Engineering a GPCR-based yeast biosensor for a highly sensitive melatonin detection from fermented beverages
Artikel i vetenskaplig tidskrift, 2024

Melatonin is a multifunctional molecule with diverse biological roles that holds great value as a health-promoting bioactive molecule in any food product and yeast’s ability to produce it has been extensively demonstrated in the last decade. However, its quantification presents costly analytical challenges due to the usual low concentrations found as the result of yeast metabolism. This study addresses these analytical challenges by optimizing a yeast biosensor based on G protein-coupled receptors (GPCR) for melatonin detection and quantitation. Strategic genetic modifications were employed to significantly enhance its sensitivity and fluorescent signal output, making it suitable for detection of yeast-produced melatonin. The optimized biosensor demonstrated significantly improved sensitivity and fluorescence, enabling the screening of 101 yeast strains and the detection of melatonin in various wine samples. This biosensor’s efficacy in quantifying melatonin in yeast growth media underscores its utility in exploring melatonin production dynamics and potential applications in functional food development. This study provides a new analytical approach that allows a rapid and cost-effective melatonin analysis to reach deeper insights into the bioactivity of melatonin in fermented products and its implications for human health. These findings highlight the broader potential of biosensor technology in streamlining analytical processes in fermentation science.

Signal transduction

Extensive screening

Melatonin

Metabolic engineering

Biosensors

GPCRs

Författare

Ricardo Bisquert

Consejo Superior de Investigaciones Científicas (CSIC)

Alba Guillén

Consejo Superior de Investigaciones Científicas (CSIC)

Sara Muñiz Calvo

Consejo Superior de Investigaciones Científicas (CSIC)

Chalmers, Life sciences, Systembiologi

José Manuel Guillamón

Consejo Superior de Investigaciones Científicas (CSIC)

Scientific Reports

2045-2322 (ISSN) 20452322 (eISSN)

Vol. 14 17852

Ämneskategorier (SSIF 2025)

Molekylärbiologi

Bioinformatik och beräkningsbiologi

DOI

10.1038/s41598-024-68633-y

PubMed

39090231

Mer information

Senast uppdaterat

2025-05-20