Dissecting the energy metabolism in Mycoplasma pneumoniae through genome‐scale metabolic modeling

Abstract Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterize...

Full description

Saved in:
Bibliographic Details
Main Authors: Judith A H Wodke, Jacek Puchałka, Maria Lluch‐Senar, Josep Marcos, Eva Yus, Miguel Godinho, Ricardo Gutiérrez‐Gallego, Vitor A P Martins dos Santos, Luis Serrano, Edda Klipp, Tobias Maier
Format: Article
Language:English
Published: Springer Nature 2013-04-01
Series:Molecular Systems Biology
Subjects:
Online Access:https://doi.org/10.1038/msb.2013.6
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint‐based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time‐dependent changes, albeit using a static model. By performing an in silico knock‐out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.
ISSN:1744-4292