High-throughput two-hybrid analysis

被引:113
作者
Fields, S
机构
[1] Univ Washington, Howard Hughes Med Inst, Dept Genome Sci, Seattle, WA 98195 USA
[2] Univ Washington, Howard Hughes Med Inst, Dept Med, Seattle, WA 98195 USA
关键词
computational methods; Plasmodium falciparum; protein-protein interaction; proteomics; yeast;
D O I
10.1111/j.1742-4658.2005.04973.x
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The two-hybrid method detects the interaction of two proteins by their ability to reconstitute the activity of a split transcription factor, thus allowing the use of a simple growth selection in yeast to identify new interactions. Since its introduction about 15 years ago, the assay largely has been applied to single proteins, successfully uncovering thousands of novel protein partners. In the last few years, however, two-hybrid experiments have been scaled up to focus on the entire complement of proteins found in an organism. Although a single such effort can itself result in thousands of interactions, the validity of these high-throughput approaches has been questioned as a result of the prevalence of numerous false positives in these large data sets. Such artifacts may not be an obstacle to continued scale-up of the method, because the classification of true and false positives has proven to be a computational challenge that can be met by a growing number of creative strategies. Two examples are provided of this combination of high-throughput experimentation and computational analysis, focused on the interaction of Plasmodium falciparum proteins and of Saccharomyces cerevisiae membrane proteins.
引用
收藏
页码:5391 / 5399
页数:9
相关论文
共 55 条
[1]   The third dimension for protein interactions and complexes [J].
Aloy, P ;
Russell, RB .
TRENDS IN BIOCHEMICAL SCIENCES, 2002, 27 (12) :633-638
[2]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[3]   Predicting protein complex membership using probabilistic network reliability [J].
Asthana, S ;
King, OD ;
Gibbons, FD ;
Roth, FP .
GENOME RESEARCH, 2004, 14 (06) :1170-1175
[4]   Analyzing yeast protein-protein interaction data obtained from different sources [J].
Bader, GD ;
Hogue, CWV .
NATURE BIOTECHNOLOGY, 2002, 20 (10) :991-997
[5]   Network biology:: Understanding the cell's functional organization [J].
Barabási, AL ;
Oltvai, ZN .
NATURE REVIEWS GENETICS, 2004, 5 (02) :101-U15
[6]   A protein linkage map of Escherichia coli bacteriophage T7 [J].
Bartel, PL ;
Roecklein, JA ;
SenGupta, D ;
Fields, S .
NATURE GENETICS, 1996, 12 (01) :72-77
[7]  
Boser B. E., 1992, Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory, P144, DOI 10.1145/130385.130401
[8]   THE 2-HYBRID SYSTEM - A METHOD TO IDENTIFY AND CLONE GENES FOR PROTEINS THAT INTERACT WITH A PROTEIN OF INTEREST [J].
CHIEN, CT ;
BARTEL, PL ;
STERNGLANZ, R ;
FIELDS, S .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1991, 88 (21) :9578-9582
[9]   Protein interactions - Two methods for assessment of the reliability of high throughput observations [J].
Deane, CM ;
Salwinski, L ;
Xenarios, I ;
Eisenberg, D .
MOLECULAR & CELLULAR PROTEOMICS, 2002, 1 (05) :349-356
[10]   Bridging structural biology and genomics: assessing protein interaction data with known complexes [J].
Edwards, AM ;
Kus, B ;
Jansen, R ;
Greenbaum, D ;
Greenblatt, J ;
Gerstein, M .
TRENDS IN GENETICS, 2002, 18 (10) :529-536