Literature DB >> 17406283

A microarray-based protocol for monitoring the growth of yeast overexpression strains.

Rebecca A Butcher1, Stuart L Schreiber.   

Abstract

Gene overexpression can be used to investigate the biological pathways that are important in the response to a small molecule or other perturbation. To facilitate the use of gene overexpression in the study of small-molecule mechanisms, we developed a microarray-based protocol for monitoring the growth of a pool of yeast strains, each overexpressing a different protein. In this protocol, yeast harboring a set of approximately 3,900 galactose-inducible overexpression plasmids are grown in the absence or presence of a small molecule for multiple generations. The plasmids are then extracted from the two populations, processed and labeled in such a manner that their relative concentrations can be determined by competitive hybridization to a microarray. Although this protocol was developed for monitoring a specific set of overexpression plasmids, it could presumably be adapted to monitor yeast that have been transformed with any set of plasmids for which the gene inserts have been spotted, or otherwise arrayed, in a microarray format. This protocol can be completed in approximately 15 hours of hands-on time over the course of several days.

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Year:  2006        PMID: 17406283     DOI: 10.1038/nprot.2006.80

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  3 in total

1.  Dosage suppression genetic interaction networks enhance functional wiring diagrams of the cell.

Authors:  Leslie Magtanong; Cheuk Hei Ho; Sarah L Barker; Wei Jiao; Anastasia Baryshnikova; Sondra Bahr; Andrew M Smith; Lawrence E Heisler; John S Choy; Elena Kuzmin; Kerry Andrusiak; Anna Kobylianski; Zhijian Li; Michael Costanzo; Munira A Basrai; Guri Giaever; Corey Nislow; Brenda Andrews; Charles Boone
Journal:  Nat Biotechnol       Date:  2011-05-15       Impact factor: 54.908

2.  A molecular barcoded yeast ORF library enables mode-of-action analysis of bioactive compounds.

Authors:  Cheuk Hei Ho; Leslie Magtanong; Sarah L Barker; David Gresham; Shinichi Nishimura; Paramasivam Natarajan; Judice L Y Koh; Justin Porter; Christopher A Gray; Raymond J Andersen; Guri Giaever; Corey Nislow; Brenda Andrews; David Botstein; Todd R Graham; Minoru Yoshida; Charles Boone
Journal:  Nat Biotechnol       Date:  2009-04-06       Impact factor: 54.908

3.  Covert genetic selections to optimize phenotypes.

Authors:  Di Wu; Elizabeth Townsley; Alan Michael Tartakoff
Journal:  PLoS One       Date:  2007-11-21       Impact factor: 3.240

  3 in total

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