21.
1.
2.
3.
WHO. Tracking SARS-CoV-2 variants (March 30, 2023) https://
www.who.int/en/activities/tracking-SARS-CoV-2-variants.
(2022).
Ito, J. et al. Convergent evolution of the SARS-CoV-2 Omicron
subvariants leading to the emergence of BQ.1.1 variant. Nat. Commun. 14, 2671 (2023).
Focosi, D., Quiroga, R., McConnell, S. A., Johnson, M. C. & Casadevall, A. Convergent evolution in SARS-CoV-2 Spike creates a
variant soup that causes new COVID-19 waves. BioRxiv, (2022)
https://doi.org/10.1101/2022.1112.1105.518843.
Nature Communications | (2023)14:2800
22.
23.
24.
Tuekprakhon, A. et al. Antibody escape of SARS-CoV-2 Omicron
BA.4 and BA.5 from vaccine and BA.1 serum. Cell 185, 2422–2433
(2022). e2413.
Kimura, I. et al. Virological characteristics of the novel SARS-CoV-2
Omicron variants including BA.4 and BA.5. Cell 185, 3992–4007
(2022). e3916.
Makowski, E. K., Schardt, J. S., Smith, M. D. & Tessier, P. M. Mutational analysis of SARS-CoV-2 variants of concern reveals key tradeoffs between receptor affinity and antibody escape. PLoS
Comput. Biol. 18, e1010160 (2022).
Aggarwal, A. et al. Mechanistic insights into the effects of key
mutations on SARS-CoV-2 RBD-ACE2 binding. Phys. Chem. Chem.
Phys. 23, 26451–26458 (2021).
Deshpande, A., Harris, B. D., Martinez-Sobrido, L., Kobie, J. J. &
Walter, M. R. Epitope classification and RBD binding properties of
neutralizing antibodies against SARS-CoV-2 variants of concern.
Front Immunol 12, 691715 (2021).
Chen, J., Wang, R., Wang, M. & Wei, G. W. Mutations strengthened
SARS-CoV-2 infectivity. J. Mol. Biol 432, 5212–5226 (2020).
Saito, A. et al. Virological characteristics of the SARS-CoV-2 Omicron BA.2.75 variant. Cell Host Microbe 30, 1540–1555
(2022). e1515.
Qu, P. et al. Evasion of neutralizing antibody responses by the SARSCoV-2 BA.2.75 variant. Cell Host Microbe 30, 1518–1526
(2022). e1514.
Arora, P. et al. Omicron sublineage BQ.1.1 resistance to monoclonal
antibodies. Lancet Infect. Dis. https://doi.org/10.1016/S14733099(22)00733-2 (2022).
Cao, Y. et al. Imprinted SARS-CoV-2 humoral immunity induces
convergent Omicron RBD evolution. Nature 614, 521–529 (2023).
Wang, Q. et al. Antibody evasion by SARS-CoV-2 Omicron subvariants BA.2.12.1, BA.4, & BA.5. Nature https://doi.org/10.1038/
s41586-022-05053-w (2022).
Cao, Y. et al. BA.2.12.1, BA.4 and BA.5 escape antibodies elicited by
Omicron infection. Nature https://doi.org/10.1038/s41586-02204980-y (2022).
GitHub. BJ.1/BM.1.1.1 (=BA.2.75.3.1.1.1) recombinant with breakpoint
in S1 [> = 5 sequences, 3x Singapore, 2x US as of 2022-09-12]
(September 13, 2022). https://github.com/cov-lineages/pangodesignation/issues/1058. (2022).
WHO. TAG-VE statement on Omicron sublineages BQ.1 and XBB
(October 27, 2022) https://www.who.int/news/item/27-10-2022tag-ve-statement-on-omicron-sublineages-bq.1-and-xbb. (2022).
Wang, Q. et al. Antigenic characterization of the SARS-CoV-2
Omicron subvariant BA.2.75. Cell Host Microbe 30, 1512–1517
(2022). e1514.
