Geese Theresa, Bang Corinna, Franke Andre, Lieb Wolfgang, Dempfle Astrid
Institute of Medical Informatics and Statistics, Kiel University and University Hospital Schleswig-Holstein, Brunswiker Straße 10, 24105, Kiel, Germany.
Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany.
BMC Microbiol. 2025 Jun 26;25(1):371. doi: 10.1186/s12866-025-04106-0.
BACKGROUND: Dysbiosis, an imbalance in the bacterial composition of the human gut microbiota, is linked to inflammatory bowel disease (IBD). Advances in biological techniques have generated vast microbiota datasets, presenting both opportunities and challenges for clinical research in that field. Network theory offers powerful tools to analyze these complex datasets. METHODS: Utilizing genetically unrelated individuals from the Kiel IBD-KC cohort, we compared network properties of the gut microbiota between patients with inflammatory bowel disease (IBD, n = 522) and healthy controls (n = 365), and between Crohn's disease (CD, n = 230) and Ulcerative Colitis (UC, n = 280). Correlation-based microbial networks were constructed, with genera as nodes and significant pairwise correlations as edges. We used centrality measures to identify key microbial constituents, called hubs, and suggest a network-based definition for a core microbiota. Using Graphlet theoretical approaches, we analyzed network topology and individual node roles. RESULTS: Global network properties differed between cases and controls, with controls showing a potentially more robust network structure characterized by e.g., a greater number of components and a lower edge density. Local network properties varied across all groups. For cases and both UC and CD, Faecalibacterium and Veillonella, and for unaffected controls Bacteroides, Blautia, Clostridium XIVa, and Clostridium XVIII emerged as unique hubs in the respective networks. Graphlet analysis revealed significant differences in terminal node orbits among all groups. Four genera which act as hubs in one state, were found to be terminal nodes in the opposite disease state: Bacteroides, Clostridium XIVa, Faecalibacterium, and Subdoligranulum. Comparing our network-based core microbiota definition with a conventional one showed an overlap in approximately half of the core taxa, while core taxa identified through our new definition maintained high abundance. CONCLUSION: The network-based approach complements previous investigations of alteration of the human gut microbiota in IBD by offering a different perspective that extends beyond a focus solely on highly abundant taxa. Future studies should further investigate functional roles of hubs and terminal nodes as potential targets for interventions and preventions. Additionally, the advantages of the newly proposed network-based core microbiota definition, should be investigated more systematically.
背景:生态失调,即人类肠道微生物群细菌组成的失衡,与炎症性肠病(IBD)有关。生物技术的进步产生了大量的微生物群数据集,为该领域的临床研究带来了机遇和挑战。网络理论为分析这些复杂数据集提供了强大的工具。 方法:利用基尔IBD-KC队列中无亲缘关系的个体,我们比较了炎症性肠病患者(IBD,n = 522)和健康对照(n = 365)之间,以及克罗恩病(CD,n = 230)和溃疡性结肠炎(UC,n = 280)之间肠道微生物群的网络特性。构建了基于相关性的微生物网络,以属为节点,显著的成对相关性为边。我们使用中心性度量来识别关键的微生物成分,即枢纽,并提出了基于网络的核心微生物群定义。使用图论方法,我们分析了网络拓扑结构和单个节点的作用。 结果:病例组和对照组的全球网络特性不同,对照组显示出潜在更强健的网络结构,其特征例如有更多的组件和更低的边密度。局部网络特性在所有组中都有所不同。对于病例组以及UC和CD组,粪杆菌属和韦荣球菌属,对于未受影响的对照组,拟杆菌属、布劳特氏菌属、 XIVa梭菌属和 XVIII梭菌属在各自的网络中成为独特的枢纽。图论分析揭示了所有组之间终端节点轨道的显著差异。发现在一种状态下作为枢纽的四个属,在相反的疾病状态下是终端节点:拟杆菌属、 XIVa梭菌属、粪杆菌属和Subdoligranulum属。将我们基于网络的核心微生物群定义与传统定义进行比较,结果显示大约一半的核心分类群有重叠,而通过我们新定义识别出的核心分类群保持高丰度。 结论:基于网络的方法通过提供一个超越仅关注高丰度分类群的不同视角,补充了先前对IBD中人类肠道微生物群改变的研究。未来的研究应进一步调查枢纽和终端节点的功能作用,作为干预和预防的潜在靶点。此外,应更系统地研究新提出的基于网络的核心微生物群定义的优势。
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