Uranium(VI) adsorption and transport in three natural, heterogeneous subsurface media were investigated in batch and column experiments. The rate of U(VI) adsorption to the natural samples was rapid over the first few hours of the experiments, and then slowed appreciably after 24 to 48 h. The adsorption of U(VI) to the samples was also nonlinear, suggesting a decreasing attraction for the surface with increased surface loading. The extent of adsorption on each of the media was strongly pH‐dependent, increasing sharply as the pH increased from 4.5 to 5.5 and then decreasing sharply over the pH range 7.5 to 8.5 as the concentration of dissolved carbonate and U(VI)–carbonate complexes increased. The similarities in the pH‐dependent behavior between the three materials despite differences in bulk mineralogy was likely due to the similar Fe contents of the materials. The transport of U(VI) through packed columns of the soils and sediments was significantly retarded but reversible. The local equilibrium assumption and the batch‐measured adsorption isotherms dramatically underestimated the degree of retardation observed in the columns. The U(VI) displacement experiments were modeled with the one‐dimensional advective–dispersive equation and several different model formulations describing the interactions of U(VI) with the solid phase. These models were able to fit the observed breakthrough curves within 0.1 root mean square error of the initial concentration.
Methylmercury (MeHg) is a bioaccumulative toxic contaminant in many ecosystems, but factors governing its production are poorly understood. Recent work has shown that the anaerobic microbial conversion of mercury (Hg) to MeHg requires the Hg-methylation genes hgcAB and that these genes can be used as biomarkers in PCR-based estimators of Hg-methylator abundance. In an effort to determine reliable methods for assessing hgcA abundance and diversity and linking them to MeHg concentrations, multiple approaches were compared including metagenomic shotgun sequencing, 16S rRNA gene pyrosequencing and cloning/sequencing hgcAB gene products. Hg-methylator abundance was also determined by quantitative hgcA qPCR amplification and metaproteomics for comparison to the above measurements. Samples from eight sites were examined covering a range of total Hg (HgT; 0.03–14 mg kg–1 dry wt. soil) and MeHg (0.05–27 μg kg–1 dry wt. soil) concentrations. In the metagenome and amplicon sequencing of hgcAB diversity, the Deltaproteobacteria were the dominant Hg-methylators while Firmicutes and methanogenic Archaea were typically ∼50% less abundant. This was consistent with metaproteomics estimates where the Deltaproteobacteria were steadily higher. The 16S rRNA gene pyrosequencing did not have sufficient resolution to identify hgcAB + species. Metagenomic and hgcAB results were similar for Hg-methylator diversity and clade-specific qPCR-based approaches for hgcA are only appropriate when comparing the abundance of a particular clade across various samples. Weak correlations between Hg-methylating bacteria and soil Hg concentrations were observed for similar environmental samples, but overall total Hg and MeHg concentrations poorly correlated with Hg-cycling genes.
Neurotoxic methylmercury (MeHg) is produced by anaerobic Bacteria and Archaea possessing the genes hgcAB, but it is unknown how organic substrate and electron acceptor availability impacts the distribution and abundance of these organisms. We evaluated the impact of organic substrate amendments on mercury (Hg) methylation rates, microbial community structure, and the distribution of hgcAB+ microbes with sediments. Sediment slurries were amended with short-chain fatty acids, alcohols, or a polysaccharide. Minimal increases in MeHg were observed following lactate, ethanol, and methanol amendments, while a significant decrease (∼70%) was observed with cellobiose incubations. Postincubation, microbial diversity was assessed via 16S rRNA amplicon sequencing. The presence of hgcAB+ organisms was assessed with a broad-range degenerate PCR primer set for both genes, while the presence of microbes in each of the three dominant clades of methylators (Deltaproteobacteria, Firmicutes, and methanogenic Archaea) was measured with clade-specific degenerate hgcA quantitative PCR (qPCR) primer sets. The predominant microorganisms in unamended sediments consisted of Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria. Clade-specific qPCR identified hgcA+ Deltaproteobacteria and Archaea in all sites but failed to detect hgcA+ Firmicutes. Cellobiose shifted the communities in all samples to ∼90% non-hgcAB-containing Firmicutes (mainly Bacillus spp. and Clostridium spp.). These results suggest that either expression of hgcAB is downregulated or, more likely given the lack of 16S rRNA gene presence after cellobiose incubation, Hg-methylating organisms are largely outcompeted by cellobiose degraders or degradation products of cellobiose. These results represent a step toward understanding and exploring simple methodologies for controlling MeHg production in the environment.IMPORTANCE Methylmercury (MeHg) is a neurotoxin produced by microorganisms that bioacummulates in the food web and poses a serious health risk to humans. Currently, the impact that organic substrate or electron acceptor availability has on the mercury (Hg)-methylating microorganisms is unclear. To study this, we set up microcosm experiments exposed to different organic substrates and electron acceptors and assayed for Hg methylation rates, for microbial community structure, and for distribution of Hg methylators. The sediment and groundwater was collected from East Fork Poplar Creek in Oak Ridge, TN. Amendment with cellobiose (a lignocellulosic degradation by-product) led to a drastic decrease in the Hg methylation rate compared to that in an unamended control, with an associated shift in the microbial community to mostly nonmethylating Firmicutes. This, along with previous Hg-methylating microorganism identification methods, will be important for identifying strategies to control MeHg production and inform future remediation strategies.
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