# Optimization of a carbon monoxide (CO) sensing hemoprotein for applications as an antidote for CO poisoning and a biosensor for CO detection in living cells > **NIH NIH K99** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2024 · $163,188 ## Abstract PROJECT SUMMARY/ABSTRACT Carbon monoxide (CO) inhalation is a leading cause of human poisoning in the United States, resulting in about 50,000 cases and at least 1,500 deaths annually, as well as long-term cardiac and neurocognitive sequelae for one-third of survivors. Unfortunately, no point of care antidotal therapy exists for CO poisoning to date. A field- deployable agent that irreversibly scavenges and sequesters CO could serve as an improved therapeutic that increases survival and long-term outcomes for patients suffering from CO poisoning. In this proposal, we will exploit the uniquely strong and specific interaction between CO and ferrous heme by utilizing a hemoprotein scaffold to develop a high-affinity CO scavenger. We recently discovered a remarkable hemoprotein domain, found in the bacterial CO-sensing transcription factor RcoM (regulator of CO metabolism), that exhibits a 900- fold increase in CO binding affinity compared to hemoglobin, the primary biological target in acute CO poisoning. This RcoM hemoprotein also shows exquisite selectivity for CO over oxygen, a critical property for a CO antidote that will be infused intravenously in humans under oxygenated conditions. In Aim 1, we will utilize in vitro spectroscopic methods to identify 1) the minimum functional RcoM subunit, and 2) key amino acid residues that confer high CO affinity, selectivity, and heme stability. In Aim 2, we will evaluate the safety and efficacy of the three RcoM truncates with highest CO affinity and selectivity in vivo. We will assess systemic and organ-specific effects of intravenous RcoM delivery in healthy mice and quantify the ability of infused RcoM to scavenge CO, reverse hemodynamic collapse, and prevent death in a severe preclinical mouse model of CO poisoning. The outcomes of these aims will provide fundamental insight into hemoprotein ligand selectivity and demonstrate the therapeutic potential of recombinant RcoM as a treatment for acute CO poisoning. While toxic at high concentrations, CO, endogenously produced as a by-product of heme degradation, serves as a cytoprotective signal at low concentrations. Preclinical and clinical studies have explored the use of CO as a therapeutic under conditions ranging from infection to ischemia/reperfusion injury. Despite potential clinical benefits, the roles of CO as a signaling molecule are poorly understood, and the CO concentration regimes corresponding to basal signaling, cytoprotection, and toxicity are poorly defined. A genetically encoded, CO-selective fluorescent reporter would be the ideal tool to tease apart physiological roles of CO in living systems. In Aim 3, we will employ the CO-sensing function of RcoM to design a genetically encoded fluorescent reporter, characterize CO- dependent response in vitro, and incorporate this reporter into the mouse genome using CRISPR/Cas9. We will quantify CO accumulation in transgenic reporter mice under different CO exposure conditions and define regimes th... ## Key facts - **NIH application ID:** 10862871 - **Project number:** 5K99HL168224-02 - **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH - **Principal Investigator:** Matthew Ryan Dent - **Activity code:** K99 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $163,188 - **Award type:** 5 - **Project period:** 2023-06-10 → 2024-07-12 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10862871 ## Citation > US National Institutes of Health, RePORTER application 10862871, Optimization of a carbon monoxide (CO) sensing hemoprotein for applications as an antidote for CO poisoning and a biosensor for CO detection in living cells (5K99HL168224-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10862871. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*