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The Map of Life
Notes on Ch.13
Judith Molka-Danielsen
Gene research
• In 1987 Nature Magazine article stated it found
the gene for manic depression. It located the
gene responsible as chromosome 11. Later
reports refuted this discovery, and laid claim to
other chromosomes responsible ie: 6, 13, 15,
and 18.
• Barabasi says this is not conflicting results.
• These discoveries demonstrate that most
illnesses are not caused by a single
malfunctioning gene. Rather, "several genes
interacting through a complex network hidden
within our cells are simultaneously responsible."
New Research Field: Bioinformatics
• Scientists were originally not aware of the fact that
not one gene, but actually a system of genes,
encode for particular traits, or characteristics; as
they are developmentally regulated in their gene
expression.
• Unknown are which, genes work together, in
developmentally regulating the expression, and
systematic development, of proteins themselves.
• This has led to the explosion of the new field
known as bioinformatics.
• Scientists, and biologists, are taking a more
computational approach to molecular biology, and
genomic data/DNA itself.
Genome project - of parts
•
•
•
On June 26, 2000, Bill Cllinton
announced the decoding of the 3
billion letters of the human genome,
saying we have been handed the
"book of life."
Barabasi says," We are repeatedly told
that everything from our personality to
future medical history is encoded in
this book. Can you read it? Let me
share a secret with you: Neither can
biologists or doctors."
Barabasi agrees that the genome
project is a triumph in reducing
complex living systems to their
smallest parts. But he stresses in
order to really understand how
illnesses work, we need to look at how
the cell functions as a network.
On June 26, 2000 President Clinton,
with J. Craig Venter, left, and Francis
Collins, announces completion of "the
first survey of the entire human
genome.
The Human Genome Project
Complex systems
Made of
many non-identical elements
connected by diverse interactions.
NETWORK
Networks of Cells
• Cells function as a network, because they are
instructed to do so by a network of genes
themselves, which encode the function of the
cells.
• Protein interactions, and developmental
pathways, ultimately determine the function of a
particular trait, or characteristic, which is
ultimately determined by the underlying genetic
pathways, or networks, themselves.
Networks
of Cells
• Networks in the
cell appear at
many levels.
• They include
protein-protein
interaction
networks (redlines), proteingene interactions
(green-lines) and
metabolic
networks (bottom).
• They together form
what is often
called the "cellular
network."
GENOME
protein-gene
interactions
PROTEOME
protein-protein
interactions
METABOLISM
Bio-chemical
reactions
Citrate Cycle
METABOLISM
Bio-chemical
reactions
Citrate Cycle
A few resources: http://www.hos.ufl.edu/meteng/HOS62312002/DATABASESANDPATHWAYS2004.htm
• BASIC WWW RESOURCES
• NCBI http://www.ncbi.nlm.nih.gov/ Entrez nucleotide and protein
data bases; Blast similarity search programs.
• TIGR http://www.TIGR.org The Institute for Genomic Research.
Annotated Arabidopsis and rice genomes. TIGR Gene Indices are
an analysis of the transcribed sequences represented in the world's
public EST data (contig assembly, analysis of expression patterns).
• ExPASy Translate Tool http://www.expasy.ch/tools/dna.html
Translates a DNA sequence in all 6 frames
• METABOLIC PATHWAY RESOURCES
• Swiss-Prot Enzyme http://www.expasy.ch/enzyme/ Enzyme
nomenclature data base (linked to SWISS-PROT protein database,
BRENDA, WIT, etc)
• BRENDA http://brenda.bc.uni-koeln.de/ Comprehensive enzyme
database.
• KEGG http://www.genome.ad.jp/kegg/ The Kyoto Encyclopedia of
Genes and Genomes
• BioCyc, EcoCyc & MetaCyc http://BioCyc.org/ EcoCyc Encyclopedia of E. coli Genes and Metabolism; MetaCyc Metabolic Encyclopedia. Also computationally-derived
Study of the topology of the metabolic network of the yeast
cell. Paper sources:
http://www.nd.edu/~networks/publications.htm#anchor-bio0002
Andreas Wagner and David
Fell, independently concluded
that the metabolic network of
E. Coli is scale-free.(from
http://bmsmudshark.brookes.ac.uk/fell.ht
ml)
The 2000 Nature paper demonstrating that the metabolism
of 43 organisms is scale-free. (from: “Metabolic Networks” )
The protein-protein
interaction network
of yeast also has a
scale-free topology:
a few proteins
interact with a large
number of other
proteins, while most
proteins have only
one or two links.
