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Ancestral SARS-CoV-2, but not Omicron, replicates less efficiently in primary pediatric nasal epithelial cells [1]

['Yanshan Zhu', 'School Of Chemistry', 'Molecular Biosciences', 'The University Of Queensland', 'Brisbane', 'Queensland', 'Keng Yih Chew', 'Melanie Wu', 'Anjana C. Karawita', 'Georgina Mccallum']

Date: 2022-08 

Abstract Children typically experience more mild symptoms of Coronavirus Disease 2019 (COVID-19) when compared to adults. There is a strong body of evidence that children are also less susceptible to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection with the ancestral viral isolate. However, the emergence of SARS-CoV-2 variants of concern (VOCs) has been associated with an increased number of pediatric infections. Whether this is the result of widespread adult vaccination or fundamental changes in the biology of SARS-CoV-2 remain to be determined. Here, we use primary nasal epithelial cells (NECs) from children and adults, differentiated at an air–liquid interface to show that the ancestral SARS-CoV-2 replicates to significantly lower titers in the NECs of children compared to those of adults. This was associated with a heightened antiviral response to SARS-CoV-2 in the NECs of children. Importantly, the Delta variant also replicated to significantly lower titers in the NECs of children. This trend was markedly less pronounced in the case of Omicron. It is also striking to note that, at least in terms of viral RNA, Omicron replicated better in pediatric NECs compared to both Delta and the ancestral virus. Taken together, these data show that the nasal epithelium of children supports lower infection and replication of ancestral SARS-CoV-2, although this may be changing as the virus evolves.

Citation: Zhu Y, Chew KY, Wu M, Karawita AC, McCallum G, Steele LE, et al. (2022) Ancestral SARS-CoV-2, but not Omicron, replicates less efficiently in primary pediatric nasal epithelial cells. PLoS Biol 20(8): e3001728. https://doi.org/10.1371/journal.pbio.3001728 Academic Editor: Bill Sugden, University of Wisconsin-Madison, UNITED STATES Received: May 26, 2022; Accepted: June 24, 2022; Published: August 1, 2022 Copyright: © 2022 Zhu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the paper and its Supporting information file. RNA-seq data is deposited at European Nucleotide Archive under the project– PRJEB43102. The scripts used for RNA-seq data analysis including differential gene expression and gene set enrichment analysis can be found in https://github.com/akaraw/Yanshan_Zhu_et_al. Funding: This work is supported by the Australia Research Council (Discovery Early Career Researcher Award DE190100565 to M.J.), The National Health and Medical Research Council (Project grant APP2010917 to F.A.M. and G.B.; Senior research Fellowship APP1155794 to F.A.M; APP1124612 to LL; 2010757 to KYC and LL; NHMRC investigator grant 2007919 to K.R.S.) the Australian Infectious Diseases Research Centre (COVID-19 seed grant to A.A.K) and Academy of Finland and COVID19 research donations (Grant 318434 to G.B.). This program has in part been funded by the Western Australian Future Health Research & Innovation Fund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: KRS is a consultant for Sanofi, Roche and NovoNordisk. The opinions and data presented in this manuscript are of the authors and are independent of these relationships. Abbreviations: ACE2, angiotensin-converting enzyme 2; ALI, air liquid interface; ARDS, acute respiratory distress syndrome; COVID-19, Coronavirus Disease 2019; DEG, differentially expressed gene; DGE, differential gene expression; ECL, enhanced chemiluminescence; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; GO, gene ontology; h.p.i, hours post-infection; HE, hematoxylin–eosin; HPRT, hypoxanthine-guanine phosphoribosyltransferase; HRP, horseradish peroxidase; NEC, nasal epithelial cell; NP, nucleoprotein; ORF, open reading frame; PAS, periodic acid–Schiff; qRT-PCR, quantitative reverse transcription PCR; ROI, region of interest; SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2; TMPRSS2, transmembrane serine protease 2; VOC, variant of concern; ZO-1, zonal occludens-1

