Identification of technological/metabolic/environmental profiles associated with cheeses accumulating the neuroactive compound tryptamine
2024
Redruello, Begoña | Arranz, David | Szekeres, Barbara | Río Lagar, Beatriz del | Álvarez González, Miguel Ángel | Principado de Asturias | European Commission | Ministerio de Ciencia, Innovación y Universidades (España) | Agencia Estatal de Investigación (España) | Consejo Superior de Investigaciones Científicas (España) | CSIC - Unidad de Recursos de Información Científica para la Investigación (URICI) | Redruello, Begoña [0000-0003-1787-5594] | Río Lagar, Beatriz del [0000-0001-8107-1975] | Álvarez González, Miguel Ángel [0000-0001-9607-7480] | Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
Tryptamine is a neuromodulator of the central nervous system. It is also a biogenic amine, formed by the microbial decarboxylation of L-tryptophan. Tryptamine accumulation in cheese has been scarcely examined. No studies are available regarding the factors that could influence its accumulation. Determining the tryptamine content and identifying the factors that influence its accumulation could help in the design of functional tryptamine-enriched cheeses without potentially toxic concentrations being reached. We report the tryptamine concentration of 300 cheese samples representing 201 varieties. 16% of the samples accumulated tryptamine, at between 3.20 mg kg-1 and 3012.14 mg kg-1 (mean of 29.21 mg kg-1). 4.7% of cheeses accumulated tryptamine at higher levels than those described as potentially toxic. Moreover, three technological/metabolic/environmental profiles associated with tryptamine-containing cheese were identified, as well as the hallmark varieties reflecting each. Such knowledge could be useful for the dairy industry to control the tryptamine content of their products.
Показать больше [+] Меньше [-]This work was funded by the Plan for Science, Technology and Innovation of the Principality of Asturias 2018– 2022, co-financed by FEDER (Grant AYUD/2021/50916) and by MCIN/AEI/10.13039/501100011033 (Grant PID2020-112629RB-I00). D. A. was the recipient of a predoctoral contract (Grant PRE2021-098772) funded by MCIN/AEI/ 10.13039/501100011033 and by “ESF Investing in your future”. B. S. was the recipient of a research fellowship funded by Agencia Estatal CSIC, JAE Program (Grant JAEINT_23_01684). The authors acknowledge support received by the Unit of Information Resources for Research (URICI-CSIC) through its CSIC Open Access Publication Support Initiative. The authors also thank Adrian Burton for language and editing assistance.
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