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Molecular & Cellular Proteomics 4:857-872, 2005.
© 2005 by The American Society for Biochemistry and Molecular Biology, Inc.
From the Protein Function Group, Faculty of Veterinary Science, University of Liverpool, Crown Street, Liverpool L69 7ZJ, United Kingdom
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ABSTRACT |
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The current generation of widely available mass spectrometers has more than adequate resolution to provide unit mass resolution across the useable mass range. At this level of performance, the possibility has arisen of developing "mass tagging" approaches for the differential analysis of protein expression. A protein or signature peptide is labeled with a tag that exists in isotopically labeled forms such that two cellular states being compared are labeled with a "light" or "heavy" variant of a tag, and the analytes are mixed before analysis. Mass spectrometric assessment of the heavy/light ratio then enables comparative expression analysis unaffected by issues such as instrument response, sample purity, and so on.
Many such mass tagging approaches use chemical labeling of complex mixtures of proteins in vitro after their extraction from cells. Such approaches include ICAT and its modifications (4–7), acrylamide labeling (8), 18O-labeling during proteolysis (9, 10), and guanidination of lysine residues (11–13). In all of these approaches, the degree of labeling is controlled by the isotope enrichment of the labeling reagent and the completeness of the modification chemistry and is applied to proteins or protein mixtures obtained after cell disruption. However, labeling after cell breakage precludes metabolic labeling, a variant approach in which stable isotopes (usually in the form of labeled amino acids) are incorporated biosynthetically into protein in vivo, via the process of translation. It is timely, therefore, to address the opportunities and pitfalls associated with metabolic labeling of proteins in vivo.
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Radioactive Versus Stable Isotopes |
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40 TBq/mmol) that even rather modest incorporation can lead to measurable accumulation of labeled material. This permits relatively short labeling time windows for incorporation of label. Furthermore, a 35S label is sufficiently energetic that it is not impeded greatly by media such as polymerized acrylamide and can therefore be used successfully in autoradiography of 1DGE1 or 2DGE. By contrast, with the types of mass spectrometer in common usage for proteomics research, it is improbable that an incorporation of a stable isotope precursor of 1% would be detectable, because particularly in single-stage instruments the noise floor (whether chemical or instrument generated) might obscure this degree of labeling. To overcome this limitation, effective metabolic labeling would require a substantial incorporation (perhaps minimally on the order of 5–10%) for accurate quantification.
Most of the emphasis on stable isotope labeling in vivo has thus far been placed on comparative proteomics in which the incorporation of a metabolic label is used to identify one of the components in a pair-wise comparison (Table I). Although apparently straightforward, this approach embodies several assumptions that are not always tested rigorously. First, it is assumed that the proteins are fully labeled with the stable isotope precursor such that the heavy/light ratio can be taken to directly represent the relative amounts of the analyte in the two systems. Second, it is often assumed that the stable isotope label in the precursor amino acid is not differentially metabolized and that it does not appear in a different amino acid.
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Selection of Stable Isotope-labeled Precursor |
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In principle, any of the 20 naturally occurring amino acids could be used as a precursor for labeling proteins, but several factors conspire to diminish those choices (summarized in Table II). To a first approximation, it is reasonable to assume that all microbes and plants are competent in the synthesis of all 20 amino acids. In animal metabolism, however, a distinction is made between those amino acids that can be synthesized by the organism (the non-essential amino acids) and those that must be provided in the diet (essential amino acids). Essential amino acids are His, Ile, Leu, Lys, Met, Phe, Thr, Trp, and Val. If the amino acid is non-essential, then the cell or organism is able to synthesize that amino acid from precursors that are not themselves labeled, which has the effect of reducing the relative isotope abundance of the precursor pool. It is also worth recognizing that some amino acids considered to be non-essential in intact animals are obligatory for cells in culture (possibly reflecting the roles of different cell types in biosynthesis of amino acids). For example, arginine, although synthesized in the reactions of the urea cycle, is often provided in the culture medium, presumably to avoid depletion of the arginine pool by protein synthesis, which would compromise the operation of this essential metabolic cycle. Further, some amino acids are metabolically highly labile and are rapidly deaminated or transaminated, and the carbon skeleton generated by this process is then oxidized or used in other biosynthetic pathways. This could deplete the labeled precursor or could even result in rapid recycling of label into other amino acid pools, which might then change the pattern of isotope incorporation into proteins.
