Central Metabolism-Responsive Biosensors for Monitoring, Screening, and Engineering in Microbial Production

Abstract

Central metabolism includes essential pathways such as glycolysis, the pentose phosphate pathway, and the tricarboxylic acid (TCA) cycle. Beyond the canonical pathways, it also involves byproduct formation, amino acid metabolism, fatty acid metabolism, and cofactor homeostasis, forming the metabolic backbone that supports cellular growth and biosynthesis. Conventional analytical methods often fail to provide real-time information in living cells, limiting their utility for guiding metabolic engineering. In this context, biosensor-assisted approaches have emerged as powerful tools for the realtime, non-destructive detection of intracellular metabolites and metabolic fluxes, while also enabling dynamic regulation of metabolic networks. In this review, we summarize recent advances in biosensors targeting key metabolites, cofactors, and regulatory nodes across central metabolism, with an emphasis on their design principles and applications in metabolic monitoring, high-throughput screening, and dynamic regulation for improved bioproduction. We also discuss current challenges related to sensor performance and implementation, and highlight the possibilities of integrating biosensors with omics, metabolic modules, and artificial intelligence (AI) to provide insights into future opportunities for biosensor development.

Keywords

Biosensor / Central metabolism / Metabolic engineering / Transcription factor / Dynamic regulation / Bioproduction

Acknowledgments

The authors acknowledge the support of the National Institute of General Medical Sciences of the National Institutes of Health. This study was supported by the College of Engineering, The University of Georgia, Athens, Georgia, United States.

Author Contributions

Conceptualization, J.Z. and Y.Y. (Yajun Yan); Writing—Original draft preparation, J.Z.; Writing—Review & Editing, J.Z., X.G., Q.G., Y.Y. (Yingyue Yu), Y.D., R.S., N.L. and Y.Y. (Yajun Yan); Project Administration, Y.Y. (Yajun Yan); Funding Acquisition, Y.Y. (Yajun Yan).

Ethics Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analysed in this study. Data sharing is not applicable to this article.

Funding

This work was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM128620.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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