ArticleInternational journal of molecular sciences2016
Bioinformatics Identification of Drug Resistance-Associated Gene Pairs in Mycobacterium tuberculosis.
Article in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 28 citations in OpenAlex.
- An in silico approach for screening non-synonymous SNPs in Mycobacterium tuberculosis PPE68 protein and impact on structure.Scientific reports · 2025Article
- Ongoing evolution of PE/PPE genes inmSystems · 2025Article
- The PE/PPE family proteins ofFrontiers in immunology · 2025Review
- Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda.BMC infectious diseases · 2024Article
- MIDESP: Mutual Information-Based Detection of Epistatic SNP Pairs for Qualitative and Quantitative Phenotypes.Biology · 2021Article
- Bayesian reconstruction ofMicrobial genomics · 2020Article
- Whole genome sequencing, analyses of drug resistance-conferring mutations, and correlation with transmission of Mycobacterium tuberculosis carrying katG-S315T in Hanoi, Vietnam.Scientific reports · 2019Article
- Antibiotic resistance genes in the Actinobacteria phylum.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2019Review
- GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions.Nature communications · 2019Article
- A complete high-quality MinION nanopore assembly of an extensively drug-resistant Mycobacterium tuberculosis Beijing lineage strain identifies novel variation in repetitive PE/PPE gene regions.Microbial genomics · 2018Article
- Transferring knowledge of bacterial protein interaction networks to predict pathogen targeted human genes and immune signaling pathways: a case study on M. tuberculosis.BMC genomics · 2018Article
- Whole genome sequencing data of 1110 Mycobacterium tuberculosis isolates identifies insertions and deletions associated with drug resistance.BMC genomics · 2018Article
- Comparative Genome Analysis of 2Evolutionary bioinformatics online · 2018Article
- Clinical implication of novel drug resistance-conferring mutations in resistant tuberculosis.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2017Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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