A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2000-02

AUTHORS

Peter Uetz, Loic Giot, Gerard Cagney, Traci A. Mansfield, Richard S. Judson, James R. Knight, Daniel Lockshon, Vaibhav Narayan, Maithreyan Srinivasan, Pascale Pochart, Alia Qureshi-Emili, Ying Li, Brian Godwin, Diana Conover, Theodore Kalbfleisch, Govindan Vijayadamodar, Meijia Yang, Mark Johnston, Stanley Fields, Jonathan M. Rothberg

ABSTRACT

Two large-scale yeast two-hybrid screens were undertaken to identify protein–protein interactions between full-length open reading frames predicted from the Saccharomyces cerevisiae genome sequence. In one approach, we constructed a protein array of about 6,000 yeast transformants, with each transformant expressing one of the open reading frames as a fusion to an activation domain. This array was screened by a simple and automated procedure for 192 yeast proteins, with positive responses identified by their positions in the array. In a second approach, we pooled cells expressing one of about 6,000 activation domain fusions to generate a library. We used a high-throughput screening procedure to screen nearly all of the 6,000 predicted yeast proteins, expressed as Gal4 DNA-binding domain fusion proteins, against the library, and characterized positives by sequence analysis. These approaches resulted in the detection of 957 putative interactions involving 1,004 S. cerevisiae proteins. These data reveal interactions that place functionally unclassified proteins in a biological context, interactions between proteins involved in the same biological function, and interactions that link biological functions together into larger cellular processes. The results of these screens are shown here. More... »

PAGES

623-627

Journal

TITLE

Nature

ISSUE

6770

VOLUME

403

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/35001009

    DOI

    http://dx.doi.org/10.1038/35001009

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1035773549

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/10688190


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