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 30 days 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.

微生物多样性以适应地球上不同环境的各种基因组景观为代表。这些基因组景观包含与群落表型相关的功能特征。在这里，我们在富含蒽醌深蓝 35 染料的培养基中培养的受污染河流相关微生物组（莫雷洛斯，墨西哥）的高分辨率水平评估基因组微生物多样性景观。我们探索由此产生的纺织染料微生物组，以推断预测的生物降解功能与宏基因组和代谢潜力之间的联系，特别是使用从个体重建基因组中获得的信息。通过使用 Hi-C 邻近连接反卷积方法，我们对 97 个基因组复合物（80% 潜在的新物种）进行反卷积。主要的分类决定因素是甲烷杆菌、梭状芽胞杆菌属和Cupriavidus属构成了整个群落概况的 50%、22% 和 11%。此外，我们观察到一个罕见的新分类群生物圈，没有明确的分类地位。在染料富集 30 天后观察到去除了 50% 的化学需氧量和 23% 的脱色。在我们的研究条件下，与过氧化氢酶-过氧化物酶、多酚氧化酶和漆酶相关的基因被预测为与纺织品染料生物降解表型相关，突出了宏基因组分析预测生物降解决定因素的潜力。这项研究促使在环境压力下对纺织染料河流沉积物微生物组或复杂群落中的个体基因组进行高分辨率筛选。