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-carbon attached hydrogen/deuterium atom can be considered to be chemically stable but is metabolically labile, in that the reversible process of transamination creates the -keto (2-oxo) acid. A good illustration of this behavior has been provided by several studies in which proteins were labeled in vivo with [2H10]leucine (Fig. 1). Although the deuterated amino acid was incorporated into protein, the masses of the products, whether analyzed as intact proteins or as tryptic fragments, were consistent with the incorporation of nine deuterium atoms for each leucine residue (22, 23). The most likely explanation was that the -carbon deuterium atom had been lost by rapid and reversible transamination. Indeed, more recent data from our laboratory have shown that this transamination process can be tissue-specific and that liver demonstrates labeling patterns consistent with the incorporation of amino acids that have partially retained the -carbon deuteron, whereas skeletal muscle incorporated only amino acids lacking the -carbon deuteron (24). The incorporation of [2H10]leucine (and other amino acid precursors carrying deuterium at the -carbon atom) has been used to generate amino acid composition data for use in the identification of intact proteins. Loss of a deuterium atom from the amino acid precursor is readily detected when heavy and light peptides are compared. However, when the mass comparison is made at the level of the intact protein, the decrease in mass accuracy can obscure this loss, causing miscalculation of the number of leucine residues in the protein and possibly misidentification. Therefore, when studying intact proteins, either the fate of the -carbon in a given tissue must be determined or precursors deuterium-labeled at the -carbon should be avoided. Of course, any loss of label should be immediately apparent in mass spectrometric analysis of peptides derived from the protein. This need not be a specific protein in that any protein synthesized in the same tissue and subcellular compartment will report on the isotope labeling pattern of the precursor.
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-amino group. Again, it is worth remembering that this amino group is transferred to another amino acid (often 2-oxo glutarate, yielding labeled glutamate) and that this has the potential not only to reduce the mass offset, but also under extreme circumstances might deliver label via another amino acid. The amino acids used most commonly for stable isotope studies are those that are least likely to contribute isotopically labeled atoms to general metabolic pools. Otherwise, this loss not only reduces the amount of label available for incorporation but also increases the chance of isotope appearing in other protein precursors. For example, labeled glutamate would be rapidly transaminated to 2-oxoglutarate and enter the tricarboxylic acid cycle. From there, labeled carbon atoms would be able to enter aspartate via oxaloacetate. Likewise, labeled alanine would generate the corresponding keto acid, pyruvate, which could be converted to lactate, or to acetyl CoA, leading in the latter instance to a range of metabolic products. For such reasons, most studies have used leucine, followed by lysine, arginine, and to a lesser extent serine, glycine, histidine, methionine, valine, and tyrosine. The isotope used in most of these early studies was predominantly 2H, although more recent studies have switched to 13C-labeled amino acids. This is almost certainly because of the propensity of 2H-labeled peptides to migrate differently from 1H counterparts under chromatographic conditions, particularly on reversed-phase HPLC (25–27).
A further consideration in the selection of the most suitable amino acid is the abundance of that amino acid in any proteome. Amino acids such as leucine and serine are the most abundant at around 10% of all amino acids (commensurate with each having six codons), whereas at the other extreme, tryptophan and cysteine are relatively rare (around 1% of amino acids in a proteome). Fig. 2 maps the correlation of amino acid abundances among four proteomes; those of the yeast Saccharomyces cerevisiae, the chicken Gallus gallus, the bacterium Salmonella typhimurium, and the malaria parasite Plasmodium falciparum. Although the correlations are strong, and the overall ranking of abundance is similar, the differences between proteomes are sufficient to advocate of a quick analysis of amino acid frequencies. In particular, the genome of P. falciparum has a high A+T content (76% AT in coding regions, 81% overall), which has a marked effect on the amino acid distribution within the proteome (www.plasmodb.org). Compared with the yeast proteome, lysine and asparagine residues are markedly elevated (Fig. 2) (codons are AAA, AAG and AAT, AAC, respectively) and arginine residues (codons CGT, CGC, CGA, CGG) are notably depressed.
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Separation Methods |
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Uses of Metabolic Labeling with Stable Isotopes |
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Although most studies have focused on peptides derived from isolated proteins or from complex mixtures, some studies have emphasized mass measurement of intact proteins. In this instance, the mass offset between the light and heavy variants can be used to determine the abundance of a particular amino acid in a protein (30).
