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Journal of Clinical Microbiology, December 2003, p. 5640-5644, Vol. 41, No. 12
0095-1137/03/$08.00+0     DOI: 10.1128/JCM.41.12.5640-5644.2003
Copyright © 2003, American Society for Microbiology. All Rights Reserved.

Use of Genetic Distance as a Measure of Ongoing Transmission of Mycobacterium tuberculosis

MRC Centre for Molecular and Cellular Biology, Department of Medical Biochemistry,¹ Department of Paediatrics and Child Health, Faculty of Health Sciences, Stellenbosch University, Tygerberg, South Africa,² Department of Medicine, McGill University Health Centre, Montreal, Quebec, Canada³

Received 6 May 2003/ Returned for modification 8 July 2003/ Accepted 26 August 2003

The stability of the genotypic marker IS6110, used to define the epidemiology of Mycobacterium tuberculosis, is one of the most important factors influencing the interpretation of DNA fingerprint data. We propose that evolved strains should be considered together with clustered strains to represent chains of ongoing transmission. For the present study we used a large set of fingerprint data for strains collected between 1992 and 1998 from residents of a community with a high incidence of tuberculosis in Cape Town, South Africa. Interstrain genetic distances were calculated by counting the banding pattern mismatches in the IS6110 DNA fingerprints of different isolates. These data demonstrate that the propensity to change by one or two bands is independent of the IS6110 copy number. Hence, the genetic distance between pairs of isolates can be simply expressed as the number of differences in the banding patterns. From this foundation, a data set which identifies newly evolved strains has been generated. Inclusion of these evolved strains into various molecular epidemiological calculations significantly increased the estimate of ongoing transmission in this study setting. The indication is that nearly all cases of tuberculosis in this community are due to ongoing transmission. This has important implications for tuberculosis control, as it indicates that the control measures used at present are unable to reduce the level of transmission. This technique may also be applicable to the study of low-incidence tuberculosis outbreaks as well as the analysis of epidemiological data from other disease epidemics.

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