Proteomics of Signal Transduction Pathways

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Proteomics

of Signal Transduction Pathways

Oliver Kleiner, Jasminka Godovac-Zimmermann

35

35.1 Introduction

All living cells have to monitor constantly their own state and physiological function. Moreover, cells have to be sensitive to their environment and its potential influence on biological processes. They have to be able to detect any internal or external changes quickly and reliably, and to initiate a pro- gram of events that is appropriate to respond to the detected change. The analysis of these initiated signaling events provides a key towards an under- standing of cellular function. In the past research into cellular signaling has usually been carried out by investigating one signaling pathway at a time and one participating molecule after the other. However, it has become increasingly clear that many signal- ing processes are extremely complex, involve very large numbers of different molecular components, involve complicated crosstalk between different sig- naling pathways and have complex spatial and tem- poral dependencies. Therefore there is an increasing need to investigate a more global level of organiza- tion in the form of signaling networks. A major re- quirement for targeting functional networks is the availability of methods for global observation of signaling processes under normal and abnormal conditions as well as in response to manipulations.

The proteomics methods developed over the past few years are increasingly able to fulfill this require- ment. It is the aim of this chapter to illustrate what the potentials of proteomics technologies are and how they are currently being used to study cellular signaling.

Since the publication of the human genome sequence in 2001, we live in a world of “ome” and

“omics”. The word PROTEOME was coined by Marc Wilkins in 1994 as the “PROTEin complement ex- pressed by a genOME or tissue” [65]. Conceptually the term PROTEOMICS now refers to the analysis of all proteins in a living system [14], including the anal- ysis of protein isoforms (alternatively spliced vari- ants, proteolysis products and post-translationally

modified proteins), their covalent and non-covalent associations, the spatial and temporal distributions of these proteins within cells and how all this is af- fected by different external and internal conditions (Fig. 35.1). Proteomics is a highly parallel technol- ogy suitable for looking at complex functional net- works, but although the idea of “total proteomics” is seductive, this is not achievable in current practice.

Consequently, several complementary variations of proteomics approaches, with strengths appropriate for extracting particular types of information, have been developed over the past few years. To put these varying approaches into context, it is useful to recall briefly some of the properties of signaling systems and the kinds of information that may be the subject of investigation.

35.2 What Makes Signaling Specific?

It has become increasingly clear that signaling path- ways cannot be understood when they are seen as independent, linear pathways. They rather should be seen as part of bigger networks that are built of different signaling modules and that contain lin- ear parts but also a lot of crosstalk. Here arises the question of how such networks can transmit a spe- cific signal to its targets when ubiquitous signaling modules such as the adenylate cyclase (AC)/protein kinase A (PKA) mechanism are used? Different re- ceptors stimulate similar collections of intracellular signaling pathways, so how can they elicit specific biological responses?

First, each receptor should have its own intrin-

sic features; second, the activity of receptors is most

likely modulated by other proteins, via either di-

rect or indirect interactions; and third, information

transfer is dependent on the availability of different

signaling molecules in terms of abundance, activ-

ity and subcellular localization. Besides the intrin-

sic features of the receptor, all other points can be

taken together as the cellular context in which the

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receptor functions. It makes sense to hypothesize that the special characteristics of a given receptor and the respective cellular context should cooperate to generate an unequivocal biological response.

This hypothesis is supported by recent experi- mental data. The tyrosine kinase Met, the receptor for hepatocyte growth factor (HGF), is able to form partnerships with other transmembrane proteins that act as tissue-restricted modulators and diversi- fiers of Met signals. By doing that they determine the specificity of the biological outcome. An additional level of specificity is achieved by tissue-specific ex- pression of diverse signaling molecules, which ac- count for the induction of distinct biological effects, in distinct cell types, by the same growth factor [5].

The cooperation of special receptor characteris- tics and the cellular context is also seen in the case of estrogen receptors (ERs). The ERs belong to the nuclear receptor superfamily, the largest group of metazoan transcription factors. The regulation of their signaling specificity is complex and involves many different levels of regulation [9, 54]. To date there are two known ERs, ER α and ERβ. The recep- tors, once bound to their physiological ligand, es- trogen (E2), are subject to conformational changes that result in complexes containing homodimers of receptors/hormones that recognize different estro- gen-responsive elements and, in combination with other transcription factors, different enhancer ele- ments, located upstream of target genes. Interac- tions between ERs and accessory proteins ultimate- ly lead to the modification of transcription of these genes [9].

The more obvious level of gaining sensitivity after E2 activation lies in the features of the recep- tors themselves. The ERs can bind to different re-

sponsive/enhancer DNA elements and can therefore regulate the activity of different genes. A further branching out is the possibility that ER α and ERβ can signal in opposite directions at these sites [28, 43]. There is also the possibility of formation of het- erodimers between ER α and ERβ, which ultimately should lead to some form of crosstalk between the elicited signals [16]. There are also reports about different splicing variants of the two types of recep- tors influencing their signaling pathways [54]. One of the major advances in the understanding of ER signaling was the finding that cellular sensitivity for either ER α or ERβ is at least in part regulated by their cellular expression patterns. An additional level of complexity is introduced by the functional modulation of ERs by co-activator and co-repressor proteins. These proteins in turn regulate selectiv- ity of the receptors by their own cellular expression pattern [9, 54].

