Nodes Links

Nodes

Links

Interaction

A

B

Network

Proteins

Physical Interaction

Protein-Protein

A

B

Protein Interaction

Metabolites

Enzymatic conversion

Protein-Metabolite

A

B

Metabolic

Transcription factorTarget genes

TranscriptionalInteraction

Protein-DNA

A

B

Transcriptional

Different types of Biological Networks

Finding Local properties of Biological Networks: Motifs

Network motifs are recurrent circuit elements.

We can study a network by looking at its parts (or motifs)

How many motifs are in the network?

Finding Local properties of Biological Networks: Motifs

Finding Local properties of Biological Networks: Motifs

Finding Local properties of Biological Networks: Motifs

Finding Local properties of Biological Networks: Motifs

What are these motifs? What biological relevance

they have?

Finding Local properties of Biological Networks: Motifs

Autoregulatory loop

The probability of having autoregulatory loops in a random network is ~ 0 !!!!.

Transcription networks: The regulation of a gene by its own product.

Protein-Protein interaction network: dimerization

Autoregulatory loop

Positive autoregulation Fast time-rise of protein

level

Negative autoregulation Stable steady state

time

[p

rote

in]

time

[p

rote

in]

What is the effect of Autoregulatory loops on gene expression levels?

Three-node loops

There are 13 possible structures with 3 nodes

Feed forward loop

X Y

Z

Feedback loop

X Y

Z

But in biological networks you can find only 2!

Feed Forward loops

Coherent Feed Forward Loop in flagella biosynthesis

A transcription coherent FFL motif ensuresThat flagella is synthesized only under appropriate conditions

Incoherent Feed Forward Loop in sporulation

A transcription incoherent FFL motif produces transient gene expression

Feed Back Loops in circadian expression

Feed back loops can produce oscillation in gene expression

X Y

Z The Drosophila CWO geneKadener 2007, Genes and Dev.

Power Heater

Thermostat

Temperature-

Single Input Module (SIMs)

The SIMs are common in sensory transcription networks:

Genes from a same Pathway (Arginine synthesis).

Genes responding to stress (DNA repair). Genes that assemble a same biological

machine (ribosomal genes).

Single Input Module (SIM)

The SIMs can generate temporal programs of expression:

Last-In First-Out (LIFO) Program

LIFO Program in ArginineBiosynthesis

First-In First-Out (FIFO) Program

Kxz1>Kxz2>Kxz3

K’xz1<K’xz2<K’xz3

Time

Kxz1

Kxz2

Kxz3

Kxz3

Kxz2

Kxz1

[X]

[Y]

]Z2[]Z3[

]Z1[

Where SIMs meet FFLs

Two interconnected SIMs can be viewed as a multi output FFL

Multi-input FFL in Neuronal Networks

FLP ASH

AVD

AVA

Nose Touch Noxious ChemicalsNose Touch

Backward movement

Dense Overlapping Regulon (DOR)

X1 X2

Y1 Y2

The DORs are more dense than randomly expected

How do Network Motifs Integrate?

The E.coli Transcription Network (partial)

A single DOR Layer

FFLs and SIMs are integrated within DORs

A Master Regulators Layer (lots of Auto-Reg.)

Summary

Network motifs can function in several biological processes (sensory systems,

development). different time scales (milliseconds, cell generations).

Network motifs can produce temporal programs (LIFO, FIFO, oscillation).

Different kinds of network may interact to generate regulation