Mycobacterium tuberculosis: Evolution, Host–Pathogen Interactions, and Implications for Tuberculosis Control

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Abstract

Mycobacterium tuberculosis continues to be a major cause of morbidity and mortality in the world. One-third of the world population is estimated to be infected with tuberculosis resulting in 8.8 million new cases and 1.4 million deaths associated to tuberculosis in 2011 (WHO-fact sheet-2011). The emergence of multidrug-resistant (MDR) and other forms of extensive-drug-resistant (XDR) tuberculosis in many parts of the world is threatening to send us back to an era when tuberculosis was an untreatable disease. Despite the fast pace of progress in the field of tuberculosis research in the last decade, the implementation of promising discoveries continues to be a challenge. In most countries, National Tuberculosis Programs are still using smear microscopy, a 120-year-old technology, to diagnose tuberculosis and treatment regimens that have not changed in the past 40 years. Furthermore, we still have important gaps in our knowledge of the basic biology of M. tuberculosis, as it pertains to pathogen and human interactions. We still do not know the extent of genetic diversity in tuberculosis bacteria, nor do we understand the implications of this diversity in terms of virulence, vaccine, and drug development. Nevertheless, there is fascinating new research into the global diversity of tuberculosis strains and its association to ancient human migrations out of Africa, as well as to more recent migration patterns of humans in the last 500 years. These most recent insights into the diversity of tuberculosis and human coevolution are promising a more far-reaching understanding of the biology of tuberculosis with potential payoffs for the eventual elimination of tuberculosis.

Keywords

Whole Genome Sequencing Tuberculosis Control Molecular Epidemiology Study National Tuberculosis Program Restriction Fragment Length Polymorphism Typing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Division of Infectious Diseases, Department of MedicineNew Mexico Veterans Healthcare SystemAlbuquerqueUSA
  2. 2.Division of Infectious DiseasesUniversity of New Mexico Health Science CenterAlbuquerqueUSA

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