Preprints
Sakuma T, Ohno S, Shimizu H. Cell-type-resolved metabolic flux inference reveals stromal metabolic reprogramming across human cardiomyopathies. bioRxiv. 2026.04.19.719409. 2026. https://www.biorxiv.org/content/10.64898/2026.04.19.719409v1
Abekawa T, Ohno S, Hirayama A, Soga T, Kuroda S. The Gibbs free energy landscape based on liver metabolome revealed thermodynamic robustness against fasting and obesity. bioRxiv. 2025.12. 04.692290. 2025. https://www.biorxiv.org/content/10.64898/2025.12.04.692290v2
Ito T, Ohno S, Wang Y, Uematsu S, Kuroda S, Shimizu H. MetDeeCINE: Deciphering metabolic regulation through deep learning and multi-omics. bioRxiv. 2025.03.24.645125. 2025. https://www.biorxiv.org/content/10.1101/2025.03.24.645125v1
Accepted
Koga, D., Kaneda, R., Komiya, C., Ohno, S., Takeuchi, A., Hara, K., Horino, M., Aoki, J., Okazaki, R., Ishii, R., Murakami, M., Tsujimoto, K., Ikeda, K., Katagiri, H., Shimizu, H., Yamada, T. (2025). Artificial intelligence identifies individuals with prediabetes using single-lead electrocardiograms. Cardiovascular Diabetology, 24, 415, pp.1-13.
Morita, K., Hatano, A., Kokaji, T., Sugimoto, H., Tsuchiya, T., Ozaki, H., Egami, R., Li, D., Terakawa, A., Ohno, S., Inoue, H., Inaba, Y., Suzuki, Y., Matsumoto, M., Takahashi, M., Izumi, Y., Bamba, T., Hirayama, A., Soga, T., Kuroda, S. (2025). Structural robustness and temporal vulnerability of the starvation-responsive metabolic network in liver of healthy and obese mice. Science Signaling, 18, eads2547, pp.1-25.
Pan, Y., Hatano, A., Ohno, S., Morita, K., Kokaji, T., Bai, Y., Sugimoto, H., Egami, R., Terakawa, A., Li, D., Uematsu, S., Maehara, H., Fujita, S., Inoue, H., Inaba, Y., Nagano, A. J., Hirayama, A., Soga, T., Kuroda, S. (2024). Time and dose selective glucose metabolism for glucose homeostasis and energy conversion in the liver. NPJ Systems Biology and Applications., 10, 107, pp.1-22.
Bai, Y., Morita, K., Kokaji, T., Hatano, A., Ohno, S., Egami, R., Pan, Y., Li, D., Yugi, K., Uematsu, S., Inoue, H., Inaba, Y., Suzuki, Y., Matsumoto, M., Takahashi, M., Izumi, Y., Bamba, T., Hirayama, A., Soga, T., Kuroda, S. (2024). Trans-omic analysis reveals opposite metabolic dysregulation between feeding and fasting in liver associated with obesity. iScience, 27, 109121, pp.1-25.
Maehara, H., Kokaji, T., Hatano, A., Suzuki, Y., Matsumoto, M., Nakayama, K. I., Egami, R., Tsuchiya, T., Ozaki, H., Morita, K., Shirai, M., Li, D., Terakawa, A., Uematsu, S., Hironaka, K.-I., Ohno, S., Kubota, H., Araki, H., Miura, F., Ito, T., Kuroda, S. (2023). DNA hypomethylation characterizes genes encoding tissue-dominant functional proteins in liver and skeletal muscle. Scientific Reports, 13(1), 19118, pp.1-19.
Kokaji, T., Eto, M., Hatano, A., Yugi, K., Morita, K., Ohno, S., Fujii, M., Hironaka, K., Ito, Y., Egami, R., Uematsu, S., Terakawa, A., Pan, Y., Maehara, H., Li, D., Bai, Y., Tsuchiya, T., Ozaki, H., Inoue, H., Kubota, H., Suzuki, Y., Hirayama, A., Soga, T., Kuroda, S. (2022). In vivo transomic analyses of glucose-responsive metabolism in skeletal muscle reveal core differences between the healthy and obese states. Scientific Reports 12(1), 13719, pp.1-19.
Terakawa, A., Hu, Y., Kokaji, T., Yugi, K., Morita, K., Ohno, S., Pan, Y., Bai, Y., Parkhitko, A. A., Ni, X., Asara, J. M., Bulyk, M. L., Perrimon, N., Kuroda, S. (2022). Trans-omics analysis of insulin action reveals a cell growth subnetwork which co-regulates anabolic processes. iScience, 25(5), 104231, pp.1-26.
Uematsu, S., *Ohno, S., Tanaka, K. Y., Hatano, A., Kokaji, T., Ito, Y., Kubota, H., Hironaka, K., Suzuki, Y., Matsumoto, M., Nakayama, K. I., Hirayama, A., Soga, T., *Kuroda, S. (2022). Multi-omics-based label-free metabolic flux inference reveals obesity-associated dysregulatory mechanisms in liver glucose metabolism. iScience, 25(2), 103787, pp.1-35. [*: Corresponding authors]
Ohno, S., Uematsu, S., & Kuroda, S. (2022). Quantitative metabolic fluxes regulated by trans-omic networks. Biochemical Journal, 479(6), pp.787-804.
