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 Color Significance

Green Activation links

Red Inhibition links

Blue Neutral 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!!