Proteomics: A Tool In Future
Pallavi Salve*, Rupali Kirtawade, Deepali Gharge, Pandurang
Dhabale and Kishor Burade
ABSTRACT
Scientists are very interested in
proteomics because it gives a much better understanding of an organism than
genomics. First, the level of transcription of a gene gives only a rough
estimate of its level of expression into a protein. Whole Genome Sequence gives
complete proteins contain, but does not show how proteins function or
biological processes occur. Proteomics gives large-scale study of proteins,
particularly their structures and functions. Proteomics is a term in the study
of genetics which refers to all the proteins expressed by a genome; proteomics
involves the identification of proteins in the body and the determination of
their role in physiological and pathphysiological functions. The term
"proteomics" was coined to make an analogy with genomics, the study
of the genes. The word "proteome" is a blend of "protein"
and "genome". Proteomics technologies are of major three types
Expression
Proteomics, Structural Proteomics, Functional Proteomics. Proteomics is applied in various fields like Tumor Metastasis,
renal disease diagnosis, Neurology etc. But proteomic technologies hold
great promise in the search for clinically useful protein biomarkers for the early
detection, diagnosis and prognosis of cancer and for monitoring response to
therapy.
KEY WORDS: Proteomics, genomics, Genome, proteome
INTRODUCTION
After genomics, proteomics is often considered the next
step in the study of biological systems. It is much more complicated than
genomics mostly because while an organism's genome is more or less constant,
the proteome differs from cell to cell and from time to time. This is because
distinct genes are expressed in distinct cell types. This means that even the
basic set of proteins which are produced in a cell needs to be determined.
In the past this was done by mRNA analysis, but this
was found not to correlate with protein content.1,2 It is now known
that mRNA is not always translated into protein3 and the amount of
protein produced for a given amount of mRNA depends on the gene it is
transcribed from and on the current physiological state of the cell. Proteomics
confirms the presence of the protein and provides a direct measure of the
quantity present.
Proteomics :
Proteomics is the large-scale study of proteins, particularly
their structures and functions4,5.Proteins are vital parts of living
organisms, as they are the main components of the physiological metabolic
pathways of cells. The term "proteomics" was first coined in 19976
to make an analogy with genomics, the study of the genes. The word
"proteome" is a blend of "protein" and "genome",
and was coined by Marc Wilkins in 1994 while working on the concept as a PhD
student.7,8 . The proteome is the entire complement of proteins,7
including the modifications made to a particular set of proteins,
produced by an organism or system. This will vary with time and distinct
requirements, or stresses, that a cell or organism undergoes.
The dream of having genomes completely
sequenced is now a reality. The complete sequence of many genomes including the
human one is known. However, the understanding of probably half a million human
proteins encoded by less than 30'000 genes is still a long way away and the
hard work to unravel the complexity of biological systems is yet to come. A new
fundamental concept called proteome (PROTEin complement to a genOME) has
recently emerged that should drastically help to unravel biochemical and
physiological mechanisms of complex multivariate diseases at the functional
molecular level. The discipline of proteomics has been initiated to
complement physical genomic research. Proteomics can be defined as the
qualitative and quantitative comparison of proteomes under different conditions
to further unravel biological processes.13
One complete set of genes in an organism (a
haploid set)10,11
Except for occasional unrepaired damage to
its DNA (= mutations), the genome is fixed.
The most common definition: All the messenger RNA
(mRNA) molecules transcribed from the genome. Varies with the differentiated
state of the cell and the activity of the transcription factors that turn gene
transcription on (and off). Speaking strictly, one would define the
transcriptome as all the RNA molecules — which includes a wide variety
of untranslated, nonprotein-encoding RNA — transcribed from the DNA of the
genome. It is now thought that 70% of our DNA (including vast amounts of
"junk" DNA) is transcribed into RNA although only 1.5% of this is
messenger RNA for protein synthesis10
Two popular definitions:
·
All the
proteins that can be synthesized by the cell.10,11,12
·
All the
proteins synthesized by a particular cell at a particular time.
