The transcriptional regulatory network of Mycobacterium tuberculosis

Under the perspectives of network science and systems biology, the characterization of transcriptional regulatory (TR) networks beyond the context of model organisms offers a versatile tool whose potential remains yet mainly unexplored. In this work, we present an updated version of the TR network o...

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Bibliographic Details
Published in:PloS one 2011-07, Vol.6 (7), p.e22178-e22178
Main Authors: Sanz, Joaquín, Navarro, Jorge, Arbués, Ainhoa, Martín, Carlos, Marijuán, Pedro C, Moreno, Yamir
Format: Article
Language:English
Subjects:
Analysis
Biology
Computer applications
Data collection
Dynamic models
E coli
Escherichia coli
Escherichia coli - genetics
Gene expression
Gene Expression Regulation, Bacterial
Gene Regulatory Networks - genetics
Genes
Genetic aspects
Genomes
Genomics
Infections
Mathematics
Medicine
Metabolism
Mycobacterium tuberculosis
Mycobacterium tuberculosis - genetics
Nucleotide Motifs - genetics
Pathogens
Physics
Proteins
Signaling
Simulation
Transcription
Transcription (Genetics)
Tuberculosis
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Summary:Under the perspectives of network science and systems biology, the characterization of transcriptional regulatory (TR) networks beyond the context of model organisms offers a versatile tool whose potential remains yet mainly unexplored. In this work, we present an updated version of the TR network of Mycobacterium tuberculosis (M.tb), which incorporates newly characterized transcriptional regulations coming from 31 recent, different experimental works available in the literature. As a result of the incorporation of these data, the new network doubles the size of previous data collections, incorporating more than a third of the entire genome of the bacterium. We also present an exhaustive topological analysis of the new assembled network, focusing on the statistical characterization of motifs significances and the comparison with other model organisms. The expanded M.tb transcriptional regulatory network, considering its volume and completeness, constitutes an important resource for diverse tasks such as dynamic modeling of gene expression and signaling processes, computational reliability determination or protein function prediction, being the latter of particular relevance, given that the function of only a small percent of the proteins of M.tb is known.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0022178