Reviews |
From the Departments of Physiology (D.K.A., I.N., J.E.V.E.) and Biochemistry (J.E.V.E.), Queens University, Kingston, Ontario, Canada.
Correspondence to J.E. Van Eyk, 429 Botterell Hall, Queens University, Kingston, Ontario, Canada K7L 3N6. E-mail JVE1{at}post.queensu.ca
| Abstract |
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Key Words: proteomics protein modification 2-D gel electrophoresis mass spectrometry cardiovascular disease molecular mechanism
| Introduction |
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Since proteins are involved in virtually every cellular function, control every regulatory mechanism, and are modified in disease (as the cause or effect), the proteome dictates the phenotype of the cell and, collectively, the tissue or organ that the cells comprise. This phenotype varies under normal conditions, such as cell cycle stage, differentiation, function, and age, or as a result of the onset of or interventions in response to acute insults or chronic diseases (for general reviews, see Haynes and Yates,2 Dutt and Lee,3 Hoving et al,4 and Blackstock and Weir5 ; cardiovascular/medical-based reviews, Jungblut et al,6 Dunn,7 and Banks et al8 ). Acute insults lead to rapid posttranslational modification (PTM) of proteins, whereas in chronic disease states, cotranslational and posttranslational protein modifications occur in concert with altered gene expression, leading to varied protein levels. For specific proteins, disease-induced modification will substantially affect function, which in turn has the potential to affect other proteins. The result is a dynamic, ongoing process of protein expression and modification. Proteomics is aimed at identifying and characterizing these protein changes.
Conceptually, proteomics is simple. In practice, it is
technically challenging. This is due to a combination of the dynamic
phenotypic modulation described above, which must be addressed for
proper experimental design and interpretation of the seemingly
limitless data that proteomic studies can provide. As outlined in
Figure 2
, numerous steps are involved in elucidation of a
proteome. Although a vast array of techniques may be used, proteomics
basically involves protein separation, protein identification, and
characterization of the nature and position of protein modifications
(for books exclusively on proteomics, see
Link,9 Wilkins et
al,10 and
Rabilloud11 ).
Two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS)
are currently the mainstay of proteomic analysis techniques,
but additional methods are exploited for reproducible and complete
separation of complex protein mixtures, as well as for characterization
of PTMs.
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Here, we overview the application of proteomics to cardiovascular research. We briefly describe considerations for appropriate experimental design, techniques used for proteomic analyses, various proteomic approaches, and examples of these approaches, including specific cardiovascular examples, where available. Although the recent advent of proteomics translates to only a sporadic selection of current examples in cardiovascular research, they will increase dramatically over the next few years. Integration of proteomics with functional data from established biochemical and physiological methods should lead, in the future, to development of functional proteomics, clarifying proteome dynamics in cardiovascular disease.
| Techniques |
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Sample Preparation
For accurate proteomic analyses, sample
preparation is of the utmost importance. Analysis of a proteome
at a specific moment of interest requires that it be arrested precisely
at that moment. Otherwise, further cellular processes may alter it
through addition or elimination of modifications. Key to the success of
resolving any proteome is maximization of protein solubility. Although
the proteome may be analyzed as a whole in a single
solubilization step, it is often preferable to prepare a set of
subproteomes. Fractionation methods exploiting specific protein
characteristics, such as their inherent chemical properties
(biospecificity12 ;
hydrophobicity13 14 15 ;
charge16 ) or differential
cellular
compartmentalization,17 18
may thus be used to selectively solubilize specific
subproteomes.19 20 21
This simplifies the daunting task of attempting to resolve thousands of
proteins simultaneously, with the added benefit that a
greater proportion of protein will most likely be solubilized. Of
course, with each additional fractionation step, a subproteomic
approach also increases the potential for undesired protein
modification. Whether analyzing an entire proteome or a group of
subproteomes, which is often guided by the specific research
objectives, sample preparation must be reproducible as well as
compatible with subsequent methods of protein separation and
identification.
Two-Dimensional Gel Electrophoresis
The workhorse of proteomic protein separation is 2-DE.
Separation in the first dimension is carried out by isoelectric
focusing (IEF), which focuses proteins by relative charge according to
their inherent charge, or isoelectric point (pI). Proteins are then
resolved orthogonally in the second dimension by their relative
molecular mass
(Mr),
typically by SDS-PAGE. Technical aspects of 2-DE have been widely
reviewed.22 23 24
After completion of 2-DE, a number of options for detection of protein spots exist, the more common including Coomassie, zinc, or silver staining; 32P or 35S radiolabeling; and/or immunodetection. Although radiolabeling is the most sensitive detection method, silver is the most commonly applied. Introduction of new fluorescent dyes with a variety of detection wavelengths and sensitivities approaching that of silver has great application potential. Experimental requirements, however, generally dictate the choice of detection method.
