Translational Proteomics: Developing a Predictive Capacity – A Review

Placenta (2006), Vol. 27, Supplement A, Trophoblast Research, Vol. 20 doi:10.1016/j.placenta.2005.11.003

Translational Proteomics: Developing a Predictive Capacity – A Review G. E. Ricea,*, H. M. Georgioub, N. Ahmedc, G. Shid and G. Kruppad a

Department of Translational Proteomics, Baker Heart Research Institute, 75 Commercial Road, Melbourne 3004, Victoria, Australia; b Mercy Perinatal Research Centre, Department of Obstetrics and Gynaecology, University of Melbourne, Mercy Hospital for Women, 163 Studley Road, Heidelberg 3084, Victoria, Australia; c Gynaecological Cancer Research Centre, The Royal Women’s Hospital, 132 Grattan Street, Carlton 3053, Victoria, Australia; d Bruker Daltonics, 2859 Bayview Drive, Fremont, CA 94538, USA Paper accepted 7 November 2005

Over the past decade, proteomics has undergone a rapid development and radiation, diversifying across the biochemical landscape. While no single technique yet delivers complete proteomic coverage, application-specific adaptations afford significant opportunity for discovery and the development of predictive capacity (e.g. surrogate biomarker and clinical diagnostics). Targeted proteomic approaches, protein profiling strategies using affinity capture mass spectrometry and solution array represent realistic opportunities to deliver predictive capacity. The aim of this review is to provide an overview of proteomic technologies and how the outcomes delivered by such platforms may be translated into applications of predictive utility in clinical and basic science. In particular, recent applications in protein/peptide profiling (solid-phase affinity capture mass spectrometry and the targeted approach of antibody arrays) and the opportunities they afford researchers within the discipline of reproductive biology to develop new diagnostic and prognostic tests and surrogate biomarkers to improve the delivery of women’s health care are considered. Placenta (2006), Vol. 27, Supplement A, Trophoblast Research, Vol. 20 Ó 2005 Published by IFPA and Elsevier Ltd. Keywords: Translational proteomics; ClinProt; SELDI; Solution array; Two dimensional gel electrophoresis

INTRODUCTION Reductionism leaves us at the end of modernity with the ghost of man brooding over a great abyss wherein swirl in endless trivial concatenation the myriad particulars of his former self. ‘‘Tis all in pieces. All coherence gone’’[1]. The objective of scientific reductionism is to isolate elements or subsets of related observations or phenomena that account for the phenotype and circumstance of a given domain of nature. This approach of reducing systems to smaller and more basic components enables hypothesis testing or problem solving [2]. It has been argued that proteomics (i.e. the systematic, reproducible, differential and quantitative measure of the protein expression in samples from a defined biological domain) has expanded the scope of biological studies from the reductionist biochemical analysis of single proteins to proteomewide measurement [3]. Proteomics proffers the opportunity to characterise physiology and pathophysiology in terms of defined and specific changes in the more than 106 proteins that comprise the human proteome. This argument, however,

* Corresponding author. Tel.: þ61 3 8532 1178; fax: þ61 3 8532 1100. E-mail address: [email protected] (G.E. Rice). 0143e4004/$esee front matter

appears to dwell more upon the potential of proteomic methodologies rather than reflecting, with fidelity, the limitations of its present application. If all that proteomics delivered was a myriad of particulars then Smith’s allegory may have credence. Translational proteomics (i.e. the processes and platforms that facilitate the delivery of applications derived from proteomic analysis), however, now offers opportunities to define protein expression profiles that reflect phenotypic change; and contribute to clinical application and utility. Such approaches apply preceptive filters to the proteome (e.g. knowledge base in the case of targeted proteomics or mathematical modeling in the case of protein/peptide profiling strategies) to extract that which is of contextual relevance. The aim of this review is to provide a brief overview of proteomic technologies and how the outcomes delivered by such platforms may be translated into applications of predictive utility in clinical and basic science. In particular, recent applications in protein/peptide profiling (solid-phase affinity capture mass spectrometry and the targeted approach of antibody arrays) and the opportunities they afford researchers within the discipline of reproductive biology to develop new diagnostic and prognostic tests and surrogate biomarkers to improve the delivery of women’s health care are considered. In particular, two profiling strategies will be highlighted: chromatographic bead-based mass spectrometry and protein solution array. Ó 2005 Published by IFPA and Elsevier Ltd.