Martin, D. P. et al. RDP5: a computer program for analyzing
recombination in, and removing signals of recombination from,
nucleotide sequence datasets. Virus Evol 7, veaa087 (2021).
GitHub. BE.1.1.1 sublineage with Orf1b:Y264H and S:N460K
(69 sequences) emerged in Nigeria (14 seqs) (August 26, 2022).
https://github.com/cov-lineages/pango-designation/issues/
993. (2022).
Smith, D. J. et al. Mapping the antigenic and genetic evolution of
influenza virus. Science 305, 371–376 (2004).
Dejnirattisai, W. et al. SARS-CoV-2 Omicron-B.1.1.529 leads to
widespread escape from neutralizing antibody responses. Cell 185,
467–484 (2022). e415.
Zahradnik, J. et al. SARS-CoV-2 variant prediction and antiviral drug
design are enabled by RBD in vitro evolution. Nat. Microbiol 6,
1188–1198 (2021).
Motozono, C. et al. SARS-CoV-2 spike L452R variant evades cellular
immunity and increases infectivity. Cell Host Microbe 29,
1124–1136 (2021).
16
Article
25. Suzuki, R. et al. Attenuated fusogenicity and pathogenicity of SARSCoV-2 Omicron variant. Nature 603, 700–705 (2022).
26. Saito, A. et al. Enhanced fusogenicity and pathogenicity of SARSCoV-2 Delta P681R mutation. Nature 602, 300–306 (2022).
27. Yamasoba, D. et al. Virological characteristics of the SARS-CoV-2
Omicron BA.2 spike. Cell 185, 2103–2115 (2022). e2119.
28. Nasser, H. et al. Monitoring fusion kinetics of viral and target cell
membranes in living cells using a SARS-CoV-2 spike-proteinmediated membrane fusion assay. STAR Protoc. 3, 101773 (2022).
29. Kimura, I. et al. The SARS-CoV-2 spike S375F mutation characterizes
the Omicron BA.1 variant. iScience 25, 105720 (2022).
30. Cao, Y. et al. Characterization of the enhanced infectivity and antibody evasion of Omicron BA.2.75. Cell Host Microbe 30, 1527–1539
(2022). e1525.
31. Stalls, V. et al. Cryo-EM structures of SARS-CoV-2 Omicron
BA.2 spike. Cell Rep. 39, 111009 (2022).
32. Mannar, D. et al. SARS-CoV-2 Omicron variant: Antibody evasion
and cryo-EM structure of spike protein-ACE2 complex. Science 375,
760–764 (2022).
33. Lan, J. et al. Structure of the SARS-CoV-2 spike receptor-binding
domain bound to the ACE2 receptor. Nature 581, 215–220 (2020).
34. Shang, J. et al. Structural basis of receptor recognition by SARSCoV-2. Nature 581, 221–224 (2020).
35. Han, P. et al. Receptor binding and complex structures of human
ACE2 to spike RBD from omicron and delta SARS-CoV-2. Cell
https://doi.org/10.1016/j.cell.2022.01.001 (2022).
36. Li, L. et al. Structural basis of human ACE2 higher binding affinity to
currently circulating Omicron SARS-CoV-2 sub-variants BA.2 and
BA.1.1. Cell 185, 2952–2960 (2022). e2910.
37. Hashimoto, R. et al. SARS-CoV-2 disrupts the respiratory vascular
barrier by suppressing Claudin-5 expression. Sci Adv 8,
eabo6783 (2022).
38. Tamura, T. et al. Comparative pathogenicity of SARS-CoV-2 Omicron subvariants including BA.1, BA.2, and BA.5. BioRxiv, (2022)
https://doi.org/10.1101/2022.1108.1105.502758.
39. Halfmann, P. J. et al. SARS-CoV-2 Omicron virus causes attenuated
disease in mice and hamsters. Nature https://doi.org/10.1038/
s41586-022-04441-6 (2022).
