Bisquert Ricardo, Guillén Alba, Muñiz-Calvo Sara, Guillamón José M
Department of Food Biotechnology, Instituto de Agroquímica y Tecnología de los Alimentos (CSIC), Avda. Agustín Escardino, 7, 46980, Paterna, Spain.
Department of Life Sciences, Chalmers University of Technology, Kemivägen 10, 412 96, Gothenburg, Sweden.
Sci Rep. 2024 Aug 1;14(1):17852. doi: 10.1038/s41598-024-68633-y.
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.
褪黑素是一种具有多种生物学作用的多功能分子,作为一种促进健康的生物活性分子,在任何食品中都具有重要价值。在过去十年中,酵母产生褪黑素的能力已得到广泛证明。然而,由于酵母代谢导致的通常较低浓度,其定量分析面临成本高昂的分析挑战。本研究通过优化基于G蛋白偶联受体(GPCR)的酵母生物传感器来检测和定量褪黑素,解决了这些分析挑战。采用了战略性基因改造来显著提高其灵敏度和荧光信号输出,使其适用于检测酵母产生的褪黑素。优化后的生物传感器显示出显著提高的灵敏度和荧光,能够筛选101株酵母菌株,并检测各种葡萄酒样品中的褪黑素。这种生物传感器在定量酵母生长培养基中褪黑素方面的功效突出了其在探索褪黑素产生动态以及在功能性食品开发中的潜在应用方面的实用性。本研究提供了一种新的分析方法,能够进行快速且经济高效的褪黑素分析,从而更深入地了解褪黑素在发酵产品中的生物活性及其对人类健康的影响。这些发现凸显了生物传感器技术在简化发酵科学分析过程方面的更广泛潜力。