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De novo identification and biophysical characterization of transcription-factor binding sites with microfluidic affinity analysis

Nature Biotechnology volume 28, pages 970–975 (2010)Cite this article

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Abstract

Gene expression is regulated in part by protein transcription factors that bind target regulatory DNA sequences. Predicting DNA binding sites and affinities from transcription factor sequence or structure is difficult; therefore, experimental data are required to link transcription factors to target sequences. We present a microfluidics-based approach for de novo discovery and quantitative biophysical characterization of DNA target sequences. We validated our technique by measuring sequence preferences for 28 Saccharomyces cerevisiae transcription factors with a variety of DNA-binding domains, including several that have proven difficult to study by other techniques. For each transcription factor, we measured relative binding affinities to oligonucleotides covering all possible 8-bp DNA sequences to create a comprehensive map of sequence preferences; for four transcription factors, we also determined absolute affinities. We expect that these data and future use of this technique will provide information essential for understanding transcription factor specificity, improving identification of regulatory sites and reconstructing regulatory interactions.

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Figure 1: Overall experimental design and procedure.
Figure 2: Detailed analysis of measured Cy5 intensities and fluorescence intensity ratios (Cy5/BODIPY-FL) for rabbit reticulocyte lysate alone, Reb1p, Cin5p and Cup9p.
Figure 3: Comparison between Kd values derived from direct measurements of concentration-dependent binding and Kd values calculated from ratio measurements at a single concentration.
Figure 4: Comparison between motifs found for all 28 S. cerevisiae transcription factors and previous literature results (SWISS, SwissRegulon30; ChIP-chip, Harbison library22; PBM1, protein binding microarray14; PBM2, protein binding microarray15).

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References

  1. Tanay, A. Extensive low-affinity transcriptional interactions in the yeast genome. Genome Res. 16, 962–972 (2006).

    Article  CAS  Google Scholar 

  2. Segal, E., Raveh-Sadka, T., Schroeder, M., Unnerstall, U. & Gaul, U. Predicting expression patterns from regulatory sequence in Drosophila segmentation. Nature 451, 535–540 (2008).

    Article  CAS  Google Scholar 

  3. Badis, G. et al. Diversity and complexity in DNA recognition by transcription factors. Science 324, 1720–1723 (2009).

    Article  CAS  Google Scholar 

  4. Kim, H.D. & O′Shea, E.K. A quantitative model of transcription factor-activated gene expression. Nat. Struct. Mol. Biol. 15, 1192–1198 (2008).

    Article  CAS  Google Scholar 

  5. Segal, E. & Widom, J. From DNA sequence to transcriptional behavior: a quantitative approach. Nat. Rev. Genet. 10, 443–456 (2009).

    Article  CAS  Google Scholar 

  6. Gertz, J., Siggia, E.D. & Cohen, B.A. Analysis of combinatorial cis-regulation in synthetic and genomic promoters. Nature 457, 215–218 (2009).

    Article  CAS  Google Scholar 

  7. Yuh, C.H., Bolouri, H. & Davidson, E.H. Cis-regulatory logic in the endo16 gene: switching from a specification to a differentiation mode of control. Development 128, 617–629 (2001).

    CAS  PubMed  Google Scholar 

  8. Iyer, V.R. et al. Genomic binding sites of the yeast cell-cycle transcription factors SBF and MBF. Nature 409, 533–538 (2001).

    Article  CAS  Google Scholar 

  9. Johnson, D.S., Mortazavi, A., Myers, R.M. & Wold, B. Genome-wide mapping of in vivo protein-DNA interactions. Science 316, 1497–1502 (2007).

    Article  CAS  Google Scholar 

  10. Garner, M.M. & Revzin, A. A gel electrophoresis method for quantifying the binding of proteins to specific DNA regions: application to components of the Escherichia coli lactose operon regulatory system. Nucleic Acids Res. 9, 3047–3060 (1981).

    Article  CAS  Google Scholar 

  11. Galas, D.J. & Schmitz, A. DNAse footprinting: a simple method for the detection of protein-DNA binding specificity. Nucleic Acids Res. 5, 3157–3170 (1978).

    Article  CAS  Google Scholar 

  12. Jost, J.P., Munch, O. & Andersson, T. Study of protein-DNA interactions by surface plasmon resonance (real time kinetics). Nucleic Acids Res. 19, 2788 (1991).

    Article  CAS  Google Scholar 

  13. Meng, X., Brodsky, M.H. & Wolfe, S.A. A bacterial one-hybrid system for determining the DNA-binding specificity of transcription factors. Nat. Biotechnol. 23, 988–994 (2005).

    Article  CAS  Google Scholar 

  14. Badis, G. et al. A library of yeast transcription factor motifs reveals a widespread function for Rsc3 in targeting nucleosome exclusion at promoters. Mol. Cell 32, 878–887 (2008).

    Article  CAS  Google Scholar 

  15. Zhu, C. et al. High-resolution DNA-binding specificity analysis of yeast transcription factors. Genome Res. 19, 556–566 (2009).

    Article  CAS  Google Scholar 

  16. Berger, M.F. et al. Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities. Nat. Biotechnol. 24, 1429–1435 (2006).

    Article  CAS  Google Scholar 

  17. Berger, M. et al. Variation in homeodomain DNA binding revealed by high-resolution analysis of sequence preferences. Cell 133, 1266–1276 (2008).

