enviRule: an end-to-end system for automatic extraction of reaction patterns from environmental contaminant biotransformation pathways

Transformation products (TPs) of man-made chemicals, formed through microbially mediated transformation in the environment, can have serious adverse environmental effects, yet the analytical identification of TPs is challenging. Rule-based prediction tools are successful in predicting TPs, especially in environmental chemistry applications that typically have to rely on small datasets, by imparting the existing knowledge on enzyme-mediated biotransformation reactions. However, the rules extracted from biotransformation reaction databases usually face the issue of being over/under-generalized and are not flexible to be updated with new reactions. We developed an automatic rule extraction tool called enviRule. It clusters biotransformation reactions into different groups based on the similarities of reaction fingerprints, and then automatically extracts and generalizes rules for each reaction group in SMARTS format. It optimizes the genericity of automatic rules against the downstream TP prediction task. Models trained with automatic rules outperformed the models trained with manually curated rules by 30% in the area under curve (AUC) scores. Moreover, automatic rules can be easily updated with new reactions, highlighting enviRule’s strengths for both automatic extraction of optimized reactions rules and automated updating thereof

Making waves: Enhancing pollutant biodegradation via rational engineering of microbial consortia.

Biodegradation holds promise as an effective and sustainable process for the removal of synthetic chemical pollutants. Nevertheless, rational engineering of biodegradation for pollutant remediation remains an unfulfilled goal, while chemical pollution of waters and soils continues to advance. Efforts to (i) identify functional bacteria from aquatic and soil microbiomes, (ii) assemble them into biodegrading consortia, and (iii) identify maintenance and performance determinants, are challenged by large number of pollutants and the complexity in the enzymology and ecology of pollutant biodegradation. To overcome these challenges, approaches that leverage knowledge from environmental bio-chem-informatics and metabolic engineering are crucial. Here, we propose a novel high-throughput bio-chem-informatics pipeline, to link chemicals and their predicted biotransformation pathways with potential enzymes and bacterial strains. Our framework systematically selects the most promising candidates for the degradation of chemicals with unknown biotransformation pathways and associated enzymes from the vast array of aquatic and soil bacteria. We substantiated our perspective by validating the pipeline for two chemicals with known or predicted pathways and show that our predicted strains are consistent with strains known to biotransform those chemicals. Such pipelines can be integrated with metabolic network analysis built upon genome-scale models and ecological principles to rationally design fit-for-purpose bacterial communities for augmenting deficient biotransformation functions and study operational and design parameters that influence their structure and function. We believe that research in this direction can pave the way for achieving our long-term goal of enhancing pollutant biodegradation

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

Complex microbial communities in environmental systems play a key role in the detoxification of chemical contaminants by transforming them into less active metabolites or by complete mineralization. Biotransformation, i.e., transformation by microbes, is well understood for a number of priority pollutants, but a similar level of understanding is lacking for many emerging contaminants encountered at low concentrations and in complex mixtures across natural and engineered systems. Any advanced approaches aiming to reduce environmental exposure to such contaminants (e.g., novel engineered biological water treatment systems, design of readily degradable chemicals, or improved regulatory assessment strategies to determine contaminant persistence a priori) will depend on understanding the causal links among contaminant removal, the key driving agents of biotransformation at low concentrations (i.e., relevant microbes and their metabolic activities), and how their presence and activity depend on environmental conditions. In this Perspective, we present the current understanding and recent methodological advances that can help to identify such links, even in complex environmental microbiomes and for contaminants present at low concentrations in complex chemical mixtures. We discuss the ensuing insights into contaminant biotransformation across varying environments and conditions and ask how much closer we have come to designing improved approaches to reducing environmental exposure to contaminants

Biodegradation of the steroid progesterone in surface waters

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonMany studies measuring the occurrence of pharmaceuticals, understanding their environmental fate and the risk they pose to surface water resources have been published. However, very little is known about the relevant transformation products which result from the wide range of biotic and abiotic degradation processes that these compounds undergo in sewers, storage tanks, during engineered treatment and in the environment. Thus, the present study primarily investigated the degradation of the steroid progesterone (P4) in natural systems (rivers), with a focus on the identification and characterisation of transformation products. Initial work focussed on assessing the removal of selected compounds (Diclofenac, Fluoxetine, Propranolol and P4) from reed beds, with identification of transformation products in a field site being attempted. However, it was determined that concentrations of parent compounds and products would be too low to work with in the field, and a laboratory study was designed which focussed on P4. Focus on P4 was based on literature evidence of its rapid biodegradability relative to the other model compounds and its usage patterns globally. River water sampling for the laboratory-based degradation study was carried out at 1 km downstream of four south east England sewage works (Blackbirds, Chesham, High Wycombe and Maple Lodge) effluent discharge points. Suspected P4 transformation products were initially identified from predictions by the EAWAG Biocatalysis Biodegradation Database (EAWAG BBD) and from a literature review. At a later stage of the present work, a replacement model for EAWAG BBD (enviPath) which became available, was used to predict P4 degradation and results were compared. Samples were analysed using low resolution and accurate-mass time-of-flight mass spectrometers. Three degradation studies were conducted. Sampling for all studies was carried out at the same time in the year to minimize temporal variability in conditions and allow for effective comparison of results. Androgenic and progesterone yeast screens were carried out to assess the biological activity of transformation products.Nigeria Tertiary Education Trust Fund (TETFund), the Uduaghan led-administration of the Delta State Government, the 2010-2015 board members of the Delta State Scholarship Board

