1.
Transcriptional regulation of bacterial virulence gene expression by molecular oxygen and nitric oxide.
Green, J, Rolfe, MD, Smith, LJ
Virulence. 2014;(8):794-809
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Abstract
Molecular oxygen (O2) and nitric oxide (NO) are diatomic gases that play major roles in infection. The host innate immune system generates reactive oxygen species and NO as bacteriocidal agents and both require O2 for their production. Furthermore, the ability to adapt to changes in O2 availability is crucial for many bacterial pathogens, as many niches within a host are hypoxic. Pathogenic bacteria have evolved transcriptional regulatory systems that perceive these gases and respond by reprogramming gene expression. Direct sensors possess iron-containing co-factors (iron-sulfur clusters, mononuclear iron, heme) or reactive cysteine thiols that react with O2 and/or NO. Indirect sensors perceive the physiological effects of O2 starvation. Thus, O2 and NO act as environmental cues that trigger the coordinated expression of virulence genes and metabolic adaptations necessary for survival within a host. Here, the mechanisms of signal perception by key O2- and NO-responsive bacterial transcription factors and the effects on virulence gene expression are reviewed, followed by consideration of these aspects of gene regulation in two major pathogens, Staphylococcus aureus and Mycobacterium tuberculosis.
2.
Modeling phenotypic metabolic adaptations of Mycobacterium tuberculosis H37Rv under hypoxia.
Fang, X, Wallqvist, A, Reifman, J
PLoS computational biology. 2012;(9):e1002688
Abstract
The ability to adapt to different conditions is key for Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), to successfully infect human hosts. Adaptations allow the organism to evade the host immune responses during acute infections and persist for an extended period of time during the latent infectious stage. In latently infected individuals, estimated to include one-third of the human population, the organism exists in a variety of metabolic states, which impedes the development of a simple strategy for controlling or eradicating this disease. Direct knowledge of the metabolic states of M. tuberculosis in patients would aid in the management of the disease as well as in forming the basis for developing new drugs and designing more efficacious drug cocktails. Here, we propose an in silico approach to create state-specific models based on readily available gene expression data. The coupling of differential gene expression data with a metabolic network model allowed us to characterize the metabolic adaptations of M. tuberculosis H37Rv to hypoxia. Given the microarray data for the alterations in gene expression, our model predicted reduced oxygen uptake, ATP production changes, and a global change from an oxidative to a reductive tricarboxylic acid (TCA) program. Alterations in the biomass composition indicated an increase in the cell wall metabolites required for cell-wall growth, as well as heightened accumulation of triacylglycerol in preparation for a low-nutrient, low metabolic activity life style. In contrast, the gene expression program in the deletion mutant of dosR, which encodes the immediate hypoxic response regulator, failed to adapt to low-oxygen stress. Our predictions were compatible with recent experimental observations of M. tuberculosis activity under hypoxic and anaerobic conditions. Importantly, alterations in the flow and accumulation of a particular metabolite were not necessarily directly linked to differential gene expression of the enzymes catalyzing the related metabolic reactions.