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Introduction: Classification of M. tuberculosis complex strains

For a long time the conservation at genome level has prohibited the development of effective molecular methods for the differentiation of clinical M. tuberculosis complex (MTBC) isolates. The differentiation of clinical MTBC isolates was classically based on morphological and phenotypic characteristics such as growth morphology on Löwenstein-Jensen slants (eugonic or dysgonic) or biochemical properties (niacin test, nitrate reduction) (Wayne 1986). Since these tests need sufficient bacterial growth, are time-consuming, do not allow an unambiguous species identification in every case and may not be performed by every laboratory routinely, there was a growing demand for molecular methods that were expected to allow a more rapid and precise species identification.
However, the development of such methods has been hampered by a high similarity on the DNA level and typical targets for species differentiation like the 16S rDNA gene and the 16S-to-23S rDNA internal transcribed spacer are identical (Feizabadi et al. 1996, Frothingham et al. 1994, Niemann et al. 2000, Harmsen et al. 2003).
IS6110 DNA fingerprinting and spoligotyping were among the first methods that have allowed a molecular finer typing of clinical isolates (van Embden et al. 1993, Kamerbeek et al. 1997, van Soolingen et al. 2003). Beyond their intensive use as markers in epidemiological studies, these methods have revealed first insights in the population structure of clinical isolates in different geographical settings. Several genotypes or strain families such as the Beijing genotype have been identified by sharing highly similar IS6110 RFLP and/or characteristic spoligotyping patterns. A large spoligotyping database (SpolDB4) has allowed a first overview on the global population structure and diversity of the MTBC (Brudey et al. 2006). The distribution of particular lineages shows a strong geographical dependence that supports the notion of a phylogeographical population structure and clonal evolution of the MTBC (e.g. van Soolingen et al. 2003, Brudey et al 2006).
Although both methods are well suited for discrimination of clinical isolates they have clear disadvantages for the investigation of the deep phylogenetic structure.
In order to define a population structure more unambiguously, genetic markers need to be independent and, ideally, leading to irreversible events. The establishment of the complete genome sequences of two strains of M. tuberculosis and one strain of M. bovis has allowed a more detailed insight in the genomic structure of MTBC isolates and has facilitated the identification of such markers, namely large sequence polymorphisms (LSPs or RDs; regions of difference) or single nucleotide polymorphisms (SNPs).
A first widely used SNP classification based on SNPs in katG at position 463 and gyrA at position 95 divided the MTBC in three principle genetic groups (Sreevatsan et al. 2007). Thereafter, different RDs have been reported that have been used to define the phylogeny of the M. tuberculosis complex (MTBC) and the identification of particular phylogenetic lineages. Initially, Gordon et al. (1999) proposed a RD classification scheme based on the observation that genomic differences exist between the vaccine strain M. bovis BCG (bacillus Calmette Guérin) and M. tuberculosis H37Rv. These genomic variations (RDs) mainly showed a loss of genetic material in the BCG strain, possibly responsible for its attenuation. Consequently, the genomes of strains of other genotypes were compared and further regions of difference specific for several lineages were discovered (e.g. Gordon et al. 1999, Brosch et al. 2002, Hirsch et al. 2004,). Using primers flanking the particular regions, their presence or absence can easily be determined. Due to the extremely clonal population structure of MTBC and virtually no horizontal gene exchange, such deletions represent robust markers for deep phylogenetic branching and identification of phylogenetic lineages (e.g. Brosch et al. 2002, Hirsch et al. 2004).
In 2002 Brosch et al. proposed a new phylogenetic scenario for the MTBC based on 20 regions of difference with a total sample number of 100 M. tuberculosis isolates. The presence or absence of particular regions was found to be characteristic for several lineages e.g. for M. tuberculosis (TbD1, except EAI strains), M. africanum (RD9), or M. bovis  (RD4). This work was extended by Gagneux and co-workers (2006), who performed a microarray-based investigation of the genome content of 875 MTBC strains from 80 countries. In principle, 6 major lineages have been identified within the MTBC. This population structure was further confirmed by studies applying SNP markers for investigation of the population structure of larger collections of clinical MTBC isolates (for an overview see Gagneux and Small 2007).
