Improved Immobilized Metal Affinity Chromatography for Large-Scale

Improved Immobilized Metal Affinity Chromatography for Large-Scale Phosphoproteomics Applications Yasmine M. Ndassa,†,|,⊥ Chris Orsi,‡ and Jarrod A. Marto*,†,§,| Biophysics Program, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts

She Chen⊥ Proteomics Facility, National Institute of Biological Sciences, Zhongguancun Life Science Park, Beijing 102206, China

Mark M. Ross Mellon Medical Biomarker Discovery Laboratory, University of Virginia, Charlottesville, Virginia Received June 9, 2006

Dysregulated protein phosphorylation is a primary culprit in multiple physiopathological states. Hence, although analysis of signaling cascades on a proteome-wide scale would provide significant insight into both normal and aberrant cellular function, such studies are simultaneously limited by sheer biological complexity and concentration dynamic range. In principle, immobilized metal affinity chromatography (IMAC) represents an ideal enrichment method for phosphoproteomics. However, anecdotal evidence suggests that this technique is not widely and successfully applied beyond analysis of simple standards, gel bands, and targeted protein immunoprecipitations. Here, we report significant improvements in IMAC-based methodology for enrichment of phosphopeptides from complex biological mixtures. Moreover, we provide detailed explanation for key variables that in our hands most influenced the outcome of these experiments. Our results indicate 5- to 10-fold improvement in recovery of singlyand multiply phosphorylated peptide standards in addition to significant improvement in the number of high-confidence phosphopeptide sequence assignments from global analysis of cellular lysate. In addition, we quantitatively track phosphopeptide recovery as a function of phosphorylation state, and provide guidance for impedance-matching IMAC column capacity with anticipated phosphopeptide content of complex mixtures. Finally, we demonstrate that our improved methodology provides for identification of phosphopeptide distributions that closely mimic physiological conditions. Keywords: immobilized metal affinity chromatography • phosphoproteomics

1. Introduction Results from large-scale human genome studies indicate that the full repertoire of biological function is orchestrated by approximately 30 000 gene products.1 This seemingly modest number has fueled interest in so-called functional proteomics; that is, methods aimed at characterizing the plethora of posttranscriptional and post-translational events that collectively amplify or expand the inherent functionality encoded within * To whom correspondence should be addressed. Dr. Jarrod A. Marto, Department of Cancer Biology, Dana-Farber Cancer Institute, 44 Binney Street, Smith 1158A, Boston, MA 02115. Phone: (617) 632-3150 (office). Fax: (617) 632-4471. E-mail: [email protected]. † Biophysics Program. ‡ Present address: OTPP, Toronto, Ontario, Canada. § Department of Biological Chemistry and Molecular Pharmacology. | Department of Cancer Biology. ⊥ S.C. and Y.M.N. contributed equally to this work. 10.1021/pr0602803 CCC: $33.50

 2006 American Chemical Society

the genome. Mass spectrometry-based proteomics, particularly liquid chromatography coupled to electrospray ionization mass spectrometry (LC-ESI-MS), continues to play a leading role in these post-genomic era activities primarily due to the technique’s capability to rapidly and directly identify primary amino acid sequence and various post-translational modifications.2,3 Moreover, multiple approaches now exist to conduct these experiments in a semiquantitative manner to monitor changes in protein expression and specific post-translational events as a function of biological perturbation.3 Although mass spectrometry is the technique of choice for proteomics analyses, it does suffer from limited dynamic range (inability to detect peptides spanning an abundance ratio greater than 5000:1 in a single scan/spectrum) and finite acquisition rate (inability to acquire MS/MS data at a rate sufficient to provide sequence information on all peptides in a complex mixture Journal of Proteome Research 2006, 5, 2789-2799

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research articles during a single LC-MS/MS run, regardless of their relative abundance). These limitations, combined with the complex array of post-transcriptional events that must exist to ensure tightly coordinated control of biological processes at multiple hierarchical levels (cells, tissues, organs, whole organism), collectively drive development of fractionation and enrichment protocols with the goal of analyzing only those proteome subpopulations of most interest in a particular study (e.g., phosphorylated proteins or peptides in so-called phosphoproteomics analyses). Although phosphoproteins may account for some 30% of the eukaryotic proteome, proteomics-based analysis of signaling networks is nonetheless exacerbated because phosphorylation on any particular protein is typically transient and present in sub-stoichiometric concentration.4,5 Ideally, protocols designed to target specific proteome subpopulations would provide high specificity and sample recovery while minimizing any accompanying chemical modifications (e.g., introduction of affinity tags). Furthermore, the final, enriched peptide pool should be in a form and buffer system directly compatible with LC-MS analysis. Finally, protocols that are easily ported to autosamplers or other robotic platforms offer the added potential for automated, high-throughput analyses. Immobilized metal affinity chromatography (IMAC) in principle fulfills these criteria and thus offers a widely applicable and robust vehicle for phosphopeptide enrichment. Work by Ficarro et al. demonstrated that conversion of peptides to their corresponding methyl esters significantly increased IMAC selectivity for phosphopeptides versus their nonphosphorylated, acid-rich counterparts and illustrated the potential of IMAC-based enrichment for global phosphoproteomics studies.6 Subsequent work quantified the performance improvements provided by peptide methylation in the context of phosphotyrosine protein immunoprecipitation.7 Others applied similar immunoprecipitation strategies combined with stable isotope labeling to quantitatively track tyrosine phosphorylation events in human IFN-alpha8 and yeast pheromone signaling.9 Recent work by Zhang et al.10 incorporating peptidebased immunoprecipitation and iTRAQ reagents11 provided dramatically improved results for time-resolved quantitation of tyrosine signaling in the EGFR pathway. Finally, we note that Ficarro successfully described a platform for automated IMAC analysis, beginning after formation of peptide methyl esters.12 Collectively, these data demonstrate several analytical figures of merit for IMAC-based enrichment of phosphopeptides: (1) high specificity when combined with a simple, 2-step chemical modification protocol; (2) efficient phosphopeptide recovery and good absolute detection limits for analysis of biologically relevant systems, even when starting material is limited; (3) detection of stoichiometrically relevant distributions of S, T, and Y phosphorylation sites; (4) compatibility with a range of protein purification and LC-MS buffer systems; (5) amenable to automated workflows for high-throughput analysis. In principle, these figures of merit strongly support the use of IMAC-based enrichment for phosphoproteomics studies; nonetheless, anecdotal evidence suggests that IMAC-based phosphoproteomics, particularly as applied to so-called global studies, has not been widely embraced. Our experience in the use of IMAC-based enrichment indicated that subtle variation in a number of experimental variables could significantly alter data quantity and quality.6,13-15 It was also clear that further optimization would likely lead to improved results. Here, we describe a series of experiments designed to improve IMAC-based enrichment of phosphopeptides from complex bio2790

