Dissecting the Role of Ferrous Iron in Pseudomonas Aeruginosa Gene Regulation

Abstract

In our quest towards a predictive understanding of biological systems, we have combined quantitative models of gene regulation with careful experimental tests of model predictions in order to determine how promoter architecture dictates the output level of gene expression. We have applied this quantitative framework to understand how cells sense and respond to extracellular cues, using ferrous iron-mediated gene regulation in Pseudomonas aeruginosa as an important case study. Upon recent discovery of a two-component system that specifically responds to ferrous iron, there is an emerging picture of the critical role of Fe(II) availability in the regulatory outputs of Pseudomonas aeruginosa. On the bench top Fe(II) is readily oxidized to Fe(III), however in infections such as in the lungs of cystic fibrosis patients, cells can encounter reducing environments containing Fe(II). Ferrous iron regulates genes related to both pathogenicity and biofilm formation. These pathways are also controlled by the quorum sensing systems and the availability of ferric iron. It is not yet clear why multiple pathways are used to sense extracellular iron or how the cell integrates information from these different pathways to effectively respond to changes in the availability and oxidation state of iron. Using statistical mechanical models of gene regulation and the tools of synthetic biology, the rules of the ferrous iron regulon are beginning to emerge. We quantified how promoter architecture dictates the regulatory response to Fe(II). A quantitative understanding of how promoters encode a ferrous iron response enabled us to predict how Fe(II) influences global gene expression patterns. Some genes respond to both Fe(II) and additional regulatory inputs, such as other transcription factors or two-component systems. We dissected these multi-input promoters to understand how cells combine ferrous iron availability with other regulatory factors to make transcriptional decisions.

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