The concept of achieving signaling specificity by restricting a signaling pathway to a highly localized area in the cell is fulfilled in the case of A

_2B

adeno- sine receptors, which couple to the cystic fibrosis transmembrane conductance regulator (CFTR) by means of Gs, AC and PKA. CFTR expression is restricted to the apical part of polarized epithelial cells; it is not found on the basolateral side. Stimu- lated A

_2B

receptors activate AC present in the api- cal membrane by means of Gs, sufficient cAMP is generated locally to activate PKA (which is linked to the membrane by a specific anchoring protein) in a diffusionally restricted apical microdomain, but not in other cellular compartments [24].

To summarize, during an investigation of a sign- aling system, we may be interested in who the play- ers are (what proteins), what form they may take

Fig. 35.1. General cellular processes that contribute to the phenotypes of proteins

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(modifications by processes such as phosphoryla- tion), how they talk to each other (protein–protein interactions), where they are or where they may move to (spatial dependence) and when or in what sequence their participation occurs (temporal de- velopment of signaling). As we will see in the fol- lowing, depending on which of these aspects is the primary goal of a particular experiment, different variations of proteomics experiments will be most appropriate.

35.3 Identifying the Players – Mass Spectrometry

At present the identification of proteins in proteom- ics is almost exclusively achieved by mass spectrom- etry (MS) [2]. There are three fundamental reasons for this. First, the MS methods can identify any pro- tein for which a genome sequence is known without the need for special reagents such as antibodies.

Second, MS is highly sensitive – proteins in femto- mole amounts can be identified on a routine basis and extension to attomole amounts is likely in the future. Third, MS can in principle exactly charac- terize the covalent structure of a protein, i.e., splice variants or post-translational modifications, with- out prior knowledge of the types of modifications or their locations. The most common MS strategies analyze peptides rather than full-length proteins.

To generate suitable peptides, the respective pro- teins are digested with sequence-specific proteases like trypsin.

Mass spectrometric measurements are carried out on ionized analytes in the gas phase. Matrix- assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI) are the two techniques most commonly used to bring the analytes as posi- tively charged ions into the gas phase [11, 27]. In the MALDI technique, samples are co-crystallized with an organic matrix and subsequently volatized and ionized by laser pulses. ESI ionizes the samples di- rectly from solution and can therefore be easily cou- pled to liquid separation methods. The linkage of liquid-chromatography to ESI-MS systems (LC-MS) allows the analysis of complex samples, whereas MALDI is usually applied to analyze relatively sim- ple mixtures. Besides the ion source a mass spec- trometer includes a mass analyzer and a detector.

The mass analyzer separates the ions by their mass- to-charge (m/z) ratios and the detector registers the numbers of ions at each individual m/z value.

In proteomics research four different kinds of mass analyzers are currently being used: time-of-flight (TOF), ion trap, quadrupole and Fourier transform

ion cyclotron resonance (FTICR) analyzers. All four types differ considerably in sensitivity, resolu- tion, mass accuracy and the possibility to fragment peptide ions, which results in mass spectra with an especially high content of information (MS/MS spectra) [2]. The combination of ion source, mass analyzer and detector is usually determined by the application.

MALDI is usually coupled to TOF analyzers that measure the m/z ratio of intact peptides. MALDI- TOF is relatively simple and robust to operate, has very good mass accuracy, high resolution and sensi- tivity and is therefore widely used in proteomics to identify proteins by a process called ”peptide mass fingerprinting” [7]. In this process the proteins of in- terest are digested with a sequence-specific enzyme like trypsin and delivered to the mass spectrometer.

The measured peptide masses are then compared against a database that comprises peptide masses of proteins from a virtual digest of all proteins from a given organism with the same sequence-specific protease. This form of protein identification needs an essentially purified target protein and the tech- nique is therefore very often used in conjunction with two-dimensional gel electrophoresis (2D- PAGE).

ESI is most often coupled to ion traps and triple quadrupole instruments. With this configuration it is possible not only to determine the mass of a given peptide, but also to draw conclusions as to its se- quence. Ions with specific m/z ratios can be selected (”trapped”) in the mass spectrometer for fragmen- tation. Energy is supplied to the selected peptide ion through collisions with an inert gas or a surface in a process called collision-induced fragmentation (CID). This energy causes the peptide ion to frag- ment at different points, commonly at the peptide bond. The recorded product ions represent the tan- dem mass spectrum (MS/MS spectrum) [1], which contains information on the amino acid sequence.

The derived MS/MS spectra (or CID spectra) are then compared against comprehensive protein se- quence databases using one out of several different algorithms [10, 37, 45].

FTICR analyzers are often used with both ion sources, MALDI and ESI. The distinctiveness of FT- ICR-MS is its unsurpassed mass resolution, which makes it a versatile tool for the studying of protein isoforms [59].

These common MS-based methods to identify

proteins are heavily dependent on sequence data-

bases and are therefore most appropriate for organ-

isms for which comprehensive sequence databases

exist.

