文章基本信息

标题：Critical Network Structures and Medical Ecology Mechanisms Underlying Human Microbiome-Associated Diseases
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作者：Zhanshan (Sam) Ma
期刊名称：iScience
印刷版ISSN：2589-0042
出版年度：2020
卷号：23
期号：6
页码：1-49
DOI：10.1016/j.isci.2020.101195
语种：English
出版社：Elsevier
摘要：SummaryA fundamental problem in studies on human microbiome-associated diseases (MADs) is to understand the relationships between microbiome structures and health status of hosts. For example, species diversity metrics have been routinely evaluated in virtually all studies on MADs, yet a recent meta-analysis revealed that, in only approximately one-third of the cases, diversity and diseases were related. In this study, we ask whether Hubbell's neutral theory (supplemented with the normalized stochasticity ratio [NSR]) or critical microbiome network structures may offer better alternatives. Whereas neutral theory and NSR focus on stochastic processes, we use core/periphery and high-salience skeleton networks to evaluate deterministic, asymmetrical niche effects, assuming that all species or their interactions were not “born” equal and focusing on non-neutral, critical network structures. We found that properties of critical network structures are more indicative of disease effects. Finally, seven findings (mechanisms, interpretations, and postulations) regarding medical ecology mechanisms underlying MADs were summarized.Graphical AbstractDisplay OmittedHighlights•Seven findings (mechanisms/interpretations/postulations) of medical ecology proposed•Critical network structures more indicative of disease effects than ecology metrics•One-third seems ceiling of diversity-disease relations, half to two-thirds of network structures•Super resilience (unexplained one-third to half gap) is likely attributed to host genomeEcology; Microbiology; Microbiome; Microbial Interactions