Nodes Links

1. Different types of Biological Networks Network Metabolic Protein Interaction Transcriptional Nodes Links Transcription factor Target genes Metabolites Proteins Enzymatic conversion Transcriptional Interaction Physical Interaction Interaction Protein-Protein Protein-DNA Protein-Metabolite A A A A B B B B

2. 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?

3. Finding Local properties of Biological Networks: Motifs

4. Finding Local properties of Biological Networks: Motifs

5. Finding Local properties of Biological Networks: Motifs

6. Finding Local properties of Biological Networks: Motifs

7. Finding Local properties of Biological Networks: Motifs • What are these motifs? • What biological relevance they have?

8. 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

9. Positive autoregulation Fast time-rise of protein level Negative autoregulation Stable steady state [protein] [protein] time time Autoregulatory loop What is the effect of Autoregulatory loops on gene expression levels?

10. X Y X Y Z Z Three-node loops There are 13 possible structures with 3 nodes • But in biological networks you can find only 2! Feed forward loop Feedback loop

11. Feed Forward loops

12. Coherent Feed Forward Loop in flagella biosynthesis A transcription coherent FFL motif ensures That flagella is synthesized only under appropriate conditions

13. Incoherent Feed Forward Loop in sporulation A transcription incoherent FFL motif produces transient gene expression

14. X Y Z Feed Back Loops in circadian expression Feed back loops can produce oscillation in gene expression The Drosophila CWO gene Kadener 2007, Genes and Dev.

15. 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).

16. Single Input Module (SIM) • The SIMs can generate temporal programs of expression: Last-In First-Out (LIFO) Program

17. LIFO Program in ArginineBiosynthesis

18. First-In First-Out (FIFO) Program Kxz1 Kxz2 [X] Kxz3 Kxz3 Kxz2 [Y] Kxz1 [Z1] [Z2] [Z3] Kxz1>Kxz2>Kxz3 K’xz1<K’xz2<K’xz3 Time

19. Where SIMs meet FFLs   Two interconnected SIMs can be viewed as a multi output FFL

20. Multi-input FFL in Neuronal Networks Noxious Chemicals Nose Touch Nose Touch FLP ASH AVD AVA Backward movement

21. Dense Overlapping Regulon (DOR) X1 X2 Y1 Y2 The DORs are more dense than randomly expected

22. FFLs and SIMs are integrated within DORs How do Network Motifs Integrate? A Master Regulators Layer (lots of Auto-Reg.) A single DOR Layer The E.coli Transcription Network (partial)

23. 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