Evidence map›Paper›PMID 35158314›Full record

ReviewCurrent opinion in biotechnology2022

Biosensor-enabled pathway optimization in metabolic engineering.

Yuxi Teng, Jianli Zhang, Tian Jiang, Yusong Zou, Xinyu Gong, Yajun Yan

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Current opinion in biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Engineering theACS synthetic biology · 2026
    Article
  2. Development of a highly efficientSynthetic and systems biotechnology · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Advancing lignocellulosic conversion though biosensor-enabled metabolic engineering.Green chemistry : an international journal and green chemistry resource : GC · 2025
    Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
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  18. Article
  19. Article
  20. 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.

Yuxi TengSchool of Chemical, Materials, and Biomedical Engineering, College of Engineering, The University of Georgia, Athens, GA 30602, USA.
Jianli ZhangSchool of Chemical, Materials, and Biomedical Engineering, College of Engineering, The University of Georgia, Athens, GA 30602, USA.
Tian JiangSchool of Chemical, Materials, and Biomedical Engineering, College of Engineering, The University of Georgia, Athens, GA 30602, USA.
Yusong ZouSchool of Chemical, Materials, and Biomedical Engineering, College of Engineering, The University of Georgia, Athens, GA 30602, USA.
Xinyu GongSchool of Chemical, Materials, and Biomedical Engineering, College of Engineering, The University of Georgia, Athens, GA 30602, USA.
Yajun YanSchool of Chemical, Materials, and Biomedical Engineering, College of Engineering, The University of Georgia, Athens, GA 30602, USA. Electronic address: yajunyan@uga.edu.

Funding

Engineering Dynamic Control of Natural Product Biosynthesis in BacteriaR35GM128620 · NIGMS · UNIVERSITY OF GEORGIA · PI Yajun Yan · 2018 to 2026
$3.0M
NIGMS NIH HHS R35 GM128620
6 · The paper itself

Abstract

Microbes can convert inexpensive renewable substrates to valuable metabolites by their natural metabolic pathways. To maximize the productivity, the pathways yet require further optimization, which remains challenging for our limited knowledge of complex biology. Genetically encoded biosensors are able to detect metabolite concentrations or environmental changes and transfer these inputs to measurable or actionable outputs, thus providing enabling regulation and monitoring tools for complicated pathway optimization. Here, we review recent advances in biosensor-mediated dynamic regulation and strain screening for the highest microbial production of diverse desirable products.

Indexed as

Biosensing TechniquesMetabolic EngineeringMetabolic Networks and Pathways

Identifiers

PMID35158314
PMCPMC9177593

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.