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logical mixtures and provide in-depth characterization of those variables that in our hands most influence experimental outcome. Our protocol provides 5- to 10-fold improvement in recovery of singly and multiply phosphorylated peptide standards in addition to significant improvement in the number of highconfidence phosphopeptide sequence assignments obtained from global analysis of cellular lysate. In addition, we quantitate observed trends in the number and distribution of phosphopeptides identified from complex biological mixtures as a function of buffer composition and IMAC column capacity. Finally, we demonstrate that our methodology provides for improved identification of physiologically relevant phosphopeptide distributions as predicted by in silico analysis. Collectively, our results provide for significantly improved IMAC-based phosphopeptide enrichment and offer valuable insight for successful application of this technique in global phosphoproteomics studies.

2. Material and Methods 2.1. Materials. Fused-silica tubing was from Polymicro Technologies (Phoenix, AZ). Column-end fittings, nuts, ferrules, and polymer (PEEK and Radel) tubing were from Valco Instrument Co. (Houston, TX) and Upchurch Scientific (Oak Harbor, WA). Teflon tubing was purchased from Zeus Industrial Products (Orangeburg, SC). Bulk resins for immobilized metal affinity chromatography (Poros MC-20) and reversed phase chromatography (ODS-AQ, 5µm diameter, 120 Å pore size C18 particles; mixed 5-15 µm diameter, 120 Å pore size C18 particles; irregular-shaped ODS-AQ C18 particles) were purchased from Applied Biosystems (Foster City, CA) and YMC (Kyoto, Japan), respectively. Yeast synthetic phosphopeptides (pSHERPDDVpSV, SHERPDDVpSV, and VHpSYTDLAYR) were from AnaSpec Inc. (San Jose, CA) and obtained at >95% purity. Synthetic peptide angiotensin II-phosphate, DRVpYIHPF, bovine serum albumin (BSA), β-lactoglobulin (BLG), carbonic anhydrase II (CA), R- and β-casein (ABC) were purchased from Sigma-Aldrich Corp. (St. Louis, MO). Sodium dodecyl sulfate, ammonium bicarbonate, anhydrous iron (III) chloride, ethylenediamine-tetraacetic acid (EDTA), nitrilotriacetic acid (NTA), nitrilotri(methyl phosphonic) acid (NTP), 2,5-dihydroxybenzoic acid (2,5-DHB), 5-sulfosalicylic acid (SSA), ascorbic acid (AA), formic acid, glacial acetic acid, thionyl chloride, sodium phosphate, guanidine hydrochloride, anhydrous methanol (d0 and d3), and acetonitrile were of biochemical-grade or equivalent and purchased from Sigma-Aldrich Corp. (St. Louis, MO). Sequencing grade modified trypsin was purchased from Promega Corp. (Madison, WI). HPLC grade acetonitrile and methanol were purchased from Fisher Scientific Intl. (Hampton, NJ). Human myeloid K562 cells were purchased from American Type Culture Collection (Manassas, VA). Buffered RPMI culture media, penicillin, streptomycin, bovine serum, and molecular biology grade ethanol, 2-propanol, chloroform, and guanidineHCl were purchased from Sigma-Aldrich Co. Fetal bovine serum was obtained from HyClone (Logan, UT). Trizol reagent was purchased from Invitrogen Corp. (Carlsbad, CA). 2.2. Cell Culture. K562 cells were maintained in suspension culture in RPMI 1640 media supplemented with 10% fetal bovine serum and 1% penicillin and streptomycin. Cells were grown at 37 °C in 5% CO2 and harvested by centrifugation during log phase. The cell pellet was washed three times with phosphate-buffered saline (pH 7.2) and aliquots of 1 × 108 cells were stored at -80 °C. 2.3. Stock Sample Preparation from Protein and Peptide Standards. BSA, BLG, CA, and ABC were dissolved in 500 µL

