Long-Read Metagenomics Profiling for Identification of Key Microorganisms Affected by Heavy Metals at Technogenic Zones

TL;DR

This study explores how heavy metal pollution affects soil microbes in industrial areas using advanced sequencing techniques.

Contribution

The study introduces long-read sequencing for strain-level profiling of metal-impacted soil microbial communities.

Findings

Heavy metal exposure altered microbial community composition without reducing diversity.

Metal-resistant taxa became dominant in contaminated soils.

Long-read sequencing provided high-resolution insights into microbial responses to pollution.

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.

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