Introduction Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus Disease 2019 (COVID-19), causes a broad range of clinical symptoms, ranging from asymptomatic infection to potentially fatal acute respiratory distress syndrome (ARDS). Children typically experience mild symptoms of COVID-19 when compared to adults [1]. There is also a significant body of evidence with the ancestral viral strain that children are less susceptible to SARS-CoV-2 infection and less likely to transmit the virus [2]. These findings have been echoed in multiple single site studies where, both within and outside of households, the infection rate of the ancestral SARS-CoV-2 among children <10 years old is significantly lower than that of adults [3,4]. Reduced SARS-CoV-2 infection and transmission is also observed in juvenile ferrets compared to their older counterparts [5]. The reasons for less frequent SARS-CoV-2 infection and symptoms in children infected with the ancestral virus strain remain unclear and may be influenced by a multitude of factors. There is evidence to suggest that nasal epithelial cells (NECs), the first site of infection, are fundamentally different in children compared to adults. Gene expression studies using the nasal epithelium of healthy individuals suggest that the transcript for the SARS-CoV-2 receptor, angiotensin-converting enzyme 2 (ACE2), is expressed at lower levels in children than in adults [6]. However, this has yet to be validated on a protein level. Moreover, this does not appear to be the case in all patient cohorts [7,8]. Following binding of the SARS-CoV-2 spike protein to ACE2, the host surface transmembrane serine protease 2 (TMPRSS2) is also involved in viral entry into the cell [9]. NECs from children express less TMPRSS2 mRNA than those from adults, which may contribute to less frequent pediatric infections with SARS-CoV-2 [10]. However, this has also yet to be confirmed at protein level. In addition to differential receptor expression, pediatric and adult NECs may also mount fundamentally different innate immune response to SARS-CoV-2. Recent RNA sequencing of the whole epithelium from pediatric and adult proximal airways suggests that there is a higher expression of genes associated with inflammation and the antiviral response in children compared to adults [11,12]. While increased inflammation and interferon production have previously been associated with elevated COVID-19 severity [13], it is important to note that such studies refer to the inflammatory response in the lower respiratory tract, where any immunopathology may lead to respiratory distress [14]. In contrast, inflammation in the upper respiratory tract plays an important role in controlling early viral replication. Specifically, elevated levels of type I IFN effectively inhibit the replication of SARS-CoV-2 across multiple studies [15–17]. Consistent with these data, nasopharyngeal swabs from SARS-CoV-2-infected children display elevated levels of interferons and inflammatory markers compared to those of SARS-CoV-2-infected adults [7]. During the course of the SARS-CoV-2 pandemic, the ancestral virus has undergone significant mutations resulting in the emergence of variants of concern (VOCs) such as Delta and Omicron. These VOCs have multiple mutations in the spike protein, the N protein, and various open reading frames (ORFs) of the virus, which has resulted in their increased transmissibility and potentially differing clinical outcome [18]. The growing dominance of VOCs has raised speculation that the epidemiology of SARS-CoV-2 infection has fundamentally changed, specifically in terms of the role that children play in spreading the virus. For example, epidemiological household transmission studies have found little evidence of differential susceptibility to Delta in children compared to adults [19,20]. In addition, data from South Africa [21] and the United States [22] found a rapid increase in pediatric COVID-19-related hospital admission associated with the Omicron wave. These data may suggest that VOCs have evolved such that they are now able to evade any protection that the innate immune response has previously afforded children in terms of infection with the ancestral virus [7,12,18,23]. However, the extrapolation of epidemiology studies to fundamental immunology are complicated by the fact that the Delta and Omicron waves emerged at a time when a large percentage of the adult population were eligible for vaccination while vaccination of children <12 years old often lagged behind. Therefore, the role of pediatric innate immunity during VOC infection remains undefined. Here, we use primary NECs, differentiated at an air–liquid interface, to investigate differential infection kinetics and antiviral responses to SARS-CoV-2 (ancestral and VOCs) infection in children and adults.