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The Necessity for Complete Labeling of Precursor Pools |
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1.0 and proteins have been almost completely replaced by protein turnover, then there can only be fully light or fully heavy peptides, irrespective of the number of amino acids in the peptide. However, if the precursor RIA is less than 1, the mass isotopomer distribution becomes more complex. Consider a simple experiment in which a precursor amino acid RIA has been set at 0.5 by appropriate mixing of labeled and unlabeled forms. As the amino acid is incorporated into protein one residue at a time, it has a 50/50 chance of being heavy or light, creating a complex mixture of protein molecules that differ both in the numbers of heavy amino acids and in their positions. Although analysis of the intact protein is problematic because of the distribution of signal over large numbers of variants of the protein of subtly different mass, it is feasible to explore these distributions at the level of the tryptic peptides. For example, a peptide with two instances of a particular amino acid will exit in four positional variants: HH, HL, LH, and LL, the middle two of which have the same mass; there are therefore three mass variants. If the precursor RIA is 0.5, the three mass peaks will exist in the ratio 1:2:1. For a peptide containing three instances of the amino acid, the distribution (H3, H2L, HL2, L3) will follow the binomial expansion and yield an abundance ratio of 1:3:3:1 (Fig. 3).
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Intact multicellular organisms (and particularly animals) present additional complexities and require novel solutions. It is possible, for example, to obtain stable isotope-labeled nematode worms by feeding them on uniformly labeled bacteria (20). Proteins in the malaria parasite P. falciparum can be labeled by growing the parasites in medium containing human erythrocytes and labeled isoleucine. Human hemoglobin contains no isoleucine residues, and P. falciparum cannot synthesize this amino acid de novo. Therefore, isoleucine must be included in the medium, and if labeled with stable isotopes can be used for specific, high abundance labeling of the proteome. This elegant study by Nirmalan et al. (33) also proved that the labeling was efficient, that the degree of incorporation attained nearly 100%, and that by implication the precursor RIA was close to unity.
However, experiments in intact organisms (and particularly in animals) usually cannot be designed so that the precursor RIA is unity. First, this would probably entail a synthetic diet with attendant issues of palatability. Second, any pre-existing protein in the body of the animal before the experiment began would be catabolized intracellularly and therefore contribute unlabeled amino acids to the labeled precursor pool, diluting that pool and diminishing the value of RIA. In such experimental systems, it is inevitable that the precursor RIA will be less than unity. Therefore, the isotope incorporation profiles become more complex, and more rigorous analysis of the mass isotopomers is required (24, 34, 35).
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Stable Isotope-labeled Amino Acids for Comparative Proteomics |
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An essential prerequisite of this experiment is that the heavy proteins are fully labeled. As the cells grow in labeled medium and double, the original pool of unlabeled amino acids is diluted. To illustrate, consider a cell culture exposed to medium containing a stable isotope labeled amino acid at an RIA of 1.0. After one doubling time (D), the cell biomass would have increased by a factor of 2, so all proteins will be (at a minimum) 50% labeled. In practice, many proteins will be much more highly labeled than this because they have been turned over intracellularly during the first doubling time. In fact, the only proteins that attain the minimal labeling of 0.5 are those that are turned over at virtually imperceptible rates. By contrast, a protein with a half-life of 0.1 D would be virtually fully labeled even within that first doubling period; 50% of this protein is replaced within one-tenth of the cell doubling time. Of course, because it is impossible to know the turnover rate of each protein in advance, it is necessary to ensure that even slow turnover proteins are fully labeled. After 1 D, 50% of these slow turnover proteins would be labeled; at 2 D, 75%; 3 D, 87.5%; 4 D, 94%; 5 D, 97%; 6 D, 98%; and 7 D, >99%. Seven doubling times should ensure that all proteins are fully labeled. It is unfortunate that some studies do not provide this precise methodological information. Without an appreciation of the need for complete labeling, cells may be only partially labeled, which in subsequent comparative analysis will bias the expression ratios.
