Abstract

Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is ∼67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in ∼590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our reconstruction is able to serve as a valuable resource in additional analyses involving objects from multiple molecular -omes. For that purpose, RefRec is freely available in the Systems Biology Markup Language format.

Highlights

  • Systems biology aims at producing information about system level phenomena in cells

  • All the yeast related molecular species and interactions were obtained from the databases and integrated into a consistent and non-overlapping network reconstruction

  • Metabolites and protein complex assembly interactions were imported from single source databases (KEGG and IntAct, respectively) which prevented the contradictions in naming conventions

Read more

Summary

Introduction

Systems biology aims at producing information about system level phenomena in cells. knowledge about cellular components, their interactions, and their state in different conditions needs to be collected and integrated. Given the large amount of information produced by the advanced measurement technologies in life sciences, it is noteworthy that no network reconstruction integrates the information globally and consistently, even not for the common model organism yeast (Saccharomyces cerevisiae). Exploring data from any single molecular -ome alone (such as genome or proteome) only enables restricted systems understanding. A more holistic view can be obtained through extensive integration of molecular species and interactions related to multiple -omes. These kinds of integrative reconstructions of global cellular networks find many applications, for example, in the building of predictive models of cellular phenomena and in the description of measurement data in the context of a system. Network reconstructions which are general enough and not tailored for any specific purpose, can be re-used in various studies

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call