Lung Epithelial Cells from Obese Patients Have Impaired Control of SARS-CoV-2 Infection

Obesity is known to increase the complications of the COVID-19 coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the exact mechanisms of SARS-CoV-2 infection in obese patients have not been clearly elucidated. This study aims to better understand the effect of obesity on the course of SARS-CoV-2 infection and identify candidate molecular pathways involved in the progression of the disease, using an in vitro live infection model and RNA sequencing. Results from this study revealed the enhancement of viral load and replication in bronchial epithelial cells (NHBE) from obese subjects at 24 h of infection (MOI = 0.5) as compared to non-obese subjects. Transcriptomic profiling via RNA-Seq highlighted the enrichment of lipid metabolism-related pathways along with LPIN2, an inflammasome regulator, as a unique differentially expressed gene (DEG) in infected bronchial epithelial cells from obese subjects. Such findings correlated with altered cytokine and angiotensin-converting enzyme-2 (ACE2) expression during infection of bronchial cells. These findings provide a novel insight on the molecular interplay between obesity and SARS-CoV-2 infection. In conclusion, this study demonstrates the increased SARS-CoV-2 infection of bronchial epithelial cells from obese subjects and highlights the impaired immunity which may explain the increased severity among obese COVID-19 patients.


Introduction
Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a wide range of clinical symptoms of variable degrees. The severity of COVID-19 has been shown to be associated with age, gender and the presence of comorbidities such as diabetes, hypertension and obesity. Numerous studies have shown that obesity increases the risk for hospitalization and mortality rate in COVID-19 patients [1]. This is particularly alarming because rates of obesity are high worldwide, with 40% of adults being obese in the United States (US) according to the Centers for Disease Control and Prevention (CDC) [2,3], making obesity one of the most important risk factors in COVID- 19. In a retrospective study in France, out of 124 COVID-19 patients admitted to the intensive care unit (ICU), 75.8% were obese [4]. The same trends have been observed in Wuhan, China, where 68% of COVID-19 patients were overweight/obese and 37% of these patients showed severe symptoms [5]. Extensive investigations have been conducted to understand this association between obesity and severe COVID-19, with the goal of ameliorating COVID-19 treatment in obese patients.
It is well documented that SARS-CoV-2 binds to angiotensin-converting enzyme-2 (ACE2), expressed in a wide variety of human structural cells in kidney, lung, thyroid and was assessed by measuring nucleocapsid mRNA, n = 4/group; (B) replication was evaluated by measuring the SARS-CoV-2 envelope (UpE) gene, which was significantly higher in NHBE cells from obese subjects (n = 4) compared to non-obese (n = 4) subjects. One-way ANOVA test and Tukey post hoc, * p < 0.05; *** p < 0.001.

Enrichment of Lipid Metabolism-Related Pathways in Infected Bronchial Epithelial Cells from Obese Subjects
Since our data displayed an increase in viral entry and replication at 4 h, with a significant difference between obese and non-obese subject groups at 24 h, we aimed to investigate the transcriptomic signature of the bronchial epithelial (NHBE) cells from non-  (B) replication was evaluated by measuring the SARS-CoV-2 envelope (UpE) gene, which was significantly higher in NHBE cells from obese subjects (n = 4) compared to non-obese (n = 4) subjects. One-way ANOVA test and Tukey post hoc, * p < 0.05; *** p < 0.001.

