Kinase Enrichment Analysis (KEA)

Category Cross-Omics>Knowledge Bases/Databases/Tools

Abstract Kinase Enrichment Analysis (KEA) is a web-based tool with an underlying database providing users with the ability to link lists of mammalian proteins/genes with the kinases that phosphorylate them.

The system draws from several available kinase-substrate databases to compute kinase enrichment probability based on the distribution of kinase-substrate proportions in the background kinase-substrate database compared with kinases found to be associated with an input list of genes/proteins.

As prior knowledge is increasingly used to interpret high-throughput results, the manufacturers anticipate that KEA is going to be especially useful for the analysis of proteomics and phosphoproteomics data.

KEA can be used for analyzing multivariate datasets collected on a time- course to observe trends in kinase activity over time.

Results that show changes in kinase enrichment under different conditions can be due to one of the following reasons: change in kinase enzymatic activity, change in kinase subcellular localization or changes in kinase concentration.

Furthermore, KEA can help researchers understand how they can perturb ‘cellular systems’ toward a desired phenotype by targeting a kinase or group of kinases with pharmacological or gene silencing means.

Kinase signaling is well-established to be disturbed in many disease states, especially in Cancer (Blume-Jensen and Hunter, 2001); while it is apparent that phenotypic integrity is controlled by the activity of the regulated behavior of multiple kinases.

Hence, mapping kinase activation patterns based on different experimental conditions and time points when measuring many genes/proteins at once in diseased/perturbed versus normal/control may directly suggest combinations of kinase inhibitors that would shift the cellular state towards a desired phenotype.

KEA Implementation --

The manufacturer first constructed a database that consolidates kinase- substrate interactions from multiple online sources.

The manufacturer integrated data describing kinase-substrate interactions from NetworKIN (a resource for exploring cellular phosphorylation networks); Phospho.ELM (a database of experimentally verified phosphorylation sites in eukaryotic proteins);

Molecular INTeraction database (MINT); Human Protein Reference Database (HPRD); PhosphoPoint (a comprehensive human kinase interactome and phospho-protein database); and

Swiss-Prot (a manually curated biological database of protein sequences); as well as phosphorylation interactions that the manufacturer manually extracted previously from literature.

The manufacturer consolidated interactions from mouse and rat into human by converting all protein/gene IDs to human Entrez gene symbols.

Each kinase-substrate data record is associated with a specific kinase, kinase family and kinase subfamily.

To group kinases into families, the manufacturer used the 'kinome tree' where kinases are classified into 10 major classes and 119 families. To further increase the size of the background dataset, the manufacturer included all direct protein-protein interactions (PPIs) involving kinases from HPRD and MINT.

By this expansion the current dataset contains a total of 11,923 interactions between 445 kinases having 3,995 substrates.

KEA Analysis process --

The analysis begins with an input list of gene symbols entered by the user for kinase enrichment analysis (KEA). Before performing the KEA, the manufacturer removes all input entries that do Not match a substrate in the consolidated background kinase-substrate dataset.

This step is necessary for achieving proportional comparison.

The expected value for a randomly generated list of kinase-substrates can be found by determining the cardinality of the set of substrates that are targeted by specific kinases (or family of kinases) dividing such number by the total number of substrates in the background dataset.

In order to detect 'statistical significant' deviations from this expected value, the manufacturer uses the Fisher Exact Test.

The P-value can be used to distinguish specific kinases among the large number of kinases appearing in the output table.

KEA Results --

All reported results can be exported to Excel via comma-separated value (CSV) files.

Additionally, users can mouse over on the number of targets for each kinase, kinase family or class to see the list of substrates and view a connectivity diagram (map) that visualizes known PPIs within the substrates using a database of PPIs the manufacturer previously published (Genes2Networks - see G6G Abstract Number 20425).

The map is dynamic where users can move nodes around and click on nodes.

The visualization of these connectivity diagrams was achieved using Adobe Flash CS4 with ActionScript.

Such sub-graphs can be used to link kinase specific substrates to pathways and complexes.

System Requirements

Web-based; command-line processing is also available.


Manufacturer Web Site Kinase Enrichment Analysis (KEA)

Price Contact manufacturer.

G6G Abstract Number 20483

G6G Manufacturer Number 104054