Evidence map›Paper›PMID 40901576›Full record

ReviewChem & bio engineering2025

Combing Directed Enzyme Evolution with Metabolic Engineering to Develop Efficient Microbial Cell Factories.

Yuyao Ren, Ewelina Celińska, Peng Cai, Yongjin J Zhou

Abstract readReview
In one paragraph

Review in Chem & bio engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Development of Bacillus subtilis cell factories for nutraceuticals production.World journal of microbiology & biotechnology · 2026
    Review
  4. 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

4 authors.

Yuyao RenDivision of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
Ewelina CelińskaDepartment of Biotechnology and Food Microbiology, Poznan University of Life Sciences, 60-637 Poznań, Poland.
Peng CaiDivision of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.ORCID https://orcid.org/0000-0001-5761-6744
Yongjin J ZhouDivision of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.ORCID https://orcid.org/0000-0002-2369-3079

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The booming field of synthetic biology and metabolic engineering provides promising approaches for sustainable manufacturing of chemicals from renewable feedstocks with microbial cell factories. Classical metabolic engineering strategies mainly focus on altering gene expression levels and enzyme concentrations to improve the metabolic fluxes of specific pathways. However, the impact and limitations of enzyme properties, which are usually ignored in classical metabolic engineering efforts, can hinder further optimization of microbial cell factories. Protein engineering and directed evolution are powerful tools for modifying proteins to achieve desirable properties, and they have been integrated into metabolic engineering efforts to build highly efficient metabolic pathways and optimal industrial chassis. In this review, we present traditional and data-driven strategies and techniques of directed evolution, including random library design, semirational design, smart library design, and

Indexed as

artificial intelligencedirected evolutionin vivo evolutionmetabolic engineeringProtein engineering

Identifiers

PMID40901576
PMCPMC12400123

What OpenQuestion holds

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Registered trials

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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.