Evidence map›Paper›PMID 39451669›Full record

ArticleBiosensors2024

High Throughput Screening of Transcription Factor LysG for Constructing a Better Lysine Biosensor.

Qinggang Li, Haojie Ren, Zhenjiang Liao, Shuchang Xia, Xue Sun

Abstract read
In one paragraph

Article in Biosensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

5 authors.

Qinggang LiKey Laboratory of Industrial Fermentation Microbiology of the Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, College of Biotechnology, Tianjin University of Science and Technology, National Engineering Laboratory for Industrial Enzymes, Tianjin 300457, China.
Haojie RenKey Laboratory of Industrial Fermentation Microbiology of the Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, College of Biotechnology, Tianjin University of Science and Technology, National Engineering Laboratory for Industrial Enzymes, Tianjin 300457, China.
Zhenjiang LiaoKey Laboratory of Industrial Fermentation Microbiology of the Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, College of Biotechnology, Tianjin University of Science and Technology, National Engineering Laboratory for Industrial Enzymes, Tianjin 300457, China.
Shuchang XiaKey Laboratory of Industrial Fermentation Microbiology of the Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, College of Biotechnology, Tianjin University of Science and Technology, National Engineering Laboratory for Industrial Enzymes, Tianjin 300457, China.
Xue SunKey Laboratory of Industrial Fermentation Microbiology of the Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, College of Biotechnology, Tianjin University of Science and Technology, National Engineering Laboratory for Industrial Enzymes, Tianjin 300457, China.

Funding

China Postdoctoral Science Foundation 2023M732615Tianjin Graduate Research and Innovation Project 2022BKY134
6 · The paper itself

Abstract

The biosensors based on transcription factors (TFs) are widely used in high throughput screening of metabolic overproducers. The unsatisfactory performances (narrow detection and dynamic ranges) of biosensors limit their practical application and need more improvement. In this study, using the TF LysG (sensing lysine) as an example, a biosensor optimization method was constructed by growth-coupled screening of TF random mutant libraries. The better the performance of the biosensor, the faster the strain grows under screening pressure. A LysG

Indexed as

Biosensing TechniquesLysineTranscription FactorsEscherichia coliHigh-Throughput Screening AssaysLysineTranscription Factorsbiosensorhigh throughput screeningLysGtranscription factors

Identifiers

PMID39451669
PMCPMC11506072

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.