Evidence map›Paper›PMID 39628519›Full record

ReviewEngineering microbiology2023

Recent advances in screening amino acid overproducers.

Junkai Tuo, Said Nawab, Xiaoyan Ma, Yi-Xin Huo

Erratum issuedAbstract readReview
In one paragraph

Review in Engineering microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Metabolic engineering: Tools and applications.Engineering microbiology · 2023
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Junkai TuoKey Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
Said NawabKey Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
Xiaoyan MaKey Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
Yi-Xin HuoKey Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, Beijing 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial fermentation has contributed to 80% of global amino acid production. The key to microbial fermentation is to obtain fermentation strains with high performance to produce target amino acids with a high yield. These strains are primarily derived from screening enormous mutant libraries. Therefore, a high-throughput, rapid, accurate, and universal screening strategy for amino acid overproducers has become a guarantee for obtaining optional amino acid overproducers. In recent years, the rapid development of various novel screening strategies has been witnessed. However, proper analysis and discussion of these innovative technologies are lacking. Here we systematically reviewed recent advances in screening strategies: the auxotrophic-based strategy, the biosensor-based strategy, and the latest translation-based screening strategy. The design principle, application scope, working efficiency, screening accuracy, and universality of these strategies were discussed in detail. The potential for screening nonstandard amino acid overproducers was also analyzed. Guidance for the improvement of future screening strategies is provided in this review, which could expedite the reconstruction of amino acid overproducers and help promote the fermentation industry to reduce cost, increase yield, and improve quality.

Indexed as

BiosensorMicrobial cell factoryRare codontRNA

Identifiers

PMID39628519
PMCPMC11610995

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.