Centre International de Recherche en Infectiologie (CIRI), Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, F-69007 Lyon, France
Dr. Pierre-Olivier Vidalain
Centre International de Recherche en Infectiologie (CIRI), Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, F-69007 Lyon, France
To initiate studies on how protein-protein interaction (or “interactome”) networks relate to multicellular functions, we have mapped a large fraction of the Caenorhabditis elegans interactome network. Starting with a subset of metazoan-specific proteins, more than 4000 interactions were identified from high-throughput, yeast two-hybrid (HT=Y2H) screens. Independent coaffinity purification assays experimentally validated the overall quality of this Y2H data set. Together with already described Y2H interactions and interologs predicted in silico , the current version of the Worm Interactome (WI5) map contains ∼5500 interactions. Topological and biological features of this interactome network, as well as its integration with phenome and transcriptome data sets, lead to numerous biological hypotheses.
The advent of systems biology necessitates the cloning of nearly entire sets of protein-encoding open reading frames (ORFs), or ORFeomes, to allow functional studies of the corresponding proteomes. Here, we describe the generation of a first version of the human ORFeome using a newly improved Gateway recombinational cloning approach. Using the Mammalian Gene Collection (MGC) resource as a starting point, we report the successful cloning of 8076 human ORFs, representing at least 7263 human genes, as mini-pools of PCR-amplified products. These were assembled into the human ORFeome version 1.1 (hORFeome v1.1) collection. After assessing the overall quality of this version, we describe the use of hORFeome v1.1 for heterologous protein expression in two different expression systems at proteome scale. The hORFeome v1.1 represents a central resource for the cloning of large sets of human ORFs in various settings for functional proteomics of many types, and will serve as the foundation for subsequent improved versions of the human ORFeome.