Final Report Summary - PRODUCTS (Predicting environment-specific biotransformation of chemical contaminants)
PROduCTS sought to improve our ability to predict rates and products of microbial biotransformation for a broad variety of chemical contaminants accurately. This is essential for chemical risk management but also in the context of contaminated site remediation or the development of green chemical alternatives. To achieve this goal, research in PROduCTS was focused on explaining observed variability in biotransformation rates and pathways through the metabolic potential of the involved environmental microbial communities. The central hypothesis of PROduCTS was that reactions rather than substrate structures should be the core element of biotransformation prediction because similar biotransformation reactions are expected to be catalyzed by similar enzymes. Therefore, these reactions should show a similar dependency on environmental conditions and the metabolic potential of the communities shaped by those conditions.
In the experimental part of PROduCTS, we were able to demonstrate that compounds undergoing the same type of biotransformation reaction indeed showed consistent patterns of biotransformation kinetics across microbial communities adapted under different conditions (e.g. sludge age, temperature or chemical composition of growth medium) with stronger dependencies observed for oxidative transformations and less dependencies for substitution reactions. These findings suggested that shared enzymes or enzyme systems that are conjointly regulated catalyze the biotransformation reactions within such groups of compounds. In line with this principle, we were able to find significant correlations between gene transcript abundances and biotransformation rate constants that were in accordance with the known reactions catalyzed by the respective gene-encoded enzymes. Three important insights emerged from these findings: (i) A novel methodology combining high-throughput metatranscriptomic sequencing for characterizing community functions and high-resolution mass spectrometry for characterizing type and kinetics of biotransformation reactions has been developed and demonstrated, which, for the first time, allows investigating the causative agents of co-metabolic biotransformation of trace organic contaminants (TrOCs) in complex environmental microbial communities, (ii) co-metabolic biotransformation of TrOCs is catalyzed by widely available, rather unspecific enzymes or enzymes systems, and (iii) it should be possible to identify indicator compounds to probe different environments for their respective co-metabolic biotransformation potential.
In the data mining part of PROduCTS, we developed enviPath, an open source, publically available database and pathway prediction system for contaminant biotransformation information (http://envipath.org). We used enviPath to electronically encode two new data packages with information (half-lives, pathways, and metadata on study conditions) from regulatory soil degradation studies for approx. 300 pesticides (Eawag-Soil, released), and from activated sludge degradation studies for approx. 100 pharmaceuticals (Eawag-Sludge, to be released by end of 2019). While knowledge on transformation products can be, and has been, used directly to analytically screen for transformation products, e.g. in Swiss groundwater, we have mined the new data for two specific purposes so far: (i) We have identified missing rules and opportunities to use the annotated metadata to explain observed variability in biotransformation half-lives as preparation for training novel QSBR models on the Eawag-Soil data that would simultaneously predict biotransformation half-lives and pathways – an effort to be continued after termination of the project, and (ii) we have developed a read-across approach to predict soil half-lives from activated sludge half-lives, which is currently being further developed into a tool to implement benign-by-design considerations at the early stages of lead structure exploration.
In the experimental part of PROduCTS, we were able to demonstrate that compounds undergoing the same type of biotransformation reaction indeed showed consistent patterns of biotransformation kinetics across microbial communities adapted under different conditions (e.g. sludge age, temperature or chemical composition of growth medium) with stronger dependencies observed for oxidative transformations and less dependencies for substitution reactions. These findings suggested that shared enzymes or enzyme systems that are conjointly regulated catalyze the biotransformation reactions within such groups of compounds. In line with this principle, we were able to find significant correlations between gene transcript abundances and biotransformation rate constants that were in accordance with the known reactions catalyzed by the respective gene-encoded enzymes. Three important insights emerged from these findings: (i) A novel methodology combining high-throughput metatranscriptomic sequencing for characterizing community functions and high-resolution mass spectrometry for characterizing type and kinetics of biotransformation reactions has been developed and demonstrated, which, for the first time, allows investigating the causative agents of co-metabolic biotransformation of trace organic contaminants (TrOCs) in complex environmental microbial communities, (ii) co-metabolic biotransformation of TrOCs is catalyzed by widely available, rather unspecific enzymes or enzymes systems, and (iii) it should be possible to identify indicator compounds to probe different environments for their respective co-metabolic biotransformation potential.
In the data mining part of PROduCTS, we developed enviPath, an open source, publically available database and pathway prediction system for contaminant biotransformation information (http://envipath.org). We used enviPath to electronically encode two new data packages with information (half-lives, pathways, and metadata on study conditions) from regulatory soil degradation studies for approx. 300 pesticides (Eawag-Soil, released), and from activated sludge degradation studies for approx. 100 pharmaceuticals (Eawag-Sludge, to be released by end of 2019). While knowledge on transformation products can be, and has been, used directly to analytically screen for transformation products, e.g. in Swiss groundwater, we have mined the new data for two specific purposes so far: (i) We have identified missing rules and opportunities to use the annotated metadata to explain observed variability in biotransformation half-lives as preparation for training novel QSBR models on the Eawag-Soil data that would simultaneously predict biotransformation half-lives and pathways – an effort to be continued after termination of the project, and (ii) we have developed a read-across approach to predict soil half-lives from activated sludge half-lives, which is currently being further developed into a tool to implement benign-by-design considerations at the early stages of lead structure exploration.