Abstract
BackgroundHigh-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted.ResultsWe describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web.ConclusionsWe have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.
Highlights
High-throughput screening of physical, genetic and chemicalgenetic interactions brings new important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, help to unravel how cellular networks are organized and facilitates the validation of therapeutic targets and drug design.Recently, many experimental procedures have been developed to help elucidate the intricate networks of proteins, genes and drugs interactions, ranging from high-throughput experiments based on genomic scale analyses [1,2,3,4,5,6] to molecular biology approaches on a specific key pathway [7,8]
Molecular interactions data related to human and model organisms are currently being integrated in diverse databases, such as BioGRID [9], Intact [10], DIP [11], STRING [12], MINT [13], HPRD [14], DrugBank [15], ChemBL [16], HMDB [17], YMDB [18], ECMDB [19], as well as KEGG [20] and Reactome [21]
The information available can be derived from diverse experimental methods, such as yeast two-hybrid (Y2H), mass spectrometry (MS), immunoprecipitation (IP), or fluorescence resonance energy transfer (FRET) assays to demonstrate protein interactions and, in some cases, interaction networks are determined solely by bioinformatics tools [22,23], which rarely consider the subcellular localization of the interactors
Summary
High-throughput screening of physical, genetic and chemicalgenetic interactions brings new important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, help to unravel how cellular networks are organized and facilitates the validation of therapeutic targets and drug design.Recently, many experimental procedures have been developed to help elucidate the intricate networks of proteins, genes and drugs interactions, ranging from high-throughput experiments based on genomic scale analyses [1,2,3,4,5,6] to molecular biology approaches on a specific key pathway [7,8]. High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. Such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted
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