Figures
Abstract
Background
Different combinations of variable number of tandem repeat (VNTR) loci have been proposed for genotyping Mycobacterium tuberculosis complex (MTBC). Existing VNTR schemes show different discriminatory capacity among the six human MTBC lineages. Here, we evaluated the discriminatory power of a “customized MIRU12” loci format proposed previously by Comas et al. based on the standard 24 loci defined by Supply et al. for VNTR-typing of MTBC in Ghana.
Method
One hundred and fifty-eight MTBC isolates classified into Lineage 4 and Lineage 5 were used to compare a customized lineage-specific panel of 12 MIRU-VNTR loci (“customized MIRU-12″) to the standard MIRU-15 genotyping scheme. The resolution power of each typing method was determined based on the Hunter-Gaston- Discriminatory Index (HGDI). A minimal set of customized MIRU-VNTR loci for typing Lineages 4 (Euro-American) and 5 (M. africanum West African 1) strains from Ghana was defined based on the cumulative HGDI.
Results and Conclusion
Among the 106 Lineage 4 strains, the customized MIRU-12 identified a total of 104 distinct genotypes consisting of 2 clusters of 2 isolates each (clustering rate 1.8%), and 102 unique strains while standard MIRU-15 yielded a total of 105 different genotypes, including 1 cluster of 2 isolates (clustering rate: 0.9%) and 104 singletons. Among, 52 Lineage 5 isolates, customized MIRU-12 genotyping defined 51 patterns with 1 cluster of 2 isolates (clustering rate: 0.9%) and 50 unique strains whereas MIRU-15 classified all 52 strains as unique. Cumulative HGDI values for customized MIRU-12 for Lineages 4 and 5 were 0.98 respectively whilst that of standard MIRU-15 was 0.99. A union of loci from the customised MIRU-12 and standard MIRU-15 revealed a set of customized eight highly discriminatory loci: 4052, 2163B, 40, 4165, 2165, 10,16 and 26 with a cumulative HGDI of 0.99 for genotyping Lineage 4 and 5 strains from Ghana.
Citation: Asante-Poku A, Nyaho MS, Borrell S, Comas I, Gagneux S, Yeboah-Manu D (2014) Evaluation of Customised Lineage-Specific Sets of MIRU-VNTR Loci for Genotyping Mycobacterium tuberculosis Complex Isolates in Ghana. PLoS ONE 9(3): e92675. https://doi.org/10.1371/journal.pone.0092675
Editor: Igor Mokrousov, St. Petersburg Pasteur Institute, Russian Federation
Received: November 8, 2013; Accepted: February 25, 2014; Published: March 25, 2014
Copyright: © 2014 Asante-Poku et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported financially by the UNICEF/UNDP/World Bank/WHO special program for research and training in Tropical Diseases for DY-M and the Leverhulme-Royal Society Africa (DY-M and SG) and NTP Ghana. Funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Tuberculosis (TB) is a major public health problem worldwide, causing 8.8 million new cases and more than 1.4 million deaths each year [1]. The main strategy for controlling TB, especially in low resourced countries, is case detection and treatment using the directly observed treatment short course (DOTS) strategy [2]. The conventional indicators used for assessing TB control programmes focuses on the proportion of patients with new sputum smear positive pulmonary disease that are cured by the end of treatment or whose sputum microscopy becomes negative after the first 2 months of treatment [3]. Such indicators ignore equally important aspects of TB control such as the duration of infectivity, the frequency of reactivation, and the risk of progression among the infected contacts, or the risk of transmission. Thus the control of TB also depends on understanding the patterns and dynamics of transmission which is useful for the implementation of public health measures to reduce sources of infection [4], [5].
A number of molecular markers are available for differentiating members of the Mycobacterium tuberculosis complex (MTBC) for conventional epidemiological investigations of TB outbreaks and to assess risk factors associated with recent transmissions [6], [7]. Mycobacterial interspersed repetitive unit-variable number of tandem repeats (MIRU-VNTR) typing, have overcome most of the shortcomings of IS6110 RFLP [8]–[10], and have now replaced this older technique as the new gold standard for molecular epidemiological investigation of TB. MIRU-VNTR typing which uses genomic diversity at different VNTR loci can have a cumulative resolution comparable to that of IS6110 RFLP analysis depending on the combination of loci analysed [11]–[17].
