大阪大学大学院 情報科学研究科 代謝情報工学講座 清水浩研究室

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戸谷 吉博(Toya Yoshihiro)

研究テーマ

  • 代謝状態の可視化とバイオプロセス制御への応用
  • 光照射による代謝フラックスの制御技術の開発
  • 光駆動ATP再生の物質生産への応用
  • 増殖停止期の細胞を利用した有用物質生産
  • 代謝フラックス解析による細胞内代謝状態の評価

[研究者総覧]

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原著論文

  1. Senoo S, Tandar ST, Kitamura S, Toya Y, Shimizu H. Light-inducible flux control of triosephosphate isomerase on glycolysis in Escherichia coli.  Biotechnol Bioeng. In press. [Publisher]
  2. Hanatani Y, Imura M, Taniguchi H, Okano K, Toya Y, Iwakiri R, Honda K. In vitro production of cysteine from glucose. Appl Microbiol Biotechnol. 2019; 103(19):8009-8019. 
  3. Tandar ST, Senoo S, Toya Y, Shimizu H. Optogenetic switch for controlling the central metabolic flux of Escherichia coli. Metab Eng. 2019; 55:68-75. [Publisher]
    大阪大学プレスリリース:細胞の代謝の流れを光照射で自在にコントロール
    内容説明資料:PDF
  4. Tokuyama K, Toya Y, Shimizu H. Prediction of rate-limiting reactions for growth-associated production using a constraint-based approach. Biotechnol J. 2019; 14:e1800431. [Publisher]
  5. Adachi S, Tanaka Y, Miyagi A, Kashima M, Tezuka A, Toya Y, Kobayashi S, Ohkubo S, Shimizu H, Kawai-Yamada M, Sage RF, Nagano AJ, Yamori W. High-yielding rice Takanari has superior photosynthetic response under fluctuating light to a commercial rice Koshihikari. J Exp Bot. In press.
  6. Kitamura S, Toya Y, Shimizu H. 13C-metabolic flux analysis reveals effect of phenol on central carbon metabolism in Escherichia coli. Front Microbiol. 2019; 10:1010. [Publisher]
  7. Kamiura R, Toya Y, Matsuda F, Shimizu H. Theophylline-inducible riboswitch accurately regulates protein expression at low level in Escherichia coli. Biotechnol Lett. 2019; 41:743-751. [Publisher]
  8. Kamata K, Toya Y, Shimizu H. Effect of precise control of flux ratio between the glycolytic pathways on mevalonate production in Escherichia coli. Biotechnol Bioeng. 2019; 11(5):1080-1088. [Publisher]
  9. Tokuyama K, Toya Y, Matsuda F, Cress BF, Koffas MAG, Shimizu H. Magnesium starvation improves production of malonyl-CoA-derived metabolites in Escherichia coli. Metab Eng. 2019; 52:215-223. [Publisher]
  10. Ogawa K, Yoshikawa K, Matsuda F, Toya Y, Shimizu H. Transcriptome analysis of the cyanobacterium Synechocystis sp. PCC 6803 and mechanisms of photoinhibition tolerance under extreme high light conditions. J Biosci Bioeng. 2018; 126(5):596-602. [Publisher]
  11. Maruyama Y, Toya Y, Kurokawa H, Fukano Y, Sato A, Umemura H, Yamada K, Iwasaki H, Tobori N, Shimizu H. Characterization of oil-producing yeast Lipomyces starkeyi on glycerol carbon source based on metabolomics and 13C-labeling. Appl Microbiol Biotechnol. 2018; 102(20):8909-8920. [Publisher]
  12. Nagai H, Masuda A, Toya Y, Matsuda F, Shimizu H. Metabolic engineering of mevalonate-producing Escherichia coli strains based on thermodynamic analysis. Metab Eng. 2018; 47:1-9. [Publisher]
  13. Tokuyama K, Toya Y, Horinouchi T, Furusawa C, Matsuda F, Shimizu H. Application of adaptive laboratory evolution to overcome a flux limitation in an Escherichia coli production strain. Biotechnol Bioeng. 2018;115(6):1542-1551. [Publisher]
  14. Ueda K, Nakajima T, Yoshikawa K, Toya Y, Matsuda F, Shimizu H. Metabolic flux of the oxidative pentose phosphate pathway under low light conditions in Synechocystis sp. PCC 6803. J Biosci Bioeng. 2018; 126(1):38-43. [Publisher]
  15. Toya Y, Ohashi S, Shimizu H. 13C-labeling of glycerol carbon source for precise flux estimation in Escherichia coli. J Biosci Bioeng. 2018; 125(3):301-305. [Publisher]
  16. Matsusako T, Toya Y, Yoshikawa K, Shimizu H. Identification of alcohol stress tolerance genes of Synechocystis sp. PCC 6803 using adaptive laboratory evolution. Biotechnol Biofuels. 2017;10:307. [Publisher]
  17. Masuda A, Toya Y, Shimizu H. Metabolic impact of nutrient starvation in mevalonate-producing Escherichia coli. Bioresour Technol. 2017; 245(Pt B):1634-1640. [Publisher]
