Organic Contaminant Mixture Significantly Changes Microbenthic Community Structure and Increases the Expression of PAH Degradation Genes - Iburg, Sven; Nybom, Inna; Bonaglia, Stefano; Karlson, Agnes M. L.; Sobek, Anna; Nascimento, Francisco J. A. (Frontiers in Environmental Science, 2020)
Studying the effects of chemical contaminants on the structure and function of microbial and meiofauna communities have traditionally focused on specific effects of single contaminants on single species. This has left the complex interactions between mixtures of contaminants and its non-specific toxicity effects on the functions and structure of sediment microbial communities mostly overlooked. In an effort to improve our insights on such questions, we performed an experiment where Baltic Sea sediments were spiked with an ecologically relevant mixture of seven organic contaminants below specific toxicity levels. We then used 16S and 18S rRNA metabarcoding from RNA extracts to monitor changes in active microbial and meiofauna diversity and community structure in the spiked treatment compared to controls. In addition, we investigated the effects of exposure to this contaminant mixture on potential nitrification rates and on the expression of key-genes in the microbial nitrification and PAH degradation pathways with qPCR. There were significant differences in both eukaryotic and microbial community structures in sediments spiked with a mixture of organic pollutants. Nematoda showed a significant increase in overall relative abundance to the added contaminants (5.5±.1.1% higher in spiked), particularly taxa of the genus Leptolaimus (increased from 10.2±.5.4% in the controls to 32.5±.10.2% in the spiked treatment). Conversely, a significant decrease in relative abundance from 18.2±.5.6% in control to 7±.3.4% in of the genus Paraplectonemus was also detected. Additionally, while the abundance of active PAH degraders was significantly higher in spiked sediments than in the controls, no significant effect of our organic mixture was found on nitrification rates or the expression of AmoA (bacterial ammonia oxidizer gene). Our data indicate that mixtures of organic pollutants can have significant effects on microbenthic community structure even when its individual components are present at concentrations below its specific toxicity. In addition, we suggest that eRNA-based metabarcoding can offer important insights in microbenthic community structure and activities and further empathizes the potential of meiofauna as bio-indicators of chemical contamination in benthic ecosystems.