Combined numerical analysis based on the molecular description of Mycobacterium tuberculosis by four repetitive sequence-based DNA typing systems

Res Microbiol. 1998 May;149(5):349-60. doi: 10.1016/s0923-2508(98)80440-3.


Mycobacterium tuberculosis clinical isolates (113 isolates from 78 patients) were typed using IS6110-RFLP, DR-RFLP, DR-based spoligotyping and direct repetitive element PCR (DRE-PCR). The similarities among isolates were compared for each individual method. The individual matrix distance files for each method were summed and averaged, and the resulting unique distance file was analysed by the UPGMA (unweighted pair group method with arithmetic averages). Combined numerical analysis with 3 genetic markers (IS6110-RFLP, DR-RFLP and spoligotyping) was performed for all 78 clinical isolates, whereas analysis with 4 genetic markers (with the addition of DRE-PCR) was performed on the 10 main clusters described. When compared to molecular analysis based on individual markers, the molecular description based on multiple genetic markers enabled comparison of the results obtained by individual methods and the obtaining of a more accurate view of strain identity and clusters comparison. The resulting cumulative dendrogram was more accurate for studying the population structure of M. tuberculosis and may be a good tool for elucidating intraspecies genetic microevolution.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bacterial Typing Techniques
  • Caribbean Region / epidemiology
  • Cluster Analysis
  • DNA, Bacterial / chemistry*
  • Evolution, Molecular
  • Genetic Markers
  • Humans
  • Mycobacterium tuberculosis / chemistry
  • Mycobacterium tuberculosis / classification*
  • Mycobacterium tuberculosis / genetics
  • Numerical Analysis, Computer-Assisted*
  • Polymerase Chain Reaction
  • Polymorphism, Restriction Fragment Length
  • Repetitive Sequences, Nucleic Acid / genetics*
  • Tuberculosis / epidemiology
  • Tuberculosis / microbiology


  • DNA, Bacterial
  • Genetic Markers