The persistence of Mycobacterium tuberculosis ( Mtb ) is a major problem in managing tuberculosis (TB). Host-generated nitric oxide (NO) is perceived as one of the signals by Mtb to reprogram metabolism and respiration for persistence . However, the mechanisms involved in NO sensing and reorganizing Mtb 's physiology are not fully understood. Since NO damages iron-sulfur (Fe–S) clusters of essential enzymes, the mechanism(s) involved in regulating Fe–S cluster biogenesis could help Mtb persist in host tissues. Here, we show that a transcription factor SufR ( Rv1460 ) senses NO via its 4Fe–4S cluster and promotes persistence of Mtb by mobilizing the Fe–S cluster biogenesis system; suf operon ( Rv1460-Rv1466 ). Analysis of anaerobically purified SufR by UV–visible spectroscopy, circular dichroism, and iron-sulfide estimation confirms the presence of a 4Fe–4S cluster. Atmospheric O 2 and H 2 O 2 gradually degrade the 4Fe–4S cluster of SufR. Furthermore, electron paramagnetic resonance (EPR) analysis demonstrates that NO directly targets SufR 4Fe–4S cluster by forming a protein-bound dinitrosyl-iron-dithiol complex. DNase I footprinting, gel-shift, and in vitro transcription assays confirm that SufR directly regulates the expression of the suf operon in response to NO. Consistent with this, RNA-sequencing of MtbΔsufR demonstrates deregulation of the suf operon under NO stress. Strikingly, NO inflicted irreversible damage upon Fe–S clusters to exhaust respiratory and redox buffering capacity of MtbΔsufR . Lastly, MtbΔsufR failed to recover from a NO-induced non-growing state and displayed persistence defect inside immune-activated macrophages and murine lungs in a NO-dependent manner. Data suggest that SufR is a sensor of NO that supports persistence by reprogramming Fe–S cluster metabolism and bioenergetics.

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Redox stimuli govern a variety of biological processes. The relative sensitivity of redox sensors plays an important role in providing a calibrated response to environmental stimuli and cellular homeostasis. This cellular machinery plays a crucial role in the human pathogen Mycobacterium tuberculosis as it encounters diverse microenvironments in the host. The redox sensory mechanism in M. tuberculosis is governed by two component and one-component systems, alongside a class of transcription factors called the extra cytoplasmic function (ECF) σ factors. ECF σ factors that govern the cellular response to redox stimuli are negatively regulated by forming a complex with proteins called zinc associated anti-σ factors (ZAS). ZAS proteins release their cognate σ factor in response to oxidative stress. The relative sensitivity of the ZAS sensors to redox processes dictate the concentration of free ECF σ factors in the cell. However, factors governing the redox threshold of these sensors remain unclear. We describe here, the molecular characterization of three σ factor/ZAS pairs-σ/RslA, σ/RseA, and σ/RshA-using a combination of biophysical and electrochemical techniques. This study reveals, conclusively, the differences in redox sensitivity in these proteins despite apparent structural similarity and rationalizes the hierarchy in the activation of the cognate ECF σ factors. Put together, the study provides a basis for examining sequence and conformational features that modulate redox sensitivity within the confines of a conserved structural scaffold. The findings provide the guiding principles for the design of intracellular redox sensors with tailored sensitivity and predictable redox thresholds, providing a much needed biochemical tool for understanding host-pathogen interaction.

Transcription in prokaryotes is a multistep process and is primarily regulated at the initiation stage. σ factors are involved in promoter recognition and thus govern prokaryotic gene expression. Mycobacterium tuberculosis (Mtb) σ factors have been previously suggested as important drug targets through large-scale genome analyses. Here we demonstrate the feasibility of specific targeting of Mtb σ factors using designed peptides. A peptide library was generated using three-dimensional structural features corresponding to the interface regions of σ factors and the RNA polymerase. In silico optimization of the peptides, employing structural as well as sequence features, aided specific targeting of σ and σ. We synthesized and characterized the best hit peptide from the peptide library along with other control peptides and studied the interaction of these peptides with σ using biolayer interferometry. The experimental data validate the design strategy. These studies suggest the feasibility of designing specific peptides via in silico methods that bind σ with nanomolar affinity. We note that this strategy can be broadly applied to modulate prokaryotic transcription by designed peptides, thereby providing a tool for studying bacterial adaptation as well as host-pathogen interactions in infectious bacteria.