I have 10 myobacterium tuberulosis samples and I will do a spoligotyping experiment, but I want to know how I can interpret these results and is there any technique which could be used instead of spoligotyping?
In addition to the comprehensive response by Sabrina Rodriguez-Campos, the spoligotyping data show to what extent your strains are related to each other and to previously isolated strains from various regions of the world, and what is the approximate evolutionary distance between the strains. Strains with the same spoligotype may have a common source of infection, though in this case the identity should be confirmed with more detailed genotyping technique, e.g., RFLP IS6110. Strains with different spoligotypes originate from different patients, as the cases when two or more different strains are isolated from the same patient are extremely rare. Ideally, if you have detailed genotypes of all strains from all patients, along with patients' personal data, you can figure out who infected whom and when.
Well, just 10 isolates of Mycobacterium tuberculosis complex (MTBC) is a small number, that could be easily studied by various methods available today for molecular typing. However, seeing such a small number of your study sample, it might be a good idea to see how they fit in within the global MTBC diversity. Thus you will need typing methods that allow you to compare your strains with a global collection, thanks to international genotyping databases.
Among various methods available today to study Mycobacterium tuberculosis complex (MTBC) genotypic polymorphism, both spoligotyping and mycobacterial interspersed repetitive units-variable number of DNA tandem repeats (MIRU-VNTRs) have gained international approval as robust, fast, and reproducible typing methods generating data in a portable format. Although spoligotyping is particularly useful to assign well-defined genotypic lineages to MTBC strains, it is known to overestimate clustering, and should be ideally followed by MIRU-VNTRs for high-resolution epidemiological studies. Hence I would suggest that you use both these methods in conjunction.
Once you have your results, you could use the SITVITWEB database released in 2012 to interpret your data. It is available at: http://www.pasteur-guadeloupe.fr:8081/SITVIT_ONLINE/ ; and contains multimarker data (spoligotyping, and 12-loci MIRUs) allowing to have a global vision of MTC genetic diversity based on 62,582 MTBC clinical isolates corresponding to 153 countries of patient origin (105 countries of isolation). This database allows to assign a specific "Spoligotype International Type" (SIT) designation for a given spoligotype pattern shared by 2 or more strains, and a "MIRU International Type" (MIT) number for a shared MIRU pattern.
Note that an upcoming database to be released by the same group in late 2014/early 2015 (tentatively named SITVIT2) will contain data on almost 112,000 MTBC clinical isolates from 169 countries of patient origin. It will also have data on 15-loci and 24-loci MIRUs.
Another useful database is MIRU-VNTRplus web application available at: http://www.miru-vntrplus.org/MIRU/index.faces ; it provides detailed genotyping data on a collection of 186 strains representing the major MTBC lineages with data on 24 MIRU loci, spoligotyping patterns, regions of difference (RD), single nucleotide polymorphisms (SNPs), IS6110 RFLP fingerprints. The integrated nomenclature server allows to generate an international nomenclature (MLVA MtbC15-9) to name different MIRU genotypes.
If you visit these databases, they will also lead you to suggested reading that might be particularly helpful to better comprehend the current strategy in MTBC molecular typing.
I agree with the answers of Nalin Rastogi and Sabrina Rodriguez-Campos. They are experts in spoligityping
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