Abstract
Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019. In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virus-infected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105 PFU; however, 1×102 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.
Keywords: SARS-CoV-2; K18-hACE2 mice; Dose-response relationship, immunologic; Transcriptome profiling; Immune response
INTRODUCTION
A cluster of pneumonia cases was reported in Wuhan, China in December 2019. The Chinese health authorities confirmed on January 7, 2020 that this cluster was associated with a novel coronavirus. The World Health Organization dubbed this novel coronavirus infection “coronavirus disease 2019” (COVID-19) on February 11 (1). The causative agent of the pandemic, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a positive-sense, single-stranded RNA virus belonging to the family Coronaviridae (2). Upon binding to epithelial cells in the respiratory tract, SARS-CoV-2 begins replication and migration to the airways, and entry into alveolar epithelial cells (3). In a separate study, the effects of infectious SARS-CoV-2 doses on the pathology of K18-hACE2 transgenic mice were evaluated (4). According to the study, 2×103 plaque-forming units (PFU) or 2×104 PFU SARS-CoV-2 were lethal enough to kill 90% of the mice around 7 days post inoculation (dpi), while some of the mice infected with 2×101 PFU or 2×102 PFU died at 10 dpi, and the others recovered and survived until 20 dpi (4). In terms of histopathology, high-dose groups exhibited extensive alveolar collapse with ruptured septa, whereas 30%–60% of low-dose groups exhibited alveolar congestion in the alveoli (4). Nevertheless, previous studies did not investigate the effects of a viral inoculum dose on the transcriptome of an animal model (4).
Several viral infections, including influenza and SARS, have demonstrated a correlation between infectious dose and disease severity (5,6). For COVID-19, high viral loads in the saliva, respiratory secretions, and blood were associated with more severe illnesses (7,8). A previous study on SARS-CoV-2 infection in 16 cynomolgus macaques demonstrated that the infectious dose indeed influenced both symptom development and seroconversion (9). Low doses of aerosolized viruses led to seroconversion and viral replication in the respiratory tract without symptom development, whereas high doses produced fever, suggesting that low infectious doses may be associated with asymptomatic infections (9). In addition, a dose titration study of SARS-CoV-2 in a ferret model demonstrated evidence of protective immunity (10). When a high (5×106 PFU) or moderate (5×105 PFU) dose of the virus was delivered intranasally, viral RNA shedding was observed in the upper respiratory tract of all animal subjects. However, only one out of 6 ferrets exhibited comparable symptoms in response to a low-dose (5×102 PFU) challenge (10).
Despite previous research on the correlation between viral concentration and the manifestation of infection, it remains unclear whether exposure to a higher viral inoculum could increase the likelihood of developing severe COVID-19. Although intuitive, obtaining such dose-response data has been difficult. In addition, the immune responses to varying doses of virus infection in K18-hACE2 transgenic mice, in which hACE2 expression is controlled by the epithelial cell cytokeratin-18 (K18) promoter for efficient SARS-CoV-2 infection, are not completely understood (11,12,13,14). Therefore, in this study, we aimed to assess the overall clinical pathogenesis and transcriptome profile of the lungs and spleens of K18-hACE2 transgenic mice intranasally inoculated with 1×105 and 1×102 PFU of SARS-CoV-2. The dose-specific response to SARS-CoV-2 infection was better comprehended through a thorough examination of these organs.
MATERIALS AND METHODS
Mice and virus
This research used 8-wk-old K18-hACE2 male mice (B6.Cg-Tg[K18-ACE2]2Prlmn/J, Hemizygous, #034860; Jackson Laboratory, Bar Harbor, ME, USA) for SARS-CoV-2 infection. The protocol for animal experiments was approved by the Institutional Animal Care and Use Committee (2020-0216, BA-2008-301-071-03) of Yonsei University College of Medicine. SARS-CoV-2 (accession number: NCCP 43326, S clade, beta variant) was obtained from the National Culture Collection for Pathogens in Korea and passaged using the Vero cell line (Korean Cell Line Bank, Korea, accession number: 10081).
Infection of mice
Mice were anesthetized with 30 mg kg-1 zoletil/10 mg kg-1 rompun. Next, intranasal infection was performed with phosphate-buffered saline for mock and 1×102 and 1×105 PFU SARS-CoV-2 in 50 μl of culture medium. The infected mice were weighed and body temperature measured daily using an implantable temperature transponder (Bio Medic Data Systems, Seaford, DE, USA). Over 20% of body weight loss and 10°C of body temperature loss mouse euthanized using CO2. All experiments with SARS-CoV-2 were conducted in the biosafety level 3 laboratory at Yonsei University College of Medicine.
Histopathological analysis
The SARS-CoV-2-infected mice were euthanized, and autopsies were conducted. The delivered tissues were fixed in 10% neutral buffered formalin for 24 h and embedded in paraffin wax. For histopathological analysis, the paraffin blocks were sectioned at 4 μm thickness, deparaffinized, and stained with H&E. The stained slides were deciphered by an animal pathologist, and lung pathological findings were categorized. Inflammation due to the infiltration of immune cells, edema, and the capillary dilatation were the main pathologies behind the lesions detected. The lesion grade, compared with control, was assessed by pathologists into 6 grades as follows: 0 (no lesions), 1 (<10% rare lesions in alveolar, endothelial and bronchus region), 2 (mild, 21%–40%), 3 (moderate, 41%–60%), 4 (severe, 61%–80%), 5 (very severe, >80%).
Cell isolation and flow cytometry
To isolate cells from inflamed tissues, lung tissues were cut into four pieces and gently stirred in flasks with solution (PBS containing 25 ml 10 mM EDTA, 3% FBS [HyClone Laboratories, Logan, UT, USA], 20mM HEPES and 1mM sodium pyruvate) for 30 min at 37°C. The segments were washed three times with PBS and digested with 5 ml RPMI 1640 containing 1 mg/ml of type V collagenase (Sigma-Aldrich, St. Louis, MO, USA) for 45 min at 37°C. Finally, the soup containing ear total cell was centrifuged and cultured in T cell media. For the surface marker staining, cells were washed with ice-cold PBS, re-suspended in 100 μl of PBS and stained with anti-CD3-BUV395, anti-CD45 (eBioscience, San Diego, CA, USA), anti-CD19-PE/Cy7 (BioLegend, San Diego, CA, USA), anti-CD4-FITC, anti-CD8-Percp5.5 (BioLegend). Dead cells were excluded using LiveDead Fixable Viability dye (Invitrogen, Waltham, MA, USA). Samples were acquired using ID7000 (Sony, Tokyo, Japan) and data were analyzed using FlowJo software (Tree Star, Ashland, OR, USA).
