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Received November 13, 2012
Accepted December 17, 2012
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Clostridium acetobutylicum의 대사망의 동적모델 개발
Development of the Dynamic Model for the Metabolic Network of Clostridium acetobutylicum
한국에너지기술연구원 신재생에너지본부 수소연료전지연구단, 대전광역시 유성구 가정로 152 1GS칼텍스(주) 기술연구소 바이오연료팀, 305-380 대전광역시 유성구 문지동 104-4 2한국과학기술원 생명화학공학과, 305-701 대전광역시 유성구 대학로 291
, Korea 1Biofuel & Biochemical Team, R&D Center, GS Caltex Corporation, 104-4 Munji-dong, Yusung-gu, Daejeon 305-380, Korea 2Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Korea
sunwon@kaist.ac.kr
Korean Chemical Engineering Research, April 2013, 51(2), 226-232(7), 10.9713/kcer.2013.51.2.226 Epub 21 May 2013
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Abstract
부탄올을 생산하는 발효반응기에서는 아세톤, 부탄올 그리고 에탄올을 주로 생산하는 Clostridium acetobutylicum이 사용된다. 본 연구에서는 이 미생물을 이용한 발효공정의 개발을 위하여, Clostridium acetobutylicum ATCC824의 대사망의 동적 모델이 제안되었다. 많은 효소기반의 대사반응들로 구성된 대사망의 복잡성과 대사반응속도식의 비선형적 특성 때문에, 유전 알고리듬과 Levenberg-Marquardt 알고리듬이 결합된 효율적인 최적화 기법을 이용하여 회분식 발효반응기의 실험 결과값으로 58개의 반응속도상수들을 결정하였다. 그리고 이 반응속도상수 결정의 정확도를 제고하기 위하여, 유전자 조작을 통해 특정 대사경로를 차단한 미생물을 이용했을 때의 실험과 초기 글루코스의 농도를 다르게 한 실험들을 수행하여 개발된 대사망의 동적모델을 분석하였다. 결과적으로, 본 연구를 통해서 개발된 대사망 모델의 정확도를 확인하였고, 이를 활용하여 발효반응공정의 생산성 향상을 위한 적절한 클로스트리듐의 개발과 발효반응기의 최적화를 위한 연구에 기여할 수 있을 것으로 기대된다.
To produce biobutanol, fermentation processes using clostridia that mainly produce acetone, butanol and ethanol are used. In this work, a dynamic model describing the metabolic reactions in an acetone-butanol-ethanol (ABE)-producing clostridium, Clostridium acetobutylicum ATCC824, was proposed. To estimate the 58 kinetic parameters of the metabolic network model with experimental data obtained from a batch fermentor, we used an efficient optimization method combining a genetic algorithm and the Levenberg-Marquardt method because of the complexity of the metabolism of the clostridium. For the verification of the determined parameters, the developed metabolic model was evaluated by experiments where genetically modified clostridium was used and the initial concentration of glucose was changed. Consequently, we found that the developed kinetic model for the metabolic network was considered to describe the dynamic metabolic state of the clostridium sufficiently. Thus, this dynamic model for the metabolic reactions will contribute to designing the clostridium as well as the fermentor for higher productivity.
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