Enrichment of Lipid Metabolism-Related Pathways in Infected Bronchial Epithelial Cells from Obese Subjects
Since our data displayed an increase in viral entry and replication at 4 h, with a significant difference between obese and non-obese subject groups at 24 h, we aimed to investigate the transcriptomic signature of the bronchial epithelial (NHBE) cells from nonobese and obese subjects at 4 h and 24 h, prior and post-SARS-CoV-2 infection. This will help explain the difference seen in the viral load among non-obese and obese subjects. Firstly, we generated a baseline transcriptome profile via individualized differentially expressed genes (iDEGs) to identify the DEGs between non-infected NHBE cells from obese and non-obese ( Figure 2). For each time point, DEGs between obese and non-obese were identified and intersected with DEGs identified in the other time point. 1234 DEGs were identified between obese and non-obese NHBE cells at 4 h, whereas 1644 DEGs were identified at the 24 h time point. Interestingly, 286 genes were differentially expressed in obese versus non-obese subjects in both time points, indicating core transcriptome difference between the 2 patient groups (Figure 2A). These 286 genes were mainly enriched in pathways related to lipid metabolism (glycerolipid biosynthetic process, triglyceride biosynthesis, positive regulation of lipid metabolic process, phosphatidylglycerol metabolic process and protein lipidation), cell shape and structure (regulation of cell shape, apical junction assembly and cilium assembly) and in pathways involved in infection and tissue repair (epithelial to mesenchymal transition in colorectal cancer, negative regulation of wound healing, herpes simplex virus 1 infection and negative regulation of response to external stimulus), as shown in Figure 2B. Secondly, we furthered our analysis to identify the DEGs between infected and noninfected NHBE cells from obese and non-obese subjects. The DEGs at each time point, 4 h and 24 h, were intersected to identify the core transcriptome differentially expressed genes. Our results displayed 41 DEGs between non-infected and infected, and in obese and non-obese subject groups ( Figure 3A). Interestingly, these 41 DEGs were enriched in pathways related to metabolic, cellular and developmental processes ( Figure 3B). Highlighting the significant increase of viral replication and load that was only seen in NHBE from obese subjects, our data presented 728 DEGs that were unique to infected obese patients' bronchial epithelial cells versus those of non-infected patients at 24 h. Interestingly, those DEGs were enriched in pathways such as those regulating the metabolism of lipid and type I interferon, among other significantly enriched pathways ( Figure 3A,C). Secondly, we furthered our analysis to identify the DEGs between infected and noninfected NHBE cells from obese and non-obese subjects. The DEGs at each time point, 4 h and 24 h, were intersected to identify the core transcriptome differentially expressed genes. Our results displayed 41 DEGs between non-infected and infected, and in obese and nonobese subject groups ( Figure 3A). Interestingly, these 41 DEGs were enriched in pathways related to metabolic, cellular and developmental processes ( Figure 3B). Highlighting the significant increase of viral replication and load that was only seen in NHBE from obese subjects, our data presented 728 DEGs that were unique to infected obese patients' bronchial epithelial cells versus those of non-infected patients at 24 h. Interestingly, those DEGs were enriched in pathways such as those regulating the metabolism of lipid and type I interferon, among other significantly enriched pathways ( Figure 3A,C). and non-obese subject groups ( Figure 3A). Interestingly, these 41 DEGs were enriched in pathways related to metabolic, cellular and developmental processes ( Figure 3B). Highlighting the significant increase of viral replication and load that was only seen in NHBE from obese subjects, our data presented 728 DEGs that were unique to infected obese patients' bronchial epithelial cells versus those of non-infected patients at 24 h. Interestingly, those DEGs were enriched in pathways such as those regulating the metabolism of lipid and type I interferon, among other significantly enriched pathways ( Figure 3A,C).

LPIN2 as a Unique DEG in Infected Bronchial Epithelial Cells from Obese Subjects
To identify key genes that are unique to bronchial epithelial cells from obese subjects and are core players in SARS-CoV-2-infected cells as compared to non-infected cells, we intersected the 2 initial comparisons which comprise the 286 DEGs (unique to obesity) and the 41 DEGs (unique to SARS-CoV-2 infection). Only five genes (CASC5 (KNL1), LPIN2, MIR143HG (CARMN), ULBP1 and THRB) were identified ( Figure 4). Interestingly, among the five genes identified, LPIN2, a magnesium-dependent phosphatide phosphatase enzyme, is known to play a major role in triglyceride metabolism, inflammasome regulation, and as a transcriptional co-regulator of gene expression [12][13][14][15].

