1. Organellar Proteomics: Turning Inventories into Insights
Jens S. Anderson and Matthias Mann

2. Human Genome and Proteome
~ 23,000 Genes in Humans
Active proteins far outnumber genes:
Alternative Splicing
Post Translational Modifications

3. Proteomics MicroArray Experiments: Gives information on expression
No location information

4. Organellar Proteomics
Traditional Techniques:
Separation and Enrichment
Microscopy

5. Fluorescence Based Microscopy
Powerful localization technique
Use of antibodies raises issues
Candidate based approach

6. Challenges Traditional techniques in mammals:
Fusion proteins are usually over expressed
Tagging is difficult and can lead to artifacts

7. Mass Spectrometry

8. Validation

9. Subtractive Proteomics
Compares the identified constituents of the complex of interest to a related background complex

10. Subtractive Proteomics
Limitations:
In large proteomes not all possible peptides will be sequenced
Successive runs of the same sample will not overlap

11. Question
How does one know if the proteins found in the nucleus are nuclear or just being transcribed there at the time of the experiment?

12. Stable Isotope Labeling in Cells
SILAC
Stable Isotope Labeling in Cells

13. Protein Correlation Profiling

14. Protein Correlation Profiling
Substantial increase in quantification accuracy
Large scale PCP has suggested error rates in published data sets between 3 and 64% owing to co purifying proteins

15. Cataloguing Proteins Bioinformatic Methods
Most useful for membrane bound organelles
Subnuclear domains, such as the nucleolus cannot be predicted accurately

16. Cataloguing Proteins Web based organellar databases Gene Ontology
Max Planck Unified Proteome Database

18. Organelle Dynamics
Organelles have both resident and transient proteins
Microscopy is limited in full classification due to its candidate based approach

19. Current State
Mass Spectroscopy Technology is no longer the limiting step
Main challenges now lie in purifying organelles and removing background proteins