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孙晓华,匡宏,裴彰明,等. 甲基丙二酸血症患者肠道菌群特征解析及靶向降低丙酸水平的膳食多糖筛选J. 食品工业科技,2026,47(8):1−9. doi: 10.13386/j.issn1002-0306.2025030279.
引用本文: 孙晓华,匡宏,裴彰明,等. 甲基丙二酸血症患者肠道菌群特征解析及靶向降低丙酸水平的膳食多糖筛选J. 食品工业科技,2026,47(8):1−9. doi: 10.13386/j.issn1002-0306.2025030279.
SUN Xiaohua, KUANG Hong, PEI Zhangming, et al. Analysis of Gut Microbiota in Patients with Methylmalonic Acidemia and Screening of Propionic Acid Reducing Dietary FactorsJ. Science and Technology of Food Industry, 2026, 47(8): 1−9. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2025030279.
Citation: SUN Xiaohua, KUANG Hong, PEI Zhangming, et al. Analysis of Gut Microbiota in Patients with Methylmalonic Acidemia and Screening of Propionic Acid Reducing Dietary FactorsJ. Science and Technology of Food Industry, 2026, 47(8): 1−9. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2025030279.

甲基丙二酸血症患者肠道菌群特征解析及靶向降低丙酸水平的膳食多糖筛选

Analysis of Gut Microbiota in Patients with Methylmalonic Acidemia and Screening of Propionic Acid Reducing Dietary Factors

  • 摘要: 甲基丙二酸血症(Methylmalonic acidemia, MMA)患者肠道丙酸水平可能会影响其病程发展,但目前干预策略尚不明确。本研究旨在明确MMA患者与健康人群粪便丙酸含量及菌群组成的差异,并通过体外粪菌发酵模型及MMA大鼠模型筛选可有效降低丙酸生成的膳食因子组合,为MMA患者的饮食管理提供新策略。实验利用气相色谱-质谱技术与宏基因组技术对28例MMA患者与17例健康人群的粪便进行丙酸含量和肠道菌群结构及物种组成的分析;然后利用体外粪菌发酵模型筛选12种膳食因子中能够高效降低丙酸含量的组合,最后选用5日龄Wistar大鼠(分为雌、雄两亚组)构建MMA模型,随机分为五组:空白组、模型组、低聚半乳糖+阿拉伯半乳聚糖组(GOS+AG组)、低聚半乳糖+银耳多糖组(GOS+TPs组)、阿拉伯半乳聚糖+银耳多糖组(AG+TPs组),对干预之前(14 d)、中期(21 d)和后期(28 d)的大鼠粪便丙酸含量进行测定分析。结果显示,MMA人群与健康人群粪便中的丙酸含量(P<0.001)以及肠道菌群结构(P=0.003)存在显著差异,与对照组相比,MMA组含有较高丰度的Blautia wexlerae、Bacteroides thetaiotaomicronBlautia producta可能是导致肠道丙酸含量变化的重要因素。发酵24 h后筛选出茯苓多糖、低聚果糖、低聚半乳糖、阿拉伯半乳聚糖、银耳多糖降低丙酸效果显著(P<0.05),将上述五种多糖进行组合后进行发酵筛选出降低效果最好的三个组合GOS+AG组、GOS+TPs组、AG+TPs组(P<0.001),最后动物实验结果表明,AG+TPs组效果最好(P<0.0001)。综上所述,MMA人群与健康人群的粪便丙酸含量可能与两组人群肠道菌群差异相关,AG+TPs组能够高效降低丙酸含量,为MMA患者的饮食管理提供了一种新的策略。

     

    Abstract: The intestinal propionic acid level in patients with methylmalonic acidemia (MMA) may affect the course of the disease, but the current intervention strategy is still unclear. This study aimed to elucidate the differences in fecal propionic acid levels and gut microbiota composition between patients with MMA and healthy people, as well as to identify dietary factor combinations that effectively reduce propionic acid production through in vitro fecal fermentation model and MMA rat model. This investigation provides a novel strategy for dietary management in patients with MMA. Gas chromatography-mass spectrometry and metagenomic sequencing were employed to analyze propionic acid content, gut microbiota structure, and species composition in the feces of 28 patients with MMA and 17 healthy people. Subsequently, an in vitro fecal bacterial fermentation model was utilized to screen for optimal combinations among 12 dietary factors capable of significantly reducing propionic acid levels. Finally, 5-day-old Wistar rats (segregated into male and female subgroups) were selected to construct the MMA model and randomly divided into five groups: control group, model group, galactooligosaccharide+arabinogalactan group (GOS+AG group), galactooligosaccharide+tremella polysaccharide group (GOS+TPs group), and arabinogalactan+tremella polysaccharide group (AG+TPs group). Propionic acid content in rat feces was measured and analyzed at three time points: prior to intervention (14 days), mid-stage (21 days), and late stage (28 days). The results demonstrated significant differences in fecal propionic acid levels (P<0.001) and gut microbiota structure (P=0.003) between patients with MMA and healthy people. Compared to the control group, higher abundances of Blautia wexlerae, Bacteroides thetaiotaomicron, and Blautia producta in the MMA group may represent critical factors influencing changes in intestinal propionic acid levels. After 24 hours of fermentation, screening identified that poria cocos polysaccharides, fructooligosaccharides, galactooligosaccharides, arabinogalactan, and tremella polysaccharides demonstrated significant efficacy in reducing propionic acid levels (P<0.05). Following the combination of the aforementioned five polysaccharides and subsequent fermentation, three combinations with the most effective reduction were identified: GOS+AG group, GOS+TPs group, AG+TPs group (P<0.001). Ultimately, animal experiments confirmed that the combination of AG+TPs group yielded the best results (P<0.0001). In conclusion, differences in fecal propionic acid levels between patients with MMA and healthy people may be associated with variations in gut microbiota composition. The combination of AG+TPs group can effectively reduce propionic acid levels, offering a promising dietary management strategy for patients with MMA.

     

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