Translating metagenomic knowledge into effective dye bioremediation for wastewater treatment

The large-scale discharge of synthetic dyes from textile and related sectors causes serious ecological and public health risks due to their toxicity, recalcitrance and carcinogenic potential. Conventional physicochemical methods for bioremediation of dyes are often costly, generate hazardous sludge, and fail to achieve complete mineralization. Whereas microbial bioremediation offers a sustainable and eco-friendly alternative; however, culture-dependent techniques capture only a fraction of microbial diversity, limiting the discovery of efficient degraders and metabolic pathways. So, Metagenomics has emerged as a transformative tool to overcome these constraints by enabling culture-independent analysis of entire microbial communities, revealing novel functional genes, enzymes, and metabolic pathways involved in dye degradation. Recent studies demonstrated that metagenomics approaches integrated with bioinformatics platforms such as MG-RAST, KEGG, and specialized databases can identify key dye degrading enzymes including azoreductase, laccase, and peroxidase, as well as pathways for the breakdown of azo, anthraquinone and triphenylmethane dyes. Additionally, metagenomics study supports source tracking of pollutants, functional annotation of microbial consortia, and the development of engineered strategies for bioaugmentation and bio stimulation. The integration of metagenomics with transcriptomics, proteomics, and metabolomics further enhances the understanding of microbial syntropy and adaptive responses under dye stress. Despite challenges related to annotation gaps, computational demands, sequencing costs and limited pilot scale validation, advances in high-throughput sequencing, bioinformatics pipelines, and AI driven analytics are expanding the scope of metagenomic application in dye bioremediation. This review highlights the current progress, available tools and future perspectives, emphasizing the potential of metagenomics to accelerate the design of efficient, robust and sustainable strategies for treating dye contaminated waste water systems.