Rice et al.: Translational Proteomics Developing a Predictive Capacity

APPLICATIONS IN REPRODUCTIVE BIOLOGY In Australia in 2002, there were more than 480,000 confirmed pregnancies and of these, 150,000 pregnancies miscarried. There were 255,095 live births. More than 40,000 of these pregnancies were complicated by conditions that contributed to acute morbidity and mortality. Included in these complicated pregnancy: 20,071 babies were born preterm and of these 4166 were delivered at less than 32 weeks’ gestation; 16,230 babies were of low birthweight with 1156 at less than 1500 g; 15,307 babies were born post-date; 5383 babies required tertiary care; 2493 died during the perinatal period; and 20 maternal deaths were recorded. Globally, more than 500,000 women die each year from complications of pregnancy and childbirth. The leading causes of pregnancy-associated maternal death are haemorrhage, sepsis, complications of abortion, prolonged or obstructed labour and hypertension. Similar statistics are shared by other developed countries. The clinical imperative for the development of diagnostic and prognostic tests and biomarkers for screening and monitoring pregnancy derives from the significant impact that undiagnosed, untreated and/or late-treated complications of pregnancy have on both the well-being of the mother and the newborn (including perinatal, neonatal and childhood development and adult susceptibility to disease). Complications of pregnancy arise, for the most part, as the sequelae of prematurity and growth restriction (for the baby) and cardiovascular related complications for the mother. The incidence of such complications of pregnancy has not diminished in recent decades. The development of predictive and diagnostic utilities for use at the first antenatal visit would provide, at least, an opportunity for more intensive monitoring of high-risk women and, at best, implementation of appropriate interventions. ANALYTICAL LIMITATIONS OF PROTEOMICS Proteomics has proved to be a rich source of biological information but too frequently it has fallen short of providing

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coherent, unifying insights into functional biology, phenotype and clinical circumstance (as evidenced by the paucity of proteomic-derived clinical biomarkers of proven efficacy). Instead it has settled for cataloguing proteins and/or observing their differential expression. The proteins isolated and identified are to a considerable extent prescribed by the limitations of the analytical procedures used and are of undetermined functional relationship. Currently, there is no single analytical platform that can deliver proteome-wide coverage e the desired holistic, non-reductionist approach. Issues of quantification of differential protein expression linger and the discipline still grapples with the processing and modeling of large multivariate data sets. Proteomics is maturing and diversifying into four principal sub-disciplines (Figure 1): (i) descriptive proteomics that seeks to define the protein complement of the human proteome; (ii) functional proteomics that seeks to define expression profiles of system response proteins, i.e. how suites of proteins change in response to challenges to homoeostasis (e.g. a response to hypoxia) [4e6], or hypertension [7]; (iii) targeted proteomics that focuses on a suite of proteins prescribed by a given knowledge base; and (iv) protein/peptide profiling that identifies and compares phenotype-specific protein expression profiles. From its early manifestations in the mid-1970’s (as Two dimensional electrophoresis, 2DE), it has become increasingly apparent that significant technological challenges limit the development of a comprehensive, holistic proteomic approach. Such limitations have been recently reviewed by others [3,8e11] and includes the large number of proteins (>106); the many possible post-translational modification variants; the analytical reproducibility of the various platforms; biological variation; and the dynamic concentration range over which proteins are expressed in the human proteome. This is particularly

Figure 1. Proteomic diversification. Proteomics is diversifying into four principal sub-disciplines: (i) descriptive proteomics that seeks to define the protein complement of the human proteome; (ii) functional proteomics that seeks to define expression profiles of system response proteins, i.e. how suites of proteins change in response to challenges to homoeostasis (e.g. a response to hypoxia, or hypertension); (iii) targeted proteomics that focuses on a suite of proteins prescribed by a given knowledge base; and (iv) protein/peptide profiling that identifies and compares phenotype-specific protein expression profiles.

