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a probabilistic functional gene network for Escherichia coli, which is an intensively studied species of bacteria, due to its utility in both exploring the molecular mechanisms underlying fundamental biological processes and manufacturing useful metabolites for the biomedical industry. Numerous techniques for molecular genetics have been developed in E. coli over the past several decades, making it the standard bacterial species for studying genetics and the molecular mechanisms underlying cellular phenotypes. This attention has led to the elucidation of many conserved metabolic pathways in E. coli, resulting in its use as a metabolic engineering platform. Despite its importance in science and engineering, a significant portion of the E. coli genome remains uncharacterized. Although traditional forward and reverse genetic approaches have played major roles in gene-to-phenotype association mapping in E. coli, a more efficient and sensitive genetics approach would facilitate characterization of the part of the genome whose function is not yet known. Network-assisted predictive genetics is an example of such an approach whose popularity is growing. These days, a tons of omics data for E. coli from experiemntal and computational studies is publicly available. As a result, we were able to use comprehensive information to build EcoliNet that is comprised of 95,520 co-functional links among 4,099 protein coding genes (covers ~99% of all E. coli coding genes).
Various network biology approaches such as guilt-by-association have been widely employed in generating novel hypotheses for gene functions and gene-phenotype associations. EcoliNet also provides such network biology tools to (i) find new members of a pathway, (ii) infer functions from network neighbors.
Moreover, EcoliNet provides not only the integrated network but also all data specific networks (~1.3 million functional links), including 54 co-expression and 4 high-throughput PPI networks via freely accessible Download page. Therefore, co-functional gene networks for other bacterial species can be constructed via orthology-based transfer of information from EcoliNet.
Data typess for 7 data types incorporated in EcoliNet
| Data type | Data set description |
|---|---|
| CC | Inferred links by co-citation of two genes across 57,062 PubMed Central articles for E. coli biology |
| CX | Inferred links by co-expression pattern of two genes (based on high-dimensional gene expression data) |
| DC | Inferred links by co-occurrence of protein domains between two coding genes |
| GN | Inferred links by similar genomic context of bacterial orthologs of two genes |
| HT | Inferred links by high-throughput protein-protein interations |
| LC | Inferred links by small/medium-scale protein-protein interactions (collected from protein-protein interaction data bases) |
| PG | Inferred links by similar phylogenetic profiles between two genes |
Hanhae Kim, Jung Eun Shim, Junha Shin, Insuk Lee*, EcoliNet: A database of co-functional gene network for Escherichia coli. Database 2015 Feb2;2015. pii: bav001 (Link)
Insuk Lee (insuklee (at) yonsei.ac.kr)
This work was supported by the National Research Foundation of Korea grant (2010-0017649, 2012M3A9B4028641, 2012M3A9C7050151).
