1
The application of proteomic tools for a systems
approach to elucidating signaling pathways
Jessica Rouleau

Abstract— The post genome era is seeing a shift towards the
study of cellular proteomes. It is becoming increasingly clear that
proteins are the dynamic systems of the cell which control the net
responses. Therefore, a wide range of novel techniques are being
used for the large scale study of proteins in a physiological
context. These techniques include mass spectrometry, two hybrid
arrays, tandem affinity purification and RNA interference.
Application of these techniques to study cellular processes will
provide a non-intuitive understanding of complex signaling
pathways. The union of systems biology and proteomics holds
vast potential for understanding multiple pathways of a cell in a
manner that is spatially and temporally regulated.
Index Terms—Mass spectrometry, Proteomics RNA
interference, Signal transduction pathway, Systems biology,
Tandem affinity purification, Two hybrid arrays.
I. INTRODUCTION
R
ESEARCH in the post genome era is shifting towards
protein based studies. It is now understood that the study
of gene expression is not sufficient to describe dynamic
processes occurring in cells [1]. The human genome contains
approximately 30000 to 40000 genes but the resulting protein
products are estimated to be composed of over a million
distinct molecular species [1]. Therefore, it has been
recognized that studying gene expression and regulation will
not provide the complete picture of cellular processes. The
large scale analysis of proteins has formed a discipline of
research referred to as proteomics. Proteomics includes
studying the abundance, structure, formation of multi-unit
complexes, modifications and isoforms of the proteome [2].
The proteome is a dynamic entity that corresponds to all the
proteins in a given cell [3].
To elucidate the many aspects of proteomics research, a
number of different high-throughput proteomic techniques
have been developed. These include mass spectrometry (MS),
two hybrid arrays, tandem affinity purification techniques
(TAP) and RNA interference (RNAi) approaches. Each of
these techniques has great potential to characterize aspects of
the proteome but as these techniques are still in their infancy,
there are many problems that need to be overcome.
Many systems biology approaches to model signaling
pathways and intracellular mechanisms have used large sets of
gene expression data to identify gene interaction networks [4].
The shortcomings of genomic approaches is they do not give a
clear indication of the abundance of proteins translated, the
lifetime of these proteins, the state of these proteins and their
interactions in the cell [1]. Therefore, proteomic data will
provide a systems approach, whereby large data sets will
explain the molecular interactions occurring in the system.
Systems biology based modeling will use this data and put it
into a context that allows non-intuitive predictions of cellular
behaviour [5]. These models will explain the states of cellular
systems and not just the connectivity of components.
To achieve a systematic understanding of signaling
pathways, an integration of extracellular stimuli, protein
dynamics and gene regulation need to be incorporated into
models. The improvement and increased use of proteomic
techniques will greatly aid in mapping out and integrating
many signal transduction pathways to develop an overall
systems understanding of cellular processes. This will lead to
a greater understanding of many disease states, the normal
physiology of the cell, targets for drug discovery and more
specific requirements for tissue engineered scaffolds.
II. PROTEOMIC TECHNIQUES
A. Mass Spectrometry
With the completion of genome sequencing, mass
spectrometry is a technique that has become central in
proteomic research. Traditionally, mass spectrometry based
proteomics has been used for peptide sequencing, the study of
protein-protein
interactions
and
post-translational
modifications [6]. Recently, novel ways to study proteins have
been developed using this technology [7, 8].
Mass spectrometry requires protein samples to be digested
into peptide fragments where they can then be separated using
high performance liquid chromatography (HPLC) or ion
exchange columns [9]. These peptides are then ionized using
one of two techniques, electrospray ionization (ESI) or matrixassisted laser desorption/ionization (MALDI) [9]. ESI ionizes
peptides out of solution and MALDI ionizes the samples from
a dry crystalline matrix. Generally ESI techniques are used to
analyze complex mixtures of proteins while MALDI is better
for analyzing simple mixtures [6]. Once inside the mass
spectrometer, the ionic fragments are in a vacuum where they
are manipulated by electric fields. Mass analyzers determine
the mass to charge ratio of the peptides. Three main types of
mass analyzers are used to identify peptide fragments: Fourier
transform mass spectrometers, time of flight mass
spectrometers and ion traps [6]. Ion traps tend to be the most
widely used to date but have relatively low mass accuracy
while Fourier transform mass analyzers have high sensitivity
and resolution but are expensive and complex to run [6]. After
obtaining the mass to charge ratio the primary structure of the
peptide can be determined. Once all the signatures of the
2
peptides are collected, databases are then used to match these
sequences to known sequences. Since the samples generally
do not contain one type of protein, these searches have to be
coupled to statistical techniques to determine the probability of
each protein in the sample being present. Researchers may use
filtering criteria to make a more accurate analysis of the
sample composition [6].
