Dataset Information

Conditional gene expression in Mycobacterium abscessus.

ABSTRACT: Mycobacterium abscessus is an emerging human pathogen responsible for lung infections, skin and soft-tissue infections and disseminated infections in immunocompromised patients. It may exist either as a smooth (S) or rough (R) morphotype, the latter being associated with increased pathogenicity in various models. Genetic tools for homologous recombination and conditional gene expression are desperately needed to allow the study of M. abscessus virulence. However, descriptions of knock-out (KO) mutants in M. abscessus are rare, with only one KO mutant from an S strain described so far. Moreover, of the three major tools developed for homologous recombination in mycobacteria, only the one based on expression of phage recombinases is working. Several conditional gene expression tools have recently been engineered for Mycobacterium tuberculosis and Mycobacterium smegmatis, but none have been tested yet in M. abscessus. Based on previous experience with genetic tools allowing homologous recombination and their failure in M. abscessus, we evaluated the potential interest of a conditional gene expression approach using a system derived from the two repressors system, TetR/PipOFF. After several steps necessary to adapt TetR/PipOFF for M. abscessus, we have shown the efficiency of this system for conditional expression of an essential mycobacterial gene, fadD32. Inhibition of fadD32 was demonstrated for both the S and R isotypes, with marginally better efficiency for the R isotype. Conditional gene expression using the dedicated TetR/PipOFF system vectors developed here is effective in S and R M. abscessus, and may constitute an interesting approach for future genetic studies in this pathogen.

SUBMITTER: Cortes M

PROVIDER: S-EPMC3240655 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Conditional gene expression in Mycobacterium abscessus.

Cortes Mélanie M Singh Anil Kumar AK Reyrat Jean-Marc JM Gaillard Jean-Louis JL Nassif Xavier X Herrmann Jean-Louis JL

PloS one 20111215 12

Mycobacterium abscessus is an emerging human pathogen responsible for lung infections, skin and soft-tissue infections and disseminated infections in immunocompromised patients. It may exist either as a smooth (S) or rough (R) morphotype, the latter being associated with increased pathogenicity in various models. Genetic tools for homologous recombination and conditional gene expression are desperately needed to allow the study of M. abscessus virulence. However, descriptions of knock-out (KO) m ...[more]

PMID: 22195042

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Project description:BACKGROUND:Although many of the genic features in Mycobacterium abscessus have been fully validated, a comprehensive understanding of the regulatory elements remains lacking. Moreover, there is little understanding of how the organism regulates its transcriptomic profile, enabling cells to survive in hostile environments. Here, to computationally infer the gene regulatory network for Mycobacterium abscessus we propose a novel statistical computational modelling approach: BayesIan gene regulatory Networks inferreD via gene coExpression and compaRative genomics (BINDER). In tandem with derived experimental coexpression data, the property of genomic conservation is exploited to probabilistically infer a gene regulatory network in Mycobacterium abscessus.Inference on regulatory interactions is conducted by combining 'primary' and 'auxiliary' data strata. The data forming the primary and auxiliary strata are derived from RNA-seq experiments and sequence information in the primary organism Mycobacterium abscessus as well as ChIP-seq data extracted from a related proxy organism Mycobacterium tuberculosis. The primary and auxiliary data are combined in a hierarchical Bayesian framework, informing the apposite bivariate likelihood function and prior distributions respectively. The inferred relationships provide insight to regulon groupings in Mycobacterium abscessus. RESULTS:We implement BINDER on data relating to a collection of 167,280 regulator-target pairs resulting in the identification of 54 regulator-target pairs, across 5 transcription factors, for which there is strong probability of regulatory interaction. CONCLUSIONS:The inferred regulatory interactions provide insight to, and a valuable resource for further studies of, transcriptional control in Mycobacterium abscessus, and in the family of Mycobacteriaceae more generally. Further, the developed BINDER framework has broad applicability, useable in settings where computational inference of a gene regulatory network requires integration of data sources derived from both the primary organism of interest and from related proxy organisms.

Dataset Information

Conditional gene expression in Mycobacterium abscessus.

Publications

Conditional gene expression in Mycobacterium abscessus.

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