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Core Microbiota in the Rhizosphere of Heavy Metal Accumulators and Its Contribution to Plant Performance.

Jipeng LuoShaohua GuXinyu GuoYuankun LiuQi TaoHe-Ping ZhaoYongchao LiangSamiran BanerjeeTingqiang Li
Published in: Environmental science & technology (2022)
Persistent microbial symbioses can confer greater fitness to their host under unfavorable conditions, but manipulating such beneficial interactions necessitates a mechanistic understanding of the consistently important microbiomes for the plant. Here, we examined the phylogenetic profiles and plant-beneficial traits of the core microbiota that consistently inhabits the rhizosphere of four divergent Cd hyperaccumulators and an accumulator. We evidenced the existence of a conserved core rhizosphere microbiota in each plant distinct from that in the non-hyperaccumulating plant. Members of Burkholderiaceae and Sphingomonas were the shared cores across hyperaccumulators and accumulators. Several keystone taxa in the rhizosphere networks were part of the core microbiota, the abundance of which was an important predictor of plant Cd accumulation. Furthermore, an inoculation experiment with synthetic communities comprising isolates belonging to the shared cores indicated that core microorganisms could facilitate plant growth and metal tolerance. Using RNA-based stable isotope probing, we discovered that abundant core taxa overlapped with active rhizobacteria utilizing root exudates, implying that the core rhizosphere microbiota assimilating plant-derived carbon may provide benefits to plant growth and host phenotype such as Cd accumulation. Our study suggests common principles underpinning hyperaccumulator-microbiome interactions, where plants consistently interact with a core set of microbes contributing to host fitness and plant performance. These findings lay the foundation for harnessing the persistent root microbiomes to accelerate the restoration of metal-disturbed soils.
Keyphrases
  • plant growth
  • microbial community
  • heavy metals
  • physical activity
  • body composition
  • machine learning
  • nk cells
  • genome wide
  • human health
  • wastewater treatment
  • single molecule