Bioremediation Potential of Rhodococcus qingshengii PM1 in Sodium Selenite-Contaminated Soil and Its Impact on Microbial Community Assembly

Abstract

Soil microbial communities are particularly sensitive to selenium contamination, which has seriously affected the stability of soil ecological environment and function. In this study, we applied high-throughput 16S rRNA gene sequencing to examine the effects of low and high doses of sodium selenite and the selenite-degrading bacterium, Rhodococcus qingshengii PM1, on soil bacterial community composition, diversity, and assembly processes under controlled laboratory conditions. Our results indicated that sodium selenite and strain PM1 were key predictors of bacterial community structure in selenium-contaminated soils. Exposure to sodium selenite initially led to reductions in microbial diversity and a shift in dominant bacterial groups, particularly an increase in Actinobacteria and a decrease in Acidobacteria. Sodium selenite significantly reduced microbial diversity and simplified co-occurrence networks, whereas inoculation with strain PM1 partially reversed these effects by enhancing community complexity. Ecological modeling, including the normalized stochasticity ratio (NST) and Sloan's neutral community model (NCM), suggested that stochastic processes predominated in the assembly of bacterial communities under selenium stress. Null model analysis further revealed that heterogeneous selection and drift were primary drivers of community turnover, with PM1 inoculation promoting species dispersal and buffering against the negative impacts of selenium. These findings shed light on microbial community assembly mechanisms under selenium contamination and highlight the potential of strain PM1 for the bioremediation of selenium-affected soils.

Keywords: Rhodococcus qingshengii; bacterial community assembly; bioremediation; selenium; stochastic processes.

Figure 1

Dynamic changes in sodium selenite concentration, microbial community composition, and alpha diversity in soils under different selenium contamination treatments. (A) Changes in sodium selenite in each selenium-contaminated treatment during the incubation period. (B) Phylum-level relative abundance of bacterial communities across treatment groups at different time points (Day 1, Day 10, Day 20, and Day 30). (C) Alpha diversity metrics, including OTU, Chao1, Shannon diversity index, and phylogenetic diversity across treatment groups and incubation times. Significant differences between treatments are indicated by different letters above the box plots (p < 0.05). The right-side graphs illustrate changes in each alpha diversity index over time, showing the impact of sodium selenite and strain PM1 on microbial diversity. NO: non-treatment soil, LO: low-dose selenium-contaminated soil, HI: high-dose selenium-contaminated soil, PM1: non-treatment soil + strain PM1, LO + PM1: low-dose selenium-contaminated soil + strain PM1, HI + PM1: high-dose selenium-contaminated soil + strain PM1.

Figure 2

Effects of sodium selenite and strain PM1 on soil bacterial beta diversity. (A,B) Principal coordinates analysis (PCoA) plots showing bacterial community structure. (A) Comparison of community structure across different treatments. (B) Community structure in treatments with PM1 inoculation. (C) Mantel test analysis showing the relationship between soil physicochemical properties and β-diversity of the bacterial community. Thicker lines indicate larger Mantel’s r values and the line color represents different significance levels. Bacterial richness is represented by the Chao index, and diversity is indicated by the Shannon index. Soil nutrients are represented by soil properties and enzyme activities. (D) Random forest analysis identifying key factors influencing bacterial community composition. (E) Redundancy Analysis (RDA) illustrating the effects of soil physicochemical properties on soil microbial diversity. (F) Structural equation models (SEMs) depicting the direct and indirect effects of sodium selenite and strain PM1 on soil properties, enzymes, and microbial community diversity. NO: non-treatment soil, LO: low-dose selenium-contaminated soil, HI: high-dose selenium-contaminated soil, PM1: non-treatment soil + strain PM1, LO + PM1: low-dose selenium-contaminated soil + strain PM1, HI + PM1: high-dose selenium-contaminated soil + strain PM1. *** p < 0.001; ** p < 0.01; * p < 0.05.

Figure 3

Co-occurrence network analysis of soil microbial community based on Pearson’s correlation analysis among OTUs. (A) Blue and red lines represent significant negative and positive correlations, respectively. The nodes indicate the OTUs, and the color of the node represents the model hub. Robustness is calculated as the proportion of remaining species in the community after randomly removing 50% of the nodes (B) or targeted hubs (C), while vulnerability (D) is determined by the highest node vulnerability in each network. (E) Putative keystone taxa in the different networks based on Pi and Zi. The solid triangle represents an OTU. NO: non-treatment soil, LO: low-dose selenium-contaminated soil, HI: high-dose selenium-contaminated soil, PM1: non-treatment soil + strain PM1, LO + PM1: low-dose selenium-contaminated soil + strain PM1, HI + PM1: high-dose selenium-contaminated soil + strain PM1.

Figure 4

The normalized stochasticity ratio (NST) (A) and Sloan’s neutral community model (NCM) (B–H) were used to assess the soil bacterial community assembly process. The blue solid line represents the fit of the neutral model, and the upper and lower blue dashed lines represent the 95% confidence interval predicted by the model. NO: non-treatment soil, LO: low-dose selenium-contaminated soil, HI: high-dose selenium-contaminated soil, PM1: non-treatment soil + strain PM1, LO + PM1: low-dose selenium-contaminated soil + strain PM1, HI + PM1: high-dose selenium-contaminated soil + strain PM1. *** p < 0.001; ** p < 0.01.

Figure 5

Distribution of beta nearest taxon index (β-NTI) among different samples (A). The proportion of heterogeneous selection, homogeneous dispersal and drift in the microbial assembly process (B). NO: non-treatment soil, LO: low-dose selenium-contaminated soil, HI: high-dose selenium-contaminated soil, PM1: non-treatment soil + strain PM1, LO + PM1: low-dose selenium-contaminated soil + strain PM1, HI + PM1: high-dose selenium-contaminated soil + strain PM1.

Figure 6

The relative importance of different ecological processes based on iCAMP analysis. NO: non-treatment soil, LO: low-dose selenium-contaminated soil, HI: high-dose selenium-contaminated soil, PM1: non-treatment soil + strain PM1, LO + PM1: low-dose selenium-contaminated soil + strain PM1, HI + PM1: high-dose selenium-contaminated soil + strain PM1.