The interconnected rhizosphere: High network complexity dominates rhizosphere assemblages

TLDR

Interactions between roots and microorganisms are well studied, but interactions among root‑associated microbes remain poorly understood. The study applied random matrix theory–based network analysis of 16S rRNA gene data from greenhouse microcosms to map bacterial networks associated with wild oat across two seasons. Rhizosphere bacterial networks were far more complex than surrounding soils, grew in complexity as plants aged even while diversity fell, were dominated by positive interactions hinting at mutualism and quorum‑based signaling, and featured low‑abundance keystone taxa, underscoring network complexity as a key rhizosphere trait.

Abstract

Abstract 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.