Improved Immobilized Metal Affinity Chromatography

of 50 mM ammonium bicarbonate (pH ∼8) to a final concentration of 50 µM for each protein. Next, 40 µg of sequencing grade modified trypsin were added, and the protein mixtures were incubated at 37 °C for 4 h. The resulting peptide mixtures were lyophilized (Labconco, Kansas City, MO). Esterification reagent was prepared by adding 40 µL of thionyl chloride to 1 mL of anhydrous methanol; the entire reagent was added directly to the dried peptide mixtures and these were subsequently sonicated for 10 min and then kept at room temperature for 1 h. The mixtures of peptide methyl esters were then dried by centrifugal concentration (Thermo Savant, Holbrook, NY) and kept at -80 °C. Synthetic peptide methyl esters were prepared exactly as above, but at 10 µM concentration and without enzymatic digestion. A working solution for optimization of IMAC sample loading and wash buffers was prepared by diluting the protein standards digest and yeast synthetic peptides (peptide methyl esters at 50 and 10 µM concentration, respectively) to 250 and 50 fmol/µL, respectively. In addition, working solutions for optimization of IMAC elution conditions were prepared from ABC and yeast synthetic peptides as described above, with the addition of a matched set of d3-methyl peptide esters. After esterification, these peptide mixtures were equally aliquoted into 20 tubes (50 pmol R and β casein, 5 pmol yeast peptides) prior to centrifugal concentration. Aliquots were stored at -80 °C. These were reconstituted to yield final working solutions of 500 and 250 fmol/µL, respectively, for ABC and yeast phosphopeptides. Specific phosphopeptide sequences used in this work include (from R-casein) VPQLEIVNpSAEER, YKVPQLEIVPNpSAEER, DIGpSEpSTEDQAMEDIK, TVDMEpSTEVFTK, EQLpSTpSEENSKK, and (from β-casein) FQpSEEQQQTEDELQDK. 2.4. Stock Sample Preparation from Cultured Cells. Frozen cell pellets containing ∼1 × 108 K562 cells were thawed on ice and resuspended with 10 mL of Trizol reagent. After incubation at room temperature for 10 min, 2 mL of chloroform were added and the mixture was briefly vortexed. Following centrifugation at 12 000 × g for 15 min at 4 °C, the top (aqueous) layer was discarded and 3 mL of ethanol were added. The mixture was vortexed briefly and centrifuged at 12 000 × g for 5 min at 4 °C. The supernatant was removed and aliquoted evenly into two fresh tubes, followed by the addition of 6 mL of 2-propanol to each tube. The tubes were briefly vortexed and then incubated at room temperature for 10 min. The samples were centrifuged at 12 000 × g for 10 min at 4 °C to obtain protein pellets. Supernatants were discarded, and 6 mL of 0.3 M guanidine-HCL in 95% ethanol were added to each tube. A spatula was used to disrupt both pellets after which they were combined into one tube. The suspension was twice sonicated for 10 min and then centrifuged at 12 000 × g for 5 min at 4 °C. The supernatant was discarded, and the remaining pellet was again mechanically disrupted. The pellet was resuspended in 10 mL of 0.3 M guanidine-HCL in 95% ethanol, and the cycle (disrupt, centrifuge, resuspend) was repeated 5 times or until the protein pellet was very fine in texture (i.e., no large chunks) and white in color. After the final wash, the pellet was resuspended in 10 mL of 100% ethanol, vortexed to create a homogeneous suspension, and then evenly aliquoted into 10 1.5-mL Eppendorf tubes, each containing protein corresponding to ca. 1 × 107 cell equivalents. Eppendorf tubes were centrifuged at 12 000 × g for 5 min at 4 °C and then stored at -80 °C. A stock protein digest was generated by first decanting the ethanol from one Eppendorf tube (1 × 107 cell equivalents or ∼2 mg total protein) and then resolubilizing the