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the case with the plasma proteome where protein concentrations span w12 orders of magnitude, and where proteins at g/l concentrations dominate and mask the expression profiles of lower abundance protein biomarkers. In response to this realisation, a reductionist approach has been further applied to proteomic analysis. That is, the fractionation of the protein complement into increasingly smaller subpopulations to avert overloading analytical systems currently available. These approaches have included the removal of high-abundance proteins (that can deliver up to 8e10fold enrichment of low abundance proteins, Figure 2) and multidimensional separation strategies e serial combinatorial permutations of 1D and 2D gel electrophoresis, capillary electrophoresis (CE), liquid chromatography (LC) and affinity capture (AF) techniques. At least three to five independent, serial separation strategies would be required to provide complete coverage of the human proteome. The application of these approaches, however, affords the opportunity to define

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complex protein mixtures and then to reassemble a more comprehensive montage of the human proteome. GEL-BASED TECHNOLOGIES There is no ideal proteomic platform, each has its own strengths and limitations and ultimately its suitability to any given application. The principal features that prescribe analytical utility include the capacity to
resolve protein species;
quantitate protein expression; and
characterise post-translational modifications (PTMs). Gel-based platforms (e.g. 2D polyacrylamide gel electrophoresis e 2D PAGE, and fluorescence 2D difference gel electrophoresis e 2D-DIGE) are still considered one of the more robust and quantitative proteomic approaches, and may be broadly viewed as being better

Figure 2. The effect of serial removal of high-abundance proteins from plasma on 2D PAGE protein display (11 cm, 10% acrylamide, pI 4e7, Criterion gels (Bio-Rad Laboratories). The top panel depicts neat plasma (50e60 g protein/l, 25 mg first dimension load), the middle panel depicts plasma following treatment with Affigel Blue and Protein A (2e3 g protein/l, 15 mg first dimension load) and the bottom panel following treatment with solid-phase anti-human plasma IgY (<1 g protein/l, 15 mg first dimension load).

Rice et al.: Translational Proteomics Developing a Predictive Capacity

suited for characterising intact proteins and their PTMs, and their relative quantitation. These strategies separate proteins with respect to their isoelectric point (in the first dimension) and subsequently by size (in the second dimension) [12e14]. Visualisation of proteins is made by one of the several possible staining methods. In caseecontrol protocols, comparison of protein displays either performed in parallel (on separate gels) or coincident (on the same gel using tagged protein sets) can reveal casedependent differentially expressed proteins. Resolved proteins can then be excised, processed and identified. The limitation of gel-based systems is their relatively low throughput, the necessity for sample processing and fractionation prior to display and limited mass range (usually 10e200 kDa) [15]. In addition, procedural protein losses and the overall experimental variation in estimating endpoints by 2D PAGE may be considerable. Procedural losses of radio-labelled proteins during 2DE PAGE display have been reported to be as high as 80% [16] but this can vary depending on the starting protein load. As with any other technique, variation is apportioned between technical replication (both within assay and between assay) and biological variation (i.e. sample-tosample). Estimates of the variation attributable to technical replication average 24% [17,18]. In our laboratory, gel-to-gel coefficient of variation based on density analysis of 99 matched spots from nine replicate gels has been estimated to average 35  3%. Biological variation has been estimated to be between 24 and 70% [18]. The inherent technical and biological variations that exist within an experimental paradigm may be accommodated by appropriate experimental design to achieve meaningful hypothesis testing (i.e. of sufficient statistical power to discriminate between empirical changes). Some of the limitations of gel-based approaches have been overcome with the development of difference gel electrophoresis [19,20]. This minimal labelling approach using fluorescent cyanine dyes (e.g. Cy3 and Cy5) increases throughput by reducing sample processing and both gel-to-gel and analytical variations by combining case and control samples into a single processing step, and by the use of an internal standard for normalisation of data across gels. DIGE also delivers useful relative quantification of protein expression profiles where the dyes are purported to have sub-nanogram sensitivity and a linear response to protein concentration of over five orders of magnitude. The dyes are also compatible with mass spectrometric analysis. With respect to analysing the plasma proteome, DIGE is still prescribed and limited by the compositional complexity of plasma and the method similarly benefits from sample fractionation and the removal of high-abundance proteins [21]. Drawbacks include the cost of the fluorescent dyes and the need for dedicated scanning equipment and gel analysis software. Within the discipline of reproductive biology, 2DE PAGE has been used extensively in descriptive and functional proteomic studies. For example, descriptive studies have been used to characterise the protein expression in reproductive tract tissues [22], gestational and fetal tissues [23e25] , plasma [26], amniotic fluid [27] and urine [28]. Functional proteomics has