大野聡、「代謝フラックスの定量によるトランスオミクスネットワークの理解」（『生物工学会誌』、日本生物工学会、Vol. 100、No. 5、pp.231-235）、2022年
Egami, R., Kokaji, T., Hatano, A., Yugi, K., Eto, M., Morita, K., Ohno, S., Fujii, M., Hironaka, K., Uematsu, S., Terakawa, A., Bai, Y., Pan, Y., Tsuchiya, T., Ozaki, H., Inoue, H., Uda, S., Kubota, H., Suzuki, Y., Matsumoto, M., Nakayama, K. I., Hirayama, A., Soga, T., Kuroda, S. (2021). Trans-omic analysis reveals obesity-associated dysregulation of inter-organ metabolic cycles between the liver and skeletal muscle. iScience, 24(3), 102217, pp.1-22.
Kokaji, T., Hatano, A., Ito, Y., Yugi, K., Eto, M., Morita, K., Ohno, S., Fujii, M., Hironaka, K., Egami, R., Terakawa, A., Tsuchiya, T., Ozaki, H., Inoue, H., Uda, S., Kubota, H., Suzuki, Y., Ikeda, K., Arita, M., Matsumoto, M., Nakayama, K. I., Hirayama, A., Soga, T., Kuroda, S. (2020). Transomics analysis reveals allosteric and gene regulation axes for altered hepatic glucose-responsive metabolism in obesity. Science Signaling, 13(660), eaaz1236, pp.1-20.
Ohno, S., Quek, L.-E., Krycer, J. R., Yugi, K., Hirayama, A., Ikeda, S., Shoji, F., Suzuki, K., Soga, T., James, D. E., Kuroda, S. (2020). Kinetic trans-omic analysis reveals key regulatory mechanisms for insulin-regulated glucose metabolism in adipocytes. iScience, 23(9), 101479, pp.1-16.
Quek, L.-E., Krycer, J. R., Ohno, S., Yugi, K., Fazakerley, D. J., Scalzo, R., Elkington, S. D., Dai, Z., Hirayama, A., Ikeda, S., Shoji, F., Suzuki, K., Locasale, J. W., Soga, T., James, D. E., Kuroda, S. (2020). Dynamic 13C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin. iScience, 23(2), 100855, pp.1-19.
Yugi, K., Ohno, S., Krycer, J. R., James, D. E., & Kuroda, S. (2019). Rate-oriented trans-omics: integration of multiple omic data on the basis of reaction kinetics. Current Opinion in Systems Biology, 15, pp.109-120.
Krycer, J. R., Yugi, K., Hirayama, A., Fazakerley, D. J., Quek, L.-E., Scalzo, R., Ohno, S., Hodson, M. P., Ikeda, S., Shoji, F., Suzuki, K., Domanova, W., Parker, L. B., Nelson, M. E., Humphrey, S. J., Turner, N., Hoehn, K. L., Cooney, G. J., Soga, T., Kuroda, S., James, D. E. (2017). Dynamic Metabolomics Reveals that Insulin Primes the Adipocyte for Glucose Metabolism. Cell Reports, 21(12), pp.3536-3547.
佐野貴規、川田健太郎、大野聡、黒田真也、「インスリン刺激の時間パターンおよび濃度による選択的遺伝子発現制御」（『シグナリングに載った日本人研究者』、AAAS、pp.28-29）、2016年
†Sano, T., †Kawata, K., †Ohno, S., Yugi, K., Kakuda, H., Kubota, H., Uda, S., Fujii, M., Kunida, K., Hoshino, D., Hatano, A., Ito, Y., Sato, M., Suzuki, Y., Kuroda, S. (2016). Selective control of up-regulated and down-regulated genes by temporal patterns and doses of insulin. Science Signaling, 9(455), ra112, pp.1-11. [†: equally-contributed]
大野聡、古澤力、清水浩、「大腸菌による有用物質生産に向けた3重反応破壊のin silicoスクリーニング」（『生物工学会誌』、日本生物工学会、Vol. 93、No. 2、p.76）、2015年
Tokuyama, K., Ohno, S., Yoshikawa, K., Hirasawa, T., Tanaka, S., Furusawa, C., Shimizu, H. (2014). Increased 3-hydroxypropionic acid production from glycerol, by modification of central metabolism in Escherichia coli. Microbial Cell Factories, 13, 64, pp.1-11.
Nakashima, N., Ohno, S., Yoshikawa, K., Shimizu, H., & Tamura, T. (2014). A vector library for silencing central carbon metabolism genes with antisense RNAs in Escherichia coli. Applied and Environmental Microbiology, 80(2), pp.564-573.
Ohno, S., Shimizu, H., & Furusawa, C. (2014). FastPros: Screening of reaction knockout strategies for metabolic engineering. Bioinformatics, 30(7), pp.981-987.
Ohno, S., Furusawa, C., & Shimizu, H. (2013). In silico screening of triple reaction knockout Escherichia coli strains for overproduction of useful metabolites. Journal of Bioscience and Bioengineering, 115(2), pp.221-228.