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Updated: May 29, 2026

Identification of Mycobacterium Species by DNA Microarray Chip Method
Published on: June 24, 2025
Mycobacterium tuberculosis spoligotypes that may derive from mixed strain infections are revealed by a novel
Luiz Claudio O Lazzarini1, Jeffrey Rosenfeld, Richard C Huard
1Institute of Thoracic Disease, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
Abstract:
Global control of tuberculosis is increasingly dependent on rapid and accurate genetic typing of Mycobacteriumtuberculosis. Spoligotyping is a first-line genotypic fingerprinting method for M.tuberculosis isolates. An international online database (SpolDB4) of spoligotype patterns has been established wherein a clustered pattern (shared by ≥2 isolates) is designated a shared international type (SIT). Dual infections of single patients by distinct strains of M. tuberculosis is increasingly reported in high tuberculosis incidence areas, raising the possibility of false composite spoligotype patterns if performed upon mixed strain samples. A computational approach was applied to SpolDB4 and found that of the reported 1939 SITs, 54% could be a composite of two other SITs. Although many of the spoligotypes listed in SpolDB4 may be the product of admixing, the majority of patterns were reported with a corresponding low case frequency and so the effect of misclassification upon database integrity with these is likely minimal. Phylogenetic analysis of the five SITs most prone to be a composite demonstrated that these patterns designate nodes from which the ramifications of large families T, MANU, LAM, and EAI emerged. We illustrate how geographic context may indicate when an observed pattern could be the product of mixed infection. Importantly, when one of the most composite-prone SITs is obtained, further genetic testing by alternate methods is prudent to rule-out mixed infection, especially in high tuberculosis prevalence areas. These findings have broad practical implications for tuberculosis control and surveillance, as well as highlight the utility of a computational approach in providing solutions to biological questions in which the information can be digitalized.
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