The majority of the studies described so far have determined the "relative" abundances of protein in two samples, one labeled with the heavy amino acid and the other unlabeled. For example, protein changes during muscle differentiation were monitored using [2H3]leucine as the labeled amino acid (17). Although quantification was consistent, analysis was hampered by the overlap between the isotopomers of heavy and light peaks, requiring a correction to peak intensities. Quantification was confirmed at the level of fragment ions during MS/MS. Because a goal for proteomics is full automation, more recent studies have employed stable isotope amino acids, providing a mass difference of 4–6 Da where overlap of isotopomers is minimized. For example, [13C6]lysine has been used to label S. cerevisiae proteins (35). Endopeptidase Lys-C generated peptides were analyzed by high resolution, single dimension reversed phase LC and FTICR-MS using automated data-dependent multiplexed MS-MS. Cleavage with endopeptidase Lys-C ensured that peptides (unless containing a missed cleavage or originally at the protein C terminus) would contain only one lysine and the use of 13C-labeled lysine ensured reliable co-introduction of heavy and light variants into the FTICR-MS. Peptide pairs differing in mass by 6.02, 3.01, or 2 Da (singly, doubly, or triply charged ions, respectively) were selected for MS/MS, and identification of y ions in the spectrum was facilitated by the consistent mass offset, promoting efficient automated interpretation. However, sample complexity was high, and additional steps to reduce sample complexity would seem warranted for the analysis of more complex proteomes.
Whereas the above study analyzed soluble, cytosolic proteins, other studies have attempted the quantification of all proteins, including membrane proteins (36). This necessitated solubilization in SDS and 1DGE separation. [13C6]Arginine was the chosen label, resulting in labeling of approximately half of the peptides after tryptic digestion. This approach worked well for quantification up to an 8-fold difference in abundance. Some label was found in proline; although not overly problematic, this was presumably a consequence of arginine catabolism.
Relative quantification using comparison of the signal intensity of heavy and light variants of the same peptide is reliable up to a dynamic range of 6–8, and the reproducibility of such measurements has allowed confidence in the significance of changes of greater than 20%. However, major goals for proteomics are full automation and the determination of the absolute quantity of each protein within a sample. Full automation is greatly facilitated by the avoidance of gel electrophoresis and the absolute co-migration of heavy and light variants before introduction to the mass spectrometer. Absolute quantification via mass spectrometry would require the simultaneous analysis of a known quantity of individual peptides within a sample. Oda et al. (37) attempted absolute quantification of a single protein by mixing known quantities of unlabeled protein with labeled sample before analysis by 1DGE, tryptic digestion, and MALDI-ToF MS. Although this method used [15N]H4Cl labeling, it is equally applicable to proteins labeled with amino acids. The method was successful, but the labor involved makes it only viable for a handful of proteins. Finally, we note with interest a recent study in which proteins in intact rats were labeled with stable isotopes by feeding a diet containing algal cells enriched with 15N (35).
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Use of Stable Isotope Amino Acids to Assist in Protein Identification |
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-carbon deuteron before incorporation. This general approach, although suitable for small genomes, is not sufficient for unique identification of proteins in complex genomes and has since been expanded by incorporating up to six different labeled amino acids (separately) to give information on amino acid composition and allow unique identification of peptides or intact proteins (28–32) without the need for tandem mass spectrometry to derive fragmentation series. The requirement to carry out multiple labeling experiments and multiple analyses detracts somewhat from the considerable gain achieved in protein identification. An additional problem is the need for several different labeled amino acids, ideally differing from the unlabeled version by a minimum of 4 mass units and the requirement for expensive 13C-labeled versions to ensure co-elution when LC is used. An alternative method for rapid protein identification has been largely directed at proteomes of lower complexity and minimal post-translational modification (19) based on the identification of a unique peptide for each protein, which when used with a mass spectrometer of high mass accuracy can be used as a unique identifier, a biomarker for that protein. For proteomes of organisms that will be subjected many times to different stimuli, the identification of an accurate mass tag for each protein will be worthwhile, allowing these masses to be selected and quantified and changes in protein abundance under different conditions be rapidly established without the redundancy involved in quantifying several peptides per protein and repeated identification. Although Smith et al. (19) used 15N labeling and experienced the expected small discrepancies in co-elution of heavy and light versions of the same accurate mass tag (problems easily overcome by using 13C-labeled amino acid precursors), they demonstrated that such an approach was feasible. For a small proteome, such as that of Deinococcus radiodurans, 51% of the tryptic peptides at 1 ppm measured mass accuracy would give a unique accurate mass tag. For application of this method to a genome as complex as the human genome, it is argued that a peptide fractionation procedure that yields 10 fractions followed by LC-FTICR might be sufficient. However, the impact of diverse post-translational modifications could be expected to lead to complications in interpretation.
