Rule-based modelling of iron homeostasis in tuberculosis
Artikel i vetenskaplig tidskrift, 2011

To establish itself within the host system, Mycobacterium tuberculosis (Mtb) has formulated various means of attacking the host system. One such crucial strategy is the exploitation of the iron resources of the host system. Obtaining and maintaining the required concentration of iron becomes a matter of contest between the host and the pathogen, both trying to achieve this through complex molecular networks. The extent of complexity makes it important to obtain a systems perspective of the interplay between the host and the pathogen with respect to iron homeostasis. We have reconstructed a systems model comprising 92 components and 85 protein-protein or protein-metabolite interactions, which have been captured as a set of 194 rules. Apart from the interactions, these rules also account for protein synthesis and decay, RBC circulation and bacterial production and death rates. We have used a rule-based modelling approach, Kappa, to simulate the system separately under infection and non-infection conditions. Various perturbations including knock-outs and dual perturbation were also carried out to monitor the behavioral change of important proteins and metabolites. From this, key components as well as the required controlling factors in the model that are critical for maintaining iron homeostasis were identified. The model is able to re-establish the importance of iron-dependent regulator (ideR) in Mtb and transferrin (Tf) in the host. Perturbations, where iron storage is increased, appear to enhance nutritional immunity and the analysis indicates how they can be harmful for the host. Instead, decreasing the rate of iron uptake by Tf may prove to be helpful. Simulation and perturbation studies help in identifying Tf as a possible drug target. Regulating the mycobactin (myB) concentration was also identified as a possible strategy to control bacterial growth. The simulations thus provide significant insight into iron homeostasis and also for identifying possible drug targets for tuberculosis.

macrophages

signal-transduction

systems biology

software environment

mycobacterium-tuberculosis

p123

model

infection

2010

network

mathematical-model

metabolism

host-pathogen interactions

rst cv

Författare

S. Ghosh

Molecular Biophysics Unit

K V S Prasad

Chalmers, Data- och informationsteknik, Datavetenskap

S. Vishveshwara

Molecular Biophysics Unit

N. Chandra

Indian Institute of Science, Bangalore

Molecular BioSystems

1742-206X (ISSN) 1742-2051 (eISSN)

Vol. 7 10 2750-2768

Ämneskategorier

Biokemi och molekylärbiologi

DOI

10.1039/c1mb05093a