Discussion Large clinical data sets and systematic reviews suggest that children are less often infected with the ancestral SARS-CoV-2 and have less severe symptoms than adults [26–28]. However, the mechanisms driving these observations have been unclear. Here, we have provided the first experimental evidence that the pediatric nasal epithelium may play an important role in reducing the susceptibility of children to ancestral SARS-CoV-2. Previous studies have suggested that the reduced susceptibility of children to SARS-CoV-2 infection is due to reduced mRNA expression of SARS-CoV-2 receptors ACE2 and TMPRSS2. Specifically, it has been proposed that the lower level of ACE2 and TMPRSS2 in pediatric upper airways epithelial cells limits disease severity and viral infectivity in children [6,29], although this has remained somewhat controversial [7,8]. In the present study, while there was a trend toward decreased ACE2 protein levels in pediatric NECs, there was significant donor-to-donor variability that precluded statistical significance. We interpret these data as suggesting that ACE2 levels may contribute to, but are not the sole factor, in the increased resistance of children to SARS-CoV-2. Despite donor-to-donor differences in ACE2 expression, we consistently observed a significant reduction in ancestral SARS-CoV-2 (QLD02) replication in pediatric NECs compared to NECs of adults. Given that the nasal epithelium is the first site of SARS-CoV-2 infection, these data are consistent with the reduced number of SARS-CoV-2-infected children recorded in household and school transmission studies [30,31]. However, we recognize it is challenging to compare data from controlled experimental studies to data obtained from patient sampling, where it is difficult to control for time of sampling relative to the onset of infection. Rather, decreased viral replication in pediatric epithelial cells is consistent with experimental studies in ferrets where aged ferrets showed higher viral load and longer nasal virus shedding [5]. Consistent with reduced ancestral SARS-CoV-2 replication in the nasal epithelium of children, pediatric epithelial cells had a more pronounced pro-inflammatory response (compared to adult cells) following an ancestral SARS-CoV-2 infection. In particular, a pronounced interferon response and the expression of interferon stimulated genes (ISGs) were higher in infected pediatric, compared to adult, NECs. Increased ISG expression and the subsequent antiviral response may contribute to the reduced viral replication observed in pediatric cells. Importantly, unlike the lower respiratory tract, any resultant cell death or immunopathology in the upper respiratory tract is unlikely to lead to respiratory distress and therefore remains beneficial to the host [13]. These findings are consistent with those of Maughan and colleagues, who analyzed transcriptional profile of airway (tracheobronchial) epithelium and observed up-regulated type I and II IFNs associated genes in children [11]. Similarly, in the nasal fluid of children and adults presenting to the emergency department with SARS-CoV-2, there were significantly higher levels of IFN-α2 in the fluid derived from children. Increased interferon signaling was also recorded in the nasopharyngeal transcriptome of children compared to that of adults during early SARS-CoV-2 infection [7]. The question remains as to why pediatric epithelial cells mount a stronger inflammatory and antiviral response to ancestral SARS-CoV-2 compared to adult cells. This may represent an adaptation to the increased antigenic challenge observed in childhood. Alternatively, it is possible that increased antigenic exposure in childhood “trains” nasal epithelium in children to mount a stronger pro-inflammatory response to any antigenic challenge. It is also possible that metabolic differences between pediatric and NECs (as potentially suggested by the different morphologies of the cells) could alter gene expression. It is striking to note that the VOC Delta also replicated significantly better in the NECs of adults compared to those of children. These data suggest that any increase in pediatric infections during the Delta wave are unlikely to be due to the fact that the virus has substantially evaded the innate immune response of pediatric NECs and are instead more likely attributable to other factors (e.g., age-dependent differences in prior infection and/or vaccination). Interestingly, the Delta variant replicated to higher titers in the NECs of both adults and children when compared to the ancestral virus. This is consistent with previous studies [32] and may be associated with the increased transmissibility of Delta compared to the ancestral virus. Interestingly, at least in adults, the more recent Omicron variant did not replicate more efficiently in the NECs than the earlier Delta variant. These data support suggestions that Omicron does not necessarily have a replicative advantage over Delta in the URT of adults [33], and the observed increase in transmission with Omicron in adults is more likely reflective of increased antibody evasion [34–37]. Surprisingly, age-dependent differences in viral replication in NECs were much less pronounced in the case of Omicron. Indeed, there was no notable difference in Omicron RNA titers at 24 h.p.i in adult versus pediatric NECs. These data may provide preliminary evidence that the Omicron variant, at least to some extent, is able to evade aspects of the pediatric innate immune response, as has previously been demonstrated [38]. Whether this is sufficient to result in an increased number of pediatric infections during the Omicron wave [39,40], or whether other factors are more important, remains to be determined. However, it is striking to note (at least in terms of RNA levels) increased titers of Omicron in pediatric NECs compared to infection with Delta and the ancestral virus. These data are consistent with the increased number of pediatric infections observed during the Omicron wave [39,40]. Finally, it is important to recognize the limitations of this study. Due to the difficulties associated with obtaining NECs from children, only a limited number of donors could be used for this study. However, as donors were not selected according to susceptibility to respiratory viral infection, their responses should be broadly representative of healthy children. Furthermore, our data focused on the role of nasal epithelial cells in age-dependent differences in SARS-CoV-2 infection. Nevertheless, there may be other mechanisms to explain the reduced susceptibility of children to SARS-CoV-2 infection that were not measured in the present study. For example, children and adolescents have higher titers of preexisting antibodies to SARS-CoV-2 compared to adults [41]. This study is unable to ascertain if this plays a more significant role than the nasal epithelium in protecting children from infection in vivo.

