Ethics statement
The virus isolation procedures in this study were approved by the Institutional Review Board of National Institute for Infectious Diseases (approval ID: 1178) and Tokyo Metropolitan Institute of Public Health (approval ID: 3KenKenKen-466) according to the Declaration of Helsinki 2013.
All experiments with hamsters were performed in accordance with the Science Council of Japan’s Guidelines for Proper Conduct of Animal Experiments. The protocols were approved by the Institutional Animal Care and Use Committee of National University Corporation Hokkaido University (approval numbers 20-0123 and 20-0060).
Epidemiological and viral sequence data of Omicron
The data of the 7-day average of new COVID-19 cases per day in South Africa and the UK by December 18, 2021 were downloaded from the Our World in Data (https://ourworldindata.org/covid-cases) on December 20, 2021. The numbers of Omicron sequences reported and the countries reported the Omicron sequences by December 24, 2021 (Extended Data Table 2) were obtained from outbreak.info (https://outbreak.info) on December 25, 2021
Estimation of viral transmissibility
We estimated the relative transmissibility of each SARS-CoV-2 lineage in South Africa (Fig. 1b) and the UK (Fig. 1d) according to the lineage dynamics determined by viral genomic surveillance data. The dynamics of five most predominant lineages in each country from January 1, 2021 to December 10, 2021 were analysed. For South Africa, the dynamics of Alpha (B.1.1.7), Beta (B.1.351), Delta (B.1.617.2 and AY lineages), Omicron (B.1.1.529, BA.1, and BA.2), and the C.1.2 lineage were used. For the UK, the dynamics of Alpha, Beta, Delta, Omicron, and the B.1.177 lineage (including its sublineages) were used.
We prepared the input data to estimate the relative transmissibility of each viral lineage for each country. The metadata of the sequenced SARS-CoV-2 strains (e.g., the collection date, collection place and PANGO lineage) were downloaded from the GISAID database (https://www.gisaid.org/) on December 20, 2021. The viral strains belonging to the lineages above were used for the following analysis. The number of isolated strains in each viral lineage in each day was counted and subsequently summarized in three-day bins. Finally, the count matrix representing the abundance of respective viral lineages (viral lineage ID k ∈ {1, 2, …, K}; K = 5) in respective time bins (t ∈ {1, 2, …, T}; T = 114) for each country was constructed.
We modelled the transition of the relative frequency of K types of viral lineages with a Bayesian multinomial logistic model as below:
![](data:image/png;base64,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)
Parameter estimation was performed by the framework of Bayesian statistical inference with Markov chain Monte Carlo methods (MCMC) implemented in Stan [CmdStan v2.28.1] (https://mc-stan.org). Non-informative priors were set for all parameters. Four independent MCMC chains were run with 2,000 and 3,000 steps of warmup and sampling iterations, respectively. We confirmed that all estimated parameters had <1.01 R-hat convergence diagnostic and >1,000 effective sampling size values, indicating that the MCMC runs were successfully convergent. The fitted model well reconstructed the observed data of the viral lineage dynamics in South Africa (R2 = 0.994; Extended Data Fig. 1b) and the UK (R2 = 0.99995; Extended Data Fig. 1d). The analyses above were performed in R v3.6.3.