LPIN2 as a Unique DEG in Infected Bronchial Epithelial Cells from Obese Subjects
To identify key genes that are unique to bronchial epithelial cells from obese subjects and are core players in SARS-CoV-2-infected cells as compared to non-infected cells, we intersected the 2 initial comparisons which comprise the 286 DEGs (unique to obesity) and the 41 DEGs (unique to SARS-CoV-2 infection). Only five genes (CASC5 (KNL1), LPIN2, MIR143HG (CARMN), ULBP1 and THRB) were identified ( Figure 4). Interestingly, among the five genes identified, LPIN2, a magnesium-dependent phosphatide phosphatase enzyme, is known to play a major role in triglyceride metabolism, inflammasome regulation, and as a transcriptional co-regulator of gene expression [12][13][14][15]. To gain insight about the expression of LPIN2 in bronchial epithelial cells during the infection, the normalized gene expression of LPIN2 was extracted from the RNA-Seq data at different time points, in both non-obese and obese subjects. The percentage of change of LPIN2 expression in infected compared to non-infected NHBE cells was plotted as a percentage against the time points in both non-obese and obese groups ( Figure 5). At 4 h To gain insight about the expression of LPIN2 in bronchial epithelial cells during the infection, the normalized gene expression of LPIN2 was extracted from the RNA-Seq data at different time points, in both non-obese and obese subjects. The percentage of change of LPIN2 expression in infected compared to non-infected NHBE cells was plotted as a percentage against the time points in both non-obese and obese groups ( Figure 5). At 4 h of SARS-CoV-2 infection, the NHBE cells from non-obese subjects exhibited higher LPIN2 expression as compared to the obese subject group ( Figure 5). However, at 24 h post-infection, LPIN2 expression was decreased in the non-obese subject group and was rather increased in obese subject groups ( Figure 5). Interestingly, LPIN2 expression was retained in the infected NHBE cells from non-obese subjects after 24 h, to reach a maximal expression peak at 48 h post-infection ( Figure 5), while those of obese subject group failed to overexpress LPIN2 after this timepoint. Such a trend of differential expression of LPIN2 might coincide with the increased viral entry and replication in NHBE cells. Additionally, this may indicate a possible modulation of the inflammatory response upon SARS-CoV-2 infection given the role of LPIN2 in the regulation of inflammation.

Bronchial Epithelial Cells from Obese Subjects Mount a Stronger Cytokine Response u SARS-CoV-2 Infection at Early Stages of Infection
Having pointed out LPIN2 as a unique DEG in SARS-CoV-2-infected NHBE ce inflammatory profile was assessed during infection by qRT-PCR in an in vitro c system. The mRNA expression of five inflammatory markers (IL-17A, IL-1β, IL-6, IL IFN-β) was measured in bronchial epithelial cells from obese and non-obese subject IL-8, IL-17A plays a role in recruiting neutrophils to the lung [16] and in contributin cell activation. Our data showed that upon SARS-CoV-2 infection, NHBE cells from subjects displayed significantly increased IL-17A mRNA levels compared to all groups at 4 h ( Figure 6A). Then, IL-17A expression quickly decreased significa match the baseline levels of the cytokine in infected and non-infected cells from non subjects, and non-infected cells from obese individuals, at the 8 h time point. Ho this expression of IL-17A mRNA was increased at 72 h in both infected non-obe obese subject groups as compared to other time points ( Figure 6A).

