These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: High-throughput identification of microbial transformation products of organic micropollutants. Author: Helbling DE, Hollender J, Kohler HP, Singer H, Fenner K. Journal: Environ Sci Technol; 2010 Sep 01; 44(17):6621-7. PubMed ID: 20799730. Abstract: 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.[Abstract] [Full Text] [Related] [New Search]