
doi: 10.1111/ele.12630
pmid: 27264635
AbstractWhile interactions between roots and microorganisms have been intensively studied, we know little about interactions among root‐associated microbes. We used random matrix theory‐based network analysis of 16S rRNA genes to identify bacterial networks associated with wild oat (Avena fatua) over two seasons in greenhouse microcosms. Rhizosphere networks were substantially more complex than those in surrounding soils, indicating the rhizosphere has a greater potential for interactions and niche‐sharing. Network complexity increased as plants grew, even as diversity decreased, highlighting that community organisation is not captured by univariate diversity. Covariations were predominantly positive (> 80%), suggesting that extensive mutualistic interactions may occur among rhizosphere bacteria; we identified quorum‐based signalling as one potential strategy. Putative keystone taxa often had low relative abundances, suggesting low‐abundance taxa may significantly contribute to rhizosphere function. Network complexity, a previously undescribed property of the rhizosphere microbiome, appears to be a defining characteristic of this habitat.
16S, Environmental management, Avena, random matrix theory, microbial ecology, microbial interactions, Microbiology, Models, Biological, Plant Roots, Ecological applications, Models, RNA, Ribosomal, 16S, Community ecology, Soil Microbiology, Ribosomal, Evolutionary Biology, Ecology, Bacteria, Bacterial, quorum sensing, Biodiversity, Biological Sciences, Biological, RNA, Bacterial, microbial networks, Ecological Applications, RNA, rhizosphere, keystone species
16S, Environmental management, Avena, random matrix theory, microbial ecology, microbial interactions, Microbiology, Models, Biological, Plant Roots, Ecological applications, Models, RNA, Ribosomal, 16S, Community ecology, Soil Microbiology, Ribosomal, Evolutionary Biology, Ecology, Bacteria, Bacterial, quorum sensing, Biodiversity, Biological Sciences, Biological, RNA, Bacterial, microbial networks, Ecological Applications, RNA, rhizosphere, keystone species
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