research articles protein pellet with 300 µL of 1% SDS. This solution was diluted to 1500 µL with 100 mM ammonium bicarbonate (pH ∼8) followed by the addition of 40 µg of sequencing-grade modified trypsin and overnight incubation at 37 °C. Methyl esters of the resulting peptides were made following the same procedure described above except that after esterification, the reaction solution was aliquoted evenly into 5 fresh 1.5-mL Eppendorf tubes with subsequent centrifugal concentration to yield dried peptide methyl ester aliquots corresponding to 2 × 106 cell equivalents, or 400 µg total protein. Dried samples were stored at -80 °C. 2.5. Capillary Column Construction. Precolumns (PC) were packed with an 8-cm bed length of 5-15 µm spherical C18 beads in 75 µm i.d. fused silica capillary tubing. Frits were cast in situ using potassium silicate as previously described.16 Potassium silicate frits were also cast in situ at the rear of the column to prevent C18 beads from escaping during depressurization (e.g., after sample loading or when removing the column from the HPLC). High-performance analytical columns (AC, 50 µm × 8 cm) were constructed as previously described17 with the exception that irregular-shaped C18 beads were used as the frit material. The small IMAC columns (small IC, 200 µm × 8 cm) were prepared analogously to the PCs with potassium silicate frits cast in situ front and rear and were packed with Poros MC-20 resin. The large IMAC columns (large IC, 530 µm × 8 cm) were constructed by first capping one end with a 2 µm frit disk enclosed in a stainless steel column-end fitting. The column was then packed with Poros MC-20 resin and a second frit disk and stainless steel column-end fitting were assembled at the other end of the column. Because the large fused silica capillary is brittle, we encased the capillary in an identical length of 1/16” o.d. × 0.03” i.d. Radel tubing (Upchurch Scientific, Oak Harbor, WA) prior to assembly of the stainless steel column-end fittings. Small lengths (∼5 cm) of 360 µm o.d. × 100 µm i.d. fused silica tubing were used at the distal ends of each column-end fitting to facilitate connection of the IMAC column to a syringe or into a pressurized sample-loading bomb, or to provide a general outlet port for column preparation and sample loading/washing. During elution of phosphopeptides, a reversed phase precolumn was connected directly to the distal end of the stainless steel column-end fitting via a PEEK sleeve and compression-style nut and ferrule. The outer diameter of the fused silica capillary tubing used for all columns was 360 µm, except for the large IMAC columns for which the outer diameter was 670 µm. 2.6. Immobilized Metal Affinity Chromatography (IMAC) for Phosphopeptide Enrichment. The general protocol for preparation, sample loading, washing, and elution of the IMAC column consisted of the following steps: (1) rinse with 20 column volumes (CV) of 100 mM EDTA; (2) rinse with 5 CV of deionized, 18 MΩ water; (3) charge column with 20 CV of 100 mM FeCl3; (4) rinse with 20 CV of sample reconstitution buffer; (5) load sample, typically 2-20 µL volume; (6) rinse with 20 CV of reconstitution buffer; (7) rinse with 2 CV 0.01% acetic acid; (8) elute phosphopeptides directly to precolumn with 50 mM sodium phosphate, pH 8.0. For each step, the buffer composition and volume was varied to maximize phosphopeptide recovery; final, optimal conditions are described below (Results and Discussion). Phosphopeptide standards were analyzed using the small IMAC column whereas phosphopeptides from K562 cell lysate were enriched using both the small and large IMAC columns, as noted below (Results and Discussion). Journal of Proteome Research • Vol. 5, No. 10, 2006 2791

research articles The general IMAC protocol was modified to facilitate evaluation of elution buffers and their effect on phosphopeptide reversed phase PC binding efficiency. For analysis of IMAC buffer elution efficiency, 1 pmol of ABC and 250 fmol of yeast peptide (d0-) methyl esters were loaded onto a small IC, followed by: (1) primary elution directly onto a reversed phase PC with 100 µL of experimental buffer (50 mM NTA, pH 3.0; 200 mM NTP, pH 3.0; 75 mM 2,5-DHB, pH 1.5; 250 mM AA, pH 2.5; or 170 mM SSA, pH 2.0); (2) immediate re-elution of the IC with 50 µL 250 mM PO4 buffer, pH 8.0 onto a fresh reversed phase PC. For each buffer tested the elution efficiency was determined from precursor abundance ratios observed in sequential LC-MS analyses of each PC pair (connected to an AC for LC-MS); an average percentage of phosphopeptides left on the IC after the primary elution was calculated across replicate experiments. In a separate series of experiments, the impact of each IMAC elution buffer on peptide binding to reversed phase sorbents was evaluated by: (1) loading 1 pmol of ABC and 250 fmol of yeast peptide (d0-) methyl esters onto a small IC; (2) direct elution onto a reversed phase PC with 50 mM PO4 (pH 8.0); (3) loading 1 pmol of ABC and 250 fmol of yeast peptide (d3-) methyl esters onto the reequilibrated IC; (4) direct elution of peptide (d3-) methyl esters onto the same reversed phase PC (containing previously eluted peptide (d0-) methyl esters) with the experimental elution buffer (NTA, NTP or SSA). All experiments were run in duplicate, after which the (d0/d3)/elution buffer pairs were reversed and again analyzed in duplicate. For each buffer tested, the PC was connected directly to an AC, and the binding efficiency of peptides onto the reversed phase PC was determined from precursor (d0/d3) abundance ratios observed in a LC-MS analysis. Furthermore all phosphopeptide ratios were normalized to those observed for corresponding peptide pairs simultaneously loaded and eluted from the IC with 50mM Phosphate buffer. Our normalization factor assumes that a given d0/d3 phosphopeptide pair will behave identically (with respect to IMAC elution and reversed phase PC capture) when loaded onto, and eluted from, the IC under identical conditions. 2.7. Liquid Chromatography-Mass Spectrometry. Agilent 1100 series binary pumps (Agilent Technologies, Santa Clara, CA) were used to generate aqueous-organic solvent gradients for online LC-MS experiments. Phosphopeptides were analyzed on 3D quadrupole ion trap, hybrid linear ion traporbitrap (Finnigan LCQ XP Plus and Finnigan LTQ Orbitrap, respectively, Thermo Electron Corp., San Jose, CA), and hybrid quadrupole time-of-flight (QSTAR XL, MDS SCIEX, Toronto, Canada) mass spectrometers. A nano-HPLC µESI assembly17 was used for on-line sample separation and introduction into the mass spectrometer. After elution of phosphopeptides from an IC the PC was rinsed with 20 CV of 0.1% acetic acid and subsequently connected to the low-flow outlet arm of a PEEK Y-style connector. The outlet end of the PC was connected directly to the inlet side of an AC using a Teflon sleeve. The µESI tip position with respect to the mass spectrometer inlet orifice was controlled by either a home-built 3-way positioner or a NanoESI Source (Proxeon Biosystems A/S, Odense, Denmark); HPLC eluent flow rate from the µESI tip was estimated at 20-50 nL/min using disposable graduated glass micropipets. HPLC solvent A was 0.2 M acetic acid and solvent B was either 70% acetonitrile/0.2 M acetic acid or 90% methanol/0.2 M acetic acid. LC-MS analysis of phosphopeptide standards was performed using a solvent gradient of 0-5% B in 5 min and 5-100% B in 35 min LC-MS analysis of phosphopeptides 2792