Image analysis follows 2-DE. Adequate image reproduction is essential to properly map detected spots. Specialized image analysis software is now available from a number of sources to deal with the tremendous complexity of protein spot patterns. Such software must fulfill a number of requirements, including spot detection and quantification, and the abilities to perform both multiple image alignments and image comparisons.25 26 Although not absolutely essential, statistical functions are often incorporated into these software packages for complete quantitative image analysis.
Alternative Protein Separation Methods
Although 2-DE is the most popular protein separation
technique for proteomic analyses, other separation methods may
be warranted, provided that they have the ability either to achieve the
resolution of 2-DE or to isolate a subproteome not amenable to
separation by 2-DE. Well-established separation methods based on the
physical attributes of proteins, alone or in combination, include ion
exchange, size exclusion, reversed-phase high-performance
liquid chromatography (HPLC) (for review, see Opiteck
et al27 and
Patterson28 ;
noncardiovascular, see Link et
al29 ), capillary IEF, and
capillary zone electrophoresis (for review, see
Manabe30 31 ;
noncardiovascular, Jensen et
al32 and Shen et
al33 ). Another separation
method, affinity chromatography, is extremely
selective, exploiting protein affinity for antibodies, specific target
proteins, or chemical moieties (cardiovascular, see
Damer et al34 and Ping et
al35 ). Affinity-based
separation may be achieved by conventional column
chromatography, immunoprecipitation, or by the newly
developed "protein chip" method (for review, see Williams and
Addona36 ;
noncardiovascular, eg, Nelson et
al37 and von Eggeling et
al38 ).
Some of these methods are advantageous in that they may be carried out under native or denaturing conditions. This is possible because proteins fractionated by many of these alternative methods remain in a soluble state, unlike protein subjected to 2-DE. Isolation of proteins in their native state thus provides the opportunity for in vitro biochemical assays after separation. A further benefit, in terms of proteomics, is that maintenance of solubility allows such methods to be linked directly to MS.
Protein Identification by Mass
Spectrometry
After separation and detection, proteins of interest
must be identified. The most significant breakthrough in the evolution
of proteomics is the development of MS for protein identification (for
review, see References 3939 to 43). Over the past few years, improvements
in MS have made it an unrivaled technique, by virtue of its accuracy of
mass detection, its detection sensitivity, its ability to deal
simultaneously with mixtures of multiple proteins, and its
amenity to automation and therefore, high throughput.
MS instruments range, in relative terms, from simple (MALDI-TOF) to highly complex tandem (MS/MS). In all mass spectrometers, peptides are ionized from the sample. This is achieved either by matrix-assisted laser desorption/ionization (MALDI) of a solid-state sample or by electrospray ionization (ESI) directly from the liquid phase. Ionized peptides are separated on the basis of their mass-to-charge ratio and detected according to their time-of-flight (TOF) distribution or analyzed by quadrupole mass filters. In tandem MS/MS, an ionized peptide of interest is selected by the first MS and fragmented by collision with inert gas, and the resulting fragments are then analyzed in the second MS. Modern ESI-based MS/MS may use LC systems such as capillary zone electrophoresis or very low flowrate reversed-phase HPLC before ionization to fractionate complex peptide mixtures. At the very least, all MS provides precise peptide masses, whereas more sophisticated instruments (particularly tandem MS) also allow peptide sequence determination.
A common approach to rapid MS protein identification is peptide mass mapping. Peptide mapping relies on in-gel digestion of proteins by sequence-specific proteases (ie, trypsin, Asp-N, Lys-C) or chemical reagents (ie, CNBr). Since most amino acid residues have a unique mass, protein digestion will yield a set of distinct peptides specific to each protein. A mass spectrum of eluted peptides results, therefore, in a unique peptide mass fingerprint (PMF). The set of peptide masses obtained by MS is then used to search against protein databases created by "in silico" cleavage of all known, predicted, or partial protein sequences (for review, see Fenyo44 ). The efficiency of this technique is such that it has become commonplace for rapid protein identification (noncardiovascular, see Conrads et al,45 Karaoglu et al,46 and Berndt et al47 ). For unambiguous protein identification, additional protein sequence information is often required, which can be achieved by tandem MS. A sequence of only five amino acid residues is often sufficient to identify a protein, unless it is obtained from a highly conserved structural or binding motif. In such cases, additional sequence information will be necessary to narrow down the possibilities and unequivocally identify an unknown protein. As MS instruments evolve, it is hoped that they will all eventually be capable of yielding sequence data, increasing the rigor of protein identification over that of mass fingerprinting.
