Rashmi Ira - D20024 thesis data - Chapter-4

This dataset supports the thesis on optimizing methane (CH₄) and hydrogen (H₂) production through a single-stage anaerobic digestion (AD) process by leveraging the natural microbial synergy within synthetically designed consortia without requiring bulk substrate treatments. A novel synthetic microbial consortium, E(C2)Tx, was developed using a waste complementarity and selective pretreatment approach, which includes heat pretreatment, load shock, and acclimatization to enrich hydrogen producers and methanogens. An untreated counterpart, E(C2)UTx, was also designed to assess the impact of heat pretreatment. This dataset captures microbial community dynamics from the starting point (SP) to the endpoint (EP) of AD using cow dung (CD) as a substrate, inoculated with E(C2)Tx, E(C2)UTx, and a negative control. It includes the relative abundance of significant bacterial and archaeal taxa, profiled using 16S rRNA metagenomic sequencing. Additionally, the dataset categorizes microbial taxa based on their functional roles in key AD processes, including hydrolysis, acidogenesis, acetogenesis, and methanogenesis. It also presents the predicted operational taxonomic units (OTUs) across all samples.