Optimized elemental sulfur recovery from sulfide-containing streams applying systems biology and genome-scale metabolic model of Thioalkalivibrio versutus D301.

Despite many reports focusing on the engineering aspects of biodesulfurization, there is a lack of comprehensive analysis on metabolic pathways and integration of engineering and metabolism. In this study, a genome-scale metabolic model was reconstructed for Thioalkalivibrio versutus D301, a potent strain in biodesulfurization. The model, named TVD301, was refined using extracted RNA sequencing data, and flux balance analysis demonstrated its accuracy in predicting growth and sulfur species rates. Importantly, experimental validation in a regulated medium confirmed a 60% decrease in sulfate production compared to control cultures, showing the strong practical relevance of the model. The TVD301 model also revealed that T. versutus lacks the enzymes needed to convert sulfide to sulfate, making it a strong strain in biodesulfurization. To optimize sulfur recovery and reduce sulfate production in industrial processes using microbial consortia, the TVD301 model was adapted to a consortium model. Sensitivity analysis highlighted the importance of DsrAB and Cys enzymes in preventing undesired sulfate production. By inhibiting these enzymes via inhibitors extracted from Brenda database, elemental sulfur production increased significantly. These findings suggest promising strategies for enhancing biodesulfurization processes in industrial settings.