40. Uriu, K. et al. Enhanced transmissibility, infectivity, and immune
resistance of the SARS-CoV-2 omicron XBB.1.5 variant. Lancet Infect
Dis. 23, 280–281 (2023).
41. Yue, C. et al. ACE2 binding and antibody evasion in enhanced
transmissibility of XBB.1.5. Lancet Infect Dis. 23, 278–280 (2023).
42. Wang, Q. et al. Alarming antibody evasion properties of rising SARSCoV-2 BQ and XBB subvariants. Cell 186, 279–286 (2023). e278.
43. Mykytyn, A. Z. et al. Antigenic mapping of emerging SARS-CoV-2
omicron variants BM.1.1.1, BQ.1.1, and XBB.1. Lancet Microbe https://
doi.org/10.1016/S2666-5247(22)00384-6 (2023).
44. Miller, J. et al. Substantial Neutralization Escape by SARS-CoV-2
Omicron Variants BQ.1.1 and XBB.1. N. Engl. J. Med. 388,
662–664 (2023).
45. Arora, P. et al. Neutralisation sensitivity of the SARS-CoV-2 XBB.1
lineage. Lancet Infect Dis. 23, 147–148 (2023).
46. Shen, L. et al. Rapidly emerging SARS-CoV-2 B.1.1.7 sub-lineage in
the United States of America with spike protein D178H and membrane protein V70L mutations. Emerg Microbes Infect. 10,
1293–1299 (2021).
47. Zhang, L. et al. The significant immune escape of pseudotyped
SARS-CoV-2 variant Omicron. Emerg Microbes Infect. 11, 1–5 (2022).
48. Uriu, K. et al. Neutralization of the SARS-CoV-2 Mu variant by convalescent and vaccine serum. N. Engl. J. Med. 385,
2397–2399 (2021).
49. Uriu, K. et al. Characterization of the immune resistance of SARSCoV-2 Mu variant and the robust immunity induced by Mu infection.
J. Infect. Dis. https://doi.org/10.1093/infdis/jiac053 (2022).
Nature Communications | (2023)14:2800
https://doi.org/10.1038/s41467-023-38435-3
50. Cerutti, G. et al. Potent SARS-CoV-2 neutralizing antibodies directed against spike N-terminal domain target a single supersite. Cell
Host Microbe 29, 819–833 (2021). e817.
51. Sasaki, A., Lion, S. & Boots, M. Antigenic escape selects for the
evolution of higher pathogen transmission and virulence. Nat. Ecol.
Evol. 6, 51–62 (2022).
52. Ozono, S. et al. SARS-CoV-2 D614G spike mutation increases entry
efficiency with enhanced ACE2-binding affinity. Nat. Commun 12,
848 (2021).
53. Ferreira, I. et al. SARS-CoV-2 B.1.617 mutations L452R and E484Q
are not synergistic for antibody evasion. J. Infect. Dis. 224,
989–994 (2021).
54. Reeves, P. J., Callewaert, N., Contreras, R. & Khorana, H. G. Structure and function in rhodopsin: high-level expression of rhodopsin
with restricted and homogeneous N-glycosylation by a
tetracycline-inducible N-acetylglucosaminyltransferase I-negative
HEK293S stable mammalian cell line. Proc. Natl. Acad. Sci. USA 99,
13419–13424 (2002).
55. Matsuyama, S. et al. Enhanced isolation of SARS-CoV-2 by TMPRSS2expressing cells. Proc. Natl. Acad. Sci. USA 117, 7001–7003 (2020).
56. Fujita, S. et al. Structural Insight into the resistance of the SARSCoV-2 Omicron BA.4 and BA.5 variants to Cilgavimab. Viruses 14,
2677 (2022).
57. Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one
FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).
