4.7 Article

Lacto-N-biose synthesis via a modular enzymatic cascade with ATP regeneration

期刊

ISCIENCE
卷 24, 期 3, 页码 -

出版社

CELL PRESS
DOI: 10.1016/j.isci.2021.102236

关键词

-

资金

  1. National Key R&D Program of China [2018YFA090010]
  2. China Postdoctoral Science Foundation Funded Project [2018M642645]
  3. Qingdao Postdoctoral Application Research Project [2018124]
  4. Major Program of Shandong Province Natural Science Foundation [ZR2018ZB0209]
  5. State Key Laboratory ofMicrobial Technology Open Projects Fund

向作者/读者索取更多资源

A synergistic strategy utilizing an in vitro multienzyme cascade system was developed to produce LNB, increasing the conversion ratio and yield significantly under optimal conditions. The integration of ATP regeneration and Pi alleviation also decreased the energy required for the reaction by 540 KJ/mol. This approach not only paved the way for producing LNB, but also showed potential for facilitating other chemicals with multienzyme cascades.
Human milk oligosaccharides (HMOs), the third most abundant solid component of human milk, are reported to be beneficial to infant health. The biosynthesis of lacto-N-biose (LNB), the building block for HMOs, suffers from excessive addition of cofactors and intermediate inhibition. Here, we developed an in vitro multienzyme cascade composed of LNB module, ATP regeneration, and pyruvate oxidase-driven phosphate recycling to produce LNB. The integration between ATP regeneration and Pi alleviation increased the LNB conversion ratio and resulted in a Delta G'degrees decrease of 540 KJ/mol. Under optimal conditions, the LNB conversion ratio was improved from 0.34 to 0.83 mol/mol GlcNAc and the ATP addition decreased to 50%. Finally, 0.96 mol/mol GlcNAc and 71.6 mg LNB g(-1) GlcNAc h(-1) of LNB yield was achieved in a 100-mL reaction system. The synergistic strategy not only paves the way for producing LNB but also facilitates other chemicals with multienzyme cascades.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据