Improved vanillin production in baker's yeast through in silico design

生物信息学 香兰素 酵母 生产(经济) 生化工程 生物技术 生物 计算生物学 生物化学 工程类 基因 宏观经济学 经济
作者
Ana Rita Brochado,Claudia Matos,Birger Lindberg Møller,Jörgen Hansen,Uffe Hasbro Mortensen,Kiran Raosaheb Patil
出处
期刊:Microbial Cell Factories [Springer Nature]
卷期号:9 (1) 被引量:234
标识
DOI:10.1186/1475-2859-9-84
摘要

Abstract Background Vanillin is one of the most widely used flavouring agents, originally obtained from cured seed pods of the vanilla orchid Vanilla planifolia . Currently vanillin is mostly produced via chemical synthesis. A de novo synthetic pathway for heterologous vanillin production from glucose has recently been implemented in baker's yeast, Saccharamyces cerevisiae . In this study we aimed at engineering this vanillin cell factory towards improved productivity and thereby at developing an attractive alternative to chemical synthesis. Results Expression of a glycosyltransferase from Arabidopsis thaliana in the vanillin producing S. cerevisiae strain served to decrease product toxicity. An in silico metabolic engineering strategy of this vanillin glucoside producing strain was designed using a set of stoichiometric modelling tools applied to the yeast genome-scale metabolic network. Two targets ( PDC1 and GDH1 ) were selected for experimental verification resulting in four engineered strains. Three of the mutants showed up to 1.5 fold higher vanillin β-D-glucoside yield in batch mode, while continuous culture of the Δpdc1 mutant showed a 2-fold productivity improvement. This mutant presented a 5-fold improvement in free vanillin production compared to the previous work on de novo vanillin biosynthesis in baker's yeast. Conclusion Use of constraints corresponding to different physiological states was found to greatly influence the target predictions given minimization of metabolic adjustment (MOMA) as biological objective function. In vivo verification of the targets, selected based on their predicted metabolic adjustment, successfully led to overproducing strains. Overall, we propose and demonstrate a framework for in silico design and target selection for improving microbial cell factories.

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
木木康完成签到,获得积分10
刚刚
m李完成签到 ,获得积分10
1秒前
dxs完成签到,获得积分10
1秒前
fly发布了新的文献求助30
2秒前
2秒前
潇洒冰蓝发布了新的文献求助10
4秒前
4秒前
不喝牛奶的猫完成签到,获得积分10
4秒前
三一完成签到 ,获得积分10
5秒前
拼搏菲鹰完成签到,获得积分10
5秒前
7秒前
XT完成签到 ,获得积分10
8秒前
儒雅鹤轩完成签到,获得积分10
9秒前
10秒前
晚风发布了新的文献求助10
11秒前
HY完成签到 ,获得积分10
11秒前
小二郎应助木木采纳,获得10
12秒前
雨寒完成签到 ,获得积分10
12秒前
DafeiWu完成签到,获得积分20
12秒前
薯条头子发布了新的文献求助60
13秒前
13秒前
Nelocope关注了科研通微信公众号
13秒前
居居子完成签到,获得积分10
13秒前
Dxy-TOFA完成签到,获得积分10
13秒前
没有名字完成签到 ,获得积分10
14秒前
15秒前
15秒前
ss发布了新的文献求助10
15秒前
顾矜应助不喝牛奶的猫采纳,获得30
15秒前
haha完成签到,获得积分10
17秒前
卓延恶发布了新的文献求助10
17秒前
17秒前
17秒前
勤劳觅风完成签到,获得积分10
18秒前
FashionBoy应助小牛采纳,获得30
19秒前
SCI完成签到,获得积分10
19秒前
19秒前
可爱归尘完成签到,获得积分10
21秒前
ZYA1999完成签到,获得积分10
21秒前
Frankll发布了新的文献求助10
21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
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Polymorphism and polytypism in crystals 1000
Social Cognition: Understanding People and Events 800
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 6028750
求助须知:如何正确求助?哪些是违规求助? 7695161
关于积分的说明 16187706
捐赠科研通 5175940
什么是DOI,文献DOI怎么找? 2769818
邀请新用户注册赠送积分活动 1753236
关于科研通互助平台的介绍 1639005