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Large-scale identification of protein–protein interaction of Escherichia coli K-12

    • 1 Graduate School of Biological Sciences, Nara Institute of Science and Technology, Ikoma, Nara 630-0101, Japan;
    • 2 Kyowa Hakko Branch, Japan Bioindustry Association in Tokyo Research Laboratories, Kyowa Hakko Kogyo, Machida-shi, Tokyo 194-8533, Japan;
    • 3 CREST, JST (Japan Science and Technology), Kawaguchi, Saitama 332-0012, Japan;
    • 4 Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0035, Japan;
    • 5 Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Nara 630-0101, Japan;
    • 6 Institute of Bioinformatics, National Yang-Ming University, Taipei 112, Taiwan, China;
    • 7 Institute for Virus Research, Kyoto University, Sakyo, Kyoto 606-8507, Japan
    • 8 Present addresses: Dragon Genomics Center, Takara Bio Inc. Yokkaichi, Mie 512-1211, Japan;
    • 9 Department of Biochemistry, BGC Trust Medical College, Chittagong, Bangladesh;
    • 10 Graduate School of Biostudies, Konoe, Kyoto University, Sakyo-ku, Kyoto 606-8315, Japan.
    • 11 These authors contributed equally to this work.
    • 12 Corresponding authors. E-mail [email protected]; fax. +81-743-72-5669. E-mail [email protected]; fax +81-75-753-7905.
Published April 10, 2006. Vol 16 Issue 5, pp. 686-691. https://doi.org/10.1101/gr.4527806
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Abstract

Protein–protein interactions play key roles in protein function and the structural organization of a cell. A thorough description of these interactions should facilitate elucidation of cellular activities, targeted-drug design, and whole cell engineering. A large-scale comprehensive pull-down assay was performed using a His-tagged Escherichia coli ORF clone library. Of 4339 bait proteins tested, partners were found for 2667, including 779 of unknown function. Proteins copurifying with hexahistidine-tagged baits on a Ni2+-NTA column were identified by MALDI-TOF MS (matrix-assisted laser desorption ionization time of flight mass spectrometry). An extended analysis of these interacting networks by bioinformatics and experimentation should provide new insights and novel strategies for E. coli systems biology.

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