The proteome is the protein
complement of the genome . It is quite a bit more complicated than the
genome because a single gene can give rise to a number of different
proteins through
·
alternative
splicing of the pre-messenger RNAs;
·
RNA
editing of the pre-messenger RNAs;
·
attachment
of carbohydrate residues to form glycoproteins,
·
addition
of phosphate groups to some of the amino acids in the protein.
While we humans may turn out to have only 25
to 30 thousand genes, we probably make at least 10 times that number of
different proteins. More than 50% of our genes produce pre-mRNAs that are
alternatively-spliced.
The study of proteomics is important because
proteins are responsible for both the structure and the functions of all living
things. Genes are simply the instructions for making proteins. It is proteins
that make life.9,25
Study
of Proteomics:
1. Isolate a homogeneous population of cells
(e.g., yeast cells that have just been switched from glucose to galactose as
their energy source).
2. Extract the contents of the cells and
separate the mix of proteins from other components.
3. Separate the proteins in the mix by two-dimensional
(2D) gel electrophoresis. This separates the proteins
o in one dimension by their electrical charge;
o in the second dimension by their size.
(The procedure is analogous to that used in
paper chromatography.)
4. Stain the gel to visualize the various spots
of protein.
5. Punch out a spot.
6. Add a protease (e.g., trypsin) to digest the
protein in that spot into a mix of peptides.
7. Run the mix through a mass spectrometer,
which will separate the peptides into sharply-defined peaks.
8. Run the resulting data through a database of
all known proteins (that have been digested with the same enzyme) to see if you
can find a match.9,14,15
What if there is no match; that is, you have stumbled
on an unknown protein?
1. Isolate individual peptides from your mix
and run one through a mass spectrometer that has been modified to
o first randomly break the peptide into a mix
of fragments containing one, two, etc. amino acids
o then measure the mass of each fragment.
2.Enter the resulting data into a database
that matches the mass data with known pairs, triplets, etc. of amino acids.
3.With the aid of overlaps, assemble the
fragments to reveal the entire sequence of the peptide.
4."Back-translate" the amino acid
sequence to determine what sequence of nucleotides in DNA could encode that
peptide.
5.Search the genome database for an open
reading frame (ORF) that contains that sequence.
6.Translate that ORF to get the entire amino
acid sequence of your protein.9,14,15
Analysis
of Protein Function:
·
Attach
the protein whose partners to find to a solid matrix in a glass column.
·
Run a
solution containing a mix of possible partners through the column.
·
Those
that can bind to the target will stick; the others will flow through.
·
Pass a
buffer through the column which will weaken the binding interactions.
·
The
partners will wash out and can be identified16,17
·
The
budding yeast, Saccharomyces cerevisiae, provides an excellent tool for
discovering protein partners. It can easily be transformed with plasmids containing
foreign DNA sequences; that is, recombinant DNA.
·
It can
live in either the haploid or diploid condition.
·
Haploid
cells can fuse to form diploid cells if they are of opposite mating types
(designated a and α).
The two-hybrid system also takes advantage
of the fact that transcription factors (proteins) usually contain
·
a DNA-binding domain: a region that
binds to a specific sequence of DNA in the promoter of the gene they turn on;
·
an
activation domain: a region that is needed to activate the assembly of the
other components of the transcription apparatus16,18
This method exploits:
·
a DNA bacteriophage
that infects E. coli;
·
its
ability to remain infectious even if one of its coat proteins contains segments
of a foreign protein.18
Protein chips work on much the same principle as DNA
chips.
·
A
library of hundreds or even thousands of different proteins from your organism
are spotted individually in a known location on a chip.
·
The
chip is flooded with a solution of the protein whose partners you seek.
·
Any
proteins on the chip that are potential binding partners will bind your test
protein.
·
Adding
a fluorescent "tag" permits these to be identified.
Although simple in principle, protein chips
are far more difficult to work with than DNA chips because proteins
·
vary
enormously in their chemistry (e.g., hydrophobic vs hydrophilic);
·
bind to
each other by several types of noncovalent interactions.