Several combinations of MIRU- VNTR loci have been published with initial methods relying on only a few loci, which turned out to have low discriminatory power among MTBC isolates [18], [37]–[39]. Subsequently, a standard MIRU-12 loci set with discriminatory power close to IS6110-RFLP was proposed for molecular epidemiological studies in TB [19]–[21]. More recently, this initial MIRU-12 set was replaced by the standard MIRU-15 set, and currently, standard MIRU- 24 loci set [34] has been proposed for optimal discrimination of closely related strains. The standard MIRU15 set which includes six of the previous MIRU- 12 with nine additional loci has been recommended as the standard for routine molecular epidemiology of TB, including outbreak investigations and population-based transmission studies. MIRU-24 set comprises the same 15 loci plus an additional nine provide additional information aimed at phylogenetic and population genetic aspects of MTBC.
The usage of the standard MIRU-15 and MIRU-24 has helped to gain insight into the transmission dynamics of MTBC. However, the initial selection of these loci was to some extent biased towards strains belonging to Lineage 4 (Euro-American lineage) [34]. The inability of the proposed loci led to new customized sets for Lineage 2 strains that include the clinically relevant Beijing family of strains [18]. However, the human-associated MTBC includes 6 additional lineages [22], [23], [45]–[47], which show a strong phylogeographic structure [24]–[26]. As observed for Lineage 2 strains, this might suggest that the usage of high discriminatory MIRU-VNTR loci may be sub-optimal in areas such as Ghana where about 20% of all TB cases are caused by Lineages 5 and 6 of MTBC (also known as M. africanum West Africa 1 and 2) [27]–[28].
Comas et al. [30] using 108 global MTBC strains [30] showed that the majority of the loci included in standard MIRU-24 had a variable discriminatory power across the different MTBC lineages. Moreover, the MIRU-VNTR loci that exhibited the highest discrimination index within one lineage were not necessarily the ones with the highest discriminatory power in other lineages. Based on the allelic diversity of individual MIRU-VNTR locus, Comas et al. [30] suggested different combinations of MIRU-VNTR loci that offered high resolution for the different MTBC lineages. These combinations offered two main advantages over the existing one; it maximized allelic diversity for a given MTBC lineage and allowed for cost effective analyses [30].
Here we evaluated this concept in the Ghanaian setting and compared the standard MIRU-15 to two lineage-specific 12-loci sets (here referred to as “customized MIRU-12”), one for Lineage 4 and one for Lineage 5, which are the most frequent MTBC lineages in Ghana [27]–[28], [49].
Materials and Methods
Ethics Statement
Ethical clearance for this study was obtained from the IRB of the Noguchi Memorial Institute for Medical Research, which has a Federal wide Assurance number FWA00001824. The procedure for sampling in this study was basically the same as those outlined by the National Tuberculosis Programme for the routine management of TB in Ghana. Informed consent both written (in the case of literate participants) and oral (for illiterates) was sought from all participants before their inclusion in the study. Consent was sought from their parents or guardians on behalf of children below sixteen years. As per the guidelines of the institutional review board of the Noguchi Memorial Institute for Medical Research, the objectives and benefits of the study were explained to all participants and they were assured of the confidentiality of all information collected from during the study.
Isolate Selection and Lineage Classification
A total of 178 MTBC isolates consecutively selected from a pool of retrospective samples were included in the study. Specimens included in this study were collected consecutively over a period of 17 months (from October 2007 to March 2009) from sputum AFB-positive pulmonary TB cases attending four main government health centres covering three different regions: Central, Greater Accra and Western regions of Ghana respectively before commencement of anti-TB drug. DNA was extracted as described previously [33]. MTBC was confirmed by IS6110 PCR [40]. The isolates were then classified into lineages by analyses of various regions of difference (RDs) as previously described [31]. Specifically, all isolates were first screened for RD9. RD9-deleted strains were screened for RD4. Isolates identified as RD9 deleted and RD4 undeleted were further sub-typed for Lineage 5 and 6 (M. africanum West Africa I and II) using RD711 and RD702 flanking primers, respectively. TaqMan real time PCR was performed according to standard procedures using probes designed by Stucki et al for the confirmation of Lineages [35]. Although Lineage 6 strains (M. africanum West Africa II) are present in Ghana [27], [28], they were removed from further analysis due to limited number (6 isolates) identified.
