Multi-omics Approaches to Decipher the Biodegradation of Recalcitrant Contaminants in PFAS

Abstract

The pervasive environmental persistence of per- and polyfluoroalkyl substances (PFAS) represents an unprecedented challenge to global remediation efforts due to the exceptional stability of the carbon-fluorine (C−F) bond. While traditional physico-chemical treatments offer sequestration, they often fail to achieve complete destruction, positioning biological degradation as a critical, sustainable alternative. This study investigates the application of multi-omics frameworks integrating metagenomics, metatranscriptomics, metaproteomics, and metabolomics to decode the complex microbial mechanisms driving the transformation of these recalcitrant contaminants. By synthesizing current research and experimental data, we demonstrate that PFAS biodegradation is rarely a solo microbial process; instead, it relies on syntrophic interactions and the differential expression of putative dehalogenases and oxygenases. Metatranscriptomic profiling revealed a significant upregulation of reductive dehalogenase genes (e.g., rdxA) under anaerobic stress, while high-resolution metabolomics identified key short-chain intermediates that validate partial defluorination pathways. Furthermore, the integration of genome-scale metabolic models (GEMs) and machine learning suggests a transition toward "precision bioremediation," allowing for the prediction of metabolic fluxes in contaminated matrices. Our findings conclude that while perfluorinated acids like PFOA and PFOS remain highly resistant, the identification of synergistic metabolic networks and the use of synthetic biology to optimize microbial consortia offer a viable roadmap for mitigating the global PFAS footprint. This systems biology perspective is essential for evolving from descriptive environmental microbiology to predictive engineering solutions for "forever chemicals."