tissues (lower row)

Quantification of TMPRSS2 in the epithelia of normal human mucosal tissues

Dunn's multiple comparison post-hoc test, ***adjusted p = 0.0007, ****adjusted p < 0.0001, ****adjusted p < 0.0001, and *adjusted p = 0.0167, respectively). TMPRSS2 in the trachea/bronchus (0.98 ± 0.08; n=21) was statistically significantly higher compared to the tongue, oro/hypo-pharynx, and esophagus

Dunn's multiple comparison post-hoc test

Quantification of TMPRSS2 in the cilia of normal human mucosal tissues. TMPRSS2 protein expression was statistically significantly higher in nasal tissues

Dunn's multiple comparison post-hoc test, **adjusted p = 0.0048 and **adjusted p = 0.0020, respectively)

Values in parentheses are presented as mean ± SD. The bands within the box plot show the median value. The bottom and top of the box plots represent the 25th and 75th percentiles, respectively. The whiskers extending from both ends of the boxes are minimum and maximum values

The authors sincerely appreciate the generosity of tissue donation from the deceased patients and their families in enabling this study. We thank members of the Nayak and Nolan labs for critical and thoughtful discussions.