Cell culture
HEK293 cells (a human embryonic kidney cell line; ATCC CRL-1573) and HEK293-ACE2/TMPRSS2 (HEK293 cells stably expressing human ACE2 and TMPRSS2)19 were maintained in Dulbecco’s modified Eagle's medium (DMEM) (high glucose) (Wako, Cat# 044-29765) containing 10% foetal bovine serum (FBS) and 1% penicillin-streptomycin (PS). A549 (a human lung epithelial cell line; ATCC CCL-185) and A549-ACE2 cells (A549 cells stably expressing human ACE2)19 were maintained in Ham’s F-12K medium (Wako, Cat# 080-08565) containing 10% FBS and 1% PS. Vero cells [an African green monkey (Chlorocebus sabaeus) kidney cell line; JCRB0111] were maintained in Eagle’s minimum essential medium (EMEM) (Wako, Cat# 051-07615) containing 10% FBS and 1% PS. VeroE6/TMPRSS2 cells (VeroE6 cells stably expressing human TMPRSS2)40 were maintained in DMEM (low glucose) (Wako, Cat# 041-29775) containing 10% FBS, G418 (1 mg/ml; Nacalai Tesque, Cat# G8168-10ML) and 1% PS. Calu-3 cells (a human lung epithelial cell line; ATCC HTB-55) were maintained in EMEM (Sigma-Aldrich, Cat# M4655-500ML) containing 10% FBS and 1% PS. Calu-3/DSP1-7 cells (Calu-3 cells stably expressing DSP1-7 cells)41 was maintained in EMEM (Wako, Cat# 056-08385) supplemented with 20% FBS and 1% PS. HeLa-ACE2/TMPRSS2 cells (HeLa cells stably expressing human ACE2 and TMPRSS2)42 were maintained in DMEM (low glucose) (Wako, Cat# 041-29775) containing 10% FBS, G418 (1 mg/ml; Nacalai Tesque, Cat# G8168-10ML) and 1% PS.
SARS-CoV-2 preparation and titration
To isolate an Omicron variant (BA.1 lineage, strain TY38-873; GISAID ID: EPI_ISL_7418017), saliva was collected from a traveller arrived at Japan, and RT-qPCR testing for SARS-CoV-2 was performed in an airport quarantine station, Japan. The sample was subjected to whole genome sequencing based on a modified ARTIC Network protocol43, and the near full-length SARS-CoV-2 genome sequence was deposited in GISAID (GISAID ID: EPI_ISL_6913953). Virus isolation was performed as previously described40. In brief, the saliva was inoculated into VeroE6/TMPRSS2 cells and cytopathic effect (CPE) was observed 4 d after inoculation. Then, the supernatant was harvested and stored at –80°C as an original virus (GISAID ID: EPI_ISL_7418017). After one more passage in VeroE6/TMPRSS2 cells, the virus was obtained from National Institute of Infectious Diseases, Japan. An early pandemic D614G-bearing isolate (B.1.1 lineage, strain TKYE610670; GISAID ID: EPI_ISL_479681) and a Delta isolate (B.1.617.2 lineage, strain TKYTK1734; GISAID ID: EPI_ISL_2378732) were used in the previous study2.
Virus preparation and titration was performed as previously described2,19. To prepare the working virus stock, 100 μl of the seed virus was inoculated into VeroE6/TMPRSS2 cells (5 × 106 cells in a T-75 flask). One hour after infection, the culture medium was replaced with DMEM (low glucose) (Wako, Cat# 041-29775) containing 2% FBS and 1% PS. At 3 d.p.i., the culture medium was harvested and centrifuged, and the supernatants were collected as the working virus stock. The viral genome sequences of working viruses were verified as described below.
The titre of the prepared working virus was measured as the 50% tissue culture infectious dose (TCID50). Briefly, one day before infection, VeroE6/TMPRSS2 cells (10,000 cells) were seeded into a 96-well plate. Serially diluted virus stocks were inoculated into the cells and incubated at 37°C for 4 d. The cells were observed under microscopy to judge the CPE appearance. The value of TCID50/ml was calculated with the Reed–Muench method44.
SARS-CoV-2 infection
One day before infection, Vero cells (10,000 cells), VeroE6/TMPRSS2 cells (10,000 cells), Calu-3 cells (10,000 cells), HeLa-ACE2/TMPRSS2 cells (10,000 cells), A549-ACE2 cells (10,000 cells) and A549 cells (10,000 cells) were seeded into a 96-well plate. SARS-CoV-2 (1,000 or 100 TCID50) was inoculated and incubated at 37°C for 1 h. The infected cells were washed, and 180 µl of culture medium was added. The culture supernatant (10 µl) was harvested at the indicated time points and used for RT–qPCR to quantify the viral RNA copy number (see below). To monitor the syncytium formation in infected cell culture, bright-field photos were obtained using an All-in-One Fluorescence Microscope BZ-X800 (Keyence).
