Microcosm-based Analysis of the Geochemical Drivers of Mercury Biomethylation in Contaminated Sediments

English Abstract:

Methylmercury contamination in aquatic systems is a pervasive problem primarily due to its widespread generation by sediment-associated microbes. The bio-geochemical cycling of mercury methylation is closely tied to Fe/S cycling, as predominantly sulfate- and iron-reducing bacteria have been found to mediate the conversion of mercury to methylmercury. Mercury resistance genes are more widespread, as many microorganisms can alter the speciation and bioavailability of mercury or demethylate existing methylmercury, meaning that further and integrated microbiological and geochemical study is needed to understand more completely how this is carried out in aquatic systems. Past research has explored these relationships in pure cultures or has concentrated on one or a few geochemical factors, however in this study microcosms were used to characterize mercury methylation in endemic microbial communities, under environmental sedimentary geochemical conditions. Two sets of batch microcosms containing local sediment (Cootes Paradise, Hamilton Harbour), including endemic microbes, and ultrapure water spiked with inorganic mercury at low (~500ppb) and high (~3ppm) concentrations were constructed and tested to identify linkages between Fe, S and C cycling and the evolution of methylmercury. The batch microcosms were sampled over the course of two months, at regular intervals to capture short-term and long-term consequences of mercury inundation. Sterile and un-spiked controls were included to adjust for abiotic transformations of mercury mediated by light infiltration or organic residues, and for the background mercury present in the system. Both overlying water and sediments were sampled for mercury speciation (CH₃Hg and HgT, assessed using cold vapour spectrometry), organic carbon content (TOC, DOC), and iron/sulfur species (Fe²⁺, Fe³⁺; H₂S, SO₄²⁻), and the microbial community structure was assessed by 16S rRNA analysis. The results from these batch experiments will be discussed.