Materials and methods Cell collection and ethics statement Primary NECs were collected from healthy adult (aged 19 to 66 years old) donors by placing a sterile nasal mucosal curette (Arlington Scientific, USA) in the mid-inferior portion of the inferior turbinate during July 2018 to May 2021 (during which time there was only sporadic community cases of COVID-19 in Queensland and Western Australia). Informed consent was obtained from all donors. Primary NECs were obtained from healthy pediatric donors (aged 2 to 11 years old) in the same manner while under general anesthetic prior to ear, nose, and throat (ENT)-related surgeries including tonsillectomies, adenoidectomies, or for sleep apnoea. Children did not have any other unknown underlying condition at the time of recruitment and sampling. This study was approved by the University of Queensland’s Human Research Ethics Committee (2020001742), the Queensland Children’s Hospital and Health Service Human Research Ethics Committee (HREC/16/QRCH/215, HREC/10/QRCH/78), Queensland University of Technology Human Research Ethics Committee 17000000039), and St John of God Subiaco Hospital Human Ethics Committee as part of the Western Australia Epithelial Research Program (WAERP) (Ethics #901). Primary NECs were established as previously described [42–44] and stored in freezing media (FBS with 10% DMSO) at passage 1 or 2. In total, we included 38 donors in this study (N = 15 adult (7 females, 8 male, 37.9 ± 16.5 years old) and N = 23 pediatric (11 female, 12 male, 5.6 ± 2.7 years old)). Cell culture African green monkey kidney epithelial Vero cells were maintained in MEM (Invitrogen), containing 10% (v/v) heat-inactivated fetal bovine serum (Cytiva), 100 U/mL penicillin, and streptomycin (Life Technologies Australia). Cell lines were obtained from American Type Culture Collection (ATCC; Virginia, USA). Primary NECs were expanded and passaged in Pneumacult EX Plus media (STEMCELL Technologies, Canada). After initial expansion, NECs were seeded at a density of 4 to 5 × 105 cells/transwell on 6.5-mm transwell polyester membranes with 0.4 μm pores (Corning Costar, USA) and cultured in EX Plus media (STEMCELL Technologies). Cells were monitored for confluence. When a confluent monolayer was achieved, cells were “air-lifted” by removing the media from the apical chamber and replacing the basolateral media with Pneumacult air liquid interface (ALI) media (STEMCELL Technologies) [45]. Medium was replaced in the basal compartment 3 times a week, and the cells were maintained in ALI conditions for at least 3 weeks until ciliated cells and mucus were observed and cells obtained a transepithelial electrical resistance (TEER) measurement greater than 800 Ω/cm2. Fully differentiated cultures were used in downstream infection experiments. Viral stocks SARS-CoV-2 isolate hCoV-19/Australia/QLD02/2020 (QLD02) (used as the original ancestral virus), hCoV-19/Australia/QLD1893C/2021 (QLD1893C) (GISAID Accession ID; EPI_ISL_2433928; Delta), and hCoV-19/Australia/NSW-RPAH-1933/2021 (GISAID Accession ID; EPI_ISL_6814922; Omicron) were kindly provided by Queensland Health Forensic and Scientific Services, Queensland Department of Health, and the Kirby Institute (in collaboration with NSW Health Pathology). In this setting, we collectively acknowledge the contribution of the scientists and pathologists of NSW Health Pathology and the Kirby Institute to this project. Growth and use of primary isolates was under approval of the NSW Chef Health Officer following independent scientific review. Virus was amplified in Vero cells expressing human TMPRSS2 and titrated by plaque assay [46]. All studies with SARS-CoV-2 were performed under physical containment 3 (PC3) conditions and were approved by the University of Queensland