Metagenomic Analysis of Microbial Communities and Corrosion-Related Functional Genes in Soil Profiles from Guangxi
Microbially influenced corrosion (MIC) poses a significant threat to buried metallic infrastructure, yet assessing MIC risks in complex, vertically stratified soil environments remains challenging. Unlike traditional models that focus on single canonical corrosion-related species, localized MIC is increasingly recognized as a community-driven process mediated by biofilm formation and stress adaptation. This study investigated the spatial and vertical distribution (0–2.5 m) of microbiomes and corrosion-associated functional genes along a transmission line in Guangxi, China, using shotgun metagenomic sequencing. Taxonomic profiling revealed pronounced site-specific divergence. Site C was enriched in Sphingomonas and nitrifying taxa that promote biofilm-mediated corrosion, whereas Site E was dominated by the iron-reducing Anaeromyxobacter, suggesting anaerobic corrosion susceptibility. Along all investigated sites, surface horizons were dominated by aerobic biofilm formers. Intermediate depths were enriched in dissimilatory iron reducers and nitrite oxidizers, while the deepest layers were dominated by acid-producing Streptomyces. Similarly, the corrosion-related functional genes exhibited a shared vertical stratification across all sites. Functional annotation identified a persistent baseline of corrosion-relevant functions—including oxidative-stress sigma factors (e.g., K03088), nickel-transport systems for hydrogenase assembly (e.g., K02035/K02033/K02034), biofilm-regulatory kinases (e.g., K12132), and ATP-binding cassette (e.g., K06147). These functional markers exhibited clear vertical stratification, with nickel-transport and stress-response genes peaking at intermediate depths. Correlation analyses suggested that K03088 was associated with high resistivity and oxidation-reduction potential, whereas the nickel-transport cluster K02035/K02033/K02034 was correlated with lower pH and reduced salinity. These findings suggest that MIC risk in soils is potentially driven by complex ecological networks, and provide candidate genetic biomarkers for the early warning and risk assessment of buried infrastructure corrosion.