MIRU-VNTR Analysis
Two sets of PCRs were performed for each isolate. The first set was performed using the 12 lineage-specific MIRU-VNTR loci proposed by Comas et al. [30], while the second set consisted of the standard MIRU-15 as described by Supply et al. [34] (Table 1). Each PCR mixture contained 10X PCR buffer, 1.5 mM MgCl2, 200 μM concentrations of deoxyribonuclueotide triphosphate, 5 μM concentration of each primer, 1 μl of HotstarTaq DNA polymerase enzyme, 5 μl Q solution and 10 ng of DNA template in a total volume of 25 μl. Negative (sterile water) and positive controls (H37Rv) were added to each PCR reaction to validate the assay. Locus amplification was carried out under the following conditions: initial denaturation at 95°C for 15 minutes, and then 40 cycles of 95°C for 1 minute, 59°C for1 minute and 72°C for 3 minutes, followed by a final extension at 72°C for 7 minutes. Gel electrophoresis was done in 2% agarose for 5 hours at 80 constant Voltage. The amplicons were sized using a 100 bp marker and the obtained size compared with allelic table as published by Supply et al. [34].
SNP Typing
TaqMan real time PCR was performed as published by Stucki et al. [35]. Briefly, in a 200 μl sterile PCR tube, 2 μl of DNA was added to a 5 μl sterile water containing 0.21 μM each reverse and forward primers for the targeted regions, 0.83 μM each probe A for ancestral allele and probe B for mutant allele (each labelled with different dyes); and 5 μl Taqman Universal MasterMix II (Applied Biosystem). The reaction was performed in Applied Biosystems 7300 real time PCR system under the following conditions: 60°C for 30 seconds, 95°C 10 minutess, 95°C 15 seconds and 60°C 1 minute for 40 cycles; 60°C for 30 seconds. The fluorescence intensity in the dyes (VIC and FAM) channels were measured at the end of each cycle.
Data Analysis
The number of repeats for each locus was determined based on the allelic table by Supply et al. [34] and clustering analysis was done using the online tool at http://www.MIRU-VNTRplus.org. MIRU-VNTR clusters were defined as isolates sharing identical patterns. The clustering rate was defined as (nc - c)/n, where nc is the total number of clustered cases, c is the number of clusters, and n is the total number of cases in the sample [29].
The Hunter-Gaston Discriminatory Index (HGDI) was used to calculate the discriminatory power of each locus as well as that of each method [36].
Determination of a Minimal Set of MIRU-VNTR Loci
Stepwise analysis was performed to identify a set of loci needed to achieve maximum discrimination. Firstly, we combined loci from the customised sets and standard MIRU-15 for each lineage under investigation. Twelve loci were shared between the customised Lineage 4 set and standard MIRU-15, addition of the remaining 4 non-shared loci from standard MIRU-15 gave a total of 16 loci for analysis. For Lineage 5, addition of 6 non-shared loci to the 9 shared loci gave a total of 17 loci. Subsequently, we calculated individual locus HGDI. The results obtained were arranged in a descending order. Starting with the highest HGDI, cumulative HGDI was then calculated by successively adding one locus after the other. Finally, the clustering rate was calculated in a similar manner by successively adding one locus after the other. The result (cumulative HGDI and percentage clustering) obtained for each lineage was plotted on a graph and the cut-off point for selection of the minimal set of loci was set at where graph plateaued meaning further addition of loci resulted in the same cumulative HGDI. The customized minimal loci-set was then extracted from the graph.
Results
MTBC Isolates and Lineage Determination
All 178 isolates included in this study were classified into Lineage 4 (N = 126) or Lineage 5 (N = 52) based on the RD and SNP typing analysis [31], [35]. Discordant samples were excluded from the study. A full set of MIRU allelic data was obtained for 158/178 (88.8%), comprising 106 Lineage 4 and 52 Lineage 5 isolates, respectively. The remaining 20 of the 178 (11.2%) isolates were excluded from the analysis for various reasons. 90% (18/20) of excluded isolates had no PCR amplicon at one or several loci whilst the remaining 10% (2/20) had double alleles at one or more MIRU-VNTR loci, indicative of the possible presence of two independent strains [32].