However, although both LSPs and SNPs allowed a definition of the main lineages within the MTBC, a finer phylogenetic classification appears to be difficult due to the low variability of such markers in the MTBC clonal complex.
Hence, the use of more variable independent markers for the analysis of the population structure is desirable. Micro- or minisatellites are powerful tools that have been successfully applied for high resolution population-genetics. For the MTBC a typing system based on Variable Number of Tandem Repeats (VNTR)-typing applying genetic elements called Mycobacterial Interspersed Repetitive Units (MIRU) as genetic markers has been proposed as a suitable tool to analyze the genetic diversity of clinical isolates (Supply et al. 2006, Allix et al. 2007). First evaluations already showed that MIRU-VNTR typing can provide unique high-resolution insights into the population structure of the MTBC and provides clear criteria for the identification of the different MTBC lineages and sub-lineages (Supply et al. 2006, Allix et al. 2007).

References:
  • Brosch R, Gordon V, Marmiesse M, Brodin P, Buchrieser C, Eiglmeier K, Garnier T, Gutierrez C, Hewinson G, Kremer K, Parsons LM, Pym AS, Samper S, van Soolingen D, Cole ST. 2002. A new evolutionary scenario for the Mycobacterium tuberculosis complex. Proc Natl Acad Sci USA 99:3684-3689. [PubMed]
  • Brudey K, Driscoll JR, Rigouts L, Prodinger WM, Gori A, Al-Hajoj SA, Allix C, Aristimuño L, Arora J, Baumanis V, Binder L, Cafrune P, Cataldi A, Cheong S, Diel R, Ellermeier C, Evans JT, Fauville-Dufaux M, Ferdinand S, de Viedma DG, Garzelli C, Gazzola L, Gomes HM, Guttierez C, Hawkey PM, van Helden PD, Kadival GV, Kreiswirth BN, Kremer K, Kubin M, Kulkarni SP, Liens B, Lillebaek T, Ly HM, Martin C, Martin C, Mokrousov I, Narvskaïa O, Ngeow YF, Naumann L, Niemann S, Parwati I, Rahim Z, Rasolofo-Razanamparany V, Rasolonavalona T, Rossetti ML, Rüsch-Gerdes S, Sajduda A, Samper S, Shemyakin IG, Singh UB, Somoskovi A, Skuce RA, van Soolingen D, Streicher EM, Suffys PN, Tortoli E, Tracevska T, Vincent V, Victor TC, Warren RM, Yap SF, Zaman K, Portaels F, Rastogi N, Sola C. 2006. Mycobacterium tuberculosis complex genetic diversity: mining the fourth international spoligotyping database (SpolDB4) for classification, population genetics and epidemiology. BMC Microbiol 6:23. [PubMed]
  • Gagneux S, DeRiemer K, Van T, Kato-Maeda M, de Jong BC, Narayanan S, Nicol M, Niemann S, Kremer K, Gutierrez MC, Hilty M, Hopewell PC, Small PM. 2006. Variable host-pathogen compatibility in Mycobacterium tuberculosis.Proc Natl Acad Sci USA 103:2869-2873. [PubMed]
  • Gagneux S, Small PM. (2007) Global phylogeography of Mycobacterium tuberculosis and implications for tuberculosis product development. Lancet Infect Dis 7:328-337. [PubMed]
  • Gordon SV, Brosch R, Billault A, Garnier T, Eiglmeier K, Cole ST. 1999. Identification of variable regions in the genomes of tubercle bacilli using bacterial artificial chromosome arrays. Mol Microbiol 32:643-655. [PubMed]
  • Feizabadi M, Robertson ID, Cousins DV, Hampson DJ. 1996. Genomic analysis of Mycobacterium bovis and other members of the Mycobacterium tuberculosis complex by isoenzyme analysis and pulsed-field gel electrophoresis. J Clin Microbiol 34:1136-1142. [PubMed]
