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Open Access Research article

Evaluation of the new advanced 15-loci MIRU-VNTR genotyping tool in Mycobacterium tuberculosis molecular epidemiology studies

Noelia Alonso-Rodríguez1, Miguel Martínez-Lirola2, Marta Herránz1, Marisa Sanchez-Benitez3, Pilar Barroso4, INDAL-TB group, Emilio Bouza1 and Darío García de Viedma1*

Author Affiliations

1 Servicio de Microbiología y Enfermedades Infecciosas. Hospital Gregorio Marañón, Universidad Complutense, Madrid, CIBER de Enfermedades Respiratorias (CIBERES), Spain

2 Complejo Hospitalario Torrecárdenas, Almería, Spain

3 Unidad de Tuberculosis de Poniente, Almería, Spain

4 Delegación de Salud Distrito Levante, Almería, Spain

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BMC Microbiology 2008, 8:34  doi:10.1186/1471-2180-8-34

Published: 24 February 2008

Abstract

Background

During the last few years, PCR-based methods have been developed to simplify and reduce the time required for genotyping Mycobacterium tuberculosis (MTB) by standard approaches based on IS6110-Restriction Fragment Length Polymorphism (RFLP). Of these, MIRU-12-VNTR (Mycobacterial interspersed repetitive units- variable number of tandem repeats) (MIRU-12) has been considered a good alternative. Nevertheless, some limitations and discrepancies with RFLP, which are minimized if the technique is complemented with spoligotyping, have been found. Recently, a new version of MIRU-VNTR targeting 15 loci (MIRU-15) has been proposed to improve the MIRU-12 format.

Results

We evaluated the new MIRU-15 tool in two different samples. First, we analyzed the same convenience sample that had been used to evaluate MIRU-12 in a previous study, and the new 15-loci version offered higher discriminatory power (Hunter-Gaston discriminatory index [HGDI]: 0.995 vs 0.978; 34.4% of clustered cases vs 57.5%) and better correlation (full or high correlation with RFLP for 82% of the clusters vs 47%). Second, we evaluated MIRU-15 on a population-based sample and, once again, good correlation with the RFLP clustering data was observed (for 83% of the RFLP clusters). To understand the meaning of the discrepancies still found between MIRU-15 and RFLP, we analyzed the epidemiological data for the clustered patients. In most cases, splitting of RFLP-clustered patients by MIRU-15 occurred for those without epidemiological links, and RFLP-clustered patients with epidemiological links were also clustered by MIRU-15, suggesting a good epidemiological background for clustering defined by MIRU-15.

Conclusion

The data obtained by MIRU-15 suggest that the new design is very efficient at assigning clusters confirmed by epidemiological data. If we add this to the speed with which it provides results, MIRU-15 could be considered a suitable tool for real-time genotyping.