  18. Nakajima T, Yoshikawa K, Toya Y, Matsuda F, Shimizu H. Metabolic flux analysis of the Synechocystis sp. PCC 6803 ΔnrtABCD mutant reveals a mechanism for metabolic adaptation to nitrogen-limited conditions. Plant Cell Physiol. 2017; 58(3):537-545. [Publisher]
  19. Yoshikawa K, Toya Y, Shimizu H. Metabolic engineering of Synechocystis sp. PCC 6803 for enhanced ethanol production based on flux balance analysis. Bioprocess Biosyst Eng. 2017; 40(5):791-796. [Publisher]
  20. Wada K, Toya Y, Banno S, Yoshikawa K, Matsuda F, Shimizu H. 13C-metabolic flux analysis for mevalonate-producing strain of Escherichia coli. J Biosci Bioeng. 2017; 123(2):177-182. [Publisher]
  21. Namakoshi K, Nakajima T, Yoshikawa K, Toya Y, Shimizu H. Combinatorial deletions of glgC and phaCE enhance ethanol production in Synechocystis sp. PCC 6803. J Biotechnol. 2016; 239:13-19. [Publisher]
  22. Maeda K, Okahashi N, Toya Y, Matsuda F, Shimizu H. Investigation of useful carbon tracers for 13C-metabolic flux analysis of Escherichia coli by considering five experimentally determined flux distributions. Metab Eng Commun. 2016; 3:187–195. [Publisher]
  23. Yoshikawa K, Aikawa S, Kojima Y, Toya Y, Furusawa C, Kondo A, Shimizu H. Construction of a genome-scale metabolic model of Arthrospira platensis NIES-39 and metabolic design for cyanobacterial bioproduction. PLoS One. 2015;10(12):e0144430. [Publisher]
  24. Mannan AA, Toya Y, Shimizu K, McFadden J, Kierzek AM, Rocco A. Integrating kinetic model of E. coli with genome scale metabolic fluxes overcomes its open system problem and reveals bistability in central metabolism. PLoS One. 2015;10(10):e0139507. [Publisher]
  25. Toya Y, Hirasawa T, Ishikawa S, Chumsakul O, Morimoto T, Liu S, Masuda K, Kageyama Y, Ozaki K, Ogasawara N, Shimizu H. Enhanced dipicolinic acid production during the stationary phase in Bacillus subtilis by blocking acetoin synthesis. Biosci Biotechnol Biochem. 2015;79(12):2073-2080. [Publisher]
  26. Toya Y, Shiraki T, Shimizu H. SSDesign: Computational metabolic pathway design based on flux variability using elementary flux modes. Biotechnol Bioeng. 2015;112(4):759-768. [Publisher]
  27. Toya Y, Hirasawa T, Morimoto T, Masuda K, Kageyama Y, Ozaki K, Ogasawara N, Shimizu H. 13C-metabolic flux analysis in heterologous cellulase production by Bacillus subtilis genome-reduced strain. J Biotechnol. 2014;179:42-49. [Publisher]
  28. Ito T, Sugimoto M, Toya Y, Ano Y, Kurano N, Soga T, Tomita M. Time-resolved metabolomics of a novel trebouxiophycean alga using 13CO2 feeding. J Biosci Bioeng. 2013;116(3):408-415.
  29. Toya Y, Nakahigashi K, Tomita M, Shimizu K. Metabolic regulation analysis of wild-type and arcA mutant Escherichia coli under nitrate conditions using different levels of omics data. Mol Biosyst. 2012;8(10):2593-2604.
  30. Toya Y, Ishii N, Nakahigashi K, Hirasawa T, Soga T, Tomita M, Shimizu K. 13C-metabolic flux analysis for batch culture of Escherichia coli and its Pyk and Pgi gene knockout mutants based on mass isotopomer distribution of intracellular metabolites. Biotechnol Prog. 2010;26(4):975-992.
  31. Nakahigashi K, Toya Y, Ishii N, Soga T, Hasegawa M, Watanabe H, Takai Y, Honma M, Mori H, Tomita M. Systematic phenome analysis of Escherichia coli multiple-knockout mutants reveals hidden reactions in central carbon metabolism. Mol Syst Biol. 2009;5:306.
  32. Toya Y, Ishii N, Hirasawa T, Naba M, Hirai K, Sugawara K, Igarashi S, Shimizu K, Tomita M, Soga T. Direct measurement of isotopomer of intracellular metabolites using capillary electrophoresis time-of-flight mass spectrometry for efficient metabolic flux analysis. J Chromatogr A. 2007;1159(1-2):134-141.
  33. Ishii N, Nakahigashi K, Baba T, Robert M, Soga T, Kanai A, Hirasawa T, Naba M, Hirai K, Hoque A, Ho PY, Kakazu Y, Sugawara K, Igarashi S, Harada S, Masuda T, Sugiyama N, Togashi T, Hasegawa M, Takai Y, Yugi K, Arakawa K, Iwata N, Toya Y, Nakayama Y, Nishioka T, Shimizu K, Mori H, Tomita M. Multiple high-throughput analyses monitor the response of E. coli to perturbations. Science. 2007;316(5824):593-597.