58. Li, H. & Durbin, R. Fast and accurate short read alignment with
Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
59. Li, H. et al. The sequence alignment/map format and SAMtools.
Bioinformatics 25, 2078–2079 (2009).
60. Cingolani, P. et al. A program for annotating and predicting the
effects of single nucleotide polymorphisms, SnpEff: SNPs in the
genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly
(Austin) 6, 80–92 (2012).
61. Lanfear, R. A global phylogeny of SARS-CoV-2 sequences from
GISAID. Zenodo https://doi.org/10.5281/zenodo.3958883. https://
zenodo.org/record/4289383#.Y6ER8C33ITs (2020).
62. Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment
software version 7: improvements in performance and usability.
Mol. Biol. Evol. 30, 772–780 (2013).
63. Martin, D. & Rybicki, E. RDP: detection of recombination amongst
aligned sequences. Bioinformatics 16, 562–563 (2000).
64. Padidam, M., Sawyer, S. & Fauquet, C. M. Possible emergence of
new geminiviruses by frequent recombination. Virology 265,
218–225 (1999).
65. Posada, D. & Crandall, K. A. Evaluation of methods for detecting
recombination from DNA sequences: computer simulations. Proc.
Natl. Acad. Sci. USA 98, 13757–13762 (2001).
66. Smith, J. M. Analyzing the mosaic structure of genes. J. Mol. Evol.
34, 126–129 (1992).
67. Boni, M. F., Posada, D. & Feldman, M. W. An exact nonparametric
method for inferring mosaic structure in sequence triplets. Genetics
176, 1035–1047 (2007).
68. Martin, D. P., Posada, D., Crandall, K. A. & Williamson, C. A modified
bootscan algorithm for automated identification of recombinant
sequences and recombination breakpoints. AIDS Res. Hum. Retroviruses 21, 98–102 (2005).
69. Gibbs, M. J., Armstrong, J. S. & Gibbs, A. J. Sister-scanning: a Monte
Carlo procedure for assessing signals in recombinant sequences.
Bioinformatics 16, 573–582 (2000).
70. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2-approximately
maximum-likelihood trees for large alignments. PLoS One 5,
e9490 (2010).
71. Nguyen, L. T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE:
a fast and effective stochastic algorithm for estimating maximumlikelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).
17
Article
72. Rambaut, A., Lam, T. T., Max Carvalho, L. & Pybus, O. G. Exploring
the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen). Virus Evol. 2, vew007 (2016).
73. Suchard, M. A. et al. Bayesian phylogenetic and phylodynamic data
integration using BEAST 1.10. Virus Evol. 4, vey016 (2018).
74. Duchene, S. et al. Temporal signal and the phylodynamic threshold
of SARS-CoV-2. Virus Evol. 6, veaa061 (2020).
75. Kimura, I. et al. The SARS-CoV-2 Lambda variant exhibits enhanced
infectivity and immune resistance. Cell Rep. 38, 110218 (2022).
76. Niwa, H., Yamamura, K. & Miyazaki, J. Efficient selection for highexpression transfectants with a novel eukaryotic vector. Gene 108,
193–199 (1991).
77. Yamasoba, D. et al. Neutralisation sensitivity of SARS-CoV-2 omicron subvariants to therapeutic monoclonal antibodies. Lancet
Infect. Dis. 22, 942–943 (2022).
78. Meng, B. et al. Altered TMPRSS2 usage by SARS-CoV-2 Omicron
impacts tropism and fusogenicity. Nature 603, 706–714 (2022).
79. Reed, L. J. & Muench, H. A simple method of estimating fifty percent
endpoints. Am. J. Hygiene 27, 493–497 (1938).
80. Zahradnik, J. et al. A protein-engineered, enhanced yeast display
platform for rapid evolution of challenging targets. ACS Synth. Biol.
10, 3445–3460 (2021).
81. Ozono, S., Zhang, Y., Tobiume, M., Kishigami, S. & Tokunaga, K.
Super-rapid quantitation of the production of HIV-1 harboring a
luminescent peptide tag. J. Biol. Chem. 295, 13023–13030 (2020).
