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原文摘要

Beta-lactamases are a major mechanism of bacterial resistance to beta-lactam antibiotics; however, their functional diversity and mutational potential in environmental microbial communities remain partially understood. This study aimed to characterize environmental beta-lactamase diversity and investigate how sequence variation influences antibiotic resistance. By integrating protein language model (PLMs) with ensemble learning, we identified more than 46,000 putative beta-lactamases across all four Ambler classes from environmental metagenomes, widely distributed across diverse habitats, with distinct habitat-associated class compositions. The candidates sharing approximately 30% sequence identity with known beta-lactamases conferred resistance to multiple beta-lactam antibiotics when expressed in Escherichia coli. Combining inverse folding model with PLMs further identified mutations that altered resistance profiles, including substitutions that increased resistance to carbapenems. Predicted high-fitness sites exhibited greater natural sequence variability overall, with higher variability in wastewater-derived than ocean-derived enzymes. These findings reveal undercharacterized beta-lactamase diversity and substantial mutational flexibility in environmental microbiomes, providing a basis for investigating their potential contribution to the diversification of antibiotic resistance.