Login / Signup

Co-Occurrence Patterns of Soil Fungal and Bacterial Communities in Subtropical Forest-Transforming Areas.

Yajun LiuXin JinShihao HuangYizhen LiuZhaoyu KongLan WuGang Ge
Published in: Current microbiology (2024)
Soil microbial communities are engineers of important biogeochemical processes and play a critical role in regulating the functions and stability of forest ecosystem. However, few studies have assessed microbial interactions during forest conversion, which is essential to the understanding of the structure and function of soil microbiome. Herein, we investigated the co-occurrence network pattern and putative functions of fungal and bacterial communities in forest-transforming areas (five sites that cover the typical forests) using high-throughput sequencing of the ITS genes and 16S rRNA. Our study showed that the bacterial network had higher average connectivity and more links than fungal network, which might indicate that the bacterial community had more complex internal interactions compared with fungal one. Alphaproteobacteria_unclassfied, Telmatobacter, 0319-6A21 and Latescibacteria_unclassfied were the keystone taxa in bacterial network. For the fungal community network, the keystone taxon was Ceratobasidium. A structural equation model indicated that the available potassium and total organic carbon were important soil environmental factors, which affected all microbial modules, including bacterial and fungi. Total nitrogen had significant effects on the bacterial module that contains a relatively rich group of nitrogen cycling functions, and pH influenced the bacterial module which have higher potential functions of carbon cycling. And, more fungal modules were directly affected by forest structure (S Tree ) compared with bacterial ones. This study provides new insights into our understanding of the feedback of underground creatures to forest conversion and highlights the importance of microbial modules in the nutrient cycling process.
Keyphrases
  • climate change
  • microbial community
  • network analysis
  • healthcare
  • mental health
  • human health
  • cell wall
  • high intensity
  • multiple sclerosis
  • genome wide
  • gene expression
  • mass spectrometry
  • dna methylation