Evidence map›Paper›PMID 36577997›Full record

ArticleMicrobial cell factories2022

Construction of cell factory through combinatorial metabolic engineering for efficient production of itaconic acid.

Jiao Feng, Chunqiu Li, Hao He, Sheng Xu, Xin Wang, Kequan Chen

Open access · goldAbstract read
In one paragraph

Article in Microbial cell factories, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
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

6 citing papers in PubMed, 16 citations in OpenAlex.

  1. Role of itaconate in intestinal disease (Review).International journal of molecular medicine · 2026
    Review
  2. Article
  3. Article
  4. Metabolic Engineering ofACS omega · 2023
    Article
  5. Article
  6. Article
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

6 authors at 2 institutions in 1 country.

Jiao FengState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, No. 30 Puzhu Road(S), Nanjing, 211816, People's Republic of China.
Chunqiu LiState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, No. 30 Puzhu Road(S), Nanjing, 211816, People's Republic of China.
Hao HePetrochemical Research Insitute of Petrochina Co. Ltd., Beijing, 102206, People's Republic of China. hehao010@petrochina.com.cn.
Sheng XuState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, No. 30 Puzhu Road(S), Nanjing, 211816, People's Republic of China. henryxu@njtech.edu.cn.
Xin WangState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, No. 30 Puzhu Road(S), Nanjing, 211816, People's Republic of China.
Kequan ChenState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, No. 30 Puzhu Road(S), Nanjing, 211816, People's Republic of China.
Nanjing Tech University · CNBeijing Institute of Petrochemical Technology · CN

Funding

Joint Funds of the National Natural Science Foundation of China U21B2097National Science Foundation of Young Scientists of China 21908099National Science Foundation of Young Scientists of China 22108123
6 · The paper itself

Abstract

backgroundItaconic acid, an unsaturated C5 dicarbonic acid, has significant market demand and prospects. It has numerous biological functions, such as anti-cancer, anti-inflammatory, and anti-oxidative in medicine, and is an essential renewable platform chemical in industry. However, the development of industrial itaconic acid production by Aspergillus terreus, the current standard production strain, is hampered by the unavoidable drawbacks of that species. Developing a highly efficient cell factory is essential for the sustainable and green production of itaconic acid.

resultsThis study employed combinatorial engineering strategies to construct Escherichia coli cells to produce itaconic acid efficiently. Two essential genes (cis-aconitate decarboxylase (CAD) encoding gene cadA and aconitase (ACO) encoding gene acn) employed various genetic constructs and plasmid combinations to create 12 recombination E. coli strains to be screened. Among them, E. coli BL-CAC exhibited the highest titer with citrate as substrate, and the induction and reaction conditions were further systematically optimized. Subsequently, employing enzyme evolution to optimize rate-limiting enzyme CAD and synthesizing protein scaffolds to co-localize ACO and CAD were used to improve itaconic acid biosynthesis efficiency. Under the optimized reaction conditions combined with the feeding control strategy, itaconic acid titer reached 398.07 mM (51.79 g/L) of engineered E. coli BL-CAR470E-DS/A-CS cells as a catalyst with the highest specific production of 9.42 g/g

conclusionsThe excellent catalytic performance per unit biomass shows the potential for high-efficiency production of itaconic acid and effective reduction of catalytic cell consumption. This study indicates that it is necessary to continuously explore engineering strategies to develop high-performance cell factories to break through the existing bottleneck and achieve the economical commercial production of itaconic acid.

Indexed as

Escherichia coliMetabolic EngineeringAconitate HydrataseSuccinatesAconitate Hydrataseitaconic acidSuccinatesE. coli catalysisEnzyme evolutionItaconic acidPathway optimizationProtein scaffolds

Identifiers

PMID36577997
PMCPMC9798595
OpenAlexW4313339542

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.