Sensing metals: The versatility of fur

Metals are essential for cell growth and survival as cofactors of diverse enzymes and as structural and regulatory ligands for various cell components. In excess amounts, however, even essential metals become toxic to cells. In order to maintain proper levels of the metals inside the cell, sensors detect the availability of specific metals inside and around the cell and regulate target genes that encode proteins responsible for acquisition, mobilization, usage, storage, and export of the corresponding metals. Among metal-sensing transcriptional regulators that modulate their activity through binding metals, Fur family regulators show remarkable diversity in the types of metals they respond to and the breadth of target genes they regulate. Since the discovery of Fur as an iron-dependent inhibitor of the iron uptake system in Escherichia coli and Salmonella in the late 1970s, the prototypical role of Fur as a transcriptional repressor in the presence of iron has been firmly established in a wide range of bacteria. However, in the last 10 years, we have witnessed an explosion of discoveries of diverse Fur subfamilies that are specialized to sense metals other than iron, such as zinc (Zur), manganese (Mur), heme iron (Irr), and nickel (Nur), to control homeostasis of each specific metal. A subfamily (PerR) that is specialized to sense peroxide through bound iron and control genes for oxidative stress response has also been discovered. Genetic, biochemical, biophysical, and structural studies have contributed to the advances in understanding of how metal binding serves structural, regulatory, and sensory roles and how it affects the activity of each subfamily. The versatile roles in gene regulation as direct repressors and activators in the presence and absence of metals have been reported. Indirect regulation through small noncoding RNAs, whose synthesis is repressed by Fur homologs, has also been discovered. Identification of specific metal-binding residues in distinct subfamilies of Fur and their target DNA motifs, along with the development of efficient bioinformatic tools, has enabled prediction of Fur subfamily members and their target genes from bacterial genome sequences.