Systems biology analysis of a small bacterium

Acquiring and integrating large-scale, quantitative biological data is a common feature of Systems Biology studies. However, integrating these diverse data and providing additional functional understanding on how cells work and how central processes are regulated remain an important challenge for the field of Systems Biology. A plausible approach to gaining novel biological insights from large-scale data-sets lies in the combined application of these independently developed methodologies in a suitable model organism to the same biological sample, but under different growth and stress conditions. We use Mycoplasma pneumoniae, a human pathogenic bacterium causing atypical pneumonia as model system for our study. Containing a reduced genome with only 690 ORFs, this bacterium is an ideal organism for quantitative, systems-wide studies, avoiding technical limitations due to sample complexity. We report here the metabolimics, transcriptomics and proteomics analysis of this simple organism. Our data shows that even the simplest of the bacteria has a level of complexity that prevents its full quantitative understanding.

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