Chemical Genomic Profiling via Barcode Sequencing to Predict Compound Mode of Action

  • Jeff S. PiotrowskiEmail author
  • Scott W. Simpkins
  • Sheena C. Li
  • Raamesh Deshpande
  • Sean J. McIlwain
  • Irene M. Ong
  • Chad L. Myers
  • Charlie Boone
  • Raymond J. Andersen
Part of the Methods in Molecular Biology book series (MIMB, volume 1263)


Chemical genomics is an unbiased, whole-cell approach to characterizing novel compounds to determine mode of action and cellular target. Our version of this technique is built upon barcoded deletion mutants of Saccharomyces cerevisiae and has been adapted to a high-throughput methodology using next-generation sequencing. Here we describe the steps to generate a chemical genomic profile from a compound of interest, and how to use this information to predict molecular mechanism and targets of bioactive compounds.

Key words

Chemical genomics Barcode sequencing Functional genomics Yeast deletion collection 



J.P., S.M., and I.O. are funded by the DOE Great Lakes Bioenergy Research Center (DOE BER Office of Science DE-FC02-07ER64494). SC is supported by a RIKEN Foreign Postdoctoral Researcher Award. C.M., and R.D. are supported by grants from the National Institutes of Health (1R01HG005084-01A1, 1R01GM104975-01, R01HG005853), a grant from the National Science Foundation (DBI 0953881), and the CIFAR Genetic Networks Program. S.W.S. is supported by an NIH Biotechnology training grant (5T32GM008347-22). C.B. is supported by the Canadian Institutes of Health Research (CIHR MOP-57830). R.A. is supported by the Natural Science and Engineering Research Council (NSERC) of Canada, the Canada Foundation for Innovation (CFI), and the Canadian Cancer Society Research Institute.


  1. 1.
    Parsons A et al (2006) Exploring the mode-of-action of bioactive compounds by chemical-genetic profiling in yeast. Cell 126:611–625PubMedCrossRefGoogle Scholar
  2. 2.
    Ho CH et al (2011) Combining functional genomics and chemical biology to identify targets of bioactive compounds. Curr Opin Chem Biol 15:66–78PubMedCrossRefGoogle Scholar
  3. 3.
    Fung S-Y et al (2013) Unbiased screening of marine sponge extracts for anti-inflammatory agents combined with chemical genomics identifies girolline as an inhibitor of protein synthesis. ACS Chem Biol 9:247–257PubMedCrossRefGoogle Scholar
  4. 4.
    Williams DE et al (2011) Padanamides A and B, highly modified linear tetrapeptides produced in culture by a Streptomyces sp. isolated from a marine sediment. Org Lett 13:3936–3939PubMedCentralPubMedCrossRefGoogle Scholar
  5. 5.
    Giaever G et al (2004) Chemogenomic profiling: identifying the functional interactions of small molecules in yeast. Proc Natl Acad Sci U S A 101:793–798PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Giaever G et al (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature 418:387–391PubMedCrossRefGoogle Scholar
  7. 7.
    Kim D-U et al (2010) Analysis of a genome-wide set of gene deletions in the fission yeast Schizosaccharomyces pombe. Nat Biotechnol 28:617–623PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Kitagawa M et al (2006) Complete set of ORF clones of Escherichia coli ASKA library (a complete set of E. coli K-12 ORF archive): unique resources for biological research. DNA Res 12:291–299CrossRefGoogle Scholar
  9. 9.
    Smith AM et al (2009) Quantitative phenotyping via deep barcode sequencing. Genome Res 19:1836–1842PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.
    Costanzo M et al (2010) The genetic landscape of a cell. Science 327:425–431PubMedCrossRefGoogle Scholar
  11. 11.
    Robinson DG, Chen W, Storey JD, Gresham D (2014) Design and analysis of bar-seq experiments. G3 (Bethesda) 4:11–18CrossRefGoogle Scholar
  12. 12.
    Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140PubMedCentralPubMedCrossRefGoogle Scholar
  13. 13.
    Andrusiak K (2012) Adapting S. cerevisiae chemical genomics for identifying the modes of action of natural compounds. Thesis. Accessed 24 Apr 2014
  14. 14.
    Smith AM et al (2010) Highly-multiplexed barcode sequencing: an efficient method for parallel analysis of pooled samples. Nucleic Acids Res 38:e142PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Jeff S. Piotrowski
    • 1
    Email author
  • Scott W. Simpkins
    • 2
  • Sheena C. Li
    • 3
  • Raamesh Deshpande
    • 2
  • Sean J. McIlwain
    • 1
  • Irene M. Ong
    • 1
  • Chad L. Myers
    • 2
  • Charlie Boone
    • 4
  • Raymond J. Andersen
    • 5
  1. 1.Great Lakes Bioenergy Research CenterUniversity of Wisconsin-MadisonMadisonUSA
  2. 2.Department of Computer Science and EngineeringUniversity of Minnesota-Twin CitiesMinneapolisUSA
  3. 3.RIKEN Center for Sustainable Resource ScienceWakoJapan
  4. 4.Terrence Donnelly Centre for Cellular and Biomolecular ResearchUniversity of TorontoTorontoCanada
  5. 5.Department of ChemistryUniversity of British ColumbiaVancouverCanada

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