Evidence map›Paper›PMID 41745292›Full record

ReviewJournal of fungi (Basel, Switzerland)2026

Mining Genetically Encoded Biosensors from Filamentous Fungi.

Shuhui Guo, Shaozheng Song, Zhunzhun Liu, Yunjun Ge, Ye Chen

Abstract readReview
In one paragraph

Review in Journal of fungi (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

5 authors.

Shuhui GuoSchool of Medicine & Health Sciences, Wuxi Taihu University, Wuxi 214064, China.
Shaozheng SongSchool of Medicine & Health Sciences, Wuxi Taihu University, Wuxi 214064, China.
Zhunzhun LiuSchool of Medicine & Health Sciences, Wuxi Taihu University, Wuxi 214064, China.
Yunjun GeWuxi School of Medicine, Jiangnan University, Wuxi 214122, China.
Ye ChenState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

Funding

start-up fund of Wuxi Taihu University 2025THQD024
6 · The paper itself

Abstract

Genetically encoded biosensors represent cutting-edge biosensors due to their capabilities in real-time monitoring and precise control in living cells. However, the development of eukaryotic genetically encoded biosensors for new analytes is constrained by the shortage of signal-receptor pairs. Bacterial biosensors have been transferred to eukaryotes to expand the signal detection space, which has achieved remarkable success. However, due to the significant differences between eukaryotic and prokaryotic gene expression systems, optimizing bacterial biosensors has proven challenging. Successful cases indicate that developing orthogonal signal-receptor pairs directly from eukaryotic systems may offer a viable solution. Indeed, the potential of filamentous fungi-a highly diverse group of organisms that share conserved as well as specific signaling and metabolic pathways with yeast and mammalian cells-has been largely overlooked in biosensor development. In this review, we systematically examine biosensing systems in filamentous fungi, summarize their signal recognition receptors, signal transduction pathways, responsive transcription factors, and provide an overview of the biosensors and synthetic tools developed from them. Finally, we highlight the promise and challenges of biosensor development from filamentous fungi and discuss their potential applications.

Indexed as

filamentous fungigenetically encoded biosensorGPCRphotoreceptorsensing elementsynthetic biologytranscription factor-based biosensor

Identifiers

PMID41745292
PMCPMC12941744

What Socratic holds

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LicenceCC BY
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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 Socratic graph.