Molecular Biology Reports

, Volume 41, Issue 9, pp 5883–5889 | Cite as

Genome-wide screening of pathogenicity islands in Mycobacterium tuberculosis based on the genomic barcode visualization



Mycobacterium tuberculosis (M. tuberculosis) is one of the most widely spread human pathogenic bacteria, and it frequently exchanges pathogenesis genes among its strains or with other pathogenic microbes. The purpose of this study was to screen the pathogenicity islands (PAIs) in M. tuberculosis using the genomic barcode visualization technique and to characterize the functions of the detected PAIs. By visually screening the barcode image of the M. tuberculosis chromosomes, three candidate PAIs were detected as MPI-1, MPI-2 and MPI-3, among which MPI-2 and MPI-3 were known to harbor pathogenesis genes, and MPI-1 represents a novel candidate. Based on the functional annotations of Pfam domains and GO categories, both MPI-2 and MPI-3 carry genes encoding PE/PPE family proteins, MPI-2 encodes the type VII secretion system, and MPI-3 encodes genes for mycolic acid synthesis in the cell wall. Some of these genes were already widely used in early diagnosis or treatment of M. tuberculosis. The novel candidate PAI MPI-1 encodes CRISPR-C as family proteins, which are known to be associated with persistent infection of M. tuberculosis. Our data represents a molecular basis and protocol for comprehensive annotating the pathogenic systems of M. tuberculosis, and will also facilitate the development of diagnosis and vaccination techniques of M. tuberculosis.


Mycobacterium tuberculosis Pathogenicity island Genomic barcode Diagnosis Vaccination 



This work was supported by National Natural Science Foundation of China (81101295 and 81071424), Specialized Research Fund for the Doctoral Program of Higher Education of China (20110061120093), China Postdoctoral Science Foundation (20110491311 and 2012T50304), Foundation of Jilin Provincial Health Department (2011Z049),Foundation of Jilin Provincial Science and Technology Department (20130522013JH), Norman Bethune Program of Jilin University (2012219). It was also supported in part by the Shenzhen Research Grant ZDSY20120617113021359, China 973 program (2011CB512003 and 2010CB732606-6) and NSFC 31000447. Computing resources were partly provided by the Dawning supercomputing clusters at SIAT CAS.

Supplementary material

11033_2014_3463_MOESM1_ESM.xls (984 kb)
Supplementary material 1 (XLS 984 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Norman Bethune Medical College of Jilin UniversityChangchunChina
  2. 2.Shenzhen Institutes of Advanced Technology, and Key Lab for Health InformaticsChinese Academy of SciencesShenzhenPeople’s Republic of China

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