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been used to identify changes in protein expression associated with oxygen tension [29e32], embryo-induced alterations in endometrium [33] and complications of pregnancy [34,35]. NON-GEL-BASED TECHNOLOGIES Of the non-gel-based proteomic approaches, liquid chromatography (LC) and capillary electrophoresis (CE) methodologies have been extensively applied in pre-analytical sample fractionation [36]. As with other proteomic approaches, the primary function of LC and CE is to reduce sample complexity. In the case of LC, separation is based upon differential analyte hydrophobicity and has high peak capacity. For CE, analyte separation is largely determined by charge and size and is faster and of higher resolution than LC. Both techniques can be used in either conservative (top-down) or reductionist (shot gun or bottom-up) paradigms. At the extreme end of reductionism is the bottom-up approach in which, for example, capillary chromatographic separations of complex peptide digests are subjected to electrospray ionisation (ESI)-ion trap MS analysis. While this approach affords greater opportunity to identify low abundance proteins, significant information about protein modifications is lost [37,38]. The serial configuration of LC chromatographic dimensions prior to MS analysis (e.g. multidimensional protein investigation technology e MudPIT) has been used to deliver greater efficiency with respect to the number and molecular weight and pI range of proteins identified [39e41]. In this approach, complex sample digests are resolved by strong cation exchange (SCX) chromatography followed by reverse phase (RP) chromatography and delivered directly into an ion trap mass spectrometer. When applied to the analysis of whole cell lysates of the yeast proteome, MudPIT (SCX and RP in an ESI ion trap MS) identified almost 5500 peptides in three experimental runs that resulted in the identification of 1484 proteins (i.e. 23% of the predicted proteome) [41]. More recently, capillary LC has been interfaced with Fourier Transform Ion Cyclotron Resonance (FTICR) MS for the analysis of tryptic digests of human biofluids including plasma [42] and CSF [43]. Such analyses have typically identified up to 6000 peptides per run. ‘‘Top-down’’ chromatographic approaches (including reverse phase HPLC, capillary electrophoresis and 2D chromatography), in which intact, native proteins are isolated and characterised before identification, conserve structural and PTM information and have superior resolution than gel-based techniques [44,45]. Mass coded labelling (MCL) MCL techniques have been developed to enhance the quantitation capabilities of LCeMS based proteomic strategies. The approaches utilise a similar coding strategy to that used in 2D-DIGE, in that complex protein samples are differentially labelled and then combined (multiplexed) before protein/ peptide tryptic digestion, separation and quantitation of the

