$10M Grant Funds Infection-Focused Center
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A new center at Stanford will focus on understanding the interactions between salmonella bacteria and immune cells infected by the pathogen, as well as on treating such infections.
The Allen Discovery Center at Stanford University for Multiscale Systems Modeling of Macrophage Infection will be directed by Markus Covert, PhD, associate professor of bioengineering. The multidisciplinary center is being funded by a four-year, $10 million grant from the Paul G. Allen Frontiers Group, a nonprofit organization aimed at spurring biomedical innovation. The center could receive as much as $10 million more after that period to fund four more years of work.
The center will integrate cutting-edge modeling, computation and experimental measurements to create multiscale models of the bacteria as they infect human immune cells, shedding new light on how this complex system of cell behaviors creates infectious disease.
Species of salmonella cause more than 100 million symptomatic infections annually, including 16 million to 20 million cases of typhoid fever. The microorganism’s modus operandi is to infect and hide out in immune cells called macrophages, manipulating the metabolism of these cells to its own benefit.
“We are grateful for the recognition and support of Stanford’s faculty in the area of quantitative bioscience,” said Stanford University President John Hennessy, PhD. “The application of engineering and computational techniques to solving the hardest problems in biomedicine is one of the most exciting and promising research directions.”
Denise Monack, PhD, associate professor of microbiology and immunology, and K.C. Huang, PhD, associate professor of bioengineering and of microbiology and immunology, will be co-investigators at the center, Covert said.
“We’ve assembled a unique team with the experience to bring the latest biological and bioengineering knowledge together with industrial-scale computational methods,” said Covert, whose research concentrates on building computational models of complex biological processes and using these models to guide experimentation. “We expect that the resulting multicellular modeling platform, which will be available to everyone, will transform the rate at which biological discovery occurs in many areas of bioscience, well beyond infectious diseases.”
