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Revealing Dual Synergistic Strategies in Sulfate-Reducing Microbiomes for Sulfamethoxazole Biodegradation via DNA-SIP and Metagenomics

Journal
Environmental science & technology (Q1)
Published
21 July 2026
Study design
Unclassified
Evidence level
Level 5, Expert Opinion (CEBM 5)
Authors
Yanyan Jia, Yujian Yan, Ben Chen, Wen-Sheng Shu, Hui Lu
PMID
42479812
DOI
10.1021/acs.est.6c05921

Why clinicians should know about it

Abstract

Sulfate-reducing microbiomes (SRMs) have shown strong potential for antibiotic remediation, yet the active microorganisms and community-level strategies associated with sulfamethoxazole (SMX) biotransformation remain poorly understood. In this study, long-term bioreactor operation (269 days; 500-1500 μg/L SMX), DNA-stable isotope probing (DNA-SIP), and metagenomic analyses were integrated to investigate the microbial contributors and functional organization underlying SRM-driven SMX biotransformation. Desulfobacterium, a key SRM member, was co-enriched with Geobacter and Leptolinea in the 13C-labeled heavy fraction, suggesting potential metabolic complementarity during community-level SMX biotransformation. Genome-resolved analyses further revealed structured patterns of inferred horizontal gene transfer (HGT) and predicted metabolite exchange among keystone taxa. The transferred genes were mainly associated with energy conservation, transport, sulfur-associated metabolism, and stress-response functions, whereas the predicted exchanged metabolites included carbon metabolites, amino acid-related sulfur compounds, purine-related intermediates, and cofactor-associated metabolites. Together, these findings suggest that HGT-associated functional redistribution and metabolic complementarity may contribute to the persistence and coordinated activity of sulfate-reducing microbiomes under high SMX stress. This study links SIP-identified active populations with genome-inferred interaction patterns in a sulfate-reducing system and provides new insight into microbiome-based anaerobic strategies for antibiotic-containing wastewater treatment.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.