Immunofluorescence staining
Immunofluorescence staining was performed as previously described2. Briefly, one day before infection, VeroE6/TMPRSS2 cells (10,000 cells) were seeded into 96-well, glass bottom, black plates and infected with SARS-CoV-2 (100 TCID50). At 24 h.p.i., the cells were fixed with 4% paraformaldehyde in phosphate-buffered saline (PBS) (Nacalai Tesque, Cat# 09154-85) for 1 h at 4°C. The fixed cells were permeabilized with 0.2% Triton X-100 in PBS for 1 h, blocked with 10% FBS in PBS for 1 h at 4°C. The fixed cells were then stained using rabbit anti-SARS-CoV-2 N polyclonal antibody (GeneTex, Cat# GTX135570, 1:1,000) for 1 h. After washing three times with PBS, cells were incubated with an Alexa 488-conjugated anti-rabbit IgG antibody (Thermo Fisher Scientific, Cat# A-11008, 1:1,000) for 1 h. Nuclei were stained with DAPI (Thermo Fisher Scientific, Cat# 62248). Fluorescence microscopy was performed on an All-in-One Fluorescence Microscope BZ-X800 (Keyence).
Plaque Assay
Plaque assay was performed as previously described2,19. Briefly, one day before infection, VeroE6/TMPRSS2 cells (100,000 cells) were seeded into a 24-well plate and infected with SARS-CoV-2 (10,000 TCID50) at 37°C. At 2 h.p.i, mounting solution containing 3% FBS and 1.5% carboxymethyl cellulose (Wako, Cat# 039-01335) was overlaid, followed by incubation at 37°C. At 3 d.p.i., the culture medium was removed, and the cells were washed with PBS three times and fixed with 4% paraformaldehyde phosphate (Nacalai Tesque, Cat# 09154-85). The fixed cells were washed with tap water, dried, and stained with staining solution [0.1% methylene blue (Nacalai Tesque, Cat# 22412-14) in water] for 30 m. The stained cells were washed with tap water and dried, and the size of plaques was measured using ImageJ.
RT–qPCR
RT–qPCR was performed as previously described2,19. Briefly, 5 μl of culture supernatant was mixed with 5 μl of 2 × RNA lysis buffer [2% Triton X-100, 50 mM KCl, 100 mM Tris-HCl (pH 7.4), 40% glycerol, 0.8 U/μl recombinant RNase inhibitor (Takara, Cat# 2313B)] and incubated at room temperature for 10 min. RNase-free water (90 μl) was added, and the diluted sample (2.5 μl) was used as the template for real-time RT-PCR performed according to the manufacturer’s protocol using the One Step TB Green PrimeScript PLUS RT-PCR kit (Takara, Cat# RR096A) and the following primers: Forward N, 5'-AGC CTC TTC TCG TTC CTC ATC AC-3'; and Reverse N, 5'-CCG CCA TTG CCA GCC ATT C-3'. The viral RNA copy number was standardized with a SARS-CoV-2 direct detection RT-qPCR kit (Takara, Cat# RC300A). Fluorescent signals were acquired using a QuantStudio 3 Real-Time PCR system (Thermo Fisher Scientific), a CFX Connect Real-Time PCR Detection system (Bio-Rad), an Eco Real-Time PCR System (Illumina), a qTOWER3 G Real-Time System (Analytik Jena) or a 7500 Real Time PCR System (Applied Biosystems).
Plasmid construction
Plasmids expressing the SARS-CoV-2 S proteins of the D614G-bearing early pandemic SARS-CoV-2 (pC-SARS2-S D614G) and Delta (pC-SARS2-S Delta) were prepared in our previous study2,19. A plasmid expressing the SARS-CoV-2 Omicron S protein (pC-SARS2-S Omicron) was generated by overlap extension PCR using pC-SARS2-S D614G2,19 and pC-SARS2-S Alpha2 as the templates and the primers listed in Supplementary Table 1. The resulting PCR fragment was digested with KpnI and NotI and inserted into the KpnI-NotI site of the pCAGGS vector45.
