Report: High-Throughput Mapping of a Dynamic Signaling Network in Mammalian Cells

1. Report: High-Throughput Mapping of a Dynamic Signaling Network in Mammalian Cells Miriam Barrio-Rodiles and Kevin R. Brown et. al.Science Vol 307 Mar 11 2005 Present by Alex Lei10/3/2007

2. Introduction • Why Dynamic protein-protein interaction network (PPI)? • Understand the protein functions • Understand the formations of the protein complexes • Understand the signal transduction pathways • Dictate the timing and intensity of network outputs • Most systematic mapping technology focuses on building static PPIs in simple organisms e.g. C. elegans, D. melanogaster etc. • Develop an automatic high-throughput method • Systematically map PPIs in mammalian cells • Ability to construct dynamic PPI

3. Method • Known as LUMIER (luminescence-based mammalian interactome mapping) • Three components: • Bait  Protein of interest fused with Renilla luciferase enzyme (RL) • Prey  mammalian cells with flag-tagged partners • Antibody  use antibody against flag to create precipitates of the protein complex (immunoprecipiates)

4. Method (cont’d)

5. Experiment Overview • Experiment focus --- cell signaling of TGFβ superfamily • Growing factor in metazoans (multi-cell organisms) • Skin cells (Healing wounds) • Bone cells (Bone formations) • Regulates epithelial-to-mesenchymal transition process (EMT) • Extracellutar molecules that triggers a series of processes

6. Experiment Overview (cont’d) • Signal pathway of TGFβ

7. Experiment # 1 • Purpose: verify the protein post-translation modifications (PTMs) in Samd pathway using LUMIER • Regulates the dynamics of PPI network to control signal transduction • Bait  Smad4 (Smad4-RL) • Prey  Flag-Smad2 (2SA) • Findings • Association between Smad4-RL &Flag-Smad2 with TGFβ signal • Association between TGFβ Type IReceptor & Smad2 with TGFβ signal • Similar finding also appears when swapping the bait and prey (mutants)

8. Experiment # 2 • Purpose: map the TGFβ PPI network automatically • Method: • Baits  core members of the pathway with RL-tagged (total 23, some with different conditions) • Preys  3 x flag-tagged cDNAs from the FANTOM1 library (total 518) • Each protein is expressed in the mammalian cells • Total about 12,000 LUMIER experiments • Robotic platform to perform automated LUMIER • Measure by LUMIER intensity ratio (LIR) --- # of fold changes over the control • LIR cutoff = 3 • False-negative 36% • False-positive 20%

9. Experiment # 2 (cont’d) • Resulting static network • is scale-free network (power law degree distribution) • Has possible hierarchical modularity clustering coefficient

10. Experiment # 2 (cont’d) • Resulting dynamic network • Interactions between Smad2 and Smad4 • With absence/presence of TGFβ signals • The movie

11. Experiment # 3 • Purpose: Identify novel connections with the TGFβ pathway • Method: • Apply clustering techniques on the TGFβ LUMIER dataset • Called binary tree-structured vector quantization (BTSVQ) • K means clustering • Self-organizing map Baits SOM Prays Repeated 2 means clustering  binary tree structure

12. Experiment # 3 (cont’d) ---background • K means clustering • Partition data into K clusters • Randomized initialization for K class centroid • Assign each item to the nearest centroid • For each class 1 to K Calculate the centroid Calculate distance from centroid to each item Assign each item to the nearest centroid • Repeat until no items are re-assigned (convergence) or another stop criterion is met K = 3

13. Experiment # 3 (cont’d) ---background • SOM • The SOM works both as a projection (Visualization) method and a clustering method • SOM is a neural network approach that uses an unsupervised training algorithm through a process called self-organizing. • Maps high-dimensional input data onto a low dimensional (usually two-dimensional) output space while preserving the topological relationships between the input data

14. Experiment # 3 (cont’d) • Results • PAK1 and TGFβ fall into the same cluster (with similar SOM patterns) • PAK family involves in regulating cytoskeletal dynamics, cell motility, survival and proliferation • No physical association with TGFβ pathway components have been reported • Further investigation on the clustering results show that PAK1-binding protein may relate to Occludin (OCLN) • OCLN is a tight junction accessory protein that is associated with the cell polarity network • Verify the interaction between the TGFβ receptors and the PAK1, OCLN is needed

15. Experiment # 3 (cont’d) • By doing a set of experiments on the mammary gland epithelial cells (NMuMG) • Discovered OCLN interacts with type I and II receptors with TGFβ signal • Discovered OCLN helps the localization of type I receptor • Located the interacting region of OCLN using LUMIER (extracellular loop 2) • Summaries from previous experiments, • OCLN regulates type I receptor localizations to tight junctions • Vital to the TGFβ-dependent dissolution of tight junctions during epithelial-to-mesenchymal transition (EMT) • Both OCLN and PAK1 regulates TGFβ pathway

16. Conclusion • Develop an automated high-throughput technology to map PPI systematically in mammalian cells • Disadvantages • Cannot measure the concentration of the flag-tagged preys in high-throughput LUMIER • Prone to noise and false positive when the LIR is low • Discover novel linkage between OCLN, PAK1 and TGFβ in the regulatory pathway

17. Reference • High-Throughput Mapping of a Dynamic Signaling Network in MammalianCells Miriam Barrios-Rodiles, Kevin R. Brown, Barish Ozdamar, Rohit Bose,Zhong Liu, Robert S. Donovan, Fukiko Shinjo, Yongmei Liu, Joanna Dembowy,Ian W. Taylor, Valbona Luga, Natasa Przulj, Mark Robinson, Harukazu Suzuki,Yoshihide Hayashizaki, Igor Jurisica, and Jeffrey L. Wrana   Science 11 March 2005 307: 1621-1625 • Transcriptional control by the TGF- /Smad signaling system Joan Massagué and David Wotton EMBO Journal Vol 19 No 8 pp 1745-1754, 2000 • Lecture slides from Alexander Weiss • Lecture slides from Professor Zhang