Genome-Scale Metabolic Modeling for Unraveling Molecular Mechanisms of High Threat Pathogens

Abstract

Pathogens give rise to a wide range of diseases threatening global health and hence drawing public health agencies' attention to establish preventative and curative solutions. Genome-scale metabolic modeling is ever increasingly used tool for biomedical applications including the elucidation of antibiotic resistance, virulence, single pathogen mechanisms and pathogen-host interaction systems. With this approach, the sophisticated cellular system of metabolic reactions inside the pathogens as well as between pathogen and host cells are represented in conjunction with their corresponding genes and enzymes. Along with essential metabolic reactions, alternate pathways and fluxes are predicted by performing computational flux analyses for the growth of pathogens in a very short time. The genes or enzymes responsible for the essential metabolic reactions in pathogen growth are regarded as potential drug targets, as a priori guide to researchers in the pharmaceutical field. Pathogens alter the key metabolic processes in infected host, ultimately the objective of these integrative constraint-based context-specific metabolic models is to provide novel insights toward understanding the metabolic basis of the acute and chronic processes of infection, revealing cellular mechanisms of pathogenesis, identifying strain-specific biomarkers and developing new therapeutic approaches including the combination drugs. The reaction rates predicted during different time points of pathogen development enable us to predict active pathways and those that only occur during certain stages of infection, and thus point out the putative drug targets. Among others, fatty acid and lipid syntheses reactions are recent targets of new antimicrobial drugs. Genome-scale metabolic models provide an improved understanding of how intracellular pathogens utilize the existing microenvironment of the host. Here, we reviewed the current knowledge of genome-scale metabolic modeling in pathogen cells as well as pathogen host interaction systems and the promising applications in the extension of curative strategies against pathogens for global preventative healthcare.

Keywords: flux balance analysis (FBA); flux variability analysis; gene essentiality; genome-scale metabolic models; infection; pathogen; pathogen-host interactions; systems biology.

Figure 1

Reconstruction process of pathogen-specific GEMs.

Figure 2

Integrated investigation of the antibiotic resistance by adaptive laboratory evolution (ALE) experiments and pathogen-specific GEMs. Multi-omics data are collected during the ALE experiments from wild-type and antibiotic-resistant pathogens at different time points. To elucidate the evolutionary response at system-level due to antibiotic pressure, high throughput omics data are computationally mapped onto the genome-scale metabolic network. Analysis of metabolic shift in the cellular metabolism and mechanism of antibiotic-resistant pathogenic GEMs facilitate the discovery of novel potential drug targets and treatment strategies against antibiotic-resistant pathogen. Fitness landscapes demonstrate the optimality in adaptive evolution of antibiotic resistance. Smooth fitness landscapes consist of a single optimum and regardless of the starting point evolutionary tendency converge to this optimum. There exist multiple optima on the rough fitness landscapes and evolutionary tendency diverge even from the same starting point.

Figure 3

Life cycle of M. tuberculosis and P. falciparum and integrated analysis at system level. (A) M. tuberculosis is transmitted by aerosol. Inhaled pathogen reaches the alveoli of the lung and grows inside the alveolar macrophages. Granuloma, where M. tuberculosis kills the macrophages and escapes from the cell for division, is formed. Subsequent to maturation, granuloma ruptures and releases M. tuberculosis into the airways. (B) P. falciparum life cycle involves the different stages in female Anopheles mosquito and human. Mosquito transmits sporozoites into the human. They infect hepatocytes and mature into schizonts which release merozoites. Merozoites invade erythrocytes and resulted in release of newly multiplied merozoites by erythrocytes destruction. Some merozoites differentiate into gametocytes which are taken up from host by mosquito. Gametocytes develop into sporozoites within mosquito. (C) Integrated analysis of tissue- and pathogen-specific GEMs with the high-throughput multi-omics data provides insight into the cellular and interaction mechanisms between the pathogen and host tissue at different stage of infection.