High-Throughput Sequencing Reveals Composition, Diversity, and Functional Prediction of Root-Associated Microbial Communities of Dominant Plants in an Ecologically Sensitive Area of the Loess Plateau
TL;DR
Different plant species were associated with distinct predicted functional taxa, which may serve as candidate biomarkers for soil remediation and candidate targets for future vegetation–microbe synergy studies in alpine mining area restoration.
Abstract
The alpine mining area of the Qilian Mountains features a fragile ecosystem, severe soil degradation due to mining disturbances, and slow natural recovery. To clarify the ecological restoration potential of rhizosphere microorganisms associated with native dominant plants, this study investigated the community structure, diversity, and functional differentiation patterns of rhizosphere bacterial and fungal communities associated with seven native dominant plant species in the Tianzhu mining area. Using Illumina NovaSeq 6000 high-throughput sequencing, we amplified the bacterial 16S rRNA V3–V4 region and the fungal ITS1 region. A total of 24 sequencing libraries (seven plant species + bare soil, three replicates each) were analyzed. Bioinformatics analyses examined ASV distributions, alpha/beta diversity, species composition, and differentially enriched taxa, followed by functional predictions. Bacterial alpha diversity (Chao1: 623.39–1553.25; Shannon: 7.49–9.67) varied significantly among plant species, with Allium przewalskianum (AP) showing the highest bacterial richness and diversity (Chao1 = 1553.25 ± 35.89, Shannon = 9.67 ± 0.02). Fungal alpha diversity also showed significant variation (Chao1: 69.66–488.56; Shannon: 3.24–4.96), with Dasiphora fruticosa (DF) exhibiting the highest fungal diversity (Chao1 = 488.56 ± 18.71, Shannon = 7.32 ± 0.06). At the phylum level, Proteobacteria (32.22–50.32%) and Actinobacteriota (15.04–23.19%) were core bacterial groups, and Ascomycota (45.54–96.07%) dominated fungal communities. PERMANOVA confirmed significant differences in community composition among plant species (bacteria: R2 = 0.78, p < 0.001; fungi: R2 = 0.84, p < 0.001). Different plant species were associated with distinct predicted functional taxa, which may serve as candidate biomarkers for soil remediation. However, all functional interpretations are predictive and require experimental validation. In conclusion, rhizosphere microbial community composition and predicted functional profiles differed among native plant species, providing correlative evidence and candidate targets for future vegetation–microbe synergy studies in alpine mining area restoration.