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Interactome Under Construction PROtein–PROTEIN INTERACTIONS TECHNOLOGY There are two main approaches for detecting APE interacting proteins: techniques that measure OSC direct physical interactions between protein /CYT O pairs — binary approaches — and those that measure interactions among groups of proteins that may not form physical contacts — co- /UC SAN DIEG SAN /UC complex methods (see ‘Tools for the search’). O The most frequently used binary method is K. ON K. the yeast two-hybrid (Y2H) system2. It has vari- ations involving different reagents, and has been adapted to high-throughput screening. The strategy interrogates two proteins, called bait and prey, coupled to two halves of a transcrip- tion factor and expressed in yeast. If the proteins make contact, they reconstitute a transcription factor that activates a reporter gene. Another method for identifying binary interactions is luminescence-based mamma- lian interactome mapping (LUMIER), a high- throughput approach developed by Jeff Wrana at the Samuel Lunefeld Research Institute in Toronto, Canada. This strategy fuses Renilla luciferaze (RL) enzyme, which catalyses light- emitting reactions, to a bait protein, which is expressed in a mammalian cell along with can- didate protein partners tagged with a polypep- The human interactome contains more than 100,000 protein interactions, only a fraction of which are known. tide called Flag. Researchers use a Flag antibody to immunoprecipitate all proteins with the Flag tag, along with any that interact with them. Interactions between the RL-fused bait and the Flag-tagged prey are detected when light Interactome under is emitted. Other binary methods include the mammalian protein–protein interaction trap and techniques based on proteome chips. The most common co-complex method is construction co-immunoprecipitation (coIP) coupled with mass spectrometry (MS). In this approach, a protein bait is tagged with a molecular marker. Developing techniques are helping researchers to build the Several types of tags are commercially available; protein interaction networks that underlie all cell functions. each requires a distinct biochemical technique to recognize the tag and fish the bait protein out of the cell lysate, bringing with it any interacting BY LAURA BONETTA open-source software for network visualiza- proteins. These are then identified by MS. tion. “That effort identified 30,000 genes, but In addition to these empirical methods, n old adage says: “Show me your friends, that is not the end goal. How the genes work in researchers have used computational techniques and I’ll know who you are.” In the same pathways and how these pathways function in to predict interactions on the basis of factors way, finding interaction partners for disease states and development is the end goal. such as amino-acid sequence and structural Aa protein can reveal its function. To that end, To accomplish this we will need to systemati- information. “People ask ‘Why are you predict- researchers are now building entire networks of cally map gene and protein interactions.” ing interactions when you can just do the exper- protein–protein interactions. Unlike biological Unlike the genome, the interactome — the iment?’” says Gary Bader, a bioinformatician at pathways, which represent a sequence of molec- set of protein-to-protein interactions that the University of Toronto. “But experimental ular interactions leading to a final result — for occurs in a cell — is dynamic. Many inter- techniques fail for some proteins.” example, a signalling cascade — networks are actions are transient, and others occur only interlinked. Represented as starbursts of pro- in certain cellular contexts or at particular FALSE READINGS tein ‘nodes’ linked by interaction ‘edges’ to form times in development. The interactome may Every step of a procedure to detect protein– intricate constellations, they provide insight into be tougher to solve than the genome, but the protein interactions — from the reagents used the mechanisms of cell functions. Furthermore, information, researchers say, is crucial for a to the cell types and experimental conditions — placing proteins encoded by disease genes into complete understanding of biology. influences the proteins that are identified. Two these networks will let researchers determine studies this year used similar methods to iden- the best candidates for assessing disease risk THE RIGHT PARTNERS tify interacting proteins in transcription factors and targeting with therapies. At any time, a human cell may contain about in embryonic stem cells3,4; there was incomplete “This is the next step after the Human 130,000 binary interactions between proteins1. overlap between the resulting data sets. “If you Genome Project,” says Trey Ideker, a