Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.

Originally published in Science Express on 3 September 2009
Science 9 October 2009:
Vol. 326. no. 5950, pp. 257 - 263
DOI: 10.1126/science.1179050
Prev | Table of Contents | Next

Research Articles

Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses

Ido Amit,1,2,3,4 Manuel Garber,1,* Nicolas Chevrier,2,3,* Ana Paula Leite,1,5,* Yoni Donner,1,* Thomas Eisenhaure,2,3 Mitchell Guttman,1,4 Jennifer K. Grenier,1 Weibo Li,2,3 Or Zuk,1 Lisa A. Schubert,6 Brian Birditt,6 Tal Shay,1 Alon Goren,1,7 Xiaolan Zhang,1 Zachary Smith,1 Raquel Deering,2,3 Rebecca C. McDonald,2,3 Moran Cabili,1 Bradley E. Bernstein,1,3,7 John L. Rinn,1 Alex Meissner,1 David E. Root,1 Nir Hacohen,1,2,3,{dagger},{ddagger} Aviv Regev1,4,8,{ddagger}

Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data but have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We applied this approach to derive regulatory networks that control the transcriptional response of mouse primary dendritic cells to pathogens. Our approach revealed the regulatory functions of 125 transcription factors, chromatin modifiers, and RNA binding proteins, which enabled the construction of a network model consisting of 24 core regulators and 76 fine-tuners that help to explain how pathogen-sensing pathways achieve specificity. This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells.

1 Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA.
2 Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA.
3 Harvard Medical School, Boston, MA 02115, USA.
4 Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
5 Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
6 NanoString Technologies, 530 Fairview Avenue N., Suite 2000, Seattle, WA 98109, USA.
7 Molecular Pathology Unit and Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA 02129, USA.
8 Howard Hughes Medical Institute.

* These authors contributed equally to this work.

{ddagger} These authors contributed equally to this work.

{dagger} To whom correspondence should be addressed. E-mail: nhacohen{at}partners.org

Read the Full Text


THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
2009: Signaling Breakthroughs of the Year.
E. M. Adler (2010)
Science Signaling 3, eg1
   Abstract »    Full Text »    PDF »
Toward a Systems-Level Analysis of Infection Biology: A New Method for Conducting Genetic Screens in Human Cells.
S. A. Stanley and D. T. Hung (2009)
Science Translational Medicine 1, 11ps13
   Full Text »    PDF »


To Advertise     Find Products

Science. ISSN 0036-8075 (print), 1095-9203 (online)