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The effects of exposure concentration on the bioaccumulation of four perfluorinated chemicals (PFCs): perfluorooctanesulfonate (PFOS), perfluoroocanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorodecanoic acid (PFDA), was investigated using green mussels, Perna viridis. Mussels were exposed to concentrations of 1 μgL(-1) and 10 μgL(-1) of each PFC for 56 days, and the bioaccumulation factors (BAF) were found to range from 15 to 859 L/kg and from 12 to 473 L/kg at 1 μgL(-1) and 10 μgL(-1), respectively. For all compounds, the BAF was larger at the lower dosage. Results suggest that the bioaccumulation of PFCs is concentration dependent. This concentration dependency can be explained by a nonlinear adsorption mechanism, which was further supported by the experimental results. The sensitivity of BAF to exposure concentration was found to be positively related to perfluorinated chain length and the binding affinity of the compounds. Bioaccumulation of long chain carboxylates and sulfonates are more easily affected by concentration changes. The validity of the conventional kinetic method was examined by comparing the results with the fundamental steady-state method: in addition to the above-mentioned batch test, mussels were also subject to 24-day exposure (1 μgL(-1) and 10 μgL(-1)) followed by 24-day depuration. Contradictions were found in the resulting kinetic BAF and model curving fittings. A new kinetic model based on adsorption mechanism was proposed, which potentially provide more accurate description of the bioaccumulation process of PFCs.

Water quality is an emergent property of a complex system comprised of interacting microbial populations and introduced microbial and chemical contaminants. Studies leveraging next-generation sequencing (NGS) technologies are providing new insights into the ecology of microbially mediated processes that influence fresh water quality such as algal blooms, contaminant biodegradation, and pathogen dissemination. In addition, sequencing methods targeting small subunit (SSU) rRNA hypervariable regions have allowed identification of signature microbial species that serve as bioindicators for sewage contamination in these environments. Beyond amplicon sequencing, metagenomic and metatranscriptomic analyses of microbial communities in fresh water environments reveal the genetic capabilities and interplay of waterborne microorganisms, shedding light on the mechanisms for production and biodegradation of toxins and other contaminants. This review discusses the challenges and benefits of applying NGS-based methods to water quality research and assessment. We will consider the suitability and biases inherent in the application of NGS as a screening tool for assessment of biological risks and discuss the potential and limitations for direct quantitative interpretation of NGS data. Secondly, we will examine case studies from recent literature where NGS based methods have been applied to topics in water quality assessment, including development of bioindicators for sewage pollution and microbial source tracking, characterizing the distribution of toxin and antibiotic resistance genes in water samples, and investigating mechanisms of biodegradation of harmful pollutants that threaten water quality. Finally, we provide a short review of emerging NGS platforms and their potential applications to the next generation of water quality assessment tools.

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