Comparative analysis of metabolic machinery of Frankia along with other selected actinobacteria

Abstract

Actinobacteria exhibits a wide range of adaptive strategies by adjusting their transcriptional and metabolic profiles for optimum utilization of available resources. Thus, a proper understanding of metabolic pathways along with their constituent enzymes may provide vital clues for survival strategies engaged by these bacteria. In the present study, we have compared the complete metabolic contour of five Frankia strains along with twelve other actinobacteria including pathogenic and non-pathogenic strains of Mycobacterium and Streptomyces. Among the Frankia strains, EAN1pec and Eul1c have the highest number of distinct metabolic enzymes while Candidatus Frankia datiscae Dg1 has the least. Frankia strains share 383 metabolic enzymes among themselves while 244 enzymes have been identified to be shared by all the studied strains. We also identified unique/maker enzymes in each of the chosen strains. Among Frankia, CcI3 bears the highest number of unique enzymes whereas Mycobacterium vanbaalenii has maximum number overall. Cluster analysis was used to explore the effluxes in crucial metabolic pathways. The analysis reveals that actinobacteria exhibit diverse routes for metabolizing substrates. Genome scale metabolic models of Frankia alni ACN14a, Streptomyces coelicolor A3 (2), and Mycobacterium tuberculosis H37Rv were utilized for analyzing metabolic capabilities based on Flux balance analysis (FBA) approach. Simulation of virtual knockouts of genes in metabolic network helped in inferring essentiality of metabolic genes and their encoded enzymes. The present study provides an overview of the metabolic capability of some actinobacteria strains and may have further implications for systematically designing novel strategies for improvement of such strains.