RNA sequencing (RNA-seq) and bioinformatic analyses
The lungs and spleens isolated from at 0, 1, 2, 5, 7 dpi of 1×105 PFU virus infected mice and at 0, 1, 2, 5, 7, 10, 14 dpi of 1×102 PFU virus infected mice were stored at −80°C in RNAlater solution. Tissues were moved to 1× PBS to remove residual RNAlater solution. Homogenization of tissues and total RNA extraction was conducted using a RNeasy plus mini kit (Qiagen, Valencia, CA, USA). Total RNA concentration was calculated by Quant-IT RiboGreen (#R11490; Invitrogen). To assess the integrity of the total RNA, samples are run on the TapeStation RNA screentape (#5067-5576; Agilent Technologies, Santa Clara, CA, USA). Only high-quality RNA preparations, with RIN greater than 7.0, were used for RNA library construction.
A library was independently prepared with 0.5 ug of total RNA for each sample by Illumina Stranded Total RNA Library Prep with Ribo-Zero Plus (#20040529; Illumina, Inc., San Diego, CA, USA). The first step in the workflow involves removing the rRNA in the total RNA. Following this step, the remaining mRNA is fragmented into small pieces using divalent cations under elevated temperature. The cleaved RNA fragments are copied into first strand cDNA using SuperScript II reverse transcriptase (#18064014; Invitrogen) and random primers. This is followed by second strand cDNA synthesis using DNA Polymerase I, RNase H and dUTP. These cDNA fragments then go through an end repair process, the addition of a single ‘A’ base, and then ligation of the adapters. The products are then purified and enriched with PCR to create the final cDNA library. The libraries were quantified using KAPA Library Quantification kits for Illumina Sequencing platforms according to the qPCR Quantification Protocol Guide (#KK4854; Kapa Biosystems, Wilmington, MA, USA) and qualified using the TapeStation D1000 ScreenTape (#5067-5582; Agilent Technologies). Indexed libraries were then submitted to an Illumina NovaSeq (Illumina, Inc.), and the paired-end (2×101 bp) sequencing was performed by the Macrogen Incorporated.
CLC Genomics Workbench 9.5.3 software (Qiagen GmbH, Hilden, Germany) was used to map the reads to the mouse genome (mm10, build name GRCm38) (Supplementary Tables 1 and 2) and SARS-CoV-2 viral genome (GenBank: MN985325.1) and generate gene expression values in the normalized form of transcripts per kilobase million. After checking quality of samples, 23 (lungs) and 22 (spleen) samples at 0 (n=4; n=5), 1 (n=5; n=5), 2 (n=5; n=4), 5 (n=5; n=4), 7 dpi (n=4; n=4) were used for analysis in 1×105 PFU. For 1×102 PFU, total 28 (lungs) and 29 (spleen) samples at 0 (n=4; n=5), 1 (n=5; n=5), 2 (n=4; n=5), 5 (n=4; n=4), 7 (n=4; n=3), 10 (n=3; n=3), 14 dpi (n=4; n=4) were used. All differentially expressed genes (DEGs) were chosen based on the Benjamini–Hochberg false discovery rate (FDR)-adjusted p-value (i.e., q value <0.01) and two-fold differences by performing a statistical ANOVA of multiple groups. For Volcano and MA plots, a 2-group comparison analysis between the infected and non-infected control groups was performed using R package DESeq2, assuming negative binomial distribution. In MA plots, differentially expressing genes were chosen based on Benjamini–Hochberg FDR-adjusted p-value (i.e., q value <0.05). RStudio v3.6.3, which includes hierarchical clustering and principal components analysis, was used to analyze RNA-seq data. Gene Ontology (GO) enrichment analysis was performed using the R package clusterProfiler4 (15). Statistical significance was set at p<0.05. Immune cell deconvolution was performed using the R package immunedeconv (16).
Statistical analysis
Statistical significance was calculated using PRISM v9.0 software (GraphPad Software, San Diego, CA, USA). Error bars display SEM and significance was calculated using 2-way ANOVA with Bonferroni’s multiple comparisons test.
RESULTS
Viral loads of SARS-CoV-2 influence mortality rates, and even low-dose infection induces pulmonary fibrosis
To determine the clinical characteristics of SARS-CoV-2 infection, we examined body weight loss and body temperature up to 14 dpi of the virus challenge. Compared with that in the negative control and at 0 dpi, the 1×102 PFU-infected mice exhibited a mild decrease in body temperature at 5–7 dpi and a decrease in body weight of approximately 20% at 5–8 dpi. Both clinical parameters steadily improved from 8 dpi to 14 dpi. In the 1×105 PFU-infected mice, however, severe clinical symptoms were observed; body temperature decreased dramatically to approximately 26.8°C at 4 dpi, and body weight was reduced by 25% (Fig. 1A and B). The survival rate varied with the infected viral dose; 50% of the 1×102 PFU-infected mice survived up to 14 dpi, whereas 83% of the 1×105 PFU-infected mice died at 7 dpi, and all died at 8 dpi (Fig. 1C). There were significant differences in the viral titers in the lungs at 2 dpi, reflecting different viral loads, but not at 7 dpi (Fig. 1D).
Figure 1. SARS-CoV-2 viral loads influence mortalities.
(A, B) Body temperature (A) and body weight (B) of PBS-infected control K18-hACE2 mice (n=6), 1×102 PFU-infected mice (n=8), and 1×105 PFU-infected mice (n=8). (C) Survival rate after infection with SARS-CoV-2. (D) Virus titer was measured at 2 and 7 dpi. Error bars are SEM and significance was calculated using 2-way ANOVA with Bonferroni’s multiple comparison test.
*p<0.05; ****p<0.0001.