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derived from K562 cell lysate was performed using a solvent gradient of 0-5% B in 10 min, 5-50% B in 115 min, and 50100% B in 20 min. Mass spectrometry data acquisition was performed in data-dependent mode on the LCQ XP Plus and Orbitrap instruments (MS scan, 350 e m/z e 1500, top 3 most abundant MS/MS scans with exclusion list and 3 Da width isolation window, 1.5 kVolt ESI voltage, 175 °C capillary temperature) and in information-dependent mode on the QSTAR XL (MS scan, 300 e m/z e 2000, top 3 most abundant MS/MS scans using low resolution for precursor isolation and using 1.5 s accumulation with enhance all mode, 2.1 kVolt ESI voltage). 2.8. Data Analysis. MS/MS spectra for phosphopeptide standards analyzed using the LCQ XP Plus and LTQ Orbitrap were manually verified, and the peak intensities for the corresponding precursor selected ion chromatograms (SIC) were used to measure relative phosphopeptide recovery as a function of the various IMAC sample loading, washing, and elution conditions examined. Replicate experiments were performed and plotted accordingly. Data analysis for evaluation of elution buffer efficiencies and their impact on binding of phosphopeptides to reversed phase sorbents was performed as described above. MS/MS data for complex mixtures of phosphopeptides isolated from K562 cellular lysate were acquired on the QSTAR XL and formatted through Analyst 1.0 sp 8 (MDS SCIEX, Toronto, Canada) for subsequent database searches using Mascot (version 2.0.00, Matrix Science, Inc., London, United Kingdom) against the human protein component of the NCBI nonredundant protein database (NCBI-GenBank release 145.0). The search parameters allowed for 2 missed cleavages for trypsin, a fixed modification of +14 or +17 for d0 and d3-methyl esters, respectively, for aspartic acid, glutamic acid, and peptide C-terminus, and variable modification of + 80 for serine, threonine, and tyrosine phosphorylation. Mass tolerance was 1.2 Da for precursors and 0.35 Da for fragment ions. A Perl script was written to extract relevant features (peptide sequence, sequence score, number, and site of phosphorylation) from the Mascot output files; these data were then further analyzed and plotted in Microsoft Excel (Microsoft Corp., Redmond, WA). For experiments designed to elucidate general trends (Figures 2, 3A,B, and 4A), the corresponding Mascot results were first screened to verify that few (typically 100 CV), particularly in the presence of 100 mM NaCl. These data clearly indicate that minimizing buffer ionic strength significantly improves (g4-fold) IMAC-based phosphopeptide recoveries. In addition, we found that reconstitution of peptide methyl esters was qualitatively facilitated by use of higher organic content and that run-to-run reproducibility was improved by matching the sample reconstitution and IMAC wash buffers. Hence, in all subsequent experiments, 33:33:33 acetonitrile/methanol/water with 0.01% acetic acid was used for sample reconstitution and IMAC wash buffers. Finally, we note that in our hands thionyl chloride provided superior conversion efficiency of carboxylate groups to their corresponding methyl esters, and somewhat reduced chemical noise in LC-MS analyses of complex phosphopeptide mixtures, as compared to acetyl chloride. Although we made no attempt to quantify this observation, we note at least one other recent study that also utilized thionyl chloride for generation of phosphopeptide methyl esters.20 The improved performance of thionyl chloride may simply be due to the absence of water (which drives Journal of Proteome Research • Vol. 5, No. 10, 2006 2793

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Figure 2. Use of large-capacity IMAC columns provides for unbiased recovery of singly- and multiply phosphorylated peptides from complex biological mixtures. Histogram plots (A and B) show the percentage of singly and multiply phosphorylated peptides identified from 1 × 105 (blue), 5 × 105 (yellow), 1 × 106 (red), 2 × 106 (grey) cell equivalents, using (A) small (200 µm × 8 cm) and (B) large (530 µm × 8 cm) IMAC columns. The green bars show the distribution of phosphopeptides predicted in silico (see Experimental Section). (C) The use of high-capacity IMAC columns recapitulates predicted distribution of singly- and multiply phosphorylated peptides: (red line) distribution of tryptic phosphopeptides predicted from in silico analysis; (blue line) distribution of tryptic phosphopeptides identified from analysis of 2 × 106 cell equivalents using a large IMAC column; (dashed line) distribution of tryptic phosphopeptides identified from analysis of 2 × 106 cell equivalents using a small IMAC column. (D) The large IMAC column provides for a linear increase in total number of phosphopeptides identified as a function of initial protein content and, (E) significantly offsets competitive binding of singly versus multiply phosphorylated peptides. (Solid line) 530 µm × 8 cm IMAC column. (Dashed line) 200 µm × 8 cm IMAC column.