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35.4 Strategic Decisions

About Fractionation Methods

Cells contain many thousands of different protein species. To analyze all of these different protein spe- cies by MS, prefractionation technologies have to be applied to reduce complexity. In practice, most of the existing protein fractionation methods, e.g., preparation of subcellular organelles, centrifuga- tion, ion exchange-, size exclusion-, affinity- and reversed-phase-chromatography, as well as gel elec- trophoresis, are used in proteomics. The goal is to resolve as many proteins as possible in the fewest number of steps. The less the experimentor has to interfere, the more the information content of the sample is preserved.

The choice of the fractionation methods is large- ly determined by the desired information about the proteins (Fig. 35.1). Should total cellular proteins be extracted and analyzed or should the analysis be performed on a subfraction of proteins correspond- ing to, for example, nuclear proteins or cytoplasmic

membrane proteins? Second, at the stage of display or resolution of individual proteins, should this be done with intact proteins or with peptides follow- ing fragmentation of the proteins by methods such as tryptic hydrolysis? This decision is particularly critical since once the proteins have been convert- ed to peptides the natural functional unit has been destroyed and its complete structure may be only partially identified or reconstructable from analy- sis of the constituent peptides. In practical terms, this decision often corresponds to whether it is sufficient to identify the protein at the level of the gene from which it is produced or whether multiple forms of the same protein differing in splice vari- ation and/or post-translational modifications need to be analyzed. Finally, should the MS identifica- tion and characterization of the proteins be done by MS analysis of intact proteins or of peptides? Direct analysis of complete proteins in a mass spectrom- eter [4, 52, 59] is primarily of interest for unraveling complex patterns of splice variations or post-trans- lational modifications and will not be considered further here.

Fig. 35.2. Two-dimensional gel of affinity-purified phosphoproteins from HeLa cells. Proteins were subjected to IEF in the pH range 4–7 and then resolved on an 11% SDS Lammli gel.

The silver-stained gel displays ~1,100 protein species

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35.4.1 Two-Dimensional Gel Electrophoresis and MS

Two-dimensional gel electrophoresis gels are the workhorse for protein separations and remain the gold standard against which all other current mul- tidimensional separation methods for proteins and peptides are compared (see below). Several hun- dreds to a few thousand proteins can be resolved on a single 2D gel. In the first dimension proteins are separated according to their charge by isoelectric focusing (IEF); in the second dimension they are separated by their molecular weight using SDS gel electrophoresis. Proteins are then visualized with hydrophobic dyes such as Coomassie blue, silver ions, fluorophores or other stains (Fig. 35.2) [44].

Although the resolving power of 2D gels is high, the resolution is still insufficient compared to the enor- mous diversity of cellular proteins and it is therefore not uncommon to find co-migrating proteins in the same spot [17]. Some of the resolution limitations can be overcome by using multiple, narrow pH- range and/or very long immobilized pH-range gra- dient gels for first-dimension separations [23, 46].

The biggest strengths of 2D gels are that the nat- ural functional unit of the proteins is retained and that different isoforms of the same protein can be separated and analyzed. The latter possibility makes 2D-PAGE especially useful in the investigation of post-translational modifications and in deciphering complex signaling events. Usually, proteins separat- ed on 2D gels are recovered from the gel matrix, di- gested with a sequence-specific enzyme like trypsin and delivered as peptides to the mass spectrometer (Fig. 35.3). Because of its easy handling and the po- tential of high-throughput analysis, MALDI-TOF is the most popular MS method to identify proteins from 2D gels [7]. An example for large-scale protein separation and identification, using the combina- tion of 2D-PAGE and MALDI-TOF, is the analysis

of the Helicobacter pylori proteome [26]. More than 1,800 protein species were separated, of which 152 were subsequently identified. In other systems, up to 10,000 cellular proteins have been visualized using multiple and/or large-format 2D gels [29, 46, 67].

One-dimensional gel electrophoresis (1D-PAGE) can also be used for large-scale protein identifica- tion studies. Since much of the resolving power of the 2D-PAGE approach is lacking, this is most of- ten used when samples of lower complexity are to be analyzed. Often multiple proteins are contained in single excised bands and cannot be identified by peptide mass fingerprinting alone. Therefore tan- dem MS fragmentation (MS/MS) has to be used to identify these proteins. This approach is often used with partially purified samples, e.g., in the analysis of signaling complexes [22] or the protein content of organelle membranes [3].

35.4.2 Gel Electrophoresis-Free Approaches and MS

Although the resolving power is undisputable, rou- tine applications of 2D gels suffer from the described difficulties in covering proteins with extreme pI val- ues and molecular weights as well as hydrophobic proteins. Unsurprisingly, several systems to frac- tionate extracts of whole proteins that make no use

Fig. 35.3. Strategies for proteome analysis. A Proteins are sepa- rated and displayed on 2D gels. Individual proteins are recovered from the gels, digested with trypsin and analyzed by mass spectrometry. B Mixtures of total proteins are digested with trypsin, separated by liquid chromatography and analyzed by mass spectrometry

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of 2D-PAGE have been developed as well (for review see [25, 33]). Despite the advantage of having to deal with far fewer species compared to peptide analy- ses (see below), these methods are currently not in widespread use for global proteomics analyses, mostly due to the handling and instability problems of proteins. This is especially the case for hydropho- bic and membrane proteins.