SARS-CoV-2 S-based fusion assay
The SARS-CoV-2 S-based fusion assay was performed as previously described2,19. This assay utilizes a dual split protein (DSP) encoding Renilla luciferase (RL) and GFP genes; the respective split proteins, DSP8-11 and DSP1-7, are expressed in effector and target cells by transfection. Briefly, on day 1, effector cells (i.e., S-expressing cells) and target cells (see below) were prepared at a density of 0.6–0.8 × 106 cells in a 6-well plate. To prepare effector cells, HEK293 cells were cotransfected with the S expression plasmids (400 ng) and pDSP8-11 (400 ng) using TransIT-LT1 (Takara, Cat# MIR2300). To prepare target cells, HEK293 cells were cotransfected with pC-ACE2 (200 ng) and pDSP8-11 (400 ng). Target HEK293 cells in selected wells were cotransfected with pC-TMPRSS2 (40 ng) in addition to the plasmids above. VeroE6/TMPRSS2 cells were transfected with pDSP1-7 (400ng). On day 3 (24 h.p.i), 16,000 effector cells were detached and reseeded into 96-well black plates (PerkinElmer, Cat# 6005225), and target cells (HEK293, VeroE6/TMPRSS2 or Calu-3/DSP1-7 cells) were reseeded at a density of 1,000,000 cells/2 ml/well in 6-well plates. On day 4 (48 h.p.i.), target cells were incubated with EnduRen live cell substrate (Promega, Cat# E6481) for 3 h and then detached, and 32,000 target cells were added to a 96-well plate with effector cells. RL activity was measured at the indicated time points using a Centro XS3 LB960 (Berthhold Technologies). To measure the surface expression level of S protein, effector cells were stained with rabbit anti-SARS-CoV-2 S S1/S2 polyclonal antibody (Thermo Fisher Scientific, Cat# PA5-112048, 1:100) or mouse anti-SARS-CoV-2 S monoclonal antibody (clone 1A9, GeneTex, Cat# GTX632604, 1:100). Normal rabbit IgG (SouthernBiotech, Cat# 0111-01, 1:100) or purified mouse IgG1 isotype control antibody (clone MG1-45, BioLegend, Cat# 401401, 1:100) or was used as negative controls, and APC-conjugated goat anti-mouse or rabbit IgG polyclonal antibody (Jackson ImmunoResearch, Cat# 115-136-146, 1:50 or Cat# 111-136-144, 1:50) was used as a secondary antibody. Surface expression level of S proteins was analysed using FACS Canto II (BD Biosciences) and FlowJo software v10.7.1 (BD Biosciences). Gating strategy for flow cytometry is shown in Supplementary Fig. 1. RL activity was normalized to the MFI of surface S proteins, and the normalized values are shown as fusion activity.
Coculture experiment
One day before transfection, effector cells (i.e., S-expressing cells) were seeded on the cover glass put in 12-well plate, and target HEK293-ACE2/TMPRSS2 cells were prepared at a density of 1.0 x 105 cells in a 12 well plate. To prepare effector cell, HEK293 cells were cotransfected with the expression plasmids for the parental D614G S, Delta S, Omicron S (500 ng) and pEGFP-C1 (500 ng) using PEI Max (Polysciences, Cat# 24765-1). To prepare target cells, HEK293 cells and HEK293-ACE2/TMPRSS2 cells were transfected with pmCherry-C1 (1000 ng). At 24 h post-transfection, target cells were detached and cocultured with effector cells. At 24 h post-coculture (at 48 h post-transfection), cells were fixed with 4% paraformaldehyde in PBS (Nacalai Tesque, cat# 09154-85) for 15 m at room temperature. Nuclei were stained with Hoechst 33342 (Thermo Fisher Scientific, Cat# H3570). The coverslips were mounted on glass slides using Fluoromount-G (Southern Biotechnology, Cat# 0100-01) with Hoechst 33342 and observed using an A1Rsi confocal microscope (Nikon). The size of syncytium (yellow area) was measured using Fiji software v2.0.0-rc-69/1.52p (ImageJ)46.
