Hi-C deconvolution of a textile dye–related microbiome reveals novel taxonomic landscapes and links phenotypic potential to individual genomes

Abstract

Microbial biodiversity is represented by a variety of genomic landscapes adapted to dissimilar environments on Earth. These genomic landscapes contain functional signatures connected with the community phenotypes. Here, we assess the genomic microbial diversity landscape at a high-resolution level of a polluted river-associated microbiome (Morelos, México), cultured in a medium enriched with anthraquinone Deep Blue 35 dye. We explore the resultant textile dye microbiome to infer links between predicted biodegradative functions, and metagenomic and metabolic potential, especially using the information obtained from individual reconstructed genomes. By using Hi-C proximity-ligation deconvolution method, we deconvoluted 97 genome composites (80% potentially novel species). The main taxonomic determinants were Methanobacterium, Clostridium, and Cupriavidus genera constituting 50, 22, and 11% of the total community profile. Also, we observed a rare biosphere of novel taxa without clear taxonomic standing. Removal of 50% chemical oxygen demand with 23% decolorization was observed after 30days of dye enrichment. Genes related to catalase-peroxidase, polyphenol oxidase, and laccase enzymes were predicted as associated with textile dye biodegradation phenotype under our study conditions, highlighting the potential of metagenome-wide analysis to predict biodegradative determinants. This study prompts high-resolution screening of individual genomes within textile dye river sediment microbiomes or complex communities under environmental pressures.