The interconnected rhizosphere: High network complexity dominates rhizosphere assemblages.
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.
Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, 94720, USA.|Department of Botany and Microbiology, Institute for Environmental Genomics, University of Oklahoma, Norman, OK, 73019, USA.
Shengjing
S
Shi
Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, 94720, USA.|Nuclear and Chemical Sciences Division, Lawrence Livermore National Laboratory, Livermore, CA, 94551, USA.
Erin E
0000-0003-0189-183X
EE
Nuccio
Department of Botany and Microbiology, Institute for Environmental Genomics, University of Oklahoma, Norman, OK, 73019, USA.
Zhou J
ZJ
Shi
Department of Botany and Microbiology, Institute for Environmental Genomics, University of Oklahoma, Norman, OK, 73019, USA.
Zhili
Z
He
Department of Botany and Microbiology, Institute for Environmental Genomics, University of Oklahoma, Norman, OK, 73019, USA.|Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.|State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
Jizhong
J
Zhou
Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, 94720, USA.|Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Mary K
MK
Firestone
D018554:Avena / Q000382:microbiology; D001419:Bacteria / Q000145:classification* / Q000235:genetics*; D044822:Biodiversity; D008954:Models, Biological; D018517:Plant Roots; D012329:RNA, Bacterial / Q000235:genetics; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D012988:Soil Microbiology
D012329:RNA, Bacterial; D012336:RNA, Ribosomal, 16S
Community ecology; keystone species; microbial ecology; microbial interactions; microbial networks; quorum sensing; random matrix theory; rhizosphere