systems So far, a mere 33,943 unique human protein– use the same protocol you will get reproducible biologist at the University of California, San protein interactions are listed on BioGRID lists of proteins. But different labs use different Diego, and principal investigator at the National (http://thebiogrid.org), a database that stores protocols, which affects the end result,” says Resource for Network Biology, which provides interaction data. Clearly, there is work to do. Raymond Poot, a cell biologist at Erasmus MC 9 DECEMBER 2010 | VOL 468 | NATURE | 851 © 2010 Macmillan Publishers Limited. All rights reserved TECHNOLOGY PROtein–PROTEIN INTERACTIONS hospital in Rotterdam, the Netherlands, and Calling out false positives — reported inter- detect the interactions. But the definition of a lead author of one of the studies. actions that don’t actually occur — and false ‘real’ interaction depends on the context. “Does In his protocol, Poot pulled interacting pro- negatives — interactions that do occur but are a real interaction mean that two proteins inter- teins from cells using nuclear extracts express- not picked up by the experimental protocol or act if they are placed next to each other in a ing different Flag-tagged transcription factors. are discarded — is one of the main challenges test tube, or that they must interact in a cell? Or He added a nuclease to his reactions to remove in the field. “Normally when you do a coIP fol- does real mean that the interaction should have DNA and eliminate possible artefacts caused lowed by MS you will get hundreds of protein a biological function?” asks Ideker. Researchers by proteins binding to it. “Transcription fac- candidates interacting with any one bait,” says can home in on functional interactions by com- tors bind to DNA so you are likely to pull out Wade Harper, a cell biologist at Harvard Medi- bining data on interactions with other types of DNA-binding factors that are not directly inter- cal School in Boston, Massachusetts. “When biological information, such as genetic interac- acting,” he explains. Purifying many different you weed out all the stochastic and non-specific tions, protein localizations or gene expression. transcription factors with the same protocol interactions you end up with many fewer pro- For instance, proteins whose genes are co- also enabled the researchers to determine which teins. Some proteins in large complexes might expressed are likely to interact with each other interactions were most likely to be specific. For have 30–50 partners, others only 4–5.” or to be part of the same complex or pathway. example, proteins that consistently co-purified One way in which researchers increase the Many tools are available on the web for inte- with all transcription factors would be treated accuracy of their results is to use more than one grating different types of information about a as unlikely to indicate a genuine interaction. method (for example, Y2H plus LUMIER) to given protein or gene. One is GeneMANIA, developed by Bader’s group in collaboration with Quaid Morris, a computational biolo- gist also at the University of Toronto. A user enters the gene names into GeneMANIA; Tools for the search the program provides a list of genes that are functionally similar or have shared properties, CS such as similar expression or localization, and RIGENI then displays a proposed interaction network, B HY showing relationships among the genes and the type of data used to gather that informa- tion. The user can click on any node to obtain information about the gene and on any link to obtain information about their relationship (such as citations for any published studies or other sources of data). “It’s like a Google for genetic and protein information,” says Bader. Other web-based interfaces that predict gene functions include STRING (http://string- db.org) developed at the European Molecular Methods such as the yeast two-hybrid system allow scientists to work out which proteins interact. Biology Laboratory in Heidelberg, Germany. It hunts for protein interactions on the basis of The two main methods for finding companies such as Hybrigenics in Paris genomic context, high-throughput experiments, protein–protein interactions are the and Dualsystems Biotech of Schlieren, co-expression and data from the literature. yeast two-hybrid (Y2H) system and Switzerland, offer Y2H-based screening. co-immunoprecipitation followed by mass “We have complex libraries with ten times KEEPING SCORE spectrometry. Several companies sell more independent clones than most other To select real protein–protein interactions, reagents for both approaches. Invitrogen of libraries, which we screen to saturation. Harper and some members of his lab, Matt Sowa Carlsbad, California, sells the ProQuest
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