Lu Jiamin, Zhang Wen, He Yuzhou, Jiang Mei, Liu Zhankui, Zhang Jirong, Zheng Lanzhi, Zhou Bingzhi, Luo Jielian, He Chenming, Shan Yunan, Zhang Runze, Fan KaiLiang, Fang Bangjiang, Wan Chuanqi
Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Institute of Acute and Critical Care, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Front Microbiol. 2025 Jun 26;16:1618177. doi: 10.3389/fmicb.2025.1618177. eCollection 2025.
Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, and its pathogenesis involves complex interactions between the host and the microbiome. The integration of multi-omics has important value in revealing the mechanism of host-microbiome interaction. It is a key tool for promoting accurate diagnosis and guiding dynamic treatment strategies in sepsis. However, multi-omics data integration faces technical challenges, such as data heterogeneity and platform variability, as well as analytical hurdles, such as the "curse of dimensionality." Fortunately, researchers have developed two integration strategies: data-driven and knowledge-guided approaches, which employ various dimensionality reduction techniques and integration methods to handle multi-omics datasets. This review discusses the applications of multi-omics technologies in host-microbiome interactions in sepsis, highlighting their potential in identifying novel diagnostic biomarkers and developing personalized and dynamic treatment strategies. It also summarizes commonly used systems biology resources and computational tools for data integration; the review outlines the challenges in this field and proposes potential directions for future studies.
脓毒症是由宿主对感染的失调反应引起的危及生命的器官功能障碍，其发病机制涉及宿主与微生物群之间的复杂相互作用。多组学整合在揭示宿主-微生物群相互作用机制方面具有重要价值。它是促进脓毒症准确诊断和指导动态治疗策略的关键工具。然而，多组学数据整合面临技术挑战，如数据异质性和平台可变性，以及分析障碍，如“维度诅咒”。幸运的是，研究人员已经开发了两种整合策略：数据驱动和知识引导方法，它们采用各种降维技术和整合方法来处理多组学数据集。本综述讨论了多组学技术在脓毒症宿主-微生物群相互作用中的应用，强调了它们在识别新型诊断生物标志物以及制定个性化和动态治疗策略方面的潜力。它还总结了用于数据整合的常用系统生物学资源和计算工具；综述概述了该领域的挑战，并提出了未来研究的潜在方向。
