Formation of Regulatory Patterns During Signal Propagation in a Mammalian Cellular Network ROBERT D. BLITZER, RAVI IYENGAR.

Slides:



Advertisements
Similar presentations
Organizational Environment for Knowledge Management
Advertisements

Cell Communication Cells need to communicate with one another, whether they are located close to each other or far apart. Extracellular signaling molecules.
Introduction to Neural Networks
Homeostasis A condition in which the internal environment of the body remains relatively constant despite changes in the external environment. Examples.
NEUROBIOKIMIA: ASPEK BIOMOLEKULER DARI MEMORI Oleh Mohammad hanafi.
Network biology Wang Jie Shanghai Institutes of Biological Sciences.
An Intro To Systems Biology: Design Principles of Biological Circuits Uri Alon Presented by: Sharon Harel.
Using the Crosscutting Concepts As conceptual tools when meeting an unfamiliar problem or phenomenon.
D ISCOVERING REGULATORY AND SIGNALLING CIRCUITS IN MOLECULAR INTERACTION NETWORK Ideker Bioinformatics 2002 Presented by: Omrit Zemach April Seminar.
Cell Communication-I Pin Ling ( 凌 斌 ), Ph.D. Department of Microbiology & Immunology, NCKU ext 5632; Reference: “Mechanisms of.
CHAPTER 9 LECTURE SLIDES
Cellular Communication. Chemical messages which elicit a response in cells serve as a form of communication between cells Found in all cells Similar in.
Seminar in Bioinformatics, Winter 2011 Network Motifs
ECE Chapter One.
HOMEOSTASIS The maintenance of a relatively stable internal environment in the face of changes in either the external or internal environment.
The Hardwiring of development: organization and function of genomic regulatory systems Maria I. Arnone and Eric H. Davidson.
Introduction to Physiology and Homeostasis
Homeostasis. Homeostasis The term is derived from the Greek word meaning ‘to stay the same’The term is derived from the Greek word meaning ‘to stay the.
Part 1 Biology 12.  An integral part of your body’s communication system.  It plays an important role in the smooth functioning of the body.  The nervous.
Basic Life processes (certain processes that distinguish organisms (living things) from non-living things Metabolism (the sum of all the chemical processes.
Synthetic Mammalian Transgene Negative Autoregulation Harpreet Chawla April 2, 2015 Vinay Shimoga, Jacob White, Yi Li, Eduardo Sontag & Leonidas Bleris.
Vertebrate Models of Learning
HOMEOSTASIS – REGULATION OF INTERNAL CONDITIONS Patterns of internal regulation in animals Principles of regulatory systems Signaling in internal regulation.
Introduction to Neural Networks. Neural Networks in the Brain Human brain “computes” in an entirely different way from conventional digital computers.
Molecular mechanisms of memory. How does the brain achieve Hebbian plasticity? How is the co-activity of presynaptic and postsynaptic cells registered.
Neural Plasticity: Long-term Potentiation Lesson 15.
synaptic plasticity is the ability of the connection, or synapse, between two neurons to change in strength in response to either use or disuse of transmission.
Regulatory Mechanisms in Animals. Regulatory Pathways Animals need to communication systems to regulate their functions effectively. The two systems which.
Cell Communication Chapter 9. Please note that due to differing operating systems, some animations will not appear until the presentation is viewed in.
York College of Pennsylvania
Meet Patel and Auriana Semans AP Biology
Cytokines, Growth Factors and Hormones SIGMA-ALDRICH.
Social Network Analysis Prof. Dr. Daning Hu Department of Informatics University of Zurich Mar 5th, 2013.
Mechanisms for memory: Introduction to LTP Bailey Lorv Psych 3FA3 November 15, 2010.
Quantitative Models of Mammalian Cell Signaling Pathways Ravi Iyengar, Ph.D. Department of Pharmacology and Systems Therapeutics Mount Sinai School of.
Microarrays.
Cell Communication.
Homeostasis Balancing the internal environment. External vs. Internal Environment What is the difference?
Li Chen 4/3/2009 CSc 8910 Analysis of Biological Network, Spring 2009 Dr. Yi Pan.
Homeostasis Balancing the internal environment. External vs. Internal Environment What is the difference?
Cell Communication.
Cell Communication Chapter Cell Communication: An Overview  Cells communicate with one another through Direct channels of communication Specific.
Graphic Organizers. Introduction Definition Effectiveness Resources.
A role for cAMP. Desensitization from persistent signal.
Cell Communication Chapter 9.
 Signaling molecules that function within an organism to control metabolic processes within cells, the growth and differentiation of tissues, the synthesis.
© 2011 Pearson Education, Inc. Lectures by Stephanie Scher Pandolfi BIOLOGICAL SCIENCE FOURTH EDITION SCOTT FREEMAN 17 Control of Gene Expression in Bacteria.
Homeostasis A condition in which the internal environment of the body remains relatively constant despite changes in the external environment. Examples.
Introduction to Homeostasis
8.2 Structures and Processes of the Nervous System
Development of a Signaling Pathway Map for the FXM Gil Sambrano, Lily Jiang, Madhu Natarajan, Alex Gilman, Adam Arkin University of California San Francisco,
Feedback systems for controlling body functions
Universe Tenth Edition Chapter 25 Cosmology: The Origin and Evolution of the Universe Roger Freedman Robert Geller William Kaufmann III.
Raster Data Models: Data Compression Why? –Save disk space by reducing information content –Methods Run-length codes Raster chain codes Block codes Quadtrees.
1 Lesson 12 Networks / Systems Biology. 2 Systems biology  Not only understanding components! 1.System structures: the network of gene interactions and.
Intracellular Signal Transduction Pathways and Cascades.
Chapter One Part 1 Introduction to Anatomy and Physiology Characteristics of Life What is Anatomy and Physiology Maintenance of Life.
BCB 570 Spring Signal Transduction Julie Dickerson Electrical and Computer Engineering.
Long Term Potentiation
An Introduction to Anatomy and Physiology
Applications of graph theory in complex systems research
Cell Communication.
Neurons, Synapses, and Signaling
Ahnert, S. E., & Fink, T. M. A. (2016). Form and function in gene regulatory networks: the structure of network motifs determines fundamental properties.
Homeostasis A condition in which the internal environment of the body remains relatively constant despite changes in the external environment. Examples.
Epigenetic Mechanisms in Cognition
Signaling Networks Cell
The Role of Neuronal Complexes in Human X-Linked Brain Diseases
Volume 133, Issue 4, Pages (May 2008)
Glutamatergic Signaling in the Central Nervous System: Ionotropic and Metabotropic Receptors in Concert  Andreas Reiner, Joshua Levitz  Neuron  Volume.
Presentation transcript:

Formation of Regulatory Patterns During Signal Propagation in a Mammalian Cellular Network ROBERT D. BLITZER, RAVI IYENGAR

Introduction  A mammalian cell - Considered as the central signaling network is connected to various cellular machines.  These cellular machines namely – transcriptional, translational, motility and secretory are responsible for phenotypic functions  They form functional local networks  The central signaling unit also receives and processes signals from extracellular entities such as hormones or neurotransmitters

Introduction  Different pathways interact to form networks and small scale regulatory configurations.  These regulatory motifs  Decode signal duration and strength  Process information  These regulatory motifs play an important role in determining the cellular choice between homeostasis and plasticity.

Outline  The authors identify the regulatory features that emerge during such information flow in a simplified representation of the mammalian hippocampal CA1 neuron.  The CA1 neuron is represented as a set of interacting components.  The components make up a network of signaling pathways that connect various cellular machines

Arrow ColorSignificance GreenActivation links RedInhibition links BlueNeutral links Visualization of the mammalian neuronal cellular network

Ligand induced signal study  Study was conducted on signal propagation that resulted from ligand occupancy of receptors  A series of sub networks originating from nodes(ligands)were analyzed  The signals initiated due to ligand-receptor interactions propagate to their downstream effectors  The analysis of the emergent sub networks showed a discernible pattern for various ligands

Contd.. 1.When the signal originating from any ligand progressed through 15 steps most of the network seemed engaged. 2.However, for each individual ligand the whole network was never fully effected. ( with a few nodes with single directed outgoing interactions not engaged)

In depth study - Key regulators of plasticity in CA1 neuron  Glutamate, NE(Norepinephrine) and BDNF(Brain derived neurotropic factor) are key regulators of plasticity in the hippocampal CA1 neurons  The networks initiated due to these three ligands were studied in detail.