Enzymatic cometabolic biotransformation of organic micropollutants in wastewater treatment plants: a review

Biotransformation of trace-level organic micropollutants (OMPs) by complex microbial communities in wastewater treatment facilities is a key process for their detoxification and environmental impact reduction. Therefore, understanding the metabolic activities and mechanisms that contribute to their biotransformation is essential when developing approaches aiming to minimize their discharge. This review addresses the relevance of cometabolic processes and discusses the main enzymatic activities currently known to take part in OMPs removal under different redox environments in the compartments of wastewater treatment plants. Furthermore, the most common methodologies to decipher such enzymes are discussed, including the use of in vitro enzyme assays, enzymatic inhibitors, the analysis of transformation products and the application of several -omic techniques. Finally, perspectives on major challenges and future research requirements to improve OMPs biotransformation are proposedThis research was funded by the Spanish Government (Agencia Estatal de Investigación) through the ANTARES project (PID2019-110346RB-C21) and a PhD Xunta de Galicia Grant (ED481A-2018/113, David Kennes). Authors from Universidade de Santiago de Compostela belong to Galician Competitive Research Group (GRC ED431C 2017/29), which is co-funded by FEDER (EU)S

Potential and limitations for monitoring of pesticide biodegradation at trace concentrations in water and soil

Pesticides application on agricultural fields results in pesticides being released into the environment, reaching soil, surface water and groundwater. Pesticides fate and transformation in the environment depend on environmental conditions as well as physical, chemical and biological degradation processes. Monitoring pesticides biodegradation in the environment is challenging, considering that traditional indicators, such as changes in pesticides concentration or identification of pesticide metabolites, are not suitable for many pesticides in anaerobic environments. Furthermore, those indicators cannot distinguish between biotic and abiotic pesticide degradation processes. For that reason, the use of molecular tools is important to monitor pesticide biodegradation-related genes or microorganisms in the environment. The development of targeted molecular (e.g., qPCR) tools, although laborious, allowed biodegradation monitoring by targeting the presence and expression of known catabolic genes of popular pesticides. Explorative molecular tools (i.e., metagenomics & metatranscriptomics), while requiring extensive data analysis, proved to have potential for screening the biodegradation potential and activity of more than one compound at the time. The application of molecular tools developed in laboratory and validated under controlled environments, face challenges when applied in the field due to the heterogeneity in pesticides distribution as well as natural environmental differences. However, for monitoring pesticides biodegradation in the field, the use of molecular tools combined with metadata is an important tool for understanding fate and transformation of the different pesticides present in the environment

Unexpected removal of the most neutral cationic pharmaceutical in river waters

Contamination of surface waters by pharmaceuticals is now widespread. There are few data on their environmental behaviour, particularly for those which are cationic at typical surface water pH. As the external surfaces of bacterio-plankton cells are hydrophilic with a net negative charge, it was anticipated that bacterio-plankton in surface-waters would preferentially remove the most extensively-ionised cation at a given pH. To test this hypothesis, the persistence of four, widely-used, cationic pharmaceuticals, chloroquine, quinine, fluphenazine and levamisole, was assessed in batch microcosms, comprising water and bacterio-plankton, to which pharmaceuticals were added and incubated for 21 days. Results show that levamisole concentrations decreased by 19 % in microcosms containing bacterio-plankton, and by 13 % in a parallel microcosm containing tripeptide as a priming agent. In contrast to levamisole, concentrations of quinine, chloroquine and fluphenazine were unchanged over 21 days in microcosms containing bacterio-plankton. At the river-water pH, levamisole is 28 % cationic, while quinine is 91–98 % cationic, chloroquine 99 % cationic and fluphenazine 72–86 % cationic. Thus, the most neutral compound, levamisole, showed greatest removal, contradicting the expected bacterio-plankton preference for ionised molecules. However, levamisole was the most hydrophilic molecule, based on its octanol–water solubility coefficient (K ow). Overall, the pattern of pharmaceutical behaviour within the incubations did not reflect the relative hydrophilicity of the pharmaceuticals predicted by the octanol–water distribution coefficient, D ow, suggesting that improved predictive power, with respect to modelling bioaccumulation, may be needed to develop robust environmental risk assessments for cationic pharmaceuticals

Consistency, inconsistency, and ambiguity of metabolite names in biochemical databases used for genome-scale metabolic modelling

Genome-scale metabolic models (GEMs) are manually curated repositories describing the metabolic capabilities of an organism. GEMs have been successfully used in different research areas, ranging from systems medicine to biotechnology. However, the different naming conventions (namespaces) of databases used to build GEMs limit model reusability and prevent the integration of existing models. This problem is known in the GEM community, but its extent has not been analyzed in depth. In this study, we investigate the name ambiguity and the multiplicity of non-systematic identifiers and we highlight the (in)consistency in their use in 11 biochemical databases of biochemical reactions and the problems that arise when mapping between different namespaces and databases. We found that such inconsistencies can be as high as 83.1%, thus emphasizing the need for strategies to deal with these issues. Currently, manual verification of the mappings appears to be the only solution to remove inconsistencies when combining models. Finally, we discuss several possible approaches to facilitate (future) unambiguous mapping.</p