The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions.

Abstract

Rhodopseudomonas palustris is a metabolically versatile purple non-sulfur bacterium involved in nitrogen and carbon cycling and commonly found in wastewater treatment systems. A comprehensive genome-scale metabolic model (M-model), designated iDT1294, was constructed for strain Bis A53, encompassing 2,721 reactions, 2,123 metabolites, and 1,294 genes. Validation against more than 350 growth conditions yielded approximately 90% prediction accuracy for diverse carbon and nitrogen sources and nearly 80% for aromatic compound assimilation. The model also accurately reproduced dynamic substrate consumption and growth rates under nine chemoheterotrophic conditions and captured metabolic shifts between photoheterotrophic and photoautotrophic states. iDT1294 is expected to facilitate mechanistic understanding of anoxygenic photosynthesis, aromatic compound degradation, and the biosynthesis of molecular hydrogen and polyhydroxybutyrate.

Mechanism

The iDT1294 genome-scale metabolic model quantitatively predicts carbon and nitrogen assimilation pathways, anaerobic aromatic compound degradation, and molecular hydrogen production routes in R. palustris Bis A53 across multiple growth modes.