Reconstruction and topological characterization of the sigma factor regulatory network of Mycobacterium tuberculosis

被引:49
|
作者
Chauhan, Rinki [1 ]
Ravi, Janani [1 ]
Datta, Pratik [1 ]
Chen, Tianlong [2 ,3 ]
Schnappinger, Dirk [4 ]
Bassler, Kevin E. [2 ,3 ,5 ]
Balazsi, Gabor [6 ,7 ]
Gennaro, Maria Laura [1 ]
机构
[1] Rutgers State Univ, New Jersey Med Sch, Publ Hlth Res Inst, Newark, NJ 07103 USA
[2] Univ Houston, Dept Phys, Houston, TX 77204 USA
[3] Univ Houston, Texas Ctr Superconduct, Houston, TX 77204 USA
[4] Weill Cornell Med Coll, Dept Microbiol & Immunol, New York, NY 10021 USA
[5] Max Planck Inst Phys Komplexer, Nothnitzer Str 38, D-01187 Dresden, Germany
[6] SUNY Stony Brook, Laufer Ctr Phys & Quantitat Biol, Stony Brook, NY 11794 USA
[7] SUNY Stony Brook, Dept Biomed Engn, Stony Brook, NY 11794 USA
基金
美国国家科学基金会;
关键词
GENERAL STRESS-RESPONSE; COMMUNITY STRUCTURE; POSTTRANSLATIONAL REGULATION; BACILLUS-SUBTILIS; STATIONARY-PHASE; IDENTIFICATION; EXPRESSION; ORGANIZATION; RECOGNITION; HIERARCHY;
D O I
10.1038/ncomms11062
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Accessory sigma factors, which reprogram RNA polymerase to transcribe specific gene sets, activate bacterial adaptive responses to noxious environments. Here we reconstruct the complete sigma factor regulatory network of the human pathogen Mycobacterium tuberculosis by an integrated approach. The approach combines identification of direct regulatory interactions between M. tuberculosis sigma factors in an E. coli model system, validation of selected links in M. tuberculosis, and extensive literature review. The resulting network comprises 41 direct interactions among all 13 sigma factors. Analysis of network topology reveals (i) a three-tiered hierarchy initiating at master regulators, (ii) high connectivity and (iii) distinct communities containing multiple sigma factors. These topological features are likely associated with multi-layer signal processing and specialized stress responses involving multiple sigma factors. Moreover, the identification of overrepresented network motifs, such as autoregulation and coregulation of sigma and anti-sigma factor pairs, provides structural information that is relevant for studies of network dynamics.
引用
收藏
页数:12
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