Evidence map›Paper›PMID 41683183›Full record

ReviewFoods (Basel, Switzerland)2026

Engineering Allosteric Transcription Factor-Based Biosensors: Advances and Prospects for Modern Food Contaminant Monitoring.

Xinyue Lan, Ziying Zhou, Yanger Liu, Xiangyang Li, Wenbiao Shi, Longjiao Zhu, Wentao Xu

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Xinyue LanFood Laboratory of Zhongyuan, Key Laboratory of Precision Nutrition and Food Quality, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Safety Assessment of Genetically, Modified Organism (Food Safety), Department of Nutrition and Health, China Agricultural University, Beijing 100193, China.
Ziying ZhouBeijing Laboratory of Food Quality and Safety, Beijing Key Laboratory of Agricultural Product Detection and Control of Spoilage Organisms and Pesticide Residue, Key Laboratory of Agricultural Product Processing and Quality Control (Co-construction by Ministry and Province), Faculty of Food Science and Engineering, Beijing University of Agriculture, Beijing 102206, China.
Yanger LiuState Key Laboratory for Quality and Safety of Agro-Products, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Haidian, Beijing 100081, China.
Xiangyang LiBeijing Laboratory of Food Quality and Safety, Beijing Key Laboratory of Agricultural Product Detection and Control of Spoilage Organisms and Pesticide Residue, Key Laboratory of Agricultural Product Processing and Quality Control (Co-construction by Ministry and Province), Faculty of Food Science and Engineering, Beijing University of Agriculture, Beijing 102206, China.
Wenbiao ShiFood Laboratory of Zhongyuan, Key Laboratory of Precision Nutrition and Food Quality, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Safety Assessment of Genetically, Modified Organism (Food Safety), Department of Nutrition and Health, China Agricultural University, Beijing 100193, China.ORCID 0000-0001-7724-9582
Longjiao ZhuFood Laboratory of Zhongyuan, Key Laboratory of Precision Nutrition and Food Quality, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Safety Assessment of Genetically, Modified Organism (Food Safety), Department of Nutrition and Health, China Agricultural University, Beijing 100193, China.
Wentao XuFood Laboratory of Zhongyuan, Key Laboratory of Precision Nutrition and Food Quality, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Safety Assessment of Genetically, Modified Organism (Food Safety), Department of Nutrition and Health, China Agricultural University, Beijing 100193, China.ORCID 0000-0002-8572-8257

Funding

Beijing Innovation Consortium of Agriculture Research System BAIC01National Key Research and Development Program 2023YFF1103704
6 · The paper itself

Abstract

Allosteric transcription factor (aTF)-based in vitro biosensors constitute a class of detection tools formed by the functional coupling of the ligand-binding domain of aTFs with a reporter system. Owing to advantages such as high specificity and sensitivity, these biosensors have emerged as a research hotspot in the field of modern food contaminant monitoring. Our work centers on the core aspect of engineering design and systematically elaborates on the modular design strategies for aTF-based in vitro biosensors, with a focus on the design principles of the molecular recognition system, signal amplification strategies, signal output systems, and sensing systems. Furthermore, the article summarizes the advances in the application of aTF biosensors for detecting various typical food contaminants and analyzes their performance advantages. Finally, in light of existing technical limitations, it prospectively discusses future directions for enhancing specificity, improving stability, and promoting commercial applications, aiming to provide a theoretical reference and application guidance for transitioning this technology from laboratory platforms to on-site real-time monitoring.

Indexed as

allosteric transcription factorconstruction strategyfood safety detectionin vitro biosensorsrecognition element

Identifiers

PMID41683183
PMCPMC12897369

What OpenQuestion holds

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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.