Evolu&on of Cellular Interac&on Networks. Pedro Beltrao Krogan and Lim UCSF
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1 Evolu&on of Cellular Interac&on Networks Pedro Beltrao Krogan and Lim UCSF
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4 Point muta&ons Recombina&on Duplica&ons
5 Mutants
6 Mutants
7 Point muta&ons Recombina&on Duplica&ons Changes in protein- protein, protein- DNA interac&ons, etc
8 Cellular interac&on networks
9 Output Point muta&ons Recombina&on Duplica&ons Input Phenotypic changes Changes in protein- protein, protein- DNA interac&ons, etc
10 Fitness differences Output Point muta&ons Recombina&on Duplica&ons Input Phenotypic changes Changes in protein- protein, protein- DNA interac&ons, etc
11 Muta&on/Change Model Consequence Codon change in open reading frames Gene&c code Amino acid changes Amino acid changes Sta&s&cal energy poten&als Impact on protein structure and/or interac&ons Changes in reac&on kine&cs or interac&ons Network model Output Input Network response
12 2 short stories
13 Details
14 Evolutionary dynamics of: 1 Protein phosphorylation 2 Drug-gene interactions
15 Evolu&onary dynamics of phosphoryla&on Mass- spec phosphoproteomics 3 yeast species Exponen&ally growing yeast cells Protein extrac&on Trypsin digest Phosphopep&de enrichment Mass- spectrometry S. cerevisiae C.albicans S.pombe Site iden&fica&on With UCSF Mass Spec facility Beltrao et al. PLoS Bio 2009
16 Phosphoryla&on is poorly conserved Phosphoryla&on sites from 3 yeast species shows they are poorly conserved
17 Phosphoryla&on of func&onal modules is well conserved Pathway or complex Average number of phosphosites per protein (normalized for proteome coverage)
18 How is phosphoryla&on translated to func&on? How many phosphoryla&on sites are func&onal? How much of this change is neutral?
19 Currently known phosphoryla&on sites Species Phospho Phospho proteins sites H.sapiens M.musculus R. norvegicus X.laevis C.elegans D.melanogaster S.pombe S.cerevisiae C.albicans A.thaliana O.sa=va > phosphorylation sites
20 Func&onal consequence of phosphoryla&on Globular regions Unstructured regions + Regula&ng interfaces Regula&ng domain ac&vity Phosphoryla&on switches ~20% ~80%
21 Phosphoryla&on of interfaces Control of protein- protein interac&ons by regula&ng interfaces Define models for protein- protein interac&on interfaces (ex. S. cerevisiae): 100 Xray structures of complexes (PDB) 1200 homology models of interac&ons (GWIDD database) 2700 docking solu&ons (Mosca et al PLoS Comp 2009) Map phosphosites to models of interfaces Evaluate conserva&on of phosphoryla&on (site and func&on)
22 Phosphoryla&on of interfaces RDI1 Phosphorylated in S. cerevisiae and C. albicans CDC42 Phosphorylated in H.sapiens Phosphorylated residues are 20 Amino- acids apart in sequence
23 Conserva&on of func&on vs conserva&on of psites Phosphosite Interfaces with psites (xray) In S. cerevisiae In S. cerevisiae Conserved in another species by aln (+/- 5 pos) Conserved in another species Frac9on conserved All In interface Frac9on conserved Interfaces with psites (docking) Interfaces with psites (compara9ve modeling) Posi9onal conserva9on under- predicts conserva9on of func9on
24 Regula&on of domain ac&vity 1. Pool all phosphosites and map them to representa&ve structures of domain families 2. Look for sequence / structural enrichment
25 Protein kinase domain phosphoryla&on propensity Ac9va9on loop (50% of psites) Regulatory hot- spot
26 HSP70 domain Phosphoryla&on propensity Substrate binding region Region 2 ATPase region Region 1 p-value < Region 2 Region 1