Bronchial Epithelial Cells from Obese Subjects Mount a Stronger Cytokine Response upon SARS-CoV-2 Infection at Early Stages of Infection
Having pointed out LPIN2 as a unique DEG in SARS-CoV-2-infected NHBE cells, the inflammatory profile was assessed during infection by qRT-PCR in an in vitro culture system. The mRNA expression of five inflammatory markers (IL-17A, IL-1β, IL-6, IL-8 and IFN-β) was measured in bronchial epithelial cells from obese and non-obese subjects. Like IL-8, IL-17A plays a role in recruiting neutrophils to the lung [16] and in contributing to T cell activation. Our data showed that upon SARS-CoV-2 infection, NHBE cells from obese subjects displayed significantly increased IL-17A mRNA levels compared to all other groups at 4 h ( Figure 6A). Then, IL-17A expression quickly decreased significantly to match the baseline levels of the cytokine in infected and non-infected cells from non-obese subjects, and non-infected cells from obese individuals, at the 8 h time point. However, this expression of IL-17A mRNA was increased at 72 h in both infected non-obese and obese subject groups as compared to other time points ( Figure 6A). Known for its role in downregulating the inflammatory response and for its antiviral properties, the mRNA expression of IFN-β was also assessed [17,18]. Differential expression of IFN-β mRNA was observed between SARS-CoV-2-infected bronchial epithelial cells from non-obese and obese subjects, where the obese group displayed significantly higher IFN-β mRNA expression at 4 h and 8 h post-infection. At 8 h post-infection, infected cells from obese subjects are at the peak of their IFN-β expression while non-infected cells from the same obese subjects already express low levels of IFN-β. However, this IFN-β Known for its role in downregulating the inflammatory response and for its antiviral properties, the mRNA expression of IFN-β was also assessed [17,18]. Differential expression of IFN-β mRNA was observed between SARS-CoV-2-infected bronchial epithelial cells from non-obese and obese subjects, where the obese group displayed significantly higher IFN-β mRNA expression at 4 h and 8 h post-infection. At 8 h post-infection, infected cells from obese subjects are at the peak of their IFN-β expression while non-infected cells from the same obese subjects already express low levels of IFN-β. However, this IFN-β expression showed reduced expression levels starting at 24 h post-infection ( Figure 6B). Notably, this correlates with the increase in internalization and replication of the virus in NHBE cells from obese subjects at 24 h post-infection, as seen in Figure 1. This also coincides with the changes in LPIN2 expression seen in cells from obese subjects post-infection ( Figure 5).
Elevated levels of IL-6, a main pro-inflammatory mediator, have been associated with a poorer prognosis in COVID-19 patients [19,20]. Independent of infection, bronchial epithelial cells from obese subjects showed a higher IL-6 expression at 4 h than the bronchial epithelial cells from non-obese subjects ( Figure 6C). From 12-48 h timepoints, IL-6 expression in all 4 groups-infected/non-infected bronchial epithelial cells from non-obese/obese subjects-was very low and spiked again at 72 h, particularly in the infected cells from obese subjects ( Figure 6C).
A significant difference of IL-8 expression was determined between the infected nonobese and obese groups. IL-8 mRNA expression in NHBE cells from obese subjects (4 h post-infection) was greater than that in the infected non-obese group ( Figure 6D). In cells from obese subjects, IL-8 expression was at its highest at the beginning of infection, but then it steadily declined. Notably, the expression of IL-8 mRNA peaked in the cells from infected non-obese subjects at 72 h, while it remained at baseline throughout the assessment period ( Figure 6D). IL-8 as a neutrophil chemoattractant might contribute to the cleanup of infected cells or exacerbating tissue damage, within different timeframes in obese (earlier) vs. non-obese (later) individuals.
In contrast to the other cytokines, expression of IL-1β remained similar between groups throughout the assessment period. In all groups, IL-1β expression increased after 48 h of infection ( Figure 6E). However, at 72 h post-infection, there was a significant increase of expression of IL-1β in the infected non-obese group as compared to all other time points of the same infected group ( Figure 6E).

Upregulated ACE2 Expression in Bronchial Epithelial Cells from Obese Subjects
Given the differential viral load and expression of cytokines in NHBE cells, we aimed to assess the mRNA levels of ACE2 during SARS-CoV-2 infection in the targeted cells. NHBE cells from obese subjects showed increased ACE2 expression at 4 h of infection compared to non-infected cells as well as infected and non-infected cells from non-obese subjects ( Figure 6F). At 24 h, a notable decrease in ACE2 expression was seen in all groups. This correlates with the changes in viral internalization/replication and cytokine changes that were described earlier. ACE2 levels in both infected non-obese and obese subjects increase again at 72 h. However, this late increase in ACE2 expression was more pronounced in the non-obese infected group.
Collectively, this data highlights the interplay between obesity and SARS-CoV-2 infection on the progression of the disease through the modulation of the inflammatory response.

