• 한국미생물생명공학회:학술대회논문집
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• 한국미생물생명공학회 2004년도 Annual Meeting BioExibition International Symposium
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• pp.60-61
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• 2004

Metabolic engineering is now a well established discipline, used extensively to determine and execute rational strategies of strain development to improve the performance of micro-organisms employed in industrial fermentations. The basic principle of this approach is that performance of the microbial catalyst should be adequately characterised metabolically so as to clearlyidentify the metabolic network constraints, thereby identifying the most probable targets for genetic engineering and the extent to which improvements can be realistically achieved. In order to harness correctly this potential, it is clear that the physiological analysis of each strain studied needs to be undertaken under conditions as close as possible to the physico-chemical environment in which the strain evolves within the full-scale process. Furthermore, this analysis needs to be undertaken throughoutthe entire fermentation so as to take into account the changing environment in an essentially dynamic situation in which metabolic stress is accentuated by the microbial activity itself, leading to increasingly important stress response at a metabolic level. All too often these industrial fermentation constraints are overlooked, leading to identification of targets whose validity within the industrial context is at best limited. Thus the conceptual error is linked to experimental design rather than inadequate methodology. New tools are becoming available which open up new possibilities in metabolic engineering and the characterisation of complex metabolic networks. Traditionally metabolic analysis was targeted towards pre-identified genes and their corresponding enzymatic activities within pre-selected metabolic pathways. Those pathways not included at the onset were intrinsically removed from the network giving a fundamentally localised vision of pathway functionality. New tools from genome research extend this reductive approach so as to include the global characteristics of a given biological model which can now be seen as an integrated functional unit rather than a specific sub-group of biochemical reactions, thereby facilitating the resolution of complexnetworks whose exact composition cannot be estimated at the onset. This global overview of whole cell physiology enables new targets to be identified which would classically not have been suspected previously. Of course, as with all powerful analytical tools, post-genomic technology must be used carefully so as to avoid expensive errors. This is not always the case and the data obtained need to be examined carefully to avoid embarking on the study of artefacts due to poor understanding of cell biology. These basic developments and the underlying concepts will be illustrated with examples from the author's laboratory concerning the industrial production of commodity chemicals using a number of industrially important bacteria. The different levels of possibleinvestigation and the extent to which the data can be extrapolated will be highlighted together with the extent to which realistic yield targets can be attained. Genetic engineering strategies and the performance of the resulting strains will be examined within the context of the prevailing experimental conditions encountered in the industrial fermentor. Examples used will include the production of amino acids, vitamins and polysaccharides. In each case metabolic constraints can be identified and the extent to which performance can be enhanced predicted

• 공업화학
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• 제18권6호
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• pp.643-649
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• 2007

부탄올의 구조이성질체(n-, iso-, sec-, tert-butanol) 와 n-부티르산에 대한 리파아제 효소.촉매 에스테르화 반응이 초임계 이산화탄소 조건 하에서 수행되었다. 본 실험은 교반속도 150 rpm, 반응 온도 323.15 K, 반응 압력 150 bar의 조건으로 고압반응기에서 5 h 동안 수행하였다. 실험에 사용된 리파아제는 Candida Antarctica lipase B (CALB)이다. 실험 결과는 HP-INNOWax 컬럼을 이용하여 FID (Flame Ionization detector)가 장착된 기체 크로마토그래피(Gas Chromatography, GC)를 이용하여 분석하였다. 반응 후 생성물의 전환률과 반응의 경향성을 분자동역학 시뮬레이션을 이용하여 예측된 결과와 정성적으로 비교하였다. 경쟁적인 저해반응이 포함된 Ping-Pong Bi-Bi 메커니즘을 기초로 하여, 반응의 각 단계를 적용하여 구조 최적화를 하였고 이를 이용해 전이상태의 에너지를 구하여 반응의 경향성을 예측하였다. 생성되는 에스테르 이성질체의 구조적 선호도는 분자동역학 시뮬레이션을 통하여 분석하였다. 이러한 방법의 개발은 앞으로 컴퓨터를 이용한 효소 반응의 설계에 유용하게 사용될 수 있을 것이다.