The microbiome of a brownfield highly polluted with mercury and arsenic.

Abandoned brownfields represent a challenge for their recovery. To apply sustainable remediation technologies, such as bioremediation or phytoremediation, indigenous microorganisms are essential agents since they are adapted to the ecology of the soil. Better understanding of microbial communities inhabiting those soils, identification of microorganisms that drive detoxification process and recognising their needs and interactions will significantly improve the outcome of the remediation. With this in mind we have carried out a detailed metagenomic analysis to explore the taxonomic and functional diversity of the prokaryotic and eukaryotic microbial communities in soils, several mineralogically distinct types of pyrometallurgic waste, and groundwater sediments of a former mercury mining and metallurgy site which harbour very high levels of arsenic and mercury pollution. Prokaryotic and eukaryotic communities were identified, which turned out to be more diverse in the surrounding contaminated soils compared to the pyrometallurgic waste. The highest diversity loss was observed in two environments most contaminated with mercury and arsenic (stupp, a solid mercury condenser residue and arsenic-rich soot from arsenic condensers). Interestingly, microbial communities in the stupp were dominated by an overwhelming majority of archaea of the phylum Crenarchaeota, while Ascomycota and Basidiomycota fungi comprised the fungal communities of both stump and soot, results that show the impressive ability of these previously unreported microorganisms to colonize these extreme brownfield environments. Functional predictions for mercury and arsenic resistance/detoxification genes show their increase in environments with higher levels of pollution. Our work establishes the bases to design sustainable remediation methods and, equally important, to study in depth the genetic and functional mechanisms that enable the subsistence of microbial populations in these extremely selective environments.