Sabih Ur Rehman Syed, Nasar Muhammad Ibtisam, Mesquita Cristina S, Al Khodor Souhaila, Notebaart Richard A, Ott Sascha, Mundra Sunil, Arasardanam Ramesh P, Muhammad Khalid, Alam Mohammad Tauqeer
Department of Biology, United Arab Emirates University, Sheik Khalifa Bin Zayed St, Asharij, P.O. Box 15551, Al Ain, Abu Dhabi, United Arab Emirates.
Bioinformatics & Digital Health Services (RTP), University of Warwick, CV4 7AL, Coventry, United Kingdom.
Brief Bioinform. 2025 Jul 2;26(4). doi: 10.1093/bib/bbaf323.
Microbiomes are crucial for human health and well-being, with microbial dysbiosis being linked to various complex diseases. Therefore, understanding the structural and functional changes in the microbiome, along with the underlying mechanisms in disease conditions, is essential. In this review, we outline the structure and function of different human microbiomes and examine how changes in their composition may contribute to diseases. We highlight critical information associated with microbial dysbiosis and explore various therapeutic strategies for restoring a healthy microbiome, including microbiota transplantation, phage therapy, probiotics, prebiotics, dietary interventions, and drug-based approaches. Further, to better understand microbiome dysbiosis, we discuss multi-omics approaches including metagenomics, metatranscriptomics, metaproteomics, and meta-metabolomics, alongside computational modeling approaches such as ecological and metabolic network analysis. We outline key challenges associated with multi-omics techniques and emphasize the importance of integrative systems biology approaches that combine multi-omics data with computational modeling. These approaches are crucial for effectively analyzing microbiome data, providing deeper insights into species interactions and microbiome dynamics. Finally, we offer insights into future research directions in the field of microbiome research. This review makes a unique contribution to microbiome research by presenting a holistic framework that integrates multi-omics data with multi-scale modeling to elucidate microbial interactions, microbiome dysbiosis, and their modulation in disease-associated contexts.
微生物群对人类健康和福祉至关重要,微生物群落失调与各种复杂疾病相关。因此,了解微生物群的结构和功能变化以及疾病状态下的潜在机制至关重要。在本综述中,我们概述了不同人类微生物群的结构和功能,并研究了其组成变化如何导致疾病。我们强调了与微生物群落失调相关的关键信息,并探索了恢复健康微生物群的各种治疗策略,包括微生物群移植、噬菌体疗法、益生菌、益生元、饮食干预和基于药物的方法。此外,为了更好地理解微生物群失调,我们讨论了多组学方法,包括宏基因组学、宏转录组学、宏蛋白质组学和宏代谢组学,以及生态和代谢网络分析等计算建模方法。我们概述了与多组学技术相关的关键挑战,并强调了将多组学数据与计算建模相结合的综合系统生物学方法的重要性。这些方法对于有效分析微生物群数据、深入了解物种相互作用和微生物群动态至关重要。最后,我们对微生物群研究领域的未来研究方向提出了见解。本综述通过提出一个整体框架,将多组学数据与多尺度建模相结合,以阐明微生物相互作用、微生物群失调及其在疾病相关背景下的调节,为微生物群研究做出了独特贡献。
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