These difficulties have led to the introduction of several different approaches for using peptides as surrogates to analyze their parent proteins. Typical- ly, total protein mixtures are hydrolyzed by trypsin and the resultant peptides separated before they are delivered to the mass spectrometer (Fig. 35.3). The main goal of these separation methods is the decon- volution of the peptide mixture, so that the MS/MS spectra are not overcrowded. As has been discussed in detail elsewhere [56], the peptide methods inher- ently have less information than methods based on separation of proteins and are therefore most appli- cable when proteins need to be identified at the level of the gene from which they are produced.

Multidimensional Protein Identification Technology

Multidimensional protein identification technology (MudPIT) is an approach in which the complexity problem is addressed at the peptide level. The first step in a MudPIT experiment is the enzymatic di- gestion of the total protein mixture to be analyzed to create a more complex peptide mixture. The peptides are then separated on a biphasic liquid chromatography column using a strong cation ex- change support as the initial phase and a reversed- phase material as the second phase and are directly delivered on-line to a tandem mass spectrometer.

With this procedure a high-resolution separation of the peptides is achieved, which reduces the total number of peptides to be analyzed concurrently to a more manageable number for the mass spectrom- eter. It is noteworthy that the complexity deconvolu- tion mainly takes place in the chromatography step, but the ability of the mass spectrometer to handle several peptides at a time also contributes to the multiple dimensions [32].

To validate its potential, the MudPIT approach was used to identify proteins from a yeast whole cell lysate [64]. In total, 1,484 proteins were identified and, more importantly, the data set included pro- teins with extreme pI values, very small and large proteins, low abundance proteins as well as mem- brane proteins. So far the biggest drawback of this technology is the lack of a commercially available system.

Accurate Mass Tags

for High-Throughput Proteomics

Another strategy for dealing with complex peptide mixtures, which was introduced recently, combines high-resolution capillary liquid chromatography separation with high-resolution accurate FTICR mass measurements [55]. In theory an enzymatic digest of all proteins from an organism will con- tain a subset of peptides that have unique molecular masses. If one calculates the mass of such a unique peptide and is able to measure it accurately enough in an experiment, the identity of the respective protein immediately becomes clear with high con- fidence, even without obtaining any additional se- quence information. Peptides are considered to be accurate mass tags (AMTs) when they are unique within the annotated genomic database of the inves- tigated organism, when their sequence is confirmed by MS/MS analysis and when their observed mass, as measured by FTICR, agrees with the theoretically calculated mass within 1 ppm mass measurement accuracy [55]. In a recent article the concept of high- throughput protein identification with AMTs was applied to the proteome of Deinococcus radiodurans [34]. After the validation of the respective AMTs by LC-MS/MS and subsequent LC-FTICR measure- ments, the combined resolving power of capillary liquid chromatography and FTICR was used togeth- er with the very high mass accuracy of the FTICR analyzer to detect AMTs in a global protein digest of the bacterium. This approach led to the high con- fidence identification of proteins corresponding to more than 61% of the predicted genes, the most comprehensive proteome coverage to date.

Although great, the resolving power of the cap- illary LC-FTICR system is not unlimited and this prevents the application of these techniques to glo- bal analyses of more complex organisms at present.

Another reason why the AMT concept is not readily applicable to higher organisms is the occurrence of unpredictable post-translational modifications of proteins, which makes it difficult to find enough peptides that could serve as reliable AMTs to cover the proteome [55].

Other Multidimensional Separations

Besides MudPIT, there are many other procedures in

use capable of separating peptides in more dimen-

sions before MS analysis. These procedures rely on

the combination of different separation techniques

coupled to tandem MS and are usually accomplished

off-line. Many usual separation techniques are in

use: capillary electrophoresis, cation exchange-, af-

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finity-, and reversed-phase- liquid chromatography [33].

A recently developed technique introduces af- finity tags into peptides, which allow the subsequent affinity enrichment of the modified peptides and therefore reduce sample complexity. Yeast proteins were labeled at cysteine residues with a biotin rea- gent and digested with trypsin. The resulting pep- tides were fractionated on a cation exchange resin and each fraction was then loaded onto an avidin column to isolate biotin-labeled peptides. Finally, LC-MS/MS was performed on each fraction collect- ed from the affinity step [19, 20]. The sequence of peptide separations was designed to enable the de- tection of low abundance proteins. This technique is also known as the isotope-coded affinity tag (ICAT) approach and is mainly applied in quantitative MS experiments (see below).