Then, we analyzed pulmonary pathology resulting SARS-CoV-2 infection. At 2 dpi, both 1×102 and 1×105 PFU-SARS-CoV-2-infected mice exhibited mild lesions (Fig. 2A and B). Inflammation due to the infiltration of immune cells, edema, and the capillary dilatation were the primary pathologies behind the lesions observed. The severity of the lesions and the pathology score were higher at 7 dpi than at 2 dpi (Fig. 2C and D). Even 1×102 PFU-infected mice exhibited fibrotic lesions at 7 dpi (Fig. 2A and C), despite an improvement in body temperature and body weight change after 8 dpi.
Figure 2. A lower dose of SARS-CoV-2 infection induces pulmonary fibrosis.
(A, B) H&E staining of lung sections in control, 1×102 PFU-, and 1×105 PFU-infected mice. Lungs infected with SARS-CoV-2 exhibit inflammation (white +), vascular edema (arrow), capillary dilatation (arrowhead), and pulmonary fibrosis (open circled). The letters ‘B’ and ‘V’ represent the bronchiole and vessel, respectively (scale bars, 100 μm). (C, D) Pathological score. Error bars are SEM and significance was calculated using 2-way ANOVA with Bonferroni’s multiple comparison test.
***p<0.001; ****p<0.0001.
SARS-CoV-2 viral loads induce temporally different but transcriptionally similar changes in the lungs
We performed RNA-seq of SARS-CoV-2-infected lungs and spleens to examine the effects of viral concentration on the host response. Evaluation of data quality confirmed relatively uniform transcriptome among samples (Supplementary Fig. 1). When the data were combined in a single PCA plot, the samples were segregated according to the organ, as determined by the principal component 1 (Supplementary Fig. 2). Principal component analysis plots demonstrated that transcriptomes of 1×105 PFU-infected mice’s lungs and spleens were temporally distinct (Supplementary Fig. 1). The lung transcriptome profile of mice infected with 1×102 PFU showed that samples at 5, 7, and 10 dpi were projected away from early infection samples, whereas samples at 14 dpi were positioned adjacent to samples taken at 0 dpi (Supplementary Fig. 1), suggesting that the transcriptome of surviving mice returned to a non-infected state. The spleen samples from the 1×102 PFU-infected mice lacked a temporally distinct transcription profile and were not discretely divided into groups (Supplementary Fig. 1). To more precisely assess the extent of infection, we mapped the RNA-seq reads to the SARS-CoV-2 genome (Supplementary Fig. 3). In the lungs, the aligned portion of reads culminated at 2 dpi at 1×105 PFU and 7 dpi at 1×102 PFU, respectively. At the peak time point, the mean percentage of mapped reads of 1×105 PFU-infected lungs to the SARS-CoV-2 genome was approximately 15 times greater than that of 1×102 PFU SARS-CoV-2-infected lungs (Supplementary Fig. 3). The spleen samples at 1×105 PFU showed a progressive increase in the aligned portion from 2 to 7 dpi, although it was significantly lower than that in the lungs where nearly 40% of counts were aligned at 2 dpi at 1×105 PFU (Supplementary Fig. 3). Compared to that of 1×105 PFU-infected spleen samples, the aligned percentage of 1×102 PFU-infected spleen samples was barely detectable (Supplementary Fig. 3).
DEGs relative to non-infected controls were identified at different time points. MA plots revealed that the number of DEGs increased over time after infection with a 1×105 PFU viral load (Supplementary Fig. 4), while it remained relatively constant regardless of the time course at 1×102 PFU in both organs; however, fewer genes were differentially expressed in spleens (Supplementary Fig. 4).
Multiple comparisons identified 1,348 and 1,094 DEGs in the lungs of mice infected with 1×105 PFU- and 1×102 PFU, respectively. At each dose, hierarchical clustering identified three and four patterns respectively, in the lungs (Supplementary Figs. 5 and 6). The GO analysis of DEGs with particular expression patterns revealed that these genes are implicated in the same biological processes in the infected lungs, irrespective of the viral doses (Supplementary Figs. 5 and 6, Supplementary Table 3). These biological processes were immunoglobulin production, chromosome segregation, and response to the virus (Supplementary Figs. 5 and 6). Several distinct pathways were also identified, but there were no significant distinctions between the representative enriched terms as a whole (Supplementary Figs. 5, 6, and Supplementary Table 3). However, DEGs within the same GO term displayed distinct temporal expression patterns in the lungs infected with 1×105 PFU- and 1×102 PFU (Fig. 3A and B). In the lungs of mice infected with 1×105 PFU, the genes associated with the response to the virus were found to be significantly upregulated at 2 dpi (Fig. 3A). However, when the mice were infected with 1 × 102 PFU, the activation of these genes was delayed and increased after 5 dpi (Fig. 3B). By 14 dpi, the expression of these genes in the lungs of mice infected with 1×102 PFU reverted to the levels observed in non-infected control animals (Fig. 3B). The same expression pattern was observed in type I and II interferon signaling as well as cytokine-mediated signaling, which were found to be stimulated by SARS-CoV-2 infection (12) (Supplementary Fig. 7). Immunoglobulin production, primarily the immunoglobulin kappa variable cluster, decreased in the lungs at both doses as viral infection progressed (Fig. 3A and B). Furthermore, genes associated with chromosome segregation were increased from 5 dpi at both doses (Fig. 3A and B). Meanwhile, in the lungs of 1 × 102 PFU-infected mice, genes associated with muscle contraction decreased until 5 dpi and subsequently increased (Fig. 3B and Supplementary Fig. 6E).
Figure 3. Viral loads of SARS-CoV-2 induce temporally distinct but equivalent transcriptional changes in the lungs, while only 1×105 PFU SARS-CoV-2 induced obvious immune response in spleens.
(A) Heatmap for 108 DEGs with 1×105 PFU-infected lungs (red: 0 dpi, green: 1 dpi, blue: 2 dpi, yellow: 5 dpi, purple: 7 dpi). (B) Heatmap for 153 DEGs with 1×102 PFU-infected lungs (red: 0 dpi, green: 1 dpi, blue: 2 dpi, yellow: 5 dpi, purple: 7 dpi, cyan: 10 dpi, dark red: 14 dpi). (C) Heatmap for 41 DEGs with 1×105 PFU-infected spleens (red: 0 dpi, green: 1 dpi, blue: 2 dpi, yellow: 5 dpi, purple: 7 dpi). (D) Heatmap for 13 DEGs with 1×102 PFU-infected spleens (red: 0 dpi, green: 1 dpi, blue: 2 dpi, yellow: 5 dpi, purple: 7 dpi, cyan: 10 dpi, dark red: 14 dpi).
