A systematic strategy using a reconstructed genome-scale metabolic network for pathogen Streptococcuspneumoniae D39 to find novel potential drug targets.

Abstract

Streptococcus pneumoniae is a Gram-positive bacterium that is one of the major causes of various infections such as pneumonia, meningitis, otitis media and endocarditis. Since antibiotic resistance of S. pneumoniae is pointed out as a challenge in the treatment of these infections, more studies are required to focus on disease prevention. In this research, a first manually curated genome-scale metabolic network of the pathogen S. pneumoniae D39 was reconstructed based on its genome annotation data, and biochemical knowledge from literature and databases. The model was validated by amino acid auxotrophies, gene essentiality analysis, and different carbohydrate sources. Then, a two-stage strategy was developed to find target genes for growth reduction of the pathogen and their importance in the various infection sites. In the first stage, growth-associated genes were identified by integration of transcriptomic data with the model and in the second stage, the importance of each gene in the metabolism for growth was evaluated using principal component analysis. The reports presented in the literature confirm the effect of some found genes on the growth of S. pneumoniae.