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Title |
Genomic polymorphisms for diagnostics of Mycobacterium avium subspecies paratuberculosis |
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Author(s) |
Semret M1,
Alexander DC1,
de Haas P2,
Overduin P2,
van Soolingen D2,
Cousins D3,
Behr MA1.
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Institution(s) |
1McGill University Health Centre, Montreal, Canada, 2National Institute of Public Health and the Environment, Bilthoven, Netherlands, 3Australian Reference Laboratory for Bovine Tuberculosis, Perth, Australia
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Source |
Eighth International Colloquium on Paratuberculosis
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Section |
5:
Diagnosis
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Presentation |
Oral
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Abstract |
M. avium subsp. paratuberculosis is an emerging pathogen of mammals, and is actively being investigated as a possible zoonotic agent. The lack of reliable diagnostic assays has hampered rational assessment of the prevalence of this organism in humans and animals. We have used a comparative genomics approach to reveal genomic differences between Mycobacterium avium subsp. paratuberculosis and its close relative M. avium subsp. avium, a highly prevalent environmental organism. From computational and DNA microarray-based study of two prototype strains, M. avium avium strain 104 and M. avium paratuberculosis strain K10, we have uncovered 2 types of large sequence polymorphisms (LSPs); those present in the former but missing in the latter (LSPAs), and those only present in the latter (LSPPs). We examined the distribution of 3 LSPAs and 17 LSPPs across a panel of 383 M. avium complex isolates in order to determine their potential utility for development of accurate diagnostic tests. Our results show that absence of 2 of the LSPAs (LSPA 8 or LSPA 14) was 100% specific for the identification of M. avium paratuberculosis. In contrast, only 7 of the 17 LSPPs show a comparable degree of specificity. Of these 7, LSPP2 and LSPP15 were also highly sensitive for the identification of M. avium paratuberculosis, while the remaining 5 LSPPs were only variably present in M. avium paratuberculosis. These data indicate LSPs best suited for diagnosis of M. avium paratuberculosis and highlight the limitations of in silico-driven comparisons of prototype sequences for development of diagnostic assays.
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