The enriched GO terms of the biological process are displayed on the right side of heatmaps.
Immunological response in the spleens is obvious at 1×105 PFU but not at 1 × 102 PFU- SARS-CoV-2 infection
In the spleens of 1×105 PFU- and 1×102 PFU-infected mice, analysis of variance identified 700 and 49 DEGs (Supplementary Figs. 8 and 9). Hierarchical clustering analysis revealed that genes were expressed in four distinctive patterns in the 1×105 PFU-infected mice spleens (Supplementary Fig. 8). At 1×102 PFU, two patterns were observed (Supplementary Fig. 9) and DEGs were changed little compared to 1×105 PFU. GO terms representing immune-related processes were significantly enriched at 1×105 PFU compared to 1×102 PFU (Supplementary Fig. 8, Supplementary Table 4). At 1×102 PFU, however, the majority of DEGs were associated with innate or adaptive immune responses, such as negative regulation of viral genome replication and lymphocyte-mediated immunity (Supplementary Fig. 9, Supplementary Table 4).
When we selected representative GO terms enriched in DEGs for each pattern, the defense response to virus was observed in the spleens at both dosages (Fig. 3C and D). Specifically, interferon-stimulated genes, such as the Oas gene family, Ifit1, Ifit3b, and Mx2, which participate in the immediate defense response upon viral intrusion, were highly expressed in the spleens during the early phase of infection at both doses (Fig. 3C and D). In particular, the expression of these genes peaked at 2 dpi in the spleens of 1×105 PFU-infected mice, just as it did in the lungs (Fig. 3A and C). Chemokine-mediated immunity genes exhibited similar expression patterns (Supplementary Fig. 10). Genes involved in interspecies interaction between organisms showed an abrupt decrease at 7 dpi in 1×105 PFU-infected spleens (Fig. 3C). Genes related to erythrocyte development pathway were decreased from 5 to 7 dpi in 1×105 PFU-infected spleens (Fig. 3C). Genes associated with response to IL-1 were dramatically upregulated during the late phase of infection at the 1×105 PFU dose (Fig. 3C). At 1×102 PFU, the number of DEGs was low, but, lymphocyte-mediated immunity, notably orchestrated by B cells, was enhanced from 10 dpi (Fig. 3D). Particularly, neutralizing Abs, such as Ighv1-3, Ighe, Ighv2-6, and Ighv9-2, were increased from 10 dpi (Fig. 3D).
SARS-CoV-2 concentrations determine gene expression levels and temporal changes associated with immune response
We conducted a gene set variation analysis (GSVA) using GO terms associated with immune response (Fig. 3) to compare the temporal changes in gene expression based on virus concentration (Fig. 4A). At 1 × 105 PFU, the majority of genes involved in the response to the virus exhibited the highest expression at 2 dpi in the lungs, followed by a slight decrease until 7 dpi (Fig. 4A). Cxcl10 and Il6 expression peaked at 2 dpi in the lungs of mice infected with 1×105 PFU (Fig. 4B), whereas Cxcl10 and Il6 exhibited delayed expression at 5 dpi at 1×102 PFU, but their maximal expression levels were lower than those at 1×105 PFU (Fig. 4B). Interestingly, at 14 dpi, Cxcl10 and Il6 expression seemed to gradually return to basal levels seen at 0 dpi (Fig. 4B), indicating normalization of gene expression in the lungs of mice that survived infection with 1×102 PFU.
Figure 4. SARS-CoV-2 dosage determines gene expression levels and temporal changes in immune response-related genes.
(A) Heatmaps of the GSVA results for response to virus (GO: 0009615) and immunoglobulin production (GO: 0002377) in lungs infected with 1×105 PFU or 1×102 PFU. (B, D) Graphs illustrating the temporal changes in expression levels caused by SARS-CoV-2 infection for representative genes (orange: 1×105 PFU, blue: 1×102 PFU). (C) Heatmaps for GSVA results for response to virus (GO: 0009615), response to IL-1 (GO: 0070555), and lymphocyte mediated immunity (GO: 0002449) in spleens.
Similar to what was observed in the lungs, genes activated against viral intrusion were highly expressed in the spleens during the early phase of infection, and their expression substantially decreased at 7 dpi (Fig. 4C). In the spleens of mice infected with 1×105 PFU, Cxcl10 and Il6 expression peaked at 2 dpi and returned to almost basal levels by 7 dpi even though mice died. At 1×102 PFU, Cxcl10 and Il6 expression were increased at 2 dpi; however, the expression level was significantly lower than that at 1×105 PFU, and similar expression levels were maintained until 5 dpi (Fig. 4D). Cxcl10 and Il6 expression decreased consistently after 5 dpi and finally returned to basal levels at 14 dpi (Fig. 4D). In contrast, at 7 dpi, genes related to response to IL-1 were markedly upregulated in the spleens of mice infected with 1×105 PFU (Figs. 3C and 4C). For example, Il1r2 and Taf9 exhibited no variation in expression during the early period, but reached their highest level at 7 dpi at 1×105 PFU. However, their expression remained nearly constant at 1×102 PFU (Fig. 4D). The recovery of expression of immunomodulatory genes such as Oas, Ifit, and Mx at 1×102 PFU may have allowed for further survival of SARS-CoV-2-infected K18-hACE2 transgenic mice, whereas the virus at 1×105 PFU virus prevented adequate recovery of both organs (17,18,19).
