The mutation rate of mycobacterial repetitive unit loci in strains of M. tuberculosis from cynomolgus macaque infection

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Abstract

Background: Mycobacterial interspersed repetitive units (MIRUs) are minisatellites within the Mycobacterium tuberculosis (Mtb) genome. Copy number variation (CNV) in MIRU loci is used for epidemiological typing, making the rate of variation important for tracking the transmission of Mtb strains. In this study, we developed and assessed a whole-genome sequencing (WGS) approach to detect MIRU CNV in Mtb. We applied this methodology to a panel of Mtb strains isolated from the macaque model of tuberculosis (TB), the animal model that best mimics human disease. From these data, we have estimated the rate of MIRU variation in the host environment, providing a benchmark rate for future epidemiologic work. Results: We assessed variation at the 24 MIRU loci used for typing in a set of Mtb strains isolated from infected cynomolgus macaques. We previously performed WGS of these strains and here have applied both read depth (RD) and paired-end mapping (PEM) metrics to identify putative copy number variants. To assess the relative power of these approaches, all MIRU loci were resequenced using Sanger sequencing. We detected two insertion/deletion events both of which could be identified as candidates by PEM criteria. With these data, we estimate a MIRU mutation rate of 2.70 × 10-03 (95% CI: 3.30 × 10-04- 9.80 × 10-03) per locus, per year. Conclusion: Our results represent the first experimental estimate of the MIRU mutation rate in Mtb. This rate is comparable to the highest previous estimates gathered from epidemiologic data and meta-analyses. Our findings allow for a more rigorous interpretation of data gathered from MIRU typing. © 2013 Ragheb et al.; licensee BioMed Central Ltd.

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Ragheb, M. N., Ford, C. B., Chase, M. R., Lin, P. L., Flynn, J. A. L., & Fortune, S. M. (2013). The mutation rate of mycobacterial repetitive unit loci in strains of M. tuberculosis from cynomolgus macaque infection. BMC Genomics, 14(1). https://doi.org/10.1186/1471-2164-14-145

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