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Use of Stable Amino Acids to Measure the Rate of Protein Turnover |
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The behavior of a protein pool can most simply be expressed as the rate of synthesis, the rate of degradation, and the protein pool size. Knowledge of any two of these parameters allows calculation of the third. It is often assumed that the calculation of protein pool size is the simplest of the three parameters to acquire, and this is usually measured. Thereafter, measurement of the rate of synthesis allows calculation of the rate of degradation or vice versa.
Synthesis measurements monitor the incorporation of label into protein; degradation experiments measure loss of label from protein. Although these two approaches might seem to have a formal equivalence, they bring with them unique problems. In biosynthesis studies using stable isotope tracers the extent of incorporation of the label might need to reach 10% of the protein, and even if the precursor RIA can be manipulated to be near unity this would still require, in the absence of growth, 15% of one half-life. For a global study, the protein with the lowest turnover would dictate this. In degradation studies, prelabeled protein is "chased" with unlabeled precursors. There are two difficulties with this approach. First, producing prelabeled material would require elongated exposure to the precursor pool, which might be difficult to achieve. Second, as prelabeled proteins are degraded, the labeled amino acids that are released become available for reincorporation into newly synthesized protein. This has the effect of artifactually elongating the measured half-life of the proteins. Nevertheless, we used stable isotope incorporation into S. cerevisiae growing in glucose-limited medium at steady state and measured the turnover of a number of abundant proteins. The label was [2H10]leucine, and S. cerevisiae were grown in a chemostat for more than seven generations to ensure full labeling. A large excess of unlabeled leucine was then added and samples taken at various stages during a 50-h chase. Proteins were separated by 2DGE and tryptic peptides analyzed by MALDI-TOF MS. Protein turnover followed first order kinetics and was remarkably consistent for multiple peptides from the same original protein. Moreover, sampling at a single time point generated comparable turnover rates (23).
When radioisotopes are used, complications are ameliorated by the ability to monitor tracer levels of labeling. The most common radiolabeling method for measurement of total protein synthesis is the "flooding dose" method, in which a large bolus of precursor is delivered in such a fashion as to swamp the endogenous pools. Hence, the precursor specific radioactivity can be taken to be that of the flooding dose material. This is of course unfeasible in stable isotope methods for turnover measurement in that mass spectrometers routinely used in proteomics cannot measure low levels of incorporation.
In experiments in which it is not possible to attain fully labeled precursor pools, precise determination of rates of protein synthesis requires knowledge of the value of precursor RIA. This can be accessed by recovery of the precursor from the tissue sample, but there is some disagreement as to whether the amino acid pool or the aminoacyl tRNA is the most appropriate reporter of the RIA of the immediate precursor of protein synthesis. However, under circumstances in which the precursor RIA is less than unity, direct analysis of peptide mass isotopomers can yield the RIA of the immediate precursor of the protein irrespective of the chemical nature or specific pool location (34, 40). This is a major advantage of stable isotope labeling. We have recently demonstrated that mass isotopomer distribution analysis can be used to derive the RIA of a precursor pool when a stable isotope amino acid is administered in the diet to an intact animal (24).
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Use of Stable Isotope Labeling to Monitor Protein Modification |
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So far, most global phosphoproteome studies have not used stable isotope metabolic labeling. Instead, methods have been developed that result in the specific isolation of proteins or peptides that have been modified by phosphorylation, thereby reducing sample complexity. These include two methods that can be applied directly to protein mixtures (specific immunoprecipitation using antibodies specific for phospho-tyrosine, -threonine, or -serine and immobilized metal (Fe3+) affinity chromatography) and three methods that involve chemical modification of phosphate groups (phosphoramidate chemistry (41), ß-elimination-Michael addition (37), and phosphoprotein ICAT (42)), which then facilitate affinity selection. These methods, together with MS/MS analysis, have all been used with reasonable success to identify phosphorylated proteins and the sites of phosphorylation. For comparative phosphoproteomics, stable isotopes have been incorporated during chemical modification methods (37, 42). With all these studies, additional work is required to distinguish between an increase in the proportion of a given protein that is phosphorylated and an overall increase in the abundance of a protein with a fixed proportion carrying the modification.
