Protein kinase substrate identification on functional protein arrays
© Meng et al; licensee BioMed Central Ltd. 2008
Received: 19 August 2007
Accepted: 28 February 2008
Published: 28 February 2008
Over the last decade, kinases have emerged as attractive therapeutic targets for a number of different diseases, and numerous high throughput screening efforts in the pharmaceutical community are directed towards discovery of compounds that regulate kinase function. The emerging utility of systems biology approaches has necessitated the development of multiplex tools suitable for proteomic-scale experiments to replace lower throughput technologies such as mass spectroscopy for the study of protein phosphorylation. Recently, a new approach for identifying substrates of protein kinases has applied the miniaturized format of functional protein arrays to characterize phosphorylation for thousands of candidate protein substrates in a single experiment. This method involves the addition of protein kinases in solution to arrays of immobilized proteins to identify substrates using highly sensitive radioactive detection and hit identification algorithms.
To date, the factors required for optimal performance of protein array-based kinase substrate identification have not been described. In the current study, we have carried out a detailed characterization of the protein array-based method for kinase substrate identification, including an examination of the effects of time, buffer compositions, and protein concentration on the results. The protein array approach was compared to standard solution-based assays for assessing substrate phosphorylation, and a correlation of greater than 80% was observed. The results presented here demonstrate how novel substrates for protein kinases can be quickly identified from arrays containing thousands of human proteins to provide new clues to protein kinase function. In addition, a pooling-deconvolution strategy was developed and applied that enhances characterization of specific kinase-substrate relationships and decreases reagent consumption.
Functional protein microarrays are an important new tool that enables multiplex analysis of protein phosphorylation, and thus can be utilized to identify novel kinase substrates. Integrating this technology with a systems biology approach to cell signalling will help uncover new layers in our understanding of this essential class of enzymes.
Eukaryotes have devoted approximately two percent of their genome to kinases, highlighting the importance of protein kinase function. Protein kinases are involved in numerous cellular processes, and aberrant kinase activity has been directly implicated in the etiology of a wide spectrum of human pathologies. In recent years, several kinase-directed drugs, including Gleevec®, Iressa®, Herceptin® and Avastin®, were approved to treat human diseases . Currently, more than 50 protein kinase drug candidates are in clinical trials to treat diseases including cancer, chronic inflammation, metabolic disorders, and neurodegenerative disease. The importance of protein phosphorylation in global regulation of cellular processes is apparent from estimates that at least one third of all proteins are phosphorylated . For the vast majority of these proteins, however, the protein kinase(s) responsible for their phosphorylation is not known. In addition, the function of many protein kinases is completely unknown or has been poorly characterized. Despite their central role in health and disease, the identification of protein kinase substrates remains a significant challenge. Techniques that advance our knowledge about the substrates of specific kinases will certainly aid in our understanding of this biologically essential class of protein enzymes.
A growing number of methods to identify substrates of protein kinases are available. Most commonly, proteins from cells are isolated either from gels, by immunoprecipitation, or by metal affinity chromatography, and the phosphorylated sequences are determined by mass spectrometry [3–5]. Kinase-substrate relationships have also been determined through the use of enzyme inhibitors, functional knockouts and analogue sensitive kinase alleles combined with mass spectrometry. There are limitations inherent to these approaches, however, such as functional redundancy, poor characterization of enzyme-inhibitor specificity, and lack of sensitivity due to under-representation of low abundance proteins in these screens. In addition, mass spectrometry-based approaches often require considerable amounts of time and a high level of technical expertise to complete assays, operate instrumentation, and perform data analysis. The use of phospho-specific antibodies against consensus phosphorylation sites has been helpful in addressing some of these issues, but the consensus sequence information or high quality phospho-specific antibodies are not available for many discovery efforts.
