Predictive models of molecular machines involved in Caenorhabditis elegans early embryogenesis

Kristin C. Gunsalus, Hui Ge, Aaron J. Schetter, Debra S. Goldberg, Jing-Dong J. Han, Tong Hao, Gabriel F. Berriz, Nicolas Bertin, Jerry Huang, Ling-Shiang Chuang, Ning Li, Ramamurthy Mani, Anthony A. Hyman, Birte Sönnichsen, Christophe J. Echeverri, Frederick P. Roth (), Marc Vidal () and Fabio Piano ()
Additional contact information
Kristin C. Gunsalus: New York University
Hui Ge: Harvard Medical School
Aaron J. Schetter: New York University
Debra S. Goldberg: Harvard Medical School
Jing-Dong J. Han: Harvard Medical School
Tong Hao: Harvard Medical School
Gabriel F. Berriz: Harvard Medical School
Nicolas Bertin: Harvard Medical School
Jerry Huang: New York University
Ling-Shiang Chuang: New York University
Ning Li: Harvard Medical School
Ramamurthy Mani: Harvard Medical School
Anthony A. Hyman: Max Planck Institute of Molecular Cell Biology and Genetics
Birte Sönnichsen: Cenix BioScience GmbH
Christophe J. Echeverri: Cenix BioScience GmbH
Frederick P. Roth: Harvard Medical School
Marc Vidal: Harvard Medical School
Fabio Piano: New York University

Nature, 2005, vol. 436, issue 7052, 861-865

Abstract: Beating the system The early stages of embryogenesis in the nematode Caenorhabditis elegans are an ideal system in which to test the potential of ‘system-level’ approaches to understanding biological processes, as opposed to the conventional reductionist approach that focuses on individual enzymes. By integrating information on how proteins interact with each other, how genes are expressed and the effect of ‘knocking-down’ hundreds of genes, Gunsalus et al. have generated a string of models of molecular machines involved in driving early embryogenesis, and are able to propose functional links between these machines. Ten previously uncharacterized proteins were identified as significant in these pathways, showing how the systems can feed information back into single-reaction experiments.

Date: 2005
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DOI: 10.1038/nature03876

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