82. Kondo, N., Miyauchi, K. & Matsuda, Z. Monitoring viral-mediated
membrane fusion using fluorescent reporter methods. Curr. Protoc.
Cell Biol (2011) Chapter 26, Unit 26 29, https://doi.org/10.1002/
0471143030.cb2609s50.
83. Hsieh, C. L. et al. Structure-based design of prefusion-stabilized
SARS-CoV-2 spikes. Science 369, 1501–1505 (2020).
84. Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–296 (2017).
85. Cardone, G., Heymann, J. B. & Steven, A. C. One number does not fit
all: mapping local variations in resolution in cryo-EM reconstructions. J. Struct. Biol. 184, 226–236 (2013).
86. Pettersen, E. F. et al. UCSF Chimera—a visualization system for
exploratory research and analysis. J. Comput. Chem. 25,
1605–1612 (2004).
87. Goddard, T. D. et al. UCSF ChimeraX: Meeting modern challenges
in visualization and analysis. Protein Sci. 27, 14–25 (2018).
88. Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and
development of Coot. Acta Crystallogr. D Biol. Crystallogr. 66,
486–501 (2010).
89. Liebschner, D. et al. Macromolecular structure determination using
X-rays, neutrons and electrons: recent developments in Phenix.
Acta Crystallogr. D Struct. Biol. 75, 861–877 (2019).
90. Williams, C. J. et al. MolProbity: More and better reference data for
improved all-atom structure validation. Protein Sci. 27,
293–315 (2018).
91. Sano, E. et al. Cell response analysis in SARS-CoV-2 infected
bronchial organoids. Commun Biol. 5, 516 (2022).
92. Yamamoto, Y. et al. Long-term expansion of alveolar stem cells
derived from human iPS cells in organoids. Nat. Methods 14,
1097–1106 (2017).
93. Konishi, S. et al. Directed induction of functional multi-ciliated cells
in proximal airway epithelial spheroids from human pluripotent
stem cells. Stem Cell Rep. 6, 18–25 (2016).
94. Gotoh, S. et al. Generation of alveolar epithelial spheroids via isolated progenitor cells from human pluripotent stem cells. Stem Cell
Rep. 3, 394–403 (2014).
95. Deguchi, S. et al. Usability of polydimethylsiloxane-based microfluidic devices in pharmaceutical research using human hepatocytes. ACS Biomater Sci Eng 7, 3648–3657 (2021).
Nature Communications | (2023)14:2800
https://doi.org/10.1038/s41467-023-38435-3
96. Huo, J. et al. A delicate balance between antibody evasion and
ACE2 affinity for Omicron BA.2.75. Cell Rep. 42, 111903 (2023).
Acknowledgements
We would like to thank all members belonging to The Genotype to Phenotype Japan (G2P-Japan) Consortium. We thank Dr. Jin Kuramochi
(Interpark Kuramochi Clinic, Japan) for providing patient sera, Dr. Kenzo
Tokunaga (National Institute for Infectious Diseases, Japan) and Dr. Jin
Gohda (The University of Tokyo, Japan) for providing reagents. We also
thank National Institute for Infectious Diseases, Japan for providing clinical
isolates of BQ.1.1 (strain TY41-796-P1; GISAID ID: EPI_ISL_15579783) and
BA.2 (strain TY40-385; GISAID ID: EPI_ISL_9595859). We appreciate the
technical assistance from The Research Support Center, Research Center
for Human Disease Modeling, Kyushu University Graduate School of
Medical Sciences. We gratefully acknowledge all data contributors, i.e.
