Understanding the Dependence of Micropollutant Biotransformation Rates on Short-Term Temperature Shifts

Abstract

Temperature is a key factor that influences chemical biotransformation potential and rates, on which exposure and fate models rely to predict the environmental (micro)pollutant fate. Arrhenius-based models are currently implemented in environmental exposure assessment to adapt biotransformation rates to actual temperatures, assuming validity in the 0-30 °C range. However, evidence on how temperature shifts affect the physicochemical and microbial features in biological systems is scarce, questioning the validity of the existing modeling approaches. In this work, laboratory-scale batch assays were designed to investigate how a mixed microbial community responds to short-term temperature shifts, and how this impacts its ability to biotransform a range of structurally diverse micropollutants. Our results revealed three distinct kinetic responses at temperatures above 20 °C, mostly deviating from the classic Arrheniustype behavior. Micropollutants with similar temperature responses appeared to undergo mostly similar initial biotransformation reactions, with substitution-type reactions maintaining Arrhenius-type behavior up to higher temperatures than oxidation-type reactions. Above 20 °C, the microbial community also showed marked shifts in both composition and activity, which mostly correlated with the observed deviations from Arrhenius-type behavior, with compositional changes becoming a more relevant factor in biotransformations catalyzed by more specific enzymes (e.g., oxidation reactions). Our findings underline the need to re-examine and further develop current environmental fate models by integrating biological aspects, to improve accuracy in predicting the environmental fate of micropollutants.

Separation of Photochemical and Non-Photochemical Diurnal In-Stream Attenuation of Micropollutants

“…To address the question of the underlying changes in environmental conditions that result in non-photochemical diurnal attenuation, the environmental parameters river water temperature and pH with a diurnal pattern during the field study were considered (Figure A). Temperature dependency of k att can be predicted based on the Arrhenius equation (for details, see Supporting Information Section S6) . For bisoprolol, diurnal attenuation could be explained to a large extent by the temperature dependency of k att (Figure C), whereas for the other TrOCs including metoprolol (Figure B and Supporting Information Figure S8), additional processes are most likely relevant.…”

“…Second, the diurnal pattern could be caused by other reactive processes besides photochemistry such as biotransformation. Biotransformation could also cause a diurnal pattern, for instance, by differences in the temperature and water chemistry, for example, pH or a light-dependent metabolic activity …”

“…Temperature dependency of k att can be predicted based on the Arrhenius equation (for details, see Supporting Information Section S6). 27 For bisoprolol, diurnal attenuation could be explained to a large extent by the temperature dependency of k att (Figure 2C), whereas for the other TrOCs including metoprolol (Figure 2B and Supporting Information Figure S8), additional processes are most likely relevant. Interestingly, on the second day, k att were higher than those predicted based on temperature dependency for most TrOCs.…”

“…18 Second, the diurnal pattern could be caused by other reactive processes besides photochemistry such as biotransformation. Biotransformation could also cause a diurnal pattern, for instance, by differences in the temperature 27 and water chemistry, for example, pH or a lightdependent metabolic activity. 28 To determine for which TrOCs diurnal attenuation, expressed as a correlation with k att,DIC , can be explained mostly by a photochemical process, k att,TrOC can be expressed as the sum of rate constants of a diurnal photochemical process k photo and a time-independent rate constant (k night ), that is identical during day and night:…”

Methodological Advances to Study Contaminant Biotransformation: New Prospects for Understanding and Reducing Environmental Persistence?

“…Emerging sets of consistent information about both biotransformation kinetics and reactions across large numbers of diverse chemicals, now accessible through HRMS/MS analysis, allow us to study patterns of contaminant biotransformation as a function of environmental and operational conditions and across different microbial communities. Kinetic analysis of biotransformation experiments with differently conditioned activated sludge and riverine biofilm communities revealed characteristic trends for groups of substances undergoing similar types of initial transformation reactions, − suggesting that shared enzymes or enzyme systems that are conjointly regulated catalyze biotransformation reactions within such groups. In a number of recent studies exploring the influence of environmental or operational conditions on contaminant biotransformation across large sets of literature-retrieved data, global models embracing all compounds were therefore compared to class-specific models for groups of contaminants hypothesized to undergo similar initial biotransformation reactions.…”