2025年8月18日 / 最終更新日 : 2025年8月18日 ad_y ニュース

2025年 新着論文 32　バイオインフォマティクス分野から論文が発表されました

An adjuvant database for preclinical evaluation of vaccines and immunotherapeutics

Cell Chem Biol. 2025 Aug 7:S2451-9456(25)00228-4. doi: 10.1016/j.chembiol.2025.07.005. Online ahead of print.

Authors

Yayoi Natsume-Kitatani  1 , Kouji Kobiyama  2 , Yoshinobu Igarashi  3 , Taiki Aoshi  4 , Noriyuki Nakatsu  3 , Lokesh P Tripathi  5 , Junichi Ito  6 , Johan Nyström-Persson  7 , Yuji Kosugi  8 , Rodolfo S Allendes Osorio  9 , Chioko Nagao  10 , Burcu Temizoz  11 , Etsushi Kuroda  12 , Daron M Standley  13 , Hiroshi Kiyono  14 , Kenji Nakanishi  12 , Satoshi Uematsu  15 , Isao Hamaguchi  16 , Yasuhiro Yasutomi  17 , Jun Kunisawa  18 , Sho Yamasaki  19 , Cevayir Coban  20 , Hiroshi Yamada  3 , Kenji Mizuguchi  10 , Ken J Ishii  21

Affiliations

  • 1 Laboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition (NIBN), Settsu, Osaka 566-0002, Japan; Institute of Advanced Medical Sciences, Tokushima University, Tokushima, Tokushima 770-8503, Japan; Institute for Protein Research, the University of Osaka, Suita, Osaka 565-0871, Japan.
  • 2 Laboratory of Vaccine Science, the Institute of Medical Science, the University of Tokyo (IMSUT), Minato-ku, Tokyo 108-8639, Japan; International Vaccine Design Center (VDesC), the Institute of Medical Science, the University of Tokyo (IMSUT), Minato-ku, Tokyo 108-8639, Japan; Division of Rheumatology, Department of Medicine, University of California, San Diego, La Jolla, CA 92093-0809, USA.
  • 3 Toxicogenomics-Informatics Project, Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition (NIBN), Settsu, Osaka 567-0085, Japan.
  • 4 Department of Immunology, Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki 852-8523, Japan.
  • 5 Laboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition (NIBN), Settsu, Osaka 566-0002, Japan; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan.
  • 6 Discovery Concept Validation Function, Eisai Co., Ltd., Kobe, Hyogo 650-0047, Japan.
  • 7 JNP Solutions, Sumida-ku, Tokyo 130-0015, Japan.
  • 8 Lifematics Ltd., Chuo-ku, Tokyo 104-0032, Japan.
  • 9 Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), the University of Osaka, Suita, Osaka 565-0871, Japan.
  • 10 Institute for Protein Research, the University of Osaka, Suita, Osaka 565-0871, Japan.
  • 11 Laboratory of Vaccine Science, the Institute of Medical Science, the University of Tokyo (IMSUT), Minato-ku, Tokyo 108-8639, Japan.
  • 12 Department of Immunology, Hyogo Medical University School of Medicine, Nishinomiya, Hyogo 663-8501, Japan.
  • 13 Department of Genome Informatics, Genome Information Research Center, Research Institute for Microbial Diseases (RIMD), the University of Osaka, Suita, Osaka 565-0871, Japan.
  • 14 Department of Human Mucosal Vaccinology, Chiba University Hospital, Chiba 260-8670, Japan; Synergy Institute for Futuristic Mucosal Vaccine Research and Development (cSIMVa), Chiba University, Chiba, Chiba 260-8670, Japan; CU-UCSD Center for Mucosal Immunology, Allergy and Vaccines (cMAV), UC San Diego School of Medicine, San Diego, CA 92093-0063, USA.
  • 15 Department of Immunology and Genomics, Graduate School of Medicine, Osaka Metropolitan University, Abeno, Osaka 545-0051, Japan; Division of Metagenome Medicine, Human Genome Center, the Institute of Medical Science, the University of Tokyo, Minato-ku, Tokyo 108-8639, Japan.
  • 16 Research Center for Biological Products in the Next Generation, National Institute of Infectious Diseases, Musashimurayama, Tokyo 208-0011, Japan.
  • 17 Tsukuba Primate Research Center, National Institutes of Biomedical Innovation, Health and Nutrition (NIBN), Tsukuba, Ibaraki 305-0843, Japan.
  • 18 Laboratory of Vaccine Materials, Center for Vaccine and Adjuvant Research, National Institutes of Biomedical Innovation, Health and Nutrition (NIBN), Ibaraki, Osaka 567-0085, Japan.
  • 19 Department of Molecular Immunology, Research Institute for Microbial Diseases (RIMD), the University of Osaka, Suita, Osaka 565-0871, Japan; Laboratory of Molecular Immunology, Immunology Frontier Research Center (IFReC), the University of Osaka, Suita, Osaka 565-0871, Japan; Center for Infectious Disease Education and Research (CiDER), the University of Osaka, Suita, Osaka 565-0871, Japan; Center for Advanced Modalities and DDS (CAMaD), the University of Osaka, Suita, Osaka 565-0871, Japan.
  • 20 International Vaccine Design Center (VDesC), the Institute of Medical Science, the University of Tokyo (IMSUT), Minato-ku, Tokyo 108-8639, Japan; Division of Malaria Immunology, Department of Microbiology and Immunology, The Institute of Medical Science (IMSUT), the University of Tokyo, Tokyo 108-8639, Japan; WPI Immunology Frontier Research Center (IFReC), the University of Osaka, Suita, Osaka 565-0871, Japan; The University of Tokyo Pandemic Preparedness, Infection and Advanced Research Center (UTOPIA), the University of Tokyo, Tokyo 108-8639, Japan.
  • 21 Laboratory of Vaccine Science, the Institute of Medical Science, the University of Tokyo (IMSUT), Minato-ku, Tokyo 108-8639, Japan; International Vaccine Design Center (VDesC), the Institute of Medical Science, the University of Tokyo (IMSUT), Minato-ku, Tokyo 108-8639, Japan; WPI Immunology Frontier Research Center (IFReC), the University of Osaka, Suita, Osaka 565-0871, Japan; The University of Tokyo Pandemic Preparedness, Infection and Advanced Research Center (UTOPIA), the University of Tokyo, Tokyo 108-8639, Japan. Electronic address: kenishii@ims.u-tokyo.ac.jp.