The clearest picture of how different proteins interact
with one another to form functional complexes will come from determining the 3D
structure of the complex. There are two methods:
·
X-ray
crystallography;
·
nuclear
magnetic resonance (NMR) spectroscopy.
X-ray crystallography requires that you be
able to crystallize the protein. This is often a difficult task and especially
difficult for complexes of two or more proteins.
Here are some links to 3D images of
proteins.
·
the glucocorticoid
receptor
·
the tryptophan
repressor
Note that although in both cases the
proteins are binding to DNA, they are also binding to each other (as
homodimers). NMR spectroscopy has been especially useful in producing 3D images
of proteins that cannot be crystallized.
The following are the major types of
proteomics:
Expression Proteomics:
This is the qualitative and quantitative
study of the expression of total proteins under two different conditions. For
example, expression proteomics of normal cells and diseased cells can be
compared to understand the protein that is responsible for the diseased state
or the protein that is expressed due to disease. Using this method
disease-specific protein can be identified and characterized by comparing the
protein-expression profile of the entire proteome or of the subproteome between
the two samples. 26,28
For example, tumor tissue samples from a
cancer patient and the same type of tissue from a normal person can be analyzed
for differential protein expression. Using two-dimensional gel electrophoresis,
mass spectrometry combined with chromatography and microarray techniques,
additional proteins that are expressed in the cancer tissues or the proteins,
which are absent, or those, which are over expressed and under-expressed can be
identified and characterized. Identification of these proteins will give
valuable information about the molecular biology of tumor formation.27
Structural Proteomics:
Structural proteomics, as the name
indicates, is about the structural aspects, including the three-dimensional
shape and structural complexities, of functional proteins. This includes the
structural prediction of a protein when its amino acid sequence is determined
directly by sequencing or from the gene with a method called homology modeling.
This can be carried out by doing a homology search and computational methods of
protein structural studies and predictions. 29,30
Apart from this, structural proteomics can
map out the structure and function of protein complexes present in a specific
cellular organelle.31 It is possible to identify all the proteins
present in a complex system such as ribosomes, membranes, or other cellular
organelles and to characterize or predict all the proteins and protein
interactions that can be possible between these proteins and protein complexes.
Structural proteomics of a specific organelle or protein complex can give
information regarding supra-molecular assemblies and their molecular
architecture in cells, organelles, and in molecular complexes.32
Functional Proteomics:
This is an assembly type of proteomic method
to analyze and understand the properties of macromolecular networks involved in
the life activities of a cell. With these methods it will be possible to
identify specific protein molecules and their role in individual metabolic
activities and their contribution to the metabolic network that operates in the
system. This forms one of the major objectives of functional proteomics. For
example, the recent elucidation of the protein network involved in the
functioning of a nuclear pore complex has led to the identification of novel
proteins involved in the translocation of macromolecules between the cytoplasm
and nucleus through these complex pores.31
Functional proteomics is yielding large databases of
interacting proteins, and extensive pathway maps of these interactions are
being scored and deciphered by novel high-throughput technologies. However,
traditional methods of screening have not been very successful in identifying
protein-protein interactionsand their inhibitors. The identification and
measurement of changes in the concentration of specific proteins that cells make
as a result of their genetic response to specific toxicants, and how these
proteins are related to each other and to the specific biological condition of
the cell, also fall under functional proteomics.33
Applications of proteomics:
1] Application of
proteomics for discovery of protein biomarkers:
Biomarkers of drug efficacy and toxicity are becoming a
key need in the drug development process. Mass spectral-based proteomic
technologies are ideally suited for the discovery of protein biomarkers in the
absence of any prior knowledge of quantitative changes in protein levels. The
success of any biomarker discovery effort will depend upon the quality of
samples analysed, the ability to generate quantitative information on relative
protein levels and the ability to readily interpret the data generated. This
review will focus on the strengths and weaknesses of technologies currently
utilized to address these issues.20,24
2] Application of
Proteomics in the Study of Tumor Metastasis:
Tumor metastasis is the dominant cause of death in
cancer patients. However, the molecular and cellular mechanisms underlying
tumor metastasis are still elusive. The identification of protein molecules
with their expressions correlated to the metastatic process would help to
understand the metastatic mechanisms and thus facilitate the development of
strategies for the therapeutic interventions and clinical management of cancer.