Biosafety Committee (IBC/374B/SCMB/2020). Viral infection Differentiated adult and pediatric NECs were infected with mock (PBS), QLD02 (1.25 × 105 PFU or 1.7 × 104 PFU), QLD1517 (1.7 × 104 PFU), or NSW1933 (1.7 × 104 PFU). Specifically, 100 μL of virus or PBS was placed on the epithelial surface in the apical compartment and incubated for 1 hour at 37 °C. Following incubation, excess virus was removed from the transwell, and cells were incubated at 37 °C with 5% CO 2 . Every 24 hours, the basolateral media was refreshed with 1 mL of new ALI media. At predetermined time points, post-infection 100 μL of PBS was added to the apical compartment, and cells were incubated at 37 °C with 5% CO 2 for 10 minutes. The apical supernatant was subsequently collected and stored at −80 °C. Cells were lysed with Buffer RLT (Qiagen, USA) containing 0.01% β-mercaptoethanol for RNA analysis. Alternatively, cells were lysed in 2% SDS/PBS lysis buffer (2% SDS/PBS buffer, 10% 10× PhosSTOP, 4% 25× protease inhibitor) for protein analysis or fixed overnight in 4% paraformaldehyde for histology. Histology Fixed cells on a transwell membrane were routine processed and embedded in paraffin, sectioned at 5 μm, and subsequently stained with hematoxylin–eosin (HE) or periodic acid–Schiff (PAS). Sections were assessed for cellular morphology by a veterinary pathologist (H.B.O.) blinded to the experimental design. Immunofluorescence Differentiated epithelial cells grown on a transwell membrane were fixed with 4% paraformaldehyde (Cat#15710, Electron Microscopy Sciences) in PBS for 45 minutes at room temperature, followed by a blocking with 0.5% BSA (Sigma) in PBS for 30 minutes and permeabilization with 0.02% of Triton X-100 (Sigma) in PBS for 15 minutes at room temperature. After washing twice with PBS/BSA and a second blocking step for 10 minutes at room temperature, samples were incubated with primary antibodies overnight at 4 °C. Primary antibodies were diluted in 0.5% BSA in PBS blocking solution: 1:400 ZO-1 (Cat#40–2200, Thermo Fisher Scientific), 1:1,000 MUC5AC (Cat#MA5-12178, Thermo Fisher Scientific), and 1:500 ACE2 (Cat#AF933, R&D Systems). After 3 washing steps with 0.5% BSA/PBS for 5 minutes each time, the samples were incubated in secondary antibody: 1:1,000 Alexa Flour 555 donkey anti-goat (Cat#A21432, Invitrogen) for 2.5 hours at room temperature in dark, and after 3 washes in PBS and 3 washes with 0.5% BSA/PBS, the cells were incubated with a 1:1,000 Alexa Fluor 488 goat anti-mouse (Cat#A32728, Invitrogen) for 2.5 hours at room temperature covered from light. The cells were simultaneously stained with 1:400 Alexa Fluor 647 Phalloidin (Cat#A22287 Invitrogen) and 1:1,000 DAPI. After 3 washes in PBS, the transwell membranes with cells were cut with a scalpel, briefly dipped in milli-q water, and mounted on a class slide using ProLong Gold Antifade Mountant (Cat# P10144, Thermo Fisher Scientific). Mounted samples were imaged on a spinning disk confocal system (Marianas; 3I) consisting of an Axio Observer Z1 (Carl Zeiss) equipped with a CSU-W1 spinning disk head (Yokogawa Corporation of America), ORCA-Flash4.0 v2 sCMOS camera (Hamamatsu Photonics), and 63× 1.4 NA/Plan-Apochromat/180 μm WD objective. Image acquisition was performed using SlideBook 6.0 (3I). A total of 150 optical sections from 5 random regions of interest (ROIs) from each sample were acquired from the top of the differentiated epithelial cells. Image processing was performed using Fiji/ImageJ (Version 2.1.0/1.53c) as follows: Background was reduced using the Substract Backgound 50 pixel rolling ball radius, and the mean fluorescence intensity (MFI, a.u. arbitrary units) was measured from the average intensity images. Western blotting For total cell lysates, cells were washed twice