| Application of Proteomics to Cardiovascular Research |
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Traditional Proteomics: Creation of Protein
Inventories
Traditional proteomic analyses seek to resolve
the entire array of proteins present in a cell during a particular
condition or at a given moment in time. Consequently, this provides a
protein inventory for that particular set of circumstances. Initial
proteomic papers, which focused on 2-DE separation of myocardial tissue
proteins, were at best able only to tentatively identify a handful of
proteins.48 49 50 51 52 53
Importantly, however, they demonstrated the potential of
proteomicsthe feasibility of simultaneously separating
and detecting hundreds of proteins, with the potential to identify and
characterize differences between experimental samples.
Compilation of information obtained from such inventories facilitates protein database construction. For proteomics, these databases ideally should provide a visual image of a 2-D gel from which one may select a protein spot of interest and obtain information about that protein (ie, Mr, pI, amino acid sequence if available, function, any PTMs, method of identification, etc) either directly from within the database itself or by cross-referencing to other protein databases (ie, SWISS-PROT, TrEMBL). Although current 2-D gel analysis software is capable of producing such databases, technical issues with 2-DE made database reliability questionable until only very recently. These issues included difficulties with IEF reproducibility and the inability to resolve all the proteins within a proteome. Two particular aspects influencing total proteome resolution by 2-DE are ineffectiveness at distinguishing lower-abundance proteins, especially in the presence of highly abundant proteins, and underrepresentation of specific classes of proteins (particularly basic and membrane proteins).
The most crucial improvement in IEF reproducibility was the introduction of immobilized pH gradient (IPG) gels. In the past, poor IEF gel-to-gel reproducibility existed both within and between laboratories, for a variety of reasons.54 55 IPG gels provide consistently reliable pH gradients, a lack of which was the main drawback to carrier ampholytebased 2-DE. IPG gels are now commercially available in a wide variety of gradients, from pH 3 to 12, in both broad (pH 3 to 10) and narrow (a variety of single pH unit) "zoom" ranges.56 57 58 Coupling of zoom gels with a subproteomic approach facilitates increased protein resolution and therefore detection of both lower-abundance proteins and protein modifications that might otherwise go undetected.
Detection of both lower-abundance proteins and subtle changes in PTMs is facilitated by reduction of proteome complexity through a subproteomic approach. For example, our recently developed selective extraction method, called "IN Sequence," enriches for high-abundance myofilament proteins in a single extract.59 This is particularly useful because fractionation facilitates not only the investigation of myofilament proteins but also that of numerous lower-abundance proteins present in other extracts. Furthermore, this method allowed detection and quantification of a very subtle change in protein phosphorylation (of myosin light chain 1, MLC1), which was otherwise obscured in whole-cell homogenates.59
Other recent improvements are now addressing particular classes of proteins that have been problematic for 2-DE. Both basic and membrane proteins have historically been underrepresented on 2-D gels. Basic proteins are difficult to focus during IEF because of electroendoosmotic effects at high pH and the resulting cathodic drift within the gel. Recent efforts have been applied to overcome this, with strategies ranging from addition of organic solvents to reduce cathodic drift60 to subproteomic enrichment of basic proteins by selective precipitation.61 Another problem with basic proteins, as well as membrane and membrane-associated proteins, is their tendency to aggregate during protein separation. This arises from their extreme hydrophobicity. Progress has recently been made in 2-D analysis of such proteins by differential combinations of sample treatment, fractionation, and detergent application (for review, see Pasquale et al62 ; noncardiovascular, see Santoni et al63 64 ). Although not yet applied to cardiovascular research, these advances may prove useful in the study of proteins associated with, for example, Ca2+ handling, mitochondria, second messenger signal transduction cascades, etc. An interesting study by Macri and colleagues17 demonstrated that altering solubilization conditions improved the resolution and detection of membrane proteins from cardiac sarcoplasmic reticulum and sarcolemmal fractions, while having little effect on whole-tissue homogenates. These differences in ability to detect these proteins were apparent only when membrane proteins were already enriched (by use of subproteomics). Despite this advance, not all membrane proteins were detected by 2-DE (ie, sarcoplasmic/endoplasmic reticulum Ca2+-ATPase, SERCA17 ), indicating that further refinement of such techniques is still required and further exemplifying the highly complex considerations that one must deal with in the design and implementation of a proteomic study.
