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Detection And Differentiate Beijing Family Isolates Of Mycobacterium Tuberculosis And Its Applications

Posted on:2010-06-27Degree:MasterType:Thesis
Country:ChinaCandidate:J ChenFull Text:PDF
GTID:2144360275491938Subject:Pathogen Biology
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Tuberculosis is still a major health threat globally,and china is one of the 22 high-burden conutries for TB disease with the seconde highest infected TB patients in the world.Traditional contact investigaion is limited for tracking Mycobacterial tuberculosis, due to the long latent period of Mycobacterium tuberculosis.Since 1990s,molecular biology technologies,which have been used for differentiating distinct Mycobacterium tuberculosis,conbined with traditional contact investigation become useful tools for interpretation the transmission of Mycobacterium tuberculosis and guide tuberculosis-control strategies.In china,molecular epidemiology research just begins to carry out and few reports about molecular epidemiology of tuberculosis on the base of population exist.The present study 1) evaluate the relationship between RD105 distribution in Beijing family strains and establish a simply and quick method to detect the Beijing family strains in Mycobacterium tuberculosis.2)search for VNTR loci that have been used for Mycobacterium tuberculosis genotyping in the published study and evaluate their discriminations,therefore,we develop a set of VNTR loci,whose discriminatory power is comparable to that of IS6110 RFLP,for differentiating Beijing strains in other provinces in China.3) investigate the mixed infection of Mycobacterium tuberculosis in shanghai using new established VNTR typing methods.What we focused on is mixed infections of Mycobacterium tuberculosis.We find out that the strains form the same patient who received tuberculosis and extra-pulmonary tuberculosis at the same time mostly share the same genotypes,which gave a new sight on the infection and propagation of Mycobacterium tuberculosis.
Keywords/Search Tags:M. tuberculosis, Beijing genotype strain, RD105, VNTR, mixed infection
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