PubMed · 40795871
An adjuvant database for preclinical evaluation of vaccines and immunotherapeutics.
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.
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Yayoi Natsume-Kitatani, Kouji Kobiyama, Yoshinobu Igarashi, Taiki Aoshi, Noriyuki Nakatsu, Lokesh P Tripathi, Junichi Ito, Johan Nyström-Persson, Yuji Kosugi, Rodolfo S Allendes Osorio, Chioko Nagao, Burcu Temizoz, Etsushi Kuroda, Daron M Standley, Hiroshi Kiyono, Kenji Nakanishi, Satoshi Uematsu, Isao Hamaguchi, Yasuhiro Yasutomi, Jun Kunisawa, Sho Yamasaki, Cevayir Coban, Hiroshi Yamada, Kenji Mizuguchi, Ken J Ishii. 2025-08-11. An adjuvant database for preclinical evaluation of vaccines and immunotherapeutics.. https://doi.org/10.1016/j.chembiol.2025.07.005
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