Discussion
The association between COVID-19 severity and obesity has been well documented. Several studies have now shown higher rates of hospitalization and more critical outcomes with cytokine storm [21]. However, and to our knowledge, an explanation of the exact mechanisms through which obesity confers increased susceptibility to SARS-CoV-2 is limited. In this study, we highlighted the enhanced viral load in bronchial epithelial cells in obese subjects upon SARS-CoV-2 infection using an in vitro infection model. We performed RNA-Seq analysis to profile the core transcriptomic difference between non-obese and obese subjects upon infection to better understand the enhanced viral load among the obese subjects. Interestingly, our data emphasized the enrichment of lipid metabolism-related pathways in infected bronchial epithelial cells from obese subjects, with LPIN2, known for inflammasome regulation, being a unique differentially expressed gene. Such findings were further translated into an in vitro application, where we have shown the dysregulation of immune responses via the altered cytokine expression in SARS-CoV-2-infected bronchial epithelial cells of obese subjects.
In a recent study, we characterized the metabolic profiling of obese COVID-19 subjects, where we highlighted the possible involvement of N6-acetyl-l-lysine and p-Cresol as two key metabolites in the pathogenesis of obese COVID-19 subjects. We showed that the elevated levels of these two metabolites could potentially enhance viral replication, on the one hand, and increase ACE2 expression, on the other, in obese subjects [22]. Previous studies suggest that SARS-CoV-2 infection subverts the host's altered lipid metabolism and exploits metabolic and immune alterations in obesity, which promotes viral propagation and chronic inflammation [23,24]. These findings correlate with our results which showed significantly higher SARS-CoV-2 internalization and replication in bronchial epithelial cells obtained from obese subjects at 24 h. It is unsurprising that differences in gene expression that were found between non-infected bronchial epithelial cells from nonobese and obese subjects via RNA-Seq are enriched in lipid-related pathways. It has been documented that host lipids affect SARS-CoV-2 entry, replication and propagation, hence affecting the virus life cycle [25]. However, our data has also identified the expression of LPIN2 as a unique DEG in the infected bronchial epithelial cells of obese subjects. LPIN2, a phosphatidic acid phosphatase-1 (PAP-1)-encoding gene, plays important roles in controlling the metabolism of fatty acids. Additionally, LPIN2 is known to be involved in inflammation-modulating apoptosis of polymorphonuclear cells and as a negative regulator of the NLRP3 inflammasome [12][13][14][15]. Mutations in LPIN2 can increase inflammasome activity and interleukin (IL)-1 release in primary human and mouse macrophages [26]. Of note, PAP-1 has important roles in the mediation of the lipid metabolism, affecting the replication and envelope formation of several mRNA viruses by regulating downstream lipid production, hence affecting its life cycle [27,28].
To gain further mechanistic insight on how obesity contributes to SARS-CoV-2 progression and susceptibility, we aimed to assess the cytokine expression of the bronchial epithelial cells from obese versus non-obese subjects upon the differential development of the viral titer. It is worth noting that one of the important mechanisms that links obesity and the worsening of COVID-19 disease is the dysfunctional immunity and the induction of the cytokine storm [29,30]. Inflammatory markers IFN-β, IL-8, IL-17A and IL-6 displayed higher expression in bronchial epithelial cells from obese subjects. Interferons (IFNs) are the first pivotal defense line against viruses at early stages of infection and its downregulation leads to uncontrolled viral replication and delayed viral elimination [30,31]. A peak in IFN-β expression was observed at 8 h post-infection in cells from obese subjects. However, as time progressed, the IFN response decreased notably, starting at 12 h. Interestingly, this correlated with the detected increase in viral internalization and replication at 24 h. Clinical observations show that obese patients fail to launch a robust innate and acquired immune responses [32]. This slow response may be the cause of more severe COVID-19 disease in obese and overweight individuals. A study has shown that a delayed IFN type I response is more detrimental, causing more lung immunopathology in mice compared to that in animals that had little to no IFN type I response during SARS-CoV-1 infections [33]. Moreover, previous studies on H1N1 influenza reported an impaired production of IFN-α and IFN-β due to leptin, a hormone produced by the adipose tissue that is known to regulate fat storage [30,31].
An important drop in cytokine expression was observed during infection. This is probably related to the virus taking over the transcriptional machinery of the cell to transcribe viral genes. This would be supported by the significant increase of viral gene expression at 24 h post-infection, where the host inflammatory response is largely downregulated. Cytokine dysregulation was also shown in other studies involving H1N1 influenza virus, driving tissue damage and pathological progression. IL-6 and IL-1β expression were shown to be downregulated in the lungs of obese mice at early stages of H1N1 infection when compared to their non-obese counterparts [34,35]. Despite this decrease of inflammatory markers, at 72 h post-infection, a remarkable increase of cytokine expression (IL-17A, IL-6, IL-1β and IL-8) was detected. Such an increase coincides with the downregulated expression of viral load and LPIN2 at 72 h, as well as downregulated IFN-β in infected cells. Remarkably, IL-6 was among the significant highly detected cytokines in infected bronchial epithelial cells from obese subjects. Mechanistic studies have shown leptin and adiponectin levels to be associated with the activation of inflammatory monocytes and neutrophils through NF-κB signaling pathways which, in turn, induces the secretion of several cytokines such as IL-6, resulting in excessive inflammatory responses or a cytokine storm [36,37].
The dysregulated immune response can also be correlated with ACE2 mRNA expression. We have previously shown that bronchial epithelial cells from obese subjects express more ACE2 mRNA at baseline [38]; hence, we wanted to evaluate the expression of ACE2 during the course of the in vitro infection. Our data show significantly higher mRNA expression of ACE2 in the infected bronchial epithelial cells from obese subjects compared to infected cells from non-obese subjects, as early as 4 h post-infection. This was expected, as upregulated ACE2 levels in obese individuals have been well established [7,23,39]. However, this expression was seen to decrease with time post-infection, in both bronchial epithelial cells from obese and non-obese subjects. The decrease in ACE2 expression seen at later stages post-infection is supported by other studies which have shown that SARS-CoV-2 infection decreases ACE2 expression [7,40]. After binding to SARS-CoV-2 spike protein, ACE2 fails to catalyze protective and anti-inflammatory Angiotensin (1-7), thus shifting the renin angiotensin system (RAS) to a pro-inflammatory phenotype which, in turn, leads to respiratory distress [29]. Despite this decrease in ACE2 expression, notably, our data displayed an elevated ACE2 expression in infected bronchial epithelial cells from non-obese subjects at 72 h post-infection, but not in infected bronchial epithelial cells from obese subjects. This could be attributed to obesity-dysregulated lipid metabolism via the sterol-response element-binding proteins (SREBP), a transcription factor associated with adipogenesis [38].
In summary, this is the first study to show the time course of SARS-CoV-2 infection in obese and non-obese bronchial epithelial cells, using an in vitro infection model. The study provided a molecular overview on the involvement of obesity in increased SARS-CoV-2 infection. It also emphasized the dual role of both obesity and SARS-CoV-2 as complementary factors that contribute to the detrimental progression of COVID-19. This study proves that bronchial epithelial cells from obese subjects are, in fact, infected at a higher rate than bronchial epithelial cells from non-obese subjects. The ensemble of dysregulated immune responses in obese subjects during the first three days of infection described here may be a pre-requisite for the cytokine storm development that is more frequently observed in this high-risk group for severe COVID-19. This may shed light on understanding the immune response in obese patients, which may aid in developing better therapeutic strategies to care for obese COVID-19 patients.