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relative intensities of differentially mass-labelled peptide doublets. In the case of DIGE, spectrally distinct tags are used (e.g. Cy3 and Cy5). In MCL techniques, proteins are coded with mass tags, that is, moieties of different mass that are easily detected by mass spectrometry [46,47]. Provided that ‘‘heavy’’ and ‘‘light’’ coded proteins behave similarly through the separation protocol, multiplexing samples eliminate inter-sample procedural variation. Predominantly, reagents incorporating stable isotopes (such as 2H, 13C, 15N and 18O) have been employed as mass tags. Typically, such mass reagents are composed of (i) a reactive group that covalently binds, for example, cysteine (Isotope Code Affinity Tag, ICAT) or lysine (Isotope Coded Protein Labelling, ICPL) residues; (ii) a linker that incorporates ‘‘light’’ or ‘‘heavy’’ isotopes that allows differentiation between peptide populations; and (iii) an affinity tag (e.g. biotin) to facilitate isolation of coded peptide. Stable isotope-labelled amino acids have been used for the metabolic labelling in cell cultures (SILAC). In such experiments, parallel cell cultures are incubated in the presence of native amino acid or stable isotope-labelled amino acid. After several cell divisions, all proteins are isotopically coded. Following experimental manipulation, cell culture extracts or conditioned media are combined, processed and the relative abundance of ‘‘heavy’’ to ‘‘light’’ peptide may be assessed to identify differentially expressed proteins. Other recent variants of MCL include iTRAQ [48] and isotope-differentiated binding energy shift tags (IDBEST) [49]. With iTRAQ up to four different protein samples may be coded by reporter-specific reactive groups that covalently bind to lysine side chains and N-termini. Samples may then be multiplexed for processing and analysis. The reporter groups generate fragment ions that appear in the low-mass region of the spectrum where other fragment ions are not generally found, and thus the protein abundance of samples differentially labelled with each reagent can be assessed by comparing the ratio of the peak areas of each reporter group. IDBEST is similar to other MCL methods in which a tag (containing 12C or 13C) is conjugated to a specific amino acid side chain. In addition, IDBEST tags include one or more high mass defect elements (elements with atomic numbers between 35 Br and 63 Eu). The incorporation of such elements enhances mass spectrometric discrimination between labelled and non-labelled peptides, thus reducing the requirement for pre-analytical sample processing. The method has been reported to be well suited to the characterisation of low abundance protein isoforms. Stable isotope coding of proteins not only affords quantitation of differential protein expression but, as affinity moieties (e.g. biotin) may be incorporated in these tags, it also affords opportunity to selectively enrich tagged proteins and peptides up to 10-fold [10]. While this approach reduces sample and mass spectra complexity and increases capacity for identifying low abundance proteins, non-target-containing peptides and proteins (including PTMs) may be excluded from the analysis.

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Non-isotopic labelling strategies have been developed, e.g. mass-coded abundance tagging (MCAT) [50]. In this technique, O-methyl isourea is used to guanidinate the C-terminal lysine residues of peptides in one sample, while the other sample remains unmodified; the samples of each are combined, and the relative abundance of each can be determined by mass spectrometry. To date, non-gel-based proteomic methodologies have not been widely applied within the field of reproductive biology and, in particular, mass coded labelling strategies. The application of such methodologies to protein profiling and targeted proteomic studies of fetal and maternal fluid compartments affords greater opportunity for the identification of biomarker proteins of clinical utility in the diagnosis and monitoring the complications of pregnancy. Liquid chromatographyemass spectrometry methodologies, however, have been developed and widely used in newborn screening [51e56]. SOLID-PHASE AFFINITY CAPTURE MASS SPECTROMETRY PROTEIN PROFILING Solid-phase affinity capture techniques are being increasingly utilised for sub-fractioning complex protein solutions prior to analysis by mass spectrometry. In common with other sample preparation approaches, solid-phase affinity capture reduces sample complexity to avert overloading analytical systems. The benefits afforded by this technology include the following: (i) diversity of surface chemistries available for sub-fractionating proteins, with protein binding achieved via hydrophobic, Lewis-acid/base, electrostatic, or coordinate covalent bond interactions; (ii) ability to isolate proteins of common or related physicochemical properties; and (iii) capacity for high-throughput automation and interfacing with MS platforms. In combination with bioinformatics tools for developing discriminant models, solid-phase affinity capture MS is rapidly emerging as a preeminent technology for disease biomarker discovery. SELDI ToF mass spectrometry In recent years, surface enhanced laser desorption ionisation (SELDI) ToF MS has been applied as a serum/plasma biomarker discovery platform. The objective of this approach is to identify reproducible patterns of protein/peptide profiles that can be used for diagnosis, prognosis and monitoring of disease progression. In such analyses, it is the pattern of multiplex protein/peptide peaks and the identity of the analyte that is modeled. For example, Ciphergen’s ProteinChip ArraysÒ employ a planar array of surface chemistries (including reverse and neutral phase, anionic, cationic and metal affinity surfaces) for simultaneous processing and sub-fractionation