with cold PBS and lysed with SDS/PBS lysis buffer (2% SDS/PBS buffer, 10% 10× PhosSTOP, 4% 25× protease inhibitor). Pierce BCA protein assay kit (Thermo Fisher Scientific) was used to equalize protein amounts. After adding LDS buffer (4×) with reducing agent (10×), mix protein samples were subsequently boiled at 100 °C for 10 minutes to denature proteins. Proteins were separated on 4% to 15% mini protean TGX precast gels (Biorad) in running buffer (200 mM Glycine, 25 mM Tris, 0.1% SDS (pH 8.6)), transferred to nitrocellulose membrane (Cat#1620112, BioRad) in blot buffer (48 nM Tris, 39 nM Glycine, 0.04% SDS, 20% MeOH), and subsequently blocked with 5% (w/v) BSA in Tris-buffered saline with Tween 20 (TBST) for 30 minutes. The immunoblots were analyzed using primary antibodies incubated overnight at 4 °C and secondary antibodies linked to horseradish peroxidase (HRP) (Invitrogen), and after each step, immunoblots were washed 3× with TBST. HRP signals were visualized by enhanced chemiluminescence (ECL) (BioRad) and imaged with an AI600 Chemiluminescent Imager (Cytiva). Primary antibodies include rabbit GAPDH (14C10) monoclonal antibody (1:2,500 dilution, Cat#2118, Cell Signaling Technology), rabbit anti-SARS-CoV-2 nucleoprotein/NP antibody (1:1,000 dilution, Cat#40143-R040, Sino Biological), goat polyclonal ACE2 (1:500 dilution, Cat#AF933, R&D Systems), and rabbit anti-TMPRSS2 antibody (1:1,000 dilution, Cat#ab109131, Abcam). ImageJ (version 1.53) was used to quantify the protein expression level relative to GAPDH levels. Cytokine levels Cytokine levels were measured by AlphaLISA (Perkin Elmer) according to the manufacturer’s instructions. Quantification of infectious virus SARS-CoV-2 titers in cell culture supernatants were determined by plaque assay on Vero cells, as described previously [46]. RNA extraction and quantitative reverse transcription PCR (qRT-PCR) RNA was extracted from NECs using Nucleozole reagent according to the manufacturer’s instructions, DNA was removed by DNase I (Thermo Fisher Scientific) treatment, and 1-μg DNA-free RNA was reverse transcribed into cDNA using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) on a Mastercycler Thermocycler (Eppendorf, Hamburg, Germany) according to the manufacturer’s instructions using random primers. Real-time PCR was performed on generated cDNA with SYBER Green (Invitrogen) using QuantStudio 6 Flex Real-Time PCR System, an Applied Biosystems Real-Time PCR Instruments (Thermo Fisher Scientific). Gene expression was normalized relative to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) or hypoxanthine-guanine phosphoribosyltransferase (HPRT) expression; fold change was calculated using the ΔΔCt method. All primers used in this study are listed in Table 1. PPT PowerPoint slide

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TIFF original image Download: Table 1. Primers used in the present study. https://doi.org/10.1371/journal.pbio.3001728.t001 RNA sequencing RNA-Seq libraries were prepared using the Illumina stranded total RNA prep ligation with the Ribo-Zero plus kit (Illumina) and IDT for Illumina RNA UD Indexes according to the standard manufacturer’s protocol. Briefly, 50 ng of total RNA was depleted of rRNA and then fragmented by heat. cDNA was synthesized from the fragmented RNA using random primers. The first strand cDNA was converted into dsDNA in the presence of dUTP to maintain the “strandedness” of the library. The 3′ ends of the cDNA were adenylated, and pre-index anchors were ligated. The libraries were then amplified with 14 to 16 cycles of PCR incorporating unique indexes for each sample to produce libraries ready for sequencing. The libraries were quantified on the Perkin Elmer LabChip GX Touch with the DNA High Sensitivity Reagent kit (Perkin