In Silico-guided Metabolic Engineering of Bacillus Subtilis for Efficient Biosynthesis of Purine Nucleosides by Blocking the Key Backflow Nodes Article Swipe
Aihua Deng
,
Qidi Qiu
,
Qinyun Sun
,
Zhenxiang Chen
,
Junyue Wang
,
Yu Zhang
,
Shuwen Liu
,
Tingyi Wen
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-1091989/v1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-1091989/v1
Background: Purine nucleosides play essential roles in cellular physiological processes and have a wide range of applications in the fields of antitumor/antiviral drugs and food. However, microbial overproductions of purine nucleosides by de novo metabolic engineering have been a great challenge due to their strict and complex regulatory machinery involved in the biosynthetic pathways. Results: In this study, we designed an in silico -guided strategy for overproducing purine nucleosides based on the genome-scale metabolic network model in Bacillus subtilis . The metabolic flux was analyzed to predict two key backflow nodes Drm (Purine nucleotides toward PPP) and YwjH (PPP-EMP) for resolving the competitive relationship between biomass and purine nucleotides synthesis. In terms of the purine synthesis pathway, the first backflow node Drm was inactivated to block the degradation of purine nucleotides and greatly increased the inosine production to 13.98–14.47 g/L without affecting cell growth. Furthermore, releasing feedback inhibition of purine operon by promoter replacement further enhanced the accumulation of purine nucleotides. In terms of the central carbon metabolic pathways, deleting the second backflow node YwjH and overexpressing Zwf were combined to increase the inosine production to 22.01±1.18 g/L by enhancing the metabolic flow of PPP. Through switching on the flux node of the glucose-6- phosphate to PPP or EMP, the final inosine engineered strain produced up to 25.81±1.23 g/L of inosine by a pgi -based metabolic switch in shake-flask cultivation, suggesting the highest yield in de novo engineered inosine bacteria. Under the guidance of the in silico- designed strategy, a general chassis bacterium was generated for the first time to efficiently synthesize inosine, adenosine, guanosine, IMP, and GMP, providing the sufficient precursor for the synthesis of various purine intermediates. Conclusions: Overall, in silico -guided metabolic engineering successfully optimized the purine synthesis pathway by exploring the efficient targets, representing a superior strategy for efficient biosynthesis of the biotechnological products.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-1091989/v1
- https://www.researchsquare.com/article/rs-1091989/latest.pdf
- OA Status
- green
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3217662661
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3217662661Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-1091989/v1Digital Object Identifier
- Title
-
In Silico-guided Metabolic Engineering of Bacillus Subtilis for Efficient Biosynthesis of Purine Nucleosides by Blocking the Key Backflow NodesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2021Year of publication
- Publication date
-
2021-11-29Full publication date if available
- Authors
-
Aihua Deng, Qidi Qiu, Qinyun Sun, Zhenxiang Chen, Junyue Wang, Yu Zhang, Shuwen Liu, Tingyi WenList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-1091989/v1Publisher landing page
- PDF URL
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https://www.researchsquare.com/article/rs-1091989/latest.pdfDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.researchsquare.com/article/rs-1091989/latest.pdfDirect OA link when available
- Concepts
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Backflow, Bacillus subtilis, Blocking (statistics), In silico, Key (lock), Chemistry, Metabolic engineering, Purine, Computational biology, Biochemistry, Computer science, Biology, Bacteria, Engineering, Enzyme, Computer network, Gene, Genetics, Computer security, Mechanical engineering, InletTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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27Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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