Modularization of Signal Transduction Pathways: detecting the trend of development among various species

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$De Machine Intelligence Unit Indian Statistical Institute 203 B. T. Road, Kolkata- 700108 West Bengal, India {losiana_t, rajat}@isical.$

1 Modularization of Signal Transduction Pathways: detecting the trend of development among various species By Losiana Nayak & Rajat K. De Machine Intelligence Unit Indian Statistical Institute 203 B. T. Road, Kolkata West Bengal, India {losiana_t,

2 Overall Goal To create valid partitions in Signal Transduction Pathways (STPs) to study, analyze and model them

3 What is a STP? Signal: any communication that encodes a message Signal Transduction: conversion of a signal from extracellular environment to functional changes within the cell Signal transduction pathway: series of steps that enable signal transmission through physical barriers like biological membranes

5 Why Study STP? Abnormal signal transduction is responsible for many diseases. Ex: Cancer (uncontrolled cell growth) Atherosclerosis (thickening of the walls of arteries) Rheumatoid arthritis (structural changes in lining of joints) Ulcerative colitis and Crohn's Disease (structural changes in the bowel wall)

6 Difficulty in study of STP! Signal transduction pathways are complex biochemical networks of biomolecules and chemical compounds. Each member s function is dependent on other intra and inter network member(s). Study of such a network s function and its relation with other signaling networks is quite difficult as a whole. So a sound strategy to study these complex networks is to decompose them into smaller units or modules.

7 Existing Algorithms Graph partitioning Algorithms Require partition number and size Rigid Community Finding Algorithms Consider Modularity Recognize naturally existing partitions Flexible can t create partitions when natural partitions don t exist

8 Modularization Process, which divides a pathway into smaller units, called modules A module can be defined as a subset of the original network, that tends to self-sufficiency have minimal dependency on the rest part of the network

9 Algorithm starts with the node having maximum number of the relations in a given network A module is created initially by including immediate neighbors of the starting node Members are included or deleted from a module based on the complexity value After completion of one module, construction of next module starts Process is repeated till all the nodes of the network get included into one of the modules

10 M O D U L A R I Z A T I O N FOR C=3 Human MAPK Signaling Pathway

11 We are getting more no. of biologically significant modules for c=3 with minimum no. of singleton and small modules. Modules GRB2, Ras and ERK divide effectively the classic MAPK pathway Modules MEKK1, MKK4, MKK7 and JNK are constituting JNK pathway p38 pathway is divided into modules p38, ASK1 and TAK1

12 There is a gradual development in MAPK pathway starting from Dog to Human and Mouse.

13 Modularization for c = 3, 4 Human calcium signaling pathway with 4 biologically significant modules marked with black lines for c = 3 and 4.

14 Modules obtained from human calcium signalling pathway for different c- values are given for comparison. Columns N and R contain no. of nodes and relations present in a module respectively

15 Human Wnt Signaling Pathway modularized for c=3

16 Modules of human Wnt Signaling Pathway The cell membrane portion of the canonical Wnt pathway is included in module WNT16 The steps of the canonical Wnt pathway taking place around the PP2AC protein scaffold is divided into modules (DVL1)1, AXIN1 and CTNNB1 The part of canonical Wnt pathway around and inside nucleus is enclosed in module LEF1 Module (DVL1)2 is made up of the Planar cell polarity pathway Module PLCB1 is comprised of the Wnt/Ca2+ pathway We cannot associate any biological significance to the very small Tp53 module

18 Innovative Aspects A complex biological system can be divided into simpler partitions for further analysis Modularization algorithm provides better modules than the existing graph partitioning and community finding algorithms Species-wise module comparisons establish trend of development and pathway sophistication among different species The algorithm is a way to delve deeper into complex systems.

19 THANK YOU

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