Cell Culture
Normal human primary bronchial epithelial (NHBE) cells from non-obese and obese subjects were purchased from a commercial source (MatTek, Ashland, MA, USA) or obtained from the Biobank of the Quebec Respiratory Health Research Network at the Meakins-Christie Laboratories, Research Institute of the McGill University Health Centre (Glen site). Table 1 represents subjects' characteristics from the non-obese and obese donors. NHBE cells were cultured in BEGM media (Lonza, Walkersville, MD, USA) supplemented with 1% antibiotic antimycotic solution (Wisent, St-Bruno, QC, Canada) in tissue culture flasks coated with Type 1 rat tail collagen (Sigma-Aldrich, Oakville, ON, Canada). Cells were harvested at 90% confluency.  The cells were then incubated for 8, 12, 18, 24, 48 and 72 h. Media were collected at each time point and stored at −80 • C for later analysis. RNA extraction reagent (500 µL) was added to each well and incubated at room temperature for 5 min. Samples were stored at −80 • C until RNA extraction.

RNA Extraction
Total RNA extraction from NHBE cells was performed using a phenol-chloroform extraction (RiboZol RNA extraction reagent, VWR, Leicestershire, UK), as directed by the manufacturer's instructions. RNA was also extracted from 100 ul of cell culture supernatant, using 1 mL of extraction reagent. Glycogen precipitated the RNA from these samples (ThermoScientific, Waltham, MA, USA), as directed in the manufacturer's instructions. Contaminating DNA was removed from 500 ng of total RNA using DNAse I and Ribolock RNAse Inhibitor (ThermoScientific, Waltham, MA, USA). This solution was incubated at 37 • C for 30 min. An amount of 1 µL of 50 mM EDTA was added to each sample and incubated at 65 • C for 10 min to inactivate the enzyme. Reverse transcription was performed using AdvanTech 5X Reverse Transcriptase Mastermix (Diamed, Mississauga, ON, Canada). Viral detection and replication were assessed by measuring levels of SARS-CoV-2 nucleocapsid (N) and viral envelope (UpE) mRNA, respectively. A standard curve generated in the Bio-Rad CFX Maestro 2.2 software of the serially diluted single-stranded complementary DNA (cDNA) extracted from the viral stock was used to quantify the relative levels of these viral genes by determining the corresponding median tissue culture infectious dose (TCID50) of each sample [41]. Viral genes were measured using AdvanTech 2X qPCR MasterMix (Diamed, Mississauga, ON, Canada) in CFX96 thermal cycler (BioRad, Hercules, CA, USA).