35.5 Differential Display Proteomics and Quantitation

It has been estimated that in typical human cells pro- teins differ in abundance over about 10

²

–10

⁸

copies per cell, covering six orders of magnitude. In some samples such as serum, the dynamic range of pro- tein concentrations extends to approximately nine orders of magnitude [50]. This represents a serious challenge for quantitative analysis by proteomics, a challenge that has similar magnitude for transcrip- tomics based on analysis of mRNA. For both 2D gel

and LC methods, one constraint on the detection of less abundant proteins is the total amount of protein or peptide that can be separated. Typical loads of 50 µg of total protein can be applied to analytical 2D gels without undue loss of resolution. The LC meth- ods are more easily scaled up and total enzymati- cally digested protein loads of up to low mg levels have been used to improve detection of low abun- dance proteins when sufficient material is available [20]. The dynamic range for conventional 2D elec- trophoresis detection methods is 10

⁴

at best, which means that without prefractionation or enrichment strategies, analysis of the lowest abundance proteins will remain elusive for most complex cells or tissues [50]. Similar limitations apply to the dynamic range for detection of peptides in mass spectrometers, where an additional complication is that the vola- tilization of the peptides can vary strongly. For ex- ample, it has been estimated that the dynamic range currently achievable in an MS experiment with a capillary LC-FTICR setup is 10

⁴

–10

⁵

[55]. The conse- quence is that both methods, 2D-PAGE and MS, may have difficulties with low abundance proteins and neither is suitable for measuring absolute amounts of proteins.

Fortunately, many proteomic applications to target drug discovery or to track signaling events are concerned with relative abundances of proteins.

Proteins are isolated from cells or tissues that are in two different states, e.g., from diseased and normal cells, and the relative abundances of the respective proteins are compared. In this type of analysis it is necessary to determine the relative amount of pro- tein and/or the relative degree of post-translational

Table 35.1. Characteristics of 2D-PAGE detection methods (data from [35, 39, 44, 61] and www.biotraces.com)

Detection method Detection

limits

Linear dynamic range

Differential display

Quantitation

Colloidal CBB 30–100 ng 1 log 2 gels Relative

Silver stain 1–5 ng 1 log 2 gels Relative

Sypro Ruby 4–8 ng 3 logs 2 gels Relative

Cye dyes 2–10 ng 4 logs 1 gel Relative

Radioactive labeling/

phosphorimager

Varies 4–5 logs 2 gels

(1 gel also possible)

Absolute and relative

MPD (1²⁵I, ¹³¹I) 10^–3–10^–4 ng 6–7 logs 1 gel Absolute and

relative

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modification associated with the proteins of interest.

The current methods for the quantitation of proteins in proteomics are in principal distinguished by the question of whether or not MS is involved.

35.5.1 2D-PAGE-Based Quantitation Techniques

Classical Staining Methods

Two-dimensional gel electrophoresis is still very often the method of choice to fractionate complex protein mixtures. It is especially useful in differen- tial display proteomics when two or more different proteomes are to be compared. It allows not only the direct comparison of different protein spot patterns, but also relative quantitation. Most often, proteins in polyacrylamide gels are detected by organic dye- and silver stain-based methods (Table 35.1). These methods are rapid, easy to perform without any spe- cial equipment, relatively cheap and allow quantita- tion, as the intensity of a stained protein provides a measure of how much protein is present in the analyzed spot. The inherent disadvantages of these stains are their low detection sensitivity (the most sensitive silver stain-based method has a detection limit of 1 ng, i.e., 10 femtomoles for a protein of molecular weight 100,000), variations in gel-to-gel staining intensity and a poor linear dynamic range of about one order of magnitude [44]. Fluorescence- based staining methods overcome at least some of these limitations. The most popular among them is the SYPRO Ruby stain, which is about as sensitive as silver staining and has a linear dynamic range extending over three orders of magnitude [35]. The disadvantages are the high costs of these stains and the need for more sophisticated equipment for quantitation of proteins (a CCD-camera-equipped image station).

Radioactive labeling of proteins is an alternative to protein stains. Among others,

¹⁴

C,

³

H and

¹²⁵

I have been used successfully to detect and quantify total proteins in 2D-PAGE applications [39, 62]. If only a subset of proteins is to be analyzed,

³²

P and

³⁵

S are popular choices for metabolic labeling of phospho- proteins and newly synthesized proteins [36, 47, 66], respectively. Modern storage phosphorimagers deliver high-resolution imaging and accurate quan- titation for a variety of radioisotopes. They also provide high sensitivity and a linear dynamic range of almost five orders of magnitude. Although sensi- tive detection is readily achieved and quantitation over a wide linear range is possible, radiolabeling in 2D-PAGE is not nearly as common as gel staining,

simply due to the hazardous nature of the radioiso- topes.

To detect differences between two samples, con- ventional 2D-PAGE relies on the comparison of im- ages from at least two gels. There are several com- mercially available software packages that allow a semiautomatic comparison of digital gel images to find differences in the observed spot patterns [51, 53]. The software not only provides information about whether or not one particular protein spot is present in all gels that are compared, it also calcu- lates quantitative differences.

The main difficulties with this kind of differ- ential display are gel-to-gel variations. Although 2D gels have become very reproducible with the development of immobilized pH gradients for the isoelectric focusing step, differences in gels are still encountered on a regular basis due to manual han- dling in general, minor sample preparation differ- ences, different loading and detection of proteins.

