期刊
ECOLOGY LETTERS
卷 19, 期 8, 页码 926-936出版社
WILEY
DOI: 10.1111/ele.12630
关键词
Community ecology; keystone species; microbial ecology; microbial interactions; microbial networks; quorum sensing; random matrix theory; rhizosphere
类别
资金
- U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research Genomic Science Program [DE-SC0004730, DE-SC0010570]
- U.S. DOE at Lawrence Livermore National Laboratory [DE-AC52-07NA27344]
- U.S. DOE Genomic Science Program [SCW1421]
- U.S. DOE under UC [00008322]
- U.S. Department of Energy (DOE) [DE-SC0004730, DE-SC0010570] Funding Source: U.S. Department of Energy (DOE)
While 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.
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