In vitro based platforms using purified components offer solutions to some of the limitations of mass spectrometry-based approaches for protein kinase substrate identification. For example, the use of peptide arrays in substrate screens has been valuable for defining consensus phosphorylation sites for many protein kinases. However, it is very difficult to predict which cellular proteins are in fact substrates of protein kinases based solely on short primary sequence information, and using this data to identify bona fide kinase substrates is often problematic. Experiments have demonstrated that the ability of a kinase to modify a protein at a specific site is influenced by its structural context, including post-translational modifications such as glycosylation [6–8], localized sequential "priming" phosphorylations , inhibitory sequences , secondary structure and solvent accessibility . For these reasons, using arrays of full-length but denatured proteins to screen for kinase substrates, as recently described by Feilner et al using arrays of denatured Arabidopsis proteins , has significant limitations, Solution-based assays using purified proteins that have been expressed, purified, and demonstrate functional activity can overcome some of these limitations but can be costly to achieve on a large scale.
Proof-of-principal for the use of arrays of native or functional proteins for kinase substrate profiling was described by MacBeath and Schreiber . Although this study utilized arrays of only a few proteins, it demonstrated some of the advantages that functional protein arrays offer over existing assays. For example, arrays containing thousands of proteins can be prepared with similar amounts of protein to rapidly establish kinase-substrate relationships with limited concentration-based artefacts. Second, the identity of the substrates is known immediately following the assay since full-length proteins are used and the position of each protein on the array is known. Third, the probability that a phosphorylated structured protein revealed in an array experiment is indeed a cellular target of the kinase should be much higher than candidate substrates identified from experiments based on peptides. Lastly, because arrays may contain up to thousands of proteins, target selectivity is quickly addressed with minimal amounts of reagent. Recently, a seminal study by Ptacek et al. profiled the activity for 87 purified yeast protein kinases against a proteome array containing over 4000 proteins expressed and purified from S. cerevisiae . The approach successfully identified thousands (4,192) of phosphorylation events mapping to 1,325 different substrate proteins. The integration of these results with multiple data types has also led to new proposals regarding yeast protein kinase interaction networks. More recently, Boyle et al. used high-content human protein microarrays to identify the actin-regulatory protein cortactin, a protein that is upregulated in several cancers, as a novel substrate of the Abl and Abl-related gene (Arg) nonreceptor tyrosine kinases . These investigators went on to show that Abl-family kinases target cortactin as an effector of cytoskeletal rearrangements in response to PDGF.
In the current study, a detailed characterization of the protein microarray kinase-substrate identification assay is presented. Arrays of human proteins are used, and critical experimental parameters are investigated to address optimal assay performance. We show that the kinase-substrate phosphorylation microarray assay reconstitutes enzyme-substrate interactions observed in solution-based assays using a set of solution-validated protein kinase-substrate pairs. Results are also presented that show that these arrays can be used to quickly identify novel substrates of human protein kinases on functional human protein arrays containing thousands of highly purified proteins and that pooling-deconvolution strategies can be employed to rapidly identify specific kinase-substrate relationships.
Results and Discussion
Solution validation of kinase-substrate interactions
Protein Array Assay
Elk-1 Fusion Protein
ATF2 (aa 19–96)
MAPK8 (JNK1) Inactive
MAPK9 (JNK2) Inactive
ATF2 (aa 19–96)
Kinase-substrate interactions on protein arrays
Six of the kinase-substrate interactions in the test set were not observed on the arrays using the standard protocol when a static Z-Score threshold of 3.0 was applied, where the Z-Score represents the number of standard deviations above the median signal value for all protein features present on the array. BSA is included at a relatively high concentration (10 mg/ml) in the standard array kinase-substrate assay in order to block non-specific interactions, but was not included in the solution phase assays used to develop the test set. Eighteen kinase-substrate interactions were observed using an array assay protocol that did not contain any BSA, with 16 interactions overlapping with those observed in the BSA protocol when a Z-Score threshold of ≥3.0 was applied (Table 1). Several kinase-substrate interactions exhibited significantly different signals depending on the protocol that was used. For example, the signals for Protein Kinase A (PKA) phosphorylation of Tau protein were approximately eight-fold greater in the absence of BSA (Figure 2c). Conversely, the signal for Map Kinase Kinase 6 (MKK6) phosphorylation of p38α was approximately 18-fold greater in the presence of BSA (Figure 2c). After combining the results of both protocols, a total of 20 true positives out of a possible 24 (83%) kinase-substrate interactions could be observed on protein arrays.