Especially with the popular silver stain, gel-to-gel reproducibility is problematic and variations of 20%

in spot intensity have been documented [49]. Often, to obtain statistically significant differences, several replicate gels must be run of each sample to gener- ate electronically averaged gels, which can then be compared. Therefore, the whole procedure is time- consuming and throughput is limited. However, it should also be remembered that many gels can be run concurrently and that special staining methods, e.g., of phosphoproteins or glycoproteins, are easily handled with the 2D gel methods [44].

Two-Dimensional Difference Gel Electrophoresis

A new strategy for 2D differential display was de-

veloped recently and named two-dimensional dif-

ference gel electrophoresis (2D-DIGE) [61]. In this

procedure two spectrally resolvable fluorescent dyes

matched for mass and charge are covalently attached

to proteins from two separate samples. The two

samples are mixed and electrophoresed in the same

2D gel. The samples are then imaged separately but

because they have originated from the same gel, the

images are directly superimposable. An additional

level of control can be achieved by introducing an

internal standard, which is created by pooling an al-

iquot of the two samples to be analyzed and labeling

it with a third fluorescent dye. This pooled fraction

is also run on the same gel, which means that eve-

ry protein from both samples is represented in the

internal standard, which is present on all gels. For

pairwise comparison of samples, this multiplexing

capability reduces the number of gels to be run, cir-

cumvents gel-to-gel variations completely, decreases

the time for image analysis and increases the confi-

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dence with which protein changes between samples can be detected and relatively quantified. Addition- al advantages are the sensitivity of the fluorescent detection (equal to silver stain) and the broad linear dynamic range (four to five orders of magnitude).

The main disadvantages of the 2D-DIGE system are the need for additional chemical labeling steps, the sophisticated equipment required for the excitation and subsequent emission detection of different dyes and the very pricey software analysis package.

2D-PAGE Coupled to Multi-photon Detection Multi-photon-detection (MPD) is a technology for the measurement of radioisotopes that decay by the electron-capture mechanism and hence emit mul- tiple photons/particles essentially simultaneously.

Background radioactivity very rarely provides coincident emissions of defined energies and can therefore be rejected from the analysis. Coincidence detection of multiple emissions by MPD thus per- mits exquisitely sensitive detection for radioactivity levels well below background radiation. Since single decay events are detected, in principle MPD imagers can show linear signals over eight orders of magni- tude down to 10

^–20

moles, or, for an MPD counter, nine orders of magnitude down to 10

^–21

moles (600 molecules) (see www.biotraces.com).

MPD is able to discriminate between the decay of different isotopes by virtue of the different energies of the emissions, thereby permitting ”multicolor”

analysis. Iodine-125 (

¹²⁵

I) and iodine-131 (

¹³¹

I) are radioisotopes that are suitable for the MPD technol- ogy and for which chemical procedures have been established to label proteins covalently [12]. The coupling of MPD to 2D-PAGE is in principal the same as for the 2D-DIGE technique. Proteins from two different samples are labeled with

¹²⁵

I or

¹³¹

I, mixed and run in the same 2D gel. The MPD imager can distinguish between the energies of the differ- ent radioisotopes and gives two separate images for the protein samples to be compared, which originate from the same gel. The MPD technology eliminates inter-gel variabilities in differential display analyses, provides ultra-high sensitivity in protein detection, has an extremely high linear dynamic range and, in principle, can give absolute rather than differential quantitation of proteins. It has been reported that MPD technology can detect 10 attomoles of proteins routinely and quantitatively on 2D gels with a linear dynamic range over six orders of magnitude of pro- tein concentrations (see www.biotraces.com). With appropriate calibrations, the measured amounts of

125

I,

¹³¹

I and the measured difference for each spot on the 2D gel are quantitative rather than representing differential amounts. The attributes of ultra-high

sensitivity and a linear dynamic range of six orders of magnitude seem promising for future analysis of low abundance proteins using a combination of 2D- PAGE and multicolor MPD.

35.5.2 Mass Spectrometry-Based Quantitation Techniques

In all MS methods the amount of analyte in the sam- ple does not correlate directly with the ion-current intensities of mass spectrometric signals. This lack of correlation is inherent to the method and inde- pendent of the ionization technique used or the in- strument employed, which means that additional techniques have to be implemented to enable dif- ferential quantitation of proteins with MS. In pro- teomics all of these additional methods involve the labeling of peptides with stable isotopes by either biosynthetic or chemical methods and allow differ- ential amounts of the same peptide to be measured over a dynamic range of about 10

⁴

[31, 38]. The main advantages of these methods are to allow simulta- neous identification of the peptide and its relative quantitation and to allow a high degree of automa- tion of the proteomic analysis.

Metabolic Isotopic Labeling

Metabolic labeling of proteins exploits the incor- poration of isotopic labels during the processes of cellular metabolism and protein synthesis. A pop- ular method for protein quantitation by MS is the labeling of proteins by incorporation of isotopically modified amino acids. This technique was recently named SILAC, for stable isotope labeling by amino acids in cell culture [41]. One population of cells is grown in medium containing the normal form of an essential amino acid; another population of cells in grown in medium supplemented with a stable iso- tope-labeled analog. After extraction the two pro- tein fractions are pooled. Proteins/peptides are then analyzed in any of the ways in which they are ana- lyzed by non-quantitative proteomics (Fig. 35.4A).

