Elucidation of complexity and prediction of interactions in microbial communities

被引:100
|
作者
Zuniga, Cristal [1 ]
Zaramela, Livia [1 ]
Zengler, Karsten [1 ]
机构
[1] Univ Calif San Diego, Dept Pediat, 9500 Gilman Dr, La Jolla, CA 92093 USA
来源
MICROBIAL BIOTECHNOLOGY | 2017年 / 10卷 / 06期
基金
美国国家卫生研究院;
关键词
CONSTRAINT-BASED MODELS; HUMAN GUT MICROBIOME; ESCHERICHIA-COLI; METAPROTEOMICS REVEALS; RHIZOSPHERE MICROBIOME; METABOLIC INTERACTIONS; SYSTEMS BIOLOGY; AMINO-ACID; GENOME; GROWTH;
D O I
10.1111/1751-7915.12855
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Microorganisms engage in complex interactions with other members of the microbial community, higher organisms as well as their environment. However, determining the exact nature of these interactions can be challenging due to the large number of members in these communities and the manifold of interactions they can engage in. Various omic data, such as 16S rRNA gene sequencing, shotgun metagenomics, metatranscriptomics, metaproteomics and metabolomics, have been deployed to unravel the community structure, interactions and resulting community dynamics insitu. Interpretation of these multi-omic data often requires advanced computational methods. Modelling approaches are powerful tools to integrate, contextualize and interpret experimental data, thus shedding light on the underlying processes shaping the microbiome. Here, we reviewcurrent methods and approaches, both experimental and computational, to elucidate interactions in microbial communities and to predict their responses to perturbations.
引用
收藏
页码:1500 / 1522
页数:23
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