Rice et al.: Translational Proteomics Developing a Predictive Capacity

of samples before analysis by ToF MS. Isolation of proteins by ‘‘on-surface’’ sample processing potentially reduces procedural losses, allows for extensive washing to reduce non-specific binding and eliminates analyte dilution effects common to other approaches. The limitations of SELDI relate to the limited protein binding capacity of the affinity surfaces; the introduction of surface-derived mass spectrometric noise and the relative lowmass accuracy of the ToF MS utilised. The technology has not been without its critics [57e60]. Issues of reproducibility and inter-laboratory validation of protein profiles remain. SELDI technology and applications have been recently reviewed and the reader is directed to these resources for further information [61e63]. Bead-based solid-phase affinity capture MALDI-ToF MS MALDI-ToF technology is becoming increasingly popular in life science research for its high mass accuracy and ability to detect macromolecules such as peptides, proteins and oligonucleotides. The speed and multiplexing of the MALDI MS analysis makes it ideal for various screening and diagnostic applications [64,65]. The complexity of biological samples, however, has imposed a major challenge for direct MALDI mass spectrometric applications. To reduce sample complexity, chromatographic media with different functional groups have been used to isolate and enrich analytes of interest before being eluted for MALDI MS analysis. This ‘‘off-line’’ sample processing approach proved to be effective and versatile. In comparison to SELDI’s ‘‘on-line’’ process, it has advantage in its scalability and the possibility of subsequent processing of eluted samples. For biomarker and proteomic studies, further analytical processing beyond initial MS screening, such as LCeMS and tandem MS, could provide crucial information on

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potential markers and proteins of interest. The introduction of chromatographic magnetic beads makes the ‘‘off-line’’ sample processing compatible with automation (Figure 3) [66]. The robotic liquid handling capacity that is afforded by the use of magnetic beads enables high sample throughput and ensures a maximum of reproducibility, both of which are critical for biomarker discovery studies (Figure 4). A commercial system (ClinProt) combining magnetic bead sample preparation, liquid handling, MALDI-ToF MS analysis and bioinformatics data analysis software has been introduced by Bruker Daltonics (Billerica, MA). Its applications in proteomic and biomarker studies are being explored by the authors and other labs [67]. ANTIBODY ARRAY APPLICATIONS Irrespective of the proteomic platform utilised, antibody-based protein profiling remains one of the principal methodologies for the application-oriented translation of proteomics. The major advantages of antibody-based approaches are (i) quantitation of analytes in multiplex format (up to 100 different analytes with solution array); (ii) good reproducibility (with CV <10%); (iii) sensitivity e often being able to detect proteins at far lower concentrations (1021 M, [68]) than other current proteomic methodologies; and (iv) specificity that minimises the effect of the dynamic range of protein concentrations in the sample to be assayed. A weakness of the current generation of approved antibody-based diagnostic and prognostic tests is that most rely upon the determination of a single analyte concentration to establish test sensitivity and specificity. In consideration of this limitation, alternative approaches of profiling disease-associated changes in selected subsets of proteins are being developed and evaluated, and are delivering promising results. This approach may be more broadly applied

