Multiomics Reveals the Key Microorganisms and Metabolites in the Resistance to Root Rot Disease of Paris polyphylla

Genes (Basel). 2023 Dec 22;15(1):21. doi: 10.3390/genes15010021.

Abstract

Root rot of Paris polyphylla has received widespread attention due to its threat to yield and leads to serious economic losses. However, the relationship among the rhizosphere microbial community, metabolites and root rot disease remained largely unexplored. Herein, we used integrated 16S rRNA, ITS, RNA sequencing and UPLC-MS/MS to systematically investigate the differences between healthy and diseased P. polyphylla. We found that root rot reduced the microbial diversity in the diseased P. polyphylla compared with the healthy control. The relative abundance of the bacterial phylum Actinobacteria increased in the diseased rhizome of P. polyphylla. For the fungal community, root rot disease contributed to an increased relative abundance of Ascomycota and decreased Glomeromycota at the phylum level. The transcriptomic results showed that the differently expressed genes were significantly enriched in the "Biosynthesis of various alkaloids", "flavonoid biosynthesis" and "isoflavonoid biosynthesis" and "Phenylpropanoid biosynthesis" was dramatically enriched in healthy P. polyphylla compared with that in diseased P. polyphylla. Likewise, the metabolomic results showed that the biosynthesis of secondary metabolites and metabolic pathways was found to be significantly enriched by differential metabolites. Taken together, the study of combining metabolomics with microbiomes can help us enhance our understanding of the mechanisms of plant resistance to root rot disease, thereby discovering specific metabolites and microorganisms that can resist pathogen infection in P. polyphylla.

Keywords: Paris polyphylla; metabolome; microbiome; root rot disease; transcriptome.

MeSH terms

  • Animals
  • Chromatography, Liquid
  • Coleoptera*
  • Liliaceae*
  • Multiomics
  • RNA, Ribosomal, 16S
  • Tandem Mass Spectrometry

Substances

  • RNA, Ribosomal, 16S

Grants and funding

This work is supported by the Major Science and Technology Project of Fujian Province, China (Grant No. 2022NZ029017), the Major Science and Technology Project of Xiamen, China (Grant No. 3502Z20211004) and the Science and Technology Project of Xiamen, China (Grant No. 3502Z20232002).