Proteomics is a systematic research approach aiming to provide the global
characterization of protein expression and function under given conditions.
Proteomic technology has been widely used in biomarker discovery and
pathogenetic studies including tumor metastasis. This article provides a brief
review of the application of proteomics in identifying molecular factors in
tumor metastasis process. The combination of proteomics with other experimental
approaches in biochemistry, cell biology, molecular genetics and chemistry,
together with the development of new technologies and improvements in existing
methodologies will continue to extend its application in studying cancer
metastasis.34
3] Application of
Proteomics Technology to the Field of Neurotrauma:
Near-completion of the Human Genome Project has
stimulated scientists to begin looking for the next step in unraveling normal
and abnormal functions within biological systems. Consequently, there is new
focus on the role of proteins in these processes. Proteomics is a burgeoning
field that may provide a valuable approach to evaluate the post-traumatic
central nervous system (CNS). Although we cannot provide a comprehensive
assessment of all methods for protein analysis, this report summarizes some of
the newer proteomic technologies that have propelled this field into the
limelight and that are available to most researchers in neurotrauma.35
4] Application of
proteomics in renal disease diagnosis:
In the diagnosis and treatment of kidney
disease, a major priority is the identification of disease-associated
biomarkers. Proteomics, with its high-throughput and unbiased approach to the
analysis of variations in protein expression patterns (actual phenotypic
expression of genetic variation), promises to be the most suitable platform for
biomarker discovery. Combining such classic analytical techniques as
two-dimensional gel electrophoresis with more sophisticated techniques, such as
MS, has enabled considerable progress to be made in cataloguing and quantifying
proteins present in urine and various kidney tissue compartments in both normal
and diseased physiological states. Despite these accomplishments, there remain
a number of important challenges that will need to be addressed, (i) completely
defining the proteome in the various biological compartments (e.g.tissues,
serum and urine) in both health and disease, which presents a major challenge
given the dynamic range and complexity of such proteomes (ii) achieving the
routine ability to accurately and reproducibly quantify proteomic expression
profiles; and (iii) developing diagnostic platforms that are readily applicable
and technically feasible for use in the clinical setting that depend on the
fruits of the preceding two tasks to profile multiple disease biomarkers.21,23
5] The Application
of Proteomics in Neurology:
In neurology and neuroscience, many applications of proteomics
have involved neurotoxicology and neurometabolism, as well as in the
determination of specific proteomic aspects of individual brain areas and body
fluids in neurodegeneration. Investigation of brain protein groups in
neurodegeneration, such as enzymes, cytoskeleton proteins, chaperones,
synaptosomal proteins and antioxidant proteins, is in progress as phenotype
related proteomics. The concomitant detection of several hundred proteins on a
gel provides sufficiently comprehensive data to determine a pathophysiological
protein network and its peripheral representatives. The rapid spread of
proteomics technology, which principally consists of twodimensional gel
electrophoresis (2-DE) with in-gel protein digestion of protein spots and
identification by massspectrometry, has provided an explosive amount of
results.20
In Alzheimer’s disease, elevations in beta secretase
create amyloid/beta-protein, which causes plaque to build up in the patient's
brain, which is thought to play a role in dementia.[citation
needed] Targeting this enzyme decreases the
amyloid/beta-protein and so slows the progression of the disease. A procedure
to test for the increase in amyloid/beta-protein is immunohistochemical
staining, in which antibodies bind to specific antigens or biological tissue of
amyloid/beta-protein.20
6] Proteomics in
Urological Cancer Research:
Proteomic analysis allows the comparison of the
proteins present in a diseased tissue sample with the proteins present in a
normal tissue sample. Any proteins, which have been altered either