RNA Sequencing
RNA from qPCR experiments above was used for total RNA sequence. RNA from NHBE cells from non-obese, obese subjects, non-infected (n = 4) and infected (n = 4) and obese (n = 4) were pooled together for the following time points: 4, 8, 12, 24, 48 and 72 h, for a total of 24 samples. The sequencing was performed by the Centre d'expertise et de services Génome Québec. Their procedure is as follows.
Total RNA was quantified using a NanoDrop Spectrophotometer ND-1000 (NanoDrop Technologies, Inc., Wilmington, DE, USA) and its integrity was assessed on a 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Libraries were generated from 10 ng of total RNA as follows. cDNA synthesis was achieved with the NEBNext RNA First Strand Synthesis and NEBNext Ultra Directional RNA Second Strand Synthesis Modules (New England BioLabs, Ipswich, MA, USA). The remaining library preparation steps were carried out using the NEBNext Ultra II DNA Library Prep Kit for Illumina (New England BioLabs, Ipswich, MA, USA). Adapters and PCR primers were purchased from New England Bio-Labs. Libraries were quantified using the Kapa Illumina GA with Revised Primers-SYBR Fast Universal kit (Kapa Biosystems, Wilmington, MA, USA). The average size fragment was determined using a LabChip GX (PerkinElmer, Waltham, MA, USA) instrument.
The libraries were normalized and pooled and then denatured in 0.05 N NaOH and neutralized using HT1 buffer. The pool was loaded at 200 pM on an Illumina NovaSeq S4 flowcell as per the manufacturer's recommendations. The run was performed for 2 × 100 cycles (paired-end mode). A phiX library was used as a control and mixed with libraries at 1% level. Base calling was performed with RTA v3.4.4. Program bcl2fastq2 v2.20 was then used to demultiplex samples and generate FASTQ reads.

Identification of Differentially Expressed Genes (DEGs)
Generated FASTQ files were uploaded to AltAnalyze to directly produce gene-expression estimates using the kallisto program for ultra-fast pseudoalignment and isoform quantification from RNA-Seq FASTQ files [42]. The resultant normalized gene expression (quantile) for each sample was then used to identify differentially expressed genes. As the samples per group were pooled to make the quantity of RNA sufficient to run RN-Seq, each pool was considered as one sample for downstream analysis. Pooling RNA samples was a good option to optimize cost and maintain power. To identify DEGs among different patient groups and different time points of infection, comparing two conditions without replicates (TCWR) has been used by applying individualized DEG (iDEG) method following a distribution calculated across a local partition of related transcripts at baseline expression; thereafter, the probability of each DEG was estimated by empirical Bayes with local false discovery rate control using a two-group mixture model. DEGs were shown if they had less than or equal to 0.05 with fold change more than 2 or less than −2 between the samples examined. The top DEGs between obese and non-obese, infected and non-infected during different time points were listed and the corresponding enriched pathways were listed using Metascape online tool (https://metascape.org/gp/index.html, accessed on 8 February 2023).

Inflammatory Marker Quantification Using qRT-PCR
Real time primers are listed in Table 2. cDNA was synthesized as mentioned above and mRNA levels of inflammatory markers and ACE2 were measured using AdvanTech 2X qPCR MasterMix (Diamed, Mississauga, ON, Canada) in CFX96 thermal cycler (BioRad, Hercules, CA, USA). PCR amplification steps were as follows: 94 • C for 1 min, followed by 40 cycles of 95 • C for 30 s and 58 • C for 1 min. At the end of the amplification, a melting temperature analysis of the amplified gene products was performed routinely for all cases: the PCR products were melted by gradually increasing the temperature from 65 • C to 95 • C in 0.5 • C increments. The ∆∆Cq method was used to measure gene expressions of inflammatory markers and ACE2 after normalizing to the reference genes, GAPDH. Table 2. Forward and reverse primers.

Statistics
One-way ANOVA test and Tukey post hoc test were used to define statistical significance.