Mass spectrometry can provide other types of data besides
peptide identification. Post-translational modifications can be
identified through analysis of the spectra. Proteins that are
modified have different spectral features. For example,
phosphorylated proteins have a prominent peak added due to
the loss of a phosphoryl group [9]. Phosphorylated proteins
can also be selected by affinity separation through the use of
anti-phosphotyrosine,
anti-phosphoserine
and
antiphosphothreonine antibodies. The purified extract can then be
analyzed in the mass spectrometer [7]. There have been
several methods created to use isotope labels to identify two
protein populations in different states or at different time
points [7, 9]. These methods allow for a more dynamic
analysis of protein populations. One other technique that may
gain popularity is a technique termed AQUA and it involves
producing known concentrations of specific peptides to be
used as internal standards for absolute quantification of
proteins [8].
Large scale proteomic studies using mass spectrometry show
great potential for characterizing different aspects of the
proteome but there are still many obstacles to overcome. The
databases used to match peptide fragment signatures need to
become more extensive, containing all potential protein
sequences, the variable splicing domains, and the post
translational modifications. Statistical analysis and the use of
filters to identify proteins from complex protein mixtures
needs to be improved and standardized.
New mass
spectrometry techniques must continue to be developed so this
instrument can be used to its greatest potential.
B. Yeast two hybrid arrays
The two hybrid method is an experimental method that is
used to study protein-protein interactions. It can be used to
generate large interaction maps and identify novel proteins that
are associated by the interaction [10]. The function of these
new proteins can then be hypothesized because of the known
function of the interacting protein. Yeast two hybrid studies
have been used to functionally map out signal transduction
pathways [10]. This method is also valuable to studying
specific protein interactions between two proteins of a larger
protein complex.
This method was devised by exploiting the knowledge about
transcription factors, which usually have separate domains for
DNA-binding (DBD) and transcriptional activation (AD) [11].
To study the interaction between two proteins using the two
hybrid method, two yeast strains need to be created. One
strain will express the protein of interest as a fusion to a DBD
and the other strain will have the other protein of interest fused
to an AD domain. Yeast strains are created by cloning PCR
products for the specific protein of interest into a plasmid
vector [10]. When these two strains are mated the fusion
proteins are present together in the progeny. If there is an
interaction between the two proteins of interest, the DBD and
AD will come together to activate transcription of a reporter
gene and this process is shown in figure 1 [11]. There are
many reporter genes that can be used such as luciferase, betagalactosidase or green fluorescent protein. Different assays can
then be used to detect the presence of these products. If no
interaction occurs then the transcription of the reporter genes
will not occur.
This technique can be used in a high
throughput fashion through the creation of many yeast strains
from cDNA libraries of the organism of interest [10].
Therefore arrays of bait and prey proteins can be studied in a
systematic nature. Data from these experiments can produce
large interaction maps of proteins [11].
Strain A
Strain B
A
B
DBD
Reporter
X
AD
Reporter
Progeny AB
Reporter
Figure 1 [11]: Schematic of yeast two hybrid method.
The advantages of this experimental approach are that it has
good resolution, it is independent of endogenous protein
expression, and transient and unstable interactions can be
detected [3]. Disadvantages to using this method are that
interactions take place in the nucleus so that many of the
proteins tested are not in the same compartment as in their
native environment. Therefore, these interactions are not
related to their physiological setting. There is relatively high
rate of false positives using the yeast two hybrid method [3].
To validate the results from two hybrid studies, repetition of
the experiments and analysis using other techniques can be
performed [11].
C. Tandem affinity purification (TAP)
There have been many different affinity purification
techniques that have been developed to study protein
complexes.
These include immunoprecipitation, epitope
tagging, and tandem affinity purification. Tandem affinity
purification is a technique that can be used in a high
throughput fashion and can identify a large number of protein
3
complexes within a cellular environment [1]. The other
techniques have limitations which make them less likely to be
used in a large scale proteomic study. As more proteomic data
is generated, it is becoming clear that cellular proteins
organize themselves through a dynamic arrangement of protein
complexes [1]. Protein complexes can vary from a few
proteins in size to large complexes with over 80 components
[12]. Analysis of complexes can facilitate a functional
understanding of many unknown proteins.
TAP isolates protein complexes through the use of a tag
which is attached to a protein of interest in the cell [12]. The
components of this tag are shown in figure 2. Proteins that
complex with this bait protein will then be purified using the
tag. Tandem affinity purification begins with the insertion of
the tag into the host DNA [12]. The tag can be inserted at the
end of the gene representing the carboxy terminus end or the
amino terminus end of the protein [1]. The TAP tag contains
specific elements, each corresponding to a specific function.