Effect of array protein concentration
Effect of Time and ATP Concentration
The protein microarray assay exclusively uses radiolabeled ATP (33Pγ-ATP) at a relatively low concentration (33 nM) compared to most kinase-substrate phosphorylation assays, which typically utilize micromolar quantities of ATP. The KM for most protein kinases is approximately 50 micromolar, raising the possibility that the enzymatic efficiency of the array assays at 33 nM ATP may not be optimal. However, when 0.45, 4.5 or 45 μM unlableled ATP was added to the p38 alpha kinase array assay, thereby providing approximately a 10-, 100-, or 1000-fold excess of unlabeled ATP, a concentration-dependent decrease in signal was observed for both the positive control protein kinases and the substrates (Figure 4b).
Substrate Identification on High Content Protein Arrays
A pooling-deconvolution strategy for substrate identification
Recently, an approach was described to improve the efficiency and accuracy of large scale screening experiments in which pools of potential interactors are applied against a defined library and then an algorithm is used to deconvolute the results . This strategy was applied to yeast two-hybrid and small molecule/cell survival screens and subsequently validated using protein arrays. In the validation study, protein-protein interaction assays were performed using pools of proteins probed against yeast protein microarrays comprised of more than 4000 yeast proteins, followed by successful deconvolution of expected individual interaction pairs.
Posttranslational modification of proteins is one of the principle regulatory mechanisms in eukaryotes. In particular, protein phosphorylation has been demonstrated to be crucial in the proper regulation of nearly all cellular processes, including metabolism, cell organization and differentiation, responses to environmental stimuli and cell-cell interactions. Nevertheless, a thorough understanding of the full range of phosphoproteins modified by a specific protein kinase is often lacking. Proteome microarrays have been described in which sets of proteins, or nearly every protein in the case of yeast, were expressed, purified, and deposited on a surface in an addressable format [22–24]. Using such a proteome-scale microarray, Ptacek et al created a map of the yeast phosphorylome by incubating the arrays with nearly every yeast kinase and identifying thousands of phosphorylation events . These studies revealed a plethora of potentially novel biological functions as well as new regulatory interactions for a spectrum of kinases. More recently, a human protein array was used to identify a novel substrate for Arg and Abl kinases, the targets of the anti-cancer drug Gleevec . In the present study, we performed a detailed characterization of the ProtoArray® technology as employed to define kinase-substrate interactions, and have identified a number of key features that can impact kinase-substrate discovery efforts.
The first task was to benchmark performance of the kinase-substrate application on protein arrays relative to standard solution-based assays. This was accomplished by defining a test set of kinase-substrate pairs and determining the correlation of substrate phosphorylation on the array relative to a solution assay. Twenty out of 24 (83%) kinase-substrate pairs were reconstituted on arrays, demonstrating that substrate phosphorylation on protein arrays is highly consistent with solution-based methods, even under the relatively generic conditions employed in these assays. Several possibilities exist for the inability to observe phosphorylation of four protein on the arrays including (1) binding of the protein to the array surface in such as way as to preferentially mask a phosphorylation site; (2) denaturing of the protein on the array that abolishes a kinase interaction domain; (3) altered kinetics of the phosphorylation reaction on the array surface; or (4) a combination of several of these factors. Nevertheless, this "false-negative" rate must be considered in light of the advantages of the array format including speed, low material requirements, and the ability to survey thousands of purified proteins in a single experiment.