Evaluation of Customized MIRU-12 for Lineage 4
One hundred and four distinct patterns (Table S1) comprising 102 singleton and 2 clusters (2 isolate per cluster) was obtained using customized MIRU-12 (clustering rate: 1.8%). Discriminatory power was calculated separately for each locus and classified into highly (HGDI ≥0.6), moderately (0.3 to 0.6), and poorly (<0.3) discriminatory based on the HGDI scores as previously reported [21]. Based on this definition, the discriminatory power of 10 loci (MIRU-VNTR loci 10, 40, 2163b, 2165, 3690, 4052, 4165 2401, 0424, and 0577) was higher than 0.6, supporting their designation as highly discriminatory loci with the remaining 2 MIRU/VNTR loci (VNTR 1955, and 23) being “moderately discriminatory”(DI: 0.3–0.59) (Table 2). Using the same set of isolates, standard MIRU-15 identified 105 distinct patterns with only one cluster of two isolates (clustering rate: 0.9%). Ten loci (66.6%; MIRU-VNTR loci 4052, 2163b, 40, 2165, 10, 4165, 3690, 2401, 26 and 0424) were highly discriminatory, 4 (26.6%) (VNTR 1955, 0577 and 23) moderately discriminatory and the remaining 1 (MIRU 4: 6.7%) poorly discriminated among the isolates.
Evaluation of Customized MIRU-12 for Lineage 5
Among 52 isolates analyzed, we obtained 51 unique patterns with 1 cluster (Table S1) comprising 2 isolates and a clustering rate of 0.9%. Five MIRU-VNTR loci (2163B, 4156, 4052, 40, 27) were highly discriminatory and the remaining 7 (23, 0577, 2165, 10, 0424, 31, 1955) being moderately discriminatory (Table 3). Standard MIRU-15 on the other hand identified 52 unique patterns. Six of the 15 loci (VNTR 2163B, 4156, 4052, 26, 16 and 40) had HGDI above 0.6 with the remaining nine MIRU-VNTR loci (0424, 10, 1955, 0577, 4, 2401, 3690, 2165 and 31) showing moderate discrimination (HGDI: 0.3–0.59).
Determination of a Minimal Set of MIRU-VNTR Loci for Genotyping Main MTBC Lineages from Ghana
Customized MIRU-12 for Lineage 4 shared 11 loci with standard MIRU-15 whilst 9 loci were shared between customized MIRU-12 for Lineage 5 and standard MIRU-15. A union of both sets of typing schemes gave a total of 16 and 17 loci for Lineage 4 and 5, respectively (Table S1). For Lineage 4, we identified six top most discriminatory loci (4052, 2163B, 40, 2165, 10 and 4165) with a cumulative HGDI of 0.99 (Table 2). Similarly, for Lineage 5, six loci: 2163B, 4165, 40, 26, 4052 and 16 (Table 3) with a cumulative HGDI of 0.99 were identified. Further addition of loci gave no significant change in cumulative HGDI values as shown in Figure 1. Note that 4 loci (4052, 2163B, 4162 and 40) were among the 6 most discriminatory in both lineage-specific sets. Hence, based on this, we propose the usage of a new set of customised typing system comprising 8 loci showing the highest discriminatory power for genotyping strains from the two most common lineages circulating in Ghana.
Individual and cumulative HGI was calculated for each locus and after successive loci addition respectively for all analysed loci using the mathematical formula as proposed by Hunter and Gaston (36). The black bars are the cumulative HGI values while crossed bars are for the individual locus values. Fig. 1a and 1b show values for lineage 4 and 5 respectively.
Discussion and Conclusion
Different combinations of MIRU and other VNTR loci have been proposed to complement the standard MIRU-15 scheme to achieve higher discrimination. Results accumulated from such studies clearly revealed that due to the strong phylogeographic structure exhibited by MTBC, the most relevant MIRU-VNTR typing schemes will likely differ depending on the specific geographical setting. For example, Shamputa et al. [18] successfully identified a reduced set of 8 loci from standard MIRU-24, which could be used to discriminate, isolates from the Republic of Korea. Similarly, Musare et al. [37], Dong et al. [38] and Zhou et al. [39] successfully defined a minimal set of 12 loci for genotyping Beijing strains which made up more than 90% of the isolates investigated from Asia. Most of the studies have been focused on Lineage 2 including the clinically important Beijing family based on its association with drug resistance [48]. However, no study has been carried out in most resource-limited settings like Ghana, where M. africanum is an important pathogen [27]–[28], [49]. If customized lineage-specific sets of MIRU-VNTR loci could be implemented in such settings, this will have an impact in terms of reducing work load and saving resources. In the present study, we evaluated such an approach for genotyping MTBC strains from Ghana, [27], [28] and compared our results with the current gold standard typing method; standard MIRU 15 as proposed by Supply et al. [34].