equilibria toward the free acid) as a byproduct of ester formation. 3.2. Increased IMAC Column Capacity for Improved Performance in Analysis of Complex Mixtures. Although the results depicted in Figure 1 represented a significant improvement in performance, it is important to note that we did not see a clear correlation between increased phosphopeptide intensity and number of phosphorylation sites per peptide. Thus, at this particular combination of peptide content and complexity (e.g., a mixture of simple standards with limited dynamic range and a small number of nonphosphorylated peptides), improvement in phosphopeptide enrichment was somewhat uniform. However, because these data were derived from an artificially constrained combination of peptide sequence and phosphorylation state, we hypothesized that competition between singly and multiply phosphorylated peptides would play an increasing role in observed recoveries as mixture complexity increased. To better characterize this phenomenon, we per2794


formed a series of experiments in which phosphopeptides derived from K562 cell lysate were captured on IMAC columns of various sizes and subsequently analyzed by LC-MS/MS on a QSTAR XL instrument. We generally observed that the higherenergy fragmentation afforded in the QSTAR XL versus the LCQ provided superior MS/MS spectra (for identification of number and specific site(s) of phosphorylation) across a wider range of phosphorylated peptides.13,21,22 For each IMAC column size, the total quantity of peptide loaded was varied by approximately 20-fold (∼1 × 105 to 2 × 106 cell equivalents, or 20 µg to 400 µg). Optimal sample reconstitution and IMAC wash buffers as determined in Figure 1 (above) were used for this series of experiments. Figure 2 demonstrates that careful matching of IMAC column capacity and overall phosphopeptide content is critical in order to avoid significant bias in observed distribution of phosphopeptides. For example, Figure 2 (A and B) shows the percentage of peptides identified as having one, two, three, or four (or more) phosphorylation sites, across four different


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Figure 3. Optimized sample reconstitution and wash buffers significantly improve IMAC-based enrichment for recovery of singly phosphorylated peptides from complex mixtures. Distribution of singly (blue), doubly (green), triply (yellow), and quadruply (red) phosphorylated peptides from 2 × 106 K562 cell equivalents enriched on a 530 µm × 8 cm IMAC column using previously described (A) and optimized (B) IMAC sample reconstitution and wash buffers. The optimized buffer system nearly doubles the total number of high-confidence phosphopeptide identifications (359 f 689) compared to previously described conditions. Significantly, 312 of the 330 newly identified peptides are singly phosphorylated. The numbers of multiply phosphorylated peptides remain essentially unchanged (∆ ) +7, +1, and +6 for doubly, triply, and quadruply phosphorylated peptides, respectively). (C) Histogram plot of ion abundance ratios for a subset of 125 singly- and multiply phosphorylated peptides identified using optimized and previously described IMAC buffers; precursors selected for MS/MS in only one of the two analyses are represented by white bars.

sample quantities (20, 100, 200, and 400 µg total protein, bars left-to-right for each phosphorylation state), on both small (Figure 2A) and large (Figure 2B) IMAC columns. Comparison of the histogram plots in Figure 2A,B) reveals that limited binding capacity of the smaller IMAC column leads to a shift in the distribution of phosphopeptides identified beginning at 100 µg of total protein analyzed. The higher binding capacity of the larger IMAC column maintains a uniform distribution of identified phosphopeptides across all sample quantities analyzed (Figure 2B). We next performed in silico analysis of the Phospho.ELM database to better evaluate the physiological relevance of these data; the green bars in Figure 2A,B show the predicted distribution of phosphopeptides resulting from this analysis. Figure 2C illustrates the in silico data (red line) and the experimental data for the largest total protein content analyzed (400 µg), using the small (dashed black line) and large (blue line) IMAC columns. Collectively, the data in Figure 2 (A and B) demonstrate that higher capacity IMAC columns provide

for identification of more uniform, and physiologically relevant, phosphopeptide distributions across a wide range of total protein content. In Figure 2D,E, we replotted our experimental data to illustrate the effects of IMAC column capacity on identification of total phosphopeptides and more specifically singly phosphorylated peptides. Figure 2D shows that the total number of phosphopeptides identified increases linearly as a function of sample quantity (20-400 µg) on the large IMAC column whereas the small IMAC column reaches a plateau at approximately 100 µg total protein. More significantly, Figure 2E shows that the number of singly phosphorylated peptides also increases linearly as a function of sample quantity (20400 µg) on the large IMAC column. However, the small column demonstrates a severe bias against retention of singly phosphorylated peptides beginning at approximately 100 µg of total protein analyzed. These data clearly show that competition among peptides of different phosphorylation state can introduce significant bias under conditions of limited IMAC column Journal of Proteome Research • Vol. 5, No. 10, 2006 2795

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Figure 4. Use of methanol for HPLC organic solvent significantly improves temporal separation of phosphopeptides in LC-MS analyses. Histogram plots for the number of phosphopeptides binned as a function of HPLC elution time using methanol (white bars) or acetonitrile (grey bars) organic gradients. (A) Histogram for all high-confidence phosphopeptides identified. (B) Histogram for 200 high-confidence phosphopeptides common between the methanol and acetonitrile systems. Methanol clearly provides a more uniform phosphopeptide elution profile.

