Department Environmental Chemistry

For many polar organic micropollutants, biotransformation by activated sludge microorganisms is a major removal process during wastewater treatment. However, our current understanding of how wastewater treatment operations influence microbial communities and their micropollutant biotransformation potential is limited, leaving major parts of observed variability in biotransformation rates across treatment facilities unexplained. Here, we present biotransformation rate constants for 42 micropollutants belonging to different chemical classes along a gradient of solids retention time (SRT). The geometric mean of biomass-normalized first-order rate constants shows a clear increase between 3 d and 15 d SRT by 160% and 87%, respectively, in two experiments. However, individual micropollutants show a variety of trends. Rate constants of oxidative biotransformation reactions mostly increased with SRT. Yet, nitrifying activity could be excluded as primary driver. For substances undergoing other than oxidative reactions, i.e. mostly substitution-type reactions, more diverse dependencies on SRT were observed. Most remarkably, characteristic trends were observed for groups of substances undergoing similar types of initial transformation reaction, suggesting that shared enzymes or enzyme systems that are conjointly regulated catalyze biotransformation reactions within such groups. These findings open up opportunities for correlating rate constants with measures of enzyme abundance, which in turn should help to identify genes or gene products associated with the respective biotransformation reactions.

Aerobic biodegradation half-lives (half-lives) are key parameters used to evaluate pesticide persistence in soil. However, half-life estimates for individual pesticides often span several orders of magnitude, reflecting the impact that various environmental or experimental parameters have on half-lives in soil. In this work, we collected literature-reported half-lives for eleven pesticides along with associated metadata describing the environmental or experimental conditions under which they were derived. We then developed a multivariable framework to discover relationships between the half-lives and associated metadata. We first compared data for the herbicide atrazine collected from 95 laboratory and 65 field studies. We discovered that atrazine application history and soil texture were the parameters that have the largest influence on the observed half-lives in both types of studies. We then extended the analysis to include ten additional pesticides with data collected exclusively from laboratory studies. We found that, when data were available, pesticide application history and biomass concentrations were always positively associated with half-lives. The relevance of other parameters varied among the pesticides, but in some cases the variability could be explained by the physicochemical properties of the pesticides. For example, we found that the relative significance of the organic carbon content of soil for determining half-lives depends on the relative solubility of the pesticide. Altogether, our analyses highlight the reciprocal influence of both environmental parameters and intrinsic physicochemical properties for determining half-lives in soil.

The presence of antibiotics in treated wastewater and consequently in surface and groundwater resources raises concerns about the formation and spread of antibiotic resistance. Improving the removal of antibiotics during wastewater treatment therefore is a prime objective of environmental engineering. Here we obtained a detailed picture of the fate of sulfonamide antibiotics during activated sludge treatment using a combination of analytical methods. We show that pterin-sulfonamide conjugates, which are formed when sulfonamides interact with their target enzyme to inhibit folic acid synthesis, represent a major biotransformation route for sulfonamides in laboratory batch experiments with activated sludge. The same major conjugates were also present in the effluents of nine Swiss wastewater treatment plants. The demonstration of this biotransformation route, which is related to bacterial growth, helps explain seemingly contradictory views on optimal conditions for sulfonamide removal. More importantly, since pterinsulfonamide conjugates show retained antibiotic activity, our findings suggest that risk from exposure to sulfonamide antibiotics may be less reduced during wastewater treatment than previously assumed. Our results thus further emphasize the inadequacy of focusing on parent compound removal and the importance of investigating biotransformation pathways and removal of bioactivity to properly assess contaminant removal in both engineered and natural systems.

To optimize removal of organic micropollutants from the water cycle, understanding the processes during activated sludge treatment is essential. In this study, we hypothesize that aliphatic amines, which are highly abundant among organic micropollutants, are partly removed from the water phase in activated sludge through ion trapping in protozoa. In ion trapping, which has been extensively investigated in medical research, the neutral species of amine-containing compounds diffuse through the cell membrane and further into acidic vesicles present in eukaryotic cells such as protozoa. There they become trapped because diffusion of the positively charged species formed in the acidic vesicles is strongly hindered. We tested our hypothesis with two experiments. First, we studied the distribution of the fluorescent amine acridine orange in activated sludge by confocal fluorescence imaging. We observed intense fluorescence in distinct compartments of the protozoa, but not in the bacterial biomass. Second, we investigated the distribution of 12 amine-containing and eight control micropollutants in both regular activated sludge and sludge where the protozoa had been inactivated. In contrast to most control compounds, the amine-containing micropollutants displayed a distinctly different behavior in the noninhibited sludge compared to the inhibited one: (i) more removal from the liquid phase; (ii) deviation from first-order kinetics for the removal from the liquid phase; and (iii) higher amounts in the solid phase. These results provide strong evidence that ion trapping in protozoa occurs and that it is an important removal mechanism for amine-containing micropollutants in batch experiments with activated sludge that has so far gone unnoticed. We expect that our findings will trigger further investigations on the importance of this process in full-scale wastewater treatment systems, including its relevance for accumulation of ammonium.

