Uncovering plasticizer-degrading potential in landfill microbiomes with curated PzDE-HMM database and multi-scale...

Plasticizers are widely used additives that leach from plastic products and accumulate in landfills, yet the microbial functions supporting their degradation remain poorly resolved. Here, we combined curated functional annotation, substrate-driven enrichment, and isolate-level validation to dissect plasticizer degradation in landfill microbiomes. A plasticizer-degrading enzyme (PzDE) hidden Markov model database (PzDE-HMM) was assembled from 49 experimentally validated enzyme families. It was applied to metagenomes from five landfill niches, identifying 2219 candidate plasticizer-degrading genes, which is 3.6- and 19-fold more than those identified by KofamScan- and BLASTp-based annotation methods, respectively. Enrichment with three legacy phthalates (DEHP, DIDP, DBP) and three non-phthalate plasticizers (DOTP, DOA, ATBC) drove pronounced shifts in landfill microbial communities and functional gene repertoires, revealing coexisting broad-spectrum and substrate-specific degraders. Culture-based isolation from enriched media yielded 51 strains, and three representative isolates showed concordance between PzDE-HMM-predicted gene repertoires, substrate breadth, and degradation ability. Synthetic consortia assembled from these strains exhibited complementary degradation capacities and achieved higher removal of several plasticizers than the best single strains, illustrating how complementary gene sets can be combined to enhance multi-substrate degradation. Together, PzDE-HMM annotation workflow and this multilevel prediction-enrichment-isolate-consortium framework uncover the plasticizer-degrading and bioremediation potential of landfill microbiomes and provide a reusable resource and workflow for future plasticizer-focused microbiome studies.