capacity. More importantly, our data show that use of higher capacity IMAC columns offers a simple and straightforward remedy and facilitates identification of a consistent and physiologically relevant distribution of phosphopeptides across a wide range of biological sample quantities. 3.3. Increased Phosphopeptide Recovery from Complex Mixtures using Optimized IMAC Reconstitution and Wash Buffers. We next sought to investigate the impact of buffer composition on the distribution of phosphopeptides observed during analysis of complex mixtures. Toward this end, phosphopeptides from K562 cell lysate (2 × 106 cell equivalents or 400 µg total protein) were enriched on a large IMAC column using sample reconstitution and wash buffers spanning a range of salt concentration and pH (as in Figure 1). Figure 3 shows the number and distribution of phosphopeptides identified for previously described (Figure 3A)6 and our optimized sample reconstitution and IMAC wash buffers (Figure 3B). Detailed 2796


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inspection of these data reveals that use of higher ionic strength buffers introduces severe, negative bias against enrichment of singly phosphorylated peptides. For example, Figure 3A shows that only 32% (115) of the 359 confidently assigned peptide sequences were singly phosphorylated while doubly- and triply phosphorylated peptides accounted for 42% (151) and 15% (54), respectively. Using the buffer compositions optimized for recovery of standard phosphopeptides (Figure 1), the distribution of observed phosphopeptides shifts dramatically; Figure 3B shows that under these conditions, the fraction of singly phosphorylated peptides nearly doubles (63% or 427) whereas doubly and triply phosphorylated peptides now account for a much smaller fraction (23% (158) and 8% (55), respectively) of all phosphopeptides observed. Significantly, we note that the observed increase in total number of peptides identified in Figure 3B (689 - 359 ) 330) is due almost entirely to improved recovery of singly phosphorylated species (427 - 115 ) 312). We performed a replicate experiment and observed essentially identical results, with the percentage of singly phosphorylated peptides increasing from 33 to 60%, out of total of 725 highconfidence phosphopeptides identified using our optimized protocol (data not shown). To further explore this observation, we extracted ion abundances for 125 (64 singly- and 61 multiply-) phosphorylated peptides from these data. Figure 3C shows the phosphopeptide precursor ratios observed using our optimized and previously described sample reconstitution and IMAC wash buffers. We observe a g2-fold increase in phosphopeptide precursor abundance for 40 out of 64 singly phosphorylated peptides, with only 1 phosphopeptide decreasing in observed abundance by >2-fold. In contrast, none of the multiply phosphorylated peptides increase in abundance by more than 2-fold, and only 4 out of the 61 decreased by g2-fold under our optimized buffer conditions. Hence, in contrast to the results obtained for analysis of phosphopeptide standards (Figure 1), we observe a significant bias in the number and distribution of phosphorylated peptides identified from complex mixtures (Figures 2 and 3) as a function of sample buffer composition and IMAC column binding capacity. We note that the data presented in Figure 1 versus that in Figures 2 and 3 are consistent given the inherent difficulty of using peptide standards to recapitulate the dynamics of a complex peptide mixture derived from cell lysate; we speculate that the distribution of phosphorylation states in our standard mixture (Figure 1) is simply too narrow to elucidate the interplay of competition between singly and multiply phosphorylated peptides. In addition, the ratio of IMAC binding capacity to total phosphopeptide content is much higher for analysis of phosphopeptide standards versus studies of phosphopeptides derived from cellular lysate, again making it difficult to decipher general trends based only on the analysis of phosphopeptide standards. Finally, we note that our choice of SDS for protein solubilization was based on its effectiveness specifically for reconstituting Trizol-extracted proteins and more generally because of its ubiquitous use throughout the research community; we surmised that successful use of SDS in our procedure would serve as a relevant benchmark for the general applicability of IMAC-based phosphopeptide enrichment. Note that depending on the concentration of SDS in the protein digest solution and the post-methylation sample reconstitution volume (0.2% and 3% SDS, respectively, for the data presented herein), the IMAC column may experience a significant concentration of sodium during sample loading. We estimate a sodium concentration of 700 mM for these experi-