Many of these advances, however, are contributing toward improved reliability of 2-D gel protein databases. Pioneering proteomic work by the laboratories of Dunn and Jungblut led to the creation of numerous online 2-D databases of human, dog, mouse, and rat myocardium.65 66 67 68 69 70 71 72 73 74 75 They are only partially complete (with roughly 200 proteins identified), but they provide a foundation for the inventory of these particular tissues. These freely accessible works in progress are tremendously important, because they provide researchers with a basis for visualization of changes in protein patterns resulting from the conditions of their particular study. For proteomics to fulfill its potential, comprehensive protein inventories must be prepared for the variety of species and tissues studied in cardiovascular research, and they must remain freely accessible.
Protein Profiling or Protein Signatures
For certain applications, protein identification is not
always a necessity. Simply monitoring a protein profile after
resolution by one or more separation methods is often sufficient to
address whether two or more experimental conditions induce the same
protein changes. This is advantageous when determining, for example,
molecular pathways of action by multiple drugs in pharmaceutical drug
discovery programs. Direct comparison of their protein profiles or
"protein signatures" facilitates rapid screening of differences
between various treatments without an absolute necessity for protein
identification (for review, see Steiner and
Witzmann76 ). The assumption
underlying this approach is that there is a consistent and
predictable pattern of protein change or modification associated with
every particular cellular event or phenotype. Testing of the
validity of phenotype consistency will, with time,
be achieved through proteomics. Such an approach may, of course, also
be applied to comparison of drug-treated versus untreated, mutant
versus wild-type, or healthy versus diseased samples.
One recent technical advance that will help in this approach is the introduction of fluorescent dyes, which have sensitivity similar to that of silver stain, but with a greater dynamic linear staining range (for review, see Patton77 ). Unlike silver, however, the use of two or more dyes that fluoresce at different wavelengths provides the opportunity to coelectrophorese differentially stained samples. Direct comparison of samples may thus be achieved within the same gel, reducing both the subjectivity of gel matching and the time required for analysis. Such a method is applicable regardless of experimental question.
Molecular Mechanisms of
Cardiovascular Disease
Although traditional proteomics and protein profiling
provide important research information, the ultimate goal of developing
proteomic techniques for cardiovascular research lies
in its ability to characterize molecular mechanisms of disease. In this
case, identification of the protein and the nature of its modification
are essential. Proteome variations that one might expect depend on
characteristics of the particular study being conducted. Altered levels
of more than forty proteins have been identified to date in a variety
of cardiovascular proteomic experiments
(Table
).
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For chronic conditions or disease states, modification of the proteome often manifests itself as altered protein levels due to specific gene upregulation or downregulation, isoform switching, or de novo protein synthesis. For example, the abundance of heat-shock proteins (HSP) and mitochondrial and other proteins involved in energy production was documented to vary significantly in a number of heart failure models.78 79 80 81 82 83 84 Isoform switching has also been reported in the case of ventricular expression of atrial MLC1 and MLC2 in neonatal rat myocytes from a phenylephrine-stimulated hypertrophy model.80 De novo synthesis of HSP72 and two unknown proteins related to the HSP70 family was shown to occur in heat-stressed endothelial cells.81 In addition, a number of putative PTMs have been documented in dilated cardiomyopathy.65 66 68 78 79 82 83 84 For example, detailed 2-DE analysis of dilated cardiomyopathydiseased human myocardial tissue revealed more than fifty HSP27 protein species by immunoblotting.66 82 Although only nine were finally confirmed to belong to HSP27 and none were analyzed for the presence of PTMs, this illustrates the potentially large number of PTMs possible for a single protein.
In acute conditions, in which there is often insufficient time to recruit de novo transcription and translation, PTMs would be the primary mechanism of protein change, resulting from modification of specific amino acids. To date, cardiovascular proteomic examples of PTM identification are lacking. A prime example of such a study is the identification of phosphorylation and palmitoylation in a membrane-receptor signal transduction cascade.85 Of course, one should not overlook the possibility of variations in protein levels evinced by protein degradation as a response to acute injury, such as with troponin I in myocardial stunning.86 87
Molecular mechanisms are addressed in one of two ways: by
broad-based screening or by a more focused proteomic approach.