quantitatively or qualitatively between the normal and diseased sample are
likely to be associated with the disease process. These proteins can be
identified and may be useful as diagnostic markers for the early detection of
the disease or prognostic markers to predict the outcome of the disease or they
may be used as drug targets for the development of new therapeutic agents. The
purpose of this review is to outline the principle technologies involved in
proteome analysis and indicate current and potential future applications of
proteomic analysis in urological cancer research.23
Initially, researchers are concentrating on ovarian and
prostate cancers, which usually are not detected in early stages when the
cancer is progressing without symptoms. By using proteomics for early
detection, tumors may be treated before they spread (metastasize) to other
parts of the body. Scientists also are studying the most common, solid human
tumors including breast, colon, lung, and pancreatic cancers.20,23
7] Application of
Proteomics in Cardiovascular research:
The development of proteomics is a timely one for
cardiovascular research. Analyses at the organ, sub cellular, and molecular
levels have revealed dynamic, complex, and subtle intracellular processes
associated with heart and vascular disease. The power and flexibility of
proteomic analyses, which facilitate protein separation, identification, and
characterization, should hasten our understanding of these processes at the
protein level. Properly applied, proteomics provides researchers with cellular
protein “inventories” at specific moments in time, making it ideal for documenting
protein modification due to a particular disease, condition, or treatment. This
is accomplished through the establishment of species- and tissue-specific
protein databases, providing a foundation for subsequent proteomic studies.20,24
Heart disease is commonly assessed using several key
protein based biomarkers. Standard protein biomarkers for CVD include interleukin-6,
interleukin-8, serum amyloid A protein, fibrinogen, and troponins. cTnI cardiac
troponin I increases in concentration within 3 to 12 hours of initial cardiac
injury and can be found elevated days after an acute myocardial infarction. A
number of commercial antibody based assays as well as other methods are used in
hospitals as primary tests for acute MI.24
8] Application of proteomics
to diabetes research:
Proteomics is the investigation of all the proteins and
their various modifications making up a system, be that a cell, tissue or
organism. The techniques involved in proteomics allow the global screening of
complex samples of proteins and provide qualitative and quantitative evidence
of altered protein expression. This lends itself to the investigation of the
molecular mechanisms underpinning disease processes and the effects of
treatment. This review describes the main techniques of proteomics and how they
have begun to be applied to diabetes research.22
CONCLUSION:
Proteome is a complement of proteins expressed
in a cell at given time and proteomics means global analysis of this
protein complement. Detailed and comprehensive characterization of proteins is
a major goal of proteomics. This goal has become more realistic today with the
latest high-resolution mass spectrometers capable of faster sequencing in a
high-throughput fashion and with the emergence of new techniques such as
protein and peptide microarrays. A promising area for discovery is the
application of these advanced mass spectrometric and other quantitative
proteomic methodologies to laboratory diagnosis.
REFERENCES:
1. Simon R., et al
,"Investigating the correspondence between transcriptomic and proteomic
expression profiles using coupled cluster models". Bioinformatics. 2008, 24 : 2894–2900. doi:10.1093/bioinformatics/btn553. PMID 18974169.
2. Vikas D, et al..
"New frontiers in proteomics research: A perspective". International
Journal of Pharmaceutics.2005,299:1–18.
3. Buckingham, Steven
5. "The major
world of microRNAs". Micrornas 2003, 01-14
4. Anderson N, Anderson
N.. "Proteome and proteomics: new technologies, new concepts, and new
words". Electrophoresis 1998,19 :1853–61.
5.
Blackstock W, Weir M. "Proteomics: quantitative
and physical mapping of cellular proteins". Trends Biotechnol. 1999, 17 : 121–7.
6. P. James. "Protein
identification in the post-genome era: the rapid rise of proteomics.". Quarterly reviews of
biophysics.1997,30:
279–331.
7.
