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PMID: 17420474 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Validation Study

Combinatorial RNAi for quantitative protein network analysis.

Sahin O, Löbke C, Korf U, Appelhans H, Sültmann H, Poustka A, Wiemann S, Arlt D

Abstract

The elucidation of cross-talk events between intersecting signaling pathways is one main challenge in biological research. The complexity of protein networks, composed of different pathways, requires novel strategies and techniques to reveal relevant interrelations. Here, we established a combinatorial RNAi strategy for systematic single, double, and triple knockdown, and we measured the residual mRNAs and proteins quantitatively by quantitative real-time PCR and reverse-phase protein arrays, respectively, as a prerequisite for data analysis. Our results show that the parallel knockdown of at least three different genes is feasible while keeping both untargeted silencing and cytotoxicity low. The technique was validated by investigating the interplay of tyrosine kinase receptor ErbB2 and its downstream targets Akt-1 and MEK1 in cell invasion. This experimental approach combines multiple gene knockdown with a subsequent quantitative validation of reduced protein expression and is a major advancement toward the analysis of signaling pathways in systems biology.

MeSH Terms
Cell Line, Tumor Combinatorial Chemistry Techniques Humans Proteins/analysis,genetics RNA Interference RNA, Small Interfering/genetics Receptor Cross-Talk/physiology Signal Transduction/physiology Systems Biology
Chemicals
Proteins RNA, Small Interfering
Authors & Affiliations
8 authors, click to expand affiliations / ORCID
Sahin Ozgür
Division of Molecular Genome Analysis, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany.
Löbke Christian
Korf Ulrike
Appelhans Heribert
Sültmann Holger
Poustka Annemarie
Wiemann Stefan
Arlt Dorit
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Article Info
Journal
Proceedings of the National Academy of Sciences of the United States of America
Abbr.
Proc Natl Acad Sci U S A
ISSN
0027-8424
Published
2007-04-17
Epub
2007-00-09
Pages
6579-84
Language
English
Region
United States
NLM ID
7505876
PMCID
PMC1849961
Subset
IM
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