John Alverdy, MD, has run a continuously funded NIH-funded laboratory that studies the molecular interactions of bacteria and the intestinal mucosa in order to understand how life-threatening infections arise after trauma and major surgery and during critical illness. He has developed several anti-infective polymer-based compounds that can attenuate the virulence of several multi-drug resistant pathogens that cause life threatening infections in surgical patients and works with the IME to synthesize, refine, and scale the compounds for pre-clinical testing.

The Alverdy lab seeks to better understand the regulation of virulence expression among potential pathogens through investigating the characteristics of the microbial context, molecular machinery that senses that context, and ultimately the lethal combinations of virulence expression that leads to disease. The majority of our work has focused on the sense and response virulence mechanisms of Pseudomonas aeruginosa, a well characterized and clinically important pathogen. We have shown a remarkable potential for this organisms to respond to host environmental cues related to stress, ischemia, immune activation and nutrient depletion. With this core model of environmental regulation of virulence expression, we are pursuing applications in intestinal transplantation, anastomotic and radiation physiology, necrotizing enterocolitis and ischemia/reperfusion injury. We are also investigating similar sense and response mechanisms in other clinically important organisms, including Staphylococcus aureus and Candida albicans. Finally, we are interested in developing virulence-based therapies to prevent virulence activation through modifications in microenvironment of the stressed host such as phosphate repletion and polymer-mediated mucosal replacement therapies.

The ultimate goal of understanding microbial virulence is to provide clinical tools to improve the care of patients. However the complexity of the host-pathogen interaction and the vast amounts of mechanistic information available constitutes a formidable barrier to translational research. Computational agent based modeling is a well suited to dynamically represent mechanistic detail in a modifiable context to recapitulate cellular behavior at the tissue, organ and patient levels.