In the early stages, Glutamate influenced more links and nodes than NE and BDNF

Regulatory motifs  Regulatory motifs were formed as signals propagated from ligands.  Positive feedback loops – Promote the persistence of signals and serve as information storage devices  Negative feedback loops - Limit the signal propagation  Scaffold motifs – Their presence indicate the mechanism for local clustering and represent spatial specification of information flow.  Positive Feed Forward loops – They provide redundant set of pathways for information flow  Negative Feed Forward Loops – They function as gates  Bi-fans – They regulate signal propagation by acting as signal sorters, filters and synchronizers

CA1 Receptors and Effectors  In the CA1 neuron, signals from the receptors affect major effectors such as  AMPA  CREB  Sub networks extending from Glutamate, NE and BDNF to AMPA and CREB were analyzed by varying the number of steps required to reach the effectors

Effect of the ligands on AMPAR and CREB  The no of nodes engaged per step was nearly linear for all the ligands – glutamate, NE, BDNF  Analysis of these sub networks indicated that even the most highly connected nodes only used some of their links to function within the preferred paths

Contd.. Glutamate - CREB & BDNF – CREB : The Negative and Positive motifs are evenly balanced through the nine steps. NE – CREB: Positive FBL and FFL are more abundant than the negative ones.

Contd.. Glutamate - AMPAR & BDNF – AMPAR : The Negative and Positive motifs are evenly balanced through the nine steps. NE – AMPAR: Positive FBL and FFL are more abundant than the negative ones.

Local Clustering  The sub networks upstream of CREB and AMPAR were analyzed  The extent of clustering was different  2 steps above CREB the CC was high(0.53)  By 2 to 4 steps upstream both effectors had CC and GC above the average values for entire network  This indicates extensive local communication between nodes.  Extensive local communication may provide homeostatic regulation of these effectors

Highly connected nodes  The impact of highly connected nodes was evaluated by generating sub networks by the progressive inclusion of nodes  The system was initially highly fragmented with 63 islands  After including nodes up to 21 connections, the network became one single island  At this point, the nodes which are crucial components for LTP in the hippocampal neurons were not included

Observations  The nodes with more than 21 links per node included four major proteins - MAPK, CaMKII, PKA, PKC  The authors say that such highly connected nodes might contribute to regulatory motifs  The contributions of specific nodes to the formation of different motifs varied  Nearly 65% of the Scaffolding motifs were formed before including enough nodes for formation of single island  Only 35% of the FBL, FFL and 20% of the bi-fan motifs were formed

Contd..  PKA and PKC contribute to 60% of the five component feedback loops  PKC and other highly connected nodes favored the emergence of positive motifs  These observations suggest that  Highly connected nodes may promote formation of regulatory motifs  These motifs allow persistence of information and thus facilitate state change when external signals are received

DIP  Maps were developed to represent the regulatory topology that the analyses identified  DIP – Density of Information Processing 1.This measure identifies the intensity and position of the information processing activities 2.Each ligand shows a “hot zone” where extensive information processing may occur

Regulatory motifs in chemical space 1.Five maps corresponding to the different cellular machines were generated. 2.They indicate location of various regulatory motifs between extracellular ligands and cellular machines 3.The graph indicates a higher density of regulatory motifs in the middle of the maps This indicates that major portion of the information processing occurs in the center of the network

Result  At the end of analyses – The authors developed a model of 545 nodes and 1259 interactions representing the signaling pathways and cellular machines in the hippocampal CA1 neuron

Thank you!!