  • Frothingham RH, Hills G, Wilson KH. 1994. Extensive DNA sequence conservation throughout the Mycobacterium tuberculosis complex. J Clin Microbiol 32:1639-1643. [PubMed]
  • Harmsen D, Dostal S, Roth A, Niemann S, Rothgänger J, Sammeth M, Albert J, Frosch M, Richter E. 2003. RIDOM: comprehensive and public sequence database for identification of Mycobacterium species. BMC Infect Dis 3:26. [PubMed]
  • Hirsh AE, Tsolaki AG, DeRiemer K, Feldman MW, Small PM. 2004. From the cover: stable association between strains of Mycobacterium tuberculosis and their human host populations. Proc Natl Acad Sci USA 101:4871-4876. [PubMed]
  • Huard RC, de Oliviera Lazzarini LC, Butler WR, van Soolingen D, Ho JL. 2003. PCR-based method to differentiate the subspecies of the Mycobacterium tuberculosis complex on the basis of genomic deletions. J Clin Microbiol 41:1637-1650. [PubMed]
  • Kamerbeek J, Schouls L, Kolk A, van Agterveld M, van Soolingen D, Kuijper S, Bunschoten A, Molhuizen H, Shaw R, Goyal M, van Embden J. 1997. Simultaneous detection and strain differentiation of Mycobacterium tuberculosis for diagnosis and epidemiology. J Clin Microbiol 35:907-914. [PubMed]
  • Mostowy S, Onipede A, Gagneux S, Niemann S, Kremer K, Desmond EP, Kato-Maeda M, Behr MA. 2004. Genomic analysis distinguishes Mycobacterium africanum. J Clin Microbiol 42:3594-3599. [PubMed]
  • Niemann, S., E. Richter, S. Rüsch-Gerdes S. 2000. Differentiation among members of the Mycobacterium tuberculosis complex by molecular and biochemical features: evidence for two pyrazinamide-susceptible subtypes of M. bovis. J Clin Microbiol 38:152-157. [PubMed]
  • Oelemann MC, Diel R, Vatin V, Haas W, Rüsch-Gerdes S, Locht C, Niemann S, Supply P. 2007. Assessment of an optimized mycobacterial interpersed repetitive unit-variable number of tandem repeat typing system combined with spoligotyping for population-based molecular epidemiology studies of tuberculosis. J Clin Microbiol 45:691-697. [PubMed]
  • Sreevatsan S, Pan X, Stockbauer KE, Connell ND, Kreiswirth BN, Whittam TS, Musser JM. 1997. Restricted structural gene polymorphism in the Mycobacterium tuberculosis complex indicates evolutionarily recent global dissemination. Proc Natl Acad Sci USA 94:9869-9874. [PubMed]
  • Supply P, Allix C, Lesjean S, Cardoso-Oelemann M, Rüsch-Gerdes S, Willery E, Savine E, de Haas P, van Deutekom H, Roring S, Bifani P, Kurepina N, Kreiswirth B, Sola C, Rastogi N, Vatin V, Gutierrez MC, Fauville M, Niemann S, Skuce R, Kremer K, Locht C, van Soolingen D. 2006. Proposal for standardization of optimized mycobacterial interspersed repetitive unit-variable number tandem repeat typing of Mycobacterium tuberculosis. J Clin Microbiol 44:4498-4510. [PubMed]
  • van Embden JD, Cave MD, Crawford JT, Dale JW, Eisenach KD, Gicquel B, Hermans P, Martin C, McAdam R, Shinnick TM. 1993. Strain identification of Mycobacterium tuberculosis by DNA fingerprinting: recommendations for a standardized methodology. J Clin Microbiol 31:406-409. [PubMed]
  • van Soolingen D, Kremer K, Vynycky E. 2003. New perspectives in the molecular epidemiology of tuberculosis. In: Kaufmann SHE, Hahn H (eds). Mycobacteria and TB. Issues Infect Dis. Basel, Karger, vol 2, pp. 17-45.
  • Wayne, LG, Kubica GP. 1986. The mycobacteria. In: Sneath PHA, Holt JG (eds.). Bergey's manual of systematic bacteriology. The Williams Co., Baltimore, Md., vol. 2, pp. 1435-1457.
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