The first component of the tag contains the sequence for a
protein that will be used to bind to specific antibodies in a
separation column. This protein will selectively bind to the
column while all other proteins will pass through. The tag
contains a TEV (tobacco etch virus) site [12]. This site is
highly susceptible to attack by the TEV protease. Cleavage by
this site specific protease releases the rest of the tag with the
protein complex. The remainder of the tag contains a
calmodulin binding peptide (CBP) and the complex of interest
[12]. The CBP site is used for a second purification step,
whereby the eluant from the first purification step will be
passed through a second affinity column of calmodulin coated
beads [1]. Elution of the protein complex is achieved using
chelating agents. This purified protein complex can then be
analyzed by mass spectrometry to identify the proteins in this
complex [12].
This purification technique has several advantages over
some of the other techniques [1]. The two step purification
tends to greatly reduce background noise caused by unspecific
binding. This reduction also reduces the complexity of the
mass spectrometry analysis. The purification steps in this
technique do not require strong detergents or high salt
concentrations, which can result in the loss of proteins within
the complex [1]. The separation steps used in TAP are kept
near physiological conditions and this gives the technique
greater physiological relevance. TAP has been shown to be
highly reproducible, using different bait proteins. Caveats of
this technique could be tag interference in protein function or
complex formation [1]. Repetition of experiments and the use
of different entry points to verify complexes will provide
stronger experimental evidence.
D. RNA interference
In the recent past, it was thought that transcription of DNA
to RNA was the main regulatory mechanism in the cell and
that RNA played a relatively simple role in the cell. This role
is translation, where genetic information is used to produce
proteins. The identification of double stranded RNA (dsRNA)
PCR of TAP tag and bait protein
Spacer
CBP
TEV site
Protein
Homologous
Recombination
Gene
Bait Protein
Spacer
[Gene Targeting]
Gene
CBP
[ TAP cassette]
TEV site
[Chromosome]
Protein
Collection of Lysates and Affinity Purification
Figure 2 [2]: Process of creating a TAP tag.
molecules in plants and Caenorhabditis elegans has altered
these views [13]. RNA interference has now been identified as
a mechanism in many cell types that cause inhibition of protein
production at a post transcriptional level [13]. Large dsRNA
molecules are processed by an enzymatic protein called Dicer
to yield 19-23 base dsRNA oligonucleotides [14]. These
oligonucleotides then associate with specific mRNA molecules
that match their sequence. This association promotes the
formation of the RNA induced silencing complex (RISC)
which has RNase activity. This complex degrades the RNA
and prevents transcription [14].
The understanding of these mechanisms has lead researchers
to use the cell’s machinery as a research tool [13]. Using the
cDNA sequence of the gene to be silenced, short interfering
RNA (siRNA) strands can be synthesized and then inserted
into the cell in a number of ways which include soaking the
cells in siRNA and injection [13]. Plasmids and viral vectors
have also been constructed to produce specific siRNA within a
cell population through transfection. There are many methods
that are currently being optimized for RNAi based studies
[13]. These studies let researchers block the action of a
specific protein within the cell and look at the resulting
phenotypes. Large scale arrays of RNAi can now be
performed and this will help to identify functions of different
proteins, their activity in signaling pathways and targets for
drug therapies [13].
The other method of gene silencing is to perform gene
knockouts. Compared with RNAi these techniques are more
complex and time consuming. Gene knockouts often produce
embryonic lethalities, so observation of the effects of the
knockout is prevented.
RNAi technology can produce
knockouts during different stages of development and target
specific tissues.
III. SYSTEMS BIOLOGY APPROACH TO PROTEOMIC MODELING
OF SIGNAL TRANSDUCTION PATHWAYS
As large scale proteomic techniques evolve and are
4
optimized, the large protein networks that make up signal
transduction pathways will be elucidated. Different techniques
will need to be combined to determine the connectivity
between different proteins, their dynamic interactions, the
states of these proteins and lifetime in the cell. Proteomics and
genomics will need to work in synchrony to determine how
signaling pathways affect transcription of signaling pathway
components and other processes going on in the cell. For
example, it is thought that the transforming growth factor
pathway regulates cell proliferation and tissue remodeling.
Therefore, proteomic techniques will be used to map out the
components of the pathway. These components have a
differential effect on gene expression of not only proteins in
the TGF- signaling pathway but proteins likely involved in
cell cycle regulation and extracellular matrix synthesis [10,
15]. A combination of proteomic and genomic techniques will
elucidate the dynamic activity of proteins in a temporal and
spatial fashion and describe the resulting changes in gene
expression that these protein pathways influence.