Elmer). Libraries were pooled in equimolar ratios, and the pool was quantified by qPCR using the KAPA Library Quantification Kit—Illumina/Universal (KAPA Biosystems) in combination with the Life Technologies Viia 7 real-time PCR instrument. Sequencing was performed using the Illumina NextSeq500 (NextSeq control software v2.2.0/Real Time Analysis v2.4.11). The library pool was diluted and denatured according to the standard NextSeq protocol and sequenced to generate single-end 76 bp reads using a 75 cycle NextSeq500/550 High Output reagent Kit v2.5 (Illumina). After sequencing, fastq files were generated using bcl2fastq2 (v2.20.0.422), which included trimming the first cycle of the insert read. Library preparation and sequencing was performed at the Institute for Molecular Bioscience Sequencing Facility (University of Queensland). RNA sequencing analysis The quality of the trimmed RNA-seq reads was assessed with FastQC [47] and MultiQC [48]. Salmon [49] was used for transcript quantification from human transcriptome (GENCODE Release 36, accessed in December 2020). A decoy aware transcriptome file was created for Salmon transcript quantification followed by the transcriptome index [49]. The R package, DESeq2 [50], was then used for differential gene expression (DGE) analysis and further validated through using the limma R package [51] with Voom transformation [52]. DGEs between virus and mock infected samples were analyzed by controlling the effect of the age group and gender of the individual samples, genes with adjusted p-value less than 0.05 were considered significant. Gene set enrichment analysis was performed using the R package GOseq [53]. All the R scripts were run on R-Studio platform (RStudio Team 2020, v 1.4.1717). Statistical analysis Where sufficient cell numbers were present, samples were performed in duplicate, and the results were averaged and shown as a single data point. If sufficient cells were not present, a single transwell was used to determine the response of that donor to viral infection. Outliers of continual variables were removed using ROUT’s test (Q = 1%). Data were tested for normality using the Shapiro–Wilk test. Where data were normally distributed, data were analyzed using an unpaired 2-tailed Student t test. Where data were not normally distributed, data were analyzed using a Mann–Whitney U test. Significance was set at p < 0.05. Each donor is shown with a distinct symbol that is used consistently throughout the paper.

Conclusions The data presented here strongly suggest that the nasal epithelium of children is distinct and that it may afford children some level of protection from ancestral SARS-CoV-2, although such age-dependent differences become less pronounced in the case of Omicron infection.

Acknowledgments We greatly thank the participants in the study and the members of the research team. The authors thank the participants and their families in the Western Australian Epithelial Research Program (WAERP) for their contribution to this study. Current members of WAERP include: Anthony Kicic, Stephen M. Stick, Elizabeth Kicic-Starcevich, Amy Greenly, Angela Fuery, Luke W. Garratt, Erika N. Sutanto, Kevin Looi, Jessica Hillas, Thomas Iosifidis, Craig Schofield, Samantha McLean, Luke Berry, Samuel T. Montgomery, Kak-Ming Ling, Renee Ng, Andrew Vaitekenas, Daniel Laucirica, Matthew Poh, Reanne Ho, Joshua Iszatt, Katherine Landwehr, Denby Evans, Rebecca Watkinson, Patricia Agudelo-Romero, Jose Caparros-Martin, Alexander de Bont, Julia Maynard, Rohan Flint, Jack Canning, Shyan Vijayasekaran, George Sim, Mairead Heaney, Tom Rawlings, Neil Chambers, Christopher Johnson, Eugene Roscioli, Alexander Larcombe, Tim Barnett, Rael, Rivers, and Kate McGee.

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