the Authors and their Originating laboratories responsible for obtaining
the specimens, and their Submitting laboratories for generating the
genetic sequence and metadata and sharing via the GISAID Initiative, on
which this research is based. The super-computing resource was provided by Human Genome Center at The University of Tokyo. This study
was supported in part by AMED SCARDA Japan Initiative for World-leading
Vaccine Research and Development Centers “UTOPIA” (JP223fa627001,
to Kei Sato), AMED SCARDA Program on R&D of new generation vaccine
including new modality application (JP223fa727002, to Kei Sato); AMED
SCARDA Kyoto University Immunomonitoring Center (KIC)
(JP223fa627009, to Takao Hashiguchi); AMED SCARDA World-leading
institutes for vaccine research and development Hokkaido Synergy
Campus (JP223fa627005 to Takasuke Fukuhara and Keita Matsuno); AMED
Research Program on Emerging and Re-emerging Infectious Diseases
(JP21fk0108574, to Hesham Nasser; JP21fk0108481, to Akatsuki Saito;
JP21fk0108465, to Akatsuki Saito; JP21fk0108493, to Takasuke Fukuhara;
JP21fk0108463 to Katsumi Maenaka; JP22fk0108617 to Takasuke Fukuhara; JP22fk0108146, to Kei Sato; JP21fk0108494 to G2P-Japan Consortium, Keita Matsuno, Shinya Tanaka, Terumasa Ikeda, Takasuke
Fukuhara, and Kei Sato; JP21fk0108425, to Kazuo Takayama, Akatsuki Saito
and Kei Sato; 22fk0108506, to Kazuo Takayama, Akatsuki Saito, and Kei
Sato; JP21fk0108432, to Kazuo Takayama, Takasuke Fukuhara and Kei
Sato); AMED Research Program on HIV/AIDS (JP22fk0410033, to Akatsuki
Saito; JP22fk0410047, to Akatsuki Saito; JP22fk0410055, to Terumasa
Ikeda; and JP22fk0410039, to Kei Sato); AMED CRDF Global Grant
(JP22jk0210039 to Akatsuki Saito); AMED Japan Program for Infectious
Diseases Research and Infrastructure (JP22wm0325009, to Akatsuki
Saito; JP22wm0125008 to Keita Matsuno); AMED Japan Initiative for
World-leading Vaccine Research and Development Centers
(JP223fa627005 to Katsumi Maenaka); AMED Project Focused on Developing Key Technology for Discovering and Manufacturing Drugs for NextGeneration Treatment and Diagnosis (JP20ae0101047 to Katsumi Maenaka); AMED Platform Project for Supporting Drug Discovery and Life
Science Research (JP21am0101093 to Katsumi Maenaka); AMED Basis for
supporting innovative drug discovery and life science research, phase 2
(JP22ama121037 to Katsumi Maenaka); AMED Advanced Research &
Development Programs for Medical Innovation (JP22gm1810004 to Katsumi Maenaka); AMED CREST (JP21gm1610005, to Kazuo Takayama); JST
PRESTO (JPMJPR22R1, to Jumpei Ito); JST CREST (JPMJCR20H4, to Kei
Sato; JPMJCR20H8, to Takao Hashiguchi); JSPS KAKENHI Grant-in-Aid for
Scientific Research C (22K07103, to Terumasa Ikeda); JSPS KAKENHI
Grant-in-Aid for Scientific Research B (21H02736, to Takasuke Fukuhara);
JSPS KAKENHI Grant-in-Aid for Early-Career Scientists (22K16375, to
Hesham Nasser; 20K15767, to Jumpei Ito; 23K14526 to Jumpei Ito); JSPS
KAKENHI Grant-in-Aid for Transformative Research Areas B (20H05773 to
Takao Hashiguchi); JSPS KAKENHI Grant-in-Aid for Scientific Research on
Innovative Areas (JP20H05873, to Katsumi Maenaka); JSPS Core-to-Core
Program (A. Advanced Research Networks) (JPJSCCA20190008, to Kei
Sato); JSPS Research Fellow DC2 (22J11578, to Keiya Uriu); JSPS Leading
Initiative for Excellent Young Researchers (LEADER) (to Terumasa Ikeda);
18
Article
World-leading Innovative and Smart Education (WISE) Program 1801 from
the Ministry of Education, Culture, Sports, Science and Technology
(MEXT) (to Naganori Nao); The Cooperative Research Program (Joint
Usage/Research Center program) of Institute for Life and Medical Sciences, Kyoto University (to Kei Sato); The Tokyo Biochemical Research