Although standard MIRU-15 showed higher discrimination in its ability to accurately identify clusters among these two lineages in our study when compared to customised lineage-specific MIRU-12 proposed previously [30], we found that not all the 15 loci were as informative for typing MTBC strains in Ghana. Even with the customized MIRU-12, based on our data, not all 12 loci were needed to achieve maximum discrimination (Figure 1). Specifically, our analysis showed that 10 of a total of 16 loci tested for Lineage 4 strains added no or only limited additional information in terms of discriminatory power. Similarly, 11 of a total of 17 loci screened for Lineage 5 strains showed limited discriminatory power. We thus explored the possibility of a minimal set of loci HGDI selected by combining the standard MIRU-15 and the customized MIRU-12 data set. Based on individual and cumulative HGDIs, and clustering rate, we defined the six top discriminatory loci for Lineage 4 (4052, 2163B, 40, 2165, 10 and 4165) (Figure 1a and 2a) and similarly for Lineage 5 (2163B, 4165, 40, 26, 4052 and 16) (Figure 1b and 2b) with 4 loci shared among the two sets (4052, 2163B, 40 and 4165). A combination of loci from Lineage 4 and 5 gave a unique customized set of 8 loci with HGDIs similar to that of standard MIRU-15.
Fig. 2a and b shows clustering rate values for lineages 4 and 5 respectively.
We now plan to apply these minimal MIRU-VNTR set for molecular epidemiological investigation of MTBC transmission in population based study in Ghana. We anticipate that this approach will save a significant amount of time. In addition we perform cost analysis on the different VNTR schemes analysed in this study. Cost was calculated based on the direct cost of reagents, materials and equipment. We compared the cost of genotyping using standard MIRU-15 and our proposed customized set of MIRU-8. With a unit cost of $11.24, the cost of performing standard MIRU-15 on one sample was $168.60, with the total material costs of analyses using our proposed customized MIRU-8 set for one sample being $89.2. Hence, by screening for only the relevant loci, we not only maximize discriminatory power but also minimize genotyping costs.
Currently, human-associated MTBC is known to comprise a total of seven main phylogenetic lineages [23], [46]–[47]. We propose that additional lineage-specific sets of MIRU-VNTR could be identified for molecular epidemiological investigation of TB transmission in resource-limited settings. Moreover, each MTBC lineage consists of a number of sub-lineages, some of which also show strong geographical associations [22, 24, and 45]. For example, the “Uganda” sub-lineage of Lineage 4 causes up to 60% of TB in Kampala, Uganda [41], suggesting that a similar customized Lineage 4 set for Uganda could be developed,which possibly would include other loci considering that most of Lineage 4 in Ghana consists of the “Cameroon” sub-lineage [42]–[44].
This study set out to define a set of loci for genotyping MTBC strains from Ghana. We acknowledge the high prevalence of M. africanum strains in Ghana, however, this prevalence is driven by Lineage 5 (M. africanum West Africa I) with limited number of Lineage 6 (M. africanum West Africa II). We acknowledge the fact that this makes our proposed customized MIRU-8 country-specific, and thus suggest that countries within West African where the high prevalence of M. africanum is driven by Lineage 6 (M. africanum West Africa II) could equally determine the minimal set of loci which gives the highest discrimination. Nevertheless, the strength of our study is the ability to genotype an unknown strain in Ghana with the proposed customized MIRU-8 loci in the most cost-efficient way.
In conclusion, this study identified a reduced set which can be applied for strain differentiation of the main MTBC lineages from Ghana.
Supporting Information
Table S1.
MIRU-VNTR Profiles of the Mycobacterial Isolates Analysed.
https://doi.org/10.1371/journal.pone.0092675.s001
(XLS)
Author Contributions
Conceived and designed the experiments: DYM SG. Performed the experiments: AAP SB MSN. Analyzed the data: AAP DYM SB MSN IC. Wrote the paper: AAP DYM SG.
References
- 1.
Global Tuberculosis report (2013) World Health Organization.
