Damian E. Helbling

Rapid removal of organic micropollutants from water by a porous β-cyclodextrin polymer.

The global occurrence in water resources of organic micropollutants, such as pesticides and pharmaceuticals, has raised concerns about potential negative effects on aquatic ecosystems and human health. Activated carbons are the most widespread adsorbent materials used to remove organic pollutants from water but they have several deficiencies, including slow pollutant uptake (of the order of hours) and poor removal of many relatively hydrophilic micropollutants. Furthermore, regenerating spent activated carbon is energy intensive (requiring heating to 500–900 degrees Celsius) and does not fully restore performance. Insoluble polymers of β-cyclodextrin, an inexpensive, sustainably produced macrocycle of glucose, are likewise of interest for removing micropollutants from water by means of adsorption. β-cyclodextrin is known to encapsulate pollutants to form well-defined host–guest complexes, but until now cross-linked β-cyclodextrin polymers have had low surface areas and poor removal performance compared to conventional activated carbons. Here we crosslink β-cyclodextrin with rigid aromatic groups, providing a high-surface-area, mesoporous polymer of β-cyclodextrin. It rapidly sequesters a variety of organic micropollutants with adsorption rate constants 15 to 200 times greater than those of activated carbons and non-porous β-cyclodextrin adsorbent materials. In addition, the polymer can be regenerated several times using a mild washing procedure with no loss in performance. Finally, the polymer outperformed a leading activated carbon for the rapid removal of a complex mixture of organic micropollutants at environmentally relevant concentrations. These findings demonstrate the promise of porous cyclodextrin-based polymers for rapid, flow-through water treatment.

High-Throughput Identification of Microbial Transformation Products of Organic Micropollutants

During wastewater treatment, many organic micropollutants undergo microbially mediated reactions resulting in the formation of transformation products (TPs). Little is known on the reaction pathways that govern these transformations or on the occurrence of microbial TPs in surface waters. Large sets of biotransformation data for organic micropollutants would be useful for assessing the exposure potential of these TPs and for enabling the development of structure-based biotransformation prediction tools. The objective of this work was to develop an efficient procedure to allow for high-throughput elucidation of TP structures for a broad and diverse set of xenobiotics undergoing microbially mediated transformation reactions. Six pharmaceuticals and six pesticides were spiked individually into batch reactors seeded with activated sludge. Samples from the reactors were separated with HPLC and analyzed by linear ion trap-orbitrap mass spectrometry. Candidate TPs were preliminarily identified with an innovative post-acquisition data processing method based on target and non-target screenings of the full-scan MS data. Structures were proposed following interpretation of MS spectra and MS/MS fragments. Previously unreported microbial TPs were identified for the pharmaceuticals bezafibrate, diazepam, levetiracetam, oseltamivir, and valsartan. A variety of previously reported and unreported TPs were identified for the pesticides. The results showed that the complementary use of the target and non-target screening methods allowed for a more comprehensive interpretation of the TPs generated than either would have provided individually.

Is biological treatment a viable alternative for micropollutant removal in drinking water treatment processes

In western societies, clean and safe drinking water is often taken for granted, but there are threats to drinking water resources that should not be underestimated. Contamination of drinking water sources by anthropogenic chemicals is one threat that is particularly widespread in industrialized nations. Recently, a significant amount of attention has been given to the occurrence of micropollutants in the urban water cycle. Micropollutants are bioactive and/or persistent chemicals originating from diverse sources that are frequently detected in water resources in the pg/L to μg/L range. The aim of this review is to critically evaluate the viability of biological treatment processes as a means to remove micropollutants from drinking water resources. We first place the micropollutant problem in context by providing a comprehensive summary of the reported occurrence of micropollutants in raw water used directly for drinking water production and in finished drinking water. We then present a critical discussion on conventional and advanced drinking water treatment processes and their contribution to micropollutant removal. Finally, we propose biological treatment and bioaugmentation as a potential targeted, cost-effective, and sustainable alternative to existing processes while critically examining the technical limitations and scientific challenges that need to be addressed prior to implementation. This review will serve as a valuable source of data and literature for water utilities, water researchers, policy makers, and environmental consultants. Meanwhile this review will open the door to meaningful discussion on the feasibility and application of biological treatment and bioaugmentation in drinking water treatment processes to protect the public from exposure to micropollutants.

Micropollutant biotransformation kinetics associate with WWTP process parameters and microbial community characteristics.