Foundation (to Kei Sato); Takeda Science Foundation (to Terumasa Ikeda
and Katsumi Maenaka); Mochida Memorial Foundation for Medical and
Pharmaceutical Research (to Terumasa Ikeda); The Naito Foundation (to
Terumasa Ikeda); Shin-Nihon Foundation of Advanced Medical Research
(to Terumasa Ikeda); Waksman Foundation of Japan (to Terumasa Ikeda);
an intramural grant from Kumamoto University COVID-19 Research Projects (AMABIE) (to Terumasa Ikeda); Ito Foundation Research Grant R4 (to
Akatsuki Saito); International Joint Research Project of the Institute of
Medical Science, the University of Tokyo (to Jiri Zahradnik, Daniel Sauter,
Terumasa Ikeda, Takasuke Fukuhara, and Akatsuki Saito); the Federal
Ministry of Education and Research Germany (BMBF; 01KI20135, to Daniel
Sauter); the Canon Foundation Europe (to Daniel Sauter), the Heisenberg
Program of the German Research Foundation (DFG; SA 2676/3-1, to Daniel
Sauter); grants of the COVID-19 program of the Ministry of Science,
Research and the Arts Baden-Württemberg (MWK; K.N.K.C.014 and
K.N.K.C.015, to Daniel Sauter); and the project of National Institute of
Virology and Bacteriology, Programme EXCELES, funded by the European
Union, Next Generation EU (LX22NPO5103, to Jiri Zahradnik).
Author contributions
J.I. performed bioinformatics, modeling, and statistical analysis.
Competing interests
Y.Y. and T.N. are founders and shareholders of HiLung, Inc. Y.Y. is a coinventor of patents (PCT/JP2016/057254; “Method for inducing differentiation of alveolar epithelial cells”, PCT/JP2016/059786, “Method of
producing airway epithelial cells”). The other authors declare that no
competing interests exist.
https://doi.org/10.1038/s41467-023-38435-3
Additional information
Supplementary information The online version contains supplementary
material available at
https://doi.org/10.1038/s41467-023-38435-3.
Correspondence and requests for materials should be addressed to
Shinya Tanaka, Keita Matsuno, Kazuo Takayama or Kei Sato.
Peer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. A
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© The Author(s) 2023
Department of Microbiology and Immunology, Faculty of Medicine, Hokkaido University, Sapporo, Japan. 2Institute for Vaccine Research and Development,
HU-IVReD, Hokkaido University, Sapporo, Japan. 3Division of Systems Virology, Department of Microbiology and Immunology, The Institute of Medical
Science, The University of Tokyo, Tokyo, Japan. 4Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. 5Department of Biomolecular Sciences,
Weizmann Institute of Science, Rehovot, Israel. 6First Medical Faculty at Biocev, Charles University, Vestec-Prague, Czechia. 7Division of Risk Analysis and
Management, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan. 8Laboratory of Biomolecular Science and Center for Research
and Education on Drug Discovery, Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan. 9Division of Molecular Virology and Genetics,
Joint Research Center for Human Retrovirus infection, Kumamoto University, Kumamoto, Japan. 10Department of Clinical Pathology, Faculty of Medicine, Suez
Canal University, Ismailia, Egypt. 11Department of Veterinary Science, Faculty of Agriculture, University of Miyazaki, Miyazaki, Japan. 12Graduate School of
Medicine and Veterinary Medicine, University of Miyazaki, Miyazaki, Japan. 13Department of Cancer Pathology, Faculty of Medicine, Hokkaido University,
Sapporo, Japan. 14Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK. 15Division of International Research Promotion,
International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan. 16One Health Research Center, Hokkaido University, Sapporo, Japan.