- 2. Guidelines for the Clinical Management of TB, HIV co-Infection in Ghana (2007)
- 3. Ghana health service report (2011)
- 4.
Mathema B, Kurepina NE, Bifani PJ, Kreiswirth BN (2006) Molecular Epidemiology of Tuberculosis: Current Insights. Clin Microbiol reviews. 19(4). p. 658–685.
- 5. Kato-Maeda M, Small PM (2000) How molecular epidemiology has changed what we know about tuberculosis. West J. Med. 172: 256–259.
- 6. Kan B, Berggren I, Ghebremichael S, Bennet R, Bruchfeld J, et al. (2008) Extensive transmission of an isoniazid-resistant strain of Mycobacterium tuberculosis in Sweden. Int.J.Tuberc.Lung Dis 12: 199–204.
- 7. Kim SL, Bai GH, Lee H, Kim HJ, Lew WJ, et al. (2001) Transmission of Mycobacterium tuberculosis among school students in Korea. Int.J.Tuberc.Lung Dis. 5: 824–830.
- 8. van Embden JD, Cave MD, Crawford JT, Dale JW, Eiseenach BM, et al. (1993) Strain differentiation of Mycobacterium tuberculosis by DNA fingerprinting: recommendation for a standard methodology. J.Clin.Microbiol. 31: 406–409.
- 9. Cowan LS, Mosher L, Diem L, Massey JP, Crawford JT (2002) Variable number tandem repeat typing of Mycobacterium tuberculosis isolates with low copy numbers of IS6110 by using mycobacterial interspersed repetitive units. J Clin Microbiol 40(5): 1592–1602.
- 10. Mokrousov I, Narvskaya O, Limeschenko E, Vyazovaya A, Otten T, et al. (2004) Analysis of the allelic diversity of the mycobacterial interspersed repetitive units in Mycobacterium tuberculosis strains of the Beijing family: practical implications and evolutionary considerations. J Clin Microbiol 42: 2438–2444.
- 11. Savine E, Warren RM, van der Spuy GD, Beyers N, van Helden PD, et al. (2002) Stability of variable-number tandem repeats of mycobacterial interspersed repetitive units from 12 loci in serial isolates of Mycobacterium tuberculosis. J Clin Microbiol 40(12): 4561–4566.
- 12. Sun YJ, Bellamy R, Lee AS, Ng ST, Ravindran S, et al. (2004) Use of mycobacterial interspersed repetitive unit-variable-number tandem repeat typing to examine genetic diversity of Mycobacterium tuberculosis in Singapore. J Clin Microbiol 42(5): 1986–1993.
- 13. Blackwood KS, Wolfe JN, Kabani AM (2004) Application of mycobacterial interspersed repetitive unit typing to Manitoba tuberculosis cases: can restriction fragment length polymorphisim be forgotten? J Clin Microbiol 42: 5001–6.
- 14. Mokrousov I, Narvskaya O, Limeschenko E, Vyazovaya A, Otten T, et al. (2004) Analysis of the Allelic Diversity of the Mycobacterial Interspersed Repetitive Units in Mycobacterium tuberculosis Strains of the Beijing Family: Practical Implications and Evolutionary Considerations. J. Clin. Microbiol 42: 2438–2444.
- 15. Yong-Jiang S, Bellamy R, Lee ASG, Sze Ta Ng, Ravindran S, et al. (2004) Use of Mycobacterial Interspersed Repetitive Unit–Variable-Number Tandem Repeat Typing To Examine Genetic Diversity of Mycobacterium tuberculosis in Singapore. J. Clin. Microbiol 42: 1986–1993.
- 16. Allix C, Walravens K, Saegerman C, Godfroid J, Supply P, et al. (2006) Evaluation of the epidemiological relevance of variable-number tandem-repeat genotyping of Mycobacterium bovis and comparison of the method with IS6110 restriction fragment length polymorphism analysis and spoligotyping. J Clin Microbiol 44: 1951–1962.
- 17. Barlow RE, Gascoyne-Binzi DM, Gillespie SH, Dickens A, Qamer S, et al. (2001) Comparison of variable number tandem repeat and IS6110-restriction fragment length polymorphism analyses for discrimination of high- and low-copy number IS6110 Mycobacterium tuberculosis.. J Clin Microbiol 50(10): 902–8.
