Protein domains vs. structure domains - an example.

1. Protein domains vs. structure domains - an example.

2. Genome of the week • Nanoarchaeum equitans - archaea • Hyperthermophile • Diverged early in evolution from other archaea • New kingdom of archaea? • Obligate symbiont with Ignicoccus • Smallest completely sequenced genome • <500kB • Genome reduction observed in symbionts (Schmidt) • Is N. equitans a “primitive” archaea or is the genome undergoing reductive evolution?

3. N. equitans lacks genes necessary for many aspects of central metabolism. • Can’t make lipids, vitamins, amino acids, etc. • Parasite, not symbiont? First archaea • Genome is quite compact. • 95% of genome codes for genes. 552. • Not primitive. • Has complete set of information pathway and cell cycle genes found in archaea. • No longer undergoing reductive evolution. • Normally would find pseudogenes - not found.

4. Protein complexes - why? • Proteins often function as large, multi-subunit complexes. • ribosomes • Can get clues about the function of a protein by knowing what other proteins it contacts.

5. Protein:protein interactions • Genetic approach • Yeast 2-hybrid • Biochemical approach • Co-immunoprecipitation • Fusion protein affinity chromatography • Cell-biology • FRET - fluorescence resonance energy transfer • Computational • Rosetta Stone • Co-regulation • Phylogenetic analysis

6. Yeast 2-hybrid approach • Based on the fact some transcriptional activators have separable DNA binding (BD) and transcriptional activation domains (AD). • GAL4, LexA • Protein you are studying = Bait • Fused to the DNA binding domain of GAL4 • Protein(s) you are screening = Fish or Prey • Fused to the activation domain of GAL4 • Transform Bait and Fish plasmids into yeast, measure the expression of a reporter gene. • Usually a gene can be selected for when expressed.

7. Image from: http://www.bioteach.ubc.ca/MolecularBiology/AYeastTwoHybridAssay/

8. Yeast 2-hybrid on a genome wide scale • Clone every gene in your genome into both the “bait” and “fish” vectors. • Systematically screen each gene for interactions. • Mate individual yeast strains. • Many false positives.

9. Interactome Term to define all of the protein interactions that take place in the cell. Book example - predicting human interactions. Based on data that only 10% of the measured interactions are physiological

10. Yeast 2-hybrid • False-positives • Some baits are “sticky” leading to non-functional interactions • False negatives • Binding not tight enough to detect interaction • Fusion proteins often do not fold correctly • Works best when comparing two proteins suspected of interacting • Bacterial 2-hybrid systems

11. Co-immunoprecipitation • Using an antibody to isolate and purify a protein from a whole cell lysate. • Normally you will only purify the protein the antibody recognizes. • Any additional proteins that co-purify are candidates for interacting proteins.

12. Hirano et al, 1997 Cell, Vol 89, 511-521, 16 May 1997

13. Fusion protein affinity chromatography • Express the protein of interest as a fusion protein. • 6-8X His residues • Glutathione S-transferase (GST) • Other “tags” • Bind and purify the protein of interest • Poly His residues will bind Ni2+ • GST will bind glutathione

14. Image from: Sigma-Aldrich

15. Fusion proteins - identifying interactions. • In vivo - express fusion protein in vivo • Purify complexes from the cell • In vitro - overexpress protein in vitro • Bind fusion protein to a column and run whole cell lysate through the column. Identify proteins that “stick” to the fusion protein.

16. Difficulties when using biochemical approaches • Stability of protein:protein interactions. • Many are not stable enough to survive purification. • Is the fusion protein functional? • Many times fusions will not be functional. • Quality of the antibody. • Is it good enough to precipitate enough protein for analysis?

17. Computational methods • Rosetta stone analysis • Search for proteins that are separate in one organism but are fused into one protein in another organism.

18. Computational methods • Co-expression • Genes that are in operons are often functionally linked. (not always true). • Determine if the structure of an operon is conserved, indicating co-expression. • Candidates for interaction. • Not a great method.

19. Phylogenetic analysis • Search for the presence of a protein in all organisms. • Determine the distribution. • Identify other proteins that also show this distribution. • Functionally interact? Physically?

20. PLEX • Protein Link EXplorer. • Uses phylogenetic profiles to predict possible associations.