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人类肠道中[具体内容缺失]的系统发育群稳态反映宿主的生理状态。

Phylogroup Homeostasis of in the Human Gut Reflects the Physiological State of the Host.

作者信息

Frolova Maria S, Kiselev Sergey S, Panyukov Valery V, Ozoline Olga N

机构信息

Department of Functional Genomics of Prokaryotes, Institute of Cell Biophysics of the Russian Academy of Sciences, Federal Research Center "Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences", 142290 Pushchino, Russia.

Department of Bioinformatics, Institute of Mathematical Problems of Biology RAS-The Branch of Keldysh Institute of Applied Mathematics of Russian Academy of Science, 142290 Pushchino, Russia.

出版信息

Microorganisms. 2025 Jul 4;13(7):1584. doi: 10.3390/microorganisms13071584.

Abstract

The advent of alignment-free -mer barcoding has revolutionized taxonomic analysis, enabling bacterial identification at phylogroup resolution within natural communities. We applied this approach to characterize intraspecific diversity in human gut microbiomes using publicly available datasets representing diverse human physiological states. By estimating the relative abundance of eight phylogroups defined by their 18-mer markers in 558 fecal samples, we compared their distribution between gut microbiomes of healthy individuals, patients with chronic bowel diseases and volunteers subjected to various external interventions. Across all datasets, phylogroups exhibited bidirectional abundance shifts in response to host physiological changes, indicating an inherent bimodality in their adaptive strategies. Correlation analysis of phylogroup persistence revealed positive intraspecific connectivity networks and dependence of their patterns on both acute interventions like antibiotic or probiotic treatment and chronic bowel disorders. Along with predominantly negative correlations with , we observed a transition from positive to negative associations with in -rich microbiomes. Several interspecific correlations individually established by phylogroups with dominant taxa suggest their potential role in shaping intraspecific networks. Machine learning techniques statistically confirmed an ability of phylogroup patterns to discriminate the physiological state of the host and virtual diagnostic assays opened a way to optimize intraspecific phylotyping for medical applications.

摘要

无比对 - 核苷酸片段条形码技术的出现彻底改变了分类分析,使得在自然群落中能够以系统发育组分辨率鉴定细菌。我们应用这种方法,利用代表不同人类生理状态的公开可用数据集来表征人类肠道微生物群的种内多样性。通过估计558份粪便样本中由其18核苷酸标记定义的八个系统发育组的相对丰度,我们比较了它们在健康个体、慢性肠道疾病患者和接受各种外部干预的志愿者的肠道微生物群之间的分布。在所有数据集中,系统发育组响应宿主生理变化呈现双向丰度变化,表明其适应策略存在固有的双峰性。系统发育组持久性的相关分析揭示了种内正连接网络及其模式对抗生素或益生菌治疗等急性干预以及慢性肠道疾病的依赖性。除了与 主要呈负相关外,我们还观察到在富含 的微生物群中,与 的关联从正到负的转变。由系统发育组与优势类群单独建立的几种种间相关性表明它们在塑造种内网络中的潜在作用。机器学习技术从统计学上证实了系统发育组模式区分宿主生理状态的能力,虚拟诊断分析为优化医学应用中的种内系统发育分型开辟了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f4c/12299893/5c2d0e45d89b/microorganisms-13-01584-g001.jpg

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