- 18. Shamputa IC, Lee J, Allix-Beguec C, Cho E-J, Rajan V, et al. (2010) Genetic diversity of Mycobacterium tuberculosis isolates from tertiary care tuberculosis Hospital in South Korea. J Clin Microbiol 48(2): 387–394.
- 19. Supply P, Lesjean S, Savine E, Kremer K, van Soolingen D, et al. (2001) Automated high-throughput genotyping for study of global epidemiology of Mycobacterium tuberculosis based on mycobacterial interspersed repetitive units. J Clin Microbiol 39(10): 3563–3571.
- 20. Scott AN, Menzies D, Tannenbaum TN, Thibert L, Kozak R, et al. (2005) Sensitivities and specificities of spoligotyping and mycobacterial interspersed repetitive unit-variable- number tandem repeat typing methods for studying molecular epidemiology of tuberculosis. J Clin Microbiol 43(1): 89–94.
- 21. Cowan LS, Diem L, Monson T, Wand P, Temporado D, et al. (2005) Evaluation of a two-step approach for large scale, prospective genotyping of Mycobacterium tuberculosis isolates in the United States. J Clin Microbiol 43(2): 688–695.
- 22. Gagneux S, DeRiemer K, Van T, Kato-Maeda M, de Jong BC, et al. (2006) Variable host-pathogen Compatibility in Mycobacterium tuberculosis.. Proc Natl Acad Sci USA 103: 2869–2873.
- 23.
Coscolla M, Lewin A, Metzger S, Maetz-Rennsing K, Calvignac-Spencer S, et al.. (2013) Novel Mycobacterium tuberculosis Complex Isolate from a Wild Chimpanzee. Emerg Infect Dis. Jun; 19(6), 969–76.
- 24.
Gagneux S (2012) Host–pathogen coevolution in human tuberculosis Phil. Trans. R. Soc. B 367, 850–859.
- 25. Homolka S, Projahn M, Feuerriegel S, Ubben T, Diel R, et al. (2012) High Resolution Discrimination of Clinical Mycobacterium tuberculosis Complex Strains Based on Single Nucleotide Polymorphisms. PLoS ONE 7(7): e39855.
- 26. Gagneux S, Small PM (2007) Global phylogeography of Mycobacterium tuberculosis and implications for tuberculosis product development. Lancet Infect Dis 7: 328–337.
- 27. Yeboah-Manu D, Asante-Poku A, Bodmer T, Stucki D, Koram K, et al. (2011) Genotypic diversity and drug susceptibility patterns among M. tuberculosis complex isolates from South-Western Ghana. PLoS One 6(7): e21906
- 28. Addo K, Owusu-Darko K, Yeboah-Manu D, Caulley P, Minamikawa M, et al. (2007) Mycobacterial species causing pulmonary tuberculosis at the Korle bu teaching hospital, Accra, Ghana. Ghana Medical Journal 41(2): 52–7.
- 29. Kremer K, Au BK, Yip PC, Skuce R, Supply P, et al. (2005) Use of variable number tandem repeat typing to differentiate Mycobacterium tuberculosis Beijing family isolates from Hong Kong and comparison with IS6110 restriction fragment length polymorphism typing and spoligotyping. J Clin Microbiol 43: 314–320.
- 30. Comas I, Homolka S, Niemann S, Gagneux S (2009) Genotyping of Genetically Monomorphic Bacteria: DNA Sequencing in Mycobacterium tuberculosis. Highlights the Limitations of Current Methodologies. PLoS ONE 4(11): e7815
- 31.
Brosch R, Gordon SV, Marmiesse M, Brodin P, Buchrieser C, et al.. (2002) A new evolutionary scenario for the Mycobacterium tuberculosis complex. Proc Natl Acad Sci U S A 99, 3684–3689.
- 32. Yesilkaya H, Meacci F, Niemann S, Hillemann D, Rüsch-Gerdes S, et al. (2006) Evaluation of molecular-beacon, TaqMan, and fluorescence resonance energy transfer probes for detection of antibiotic resistance-conferring single nucleotide polymorphisms in mixed Mycobacterium tuberculosis DNA extracts. J Clin Microbiol 44: 3826–3829
- 33. Abadia E, Zhang J, Ritacco V, Kremer K, Ruimy R, et al. (2011) The use of microbead-based spoligotyping for Mycobacterium tuberculosis complex to evaluate the quality of the conventional method: Providing guidelines for Quality Assurance when working on membranes. BMC Infectious Diseases. 11: 110.
