Metabolic Flux-Based Modularity using Shortest Retroactive distances

BMC Systems Biology

Kyongbum Lee²  Soha Hassoun¹  Michael Yi²  Gautham Vivek Sridharan² 

[1] Department of Computer Science, Tufts University, Medford, MA, USA;Department of Chemical and Biological Engineering, Tufts University, 4 Colby Street, Room 150, Medford MA 02155, USA

关键词: Retroactivity;    Adipocyte metabolism;    Edge-weighting;    Metabolic flux;    Metabolic networks;    Modularity;   

Others  :  1143336
DOI  :  10.1186/1752-0509-6-155

 received in 2012-08-06, accepted in 2012-11-27,  发布年份 2012

【 摘 要 】

Background

Graph-based modularity analysis has emerged as an important tool to study the functional organization of biological networks. However, few methods are available to study state-dependent changes in network modularity using biological activity data. We develop a weighting scheme, based on metabolic flux data, to adjust the interaction distances in a reaction-centric graph model of a metabolic network. The weighting scheme was combined with a hierarchical module assignment algorithm featuring the preservation of metabolic cycles to examine the effects of cellular differentiation and enzyme inhibitions on the functional organization of adipocyte metabolism.

Results

Our analysis found that the differences between various metabolic states primarily involved the assignment of two specific reactions in fatty acid synthesis and glycerogenesis. Our analysis also identified cyclical interactions between reactions that are robust with respect to metabolic state, suggesting possible co-regulation. Comparisons based on cyclical interaction distances between reaction pairs suggest that the modular organization of adipocyte metabolism is stable with respect to the inhibition of an enzyme, whereas a major physiological change such as cellular differentiation leads to a more substantial reorganization.

Conclusion

Taken together, our results support the notion that network modularity is influenced by both the connectivity of the network’s components as well as the relative engagements of the connections.

【 授权许可】

   
2012 Sridharan et al.; licensee BioMed Central Ltd.

【 图 表 】

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