Integrative phytochemical profiling and in silico nutrigenomic predictions of Chinese tea-Saudi Mentha longifolia blend formulations

中国茶-沙特长叶薄荷混合配方的综合植物化学成分分析和计算机营养基因组学预测

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Abstract

Medicinal plants represent valuable sources of bioactive compounds with therapeutic and economic potential. In Saudi Arabia, Mentha longifolia L. has long been used in traditional medicine, while China is renowned for its diverse teas derived from Camellia sinensis L. However, the tissue-specific genomic impact of their metabolites remains poorly understood. We tested three replicates of each blending ratio: 1:1, 1:2, and 2:1 (Tea:Mentha). Moreover, we investigated the putative expression profiles of 273 genes across human tissues using transcriptomic databases to explore the nutrigenomic effects of tea-Mentha blends. 1:2 (Tea:Mentha) Replicate 2 was dominated with 50.77% bioactive compounds, making it the strongest candidate overall. The highest Mentha aroma and bioactive compounds included eucalyptol (~17.3%), (+)-2-bornanone (~12.2%), n-hexadecanoic acid (~16.6%), and phytol (~3.2%). Lipid-derived molecules, including phytol, oleamide, and linolenic acids, showed the strongest transcriptional activation, particularly in endocrine and reproductive tissues, whereas alkaloids such as caffeine exhibited moderate effects. The preliminary integrative analysis combining experimental phytochemical profiling with computational nutrigenomic predictions is designed to generate testable hypotheses for future functional assays. Such blends may contribute to product diversification, standardization, and quality enhancement in the herbal tea industry.

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