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Microorganisms are ubiquitous on earth and have diverse metabolic transformative capabilities important for environmental biodegradation of chemicals that helps maintain ecosystem and human health. Microbial biodegradative metabolism is the main focus of the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD). UM-BBD data has also been used to develop a computational metabolic pathway prediction system that can be applied to chemicals for which biodegradation data is currently lacking. The UM-Pathway Prediction System (UM-PPS) relies on metabolic rules that are based on organic functional groups and predicts plausible biodegradative metabolism. The predictions are useful to environmental chemists that look for metabolic intermediates, for regulators looking for potential toxic products, for microbiologists seeking to understand microbial biodegradation, and others with a wide-range of interests.

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.

The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.msi.umn.edu/) began in 1995 and now contains information on almost 1200 compounds, over 800 enzymes, almost 1300 reactions and almost 500 microorganism entries. Besides these data, it includes a Biochemical Periodic Table (UM-BPT) and a rule-based Pathway Prediction System (UM-PPS) (http://umbbd.msi.umn.edu/predict/) that predicts plausible pathways for microbial degradation of organic compounds. Currently, the UM-PPS contains 260 biotransformation rules derived from reactions found in the UM-BBD and scientific literature. Public access to UM-BBD data is increasing. UM-BBD compound data are now contributed to PubChem and ChemSpider, the public chemical databases. A new mirror website of the UM-BBD, UM-BPT and UM-PPS is being developed at ETH Zürich to improve speed and reliability of online access from anywhere in the world.

The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.ahc.umn.edu/) provides curated information on microbial catabolic enzymes and their organization into metabolic pathways. Currently, it contains information on over 400 enzymes. In the last year the enzyme page was enhanced to contain more internal and external links; it also displays the different metabolic pathways in which each enzyme participates. In collaboration with the Nomenclature Commission of the International Union of Biochemistry and Molecular Biology, 35 UM-BBD enzymes were assigned complete EC codes during 2000. Bacterial oxygenases are heavily represented in the UM-BBD; they are known to have broad substrate specificity. A compilation of known reactions of naphthalene and toluene dioxygenases were recently added to the UM-BBD; 73 and 108 were listed respectively. In 2000 the UM-BBD is mirrored by two prestigious groups: the European Bioinformatics Institute and KEGG (the Kyoto Encyclopedia of Genes and Genomes). Collaborations with other groups are being developed. The increased emphasis on UM-BBD enzymes is important for predicting novel metabolic pathways that might exist in nature or could be engineered. It also is important for current efforts in microbial genome annotation.