Broad-based screening is applicable in situations in which little is
known of the molecular mechanisms or for an unbiased look at the entire
proteome to identify previously unknown protein changes involved in the
disease or condition. This extends traditional or protein profiling
approaches to the next logical step, identification of the
modifications. Cardiovascular examples of broad-based
screening include extensive studies on human and bovine
cardiomyopathies, as well as many of the studies
mentioned above that document changes in protein levels (see
Table
).
Focused proteomics, conversely, analyzes only a discrete
subproteome. This may be applied to situations in which a molecular
mechanism is understood but some components of this mechanism are not.
One such example, in cardiovascular research, was
carried out by use of protein kinase C (PKC) monoclonal antibodies to
immunoprecipitate proteins involved in PKC signaling
cascades.35 This recent
study identified a large number of previously
unsuspected proteins that may be downstream targets of PKC signaling
during myocardial
preconditioning.35 An
analogous approach in vascular smooth muscle identified a number of
phosphatase-binding proteins by means of microcystin-biotin affinity
chromatography.34
Regardless of the approach, whether broad-based or focused, the most
difficult and time-consuming process for proteomic studies of molecular
mechanisms is identification of a protein and, if modified, the nature
and site of this modification.
Before the advent of MS, this difficult process was limited to traditional methods of amino acid analysis, N-terminal amino acid sequencing by Edman degradation, or in cases in which antibodies against a protein were available, by immunological methods. Although amino acid analysis and Edman degradation require pure protein for accurate identification, MS allows concurrent identification of multiple proteins by means of PMFs. This makes MS an indispensable tool for protein identification in situations in which proteins have not successfully been resolved from one another (ie, comigration during 2-DE69 ).
| Protein Identification |
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As described in the Techniques section, there are a number of commonly used exoproteases and endoproteases for in-gel digestion, as well a number of technical tips to improve peptide digestion and recovery.89 90 For optimization of PMF, it is important to note that the choice of protease or combination of proteases can have a dramatic effect on coverage of protein sequence. For example, human myocardial MLC1 sequence coverage was 56% with Asp-N digestion, compared with 44% for trypsin, whereas a combination of both Asp-N and trypsin increased coverage to 80%, thereby increasing the probability of correct protein identification.91 Multiple protease digestion, however, may not always be beneficial. For example, the specificity of trypsin and/or Lys-C would lead to far too small and far too numerous peptide fragments if used to digest troponin I, whereas a partial digest or a single cleavage by Asp-N does allow correct identification. Thus, optimal conditions for fragmentation of a particular protein must be determined empirically and are not always inherently obvious.
PMF protein identification is also complicated in the study of species underrepresented in protein databases. This is often the case with cardiovascular proteomic studies, because some species traditionally used as cardiovascular models (rabbit, dog, and swine) currently face this problem. This harkens back to the importance of protein inventories. For underrepresented species, one needs to maximize amino acid sequence (protein) coverage, which may necessitate multiple PMFs. Low amino acid sequence homology between proteins present in databases and the protein under examination may further complicate cross-species identification. In this case, greater sequence coverage is also beneficial because it increases the likelihood of matching a highly conserved region of the protein.92 Database searches based on newly developed algorithms for protein matches based on weak amino acid sequence homologies93 should improve the ability to positively identify such proteins.
Even the best strategy may lead to false-positive protein identification, for a number of reasons. Partial amino acid sequences obtained by MS may be too short or not specific enough (ie, in nonconserved regions of the protein). Database size may be insufficient, with either few representatives of the protein or an absence of that protein sequence for a particular species of interest. A small number of detected peptide fragments would result in poor sequence coverage, a problem that may be exacerbated by the presence of PTMs, which might also contribute to decreased numbers of matching peptides. Also, if peptide masses were not obtained within a reasonable peptide mass tolerance, results might be misleading, suggesting incorrect protein identity, or inconclusive, with no likely matches obtained. Finally, previously unidentified proteins would be absent from any protein database. Therefore, even with the advantages of MS, confidence in protein identification is supported by means of additional identification methods.
