Substrate promiscuity of xenobiotic-transforming hydrolases from stream biofilms impacted by treated wastewater

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 28, 2023

Abstract Organic contaminants enter aquatic ecosystems from various sources, including wastewater treatment plant effluent. Freshwater biofilms play a major role in the removal of organic receiving water bodies, but knowledge molecular mechanisms driving contaminant biotransformations complex stream biofilm (periphyton) communities remains limited. Previously, we demonstrated that experimental flume systems grown at higher ratios treated (WW) to displayed an increased biotransformation potential for number contaminants. We identified positive correlation between WW percentage and rates widely-used insect repellent, N,N -diethyl-meta-toluamide (DEET). Here, conducted deep shotgun sequencing metagenomic read abundances DEET hydrolase (DH) homologs. To test causality this association, constructed targeted library DH homologs biofilms. screened our complete activity with four different substrates subset thereof 183 WW-related compounds. The majority active hydrolases preferred aliphatic aromatic ester while, remarkably, only single reference enzyme was capable hydrolysis. Of 626 total enzyme-substrate combinations tested, approximately 5% were pairs. Metagenomic family revealed broad substrate promiscuity spanning 22 compounds when summed across all enzymes tested. biochemically characterized most promiscuous based on analysis uncultivated Rhodospirillaceae Planctomycetaceae . In addition characterizing new enzymes, exemplified framework linking metagenome-guided hypothesis generation validation. Overall, study expands scope known enzymatic WW-receiving communities. Graphical abstract Highlights wastewater. Eleven out 64 tested exhibited hydrolysis activity. Related biotransform 20+ Reference shows preference benzamide moieties. ‘True’ are low abundance even degrade DEET.

Language: Английский

Machine learning reveals signatures of promiscuous microbial amidases for micropollutant biotransformations

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 9, 2024

Abstract Organic micropollutants - including pharmaceuticals, personal care products, pesticides and food additives are prevalent in the environment have unknown potentially toxic effects. Humans a direct source of as majority pharmaceuticals primarily excreted through urine. Urine contains its own microbiota with potential to catalyze micropollutant biotransformations. Amidase signature (AS) enzymes known for their promiscuous activity biotransformations, but AS from urinary transform is not known. Moreover, characterization identify key chemical enzymatic features predictive biotransformation profiles critical developing benign-by-design chemicals removal strategies. In this study, we biochemically characterized new enzyme arylamidase urine isolate, Lacticaseibacillus rhamnosus, demonstrated capability hydrolyze other micropollutants. To uncover signatures enzyme-substrate specificity, then designed targeted library consisting 40 homologs diverse isolates tested it against 17 structurally compounds. We found that 16 out showed on at least one substrate exhibited specificities, most active nine different substrates. Using an interpretable gradient boosting machine learning model, identified amino acid Key our substrates included molecular weight amide carbonyl substituent number charges molecule. Important were be located protein surface four residues close proximity tunnel entrance. Overall, work highlights understudied role urine-derived microbial arylamidases contributes sequence-structure-substrate-based predictions

Language: Английский