A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis
<p>Abstract</p> <p>Background</p> <p>Low oxygen availability has been shown previously to stimulate <it>M. tuberculosis </it>to establish non-replicative persistence <it>in vitro</it>. The two component sensor/regulator <it>dosRS </it>...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2008-02-01
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| Series: | BMC Genomics |
| Online Access: | http://www.biomedcentral.com/1471-2164/9/87 |
| _version_ | 1818757176531877888 |
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| author | Wernisch Lorenz Hatch Kim A Zhang Yi Bacon Joanna |
| author_facet | Wernisch Lorenz Hatch Kim A Zhang Yi Bacon Joanna |
| author_sort | Wernisch Lorenz |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>Low oxygen availability has been shown previously to stimulate <it>M. tuberculosis </it>to establish non-replicative persistence <it>in vitro</it>. The two component sensor/regulator <it>dosRS </it>is a major mediator in the transcriptional response of <it>M. tuberculosis </it>to hypoxia and controls a regulon of approximately 50 genes that are induced under this condition.</p> <p>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.</p> <p>Results</p> <p>A novel aspect of our work is the use of chemostat cultures of <it>M. tuberculosis </it>which allowed us to control environmental conditions very tightly. We exposed <it>M. tuberculosis </it>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.</p> <p>Conclusion</p> <p>The majority of the <it>dosR</it>-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.</p> |
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| format | Article |
| id | doaj.art-3802a7529f794812929a940b0ec16b12 |
| institution | Directory Open Access Journal |
| issn | 1471-2164 |
| language | English |
| last_indexed | 2024-12-18T06:06:47Z |
| publishDate | 2008-02-01 |
| publisher | BMC |
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| series | BMC Genomics |
| spelling | doaj.art-3802a7529f794812929a940b0ec16b122022-12-21T21:18:31ZengBMCBMC Genomics1471-21642008-02-01918710.1186/1471-2164-9-87A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosisWernisch LorenzHatch Kim AZhang YiBacon Joanna<p>Abstract</p> <p>Background</p> <p>Low oxygen availability has been shown previously to stimulate <it>M. tuberculosis </it>to establish non-replicative persistence <it>in vitro</it>. The two component sensor/regulator <it>dosRS </it>is a major mediator in the transcriptional response of <it>M. tuberculosis </it>to hypoxia and controls a regulon of approximately 50 genes that are induced under this condition.</p> <p>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.</p> <p>Results</p> <p>A novel aspect of our work is the use of chemostat cultures of <it>M. tuberculosis </it>which allowed us to control environmental conditions very tightly. We exposed <it>M. tuberculosis </it>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.</p> <p>Conclusion</p> <p>The majority of the <it>dosR</it>-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.</p>http://www.biomedcentral.com/1471-2164/9/87 |
| spellingShingle | Wernisch Lorenz Hatch Kim A Zhang Yi Bacon Joanna A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis BMC Genomics |
| title | A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis |
| title_full | A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis |
| title_fullStr | A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis |
| title_full_unstemmed | A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis |
| title_short | A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis |
| title_sort | bayesian change point model for differential gene expression patterns of the dosr regulon of mycobacterium tuberculosis |
| url | http://www.biomedcentral.com/1471-2164/9/87 |
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