Abstract

Adjuvants are immunostimulators used to enhance vaccine efficacy against infectious diseases. However, current methods for evaluating their efficacy and safety are limited, hindering large-scale screening. To address this, we developed a prototype Adjuvant Database (ADB) containing transcriptome data, generated using the same protocols as the widely used Open TG-GATEs (OTG) toxicogenomics database, covering 25 adjuvants across multiple species, organs, time points, and doses. This enabled cross-database integration of ADB and OTG. Transcriptomic patterns successfully distinguished each adjuvant regardless of organs or species. Using both databases, we built machine learning models to predict adjuvanticity and hepatotoxicity. Notably, we identified colchicine’s adjuvant activity and FK565’s liver toxicity through data-driven analysis. Overall, ADB combined with OTG offers a framework for transcriptomics-based, data-driven screening of adjuvant candidates.

Keywords: NOD1; RLR; STING; TLR; adjuvant; innate immunity; machine learning; pharmacology; toxicology; vaccine.

Conflict of interest statement

Declaration of interests The following authors have conflicts of interest to declare: K.J.I. holds a patent on the CpG adjuvants, CpG-D35, and CpG-K3. K.K., T.A., and K.J.I. hold a patent on K3-SPG. C.C. and K.J.I. hold a patent on sHZ. E.T. and K.J.I. hold a patent on cdiGMP and cGAMP.

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