In a second set of experiments, we investigated the effect of assay conditions – specifically, the presence or absence of BSA in the assay buffer – on the results obtained with the arrays. Interestingly, 75% of the proteins phosphorylated in solution were observed to be phosphorylated on the arrays either in the presence or absence of BSA; however, the substrates identified under the different conditions did not completely overlap. A subset of protein substrates were observed only in the presence of BSA, while others were only seen to be phosphorylated on the array in the absence of BSA. In the former case, BSA may be stimulating substrate phosphorylation through a 'crowding' effect by increasing the effective local concentration of protein kinase at the array surface. In the latter case, BSA may be interfering with substrate phosphorylation through either binding to protein kinases, and/or by being a substrate for the kinase itself, thereby lowering the amount of available 33Pγ-ATP and/or kinase in the assay below the threshold required to give adequate phosphorylation of the substrate. Assays in which BSA was included in the buffer gave rise to a higher mean Z-Score across the test set of 24 kinase-substrate pairs, with 17 of the 24 pairs resulting in higher Z-Scores when BSA was present in the assay buffer. Based on this result, BSA-containing buffers are recommended if a single assay condition is to be employed. Further investigation will be required to determine the exact mechanism of the effect of BSA in this assay, and carrying out assays under both assay conditions should be considered in order to maximize the probability of observing substrate phosphorylation.
The study investigating the yeast phosphorylome reported that approximately two-thirds of previously annotated phosphorylation events were not observed in their protein array experiments. One possible explanation for this observation is that the amount of protein spotted on the array was too low to be phosphorylated by kinase. To explore this issue, we measured the relative amount of protein that must be spotted on the arrays for significant phosphorylation to be observed, and determined that the median LOD for the test set of kinase-substrate interactors was approximately 2 ng/μL, which is equivalent to approximately 2 pg of spotted protein. The median level of proteins on the yeast and human proteome arrays are approximately four-fold greater than this amount, suggesting that the majority of proteins on the arrays are present in quantities sufficient to observe phosphorylation. It should also be noted that this amount of spotted protein is approximately 1000-fold less protein than is required to observe phosphorylation in a solution-based assay.
Another factor that could influence the identification of proteins on the array as substrates for exogenous kinases could be masking of potential phosphorylation sites as a result of phosphorylation occurring during protein production by endogenous kinases. Using both anti-phosphoamino acid antibodies and phosphoamino acid stains such as ProQ Diamond, we have shown that many yeast and human proteins expressed from either yeast or insect cells and spotted on protein arrays are indeed phosphorylated (data not shown). As shown in Figure 6, CK2 phosphorylated several proteins only after dephosphorylation of proteins on the array with lambda protein phosphatase. For some proteins, the removal of the phosphate groups through enzymatic treatment with phosphatase was required in order to observe substrate phosphorylation on the array. It should also be pointed out that phosphorylation by some kinases may require that substrates are pre-phosphorylated or "primed" on specific residues.
We have provided further evidence that high content human protein arrays can be used to make novel insights into the biology of human protein kinases. In one example, 23 substrates were identified and validated for CamK2, 11 of which could be assigned to specific functions or pathways. The two protein substrates exhibiting the strongest signals were Doublecortin (DCX) transcript variants 4 and 2. Doublecortin, which has not previously been reported as a CAMK2 subsrate, is important for neurite outgrowth in the developing brain, and acts by stabilizing microtubules . The observation that that calmodulin-kinase 2 phosphorylates doublecortin suggests a mechanism by which CamK2 regulates neuronal migration by influencing microtubule stability, and is consistent with the well established role for CamK2 in neuroplasticity [26, 27].
