Pollutants

Antimicrobial peptides (AMPs) are increasingly important as a last resort against multi-drug resistant bacteria due to resistance formation towards conventional antibiotics. However, many AMPs were introduced to the market before environmental risk assessment was required, e.g., by the European Medicines Agency (EMA) since 1998. While AMPs have been administered as antibiotics and growth promotors in feedstock since the 1960s and were reconsidered for human medicine by the EMA in 2013, details about their mobility and persistence in the environment remain unknown. This study investigated the environmental fate of three commonly used AMPs: bacitracins, daptomycin, and polymyxins B and E (Colistin). We observed moderate sorption affinity of daptomycin to standard European soils (K_d = 20.6–48.6), while polymyxins adsorbed irreversibly. Bacitracin variants sorbed slightly to sandy soil (K_d = 5.8–8) and significantly to clayey soil (K_d = 169–250). We further investigated photochemical and microbial transformation processes relevant in surface waters. We demonstrated that phototransformation of all AMPs was enhanced in the presence of dissolved organic matter and fast bimolecular reaction rate constant with singlet oxygen contributed largely to indirect phototransformation (15–41%). Phototransformation product analysis for daptomycin was consistent with expected modifications of the tryptophan and kynurenine moieties. Moreover, riverine biofilm communities demonstrated biotransformation potential for all AMPs. Our findings of sorption behaviour, photo- and biotransformation suggest that these processes play a critical role in the fate of bacitracins, daptomycin, and polymyxins in environmental systems.

Biotransformation of chemical contaminants is of importance in various natural and engineered systems. However, in complex microbial communities and with chemical contaminants at low concentrations, our current understanding of biotransformation at the level of enzyme-chemical interactions is limited. Here, we explored an approach to identify associations between micropollutant biotransformation and specific gene products in complex microbial communities, using association mining between chemical and metatranscriptomic data obtained from experiments with activated sludge grown at different solid retention times. We successfully demonstrate proportional relationships between the measured rate constants and associated gene transcripts for nitrification as a major community function, but also for the biotransformation of two nitrile-containing micropollutants (bromoxynil and acetamiprid) and transcripts of nitrile hydratases, a class of enzymes that we experimentally confirmed to produce the detected amide transformation products. As these results suggest that metatranscriptomic information can indeed be quantitatively correlated with low abundant community functions such as micropollutant biotransformation in complex microbial communities, we proceeded to explore the potential of association mining to highlight enzymes likely involved in catalyzing less well-understood micropollutant biotransformation reactions. Specifically, we use the cases of nitrile hydration and oxidative biotransformation reactions to show that the consideration of additional experimental evidence (such as information on biotransformation pathways) increases the likelihood of detecting plausible novel enzyme-chemical relationships. Finally, we identify a cluster of mono- and dioxygenase fourth-level enzyme classes that most strongly correlate with oxidative micropollutant biotransformation reactions in activated sludge.

Ferrous iron formed during microbial ferric iron reduction induces phase transformations of poorly crystalline into more crystalline and thermodynamically more stable iron (oxyhydr)oxides. Yet, characterizing the resulting decreases in the reactivity of the remaining oxide ferric iron toward reduction (i.e., its reducibility) has been challenging. Here, we used the reduction of six-line ferrihydrite by Shewanella oneidensis MR-1 as a model system to demonstrate that mediated electrochemical reduction (MER) allows directly following decreases in oxide ferric iron reducibility during the transformation of ferrihydrite into goethite and magnetite which we characterized by X-ray diffraction analysis and transmission electron microscopy imaging. Ferrihydrite was fully reducible in MER at both pH_MER of 5.0 and 7.5. Decreases in iron oxide reducibility associated with ferrihydrite transformation into magnetite were accessible at both pH_MER because the formed magnetite was not reducible under either of these conditions. Conversely, decreases in iron oxide reducibility associated with goethite formation were apparent only at the highest tested pH_MER of 7.5 and thus the thermodynamically least favorable conditions for iron oxide reductive dissolution. The unique capability to adjust the thermodynamic boundary conditions in MER to the specific reducibilities of individual iron (oxyhydr)oxides makes this electrochemical approach broadly applicable for studying changes in iron oxide reducibility in heterogeneous environmental samples such as soils and sediments.

The use of omics is gaining importance in the field of nanoecotoxicology; an increasing number of studies are aiming to investigate the effects and modes of action of engineered nanomaterials (ENMs) in this way. However, a systematic synthesis of the outcome of such studies regarding common responses and toxicity pathways is currently lacking. We developed an R-scripted computational pipeline to perform reanalysis and functional analysis of relevant transcriptomic data sets using a common approach, independent from the ENM type, and across different organisms, including Arabidopsis thaliana, Caenorhabditis elegans, and Danio rerio. Using the pipeline that can semiautomatically process data from different microarray technologies, we were able to determine the most common molecular mechanisms of nanotoxicity across extremely variable data sets. As expected, we found known mechanisms, such as interference with energy generation, oxidative stress, disruption of DNA synthesis, and activation of DNA-repair but also discovered that some less-described molecular responses to ENMs, such as DNA/RNA methylation, protein folding, and interference with neurological functions, are present across the different studies. Results were visualized in radar charts to assess toxicological response patterns allowing the comparison of different organisms and ENM types. This can be helpful to retrieve ENM-related hazard information and thus fill knowledge gaps in a comprehensive way in regard to the molecular underpinnings and mechanistic understanding of nanotoxicity.

We studied the role of the fish intestine as a barrier for organic chemicals using the epithelial barrier model built on the rainbow trout (Oncorhynchus mykiss) intestinal cell line, RTgutGC and the newly developed exposure chamber, TransFEr, specifically designed to work with hydrophobic and volatile chemicals. Testing 11 chemicals with a range of physicochemical properties (logK_OW: 2.2 to 6.3, logHLC: 6.1 to 2.3) and combining the data with a mechanistic kinetic model enabled the determination of dominant processes underlying the transfer experiments and the derivation of robust transfer rates. Against the current assumption in chemical uptake modeling, chemical transfer did not strictly depend on the logK_OW but resulted from chemical-specific intracellular accumulation and biotransformation combined with paracellular and active transport. Modeling also identified that conducting elaborate measurements of the plastic parts, including the polystyrene insert and the PET filter, is unnecessary and that stirring in the TransFEr chamber reduced the stagnant water layers compared to theoretical predictions. Aside from providing insights into chemical uptake via the intestinal epithelium, this system can easily be transferred to other cell-based barrier systems, such as the fish gill or mammalian intestinal models and may improve in vitro–in vivo extrapolation and prediction of chemical bioaccumulation into organisms.