Figure 3. ClinProt Robot Workflow. Protein samples (e.g. 96  5 ml plasma) are incubated with affinity chromatographic magnetic beads (e.g. 5 ml MB-IMACCu) and then washed (using magnetic strips to manipulate the beads) to remove non-bound material. Bound proteins are then eluted from the beads and spotted on a MALDI target (AnchorChip, Bruker Daltonics). MALDI-ToF spectra obtained from case and control samples are then interrogated using a genetic mutation algorithm to identify disease-related differences in the protein profiles (ClinProt Tools).

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Figure 4. Reproducibility of protein profiles obtained using IMAC-Cu magnetic beads on a ClinProt Robot (Bruker Daltonics). Four aliquots (5 ml each) of a single plasma sample were processed in parallel and through affinity chromatographic separation using IMAC-Cu magnetic beads, applied to a AnchorChip. Mass spectra were obtained using a Bruker Autoflex II Tof/Tof mass spectrometer used in linear mode.

Figure 5. Multiplex Solution Array Workflow. Samples (e.g. 96  20e50 ml plasma diluted 1:4) are incubated with antibody-coupled, coded microspheres. Up to 100 spectrally distinct microspheres are available, each potentially representing a different analyte assay. The non-bound fraction is removed by vacuum filtration using 96-well filter-bottom ELISA plates. The beads are resuspended and incubated with a biotin-labelled sandwich antibody, washed and then incubated with phycoerythrin (PE)-labelled streptavidin. Washed beads are then aspirated into a flow cell where individual beads are interrogated to establish bead identity (at 635 nm) and PE-dependent fluorescence (at 532 nm). Fluorescence intensity for each bead type is recorded separately for generation of individual standard curves and sample analyte concentration.

Property

2DE

DIGE

MudPIT

Separation

Electrophoresis IEF/PAGE

Electrophoresis IEF/PAGE

LC/LC of peptide

Quantitation

Densitometry

Fluorescence Cy dyes

Identification

Peptide Fingerprint Mapping

No. of peptide

IT

SELDI

ClinProt

Protein arrays

Solution array

LC/LC of peptide

Affinity binding

Affinity binding

Affinity binding

Affinity binding

None

Relative difference

Comparison of MS peaks

Comparison of MS peaks

Densitometry/ Fluorescence

Fluorescence

Peptide Fingerprint Mapping

MS/MS

MS/MS

Orthogonal

MS/MS

Specific affinity binding

Specific affinity binding

100s

100s

100e1000

100e1000

100s

100s

100

10e100

Hydrophobic

Moderate

Moderate

Moderate/Good

Moderate

Moderate

Moderate

Moderate

Moderate

Low abundance

Marginal

Marginale Moderate

Moderate

Moderate

Marginale Moderate

Moderate

Moderatee Good

Good

PTM

Good

Good

Nil

Nil

Poor

Poor

Moderate

Moderate

Noncandidate

Yes

Yes

Yes

Yes

Yes

Yes

No

No

Pros

Intact proteins, ID of isoforms

Better quantitation, reduced workflow

High resolution, MS/MS ID

High resolution, better coverage

Affinity capture

Affinity capture, MS/MS ID

High throughput, rapid screening

High throughput, quantitation, rapid screening

Cons

Low sensitivity, difficulty of spot matching Low no. of proteins

Low no. of proteins

Lack of quantitation

Loss of structural and isoform information

Difficult to ID, Matrix-derived noise, low-mass accuracy

MS/MS limited by signal peak intensity

Specificity of antigen/antibody binding

Fewer analytes, candidatebased

Rice et al.: Translational Proteomics Developing a Predictive Capacity

Table 1. Current generation of proteomics platform and the performance characteristics