Specific immune effector cell populations are differentially affected by viral loads in the lungs and spleens
To further characterize the immune response induced by varying concentrations of SARS-CoV-2, we used an in silico deconvolution tool that infers cell-type fractions from bulk RNA-seq data (16). The results of deconvolution revealed the differences in the relative amounts of adaptive immune effectors (Supplementary Figs. 11 and 12). In the lungs, the number of transcripts associated with CD8+ T cells increased at 5 and 10 dpi in the 1×102 PFU-infected mice compared to non-infected controls, but not in the 1×105 PFU-infected mice at any time point (Supplementary Fig. 11). T cell activation was one of the GO terms for genes that displayed pattern B in the lungs of 1×102 PFU-infected mice (Supplementary Fig. 6B). Furthermore, our immunohistochemical analysis revealed a progressive and significant increase in CD8+ T cells in the lungs of mice infected with 1×102 PFU, as compared to mice infected with 1×105 PFU (Fig. 5A). To confirm this, we conducted flow cytometry experiments to determine the T cell fraction in 1×105 PFU-and 1×102 PFU-infected lungs (Fig. 5B and C, Supplementary Fig. 13). The results revealed that the total T cell proportion increased continuously from 5 to 14 dpi at 1×102 PFU, whereas no significant difference was observed in the total T cell composition of 1×105 PFU-infected lungs when compared to 0 dpi (Fig. 5B, Supplementary Fig. 13A). It also demonstrated that the proportion of CD8+ T cell portion in 1×102 PFU-infected lungs increased up to 2-fold from 2 to 14 dpi (Fig. 5C). In contrast, CD4+ T cell proportion in 1×102 PFU-infected lungs did not increase until 14 dpi (Supplementary Fig. 13B). After we confirmed the consistency between deconvolution result and flow cytometry data, we attempted to examine the specific expression of much more diverse marker genes associated with T cell in the 10 dpi of 1×102 PFU-infected lungs. We selected 28 marker genes related to T cell identification and profiling (20,21) and labeled 6 highly significant markers among them on volcano plots (Fig. 5D). Expression of granzyme B, which is detected at significantly higher frequencies in SARS-CoV-2–specific T cells of convalescent donors (21), was significantly upregulated at 10 dpi in the 1×102 PFU-infected mice lungs (Fig. 5D). The subsequent gene set enrichment analysis revealed that genes related to cytolytic effector CD8+ T cells (22) were highly enriched by SARS-CoV-2 infection at 10 dpi in the 1×102 PFU-infected mice lungs (Fig. 5E). In conclusion, the number of CD8+ T cell in the lungs increased continuously from 2 dpi by 1×102 PFU, but not by 1×105 PFU SARS-CoV-2.
Figure 5. Changes in CD8+ T cells and B cells in the lungs and spleens of SARS-CoV-2 infected mice.
(A) Immunohistochemistry for CD8+ T cells during the progression of infection. The graph depicts the number of CD8+ cells relative to total number of cells at 40× high power field (scale bars, 50 µm). (B, C) Flow cytometric analysis of total T cells (B) and CD8+ T cells (C) in SARS-CoV-2-infected lungs at 2, 5, 7, or 14 dpi with SARS-CoV-2 (left: 1×102 PFU, right: 1×105 PFU). A 0 dpi indicates naïve mice. Bars represent the relative proportion of T cells in each dpi relative to naïve mice (at least 2 independent experiments per group). (D) Volcano plots comparing total genes from lung samples collected at 10 dpi relative to 0 dpi at 1×102 PFU. Red indicates 28 genes that were related to T cell identification and profiling in the previous studies (21,22). The 6 most significant genes are labeled. (E) Gene set enrichment analysis for genes related to cytolytic CD8+ effector T cells (22). (F) Immune deconvolution results identifying B cell composition in the spleens. Bars represent mean ± SEM. (G) Flow cytometric analysis of B cells in SARS-CoV-2-infected spleens at 2, 5, 7, or 14 dpi with SARS-CoV-2 (left: 1×102 PFU, right: 1×105 PFU). A 0 dpi indicates naïve mice. Bars represent the relative proportion of B cells in each dpi relative to naïve mice (at least 2 independent experiments per group). (H) Volcano plots comparing total genes from spleen samples collected at 7 dpi relative to 0 dpi at 1×105 PFU. Red represents the 32 B cell markers utilized in the immune deconvolution analysis. The 6 most significant markers are labeled. (I) Gene set enrichment analysis for genes related to adaptive B2 lymphocytes (23).
Changes in the proportion of B cells were prominent among immune effectors in the spleens, whereas other immune cell types exhibited only minor variations (Fig. 5F, Supplementary Fig. 12). Specifically, the proportion of transcripts associated with B cells dropped precipitously at 7 dpi in the spleens of 1×105 PFU-infected mice (Fig. 5F). Throughout the time course, the number of transcripts associated with B cells in the 1×102 PFU-infected mice spleens did not differ significantly from that 1×105 PFU-infected mice spleens (Fig. 5F). Subsequent experimental quantification of B cell composition via flow cytometry corroborated deconvolution analysis results demonstrating a decrease in B cell fraction at 7 dpi in 1×105 PFU (Fig. 5G, Supplementary Fig. 14). Volcano plots confirmed that the expression of B cell marker genes in the spleens of 1×105 PFU-infected mice was lower at 7 dpi compared to non-infected controls (Fig. 5H). In addition, genes associated with adaptive B2 lymphocytes (23) demonstrated a significant negative enrichment in the 7 dpi spleen samples at 1×105 PFU (Fig. 5I). CD8+ T cells and B cells each responded differentially to various viral concentrations in the lungs and spleens.
Pulmonary fibrosis occurs as a sequela of low-dose SARS-CoV-2
Histopathological data demonstrated that fibrosis progressed in the lungs of mice infected with 1×102 PFU SARS-CoV-2 at 7 dpi (Fig. 2A and C). With 1×105 PFU, however, no pulmonary fibrosis was observed (Fig. 2B and D). Although clinical and transcriptome results indicated that the intense immune response exerted by infiltrating immune cells was predominant at both dosages, pulmonary fibrosis was only observed at the lower dose. For this reason, we further investigated the transcriptional changes in genes associated with pulmonary fibrosis over time. The expression of some fibrosis-associated genes reached its peak at 5 dpi in the lungs of mice infected with a viral dose of 1×102 PFU (Fig. 6A). At 7 dpi, most genes exhibited a moderate level of expression in the lungs. This expression of some fibrosis-related genes, such as Ccl2, Ccl3, Ccl4, Mt2, Plau and Timp1, remained consistent until 10 dpi after exposure to 1×102 PFU (Fig. 6A). In contrast, about half of genes were increased till 7 dpi at 1×105 PFU (Fig. 6A).
Figure 6. Genes associated with pulmonary fibrosis are upregulated by SARS-CoV-2 infection.
(A) Heatmaps for genes related to pulmonary fibrosis in the lungs (top: 1×105 PFU, bottom: 1×102 PFU). (B, C) Gene set enrichment analysis for genes associated with lung fibrosis using C2 gene sets from molecular signatures database (MsigDB) at 1×105 PFU (B) and at 1×102 PFU (C). (D) Gene set enrichment analysis of for genes associated with apoptosis using C2 gene sets from MsigDB (left: 7 dpi versus 0 dpi 1×105 PFU, right: 7 dpi versus 0 dpi 1×102 PFU).