We have also demonstrated for the first time that a pooling-deconvolution strategy can be applied to protein kinase substrate identification on protein arrays. In these experiments, four protein substrates were identified (FLJ22795, SH3YL1, CRKL, ABI1) that were uniquely phosphorylated on arrays treated with the Abl protein kinase. Signaling through Abl is critical to regulation of several cellular functions including organization of the actin cytoskeleton . CRKL is a known substrate of Abl , and ABI1 is a known Abl interacting protein that has been shown to facilitate phosphorylation of Mena, a protein involved in cell adhesion and motility . The protein SH3YL1 is homologous to the yeast protein Ysc84, which localizes to the cortical cytoskeleton in yeast and is involved in coupling endocytosis to the actin network . This type of data argues that bona fide interactors can quickly be identified from screens on protein arrays. However, it is likely that a subset of proteins identified from such screens will not validate in vivo as protein kinase substrates, particularly if kinase and substrate occupy separate subcellular compartments. In addition, various factors in the in vitro array assay, such as kinase and/or substrate concentration, cofactors or lack thereof, or ionic conditions, may lead to inappropriate phosphorylation events. Finally, it is likely that many membrane-associated proteins, especially those which have regions that span the membrane, do not exhibit a native conformation on the array due to the lack of lipid, and thus may be phosphorylated in regions that are normally not accessible to a kinase. Assimilation of protein microarray data with orthogonal data types such as protein expression, localization, and interaction networks will most certainly enrich inventories of in vitro kinase-substrate pairs and expand our understanding of protein kinases function in cellular processes. We believe such integrated datasets will provide novel insights to intracellular phosphoprotein signaling which could ultimately foster important new efforts for drug discovery and development.
Commerical protein substrates were purchases from Cell Signalling, Upstate, Calbiochem and Invitrogen. Commercial protein kinases were purchased from Upstate and Invitrogen. All clones used to generate the human protein collection were fully sequenced and subcloned into the expression vector, pDEST™20 (Invitrogen Corp.). These clones were then used to express proteins in Sf9 insect cells as N-terminal GST-fusions using the Bac-to-Bac® Baculovirus Expression System (Invitrogen Corp). Insect cell lysates were loaded directly into 96-well plates containing glutathione resin (GE Healthcare). After washing, proteins were eluted under non-denaturing conditions by the addition of 10 mM glutathione. ProtoArray® Human Protein Microarrays v1.0 (Invitrogen Corp., Carlsbad, CA) were printed on 1 × 3 inch modified glass slides using a 48 pin contact arrayer (OmniGrid, Genomics Solutions). Protein arrays were stored at -20°C until use.
Solution kinase assay
10 μl reaction mixtures contained assay buffer II (BSA-free) (1% Brij35, 100 mM MOPS pH 7.2, 100 mM NaCl, 5 mM MgCl2, 5 mM MnCl2, 1 mM DTT), 33Pγ-ATP (33 nM, 1 μCi/μl), substrate (10–100 ng), and kinase (1–50 nM). Assays were incubated at 30°C for 1 hour and terminated by the addition of 10 μl 2× SDS NuPAGE® Sample Buffer. Proteins were denatured in a 95°C water bath for 10 minute. 20 μl of samples were loaded into NuPAGE® 10% precast gels. Electrophoresis was performed on the gels at 120 V for 1 hour. The gels were fixed in 10% acetic acid and 45% methanol for 45 minutes at RT, then washed twice with ddH2O for 30 minutes. Gels were encased in Saran Wrap and transferred to film cassette containing a phosphorimager screen to detect 33P activity at room temperature overnight.