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to discovery-oriented proteomics by limiting the search for putative biomarkers to a predefined knowledge base [8]. For example, by limiting protein profiling to candidates identified by microarray analysis of disease-associated changes in the gene expression, the likelihood of identifying proteins of utility is increased [69]. In general, antibody-based protein profiling methodologies are based upon the specific absorption of proteins to antibodies (or bait) arranged in planar or particulate solid-phase arrays [70]. Following analyte capture, detection and quantification are similar to ELISA-based assay [71]. SELDI and ClinProt antibody-based capture protocols are considered mass spectrometer variants with reduced capacity for quantitation and limited capacity for multiplexing. Of the current generation of antibody-based protein profiling technologies, solution array (Liminex, Austin, TX, USA) is one of the more effective platforms. This system utilises a sandwich ELISA-like protocol, in which capture antibodies are coupled to spectrally distinct polystyrene beads (5e6 mm diameter), biotinylated sandwich antibody and streptavidinephycoerytherin (PE) fluorophore. Assays are conducted in 96-well filter-bottom plates and beads are manipulated by vacuum filtration. Bead identity and analyte-specific fluorescence are assessed using a flow cytometer (Figure 5). Solution array offers excellent reproducibility (CV <10%) and analyte quantitation and has capacity to multiplex up to 100 different analytes in small sample volumes (e.g. 20e50 ml plasma). More than 250 multiplexed solution array assays are now commercially available, including: cancer (AFP, CA125, CEA and PSA); cardiac (PAP, creatine kinase); diabetes (insulin, leptin, C-peptide); metabolic (apolipoproteins, FABO, GST) and infectious disease (CMV, Cholera toxin, HPV) markers; cell signalling proteins (Akt, Erk1/2 IKB); cytokines; and MMPs. In our own laboratories using

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commercially-available 17-plex cytokine assays, we observed a limit of detection of 1e40 pg/ml plasma and intra- and inter-assay coefficients of variation of 4e6% and 8e14%, respectively (Bio-Plex: Interleukin-1b, 2, 4, 5, 6, 7, 8, 10, 12, 13, 17, Tumor Necrosis Factor a, Interferon g, Macrophage Chemotatic Protein-1, Macrophage Inflammatory Protein-1 alpha, Granulocyte Colony-Stimulating Factor, GranulocyteeMacrophage Colony-Stimulating Factor). Solution array now provides a pathway for the rapid translation of proteomic data obtained from any platform (discovery or candidate-based) into applications of predictive utility. The technology builds upon well-established and conventional immunoassay principles, is independent of the dynamic range effects that limit other proteomic platforms and is of suitable sensitivity. The pathway for translation has recently been further expanded with the development of a fully automated clinical pathology diagnostic solution array instrument (Bio-Plex 2200, Bio-Rad Laboratories, Hercules, CA, USA). Assays currently being evaluated for this platform include an antinuclear antibody screening panel [72]; and Epstein-Barr virus screening [73]. CONCLUDING COMMENTS Sir Peter Medawar once said ‘‘No branch of science can be called truly mature until it has developed some form of predictive capacity’’. Proteomics has undergone a rapid radiation, diversifying across the biochemical landscape. While no single technique yet delivers complete proteomic coverage, application-specific adaptations afford significant opportunity for discovery (Table 1). Targeted proteomic approaches, protein profiling strategies using affinity capture mass spectrometry and solution array represent realistic opportunities to deliver a predictive capacity.

ACKNOWLEDGEMENTS GER is the recipient of a National Health and Medical Research Council of Australia Principal Research Fellowship. Ms K. Oliva, G. Barker and L.A. Rice are acknowledged for their expert technical support of this project. GER gratefully acknowledges the support of the BHP Billiton Community Trust, GE Money and The George Hicks Foundation.

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