Identification of Novel Protein–Ligand Interactions by Exon Microarray Analysis of Yeast Surface Displayed cDNA Library Selection Outputs

  • Scott Bidlingmaier
  • Bin LiuEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1319)


Yeast surface display is widely utilized to screen large libraries for proteins or protein fragments with specific binding properties. We have previously constructed and utilized yeast surface displayed human cDNA libraries to identify protein fragments that bind to various target ligands. Conventional approaches employ monoclonal screening and sequencing of polyclonal outputs that have been enriched for binding to a target molecule by several rounds of affinity-based selection. Frequently, a small number of clones will dominate the selection output, making it difficult to comprehensively identify potentially important interactions due to low representation in the selection output. We have developed a novel method to address this problem. By analyzing selection outputs using high-density human exon microarrays, the full potential of selection output diversity can be revealed in one experiment. FACS-based selection using yeast surface displayed human cDNA libraries combined with exon microarray analysis of the selection outputs is a powerful way of rapidly identifying protein fragments with affinity for any soluble ligand that can be fluorescently detected, including small biological molecules and drugs. In this report we present protocols for exon microarray-based analysis of yeast surface display human cDNA library selection outputs.

Key words

Yeast surface display cDNA library Exon microarray Phosphatidylinositide Novel nuclear phosphatidylinositide-binding proteins 



The work is supported by grants from the National Institute of Health (R01 CA171315, R01 CA118919, and R01 CA129491).


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Anesthesia, UCSF Helen Diller Family Comprehensive Cancer CenterUniversity of California at San FranciscoSan FranciscoUSA

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