Microbial biodegradation of biuret: defining biuret hydrolases within the isochorismatase superfamily

Serina L. Robinson, Jonathan P. Badalamenti, Anthony G. Dodge, Lambros J. Tassoulas, Lawrence P. Wackett

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Biuret is a minor component of urea fertilizer and an intermediate in s-triazine herbicide biodegradation. The microbial metabolism of biuret has never been comprehensively studied. Here, we enriched and isolated bacteria from a potato field that grew on biuret as a sole nitrogen source. We sequenced the genome of the fastest-growing isolate, Herbaspirillum sp. BH-1 and identified genes encoding putative biuret hydrolases (BHs). We purified and characterized a functional BH enzyme from Herbaspirillum sp. BH-1 and two other bacteria from divergent phyla. The BH enzymes reacted exclusively with biuret in the range of 2-11 µmol min−1 mg−1 protein. We then constructed a global protein superfamily network to map structure-function relationships in the BH subfamily and used this to mine > 7000 genomes. High-confidence BH sequences were detected in Actinobacteria, Alpha- and Beta-proteobacteria, and some fungi, archaea and green algae, but not animals or land plants. Unexpectedly, no cyanuric acid hydrolase homologs were detected in > 90% of genomes with BH homologs, suggesting BHs may have arisen independently of s-triazine ring metabolism. This work links genotype to phenotype by enabling accurate genome-mining to predict microbial utilization of biuret. Importantly, it advances understanding of the microbial capacity for biuret biodegradation in agricultural systems.

Original languageEnglish (US)
Pages (from-to)2099-2111
Number of pages13
JournalEnvironmental microbiology
Issue number6
StatePublished - Jun 2018

Bibliographical note

Funding Information:
We thank James Christenson for assistance with gel filtration and Matthew McNearney and Carl Rosen for providing soil samples for enrichment culturing. The Harcombe lab is acknowledged for use of the Tecan Shaker. Kelly Aukema and Jack Richman are acknowledged for thoughtful comments on the manuscript. We acknowledge the University of Minnesota Supercomputing Institute (MSI) for computational support and the University of Minnesota Genomics Center for sequencing support. This work was supported by the University of Minnesota Grand Challenges Initiative and MnDRIVE. SLR is supported by a United States National Science Foundation (NSF) Graduate Research Fellowship (Grant no. 00039202).


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