Long-Read Metagenomics Profiling for Identification of Key Microorganisms Affected by Heavy Metals at Technogenic Zones
Abstract
Heavy metal pollution poses a serious threat to soil ecosystems worldwide, as long-term exposure can alter microbial community functioning and reduce overall ecosystem resilience. This study investigated the impact of heavy metal contamination in technogenic industrial areas of the East Kazakhstan Region on soil microbial communities. Soil samples were collected for chemical and metagenomic analyses. Concentrations of Zn, Pb, Cu, and Cd were quantified by flame atomic absorption spectrometry (FAAS). Using long-read whole-metagenome nanopore sequencing, we conducted strain-level profiling of soils with different levels of metal contamination. This approach provided high-resolution taxonomic data, enabling detailed characterization of microbial community structure. Heavy metal exposure did not significantly reduce microbial diversity or richness but influences the quality of community composition. Metal-resistant taxa dominated contaminated soils. Overall, the results highlight the value of long-read sequencing for resolving strain-level responses to environmental contamination.