Current proteomic techniques are able to get a basic
understanding of the large compendium of proteins within a
cell. Mass spectrometry approaches allow for identification of
proteins in complex samples. This technique can also identify
phosphorylation states and abundance of these proteins in a
snapshot of time. Interactions of these proteins can be
identified using the yeast two hybrid techniques. These
techniques are able to build upon mass spectrometry data to
begin construction of a protein interaction network. Another
layer of complexity is the determination of larger complexes
within the cell through affinity purification. This will refine
the protein interaction network of signaling pathways.
Throughout the process RNAi techniques can be used to look
at the importance of specific proteins in a pathway and how
each protein affects downstream signaling and interaction of
protein complexes. These techniques will be able to identify
redundant pathways or processes as well as points of cross-talk
between different signaling pathways.
V. CONCLUSIONS
Overall, these techniques will aid in understanding the cell
as a system. Large scale studies can be fit into models that
systems biology attempts to create. Models will be developed
in an iterative fashion to identify areas that need to be altered
and expanded. It is the goal of systems biology to combine
signaling pathways, cellular metabolism and nuclear processes
of a system to develop a model that can be used for patient
based treatments and therapies. Proteomic techniques will aid
in elucidating signal transduction networks. In the future,
models of these networks will be integrated with other models
to develop a mechanism whereby cellular physiology can be
understood and predicted at the systems level.
REFERENCES
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
IV. FUTURE CHALLENGES
[12]
Proteomic techniques still face many challenges. These
techniques need to be used in way that enables a more dynamic
look at signaling pathways instead of just snapshots. The
reduction in the number of false positives and false negatives
needs to occur. More stringent procedures need to be
implemented in these studies. Proteomics needs to address the
low abundance of many signaling molecules and the high
sensitivity needed to be able to measure and monitor these
proteins. The large range of protein levels is also a major
barrier to analysis, there are proteins that only have a couple of
copies per cell but others have millions of the same protein
within a cell. A technique needs to be sensitive enough to
detect the low abundance of proteins but have large enough
range to be able to monitor higher levels of other proteins.
The similar challenge is seen when looking at time scales
within a cell. Some processes occur in seconds while others
take hours and these large ranges need to be addressed.
[13]
[14]
[15]
A. Bauer and B. Kuster, “Affinity purification-mass spectrometry,”
Eur. J. Biochem, 270: 570-578, 2003.
M. Tyers and M. Mann, “From genomics to proteomics” Nature, 422:
193-197, 13 March 2003.
C. von Mering, et al. “Comparative assessment of large-scale data sets
of protein-protein interactions”. Nature, 417: 399-403, 23 May 2002.
P. Brazhnik, A. de la Fuente, P. Mendes, “Gene networks: how to put
the function in genomics”. Trends in Biotech. 20: 467-472, November
2002.
H. Kitano, “Looking beyond the details: a rise in system-oriented
approaches in genetics and molecular biology”. Curr. Genetics. 41: 110, 2002.
R. Abersold and M. Mann. “Mass spectrometry-based proteomics”
Nature, 422: 198-207, 13 March 2003.
B. Blagoev, S.E. Ong, I. Kratchmarova, M. Mann. “Temporal analysis
of phosphotyrosine-dependent signaling networks by quantitative
proteomics”. Nature Biotech. 22: 1139-1145, September 2004.
S.A. Gerber et al. “Absolute quantification of proteins and
phosphoproteins from cell lysates by tandem MS”. Proc. Nat. Acad. Sci.
100: 6040-45, 2003.
H. Steen and M. Mann, “The ABC’s (and XYZ’s) of peptide
sequencing”. Nature Reviews: Molecular Cell Biology. 5: 699-710,
Septermber 2004.
F. Colland, X. Jacq, V. Trouplin, C. Mougin, C. Groizeleau, A.
Hamburger, A. Meil, J. Wojcik, P. Legrain, J.M. Gauthier. “Functional
Proteomics Mapping of a Human Signaling Pathway”. Genome
Research. 14: 1324-1332, 2004.
P. Utez. “Two-hybrid arrays” Current Opinions Chem. Bio. 6:57-62,
2001.
A-C. Gavin et al. “Functional organization of the yeast proteome by
systematic analysis of protein complexes”. Nature. 415: 141-147, 2002.
O. Milhavet, D.S. Gary, M.P. Mattson, “RNA interference in biology
and medicine”. Pharma. Reviews. 55: 629-648, 2003.
C.C. Mello and D. Conte, “Revealing the world of RNA interference”.
Nature. 431: 338- 342, 16 September 2004.
M. Schiller, D. Javelaud, A. Mauviel, “TGF--induced SMAD signaling
and gene regulation: consequences for extracellular matrix remodeling
and wound healing”. J. of Derm. Sci. 35: 83-92, 2004.