    Article  CAS  Google Scholar 

  18. De Silva, E.K. et al. Specific DNA-binding by apicomplexan AP2 transcription factors. Proc. Natl. Acad. Sci. USA 105, 8393–8398 (2008).

    Article  CAS  Google Scholar 

  19. Bonham, A.J., Neumann, T., Tirrell, M. & Reich, N.O. Tracking transcription factor complexes on DNA using total internal reflectance fluorescence protein binding microarrays. Nucleic Acids Res. 37, 94 (2009).

    Article  Google Scholar 

  20. Maerkl, S.J. & Quake, S.R. A systems approach to measuring the binding energy landscapes of transcription factors. Science 315, 233–237 (2007).

    Article  CAS  Google Scholar 

  21. Ralston, A. De Bruijn sequences-a model example of the interaction of discrete mathematics and computer science. Math. Mag. 55, 131–143 (1982).

    Google Scholar 

  22. Harbison, C.T. et al. Transcriptional regulatory code of a eukaryotic genome. Nature 431, 99–104 (2004).

    Article  CAS  Google Scholar 

  23. Foat, B.C., Morozov, A.V. & Bussemaker, H.J. Statistical mechanical modeling of genome-wide transcription factor occupancy data by MatrixREDUCE. Bioinformatics 22, e141–e149 (2006).

    Article  CAS  Google Scholar 

  24. Wu, R., Chaivorapol, C., Zheng, J., Li, H. & Liang, S. fREDUCE: detection of degenerate regulatory elements using correlation with expression. BMC Bioinformatics 8, 399 (2007).

    Article  Google Scholar 

  25. Vogel, K., Horz, W. & Hinnen, A. The two positively acting regulatory proteins PHO2 and PHO4 physically interact with PHO5 upstream activation regions. Mol. Cell. Biol. 9, 2050–2057 (1989).

    Article  CAS  Google Scholar 

  26. Wieland, G. et al. Determination of the binding constants of the centromere protein Cbf1 to all 16 centromere DNAs of Saccharomyces cerevisiae. Nucleic Acids Res. 29, 1054–1060 (2001).

    Article  CAS  Google Scholar 

  27. Liu, Y. et al. A suite of web-based programs to search for transcriptional regulatory motifs. Nucleic Acids Res. 32, W204–W207 (2004).

    Article  CAS  Google Scholar 

  28. Bailey, T.L. et al. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 37, W202–W208 (2009).

    Article  CAS  Google Scholar 

  29. Pavesi, G. et al. MoD Tools: regulatory motif discovery in nucleotide sequences from co-regulated or homologous genes. Nucleic Acids Res. 34, W566–W570 (2006).

    Article  CAS  Google Scholar 

  30. Pachkov, M., Erb, I., Molina, N. & Van Nimwegen, E. SwissRegulon: a database of genome-wide annotations of regulatory sites. Nucleic Acids Res. 35, D127–D131 (2007).

    Article  CAS  Google Scholar 

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Acknowledgements

P.M.F. was supported by a Howard Hughes Medical Institute/Helen Hay Whitney Foundation Postdoctoral Fellowship. J.L.D., S.R.Q. and this work were supported by the Howard Hughes Medical Institute. We thank A. Potanina for assistance with fabrication of microfluidic devices, O. Homann for implementation of PSAM functionality with MochiView and D. Breslow, F. Caro, S. Churchman, M. Dimon, T. Kiers, A. Kistler, C. Nelson, K. Sorber, E. Yeh and I. Zuleta for careful reading of the manuscript.

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Author notes

  1. Polly M Fordyce, Doron Gerber, Joseph L DeRisi and Stephen R Quake: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA

    Polly M Fordyce, Jiashun Zheng, Hao Li & Joseph L DeRisi

  2. Howard Hughes Medical Institute, Chevy Chase, Maryland, USA

    Polly M Fordyce, Joseph L DeRisi & Stephen R Quake

  3. Department of Life Sciences, Bar Ilan University, Ramat Gan, Israel

    Doron Gerber

  4. Departments of Bioengineering and Applied Physics, Stanford University, Palo Alto, California, USA

    Danh Tran & Stephen R Quake

  5. Center for Theoretical Biology, Peking University, Beijing, China

    Hao Li

Authors
  1. Polly M Fordyce
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Contributions

P.M.F. designed experiments, designed, created and printed the DNA library, made linear expression templates, fabricated microfluidic devices, performed microfluidic experiments assessing concentration-dependent binding and binding to the 8-mer library, analyzed data and wrote the manuscript. D.G. designed experiments, designed and fabricated microfluidic devices and performed microfluidic experiments assessing binding to the 8-mer library. D.T. fabricated microfluidic devices and performed microfluidic experiments assessing binding to the 8-mer library. J.Z. and H.L. analyzed data. S.R.Q. designed experiments, analyzed data and wrote the manuscript. J.L.D. designed experiments, assisted with printing the DNA library, analyzed data and wrote the manuscript.

Corresponding authors

Correspondence to Joseph L DeRisi or Stephen R Quake.

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The authors declare no competing financial interests.

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Supplementary Text and Figures

Supplementary Tables 1–8, Supplementary Figs. 1–19 and Supplementary Methods (PDF 4961 kb)

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Fordyce, P., Gerber, D., Tran, D. et al. De novo identification and biophysical characterization of transcription-factor binding sites with microfluidic affinity analysis. Nat Biotechnol 28, 970–975 (2010). https://doi.org/10.1038/nbt.1675

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