In silico metabolic engineering of Clostridium ljungdahlii for synthesis gas fermentation

代谢工程 合成气 发酵 化学 生物信息学 通量平衡分析 梭菌 生物化学 生化工程 生物 细菌 遗传学 工程类 基因 催化作用
作者
Jin Chen,Michael A. Henson
出处
期刊:Metabolic Engineering [Elsevier]
卷期号:38: 389-400 被引量:39
标识
DOI:10.1016/j.ymben.2016.10.002
摘要

Synthesis gas fermentation is one of the most promising routes to convert synthesis gas (syngas; mainly comprised of H2 and CO) to renewable liquid fuels and chemicals by specialized bacteria. The most commonly studied syngas fermenting bacterium is Clostridium ljungdahlii, which produces acetate and ethanol as its primary metabolic byproducts. Engineering of C. ljungdahlii metabolism to overproduce ethanol, enhance the synthesize of the native byproducts lactate and 2,3-butanediol, and introduce the synthesis of non-native products such as butanol and butyrate has substantial commercial value. We performed in silico metabolic engineering studies using a genome-scale reconstruction of C. ljungdahlii metabolism and the OptKnock computational framework to identify gene knockouts that were predicted to enhance the synthesis of these native products and non-native products, introduced through insertion of the necessary heterologous pathways. The OptKnock derived strategies were often difficult to assess because increase product synthesis was invariably accompanied by decreased growth. Therefore, the OptKnock strategies were further evaluated using a spatiotemporal metabolic model of a syngas bubble column reactor, a popular technology for large-scale gas fermentation. Unlike flux balance analysis, the bubble column model accounted for the complex tradeoffs between increased product synthesis and reduced growth rates of engineered mutants within the spatially varying column environment. The two-stage methodology for deriving and evaluating metabolic engineering strategies was shown to yield new C. ljungdahlii gene targets that offer the potential for increased product synthesis under realistic syngas fermentation conditions.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Magnolia关注了科研通微信公众号
刚刚
1秒前
小米饭完成签到,获得积分10
1秒前
周周发布了新的文献求助10
1秒前
Magnolia发布了新的文献求助10
2秒前
NexusExplorer应助细腻的易真采纳,获得10
2秒前
2秒前
量子星尘发布了新的文献求助10
3秒前
3秒前
明哲派完成签到,获得积分10
4秒前
充电宝应助Enticed采纳,获得10
4秒前
4秒前
向日葵班第一深情完成签到,获得积分10
4秒前
微瑕发布了新的文献求助10
4秒前
5秒前
传奇3应助科研通管家采纳,获得10
5秒前
大模型应助科研通管家采纳,获得10
5秒前
5秒前
5秒前
5秒前
lyw完成签到 ,获得积分10
5秒前
5秒前
iyoi应助科研通管家采纳,获得10
5秒前
5秒前
李1应助科研通管家采纳,获得10
5秒前
充电宝应助科研通管家采纳,获得10
5秒前
所所应助科研通管家采纳,获得10
5秒前
今后应助科研通管家采纳,获得10
5秒前
5秒前
李爱国应助科研通管家采纳,获得10
5秒前
5秒前
小二郎应助科研通管家采纳,获得10
6秒前
6秒前
6秒前
Akim应助科研通管家采纳,获得10
6秒前
隐形曼青应助科研通管家采纳,获得10
6秒前
6秒前
奋斗发布了新的文献求助20
6秒前
深情安青应助科研通管家采纳,获得10
6秒前
Hello应助科研通管家采纳,获得10
6秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Relation between chemical structure and local anesthetic action: tertiary alkylamine derivatives of diphenylhydantoin 1000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
Principles of town planning : translating concepts to applications 500
Iron‐Sulfur Clusters: Biogenesis and Biochemistry 400
Healable Polymer Systems: Fundamentals, Synthesis and Applications 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6071612
求助须知:如何正确求助?哪些是违规求助? 7903118
关于积分的说明 16340519
捐赠科研通 5211885
什么是DOI,文献DOI怎么找? 2787609
邀请新用户注册赠送积分活动 1770370
关于科研通互助平台的介绍 1648148