The quantitation takes place at the level of the pep-

tide mass spectrum or the peptide fragment mass

spectrum as the peptides will preserve the exact ra-

tio of the labeled to unlabeled protein. Among oth-

ers a combination of normal arginine (

¹²

C

₆

-Arg) and

fully substituted

¹³

C-labeled arginine (

¹³

C

₆

-Arg) has

been used to label proteins metabolically [42]. Iden-

tical peptides with one arginine residue from cells

grown in normal medium and from cells grown in

medium supplemented with

¹³

C

₆

-Arg show a mass

difference of 6 Da and can therefore easily be spot-

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Fig. 35.4a–d. Protein quantitation by mass spectrometry. a The SILAC strategy. b MALDI-TOF spectrum of the ¹²C6-Arg and the

13C6-Arg form of the peptide ITPSYVAFTPEGER. c The ICAT strat- egy. d The ICAT reagents

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ted. Quantitation is possible because both peptides have equal ionization efficiencies. The ratio of the peak heights or peak areas directly reflects the dif- ference in amount of the protein in the two different cell pools (Fig. 35.4B). An additional advantage of the SILAC method is the availability of many pep- tide pairs per protein to choose from for quantita- tion to ensure that the extent of change is the same.

Another simple and universal method for intro- ducing an isotopic label is by growing one experi- mental cell population in an isotopically depleted medium enriched in

¹⁵

N, and the other in standard

14

N-rich medium. The resulting two proteins sam- ples are pooled and analyzed essentially as described above. This approach has also been proven to be an accurate quantitation methodology [40, 63].

Until very recently the use of metabolic labeling was limited to samples derived from cell culture.

The applicability of the method has been extended by quantitative

¹⁵

N metabolic labeling of the mul- ticellular organisms Caenorhabditis elegans and

Drosophila melanogaster [30]. After labeling the or-

ganisms by feeding them on

¹⁵

N-labeled E. coli and yeast, respectively, the relative abundance of indi- vidual proteins was determined by MS.

Chemical Labeling

When metabolic labeling of proteins is not pos- sible, chemical-labeling techniques can be used as an alternative quantitative tool. The most widely used chemical labeling technique for quantitative proteomics is the isotope-coded affinity tag (ICAT) method [19], and modified versions of it [15, 48, 68].

In the original approach an isotopically labeled bi- otin affinity reagent was attached to cysteinyl resi- dues in all proteins of a sample representing one population of cells and the same affinity reagent without being isotopically labeled was attached to all proteins of cells representing another popula- tion. The two protein samples are then combined and enzymatically cleaved into peptide fragments.

The tagged peptides are subsequently isolated by af- finity chromatography on avidin columns and ana- lyzed by microcapillary LC-MS/MS. The MS step al- lows the identification and quantitation of peptides (Fig. 35.4C, D). Again, quantitation is achieved by measuring the relative signal intensities for pairs of peptide ions that are tagged with the isotopically light or heavy forms of the affinity reagent and that therefore exhibit a mass difference encoded by the affinity reagents. The beauty of the ICAT analysis lies in its independence of the protein source and that the complexity of the peptide mixture is greatly reduced while protein quantitation and identifica- tion are still achieved.

Several other techniques that use chemical labe- ling of proteins/peptides with different isotopes and reagents have been developed and are in widespread use. For a comprehensive review, the interested reader is referred to [31].

35.6 Examples of Proteomics in Signaling Systems

By now there are many hundreds of applications of proteomics to signaling and other aspects of cellu- lar biology. It is not possible to review all of these in detail here and the reader is referred to a compre- hensive overview of recent applications to signal- ing systems [56]. In this section we briefly describe three recent experiments that illustrate the differ- ent proteomics approaches outlined above, with the expectation that this might be an aid to thinking about the most appropriate approach for the prob- lem at hand for those readers contemplating using proteomics.

35.6.1 Phosphorylation Signaling Cascades Excited by Stimulation

of Membrane Receptors

One of the characteristics of signaling systems is

large differences in the time scales for different re-

sponses. In general, rapid processes (seconds to sev-

eral minutes) are dominated by changes in the cov-

alent forms of proteins through post-translational

processes such as phosphorylation. In this case,

proteomics methods appropriate for observing dif-

ferent variants of the same protein are needed and

2D gels remain by far the most effective method for

detecting which proteins show changes as the con-

sequence of a signaling process. For example, in a

recent study the rapid phosphorylation and dephos-

phorylation of a variety of proteins downstream of

endothelin receptors A (ETA) and B (ETB) follow-

ing stimulation of human lung fibroblasts with en-

dothelin was investigated with this methodology

[58]. Proteins phosphorylated on tyrosine, serine

and threonine were individually isolated from stim-

ulated and unstimulated cells, separated on 2D gels

and subjected to a differential display analysis. The

identification of differentially displayed proteins by

MS revealed changes in phosphorylation of proteins

involved in the cell cycle, cytoskeleton, membrane

channels, transcription, angiogenesis, and metabo-

lism. An interesting feature of this study was an in-

dication that some of the downstream phosphatases

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were partitioned between different functional proc- esses and that only a small fraction of the cellular PP2A or cdc25 participated in the mitogenic effects of endothelin signaling on the cell cycle [58].

