A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis
2008

Studying Gene Responses of Mycobacterium tuberculosis to Low Oxygen

Sample size: 42 publication Evidence: moderate

Author Information

Author(s): Zhang Yi, Hatch Kim A, Wernisch Lorenz, Bacon Joanna

Primary Institution: School of Crystallography, Birkbeck College, University of London

Hypothesis

Is the induction of the DosR regulon in Mycobacterium tuberculosis a synchronous event or a cascade of events triggered by different oxygen levels?

Conclusion

The study found that most dosR-dependent genes are up-regulated at very low oxygen levels, but some respond to higher oxygen levels, indicating a complex regulatory response.

Supporting Evidence

  • The study used a novel Bayesian change point analysis to detect shifts in gene expression.
  • It confirmed that most dosR-dependent genes are triggered by very low oxygen levels.
  • Some genes were found to respond to higher oxygen levels, indicating a more complex regulation.

Takeaway

This study looked at how a bacteria called Mycobacterium tuberculosis reacts to low oxygen. It found that some of its genes turn on quickly when oxygen drops, while others take longer.

Methodology

The researchers used chemostat cultures to control oxygen levels and applied a Bayesian change point analysis to study gene expression over time.

Limitations

The study is based on a single time course experiment, which may not capture all regulatory dynamics.

Digital Object Identifier (DOI)

10.1186/1471-2164-9-87

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