Interactome

Part of the DISC1 interactome with genes represented by text in boxes and interactions noted by lines between the genes. From Hennah and Porteous, 2009.

In molecular biology an Interactome is defined as the whole set of molecular interactions in cells. Specifally it means physical interactions among molecules but can also mean indirect interactions among genes, i.e. genetic interactions. It is usually displayed as a directed graph. The word "interactome" was originally coined in 1999 by a group of French scientists headed by Bernard Jacq.

Molecular interaction networks

Molecular interactions can occur between molecules belonging to different biochemical families (proteins, nucleic acids, lipids, carbohydrates, etc.) and also within a given family. When spoken in terms of proteomics, interactome refers to protein–protein interaction network (PPI), or protein interaction network (PIN). Another extensively studied type of interactome is the protein–DNA interactome (network formed by transcription factors (and DNA or chromatin regulatory proteins) and their target genes.

Size of interactomes

It has been suggested that the size of an organism's interactome correlates better than genome size with the biological complexity of the organism. Although protein–protein interaction maps containing several thousands of binary interactions are now available for several organisms, none of them is presently complete and the size of interactomes is still a matter of debate.

Genetic interaction networks

In 2010, the most "complete" gene interactome produced to date was compiled from 54 million two-gene comparisons to describe "the interaction profiles for ~75% of all genes in the Budding yeast," with 170,000 gene interactions.

Although extremely important and useful, the interactome is still being developed and is not complete (as of October 2010). There are various factors that have a role in protein interactions that have yet to be incorporated in the interactome. Many have termed the interactome as a whole as being fuzzy. The binding strength of the various proteins, microenvironmental factors, sensitivity to various procedures, and the physiological state of the cell all affect protein–protein interactions, yet are not accounted for in the interactome. Although the interactome is useful in some ways, it must be analyzed knowing that these factors exist and can affect the protein interactions.

Methods of mapping the interactome

The study of the interactome is called interactomics. The basic unit of a protein network is the protein–protein interaction (PPI). Because the interactome considers the whole cells or organisms, there is a need to collect a massive amount of information.

Experimental methods to identify PPIs: the yeast two hybrid system (Y2H) is suited to explore the binary interactions among two proteins at a time. Affinity purification and subsequent mass spectrometry is suited to identify a protein complex. Both methods can be used in a high-throughput (HTP) fashion.

Predicting PPIs: Using experimental data as a starting point, homology transfer is the most straightforward algorithm to predict interactomes. Here, PPIs from one organism are used to predict interactions among homologous proteins in another organism. Other algorithms produce detailed atomic models of protein protein complexes as well as other protein–molecule interactions.

Eukaryotic Interactomes

There have been several efforts to map eukaryotic interactomes through HTP methods. As of 2006, yeast, fly, worm, and human HTP maps have been created. Recently, pathogen-host interactome (Hepatitis C Virus/Human (2008), Epstein Barr virus/Human (2008), Influenza virus/Human (2009)) was also delineated through HTP to identify essential molecular components for pathoghens but also for the host to recognize pathogens and trigger efficient innate immune response.

Using the interactome

Researchers have begun to use preliminary versions of the interactome to gain understanding about the biology and function of the molecules within them. For example, protein interaction networks have been used to produce improved protein functional annotations (or nannotations) for proteins with unknown functions.

Interactome web servers

• Protinfo PPC predicts the atomic 3D structure of protein protein complexes.

Interactome databases

• APID: Agile Protein Interaction DataAnalyzer – an interactive bioinformatic web-tool that integrates and unifies main known experimentally validated protein–protein interactions (Prieto and De Las Rivas, 2006).
• BioGRID database
• Bioverse database
• ConsensusPathDB includes functional interactions from 12 other databases
• Database of interacting proteins (DIP)
• MIPS database
• PSIMAP database — the first protein structural interactome DB
• InterPare database — a structural protein interfaceome DB
• Biomolecular Interaction Network Database (BIND)
• Online Predicted Human Interaction Database (OPHID)
• Human Protein Reference Database (HPRD)
• HPID: Human Protein Interaction Database (Inha University, Korea)
• MINT: Molecular INTeraction database (Chatr-aryamontri et al. 2006)
• PINdb: Proteins Interacting in the Nucleus Database (Luc PV and Tempst P, 2004)
• IntAct: The Molecular Interaction Database
• VirHostNet — Virus-Host protein–protein interaction Networks knowledgebase
• Interactome Databases — interactome projects at CCSB.
• TRANSFAC, a database about transcription regulating eukaryotic protein-DNA interactions
• PSIbase Database — a global interactome DB based on PSIMAP.
• Interactome.org — a dedicated interactome web site.

See also

• Bioinformatics
• Omics
• List of omics topics in biology

References

• De Las Rivas J, Fontanillo C (June 2010). "Protein–Protein Interactions Essentials: Key Concepts to Building and Analyzing Interactome Networks". PLoS Computational Biology 6 (6): e1000807. doi:10.1371/journal.pcbi.1000807. PMC 2891586. PMID 20589078. http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2891586. .
• Sanchez C, Lachaize C, Janody F, Bellon B, Röder L, Euzenat J, Rechenmann F, Jacq B (1999). "Grasping at molecular interactions and genetic networks in Drosophila melanogaster using FlyNets, an Internet database". Nucleic Acids Res. 27 (1): 89–94. doi:10.1093/nar/27.1.89. PMC 148104. PMID 9847149. http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=148104. 
• Park J, Lappe M, Teichmann SA (Mar 2001). "Mapping protein family interactions: intramolecular and intermolecular protein family interaction repertoires in the PDB and yeast". J Mol Biol. 307 (3): 929–38. doi:10.1006/jmbi.2001.4526. PMID 11273711. 
• Navratil V. et al. (2009) VirHostNet: a knowledge base for the management and the analysis of proteome-wide virus-host interaction networks. Nucleic Acids Res. 2009 Jan;37(Database issue):D661-8. Epub 2008 Nov 4.