We also examined the enrichment of lung fibrosis gene set from the Molecular Signatures Database. At 1×105 PFU, fibrosis-related genes were positively enriched at all time points (Fig. 6B). At 1×102 PFU, these genes began to be positively enriched from 5 to 10 dpi, and their expression decreased at 14 dpi (Fig. 6C). While fibrosis-related genes were found to be elevated at both 1×105 PFU and 1×102 PFU, the enrichment of apoptosis was only significant at 1×105 PFU (Fig. 6D). These results suggest that pulmonary fibrosis may be a comorbidity or complication associated with SARS-CoV-2 long-term infection.
DISCUSSION
In this study, we conducted a transcriptome analysis and flow cytometry to obtain insight into the dose-dependent host response to SARS-CoV-2 in lungs and spleens of K18-hACE2 mice. The results demonstrated that CD8+ T cells were increased in 1×102 PFU-infected lungs, whereas B cells were decreased in 1×105 PFU-infected spleens. In 1×102 PFU-infected lungs, pulmonary fibrosis and the upregulation of fibrotic genes were also observed.
Prior research involving the inoculation of ferrets with high (5×106 PFU), medium (5×104 PFU), and low (5×102 PFU) titers of SARS-CoV-2 revealed that the high- and medium-dose groups exhibited high pathology scores (10). In addition, mild multifocal bronchopneumonia was observed, particularly at 3 and 5 dpi, corroborating our results (10). In contrast to our findings, viral RNA was not detectable in the lungs of high- and medium-dose-infected ferrets (10). Our observation of pulmonary fibrosis at 1×102 PFU was the most significant difference between our histology data and the previous study report (10). In addition, no signs of pulmonary fibrosis were observed in the histopathology of animals infected with UV-inactivated SARS-CoV or SARS-CoV-2 in previous studies (24,25). Although fibrotic genes were increased in the lungs with a viral load of 1×105 PFU, it appeared that the initiation of apoptosis may have hindered the progression of pulmonary fibrosis at 7 dpi in mice infected with 1×105 SARS-CoV-2. Pulmonary fibrosis is a common complication in patients with COVID-19 (26) and developed in the post-discharge phase of more than one-third of the infected patients who survived severe COVID-19 pneumonia (27,28). Cytokine storms may have inflicted repetitive injuries on the alveolar epithelium. In addition to the massive cytokine secretion, an imbalance between proteases and their inhibitors may have contributed to the excessive accumulation of extracellular matrix during tissue reconstruction (29). The correlation between the severity of infection and pulmonary fibrosis is not fully understood. Nonetheless, our study on 1×102 PFU-infected mice demonstrating the occurrence of fibrosis suggests that persistent infection can leave permanent histological scars and further impede normal ventilatory function by decreasing the capacity for gas exchange.
Lung transcriptome profiles revealed that viral loads influenced the temporal variations. In particular, the expression of immunomodulatory mediators in the lungs of 1×102 PFU-infected mice was delayed by approximately 3 days. Prediction of immune effector types that infiltrate lungs provides insight into the mechanism that may help the host avoid lethality and manage survival at 1×102 PFU. After 2 dpi, CD8+ T cells increased in 1×102 PFU-infected lungs. Intriguingly, the enhanced regeneration of these effectors occurred 14 days after infection. This phenomenon is noteworthy because the recovery of immunocompetence following hematopoietic stress or injury is essential for effective pathogen responses (30).
1×105 PFU of SARS-CoV-2 induced diverse immune-related responses in the spleens. Notably, inflammation-related pathways were significantly upregulated during the late phase of infection in the spleens of mice infected with 1×105 PFU. Hyperinflammation may result from excessive stimulation of multiple inflammatory pathways. Despite the fact that the cascade of cytokine release eliminated the virus, tissue destruction and organ failure were inevitable. In contrast, at a lower dose, temporal change appeared negligible, as indicated by the small number of DEGs. At 7 dpi, the proportion of B cells was significantly reduced in the spleens of 1×105 PFU-infected mice. Continued B cell depletion compromises the adaptive immune response and the ability to produce neutralizing Abs, thereby exacerbating the severity of persistent COVID-19 in patients (31). A deficient B cell immune segment in the late period is indicative of severe spleen destruction at lethal virus concentrations.
Despite the fact that this study determined the dose-dependent host response of SARS-CoV-2-infected lungs and spleens in K18-hACE2 mice, the mortality fate of each 1×102 PFU-infected animal could not be predicted. Since we did not track animal survival and sacrificed them at specific time points for experiments, it is challenging to predict which mice were destined to die or survive based on early infection-stage clinical and transcriptome data.
Combining the aforementioned observations, we deduced that the 1×105 PFU virus concentration may have triggered irreversible organ failure in the lungs and spleens, resulting in death. At 1×102 PFU, however, recovery of activated defense mechanisms in the lungs to basal expression levels could have helped the host avoid death. The effects of compositional shifts in adaptive immune cell types at specific infection time points may also be associated with increased survival. However, animals that survive long-term infections may experience complications, such as fibrosis, following recovery.
ACKNOWLEDGEMENTS
This study was supported by the National Research Foundation of Korea (NRF) funded by the Korean government (MSIT) (2020M3A9D5A01082439 and 2018R1A5A2025079 to H.Y.G., 2016M3A9D5A01952416 to K.T.N, and Bio & Medical Technology Development Program 2021M3H9A1038083 to K.T.N).
Abbreviations
- COVID-19
coronavirus disease 2019
- DEG
differentially expressed gene
- dpi
days post-inoculation
- FDR
false discovery rate
- GO
Gene Ontology
- GSVA
gene set variation analysis
- PFU
plaque-forming unit
- RNA-seq
RNA-sequencing
- SARS-CoV-2
severe acute respiratory syndrome coronavirus 2
- TPM
transcripts per kilobase million
Footnotes
Conflict of Interest: The authors declare no potential conflicts of interest.
- Conceptualization: Seo JY, Nam KT, Seong JK.
- Data curation: Kim JA, Kim SH, Kim JJ, Noh H.
- Formal analysis: Kim JA, Kim SH, Kim JJ, Noh H.