The objective of this work was to identify relevant wastewater treatment plant (WWTP) parameters and underlying microbial processes that influence the biotransformation of a diverse set of micropollutants. To do this, we determined biotransformation rate constants for ten organic micropollutants in batch reactors seeded with activated sludge from ten diverse WWTPs. The estimated biotransformation rate constants for each compound ranged between one and four orders of magnitude among the ten WWTPs. The biotransformation rate constants were tested for statistical associations with various WWTP process parameters, amoA transcript abundance, and acetylene-inhibited monooxygenase activity. We determined that (i) ammonia removal associates with oxidative micropollutant biotransformation reaction rates; (ii) archaeal but not bacterial amoA transcripts associate with both ammonia removal and oxidative micropollutant biotransformation reaction rates; and (iii) the activity of acetylene-inhibited monooxygenases (including ammonia monooxygenase) associates with ammonia removal and the biotransformation rate of isoproturon, but does not associate with all oxidative micropollutant biotransformations. In combination, these results lead to the conclusion that ammonia removal and amoA transcript abundance can potentially be predictors of oxidative micropollutant biotransformation reactions, but that the biochemical mechanism is not necessarily linked to ammonia monooxygenase activity.

A tiered procedure for assessing the formation of biotransformation products of pharmaceuticals and biocides during activated sludge treatment.

Upon partial degradation of polar organic micropollutants during activated sludge treatment, transformation products (TPs) may be formed that enter the aquatic environment in the treated effluent. However, TPs are rarely considered in prospective environmental risk assessments of wastewater-relevant compound classes such as pharmaceuticals and biocides. Here, we suggest and evaluate a tiered procedure, which includes a fast initial screening step based on high resolution tandem mass spectrometry (HR-MS/MS) and a subsequent confirmatory quantitative analysis, that should facilitate consideration of TPs formed during activated sludge treatment in the exposure assessment of micropollutants. At the first tier, potential biotransformation product structures of seven pharmaceuticals (atenolol, bezafibrate, ketoprofen, metoprolol, ranitidine, valsartan, and venlafaxine) and one biocide (carbendazim) were assembled using computer-based biotransformation pathway prediction and known human metabolites. These target structures were screened for in sludge-seeded batch reactors using HR-MS/MS. The 12 TPs found to form in the batch experiments were then searched for in the effluents of two full-scale, municipal wastewater treatment plants (WWTPs) to confirm the environmental representativeness of this first tier. At the second tier, experiments with the same sludge-seeded batch reactors were carried out to acquire kinetic data for major TPs that were then used as input parameters into a cascaded steady-state completely-stirred tank reactor (CSTR) model for predicting TP effluent concentrations. Predicted effluent concentrations of four parent compounds and their three major TPs were corroborated by comparison to 3-day average influent and secondary effluent mass flows from one municipal WWTP. CSTR model-predicted secondary effluent mass flows agreed within a factor of two with measured mass flows and confidence intervals of predicted and measured mass flows overlapped in all cases. The observed agreement suggests that the combination of batch-determined transformation kinetics with a simple WWTP model may be suitable for estimating aquatic exposure to TPs formed during activated sludge treatment. Overall, we recommend the tiered procedure as a realistic and cost-effective approach to include consideration of TPs of wastewater-relevant compounds into exposure assessment in the context of prospective chemical risk assessment.

Structure-Based Interpretation of Biotransformation Pathways of Amide-Containing Compounds in Sludge-Seeded Bioreactors

Partial microbial degradation of xenobiotic compounds in wastewater treatment plants (WWTPs) results in the formation of transformation products, which have been shown to be released and detectable in surface waters. Rule-based systems to predict the structures of microbial transformation products often fail to discriminate between alternate transformation pathways because structural influences on enzyme-catalyzed reactions in complex environmental systems are not well understood. The amide functional group is one such common substructure of xenobiotic compounds that may be transformed through alternate transformation pathways. The objective of this work was to generate a self-consistent set of biotransformation data for amide-containing compounds and to develop a metabolic logic that describes the preferred biotransformation pathways of these compounds as a function of structural and electronic descriptors. We generated transformation products of 30 amide-containing compounds in sludge-seeded bioreactors and identified them by means of HPLC-linear ion trap-orbitrap mass spectrometry. Observed biotransformation reactions included amide hydrolysis and N-dealkylation, hydroxylation, oxidation, ester hydrolysis, dehalogenation, nitro reduction, and glutathione conjugation. Structure-based interpretation of the results allowed for identification of preferences in biotransformation pathways of amides: primary amides hydrolyzed rapidly; secondary amides hydrolyzed at rates influenced by steric effects; tertiary amides were N-dealkylated unless specific structural moieties were present that supported other more readily enzyme-catalyzed reactions. The results allowed for the derivation of a metabolic logic that could be used to refine rule-based biotransformation pathway prediction systems to more specifically predict biotransformations of amide-containing compounds.

