High-Throughput Screen for Cell Wall Synthesis Network Module in Mycobacterium tuberculosis Based on Integrated Bioinformatics Strategy

被引:3
|
作者
Luo, Xizi [1 ]
Pan, Jiahui [1 ]
Meng, Qingyu [1 ]
Huang, Juanjuan [1 ]
Wang, Wenfang [1 ]
Zhang, Nan [2 ]
Wang, Guoqing [1 ]
机构
[1] Jilin Univ, Dept Pathogenobiol, Coll Basic Med Sci, Key Lab Zoonosis,Chinese Minist Educ, Changchun, Peoples R China
[2] Jilin Univ, Coll Math, Changchun, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Mycobacterium tuberculosis; cell wall; module; regulatory networks; enrichment analysis;
D O I
10.3389/fbioe.2020.00607
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: Mycobacterium tuberculosis is one of the deadliest pathogens in humans. Co-infection of M. tuberculosis with HIV and the emergence of multi-drug-resistant tuberculosis (TB) constitute a serious global threat. However, no effective anti-TB drugs are available, with the exception of first-line drugs such as isoniazid. The cell wall of M. tuberculosis, which is primarily responsible for the lack of effective antiTB drugs and the escape of the bacteria from host immunity, is an important drug target. The core components of the cell wall of M. tuberculosis are peptidoglycan, arabinogalactan, and mycotic acid. However, the functional genome and metabolic regulation pathways for the M. tuberculosis cell wall are still unknown. In this study, we used the biclustering algorithm integrated into cMonkey, sequence alignment, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and other bioinformatics methods to scan the whole genome of M. tuberculosis as well as to identify and statistically analyze the genes related to the synthesis of the M. tuberculosis cell wall. Method: We performed high-throughput genome-wide screening for M. tuberculosis using Biocarta, KEGG, National Cancer Institute Pathway Interaction Database (NCIPID), HumanCyc, and Reactome. We then used the Database of Origin and Registration (DOOR) established in our laboratory to classify the collection of operons for M. tuberculosis cell wall synthetic genes. We used the cMonkey double clustering algorithm to perform clustering analysis on the gene expression profile of M. tuberculosis for cell wall synthesis. Finally, we visualized the results using Cytoscape. Result and Conclusion: Through bioinformatics and statistical analyses, we identified 893 M. tuberculosis H37Rv cell wall synthesis genes, distributed in 20 pathways, involved in 46 different functions related to cell wall synthesis, and clustered in 386 modules. We identified important pivotal genes and proteins in the cell wall synthesis pathway such as murA, a class of operons containing genes involved in cell wall synthesis such as ID6951, and a class of operons indispensable for the survival of the bacteria. In addition, we found 41 co-regulatory modules for cell wall synthesis and five co-expression networks of molecular complexes involved in peptidoglycan biosynthesis, membrane transporter synthesis, and other cell wall processes.
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页数:11
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