Optimization of chondroitin production in E. coli using genome scale models†

IF 3.2 3区 工程技术 Q2 CHEMISTRY, PHYSICAL
Márcia R. Couto, Joana L. Rodrigues, Adelaide Braga, Oscar Dias and Lígia R. Rodrigues
{"title":"Optimization of chondroitin production in E. coli using genome scale models†","authors":"Márcia R. Couto, Joana L. Rodrigues, Adelaide Braga, Oscar Dias and Lígia R. Rodrigues","doi":"10.1039/D3ME00199G","DOIUrl":null,"url":null,"abstract":"<p >Chondroitin is a natural occurring glycosaminoglycan with applications as a nutraceutical and pharmaceutical ingredient and can be extracted from animal tissues. Microbial chondroitin-like polysaccharides emerged as a safer and more sustainable alternative source. However, chondroitin titers using either natural or recombinant microorganisms are still far from meeting the increasing demand. The use of genome-scale models and computational predictions can assist the design of microbial cell factories with possible improved titers of these value-added compounds. Genome-scale models have been herein used for the first time to predict genetic modifications in <em>Escherichia coli</em> engineered strains that would potentially lead to improved chondroitin production. Additionally, using synthetic biology approaches, a pathway for producing chondroitin has been designed and engineered in <em>E. coli</em>. Afterwards, the most promising mutants identified based on bioinformatics predictions were constructed and evaluated for chondroitin production in flask fermentation. This resulted in the production of 118 mg L<small><sup>−1</sup></small> of extracellular chondroitin by overexpressing both superoxide dismutase (<em>sodA</em>) and a lytic murein transglycosylase (<em>mltB</em>). Then, batch and fed-batch fermentations at the bioreactor scale were also evaluated, in which the mutant overexpressing <em>mltB</em> led to an extracellular chondroitin production of 427 mg L<small><sup>−1</sup></small> and 535 mg L<small><sup>−1</sup></small>, respectively. The computational approach herein described identified several potential novel targets for improved chondroitin biosynthesis, which may ultimately lead to a more efficient production of this glycosaminoglycan.</p>","PeriodicalId":91,"journal":{"name":"Molecular Systems Design & Engineering","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/me/d3me00199g?page=search","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Systems Design & Engineering","FirstCategoryId":"5","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/me/d3me00199g","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Chondroitin is a natural occurring glycosaminoglycan with applications as a nutraceutical and pharmaceutical ingredient and can be extracted from animal tissues. Microbial chondroitin-like polysaccharides emerged as a safer and more sustainable alternative source. However, chondroitin titers using either natural or recombinant microorganisms are still far from meeting the increasing demand. The use of genome-scale models and computational predictions can assist the design of microbial cell factories with possible improved titers of these value-added compounds. Genome-scale models have been herein used for the first time to predict genetic modifications in Escherichia coli engineered strains that would potentially lead to improved chondroitin production. Additionally, using synthetic biology approaches, a pathway for producing chondroitin has been designed and engineered in E. coli. Afterwards, the most promising mutants identified based on bioinformatics predictions were constructed and evaluated for chondroitin production in flask fermentation. This resulted in the production of 118 mg L−1 of extracellular chondroitin by overexpressing both superoxide dismutase (sodA) and a lytic murein transglycosylase (mltB). Then, batch and fed-batch fermentations at the bioreactor scale were also evaluated, in which the mutant overexpressing mltB led to an extracellular chondroitin production of 427 mg L−1 and 535 mg L−1, respectively. The computational approach herein described identified several potential novel targets for improved chondroitin biosynthesis, which may ultimately lead to a more efficient production of this glycosaminoglycan.

Abstract Image

受邀为分子仿生工程特别论文集投稿:利用基因组规模模型优化大肠杆菌中软骨素的生产
软骨素是从动物组织中提取的一种天然糖胺聚糖,可用作营养保健品和药物成分。微生物类软骨素多糖是一种更安全、更可持续的替代来源。然而,利用天然或重组微生物生产的软骨素滴度仍远远不能满足日益增长的需求。利用基因组尺度模型和计算预测可以帮助设计微生物细胞工厂,从而提高这些高附加值化合物的滴度。本文首次使用基因组尺度模型来预测大肠杆菌工程菌株的基因修饰,这可能会提高软骨素的产量。此外,利用合成生物学方法,在大肠杆菌中设计并改造了生产软骨素的途径。随后,构建了根据生物信息学预测确定的最有前景的突变体,并对其在瓶式发酵中生产软骨素的情况进行了评估。通过过量表达超氧化物歧化酶(sodA)和溶菌性金霉素转糖基化酶(mltB),生产出 118 mg/L 的细胞外软骨素。然后,还评估了生物反应器规模的批量和饲料批量发酵,其中过表达 mltB 的突变体的细胞外软骨素产量分别为 427 毫克/升和 535 毫克/升。本文所述的计算方法确定了改善软骨素生物合成的几个潜在新靶标,这可能最终导致更高效地生产这种氨基糖。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Molecular Systems Design & Engineering
Molecular Systems Design & Engineering Engineering-Biomedical Engineering
CiteScore
6.40
自引率
2.80%
发文量
144
期刊介绍: Molecular Systems Design & Engineering provides a hub for cutting-edge research into how understanding of molecular properties, behaviour and interactions can be used to design and assemble better materials, systems, and processes to achieve specific functions. These may have applications of technological significance and help address global challenges.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信