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Proteomics and annotation

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Title: Proteomics and annotation


1
Proteomics and annotation
2
Definition of proteomics
  • Study of all the proteins in an organism
  • Derived from genomics all the DNA in an organsim
  • On some levels it is a catalog of all the
    functional proteins, but in many contexts it is
    also the study of the interactions of the proteins

3
Central Dogma
  • DNA --gt RNA --gt AA --gt function

4
Proteomics techniques
  • Protein identification/quanitfication
  • High throughput elusive
  • Now typically
  • Separate
  • Isolate
  • Identify
  • Enumerating protein interactions
  • Protein protein
  • Protein DNA/RNA

5
How to separate proteins
  • Proteins are made up of 20 AA not 4 NT
  • DNA size- migration through a charged field
  • Protein
  • Size
  • Charge
  • Hydrophobic
  • Solubility
  • Fraction of the cell
  • Much more structure

6
2D gels
3 pH
10 pH
Big
Little
7
Limitations of 2D
  • Very large and small proteins dont work well
  • Membrane bound proteins
  • Solubility of the protein
  • Disulfide bonds
  • Rare proteins
  • Can stain with silver stain
  • Non-linear
  • 100X

8
Mass spectrometry
  • Simple principle
  • Explode the charged peptides off the sample
  • Electro-spray charged cone
  • Laser -gt Vapor -gt charged grid
  • See how big they are
  • Detect number of ions/mass
  • Ion trap- kind of like TV
  • TOF- how far did it go

9
Mass of AA
10
Mass spectrum
Major Ion H
Actual mass
C13
11
Post-translational modification
  • Cleavage
  • removing portions of the protein by enzymatic
    action.
  • Can change location, function, activity
  • Additions
  • Adding a chemical
  • Regulated activity
  • Can change protein function/activity

12
Modifications
13
Limitations of mass spec
  • Most frequently sequenced protein keratin
  • Ionization is not strictly quantitative
  • Can cleave the protein into peptides
  • Complicated by mixtures
  • Issues on searching the database
  • http//prospector.ucsf.edu/
  • http//fields.scripps.edu/sequest/index.html

14
QCAT
  • Way to quantitatively analyze multiple proteins
    (Nature Methods 2, 587 - 589 (2005)).
  • Depends on concatemers assembled from segments of
    the proteins of interest. Each protein has one
    segment that would be produced by a tryptic
    digest (QCAT)

15
Cont.
  • Grow the peptide in heavy and light isotopes, get
    standard curve
  • Spike your sample with heavy QCAT
  • This produces an internal standard for each
    protein of interest.
  • This allows quantitation of many (100) proteins
    in one experiment.

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18
Protein-protein interactions
  • Types of interactions
  • Stable
  • Multimers, complexes
  • Association forms complete unit
  • Quaternary structure
  • Unstable
  • Pathways
  • Signaling events
  • Transient interactions

19
Yeast two-hybrid
20
How accurate is the Y2H data?
  • False Negative
  • proteins that have very transient interaction,
    sporadic interactions or that may be located in
    the membrane.
  • Non-physiological test conditions
  • False Positive
  • Self activators
  • Weak non-specific interactions
  • Non-physiological test conditions

21
How to assess
  • Remove proteins with above average number of
    interactions
  • Intersection of a number of experiments (Y2H,
    Co-IP, and co-expression)
  • Network properties.
  • Other documented signals of interaction.

22
Network comparison
  • Genome Biology 2006, Volume 7, Issue 11, Article
    120

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27
How to find protein/DNA interactions
  • Have a typical Transfac binding site 10 bp long
    with 2 bases somewhat ambiguous. How often does
    it appear by chance in the genome?
  • How can you determine if genes are co-expressed.
  • DNA foot-printing
  • Deletion experiements
  • High throughput?

28
ChIP on chip
29
Design
  • Need very specific antibody for each
    transcription factor that you wish to study
  • cDNA will not work with large introns
  • Whole genome chips
  • Human 21, 22
  • 3 x106 spots
  • SAGE
  • Look for enriched vs non-enriched
  • Looking for a population rather than one sequence

30
Results
31
Annotation
  • Systematically adding knowledge
  • Human vs computer
  • Throughput
  • Accuracy
  • Repeatability
  • Typical course
  • Found in one organism
  • Mapped to all other homologous segments
  • Function as a consequence of sequence

32
Prosite
  • PROSITE is a method of determining what is the
    function of uncharacterized proteins translated
    from genomic or cDNA sequences. It consists of a
    database of biologically significant sites and
    patterns formulated in such a way that with
    appropriate computational tools it can rapidly
    and reliably identify to which known family of
    protein (if any) the new sequence belongs.
  • http//ca.expasy.org/prosite/
  • Take a smaller segment of the protein and build
    up annotation for the whole protein

33
Structured languages
  • The Gene Ontology (GO) project is a collaborative
    effort to address the need for consistent
    descriptions of gene products in different
    databases. The project began as a collaboration
    between three model organism databases, FlyBase
    external link (Drosophila), the Saccharomyces
    Genome Database external link (SGD) and the Mouse
    Genome Database external link (MGD), in 1998.
    Since then, the GO Consortium has grown to
    include many databases, including several of the
    world's major repositories for plant, animal and
    microbial genomes. See the GO Consortium page for
    a full list of member organizations.
  • http//www.geneontology.org/GO.doc.shtml

34
Other Types
  • Systems biology
  • Protein structure
  • Enzymatic pathways

35
Kegg API example
  • http//sial.org/howto/perl/life-with-cpan/non-root
    /

36
Bioperl annotation examples
  • Get info from genbank
  • Graphical annotation
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