17
Division of Molecular Pathobiology, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan. 18Center for iPS Cell Research and
Application (CiRA), Kyoto University, Kyoto, Japan. 19Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Sapporo, Japan.
20
Laboratory of Medical Virology, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan. 21Department of Medicinal Sciences, Graduate
School of Pharmaceutical Sciences, Kyushu University, Fukuoka, Japan. 22Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
23
Institute for Medical Virology and Epidemiology of Viral Diseases, University Hospital Tübingen, Tübingen, Germany. 24Institute for Genetic Medicine,
Hokkaido University, Sapporo, Japan. 25Tokyo Metropolitan Institute of Public Health, Tokyo, Japan. 26HiLung, Inc., Kyoto, Japan. 27Global Station for
Biosurfaces and Drug Discovery, Hokkaido University, Sapporo, Japan. 28Division of Pathogen Structure, International Institute for Zoonosis Control, Hokkaido
University, Sapporo, Japan. 29CREST, Japan Science and Technology Agency, Kawaguchi, Japan. 30AMED-CREST, Japan Agency for Medical Research and
Development (AMED), Tokyo, Japan. 31Laboratory of Virus Control, Research Institute for Microbial Diseases, Osaka University, Suita, Japan. 32Center for
Animal Disease Control, University of Miyazaki, Miyazaki, Japan. 33International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido
University, Sapporo, Japan. 34International Research Center for Infectious Diseases, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
35
International Vaccine Design Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan. 36Collaboration Unit for Infection, Joint
Research Center for Human Retrovirus infection, Kumamoto University, Kumamoto, Japan. 41These authors contributed equally: Tomokazu Tamura, Jumpei
e-mail: tanaka@med.hokudai.ac.jp;
Ito, Keiya Uriu, Jiri Zahradnik, Izumi Kida, Yuki Anraku, Hesham Nasser, Maya Shofa, Yoshitaka Oda, Spyros Lytras.
matsuk@czc.hokudai.ac.jp; kazuo.takayama@cira.kyoto-u.ac.jp; KeiSato@g.ecc.u-tokyo.ac.jp
Nature Communications | (2023)14:2800
19
Article
https://doi.org/10.1038/s41467-023-38435-3
The Genotype to Phenotype Japan (G2P-Japan) Consortium
Hayato Ito1, Naoko Misawa3, Izumi Kimura3, Mai Suganami3, Mika Chiba3, Ryo Yoshimura3, Kyoko Yasuda3, Keiko Iida3,
Naomi Ohsumi3, Adam P. Strange3, Otowa Takahashi9, Kimiko Ichihara9, Yuki Shibatani11, Tomoko Nishiuchi11, Marie Kato13,
Zannatul Ferdous13, Hiromi Mouri13, Kenji Shishido13, Hirofumi Sawa2,15,16,17, Rina Hashimoto18, Yukio Watanabe18,
Ayaka Sakamoto18, Naoko Yasuhara18, Tateki Suzuki20, Kanako Kimura20, Yukari Nakajima20, So Nakagawa37, Jiaqi Wu37,
Kotaro Shirakawa38, Akifumi Takaori-Kondo38, Kayoko Nagata38, Yasuhiro Kazuma38, Ryosuke Nomura38,
Yoshihito Horisawa38, Yusuke Tashiro38, Yugo Kawai38, Takashi Irie39, Ryoko Kawabata39, Chihiro Motozono40,
Mako Toyoda40 & Takamasa Ueno40
37
Tokai University School of Medicine, Isehara, Japan. 38Kyoto University, Kyoto, Japan. 39Hiroshima University, Hiroshima, Japan. 40Kumamoto University,
Kumamoto, Japan.
Nature Communications | (2023)14:2800
20
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