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The release of toxic organic pollutants and heavy metals by primitive electronic waste (e-waste) processing to waterways has raised significant concerns, but little is known about their potential ecological effects on aquatic biota especially microorganisms. We characterized the microbial community composition and diversity in sediments sampled along two rivers consistently polluted by e-waste, and explored how community functions may respond to the complex combined pollution. High-throughput 16S rRNA gene sequencing showed that Proteobacteria (particularly Deltaproteobacteria) dominated the sediment microbial assemblages followed by Bacteroidetes, Acidobacteria, Chloroflexi and Firmicutes. PICRUSt metagenome inference provided an initial insight into the metabolic potentials of these e-waste affected communities, speculating that organic pollutants degradation in the sediment might be mainly performed by some of the dominant genera (such as Sulfuricurvum, Thiobacillus and Burkholderia) detected in situ. Statistical analyses revealed that toxic organic compounds contributed more to the observed variations in sediment microbial community structure and predicted functions (24.68% and 8.89%, respectively) than heavy metals (12.18% and 4.68%), and Benzo(a)pyrene, bioavailable lead and electrical conductivity were the key contributors. These results have shed light on the microbial assemblages in e-waste contaminated river sediments, indicating a potential influence of e-waste pollution on the microbial community structure and function in aquatic ecosystems., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The crude processing of electronic waste (e-waste) has led to serious contamination in soils. While microorganisms may play a key role in remediation of the contaminated soils, the ecological effects of combined pollution (heavy metals, polychlorinated biphenyls, and polybrominated diphenyl ethers) on the composition and diversity of microbial communities remain unknown. In this study, a suite of e-waste contaminated soils were collected from Guiyu, China, and the indigenous microbial assemblages were profiled by 16S rRNA high-throughput sequencing and clone library analysis. Our data revealed significant differences in microbial taxonomic composition between the contaminated and the reference soils, with Proteobacteria, Acidobacteria, Bacteroidetes, and Firmicutes dominating the e-waste-affected communities. Genera previously identified as organic pollutants-degrading bacteria, such as Acinetobacter, Pseudomonas, and Alcanivorax, were frequently detected. Canonical correspondence analysis revealed that approximately 70% of the observed variation in microbial assemblages in the contaminated soils was explained by eight environmental variables (including soil physiochemical parameters and organic pollutants) together, among which moisture content, decabromodiphenyl ether (BDE-209), and copper were the major factors. These results provide the first detailed phylogenetic look at the microbial communities in e-waste contaminated soils, demonstrating that the complex combined pollution resulting from improper e-waste recycling may significantly alter soil microbiota.