- Investigation: Kim JA, Kim SH, Kim JJ, Noh H, Lee SB, Jeong H, Kim J, Jeon D, Seo JS, On D, Yoon S, Lee SG, Lee YW, Jang HJ, Park IH, Oh J, Seok SH, Lee YJ, Hong SM, An SH, Bae JY, Choi JA, Kim SY, Kim YB, Hwang JY, Lee HJ, Kim HB, Jeong DG, Song D, Song M, Park MS, Choi KS, Park JW, Yun JW, Shin JS, Lee HY, Kwon HK.
- Methodology: Kim JA, Kim SH, Kim JJ, Noh H.
- Project administration: Seo JY, Nam KT, Gee HY, Seong JK.
- Resources: Seo JY, Nam KT, Gee HY, Seong JK.
- Supervision: Seo JY, Nam KT, Gee HY, Seong JK.
- Validation: Kim JA, Kim SH, Kim JJ, Noh H.
- Writing - original draft: Kim JA, Kim SH, Gee HY.
- Writing- review & editing: Seo JY, Nam KT, Gee HY, Seong JK.
SUPPLEMENTARY MATERIALS
Reads statistics of RNA sequencing data
Reads statistics of RNA sequencing data
DEGs used in GO analysis in Fig. 3A and B
DEGs used in GO analysis in Fig. 3C and D
Principal component analysis of RNA-seq data of the lungs and spleens of mice infected with SARS-CoV-2 by dose. Box plots (left) indicate that normalized transcripts of all samples are equally distributed. Normalized TPM of 48,440 genes were used for analyses.
Principal component analysis of RNA-seq data of total samples.
Proportion of sequence reads that map to the SARS-CoV-2 viral genome. (A-B) The bar plots show the percentage of reads mapped to SARS-CoV-2 virus genome (GenBank: MN985325.1). Percentage of mapped reads was calculated by dividing counted fragments with total fragments aligned to the respective reference genome. Red represents non-infected controls, while black indicates infected samples.
Distribution of differentially expressing genes following the progression of infection. MA plots comparing the total genes in organs infected with 1×105 PFU- and 1×102 PFU. Yellow represents lung samples, while blue represents spleen samples. The transparent color indicates 1×102 PFU. Blue dots represent genes with the 5% FDR threshold. The number of blue dots is indicated.
Transcriptional changes in the lungs of K18-hACE2 transgenic mice infected with 1×105 PFU SARS-CoV-2. (A) Heatmap for 1,348 DEGs. DEGs were classified into 3 expression patterns. The gene expression levels in the heatmap are z-score normalized TPM values. (B-D) GO analysis of DEGs. After analyzing the GO category representing biological process and removing redundant terms, the top 15 GO terms were listed. The color and size of each dot represent p-value and gene ratio (gene counts in specific term/total genes), respectively.
Transcriptional changes in the lungs of K18-hACE2 transgenic mice infected with 1×102 PFU SARS-CoV-2. (A) Heatmap for 1,094 DEGs. DEGs were classified into 4 expression patterns. The gene expression levels in the heatmap are z-score normalized TPM values. (B-E) GO analysis of DEGs. After analyzing the GO category representing biological process and removing redundant terms, the top 15 GO terms were listed. The color and size of each dot represent p-value and gene ratio (gene counts in specific term/total genes), respectively.
Transcriptional alterations of immune-related genes in lungs induced by SARS-CoV-2 infection. Heatmaps of significantly upregulated genes associated with cytokine-mediated signaling pathway, type I interferon, and cellular response to IFN-γ. The gene sets are from a prior study (12). Top: 1×105 PFU-infected lungs; Bottom: 1×102 PFU-infected lungs. Rows represent genes, while columns represent samples. The gene expression levels in the heatmaps are z-score normalized TPM values.
Transcriptional changes in the spleen of K18-hACE2 transgenic mice infected with 1×105 PFU SARS-CoV-2. (A) Heatmap for 700 DEGs. DEGs were classified into 4 expression patterns. The gene expression levels in the heatmaps are z-score normalized TPM values. (B-E) GO analysis of DEGs. After analyzing the GO category representing biological process and removing redundant terms, the top 15 GO terms were listed. The color and size of each dot represent p-value and gene ratio (gene counts in specific term/total genes), respectively.
Transcriptional changes in the spleen of K18-hACE2 transgenic mice infected with 1×102 PFU SARS-CoV-2. (A) Heatmap for 49 DEGs. DEGs were classified into 2 expression patterns. The gene expression levels in the heatmaps are z-score normalized TPM values. (B-C) GO enrichment analysis of DEGs. After analyzing the GO category representing biological process and removing redundant terms, the top 15 GO terms were listed. The color and size of each dot represent p-value and gene ratio (gene counts in specific term/total genes), respectively.
Transcriptional alterations of immune-related genes in spleen induced by SARS-CoV-2-infection. Heatmaps of significantly upregulated genes associated with cytokine-mediated signaling pathway, type I interferon, and cellular response to IFN-γ. The gene sets are from a prior study (12). Top: 1×105 PFU-infected spleen; Bottom: 1×102 PFU-infected spleen. Rows represent genes, while columns represent samples. The gene expression levels in the heatmaps are z-score normalized TPM values.
Transcriptome-based immune cell quantification in the lungs of SARS-CoV-2-infected K18-hACE2 transgenic mice. Immune deconvolution was done using the immunedeconv to identify immune cell composition in the 1×105 PFU- and 1×102 PFU-infected lungs. Bars represent mean ± SEM. Dark gray: 1×105 PFU-infected lungs, Light gray: 1×102 PFU-infected lungs.
Transcriptome-based immune cell quantification in the spleen of SARS-CoV-2-infected K18-hACE2 transgenic mice. Immune deconvolution was done using the immunedeconv to identify immune cell composition in the 1×105 PFU- and 1×102 PFU-infected spleen. Bars represent mean ± SEM. Dark gray: 1×105 PFU-infected spleen, Light gray: 1×102 PFU-infected spleen.
Flow cytometry of T cell fraction in SARS-CoV-2-infected lungs. (A) Histograms of T cell fraction in lungs. Representative flow cytometric plots and frequencies of T cells (CD3+TCRb+) in lung tissues at 0, 2, 5, 7, or 14 dpi from SARS-CoV-2-infected K18-hACE2 mice (upper: 1 × 102 PFU, lower: 1× 105 PFU). At least 2 independent experiments per group. (B) Changes in CD4+ T cells in lungs during SAR2-CoV-2 infection. A 0 dpi indicates naïve mice.