Western blot
Western blotting was performed as previously described2,19. To quantify the level of the cleaved S2 protein in the cells, the harvested cells were washed and lysed in lysis buffer [25 mM HEPES (pH 7.2), 20% glycerol, 125 mM NaCl, 1% Nonidet P40 substitute (Nacalai Tesque, Cat# 18558-54), protease inhibitor cocktail (Nacalai Tesque, Cat# 03969-21)]. After quantification of total protein by protein assay dye (Bio-Rad, Cat# 5000006), lysates were diluted with 2 × sample buffer [100 mM Tris-HCl (pH 6.8), 4% SDS, 12% β-mercaptoethanol, 20% glycerol, 0.05% bromophenol blue] and boiled for 10 m. Then, 10 μl samples (50 μg of total protein) were subjected to Western blotting. To quantify the level of the cleaved S2 protein in the virions, 900 μl of the culture medium containing the pseudoviruses was layered onto 500 μl of 20% sucrose in PBS and centrifuged at 20,000 × g for 2 h at 4°C. Pelleted virions were resuspended in 1× NuPAGE LDS sample buffer (Thermo Fisher Scientific, Cat# NP0007) containing 2% β-mercaptoethanol, and the lysed virions were subjected to Western blotting. For protein detection, the following antibodies were used: mouse anti-SARS-CoV-2 S monoclonal antibody (clone 1A9, GeneTex, Cat# GTX632604, 1:10,000), rabbit anti-SARS-CoV-2 N monoclonal antibody (clone HL344, GeneTex, Cat# GTX635679, 1:5,000), rabbit anti-beta actin (ACTB) monoclonal antibody (clone 13E5, Cell Signalling, Cat# 4970, 1:5,000), mouse anti-alpha tubulin (TUBA) monoclonal antibody (clone DM1A, Sigma-Aldrich, Cat# T9026, 1:10,000), horseradish peroxidase (HRP)-conjugated donkey anti-rabbit IgG polyclonal antibody (Jackson ImmunoResearch, Cat# 711-035-152, 1:10,000) and HRP-conjugated donkey anti-mouse IgG polyclonal antibody (Jackson ImmunoResearch, Cat# 715-035-150, 1:10,000). Chemiluminescence was detected using SuperSignal West Femto Maximum Sensitivity Substrate (Thermo Fisher Scientific, Cat# 34095) or Western BLoT Ultra Sensitive HRP Substrate (Takara, Cat# T7104A) according to the manufacturers’ instructions. Bands were visualized using an Amersham Imager 600 (GE Healthcare), and the band intensity was quantified using Image Studio Lite v5.2 (LI-COR Biosciences) or ImageJ v2.2.0. Uncropped blots are shown in Supplementary Fig. 2.
Animal experiments
Syrian hamsters (male, 4 weeks old) were purchased from Japan SLC Inc. (Shizuoka, Japan). Baseline body weights were measured before infection. For the virus infection experiments, hamsters were euthanized by intramuscular injection of a mixture of 0.15 mg/kg medetomidine hydrochloride (Domitor®, Nippon Zenyaku Kogyo), 2.0 mg/kg midazolam (Dormicum®, FUJIFILM Wako Chemicals) and 2.5 mg/kg butorphanol (Vetorphale®, Meiji Seika Pharma). The B.1.1 virus, Delta or Omicron (104 TCID50 in 100 µl) were intranasally infected under anaesthesia. Oral swabs were daily collected under anaesthesia with isoflurane (Sumitomo Dainippon Pharma). Body weight, enhanced pause (Penh, see below) and subcutaneous oxygen saturation (SpO2, see below) were monitored at 1, 3, 5 and 7 d.p.i. Lung tissues were collected at 1, 3, 5 and 7 d.p.i, and viral RNA levels in lung tissues were determined by qRT-PCR. These tissues were also used for histopathological analysis (see below).
