Stoichiometric modeling of oxidation of reduced inorganic sulfur compounds (Riscs) in Acidithiobacillus thiooxidans

• Published in: Biotechnology and bioengineering 2013-08, Vol.110 (8), p.2242-2251
• Main Authors: Bobadilla Fazzini, Roberto A., Cortés, Maria Paz, Padilla, Leandro, Maturana, Daniel, Budinich, Marko, Maass, Alejandro, Parada, Pilar
• Format: Article
• Language: English
• Subjects: Acidithiobacillus thiooxidans; Acidithiobacillus thiooxidans - growth & development; Acidithiobacillus thiooxidans - metabolism; At. thiooxidans; Bacteria; Beggiatoa; Biomass; Chemoautotrophic Growth; chemolithoautotrophic oxidation; Genomics; Mathematical models; Models, Biological; Models, Theoretical; Oxidation; Oxidation-Reduction; Paracoccus; Prokaryotes; reduced Inorganic sulfur compounds (RISCs); RISC; Stoichiometry; Sulfur; Sulfur compounds; Sulfur Compounds - metabolism
• ISSN: 0006-3592; 1097-0290
• DOI: 10.1002/bit.24875

The prokaryotic oxidation of reduced inorganic sulfur compounds (RISCs) is a topic of utmost importance from a biogeochemical and industrial perspective. Despite sulfur oxidizing bacterial activity is largely known, no quantitative approaches to biological RISCs oxidation have been made, gathering all the complex abiotic and enzymatic stoichiometry involved. Even though in the case of neutrophilic bacteria such as Paracoccus and Beggiatoa species the RISCs oxidation systems are well described, there is a lack of knowledge for acidophilic microorganisms. Here, we present the first experimentally validated stoichiometric model able to assess RISCs oxidation quantitatively in Acidithiobacillus thiooxidans (strain DSM 17318), the archetype of the sulfur oxidizing acidophilic chemolithoautotrophs. This model was built based on literature and genomic analysis, considering a widespread mix of formerly proposed RISCs oxidation models combined and evaluated experimentally. Thiosulfate partial oxidation by the Sox system (SoxABXYZ) was placed as central step of sulfur oxidation model, along with abiotic reactions. This model was coupled with a detailed stoichiometry of biomass production, providing accurate bacterial growth predictions. In silico deletion/inactivation highlights the role of sulfur dioxygenase as the main catalyzer and a moderate function of tetrathionate hydrolase in elemental sulfur catabolism, demonstrating that this model constitutes an advanced instrument for the optimization of At. thiooxidans biomass production with potential use in biohydrometallurgical and environmental applications. Biotechnol. Bioeng. 2013; 110: 2242–2251. © 2013 Wiley Periodicals, Inc.