総説

  1. Matsuda F, Toya Y, Shimizu H, Learning from quantitative data to understand central carbon metabolism. Biotechnol Adv. 2017; 35(8):971-980.
  2. Toya Y, Shimizu H. Flux analysis and metabolomics for systematic metabolic engineering of microorganisms. Biotechnol Adv. 2013; 31(6):818-826.
  3. Toya Y, Kono N, Arakawa K, Tomita M. Metabolic flux analysis and visualization. J Proteome Res. 2011; 10(8):3313-3323.

解説

  1. 戸谷吉博, 松田史生. 代謝工学におけるバイオインフォマティクスの利用. 生物工学会誌. 2019; 97(5):261-264. [Link]
  2. 戸谷吉博. 計算機シミュレーションを利用した代謝デザイン技術-有用物質生産の効率化を目的とした代謝経路の改変. 化学と生物. 2017; 55(2):83-85. [Link]
  3. 清水浩, 松田史生, 戸谷吉博. 代謝デザインと13C同位体標識を用いた代謝フラックス解析の物質生産への応用. 化学と生物. 2015; 53(7):455-461.
  4. 清水浩, 古澤力, 平沢敬, 吉川勝徳, 小野直亮, 戸谷吉博, 白井智量. 代謝工学の創成と発展-代謝解析とオミクス研究との融合. 生物工学会誌. 2012; 90:619-620.
  5. 戸谷吉博, 石井伸佳, 冨田勝. 微生物代謝のシステムバイオロジー ―オミックス解析からシミュレーションへ―. バイオインダストリー. 2008; 25:44-51.
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