- 34.
Supply P, Allix C, Lesjean S, Cardoso-Oelemann M, Rusch-Gerdes S, et al.. (2006) Proposal for Standardization of Optimized Mycobacterial Interspersed Repetitive Unit–Variable-Number Tandem Repeat Typing of Mycobacterium tuberculosis. J. Clin. Microbiol. 4498–4510.
- 35. Stucki D, Malla B, Hostettler S, Huna T, Feldmann J, et al. (2012) Two new rapid SNP-typing methods for classifying Mycobacterium tuberculosis complex into the main phylogenetic lineages. PLoS One. 7(7): e41253.
- 36. Hunter PR, Gaston MA (1988) Numerical Index of the Discriminatory Ability of Typing Systems: an Application of Simpson’s Index of Diversity. J. Clin. Microbiol 26: 2465–2466.
- 37. Murase Y, Mitari S, Sugawara I, Kato S, Maeda S (2008) Promising loci of variable number of tandem repeats for typing Beijing family Mycobacterium tuberculosis. J. Med. Microbiol. 57: 873–880.
- 38.
Dong H, Shi L, Zhao X, BaSang, Lv B, et al.. (2012) Genetic diversity of Mycobacterium tuberculosis isolates from Tibetans in Tibet, China. PLos One 7 (3).
- 39. Zhou A, Nawaz M, Xue X, Karakousis PC, Yao Y, et al. (2011) Molecular genotyping of Mycobacterium tuberculosis in Xi’an,China using MIRU-VNTR typing. Int J Tuberc Lung Dis 15(4): 517–522.
- 40. Yeboah-Manu D, Yates MD, Stuart MW (2001) Application of a simple multiplex polymerase chain reaction to aid in the routine work of the mycobacterium reference laboratory. J Clin Microbiol 39: 4166–4168.
- 41. Wampande EM, Mupere E, Debanne SM, Asiimwe BA, Nsereko M, et al. (2013) Long-term dominance of Mycobacterium tuberculosis Uganda family in peri-urban Kampala-Uganda is not associated with cavitary disease. BMC Infectious Diseases 13: 484.
- 42. Niobe-Eyangoh S, Kuaban C, Sorlin P, Cunin P, Thonnon J, et al. (2003) Genetic Biodiversity of Mycobacterium tuberculosis complex strains from patients with pulmonary tuberculosis in Cameroon. J Clin Microbiol 41: 2547–2553.
- 43. Assam Assam JP, Penlap VB, Cho-Ngwa F, Tedom JC, Anyangwe I, et al. (2011) Mycobacterium tuberculosis complex drug resistance pattern and identification of species causing TB in the west and centre regions of Cameroon. BMC Infect Dis 11: 94.
- 44. Assam Assam, Penlap Beng E, Cho-Ngwa F, Toukam V, Ngoh A-A, et al. (2013) Mycobacterium tuberculosis is the causative agent of tuberculosis in the southern ecological zones of Cameroon, as shown by genetic analysis. BMC Infectious Diseases 13: 431.
- 45. Reed MB, Pichler VK, McIntosh F, Mattia A, Fallow A, et al. (2009) Major Mycobacterium tuberculosis Lineages Associate with Patient Country of Origin. J. Clin. Microbiol 47: 1119–1128.
- 46. Comas I, Coscolla M, Luo T, Borrell S, Holt KE, et al. (2013) Out-of-Africa migration and Neolithic coexpansion of Mycobacterium tuberculosis with modern humans. Nat Genet. Oct;45 (10): 1176–82.
- 47. Firdessa R, Berg S, Hailu E, Schelling E, Gumi B, et al. (2013) A Mycobacterial lineages causing pulmonary and extrapulmonary tuberculosis, Ethiopia. Emerg Infect Dis. Mar; 19 (3): 460–3.
- 48. Borrell S, Gagneux S (2009) Infectiousness, reproductive fitness and evolution of drug-resistant Mycobacterium tuberculosis. Int J Tuberc Lung Dis 13(12): 1456–66.
- 49. Goyal M, Lawn S, Afful B, Acheampong JW, Griffin G, et al. (1999) Spoligotyping in molecular epidemiology of tuberculosis in Ghana. J Infect; 38 (3): 171–5.