Histopathological analysis
Histopathological analysis was performed as described in the previous study2. Briefly, excised animal tissues were fixed with 4% paraformaldehyde in PBS, and processed for paraffin embedding. The paraffin blocks were sectioned with 3-µm-thickness and then mounted on silane-coated glass slides (MAS-GP, Matsunami). H&E staining was performed according to a standard protocol. For IHC, an Autostainer Link 48 (Dako) was utilized. The deparaffinized sections were exposed to EnVision FLEX target retrieval solution high pH (Agilent, Cat# K8004) for 20 m at 97°C to activate, and a mouse anti-SARS-CoV-2 N monoclonal antibody (R & D systems, Clone 1035111, Cat# MAB10474-SP, 1:400) was used as a primary antibody. The sections were sensitized using EnVision FLEX (Agilent) for 15 m and visualised by peroxidase-based enzymatic reaction with 3,3’-diaminobenzidine tetrahydrochloride as substrate for 5 m.
Histopathological scoring of lung lesion
Histopathological scoring was performed as described in the previous study2. Briefly, pathological features including bronchitis or bronchiolitis, hemorrhage or congestion, alveolar damage with epithelial apoptosis and macrophage infiltration, presence of type II pneumocytes, and the area of the presence of large type II pneumocytes were evaluated by certified pathologists and the degree of these pathological findings were arbitrarily scored using four-tiered system as 0 (negative), 1 (weak), 2 (moderate), and 3 (severe). Total histopathological score is the sum of these five indices.
Lung function test
Respiratory parameters were measured by using a whole-body plethysmography system (DSI) according to the manufacturer's instructions. In brief, a hamster was placed in an unrestrained plethysmography chamber and allowed to acclimatize for 30 s, then, data were acquired over a 3-m period by using FinePointe Station and Review softwares v2.9.2.12849 (STARR). The state of oxygenation was examined by measuring percutaneous oxygen saturation (SpO2) using pulse oximeter, MouseOx PLUS (STARR). SpO2 was measured by attaching a measuring chip to the neck of hamsters sedated by sedated by 0.25 mg/kg medetomidine hydrochloride.
Viral genome sequencing analysis
The sequences of the working viruses were verified by viral RNA-sequencing analysis. Viral RNA was extracted using QIAamp viral RNA mini kit (Qiagen, Cat# 52906). The sequencing library for total RNA-sequencing was prepared using NEB Next Ultra RNA Library Prep Kit for Illumina (New England Biolabs, Cat# E7530). Paired-end, 150-bp sequencing was performed using MiSeq (Illumina) with MiSeq reagent kit v3 (Illumina, Cat# MS-102-3001). Sequencing reads were trimmed using fastp v0.21.047 and subsequently mapped to the viral genome sequences of a lineage A isolate (strain WK-521; GISIAD ID: EPI_ISL_408667)40 using BWA-MEM v0.7.1748. Variant calling, filtering, and annotation were performed using SAMtools v1.949 and snpEff v5.0e50.
For the clinical isolates [an Omicron isolate (strain TY38-873; GISAID ID: EPI_ISL_7418017), a Delta isolate (strain TKYTK1734; GISAID ID: EPI_ISL_2378732)2 and a D614G-bearing B.1.1 isolate (strain TKYE610670; GISAID ID: EPI_ISL_479681)2], the detected variants that are present in the original sequences were excluded. Information on the detected mutations is summarized in Supplementary Table 2.
Statistics and reproducibility
Statistical significance was tested using a two-sided Student's t-test or a two-sided Mann–Whitney U-test unless otherwise noted. The tests above were performed using Excel software v16.16.8 (Microsoft) or Prism 9 software v9.1.1 (GraphPad Software).
In the time-course experiments using hamsters (Fig. 3h), to evaluate the difference between experimental conditions thorough all over timepoints, a multiple regression analysis including experimental conditions as explanatory variables and timepoints as qualitative control variables was performed. The P value was calculated by a two-sided Wald test. Subsequently, family-wise error rates were calculated by Holm method. The analyses above were performed in R v3.6.3.
In Fig. 3e–3g, photographs shown are the representative areas of two independent experiments by using 3 hamsters at each timepoint. In Fig. 2b–2d and Extended Data Fig. 3, 4b, assays were performed in triplicate. Photographs shown are the representatives of 20 fields of view taken for each sample.