Developing models for the prediction of microbial biotransformation pathways and half-lives of trace organic contaminants in different environments requires as training data easily accessible and sufficiently large collections of respective biotransformation data that are annotated with metadata on study conditions. Here, we present the Eawag-Soil package, a public database that has been developed to contain all freely accessible regulatory data on pesticide degradation in laboratory soil simulation studies for pesticides registered in the EU (282 degradation pathways, 1535 reactions, 1619 compounds and 4716 biotransformation half-life values with corresponding metadata on study conditions). We provide a thorough description of this novel data resource, and discuss important features of the pesticide soil degradation data that are relevant for model development. Most notably, the variability of half-life values for individual compounds is large and only about one order of magnitude lower than the entire range of median half-life values spanned by all compounds, demonstrating the need to consider study conditions in the development of more accurate models for biotransformation prediction. We further show how the data can be used to find missing rules relevant for predicting soil biotransformation pathways. From this analysis, eight examples of reaction types were presented that should trigger the formulation of new biotransformation rules, e.g., Ar-OH methylation, or the extension of existing rules, e.g., hydroxylation in aliphatic rings. The data were also used to exemplarily explore the dependence of half-lives of different amide pesticides on chemical class and experimental parameters. This analysis highlighted the value of considering initial transformation reactions for the development of meaningful quantitative-structure biotransformation relationships (QSBR), which is a novel opportunity offered by the simultaneous encoding of transformation reactions and corresponding half-lives in Eawag-Soil. Overall, Eawag-Soil provides an unprecedentedly rich collection of manually extracted and curated biotransformation data, which should be useful in a great variety of applications.

Improved micropollutant (MP) biotransformation during biological wastewater treatment has been associated with high ammonia oxidation activities, suggesting co-metabolic biotransformation by ammonia oxidizing bacteria as an underlying mechanism. The goal of this study was to clarify the contribution of ammonia oxidizing bacteria to increased MP degradation in nitrifying activated sludge (NAS) communities using a series of inhibition experiments. To this end, we treated a NAS community with two different ammonia oxidation inhibitors, namely octyne (OCT), a mechanistic inhibitor that covalently binds to ammonia monooxygenases, and allylthiourea (ATU), a copper chelator that depletes copper ions from the active center of ammonia monooxygenases. We investigated the biotransformation of 79 structurally different MPs by the inhibitor-treated and untreated sludge communities. Fifty-five compounds exhibited over 20% removal in the untreated control after a 46 h-incubation. Of these, 31 compounds were significantly inhibited by either ATU and/or OCT. For 17 of the 31 MPs, the inhibition by ATU at 46 h was substantially higher than by OCT despite the full inhibition of ammonia oxidation by both inhibitors. This was particularly the case for almost all thioether and phenylurea compounds tested, suggesting that in nitrifying activated sludge communities, ATU does not exclusively act as an inhibitor of bacterial ammonia oxidation. Rather, ATU also inhibited enzymes contributing to MP biotransformation but not to bulk ammonia oxidation. Thus, inhibition studies with ATU tend to overestimate the contribution of ammonia-oxidizing bacteria to MP biotransformation in nitrifying activated sludge communities. Biolog tests revealed only minor effects of ATU on the heterotrophic respiration of common organic substrates by the sludge community, suggesting that ATU did not affect enzymes that were essential in energy conservation and central metabolism of heterotrophs. By comparing ATU- and OCT-treated samples, as well as before and after ammonia oxidation was recovered in OCT-treated samples, we were able to demonstrate that ammonia-oxidizing bacteria were highly involved in the biotransformation of four compounds: asulam, clomazone, monuron and trimethoprim.

The University of Minnesota Biocatalysis/Biodegradation Database and Pathway Prediction System (UM-BBD/PPS) has been a unique resource covering microbial biotransformation pathways of primarily xenobiotic chemicals for over 15 years. This paper introduces the successor system, enviPath (The Environmental Contaminant Biotransformation Pathway Resource), which is a complete redesign and reimplementation of UM-BBD/PPS. enviPath uses the database from the UM-BBD/PPS as a basis, extends the use of this database, and allows users to include their own data to support multiple use cases. Relative reasoning is supported for the refinement of predictions and to allow its extensions in terms of previously published, but not implemented machine learning models. User access is simplified by providing a REST API that simplifies the inclusion of enviPath into existing workflows. An RDF database is used to enable simple integration with other databases. enviPath is publicly available at envipath.org with free and open access to its core data.

There is increasing interest in using meta-omics association studies to investigate contaminant biotransformations. The general strategy is to characterize the complete set of genes, transcripts, or enzymes from in situ environmental communities and use the abundances of particular genes, transcripts, or enzymes to establish associations with the communities' potential to biotransform one or more contaminants. The associations can then be used to generate hypotheses about the underlying biological causes of particular biotransformations. While meta-omics association studies are undoubtedly powerful, they have a tendency to generate large numbers of non-causal associations, making it potentially difficult to identify the genes, transcripts, or enzymes that cause or promote a particular biotransformation. In this perspective, we describe general scenarios that could lead to pervasive non-causal associations or conceal causal associations. We next explore our own published data for evidence of pervasive non-causal associations. Finally, we evaluate whether causal associations could be identified despite the discussed limitations. Analysis of our own published data suggests that, despite their limitations, meta-omics association studies might still be useful for improving our understanding and predicting the contaminant biotransformation capacities of microbial communities.