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A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis

BACKGROUND: Low oxygen availability has been shown previously to stimulate M. tuberculosis to establish non-replicative persistence in vitro. The two component sensor/regulator dosRS is a major mediator in the transcriptional response of M. tuberculosis to hypoxia and controls a regulon of approxima...

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Detalles Bibliográficos
Autores principales: Zhang, Yi, Hatch, Kim A, Wernisch, Lorenz, Bacon, Joanna
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2275270/
https://www.ncbi.nlm.nih.gov/pubmed/18294384
http://dx.doi.org/10.1186/1471-2164-9-87
Descripción
Sumario:BACKGROUND: Low oxygen availability has been shown previously to stimulate M. tuberculosis to establish non-replicative persistence in vitro. The two component sensor/regulator dosRS is a major mediator in the transcriptional response of M. tuberculosis to hypoxia and controls a regulon of approximately 50 genes that are induced under this condition. The aim of this study was to determine whether the induction of the entire DosR regulon is triggered as a synchronous event or if induction can unfold as a cascade of events as the differential expression of subsets of genes is stimulated by different oxygen availabilities. RESULTS: A novel aspect of our work is the use of chemostat cultures of M. tuberculosis which allowed us to control environmental conditions very tightly. We exposed M. tuberculosis to a sudden drop in oxygen availability in chemostat culture and studied the transcriptional response of the organism during the transition from a high oxygen level (10% dissolved oxygen tension or DOT) to a low oxygen level (0.2% DOT) using DNA microarrays. We developed a Bayesian change point analysis method that enabled us to detect subtle shifts in the timing of gene induction. It results in probabilities of a change in gene expression at certain time points. A computational analysis of potential binding sites upstream of the DosR-controlled genes shows how the transcriptional responses of these genes are influenced by the affinity of these binding sites to DosR. Our study also indicates that a subgroup of DosR-controlled genes is regulated indirectly. CONCLUSION: The majority of the dosR-dependent genes were up-regulated at 0.2% DOT, which confirms previous findings that these genes are triggered by hypoxic environments. However, our change point analysis also highlights genes which were up-regulated earlier at levels of about 8% DOT indicating that they respond to small fluctuations in oxygen availability. Our analysis shows that there are pairs of divergent genes where one gene in the pair is up-regulated before the other, presumably for a flexible response to a constantly changing environment in the host.