A handful of studies have used metabolic labeling to monitor protein modifications and phosphorylation in particular. Oda et al. (37) observed the differences in abundance of peptides derived from two S. cerevisiae strains differing only in their ability to express G1 cyclin. A 50/50 mixture of the two strains (one labeled in 15N medium) was analyzed, and the parent proteins of tryptic peptides showing unequal abundance were identified. A study of other peptides from the same parent proteins revealed those peptides that differed as a result of post-translational modification rather than a change in the overall abundance of the protein in the two strains. The type of modification was then established during MS/MS. In another study, [2H3]serine labeling coupled with 1DGE separation was used to allow immediate focus on peptides that could serve as substrates for protein kinase A (32). The phosphorylation of a histone protein from human skin fibroblasts in response to low dose irradiation was demonstrated.
A number of studies have assessed the phosphorylation of individual proteins. This has been achieved by generating a variant of the protein such that it is readily purified from whole cells (for example, by including a His tag or an immunoprecipitable epitope in the gene). These constructs were then transiently expressed in cells grown in labeled or unlabeled medium, and the labeled cells were subjected to various stimuli. Labeled and unlabeled cells were then mixed, the protein under study recovered, and differences in modifications established by mass spectrometry (43). The study can be focused toward the modification of specific residues, for example tyrosine, by using tyrosine as the labeled amino acid and selecting peptides that differ in intensity in mass spectrometry for further study by MS/MS (44).
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Bioinformatics for Stable Isotope Labeling |
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Few tools for automated identification and quantification of isotopically differentiated peptides are generally available. Two tools, however, are worthy of note. The first, MS-Isotope, is part of the Protein Prospector package (Ref. 47; prospector.ucsf.edu) and is a web-based tool that allows the natural isotope distribution profile of any peptide to be calculated. This facilitates calculation of relative abundances of peptides when, in particular, the natural isotope profiles of the unlabeled and labeled peptides overlap. The second tool, MS-Quant (Ref. 48, msquant.sourceforge.net) is a stand alone application that is able to extract quantitative data from isotope-labeled mass spectra.
A simple approach to identification of isotopically labeled pairs of peptides is to code them in search algorithms as a pseudo-post-translational modification. Search algorithms will then identify stable isotope-labeled amino acids as mass-modified peptides and are of course tolerant to multiple instances of the same amino acid in a peptide. This can also be applied to analysis of MS/MS spectra.
On the other hand, if a peptide pair is readily identifiable by manual inspection of the mass spectrum, it is possible to include the additional information about the amino acid composition in the search term. The MASCOT (Ref. 49, www.matrixscience.co.uk) search engine in particular includes the capability to encode amino acid composition data using appropriate search terms. Thus, a search string of the form "[M+H]+ comp(Leu[n])" not only submits the peptide mass to the search algorithm but also restricts the search space further by including the number of leucine residues (n) present in the peptide.
However, a mass spectrum containing both labeled and unlabeled variants of a number of peptides is complex, particularly when the precursor RIA is less than unity. In our experience, there is no automatic way to process such complex spectra, and it is common to resort to manual interpretation and analysis. The lack of automatic processing of spectra, made more complex by the use of stable isotope labeled precursors, is a disincentive to wider adoption of this approach.
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Conclusions |
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With the emergence of systems biology, it is increasingly clear that proteomics must undergo a paradigm shift and evolve from relative quantification to absolute quantification. Stable isotope-labeled internal standards will become increasingly important in absolute quantification, although this is beyond the scope of this review. In addition, there is an increasing need to understand variation in protein expression in terms of protein turnover, which requires robust methods to measure dynamics on a proteome wide scale; the methods that are being developed are largely based on stable isotope labeling strategies. Many more developments in the use of such strategies in complete and definitive proteome comparison may be anticipated.
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FOOTNOTES |
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Published, MCP Papers in Press, April 22, 2005, DOI 10.1074/mcp.R400010-MCP200
1 The abbreviations used are: 1DGE, one-dimensional SDS-PAGE; 2DGE, two-dimensional SDS-PAGE; RIA, relative isotope abundance; D, doubling time; FTICR, Fourier transform ion cyclotron resonance. 
* This work was supported by the Biotechnology and Biological Sciences Research Council. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
To whom correspondence should be addressed. Tel.: 44-151-794-4312; Fax: 44-151-794-4243; E-mail: r.beynon{at}liv.ac.uk
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REFERENCES |
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ABSTRACT
Radioactive Versus Stable...
