ABSTRACT
Metformin is used globally to treat type II diabetes, has demonstrated anti-ageing and COVID mitigation effects and is a major anthropogenic pollutant to be bioremediated by wastewater treatment plants (WWTPs). Metformin is not adsorbed well by activated carbon and toxic N-chloro derivatives can form in chlorinated water. Most earlier studies on metformin biodegradation have used wastewater consortia and details of the genomes, relevant genes, metabolic products, and potential for horizontal gene transfer are lacking. Here, two metformin-biodegrading bacteria from a WWTP were isolated and their biodegradation characterized. Aminobacter sp. MET metabolized metformin stoichiometrically to guanylurea, an intermediate known to accumulate in some environments including WWTPs. Pseudomonas mendocina MET completely metabolized metformin and utilized all the nitrogen atoms for growth. Pseudomonas mendocina MET also metabolized metformin breakdown products sometimes observed in WWTPs: 1-N-methylbiguanide, biguanide, guanylurea, and guanidine. The genome of each bacterium was obtained. Genes involved in the transport of guanylurea in Aminobacter sp. MET were expressed heterologously and shown to serve as an antiporter to expel the toxic guanidinium compound. A novel guanylurea hydrolase enzyme was identified in Pseudomonas mendocina MET, purified, and characterized. The Aminobacter and Pseudomonas each contained one plasmid of 160 kb and 90 kb, respectively. In total, these studies are significant for the bioremediation of a major pollutant in WWTPs today.
ABSTRACT
The widely prescribed pharmaceutical metformin and its main metabolite, guanylurea, are currently two of the most common contaminants in surface and wastewater. Guanylurea often accumulates and is poorly, if at all, biodegraded in wastewater treatment plants. This study describes Pseudomonas mendocina strain GU, isolated from a municipal wastewater treatment plant, using guanylurea as its sole nitrogen source. The genome was sequenced with 36-fold coverage and mined to identify guanylurea degradation genes. The gene encoding the enzyme initiating guanylurea metabolism was expressed, and the enzyme was purified and characterized. Guanylurea hydrolase, a newly described enzyme, was shown to transform guanylurea to one equivalent (each) of ammonia and guanidine. Guanidine also supports growth as a sole nitrogen source. Cell yields from growth on limiting concentrations of guanylurea revealed that metabolism releases all four nitrogen atoms. Genes encoding complete metabolic transformation were identified bioinformatically, defining the pathway as follows: guanylurea to guanidine to carboxyguanidine to allophanate to ammonia and carbon dioxide. The first enzyme, guanylurea hydrolase, is a member of the isochorismatase-like hydrolase protein family, which includes biuret hydrolase and triuret hydrolase. Although homologs, the three enzymes show distinct substrate specificities. Pairwise sequence comparisons and the use of sequence similarity networks allowed fine structure discrimination between the three homologous enzymes and provided insights into the evolutionary origins of guanylurea hydrolase.IMPORTANCE Metformin is a pharmaceutical most prescribed for type 2 diabetes and is now being examined for potential benefits to COVID-19 patients. People taking the drug pass it largely unchanged, and it subsequently enters wastewater treatment plants. Metformin has been known to be metabolized to guanylurea. The levels of guanylurea often exceed that of metformin, leading to the former being considered a "dead-end" metabolite. Metformin and guanylurea are water pollutants of emerging concern, as they persist to reach nontarget aquatic life and humans, the latter if it remains in treated water. The present study has identified a Pseudomonas mendocina strain that completely degrades guanylurea. The genome was sequenced, and the genes involved in guanylurea metabolism were identified in three widely separated genomic regions. This knowledge advances the idea that guanylurea is not a dead-end product and will allow for bioinformatic identification of the relevant genes in wastewater treatment plant microbiomes and other environments subjected to metagenomic sequencing.