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Bioinformatics Identification of Drug Resistance-Associated Gene Pairs in Mycobacterium tuberculosis

View Article: PubMed Central - PubMed

ABSTRACT

Tuberculosis is a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb). Due to the extensive use of anti-tuberculosis drugs and the development of mutations, the emergence and spread of multidrug-resistant tuberculosis is recognized as one of the most dangerous threats to global tuberculosis control. Some single mutations have been identified to be significantly linked with drug resistance. However, the prior research did not take gene-gene interactions into account, and the emergence of transmissible drug resistance is connected with multiple genetic mutations. In this study we use the bioinformatics software GBOOST (The Hong Kong University, Clear Water Bay, Kowloon, Hong Kong, China) to calculate the interactions of Single Nucleotide Polymorphism (SNP) pairs and identify gene pairs associated with drug resistance. A large part of the non-synonymous mutations in the drug target genes that were included in the screened gene pairs were confirmed by previous reports, which lent sound solid credits to the effectiveness of our method. Notably, most of the identified gene pairs containing drug targets also comprise Pro-Pro-Glu (PPE) family proteins, suggesting that PPE family proteins play important roles in the drug resistance of Mtb. Therefore, this study provides deeper insights into the mechanisms underlying anti-tuberculosis drug resistance, and the present method is useful for exploring the drug resistance mechanisms for other microorganisms.

No MeSH data available.


The workflow of the method used in this study.
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ijms-17-01417-f003: The workflow of the method used in this study.

Mentions: Taking into account that the mutation in a target gene is a key factor for drug resistance, the SNP pairs obtained by GBOOST were assigned to the corresponding genes. Subsequently the gene pairs that contained at least one target gene were screened for further analysis. We also used permutation tests to reduce the risk of false-positives (calculating 10,000 times in total). The results of the chi-square test can be further corrected using permutation tests (FDR < 0.005). The overall workflow of our method is presented as Figure 3.


Bioinformatics Identification of Drug Resistance-Associated Gene Pairs in Mycobacterium tuberculosis
The workflow of the method used in this study.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5037696&req=5

ijms-17-01417-f003: The workflow of the method used in this study.
Mentions: Taking into account that the mutation in a target gene is a key factor for drug resistance, the SNP pairs obtained by GBOOST were assigned to the corresponding genes. Subsequently the gene pairs that contained at least one target gene were screened for further analysis. We also used permutation tests to reduce the risk of false-positives (calculating 10,000 times in total). The results of the chi-square test can be further corrected using permutation tests (FDR < 0.005). The overall workflow of our method is presented as Figure 3.

View Article: PubMed Central - PubMed

ABSTRACT

Tuberculosis is a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb). Due to the extensive use of anti-tuberculosis drugs and the development of mutations, the emergence and spread of multidrug-resistant tuberculosis is recognized as one of the most dangerous threats to global tuberculosis control. Some single mutations have been identified to be significantly linked with drug resistance. However, the prior research did not take gene-gene interactions into account, and the emergence of transmissible drug resistance is connected with multiple genetic mutations. In this study we use the bioinformatics software GBOOST (The Hong Kong University, Clear Water Bay, Kowloon, Hong Kong, China) to calculate the interactions of Single Nucleotide Polymorphism (SNP) pairs and identify gene pairs associated with drug resistance. A large part of the non-synonymous mutations in the drug target genes that were included in the screened gene pairs were confirmed by previous reports, which lent sound solid credits to the effectiveness of our method. Notably, most of the identified gene pairs containing drug targets also comprise Pro-Pro-Glu (PPE) family proteins, suggesting that PPE family proteins play important roles in the drug resistance of Mtb. Therefore, this study provides deeper insights into the mechanisms underlying anti-tuberculosis drug resistance, and the present method is useful for exploring the drug resistance mechanisms for other microorganisms.

No MeSH data available.