Tuberculosis: Image processing and systems biology of macrophage infection

Tuberculosis is one of the most widespread diseases in the world, with about a third of the population infected. While most infections are asymptomatic, latent tuberculosis can progress into an acute and life-threatening condition. As most infections occur in third-world countries where medical practice often remains below standard due to challenging circumstances, and high prevalence of AIDS leads to more active TB, the prolonged misuse of antibiotics has led to multiresistent strains, and several first-line and second-line antibiotics have been found to be ineffective. This project aims at modeling the macrophage infection mechanism using high-throughput experimentation and the development of novel algorithms to the associated computational challenges, in order to gain a systems level understanding of the infection process, which might facilitate new hypotheses about potential new drug targets.

For further information contact Alexander Schliep (alexander@schlieplab.org).

Team

Members: Alexander Schliep, Alexander Schliep, John Wiedenhoeft. Collaborators: Marila Gennaro (Public Health Research Institute (UMDNJ)), Eduardo Sontag (Department of Mathematics, Rutgers University).