Flow cytometry of B cell fraction in SARS-CoV-2-infected spleens. Representative flow cytometric plots and frequencies of B cells (CD19+TCRb−) in spleen tissues at 0, 2, 5, 7, or 14 dpi from SARS-CoV-2-infected K18-hACE2 mice. At least 2 independent experiments per group.
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Associated Data
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Supplementary Materials
Reads statistics of RNA sequencing data
Reads statistics of RNA sequencing data
DEGs used in GO analysis in Fig. 3A and B
DEGs used in GO analysis in Fig. 3C and D
Principal component analysis of RNA-seq data of the lungs and spleens of mice infected with SARS-CoV-2 by dose. Box plots (left) indicate that normalized transcripts of all samples are equally distributed. Normalized TPM of 48,440 genes were used for analyses.
Principal component analysis of RNA-seq data of total samples.
Proportion of sequence reads that map to the SARS-CoV-2 viral genome. (A-B) The bar plots show the percentage of reads mapped to SARS-CoV-2 virus genome (GenBank: MN985325.1). Percentage of mapped reads was calculated by dividing counted fragments with total fragments aligned to the respective reference genome. Red represents non-infected controls, while black indicates infected samples.
Distribution of differentially expressing genes following the progression of infection. MA plots comparing the total genes in organs infected with 1×105 PFU- and 1×102 PFU. Yellow represents lung samples, while blue represents spleen samples. The transparent color indicates 1×102 PFU. Blue dots represent genes with the 5% FDR threshold. The number of blue dots is indicated.
Transcriptional changes in the lungs of K18-hACE2 transgenic mice infected with 1×105 PFU SARS-CoV-2. (A) Heatmap for 1,348 DEGs. DEGs were classified into 3 expression patterns. The gene expression levels in the heatmap are z-score normalized TPM values. (B-D) GO analysis of DEGs. After analyzing the GO category representing biological process and removing redundant terms, the top 15 GO terms were listed. The color and size of each dot represent p-value and gene ratio (gene counts in specific term/total genes), respectively.
Transcriptional changes in the lungs of K18-hACE2 transgenic mice infected with 1×102 PFU SARS-CoV-2. (A) Heatmap for 1,094 DEGs. DEGs were classified into 4 expression patterns. The gene expression levels in the heatmap are z-score normalized TPM values. (B-E) GO analysis of DEGs. After analyzing the GO category representing biological process and removing redundant terms, the top 15 GO terms were listed. The color and size of each dot represent p-value and gene ratio (gene counts in specific term/total genes), respectively.
Transcriptional alterations of immune-related genes in lungs induced by SARS-CoV-2 infection. Heatmaps of significantly upregulated genes associated with cytokine-mediated signaling pathway, type I interferon, and cellular response to IFN-γ. The gene sets are from a prior study (12). Top: 1×105 PFU-infected lungs; Bottom: 1×102 PFU-infected lungs. Rows represent genes, while columns represent samples. The gene expression levels in the heatmaps are z-score normalized TPM values.
Transcriptional changes in the spleen of K18-hACE2 transgenic mice infected with 1×105 PFU SARS-CoV-2. (A) Heatmap for 700 DEGs. DEGs were classified into 4 expression patterns. The gene expression levels in the heatmaps are z-score normalized TPM values. (B-E) GO analysis of DEGs. After analyzing the GO category representing biological process and removing redundant terms, the top 15 GO terms were listed. The color and size of each dot represent p-value and gene ratio (gene counts in specific term/total genes), respectively.
Transcriptional changes in the spleen of K18-hACE2 transgenic mice infected with 1×102 PFU SARS-CoV-2. (A) Heatmap for 49 DEGs. DEGs were classified into 2 expression patterns. The gene expression levels in the heatmaps are z-score normalized TPM values. (B-C) GO enrichment analysis of DEGs. After analyzing the GO category representing biological process and removing redundant terms, the top 15 GO terms were listed. The color and size of each dot represent p-value and gene ratio (gene counts in specific term/total genes), respectively.
Transcriptional alterations of immune-related genes in spleen induced by SARS-CoV-2-infection. Heatmaps of significantly upregulated genes associated with cytokine-mediated signaling pathway, type I interferon, and cellular response to IFN-γ. The gene sets are from a prior study (12). Top: 1×105 PFU-infected spleen; Bottom: 1×102 PFU-infected spleen. Rows represent genes, while columns represent samples. The gene expression levels in the heatmaps are z-score normalized TPM values.
Transcriptome-based immune cell quantification in the lungs of SARS-CoV-2-infected K18-hACE2 transgenic mice. Immune deconvolution was done using the immunedeconv to identify immune cell composition in the 1×105 PFU- and 1×102 PFU-infected lungs. Bars represent mean ± SEM. Dark gray: 1×105 PFU-infected lungs, Light gray: 1×102 PFU-infected lungs.
Transcriptome-based immune cell quantification in the spleen of SARS-CoV-2-infected K18-hACE2 transgenic mice. Immune deconvolution was done using the immunedeconv to identify immune cell composition in the 1×105 PFU- and 1×102 PFU-infected spleen. Bars represent mean ± SEM. Dark gray: 1×105 PFU-infected spleen, Light gray: 1×102 PFU-infected spleen.
Flow cytometry of T cell fraction in SARS-CoV-2-infected lungs. (A) Histograms of T cell fraction in lungs. Representative flow cytometric plots and frequencies of T cells (CD3+TCRb+) in lung tissues at 0, 2, 5, 7, or 14 dpi from SARS-CoV-2-infected K18-hACE2 mice (upper: 1 × 102 PFU, lower: 1× 105 PFU). At least 2 independent experiments per group. (B) Changes in CD4+ T cells in lungs during SAR2-CoV-2 infection. A 0 dpi indicates naïve mice.
Flow cytometry of B cell fraction in SARS-CoV-2-infected spleens. Representative flow cytometric plots and frequencies of B cells (CD19+TCRb−) in spleen tissues at 0, 2, 5, 7, or 14 dpi from SARS-CoV-2-infected K18-hACE2 mice. At least 2 independent experiments per group.