APR 25, 2019 12:00 PM PDT

Diagnosis and Treatment of Tuberculosis, a Case Study in Challenges and Threats Posed by Infectious Diseases

C.E. CREDITS: P.A.C.E. CE | Florida CE
Speakers
  • Director & Professor, Biomedical Informatics Research Center, Laboratory for Pathogenesis of Clinical Drug Resistance and Persistence, San Diego State University
    Biography
      My work, has been focused on genetic and epigenetic basis for emergence of new phenotypes in Mycobacterium tuberculosis (M. tuberculosis). Within this realm, we have used a wide variety of approaches including long-read Whole Genome Sequencing (WGS), comparative genomics for genome-wide causal variant identification, metabolomic and regulatory network models, functional elucidation of genetic dark matter, genomic structural anomaly detection, phylogenomic analysis of bacterial species, identification of the role of epigenetic (methylome) variations in phenotypic changes, and machine learning for causal inference in genomics and epigenetics. During the past ten years, my laboratory has focused on applying these techniques to study clinical species of M. tuberculosis collected from various parts of the world (17 countries from far east, eastern Europe, and Africa) to better understand the causation and emergence of drug resistance, virulence, and persistence. Our work, for the past ten years, has been funded by NIAID.

    Abstract:

    Tuberculosis has killed more than one billion people in the last 200 years. It is the oldest and the deadliest human pathogen, recently surpassing HIV. Its adaptation to host and drug pressures is remarkable given its slow rate of growth and provides a moving target in molecular epidemiology of the disease. In this talk we will discuss the epidemiology of the disease, the challenges that the pathogen offers in its adaptation, and the challenges faced in the diagnosis and treatment of the disease. We will discuss the advantages and disadvantages of various diagnostics platforms and outline some exciting new developments on the diagnostics and prognostics fronts. 

    Learning Objectives: 

    1. Epidemiology of tuberculosis
    2. Diagnostic approaches for detection of antibiotic resistance


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