Cell factories for biosynthesis of D-glucaric acid: a fusion of static and dynamic strategies.

Junping Zhou, Yinan Xue, Zheng Zhang, Yihong Wang, Anyi Wu, Xin Gao, Zhiqiang Liu, Yuguo Zheng

Abstract readReview

In one paragraph

Review in World journal of microbiology & biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Junping ZhouThe National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, 310014, China.

Yinan XueKey Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, 310014, China.

Zheng ZhangKey Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, 310014, China.

Yihong WangKey Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, 310014, China.

Anyi WuKey Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, 310014, China.

Xin GaoKey Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, 310014, China.

Zhiqiang LiuThe National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, 310014, China. microliu@zjut.edu.cn.

Yuguo ZhengThe National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, 310014, China.

Funding

National Natural Science Foundation of China 32101170Natural Science Foundation of Zhejiang Province LQ22C010001

6 · The paper itself

Abstract

D-glucaric acid is an important organic acid with numerous applications in therapy, food, and materials, contributing significantly to its substantial market value. The biosynthesis of D-glucaric acid (GA) from renewable sources such as glucose has garnered significant attention due to its potential for sustainable and cost-effective production. This review summarizes the current understanding of the cell factories for GA production in different chassis strains, from static to dynamic control strategies for regulating their metabolic networks. We highlight recent advances in the optimization of D-glucaric acid biosynthesis, including metabolic dynamic control, alternative feedstocks, metabolic compartments, and so on. Additionally, we compare the differences between different chassis strains and discuss the challenges that each chassis strain must overcome to achieve highly efficient GA productions. In this review, the processes of engineering a desirable cell factory for highly efficient GA production are just like an epitome of metabolic engineering of strains for chemical biosynthesis, inferring general trends for industrial chassis strain developments.

Indexed as

Glucaric AcidMetabolic EngineeringMetabolic Networks and PathwaysGlucoseIndustrial MicrobiologyGlucaric AcidGlucoseCell factoryD-glucaric acidDynamic controlMetabolic engineering

Identifiers

PMID39112688

DOI10.1016/j.ymben.2018.08.005

What Socratic holds

Textmetadata

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.