Protein quantification is important in assessment of changes in gene expression resulting from disease or a particular cellular intervention. One new technology, which allows accurate quantification by MS, is stable isotope labeling. This ability to quantify samples represents an exciting new dimension for MS. The method involves growing cultured cells in two differently labeled media,94 or more recently, by labeling after sample preparation, through the use of isotope-code affinity tag peptide labeling.95 Proteins from two different experimental conditions are reacted with the isotope-code affinity tag reagent (consisting of biotin and a specific cysteine [thiol] reactive group), one labeled with hydrogen ions, the other with deuterium ions, to produce a mass difference. With or without further protein separation, a particular protein (or group of proteins) is digested, and the biotin-containing cysteine-derivatized fragments are isolated via avidin affinity. The ratio of the light to heavy peptide fragments determined by MS indicates differences in the quantity of that particular protein between the experimental conditions. Although this is the first flexible method for quantitative MS, the technique is limited in terms of PTM identification. Because protein derivatization occurs after sample harvesting, it may lead to further PTMs that were not the result of original experimental conditions.
| Identification and Characterization of PTMs |
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Relative to standard biochemical methods, the use of MS for PTM identification is powerful because it can provide, in a single step, information about the type of modification as well as mapping the modified amino acid residue. In addition, whereas various biochemical methods are individually geared toward identifying one form of PTM, bioinformatic analysis of MS PMF data may be carried out for concurrent identification of up to twenty-two known PTMs or may be used to predict possible modifications on the basis of amino acid sequence homology. Several web-based programs are available to assist in identifying PTMs (ie, MODFIND,104 BOLD,105 NetPhos,106 ), and new ones are continually being introduced (eg, GlycoSuite107 ).
Since pI shifts of protein spots on 2-D gels may also be indicative of PTM, determination of the modifications producing these shifts in the myocardium (or sample of interest) are essential for revealing their roles in physiological function. Ultimately, the type of modification and the modified amino acid residue(s) must be determined, through either biochemical techniques, amino acid sequencing, or MS analysis. In the case of MS, the sample must be analyzed by an instrument that further fragments peptides, allowing their analysis at the amino acid level. This may now be done by a MALDI-TOF-PSD (postsource decay), but many researchers rely on the more complex LC-nESI triple quadrupole or the hybrid MALDI quadrupole TOF (ie, Q-TOF). The more sophisticated the MS instrument, the greater the likelihood of accurately identifying a specific PTM on a particular protein. Even though these experiments are very time-consuming, they are absolutely critical for determination of underlying molecular mechanisms of protein change.
| Functional Proteomics |
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To completely understand how every protein modification either contributes to or plays a role in an observed phenotype, it is important to delineate the exact sequence of events that occur. A time course of protein change with measured alterations in physiological and biochemical parameters allows a reconstruction of the events leading up to and/or resulting from an altered phenotype. As a result, it may be possible to determine exact functional changes arising from specific protein modifications or of specific protein modifications arising from a particular functional change. In this way, functional proteomics may reveal whether a protein modification is the cause or the result of a particular disease process. To add to the complexity of the issues involved in a functional proteomic study, it must also be mentioned that a single observed phenotype may arise from multiple pathways. For example, an observed systolic contractile dysfunction might arise as a result of modification of calcium-handling proteins, of myofilament proteins, or some combination of the two. We hope that this provides some idea of the daunting logistics of incorporating functional data into the already complex process of conducting a proteomic analysis, which we hinted at earlier. It will not be easily amenable for a single laboratory to tackle all aspects of a functional proteomic study on its own. Therefore, the feasibility of such studies will most likely require collaboration between laboratories involved in the biochemistry, physiology, and pathophysiology of cardiovascular disease that are properly equipped to provide specific individual components of an integrated functional proteomic effort.
Incorporation of proteomics within this established cardiovascular research framework provides a means of identifying and characterizing complex protein changes associated not only with cardiovascular dysfunction but also with pharmacological interventions taken in response to dysfunction. Proteomics has clearly revealed dynamic and remarkable changes that occur at the cellular level, many of which have never previously been observed. Successful incorporation of new technologies and the coordinated application of the variety of proteomic approaches now available will help to unravel the intricacies of proteome change in cardiovascular disease.
| Acknowledgments |
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| Footnotes |
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This Review is part of a thematic series on Proteomics, which includes the following articles:
Cardiovascular Proteomics: Evolution and Potential
Proteomics in the Cardiomyopathies and Heart Failure: A Step Beyond Genomics
Dynamic Cellular Response: Detection and Characterization of Protein Posttranslational Modification
Applied Proteomics: Receptor-Mediated Response
Applied Proteomics: Mitochondrial Proteins and Effect on Function
Jennifer E. Van Eyk, Guest Editor
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