Kinase Substrate Identification (KSI) microarray assay
For Buffer System I (BSA), the blocking buffer was 1% BSA in PBS, and the kinase reaction buffer contained 1% BSA, 1% NP-40, 100 mM MOPS pH 7.2, 100 mM NaCl, 5 mM MgCl2, 5 mM MnCl2, 1 mM DTT. For Buffer System II (BSA-free), the blocking buffer contained 50 mM Tris pH 7.5, 0.1% Brij35, and 5 mM MgSO4, and the kinase reaction buffer contained 1% Brij35, 100 mM MOPS pH 7.2, 100 mM NaCl, 5 mM MgCl2, 5 mM MnCl2, 1 mM DTT. Protein microarrays were blocked for 2 hours in blocking buffer. 120 μl of kinase reaction mixture containing γ33P-ATP (1 μCi/μl) and kinase (1–50 nM) was added to the surface of the microarrays. Arrays were covered with a Hyperslip™ coverslip, placed into a 50 ml cubicle tube, and transferred to a 30°C incubator with the array face up. After 60 minutes incubation, arrays were washed twice with 0.5% SDS and then twice with distilled water. After washing, arrays were placed into a 25-slide holder and spun for 2 minutes at 2000 rpm in a plate centrifuge. Dry arrays were exposed overnight to a phosphorimager screen and images were analyzed by the Genepix software and further analyzed using Microsoft Excel software or Prospector (Invitrogen). Three independent samples of 50 nM CaMKII and 33 nM γ33P-ATP in Buffer System I were prepared and incubated on arrays, alongside a single negative control assay lacking kinase. A second set of three independent samples of 50 nM CaMKII and 33 nM γ33P-ATP in the presence of 5 mM CaCl2 and 600 nM calmodulin, in Buffer System I was prepared and incubated on arrays, alongside a single negative control assay lacking kinase. For pooling-deconvolution assays, kinase pools were prepared in Buffer System I.
Phosphatase treatment of the protein microarray
The phosphatase reaction mix contained 400 Unit/ml of lambda protein phosphatase (New England Biolabs), 50 mM Tris-HCl pH7.5, 0.1 Na2EDTA, 5 mM DTT and 0.01% Brij35. 120 μl of phosphatase reaction mixture was added to the surface of the microarrays. Arrays were covered with a Hyperslip™ coverslip, placed into a 50 ml cubicle tube, and transferred to a 30°C incubator with the array face up for 2 hours. Arrays then proceeded to the KSI microarray assay or the Pro-Q microarray staining assay.
Pro-Q microarray staining
Microarrays were blocked in 1% BSA, 50 mM HEPES pH 7.5, 200 mM NaCl, 0.1% Triton X-100, 25% glycerol, 20 mM reduced glutathione, 0.5 mM DTT at 4°C for 2 hours. Arrays were placed into a 25 slide holder and spun at 4000 rpm for 2 minutes to remove excess liquid from the slide surface. Immediately, 120 μl of Pro-Q Diamond™ phosphoprotein/phosphopeptide microarray stain was added to the surface of the microarrays. Arrays were covered with a Hyperslip™ coverslip, placed into a 50 ml cubicle tube, and incubated for 30°C at RT with array face up. Arrays were washed with Pro-Q Diamond microarray-destaining solution twice for 15 minutes and then washed with water twice for 15 minutes. After washing, arrays were placed into a 25-slide holder and spun 2 minutes at 2000 rpm in a plate centrifuge to dry. Dry arrays were scanned with an Axon Scanner using the 535 nm wavelength setting, 100% Laser Power, and 600 PMT. Images were analyzed by the Genepix software and further analyzed using Protoarray™ Prospector (Invitrogen).
Low content arrays: Negative GST control signals were used to determine background signals for each subarray. For each spot, the mean background value was subtracted from the signal for spots in each subarray. Background-corrected signals were called significant when they were greater than three times the standard deviation of the average background signal in the same subarray. High content arrays: Arrays were analyzed in ProtoArray Prospector 3.0, including the signal scatter correction feature, and background signal normalization performed per subarray from the signal mean from GST and buffer spots.
We are grateful to the members of the protein expression, purification and array manufacturing groups at the Invitrogen Protein Array Center that have made these experiments possible. Funding to support the microarray and solution phase assays was provided by Invitrogen Corporation. Funding to support the pooling/deconvolution analysis effort was provided to JH by US National Institutes of Health National Human Genome Research Institute grant HG003729.
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