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

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

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)

Method (cont’d)

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

Experiment Overview (cont’d)

Signal pathway of TGFβ

Experiment # 1 Purpose: verify the protein post-translation modifications (PTMs) i

n Samd pathway using LUMIER Regulates the dynamics of PPI network to control signal transduct

ion Bait Smad4 (Smad4-RL) Prey Flag-Smad2 (2SA) Findings

1. Association between Smad4-RL &Flag-Smad2 with TGFβ signal

2. Association between TGFβ Type I Receptor & Smad2 with TGFβ signal

Similar finding also appears when swapping the bait and prey

(mutants)

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%

Experiment # 2 (cont’d) Resulting static network

is scale-free network (power law degree distribution) Has possible hierarchical modularity

clustering coefficient

Experiment # 2 (cont’d)

Resulting dynamic network Interactions between Smad2 and Smad4 With absence/presence of TGFβ signals

The movie

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

Repeated 2 means clustering binary tree structure

Baits

Prays

SOM

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

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

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

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

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

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