Ji Jiacheng, Wei Xinxin, Guan Huan, Jin Zikang, Yue Xin, Jiang Zhuoran, Su Youla, Sun Shuying, Chen Guilin
Key Laboratory of Herbage and Endemic Crop Biology, Ministry of Education, School of Life Sciences, Inner Mongolia University, Hohhot, China.
The Good Agriculture Practice Engineering Technology Research Center of Chinese and Mongolian Medicine in Inner Mongolia, Inner Mongolia University, Hohhot, China.
Front Plant Sci. 2025 Jul 17;16:1586682. doi: 10.3389/fpls.2025.1586682. eCollection 2025.
The efficacy of traditional Chinese medicine is determined by its bioactive components, which exhibit variability depending on environmental conditions and hereditary influences. In this study, we focus on Rupr., a medicinally significant species facing sustainability challenges. However, the ecological drivers governing its distribution, as well as the relationship between environmental factors and bioactive components, remain unclear. Thus, we sampled 28 representative distribution areas of in China. Employing Maximum Entropy (MaxEnt) modeling, we projected current and future (2050s-2090s) habitat suitability under four emission scenarios. Notably, species distribution exhibited expansion (8.03%-29.06% range increase across scenarios) with precipitation of the wettest month (BIO13) and soil pH emerging as key drivers (combined contribution >49%). Ultra-performance liquid chromatography (UPLC) fingerprinting combined with machine learning regression was applied to quantify six key bioactive components in , 3,4-dihydroxybenzaldehyde, catechin, epicatechin, ursolic acid, total phenolics, and crude polysaccharides-revealing significant concentration variations among geographically distinct populations. Slope gradient (slope), min temperature of coldest month (BIO6), precipitation of coldest quarter (BIO19), sunshine duration in growing season(hsdgs), and isothermality (BIO3) were identified as key regulatory factors influencing the accumulation of multiple components. Specifically, slope acted as a key shared negative regulator for 3,4-dihydroxybenzaldehyde, catechin, and crude polysaccharides. BIO6 served as a key shared positive regulator for catechin and total phenolics, while functioning as a key negative regulator for ursolic acid. BIO19 was identified as a key shared negative regulator for catechin and epicatechin. Hsdgs acted as a key positive regulator for ursolic acid while negatively regulating crude polysaccharides. Additionally, BIO3 served as a key shared positive regulator for both ursolic acid and total phenolics. This study provides the scientific basis for enabling targeted cultivation zones that balance therapeutic compound yield with arid ecosystem conservation.
中药的功效由其生物活性成分决定，这些成分会因环境条件和遗传影响而表现出变异性。在本研究中，我们聚焦于蒙古黄芪（Astragalus membranaceus (Fisch.) Bunge var. mongholicus (Bunge) Hsiao & K. C. Hsia），这是一种面临可持续性挑战的重要药用植物。然而，控制其分布的生态驱动因素以及环境因素与生物活性成分之间的关系仍不明确。因此，我们在中国采集了28个蒙古黄芪的代表性分布区域样本。采用最大熵（MaxEnt）建模方法，我们预测了在四种排放情景下当前和未来（2050年代至2090年代）的栖息地适宜性。值得注意的是，物种分布呈现出扩张趋势（各情景下范围增加8.03% - 29.06%），最湿润月份的降水量（BIO13）和土壤pH值成为关键驱动因素（综合贡献率>49%）。应用超高效液相色谱（UPLC）指纹图谱结合机器学习回归方法，对蒙古黄芪中的六种关键生物活性成分进行了定量分析，这六种成分分别为3,4 - 二羟基苯甲醛、儿茶素、表儿茶素、熊果酸、总酚和粗多糖，结果显示地理上不同种群之间这些成分的浓度存在显著差异。坡度梯度（slope）、最冷月最低温度（BIO6）、最寒冷季节降水量（BIO19）、生长季日照时长（hsdgs）和等温性（BIO3）被确定为影响多种成分积累的关键调节因子。具体而言，坡度是3,4 - 二羟基苯甲醛、儿茶素和粗多糖的关键共同负调节因子。BIO6是儿茶素和总酚的关键共同正调节因子，同时是熊果酸的关键负调节因子。BIO19被确定为儿茶素和表儿茶素的关键共同负调节因子。Hsdgs是熊果酸的关键正调节因子，同时对粗多糖起负调节作用。此外，BIO3是熊果酸和总酚的关键共同正调节因子。本研究为划定目标种植区提供了科学依据，以实现治疗性化合物产量与干旱生态系统保护之间的平衡。
