Dataset for metagenomics profiling of microbial communities grown in constructed wetland-microbial fuel cell system during sewage wastewater treatment
Description
Sewage wastewater is a toxic waste generated from domestic, industrial, and stormwater sources and contains complex organic materials that challenge treatment and disposal. Constructed wetland-microbial fuel cell (CW-MFC) technology has emerged as an eco-sustainable solution, enhancing wastewater remediation while generating bioelectricity. To explore microbial community roles in SWW treatment and bioelectricity generation using lab-scale Canna indica-based CW-MFC, metagenomic profiling was conducted on sludge samples collected from the root zone (RSS) and cathode (CSS). High-throughput sequencing of the V3–V4 hypervariable region of 16S rRNA genes revealed diversity, composition, and functional roles of microbial communities in CW-MFC treating SWW. DNA extraction was performed using the Nucelospin Soil kit, followed by library preparation, purification, and sequencing on the Illumina MiSeq PE300 platform. Bioinformatics tools, such as FastQC, Trimmomatic, FLASH, and DADA2 were employed to process raw sequencing data into high-quality reads. Furthermore, taxonomic analysis revealed Proteobacteria dominance at the phylum level in both RSS and CSS. Functional predictions through PICRUSt2 revealed degradative and metabolic pathways, genes, and proteins. The present dataset consists of raw and high-quality next-generation sequencing data files, OTU, pie charts, and featured tables of the analysed microbial communities. In addition, it also consists of the analyzed rarefaction curve, heat map, Krona chart, KEGG annotation, COG annotation, EC annotation, and MetCyc annotation reports. The study highlights significant differences in microbial diversity and taxonomic abundance between rhizospheric and cathodic samples, offering insights into microbial roles in SWW treatment and bioelectricity production in developed CW-MFC systems.