Evidence map›Paper›PMID 41002296›Full record

ReviewBiosensors2025

Synthetic Gene Circuits Enable Sensing in Engineered Living Materials.

Yaxuan Cai, Yujie Wang, Shengbiao Hu

Abstract readReview
In one paragraph

Review in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Review
  6. Designing Neural Dynamics: From Digital Twin Modeling to Regeneration.International journal of molecular sciences · 2025
    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

3 authors.

Yaxuan CaiHunan Provincial Key Laboratory of Microbial Molecular Biology, College of Life Science, Hunan Normal University, No. 36 Lushan Street, Changsha 410081, China.ORCID 0009-0007-9380-038X
Yujie WangDepartment of Pharmaceutical Engineering, China Pharmaceutical University, No. 639 Longmian Avenue, Nanjing 211198, China.
Shengbiao HuHunan Provincial Key Laboratory of Microbial Molecular Biology, College of Life Science, Hunan Normal University, No. 36 Lushan Street, Changsha 410081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Engineered living materials (ELMs) integrate living cells-such as bacteria, yeast, or mammalian cells-with synthetic matrices to create responsive, adaptive systems for sensing and actuation. Among ELMs, those endowed with sensing capabilities are gaining increasing attention for applications in environmental monitoring, biomedicine, and smart infrastructure. Central to these sensing functions are synthetic gene circuits, which enable cells to detect and respond to specific signals. This mini-review focuses on recent advances in sensing ELMs empowered by synthetic gene circuits. Here, we highlight how rationally designed genetic circuits enable living materials to sense and respond to diverse inputs-including environmental chemicals, light, heat, and mechanical loadings-via programmable signal transduction and tailored output behaviors. Input signals are classified by their source and physicochemical properties, including synthetic inducers, environmental chemicals, light, thermal, mechanical, and electrical signals. Particular emphasis is placed on the integration of genetically engineered microbial cells with hydrogels and other functional scaffolds to construct robust and tunable sensing platforms. Finally, we discuss the current challenges and future opportunities in this rapidly evolving field, providing insights to guide the rational design of next-generation sensing ELMs.

Indexed as

Biosensing TechniquesGene Regulatory NetworksGenetic EngineeringSynthetic Biologybiosensingengineered living materialsgene circuitssignal transduction

Identifiers

PMID41002296
PMCPMC12467368

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.