From hairballs to hypotheses-biological insights from microbial networks

被引:424
作者
Rottjers, Lisa [1 ]
Faust, Karoline [1 ]
机构
[1] Katholieke Univ Leuven, Dept Microbiol & Immunol, Rega Inst, Lab Mol Bacteriol, Leuven, Belgium
关键词
networks; hub species; network properties; benchmarking; ecological networks; interactions; TIME-SERIES ANALYSIS; GUT MICROBIOTA; QUANTITATIVE-ANALYSIS; SPECIES-INTERACTION; REGULATORY NETWORK; ANALYSIS REVEALS; SYSTEMS BIOLOGY; COMMUNITY; MODELS; DYNAMICS;
D O I
10.1093/femsre/fuy030
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Microbial networks are an increasingly popular tool to investigate microbial community structure, as they integrate multiple types of information and may represent systems-level behaviour. Interpreting these networks is not straightforward, and the biological implications of network properties are unclear. Analysis of microbial networks allows researchers to predict hub species and species interactions. Additionally, such analyses can help identify alternative community states and niches. Here, we review factors that can result in spurious predictions and address emergent properties that may be meaningful in the context of the microbiome. We also give an overview of studies that analyse microbial networks to identify new hypotheses. Moreover, we show in a simulation how network properties are affected by tool choice and environmental factors. For example, hub species are not consistent across tools, and environmental heterogeneity induces modularity. We highlight the need for robust microbial network inference and suggest strategies to infer networks more reliably.
引用
收藏
页码:761 / 780
页数:20
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