Microbial communities and functional genes associated with soil arsenic contamination and the rhizosphere of the arsenic-hyperaccumulating plant Pteris vittata L

Abstract

To understand how microbial communities and functional genes respond to arsenic contamination in the rhizosphere of Pteris vittata, five soil samples with different arsenic contamination levels were collected from the rhizosphere of P. vittata and nonrhizosphere areas and investigated by Biolog, geochemical, and functional gene microarray (GeoChip 3.0) analyses. Biolog analysis revealed that the uncontaminated soil harbored the greatest diversity of sole-carbon utilization abilities and that arsenic contamination decreased the metabolic diversity, while rhizosphere soils had higher metabolic diversities than did the nonrhizosphere soils. GeoChip 3.0 analysis showed low proportions of overlapping genes across the five soil samples (16.52% to 45.75%). The uncontaminated soil had a higher heterogeneity and more unique genes (48.09%) than did the arsenic-contaminated soils. Arsenic resistance, sulfur reduction, phosphorus utilization, and denitrification genes were remarkably distinct between P. vittata rhizosphere and nonrhizosphere soils, which provides evidence for a strong linkage among the level of arsenic contamination, the rhizosphere, and the functional gene distribution. Canonical correspondence analysis (CCA) revealed that arsenic is the main driver in reducing the soil functional gene diversity; however, organic matter and phosphorus also have significant effects on the soil microbial community structure. The results implied that rhizobacteria play an important role during soil arsenic uptake and hyperaccumulation processes of P. vittata.

FIG. 1.

Community metabolic diversity (CMD) of the soil samples analyzed with the Biolog system (threshold OD of 0.25).

FIG. 2.

Proportion of functional gene categories detected. The percentages were calculated by the total signal intensity values of each gene family divided by the total signal intensity values of all genes detected on the array after combination and normalization. C deg and C fix represent carbon degradation and carbon fixation, respectively.

FIG. 3.

Canonical correspondence analysis (CCA) of GeoChip 3.0 hybridization signal intensities and soil geochemistry variables. The percentage of variation explained by each axis is shown.

FIG. 4.

Variation partitioning analysis (VPA) of the variance in microbial diversity among important geochemical variables, As, O-M, and P, and their interactions.