Proteomics, the next step

1
Proteomics, the next step

• What does each protein do?
• Where is each protein located?
• What does each protein interact with, if
  anything?
• What role does it play in the cell or tissue?

2
Gene Ontology

• Biological process
• Molecular function
• Cellular component
• Kinda like the EC commission, a mechanism for
  uniformity among disparate systems
• http//www.geneontology.org/

3
Assigning ontology

• Functional genomics using mini-Tn
• Promoter-less lacZ with selectable markers ,
  epitope tag and flanked by lox recombination
  sites
• Isolated gt11,000 Tn mutants that turn blue during
  vegetative growth (transcription and translation
  occur)
• In addition to ontology, you also get info on
  regulation (expression) via lacZ handle
• 1917 ORFs/6358 strains were mutated at least
  once, many multiple times

4
Macroarrays

• How do you examine that many yeast strains?
• Robots spot strains on agar plates, and plates
  incubated under various conditions
• Limited by number of conditions used 20 in this
  study, some quite inventive

5
Caveats

• Can mutate same gene, with different effects
• 11 distinct insertions were characterized for
  Imp2
• Observe differing effects on glycerol metabolism
  an cell wall synthesis

6
Clustering

• Each column a condition, each row a mutant strain
  which ones behave most similarly
• Allows visualization of proteins involved in gt1
  process or observing a potential role for an
  uncharacterized ORF but how do you get ontology?

7
Everything you want

• Phenotypic analysis will divine with certainty at
  least one biological process the gene is involved
• Molecular function would have to be assessed
  biochemically
• Use epitope as localization tool

8
Bar coding genes

• Delete ORFs by homologous recombination and
  replace with selectable marker and 20 bp DNA
  sequences UPTAGS and DOWNTAGS
• Each TAG (barcode) is unique to an ORF
• Can PCR amplify TAGS using same set of primers
• Construct a DNA barcode microarray
• Each mutant strain had two, and only two spots
  that it would hybridize to

9
Contamination!

• With this strategy, the investigators mixed 558
  strains in same flaskremoved samples at
  different time points (first point label PCR
  reaction red and second (6hrs later) label
  green).
• Use the microarray to determine which strains are
  able to better compete

10
So

• Bar code methodology shows which proteins provide
  a selective advantage in a mixed population of
  cells
• Two spots of different sequences provides an
  internal control for the experiment

11
How do you know youve sampled enough cells?

• Binomial probability distribution
• Binary outcome, either get a 1 or 0
• If p is the probability of getting a 1 (in a
  single trial), (1-p) is the probability of
  getting a 0, then the probability that k out of N
  tries gives a 1 is
• P(k 1s out of N) (N over k) pk (1-p)N-k

12
pk (1-p)N-k

• These terms represent the probability of
  observing a 1 with k successes and N- k failures

13
(N over k)

• This term counts the number of ways you get a 1
• (N over k) denotes the number of ways of choosing
  k objects from N which is the factorial function
  n!/k!(n-k)!
• This is also known as the binomial coefficient
• Work through math minute 6.1

14
Structural Genomics

• Inferring function from structure (Archaea)
• Aquaporin structure/function
• Co-crystals as binding assays
• Prion protein in yeast Sup35
• Overproduction of prion protein in yeast leads to
  infectious particle

15
Protein interaction networks

• Identified by comparative genomics analyses
  neighbors interact
• Yeast two-hybrid system
• Various repositories for interaction data
• BIND www.bind.ca
• DIP http//dip.doe-mbi.ucla.edu/hold/

16
Deciphering protein network graphs

• Node, edges, degrees
• Example in MM 6.2
• Calculate the mean and standard deviation for
  degrees in any given network
• If the degree of a node is gt than mean degree 2
  S. D., it has high connectivity in that network

17
Schwikowski paper

• www.uwp.edu/barber/bioinformatics/benno.pdf
• Book web-site
• http//occawlonline.pearsoned.com/bookbind/pubbook
  s/bc_mcampbell_genomics_1/chapter1/deluxe.html
• Discovery questions 44-49 for next week