27 Regulatory hot- spots in S. cerevisiae Hsp70 SSA1 7 cytosolic Hsp70 (SSA1-4, SSB1-2 and SSZ1) Mutants generated for SSA1: Region 2 Region 1 mutant 1: SSA1 T492A mutant 2: SSA1 T492D mutant 7: SSA1 T492A, S495A mutant 8: SSA1 T492D, S495D mutant 9: SSA1 T492A, T499A mutant 10: SSA1 T492D, T499D mutant 15: SSA1 T492A, S495A, T499A mutant 16: SSA1 T492D, S495D, T499D mutant 19: SSA1 T495A mutant 20: SSA1 T495D mutant 23: SSA1 T36A mutant 24: SSA1 T36D mutant 25: SSA1 S38A mutant 26: SSA1 S38D mutant 27: SSA1 T36A S38A mutant 28: SSA1 T36D S38D Pep&de binding domain ATPase domain Collabora&on with: Veronique Albanese, Frydman Stanford
28 Complementa&on assay for the mutants Region 2 None of the SSA1 mutants complement the null
29 Preliminary func&onal assays Region 2 SSA1 T492A T492D Interaction of the mutants with cochaperone SSE1 Cell morphology
30 Post- transla&onal switches Different PTMs tend to co- occur in the same proteins More than 75% of ubi proteins are also phosphorylated Different PTMs cluster within proteins Phosphoacceptor phosphoryla&on increases near Ubi sites Phosphosites near other PTMs are more conserved 2X more than average? Ongoing: ~2000 Ubiquitylation sites for H.sapiens
31 Summary: evolu&on of protein phosphoryla&on Regula&on by protein phosphoryla&on diverges quickly Phosphosites with predicted func&on are more likely to be conserved Phosphosites at interfaces Phosphosites near other PTMs (phospho- switches) Regulatory hot- spots Some evidence for neutral varia&on Conserva&on of interface phosphoryla&on despite divergence of site Co- evolu&on of phospho- switches
32 Drug-gene interactions (Chemogenomics)
33 Drug- gene interac&ons in S. cerevisiae and S. pombe Kapitzky L, Beltrao P et al. MSB 2010
34 Drug- gene scores are reproducible 438 S. pombe KOs 727 S. cerevisiae KOs X 21 compounds 2 technical replicates 2 biological replicates
35 Drug- gene interac&ons are poorly conserved
36 Drug- gene vs. Drug- module interac&ons
37 Drug- gene vs. Drug- module interac&ons Gold-standard drug-gene and drug-complex (functional) interactions obtained from STITCH database for S. cerevisiae S. cerevisiae Drug-gene predictions S. cerevisiae Drug-complex predictions S. cerevisiae plus S. pombe S. pombe data S. cerevisiae data S.cerevisiae liquid+agar S. cerevisiae plus S. pombe S. pombe data S. cerevisiae data Area under the ROC curve 0,5 0,6 0,7 0,8 0,9 0,5 0,6 0,7 0,8 0,9
38 Drug- gene interac&ons vs. Gene&c interac&ons S.pombe S.cerevisiae Gene&c int. Chemical gene&c int.
39 Summary: cross- species drug studies Drug- complex interac&ons more likely conserved than individual drug- gene interac&ons Combined cross- species improves predic&ons for drug mode- of- ac&on (MoA) Predicted MoA for 10 compounds (1 validated) Divergence of drug- gene interac&ons correlates with divergence of gene&c interac&ons What about drug combina&ons? (synergy)
40 Fitness differences Output Point muta&ons Recombina&on Duplica&ons Input Phenotypic changes Changes in protein- protein, protein- DNA interac&ons, etc
41 Supervisors: Nevan Krogan Wendell Lim Thank you! Collaborators: Fungal phosphoryla&on Jonathan Trinidad UCSF Alma Burlingame UCSF Ubiquityla&on Cell Signaling Judit Villen Uni. Wash Coprinus cinereus Jason Stajich UC Riverside Laura Kapitzky Krogan Lab Veronique Albanese Frydman lab Blog
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1 2 Contact Information Dr. Sonish Azam Office: SP 375.23 Tel: 514-848-2424 ex 3488 Email: sonish.azam@concordia.ca (Please mention BIOL 266 in subject) Office hours: after the class or by appointment