• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Biotechnology Progress >Exploring De Novo metabolic pathways from pyruvate to propionic acid
【24h】

Exploring De Novo metabolic pathways from pyruvate to propionic acid

机译：探索从丙酮酸到丙酸的De Novo代谢途径

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Industrial biotechnology provides an efficient, sustainable solution for chemical production. However, designing biochemical pathways based solely on known reactions does not exploit its full potential. Enzymes are known to accept non-native substrates, which may allow novel, advantageous reactions. We have previously developed a computational program named Biological Network Integrated Computational Explorer (BNICE) to predict promiscuous enzyme activities and design synthetic pathways, using generalized reaction rules curated from biochemical reaction databases. Here, we use BNICE to design pathways synthesizing propionic acid from pyruvate. The currently known natural pathways produce undesirable by-products lactic acid and succinic acid, reducing their economic viability. BNICE predicted seven pathways containing four reaction steps or less, five of which avoid these by-products. Among the 16 biochemical reactions comprising these pathways, 44% were validated by literature references. More than 28% of these known reactions were not in the BNICE training dataset, showing that BNICE was able to predict novel enzyme substrates. Most of the pathways included the intermediate acrylic acid. As acrylic acid bioproduction has been well advanced, we focused on the critical step of reducing acrylic acid to propionic acid. We experimentally validated that Oye2p from Saccharomyces cerevisiae can catalyze this reaction at a slow turnover rate (10(-3) s(-1)), which was unknown to occur with this enzyme, and is an important finding for further propionic acid metabolic engineering. These results validate BNICE as a pathway-searching tool that can predict previously unknown promiscuous enzyme activities and show that computational methods can elucidate novel biochemical pathways for industrial applications. (c) 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:303-311, 2016
机译：工业生物技术为化学生产提供了高效，可持续的解决方案。但是，仅根据已知反应设计生化途径并不能充分发挥其潜力。已知酶会接受非天然底物，这可能会导致新的有利反应。我们以前已经开发了一个计算程序，名为Biological Network Integrated Computational Explorer（BNICE），可使用从生化反应数据库中筛选的广义反应规则来预测混杂酶的活性并设计合成途径。在这里，我们使用BNICE设计从丙酮酸合成丙酸的途径。当前已知的天然途径产生不希望的副产物乳酸和琥珀酸，降低了它们的经济可行性。 BNICE预测了七个包含四个或更少反应步骤的途径，其中五个避免了这些副产物。在包含这些途径的16种生化反应中，有44％已通过文献引用得到验证。这些已知反应中有超过28％不在BNICE训练数据集中，表明BNICE能够预测新型酶底物。大多数途径包括中间体丙烯酸。随着丙烯酸生物生产的发展，我们将重点放在了将丙烯酸还原为丙酸的关键步骤上。我们通过实验验证了酿酒酵母中的Oye2p可以以较低的周转率（10（-3）s（-1））催化该反应，这是该酶未知的反应，对于进一步的丙酸代谢工程来说是重要的发现。这些结果验证了BNICE作为一种途径搜索工具，可以预测以前未知的混杂酶活性，并表明计算方法可以阐明用于工业应用的新型生化途径。 （c）2016美国化学工程师学会生物技术学会。 Prog。，32：303-311，2016

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号