(See: “Network Biology:
Understanding the Cell’s
Functional Organization”,
Albert-László Barabási &
Zoltán N. Oltvai, Nature
Reviews, Vol 5, Feb 2004.)
”Lethality and centrality in protein networks”,
Nature, 411, 41-42- (2001)
H. Jeong, S. Mason. A.-L. Barabasi, and Zoltan N. Oltvai
Metabolic Network
Nodes: chemicals (substrates)
Links: bio-chemical reactions
Metabolic network
Archaea
Bacteria
Eukaryotes
Organisms from all three domains of life are
scale-free networks!
H. Jeong, B. Tombor, R. Albert, Z.N. Oltvai, and A.L. Barabasi, Nature, 407 651 (2000)
Yeast protein network
Nodes: proteins
Links: physical interactions (binding)
P. Uetz, et al. Nature 403, 623-7 (2000).
Topology of the protein network
Nodes: proteins
Links: physical interactions-binding
P(k ) ~ (k  k0 )  exp( 
k  k0
)
k
H. Jeong, S.P. Mason, A.-L. Barabasi, Z.N. Oltvai, Nature 411, 41-42 (2001)
Preferential attachment in protein Interaction networks
ki
ki
  ( ki ) ~
t
t
k vs. k : increase in the No. of links in a unit time
No PA: k is independent of k
PA: k ~k
Eisenberg E, Levanon EY, Phys. Rev. Lett. 2003
Jeong, Neda, A.-L.B, Europhys. Lett. 2003
Origin of the scale-free topology in the cell: Gene Duplication
Proteins with more interactions are more likely to obtain new links:
Π(k)~k
(preferential attachment)
Wagner 2001; Vazquez et al. 2003; Sole et al. 2001; Rzhetsky & Gomez 2001;
Qian et al. 2001; Bhan et al. 2002.
C. Elegans
Li et al. Science 2004
Drosophila M.
Giot et al. Science 2003
Studying Diseases
• In cancer, scientists found that the p53 gene is
responsible (when it does not function to stop cell
growth).
• Barabasi writes that instead of obsessing over the p53
molecule, we should focus instead on the p53 network: a
sum of all molecules interacting with the p53 molecule.
• Diseases are usually the result of defects in proteins,
which interact with other molecules. Other defects in
protein folding are the result of diseases themselves.
• Some researchers try to study protein pathways and
interactions.
Nature 408 307 (2000)
…“One way to understand the p53
network is to compare it to the Internet.
The cell, like the Internet, appears to
be a ‘scale-free network’.”
P53 Networks,
Vogelsteing, Lane and Levine
suggested that the role of the p53
molecule is a hub in the p53
network. (Nature 408, 307 (2000)).
p53 network (mammals)
•Activation of the network (by stresses such as
DNA damage, ultraviolet light and oncogenes)
stimulates enzymatic activities that modify p53
and its negative regulator,MDM2.
This results in increased levels of activated
p53 protein. The expression of several target
genes is then activated by binding of the
activated p53 to their regulatory regions. These
genes are involved in processes that slow down
the development of tumors. For example,
some genes inhibit cell-cycle progression or the
development of blood vessels to feed a growing
tumor; others increase cell death (apoptosis).
A negative feedback loop between MDM2 and
p53 restrains this network. Many other
components of this network, not shown here,
have been identified. Similarly, p53 activation
results in a variety of other effects, including the
maintenance of genetic stability, induction of
cellular differentiation, and production of extra
cellular matrix, cytoskeleton and secreted
proteins. (Contributed by Dr. Koji Nakade)
Tools for studying genes
A micro-array chip can record
which of the genes are active in
a cell-offering unprecedented
opportunities as a future
diagnostic tool.
For a description of how the
DNA chip works, see
http://www.devicelink.com/ivdt/a
rchive/98/09/009.html
RT² Real-Time™ Gene Expression Assay Kit
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Personalized medicine
• Barabasi says that once we understand DNA in terms of
a network, scientists will be able to deliver prescription
medicines catered specifically to an individual's DNA.
• Second, in producing antibiotics, scientists will be able to
develop drugs which can kill a particular strain of
bacteria, rather than wiping out all the bacteria in the
body (good and bad bacteria) as current medicines do.
• He also says that this can be accomplished within the
next 20 years.
• Researchers claim this is possible because,
Recombinant DNA technology will enable us to target,
and sequence, individual bacteria, and hence to invent
Antibiotics which are specific to certain strands of the
bacterial genome itself.
Business ties in US biotech-industry
Nodes: companies: investment
pharma
research labs
public
biotechnology
Links: financial
R&D collaborations
http://ecclectic.ss.uci.edu/~drwhite/Movie