1. Regulatory networks 10/29/07

3. Definition of a module Module here has broader meanings than before. A functional module is a discrete entity whose function is separable from those of other molecules. –Examples: ribosome, sensory system for food in bacteria, etc.

4. (Hartwell et al. 1999)

5. Network behavior Amplification Adaptation Robustness Insulation Error correction Conincidence detection etc Hartwell et al. 1999

6. Types of regulatory networks Transcriptional network Protein-protein network Genetic-interaction network Metabolic network

7. A cell-cycle regulatory network in yeast A regulator is transcriptionally controlled by another regulator. Sometime a regulator controls its own regulation. The cell-cycle gene transcription is NOT controlled by a single regulator but the network as a whole. Lee et al. 2002

8. Transcription network in yeast Many genes are regulated by multiple regulators. Many regulators regulate multiple genes. Lee et al. 2002

9. Different cellular processes are connected Lee et al. 2002 Cell cycle Developmental processes DNA/RNA/protein biosynthesis Environmental response Metabolism

10. Protein-protein interactions

12. Methods for probing protein-protein interactions Protein affinity chromatography Western blotting Yeast two-hybrid Mass spectrometry

13. Protein affinity chromatography Phizicky and Fields 1995

14. Western blot

15. Yeast two-hybrid system

16. Mass spectrometry Source: http://www.sanger.ac.uk

17. Yeast protein-protein interaction network Jeong et al. 2001

18. A human protein-protein interaction network 4456 bait 5632 prey 3186 interactions Stelzl et al. 2005

19. Genetic interactions Genetic interaction: The collaboration of several different genes in the production of one phenotypic character (or related group of characters). Synthetic lethal: neither gene is essential, but the organism dies when both are deleted. –Example: ERG2 and ERG24 are yeast sterol biosynthetic genes.

20. Tong et al. 2001

21. A genetic-interaction network in yeast Tong et al. 2005

22. Metabolic network A metabolic network is the complete set of metabolic and physical processes that determine the physiological and biochemical properties of a cell. As such, these networks comprise the chemical reactions of metabolism as well as the regulatory interactions that guide these reactions.

23. Villas-Boas et al. 2005

24. Network motifs (Milo et al. 2002) Basic idea: identify recurring inter-connection patterns in complex networks. These patterns can be viewed as the basic building blocks of a network and may have special functions.

25. All possible three-node connected subgraphs Question: which graphs are used more often than randomly expected? (Milo et al. 2002)

26. Generate randomized networks real network

27. Generate randomized networks real network

28. Generate randomized networks real network

29. Generate randomized networks real network

30. Generate randomized networks real network random network 1 random network 2

31. Rules for randomization An edge can be added, removed, redirected, or reversed. Each node contains the number of incoming and outgoing edges as original network, so that the basic probability properties are perserved.

32. Generate randomized networks real network random network 1 random network 2

33. Occurance of the feed-forward loop motif in E. coli transcription subnetworks feedforward loop motif

34. Occurance of the feed-forward loop motif in E. coli transcription subnetworks feedforward loop motif (Milo et al. 2002)

36. Network motifs in transcription network in yeast auto-regulationmulti-componentfeed-forward regulator chain single input modulemulti-input module Lee et al. 2002

37. Are network motifs evolutionarily conserved Basic idea: If there is evolutionary pressure to select specific network motifs, then their components should be evolutionarily conserved and have identifiable orthologs in other species. A motif incidence is conserved if all its proteins are conserved. Evaluate the statistical significance by random assignment of orthologous proteins to different nodes. Wuchy et al. (2003)

38. Results (Wuchy et al. 2003)7

39. Large motifs tend to be conserved as a whole. (Wuchy et al. 2003)

40. Most real biological networks are scale-free Barabasi and Oltval 2004

41. Network topology

42. c node edge

43. Network topology Degree of a node = Number of edges that start from the node.

44. Random network The probability for connecting any pair of nodes is equal. The node degrees follow a Poisson distribution.

45. Scale-free network The node degree distribution obeys a power law: k  There are a few hubs which are highly connected nodes. Most nodes are poorly connected.

46. Many biological networks are scale-free protein-protein network in human Network for co-expressed genes in yeast (Stelzl et al. 2005)(van Noort et al. 2004)

47. But the TF network is not scale-free (Lee et al. 2002)

48. Reading list Hartwell et al. 1999 –Call for “modular biology”. Very influential among biologists. Precursor for “systems biology”. Milo et al. 2002 –Define network motif Wuchy et al. 2003 –Evolution of network motif Barabasi and Oltvai 2004 –Review of network biology