ReviewEngineering microbiology2026
Genetically encoded biosensors enabled high-throughput screening of microbial cell factories.
Review in Engineering microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genetically encoded biosensors provide powerful tools for coupling desired phenotypes to detectable outputs and have been extensively developed to detect a wide range of natural and unnatural products. When integrated with diverse high-throughput screening (HTS) approaches, these biosensors enable efficient product-driven screening across various throughputs, thereby expediting the engineering and optimization of microbial cell factories to produce various target compounds. For effective HTS of microbial cell factories, biosensors need to possess certain crucial characteristics. The performance features of biosensors significantly influence their application potential in HTS and can be precisely engineered through synthetic biology strategies. Furthermore, to ensure biosensor-driven HTS, additional engineering and optimizations of the biosensors are often required to increase the success rate and reduce false positives in the screening process. This review discusses the essential features of genetically encoded biosensors designed for HTS and then summarizes the latest advances in biosensor engineering for HTS purposes via synthetic biology strategies. Following this, the challenges and optimization of biosensors to adapt to different HTS processes are also discussed and exemplified. Finally, the key concerns and research prospects of developing biosensors for HTS applications are highlighted. Overall, this review provides comprehensive guidance on the engineering of genetically encoded biosensors and their applications in HTS for developing microbial cell factories to produce diverse target compounds.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.