Systems Biology approach: cell cycle (sixth framework program: DIAMOND)

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Systems Biology approach cell cycle (sixth
framework program DIAMOND)

• Integrative approach to build a basic model of
  cell cycle in 4 different species
• S.cerevisae (budding yeast)
• S. Pombe (fission yeast)
• A. Thaliana (weed)
• Human
• Objectives
• Identification of cell cycle targets of major
  signaling pathways affecting cell division
• knowledge base for further cell cycle control
  research
• design of a mathematical model of cell cycle
  network on basis of genome wide
• data sets
• Analysis
• transcriptome
• targeted proteomics approaches
• literature
• annotated databases

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different research areas of the project

• I. Cell cycle events in synchronized cell
  cultures
• II. Cell cycle exit/entry in response to
  extracellular signaling
• III. DNA damage checkpoint

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1. Cell cycle events in synchronized cell cultures

• ? measure regular cyclic changes under
  standard growth conditions
• double thymidine block and
  nocodazole/aphidicolin
• samples for RNA 12 or 24 time
  points after release from block
• study available Identification of Genes
  Periodically Expressed in the
• Human
  Cell Cycle and Their Expression in Tumors
• 
  Michael L. Whitfield, Gavin Sherlock, Alok J.
  Saldanha, John I. Murray,
• Catherine A. Ball, Karen E.
  Alexander, John C. Matese, Charles M. Perou,
• Myra
  M. Hurt, Patrick O. Brown, and David Botstein
• 
  Departments of Genetics and
   Biochemistry,  Howard Hughes Medical Institute,
  Stanford University School of
• Medicine, Stanford, California 94305
   Department of Biomedical Sciences, College of
  Medicine, Florida State
• 
  University, Tallahassee,Florida
  32306 and  Department of Genetics, Lineberger
  Comprehensive Cancer Center,
• University of North Carolina at
  Chapel Hill, Chapel Hill, North Carolina 27599

• HeLa cells
• cDNA micro array representing 16332 different
  human genes
• 5 independent arrays

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II. Cell cycle exit/entry in response to
extracellular signaling

• ? measure gene response to
  proliferative stimuli (cytokines)
• study available The Transcriptional Program in
  the Response of Human Fibroblasts to Serum
• Vishwanath
  R. Iyer, Michael B. Eisen, Douglas T. Ross,
• Greg
  Schuler, Troy Moore, Jeffrey C. F. Lee, Jeffrey
  M. Trent,
• Louis M.
  Staudt, James Hudson Jr., Mark S. Boguski,
• Deval
  Lashkari, Dari Shalon, David Botstein, Patrick O.
  Brown
• V. R. Iyer and D. T. Ross, Department of
  Biochemistry,Stanford University School of
  Medicine,
• 
  Stanford CA94305, USA. M. B. Eisen and D.
  Botstein, Department of Genetics, Stanford
  University
• 
  School of Medicine, Stanford CA 94305, USA.
• SCIENCE VOL 283 1 JANUARY 1999

• normal diploid human fibroblast cell line
  derived from foreskin
• cDNA micro array representing 8613 different
  human genes
• 3 independent arrays

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Research areas of the project
III. DNA damage checkpoint
? monitoring the effects of DNA damage,
changes in gene expression profile after various
time points double strand
breaks, induction of ATM dependent checkpoint by
ionizing radiation single strand breaks,
induction of ATR dependent checkpoint by UV
problems with available studies -
usage of cancer cell lines -
arrays representing to less genes
- fold changes in expression levels of known DNA
damage responsive genes quite
low (e.g. p21) - focus on
either G1 or G2 checkpoint -
influence of biological and experimental variance
? too few samples ?
too few arrays
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Experimental procedure
p53 deficient human diploid fibroblasts (Tig3)
normal human diploid fibroblasts (Tig3)
Cell lines
UVC (25 J/m2)
?-irradiation (10GY)
non stressed
Treatment
harvest cells after 0 6h
microarray
FACS
expression p53,p21,Puma (qPCR, immunoblotting)
Analysis
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p53 knock down in Tig3-tert cells
P53
wt p53kd
P21Cip1
wt p53kd
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Induction of p53 target genes after DNA damage
gamma irradiation
UVC
p21
Puma
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Gene chip

• Human Genome U133 Plus 2.0 Array
• comprehensive coverage of the transcribed human
  genome on a
• single array
• Analyzes the expression level of over 47,000
  transcripts and variants,
• including 38,500 well-characterized human
  genes
• Comprised of more than 54,000 probe sets and
  1,300,000 distinct oligonucleotide features
• The sequences from which these probe sets were
  derived, were selected from
• GenBank,
• dbEST
• RefSeq.
• The sequence clusters were created from the
  UniGene database and then refined by analysis
• and comparison with a number of other
  publicly available databases (Washington
  University EST
• trace repository and the University of
  California, Santa Cruz Golden-Path human genome
  database)

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Cluster image showing the different classes of
gene expression profiles
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Genes downregualted by UVC p53kd
Genes downregualted by UVC partially IR
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P53 dependent upregulated
P53 dependent upregulated
Genes upregualted by UVC IR
P53 independent downregulated
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Genes upregualted by UVC in wt cells
Genes upregualted by UVC in wt p53kd
Genes upregualted by UVC downregulated In IR
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Venndiagram
Wt UVC/ wt IR (6673 probeset)
p53kd UVC/ wt IR (3187 probeset)
517
3832
2530
122
189
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93
P53kd none/ wt none (422 probeset)
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Software Databases

• DAVID (Database for Annotation, Visualization
  and Integrated Discovery)
• http//apps1.niaid.nih.gov/david/
• DAVID Tools
• Annotation Tool
• GOCharts
• KEGGCharts
• DomainCharts
• EASEonline
• Silicon Genetics gene expression and genotyping
  software
• Genespring

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Classification of DNA damage induced p53
dependent genes into biological processes
death genes 2
stress signaling 1,2
cell cycle 5,3
cell growth 9,8
(WT UVC IR subset 3832, p53 depenndent)
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Array validation by QPCR
First validations by QPCR
p21
Fas
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