Zhang Zeming, Zhang Yining, Yuan Qixiang, Wang Zuoyi, Hu Songnian, Yin Peng, He Zilong
School of Engineering Medicine, Beihang University, Rd37, Xueyuan, Haidian, Beijing 100191, China.
Key Laboratory of Big Data-Based Precision Medicine, Beihang University, Ministry of Industry and Information Technology of the People's Republic of China, Beijing 100191, China.
Microorganisms. 2024 Dec 13;12(12):2567. doi: 10.3390/microorganisms12122567.
The intestinal mycobiome is closely related to human health. There have been several reports investigating the association between the gut fungi and disease, but there is still a lack of overall assessment of the human gut mycobiome. Here, we performed a meta-analysis based on 2372 ITS (Internal Transcribed Spacer) data collected publicly online. We found that the mycobiome diversity of human gut fungi varies significantly across diseases by using EasyAmplicon, and these fungi are mainly composed of three genera, , , and . In addition, we performed the construction of disease prediction models based on ITS data by using the random forest model and verified the generalization ability of the models. We hope that our results will provide strong support for subsequent studies of the intestinal mycobiome.
肠道真菌群落与人类健康密切相关。已有多篇报道研究肠道真菌与疾病之间的关联，但目前仍缺乏对人类肠道真菌群落的全面评估。在此，我们基于公开在线收集的2372个ITS（内转录间隔区）数据进行了一项荟萃分析。我们发现，使用EasyAmplicon软件，人类肠道真菌的真菌群落多样性在不同疾病间存在显著差异，且这些真菌主要由三个属组成，即 、 和 。此外，我们利用随机森林模型基于ITS数据构建了疾病预测模型，并验证了模型的泛化能力。我们希望我们的研究结果能为后续肠道真菌群落的研究提供有力支持。
