DocumentCode
2341280
Title
Bioinformatics Analysis of Mycobacterium Tuberculosis Gene rspL and Its Mutation
Author
Chen, Gao ; Wu Yanlong ; Xiao, Shijun ; Li Canghai
Author_Institution
Sch. of Life Sci., Hubei Univ., Wuhan, China
fYear
2010
fDate
23-25 April 2010
Firstpage
1
Lastpage
4
Abstract
The emergence and spread of multidrug-resistant strains of Mycobacterium tuberculosis represent an increasing public health problem. Understanding multidrug-resistant mechanism(s) is essential for efficient treatment and control of tuberculosis. Mutations in gene rpsL, encoding the ribosomal protein S12, are responsible for most of the high-level Streptomycin resistance in Mycobacterium tuberculosis. Recently, a mass of data about gene rpsL continue to accumulate rapidly, but it is lack for systemic analysis using these data. Here, we used bioinformatics tools to analyze globe data about the rpsL of Mycobacterium tuberculosis. Phylogenetic analysis showed that the rpsL and its homologs were clearly divided into three groups, but they are all from organisms known as tuberculosis pathogens, which implied that general conformational structure of the rpsL did not change. Structure analysis showed that the 43 region of the rpsL alter hydrophilic nature in the wild-type rpsL to hydrophobic nature in the mutation. Prediction of the secondary structure of ribosomal protein S12 displayed a coil within the helix structure of the 43 region in the wild-type rpsL whereas just helix structure in the mutation. Therefore, it was suggested that mutations of hydrophilic nature and coil within the helix structure of the 43 region of gene rpsL are responsible for most of the high-level Streptomycin resistance in Mycobacterium tuberculosis.
Keywords
bioinformatics; data analysis; diseases; patient treatment; bioinformatics analysis; data systemic analysis; helix structure; high-level streptomycin resistance; multidrug-resistant mechanism; mycobacterium tuberculosis gene rspL; phylogenetic analysis; public health problem; ribosomal protein S12 encoding; tuberculosis treatment; Bioinformatics; Capacitive sensors; Coils; Data analysis; Encoding; Genetic mutations; Immune system; Phylogeny; Proteins; Public healthcare;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5315-3
Type
conf
DOI
10.1109/ICBECS.2010.5462484
Filename
5462484
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