William R. Bishai, MD, PhD

Co-Director

Titles:

Co-Director, Center for Tuberculosis Research

Professor, Medicine,Pathology, and Molecular Microbiology Immunology

SciVal:

SciVal Link

Area of Research

Bacterial gene regulation, pathogenesis, tuberculosis, latent infections, sigma factors.

Specific Research Interests

Transcription factors regulate bacterial adaptive response for switching between rapid growth leading to overt disease and stationary phase survival during which the host is colonized and at risk for disease. We study the role of stationary phase-specific transcription factors in diseases caused by Mycobacterium tuberculosis and Staphylococcus aureus. Latent tuberculosis is a colonization state which affects one-third of the world’s population and carries a significant risk for active TB. M. tuberculosis possesses 12 alternate RNA polymerase sigma factors several of which govern virulence and persistence in animal models and survival in vitro under stationary phase and stress conditions. We are using molecular genetic strategies including microarray analysis with recombinant bacteria to characterize the roles of these transcription factors in diseases caused by M. tuberculosis. Testing of virulence and persistence is performed locally using either the mouse or rabbit models of tuberculosis.

Additionally, clinical research on TB has been an active interest in the laboratory, and we have ongoing collaborative projects with other members of the Center for Tuberculosis Research on experimental therapeutics and diagnostics, both in Baltimore City and in several foreign settings.

Staff & Students

Research Associate:

Post docs

PhD students

Categories

Events

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Projects

ICOHRTA Training Program (Fogarty)

International Clinical, Operational, and Health Services Research Award (ICOHRTA) training program. A training program that...

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Impact of diabetes on TB treatment outcomes...

This is a study to prospectively enroll and follow TB patients co-infected with diabetes and TB patients without diabetes...

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A Blueprint for Success: Understanding the...

We are using a combination of statistical analysis and transmission modeling, in collaboration with the NYC Dept of Health &...

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Understanding the role of repeat testing and...

We have developed a Markov model of serial IGRA testing to help improve testing algorithms with TST vs. IGRA in low-risk...

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TB Modeling and Analysis Consortium

The TB MAC brings TB modelers together from a wide range of institutions to answer questions of global policy relevance.  I...

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