Marc R. Wilkins,. "From Proteins to Proteomes:
Large Scale Protein Identification by Two-Dimensional Electrophoresis and
Arnino Acid Analysis". Nature Biotechnology.1996, 14 : 61–65.
8. Wilkins, Marc R., et al. New Frontiers in
Functional Genomics. Proteome Research
9. Belhajjame, K. et al. Proteome Data
Integration: Characteristics and Challenges. Proceedings of the
10.
11.
Wilkins MR, Williams KL, Appel RD,
Hochstrasser DF. Proteome Research: New Frontiers in Functional Genomics ,
Principles and Practice. 1997, 3-540-62753-7.
12.
13. Fuchs, Jurgen, and Maurizio Podda, editors. Encyclopedia
of Medical Genomics and Proteomics.
14. Aebersold R., Mann M. Mass Spectrometry-Based Proteomics. Nature.2003,
422: 198–207.
15. Zhu, W., et al. 'Detection of
Cancer-Specific Markers Amid Massive Mass Spectral Data.' Proceedings of the
16. Zhu H, et al. Global analysis of protein
activities using proteome chips. Science . 2001,293:2101–2105
17. Arora PS,.Comparative
evaluation of two two-dimensional gel electrophoresis image analysis software
applications using synovial fluids from patients with joint disease. J Orthop Sci 2005,10,2: 160–6
18. Jorg von Hagen, VCH-Wiley Proteomics Sample Preparation. 2008,978-3-527-31796-7
19. Westermeier, R. and T. Naven.. Proteomics in
practice: a laboratory manual of proteome analysis. 2002, 3-527-30354-5.
20. Hye A, Lynham S,
Thambisetty M, et al. Proteome-based plasma biomarkers for
Alzheimer's disease. Brain. 2006,129 ,Pt 11: 3042–50.
21. Perroud B, Lee J,
Valkova N, et al. Pathway
analysis of kidney cancer using proteomics and metabolic profiling. Mol Cancer. 2006. 5: 64.
22. Yohannes E, et al . Proteomics analysis identifies molecular
targets related to diabetes mellitus-associated bladder dysfunction. Mol. Cell
Proteomics. 2008,7: 1270–85.
23.
24. Vasan R., Biomarkers of
cardiovascular disease: molecular basis and practical considerations. Circulation . 2006, 113 : 2335–62.
25. Weaver R., Molecular
biology , 3rd ed,
26. Karp N, et al, Impact of replicate types on proteomic expression analysis. Journal
of proteome research. 2005, 4:1867-71
27. Karp N, Lilley KS., Maximising sensitivity for detecting changes in protein expression:
experimental design using minimal CyDyes,. Proteomics.
2005 , 5:3105-15.
28. Martins D, et al., The untiring search for the most complete proteome representation:
reviewing the methods, Brief Funct
Genomic Proteomic. 2008, 7:312-21.
29. Dobrovetsky E, et al., A robust purification strategy to accelerate
membrane proteomics. Methods. 2007, 41:381-7.
30. Watson J.,
Towards fully automated structure-based function prediction in
structural genomics: a case study. J Mol Biol. 2007, 13;367:1511-22.
31. Norin M, Sundström M..Structural proteomics: developments in structure-to-function
predictions,Trends
Biotechnol. 2002 , 20:79-84.
32. Yakunin A., et al, Structural proteomics: a
tool for genome annotation. Curr Opin Chem Biol. 2004, 8:42-8.
33. Frederic C., Functional Proteomics Mapping of
a Human Signaling Pathway. Genome Res.,2004,14: 24-1332.
34. Cai Z, Chiu JF, He QY. Application
of proteomics in the study of tumor metastasis. Genomics
Proteomics Bioinformatics. 2004, 2:152-66.
35. Nancy Denslow,et al., Application
of Proteomics Technology to the Field of Neurotrauma. Journal of
Neurotrauma. 2003, 20: 401-407.
Received on 18.09.2009
Accepted on 23.10.2009
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Research J. Pharmacology and
Pharmacodynamics 1(3) Nov. – Dec 2009; 99-103