Continuous monitoring of residual chlorine concentrations in response to controlled microbial intrusions in a laboratory-scale distribution system

The objective of this work was to evaluate the efficacy of deploying free chlorine sensors as surrogate monitors for bacterial contamination events in drinking water distribution systems. An on-line sensor integral with a laboratory-scale distribution system (LDS) was shown to respond rapidly to changes in residual free chlorine concentrations induced by injected loads of Escherichia coli suspended in a chlorine demand free buffer. The magnitude of the residual response was proportional to the injected cell concentration, the background free chlorine concentration in the LDS, and the contact time between the chlorine residual and the injected suspension, consistent with previous results in batch reactors. The magnitude of the residual response was predicted when kinetic models developed from reaction kinetics between free chlorine and E. coli determined in batch systems were evaluated at contact times determined from LDS hydraulics. This result highlights the suitability of using batch kinetics when modeling contaminant-induced chlorine decay in the distribution system. Modeling the propagation of chlorine demand signals generated by specific pathogens could aid in the assessment of distribution system vulnerability.

The activity level of a microbial community function can be predicted from its metatranscriptome

The objective of this work was to improve our understanding of the quantitative predictive capabilities of metatranscriptomics. To meet this objective, we investigated whether we can predict the activity level of a specific biochemical function based on the abundance of the corresponding gene transcript within measured community metatranscriptomes. In addition, we investigated the lower limit of a microorganisms abundance that still allows detection of its transcripts within a metatranscriptome and prediction of the activity levels of the enzyme encoded by the transcript. To do this, we amended an undefined microbial community with varying fractions of an Escherichia coli strain that can catalyze a specific transformation reaction for the herbicide atrazine. We observed a linear and proportional relationship between the activity level of the transformation reaction and the abundance of its associated encoding transcript down to an E. coli cell density of 0.05% of the population.

Systematic Exploration of Biotransformation Reactions of Amine-Containing Micropollutants in Activated Sludge

The main removal process for polar organic micropollutants during activated sludge treatment is biotransformation, which often leads to the formation of stable transformation products (TPs). Because the analysis of TPs is challenging, the use of pathway prediction systems can help by generating a list of suspected TPs. To complete and refine pathway prediction, comprehensive biotransformation studies for compounds exhibiting pertinent functional groups under environmentally relevant conditions are needed. Because many polar organic micropollutants present in wastewater contain one or several amine functional groups, we systematically explored amine biotransformation by conducting experiments with 19 compounds that contained 25 structurally diverse primary, secondary, and tertiary amine moieties. The identification of 144 TP candidates and the structure elucidation of 101 of these resulted in a comprehensive view on initial amine biotransformation reactions. The reactions with the highest relevance were N-oxidation, N-dealkylation, N-acetylation, and N-succinylation. Whereas many of the observed reactions were similar to those known for the mammalian metabolism of amine-containing xenobiotics, some N-acylation reactions were not previously described. In general, different reactions at the amine functional group occurred in parallel. Finally, recommendations on how these findings can be implemented to improve microbial pathway prediction of amine-containing micropollutants are given.

Emerging chemicals and the evolution of biodegradation capacities and pathways in bacteria

The number of new chemicals produced is increasing daily by the thousands, and it is inevitable that many of these chemicals will reach the environment. Current research provides an understanding of how the evolution of promiscuous enzymes and the recruitment of enzymes available from the metagenome allows for the assembly of these pathways. Nevertheless, physicochemical constraints including bioavailability, bioaccessibility, and the structural variations of similar chemicals limit the evolution of biodegradation pathways. Similarly, physiological constraints related to kinetics and substrate utilization at low concentrations likewise limit chemical-enzyme interactions and consequently evolution. Considering these new data, the biodegradation decalogue still proves valid while at the same time the underlying mechanisms are better understood.