Integration of published information into a resistance-associated mutation database for mycobacterium tuberculosis

Hugh Salamon, Ken D. Yamaguchi, Daniela M. Cirillo, Paolo Miotto, Marco Schito, James Posey, Angela M. Starks, Stefan Niemann, David Alland, Debra Hanna, Enrique Aviles, Mark D. Perkins, David L. Dolinger

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Tuberculosis remains a major global public health challenge. Although incidence is decreasing, the proportion of drug-resistant cases is increasing. Technical and operational complexities prevent Mycobacterium tuberculosis drug susceptibility phenotyping in the vast majority of new and retreatment cases. The advent of molecular technologies provides an opportunity to obtain results rapidly as compared to phenotypic culture. However, correlations between genetic mutations and resistance to multiple drugs have not been systematically evaluated. Molecular testing of M. tuberculosis sampled from a typical patient continues to provide a partial picture of drug resistance. A database of phenotypic and genotypic testing results, especially where prospectively collected, could document statistically significant associations and may reveal new, predictive molecular patterns. We examine the feasibility of integrating existing molecular and phenotypic drug susceptibility data to identify associations observed across multiple studies and demonstrate potential for well-integrated M. tuberculosis mutation data to reveal actionable findings.

Original languageEnglish (US)
Pages (from-to)S50-S57
JournalJournal of Infectious Diseases
StatePublished - 2015

All Science Journal Classification (ASJC) codes

  • Immunology and Allergy
  • Infectious Diseases


  • Database
  • Drug resistance
  • Drug susceptibility testing
  • Genomic sequencing
  • Resistance-associated mutations
  • Tuberculosis


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