It has been mentioned before that different re- ceptors should have different intrinsic properties and should be regulated differently. In a companion paper, these authors also studied ETA and ETB iso- lated from human fibroblast cells before and after stimulation with endothelin. The post-translational modifications of the receptors were determined by MS. The MS analysis revealed that the ETA recep- tor was modified at 20 sites (15 phosphorylation, 5 palmitoylation) and ETB at 17 sites (13 phosphoryla- tion, 4 palmitoylation). In both the stimulated and unstimulated states, multiple isoforms differing in number and location of post-translational modi- fications were present and were shown to change rapidly following stimulation. The multiple forms of these receptors could represent a mechanism for incremental modulation of receptor activity and/or for the excitation of parallel signaling pathways at spatially and functionally distinct endothelin re- ceptor isoforms [57].

35.6.2 Systematic Identification of Protein Complexes

Protein–protein interaction networks are a major characteristic of cellular function and the elucida- tion of these networks is therefore an important step towards the understanding of signaling. Proteomics methods have often been used to determine the con- stituents of protein complexes and recently this has been extended to systematic analyses of protein–

protein interactions in the yeast proteome [13, 22].

Multiprotein complexes were systematically puri- fied by affinity selection of genetically tagged ”bait”

proteins. Both groups used 1D gel electrophoresis to resolve proteins in complexes, while either MAL- DI-TOF peptide mass fingerprinting or LC-MS/MS peptide sequencing were used to identify the protein constituents (at the level of the gene from which they are produced). Both approaches detected approxi- mately 1,500 different interacting proteins repre- senting 25% of the yeast proteome. This included many of the kinases and phosphatases vital to cel- lular signaling. In contrast to approaches such as the yeast two-hybrid methodology, this technology is capable of directly detecting many components of large protein complexes. Although further work will be needed to unravel the (transient) inclusion of the same protein in different complexes, the resulting protein–protein interaction networks represent a

functional description of a eukaryotic proteome at a higher level of organization.

35.6.3 Monitoring Subcellular Spatial Locations of Proteins

Over recent years it has become apparent that chang- es in the subcellular location of proteins are an in- tegral part of many signaling processes. In contrast to methods such as confocal fluorescence micro- scopy, the kinds of proteomics methods described here are not capable of following the intracellular location of tagged proteins in real time. However, the proteomics methods can be used to monitor in parallel thousands of proteins located in subcellular organelles for any dynamic changes in their content within the organelle. The reader is referred to recent reviews about the measurement of the protein con- tent of different subcellular organelles by proteom- ics methods [8, 60].

In a dynamic proteomics approach, changes in the content of membrane and membrane-attached microsomal proteins were investigated as a function of differentiation induced by exposure of the human cell line HL-60 to 12-phorbol-13-myristate acetate (PMA) [21]. Because this study dealt with mem- brane proteins, tryptic digestion of total proteins was an effective means to obtain reporter peptides from poorly soluble proteins. By labeling with ICAT reagents and using multidimensional LC-MS/MS for identification, relative abundances of proteins be- fore and after induction of differentiation could be measured. Altogether 491 membrane proteins could be monitored. The measured changes included dif- ferent behavior for different isoforms of the same protein family, e.g., among protein kinases C- α, -β1 and - θ [21]. Subcellular compartmentalization of proteins is very important to cellular function, and dynamic proteomics studies of this type are likely to be a highly productive means for obtaining infor- mation on cellular function.

35.7 Conclusion

We hope that this brief review will be helpful in em- phasising the powerful capabilities that proteomics approaches have for analysis of signaling systems.

All of the various approaches are in a phase of very

rapid technical development and further increases

in sensitivity, quantitation and throughput can be

expected. For prospective users of proteomics in

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signaling systems, we would emphasize that strate- gic decisions about whether fractionation should be undertaken for proteins or for peptides are crucially dependent on the goals of the experiment. We refer the reader to a recent comprehensive discussion of when "top-down" analysis of proteins is preferable [56].

Selected Reading

Stannard C, Brown LR, Godovac-Zimmermann J. New paradigms in cellular function and the need for top-down proteomics analyses. Curr Proteom 2004;1:13–25. (The reader is introduced to new paradigms in cellular function and the im- plications of these new paradigms for proteomics are discussed.)

Godovac-Zimmermann J, Brown LR. Proteomics approaches to elucidation of signal transduction pathways. Curr Opin Mol Ther 2003;5:241–249. (This article gives an extensive overview of the latest developments and applications for global proteomics methods. A comparison between bottom-up and top-down proteomics approaches is given.)

Aebersold R, Mann M. Mass spectrometry-based proteomics. Nature 2003;422:198–207. (The latest developments in biological mass spectrometry and their applications in proteomics are reviewed.)

Zhu H, Bilgin M, Snyder M. Proteomics. Annu Rev Biochem 2003;72:783–812. (The article discusses high-throughput technologies for proteome analysis and their applications.

Approaches for the integrated analysis of voluminous sets of data generated by global proteome analysis are also rea- soned.)

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