16SrRNA for microbial electrolysis cell with lysozyme

This dataset comprised raw 16S rRNA gene sequencing data from microbial communities in a single chamber membraneless microbial electrolysis cell (MEC) before and after lysozyme treatment, aiming to characterize the impact of enzymatic intervention on biofilm microbial structure and functional dynamics.The study specifically targeted shifts in microbial taxonomic composition, focusing on electroactive bacteria (Geobacter) and competing populations (methanogenic archaea), which are critical for electron transfer efficiency and gas product selectivity in MECs. By comparing pre and post treatment microbial profiles, the dataset seeks to identify lysozyme mediated alterations in key functional taxa, such as changes in the relative abundance of electroactive species or suppression of methanogenic pathways, which may explain observed performance changes (increased Coulombic efficiency and reduced hydrogen or methane production).The relevance of these data lies in their ability to link microbial community shifts with engineered biofilm functions in MECs, a technology pivotal for sustainable bioenergy production and wastewater treatment. Lysozyme, as a non-toxic enzyme targeting bacterial cell walls, offers a novel strategy to modulate biofilm composition without chemical interference. These raw sequencing data provide a foundational resource for downstream analyses, including taxonomic classification, diversity indices, and network co-occurrence patterns, enabling researchers to explore mechanistic connections between enzymatic treatment, microbial ecology, and electrochemical performance. By depositing these data, we aim to promote reproducibility in microbial electrochemical studies and facilitate cross-study comparisons, ultimately advancing the understanding of enzyme mediated biofilm engineering for improved MEC efficiency and stability.