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Updated: Jun 10, 2026

Development of Sulfidogenic Sludge from Marine Sediments and Trichloroethylene Reduction in an Upflow Anaerobic Sludge Blanket Reactor
Published on: October 15, 2015
Structure-based interpretation of biotransformation pathways of amide-containing compounds in sludge-seeded
Damian E Helbling1, Juliane Hollender, Hans-Peter E Kohler
1Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland.
Abstract:
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.
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