ments and speculate that this also contributes to the reduced improvement in phosphopeptide recovery observed for analyses of the complex (∼3-fold) and standard (g5-fold) mixtures. The use of a nondetergent-based solubilization agents such as urea or guanidine may provide an alternative route, although these would require a desalting step prior to peptide methylation. Further studies are required to characterize the subset of peptides that exhibit poor retention on the IMAC column in the presence of excess sodium (e.g., loading sample to the IC in the presence of SDS) versus those whose hydrophilicity hinders their binding to reversed phase de-salting columns (e.g., de-salting peptides from urea or guanidine solutions prior to methylation). The results described in Figures 1-3 agree well with previous work7 that demonstrated significantly improved selectivity when peptides were converted to their corresponding methyl esters prior to phosphopeptide enrichment via IMAC. However, these previous data were based on recoveries of selected phosphorylated standards by IMAC from mixtures already enriched via immunoprecipitation of tyrosine phosphorylated proteins. In contrast, we chose to pursue global phosphopeptide enrichment (not just tyrosine phosphorylation) from cellular lysate specifically to tax the performance capabilities of IMAC and decipher those variables that most influence final outcome. Our results clearly show that the use of peptide methyl esters is a necessary, but not sufficient, prerequisite for successful application of IMAC. Our data provide significant and in-depth characterization of the complex interplay between phosphopeptide competition, IMAC column capacity, and buffer composition and unequivocally demonstrate that without very careful control of these variables practitioners attempting IMAC-based phosphopeptide enrichment (particularly in the context of complex biological samples) may suffer systematic and deleterious experimental bias, and risk severe misinterpretation of their results. Fortunately, our results also show that careful attention to IMAC column capacity and buffer ionic strength provides robust and reproducible enrichment of phosphopeptides from complex biological mixtures. 3.4. Optimized HPLC Gradient Conditions for Improved Phosphopeptide Sequence Analysis. At least one mass spectrometry-based proteomics study23 has confirmed earlier reports24,25 that increased hydrophilicity conferred to peptides by a phosphate moiety may lead to diminished retention on reversed phase sorbents. As a result, we reasoned that organic gradient conditions typically used in LC-MS may not be optimal for analysis of phosphopeptides. In experiments analogous to those described in Figures 2 and 3, we attempted to increase temporal peptide separation, and thus offset inherent limitations in mass spectrometer MS/MS acquisition rate, and therefore improve sequence identification via MS/MS, by simply decreasing the organic gradient slope. Unfortunately, we quickly reached a point of diminishing returns as characterized by excessively wide chromatographic elution profiles (>5 min, data not shown). We next substituted methanol for acetonitrile in our HPLC solvent system. We reasoned that the lower elution strength of methanol relative to acetonitrile26 for reversed phase separations would provide a more uniform distribution of phosphopeptides across the HPLC elution profile. Figure 4A shows a histogram plot of the number of high-confidence phosphopeptide sequence assignments as a function of HPLC elution time, binned in 30 min intervals, for methanol (white bars) and acetonitrile (grey bars) solvent systems. As we hypothesized, the observed phosphopeptide

research articles elution profile was much more uniform for methanol versus acetonitrile throughout the acquisition period. To further investigate this phenomenon, we extracted phosphopeptides that were common to both LC-MS analyses and spanned the entire elution profile for each solvent system. Figure 4B shows the histogram plot for this subset of phosphopeptides. As in Figure 4A, we observed a more consistent elution profile of phosphopeptides across the entire HPLC gradient. In fact, our preliminary analysis of these data indicate that methanol alone may not efficiently elute the most hydrophobic phosphopeptides from the column; we are currently investigating the use of tertiary gradients (for example, methanol followed by acetonitrile) to obtain the advantages of each individual solvent. Ultimately, this approach may represent a simple strategy to counter the apparent tendency of phosphopeptides to elute relatively early under typical HPLC gradient conditions and result in identification of a greater number of phosphopeptide sequences from complex mixtures. 3.5. Impact of IMAC Elution Buffer on Phosphopeptide Recovery. The results in Figure 4 and the fact that the majority of published reports rely on basic solutions of either ammonia8,27 or phosphate6,7,10,12,20,28,29 to elute phosphopeptides from an IMAC column suggested that the capture of phosphopeptides on a reversed phase PC at elevated pH (after elution from an IMAC column) may be inefficient and result in reduced phosphopeptide recovery. To investigate this phenomenon, we performed a series of experiments designed to elucidate the relative capture efficiency of phosphopeptides on a reversed phase PC as a function of IMAC elution buffer composition. On the basis of previous observations,23-25 our expectation was that acidic IMAC elution buffers would drive equilibria toward protonated phosphate moieties, thus countering the generally higher hydrophilicity of phosphopeptides and their purportedly diminished binding to reversed phase sorbents. We evaluated a number of compounds, including H3PO4, NTA, NTP, AA, 2,5DHB, and SSA, under acidic elution conditions. To ensure appropriate comparison, we first sought to evaluate the IMAC elution efficiency of these reagents. In principle, each compound, except AA, should elute phosphopeptides by competitive chelation of Fe3+; ascorbic acid should facilitate elution by reducing Fe3+ to Fe2+, thus diminishing overall IC affinity for bound phosphopeptides. We performed serial re-elution of peptide (d0-) methyl esters from an IC with 250 mM phosphate buffer (pH 8) immediately after primary IMAC elution with the experimental buffer. Our results (not shown) indicated that NTA, NTP, AA, 2,5-DHB, each eluted g95% of phosphopeptides from an IC, with SSA performing even better with a typical elution efficiency g99%. On the basis of these results, we chose SSA as our elution agent to probe the impact of IMAC elution pH on subsequent binding efficiency of phosphopeptides onto reversed phase sorbents. As described above, we separately eluted peptide (d0/d3) methyl esters onto a single PC using 50 mM phosphate buffer (pH 8) in the first elution and 170 mM SSA (pH 2) in the second elution (after complete re-equilibration of the IC). To reduce the influence of systematic bias, these experiments were performed in duplicate and with both (d0/ d3)-methyl isotope-elution buffer combinations, and all intensity ratios were normalize against those for peptide (d0/d3) methyl ester ratios observed from simultaneous loading onto an IC. Interestingly, elution of the IMAC column under the acidic conditions did not significantly improve phosphopeptide retention on the reversed-phase precolumn; we observed an average precursor intensity ratio of 1.2 across the (d0/d3)-methyl Journal of Proteome Research • Vol. 5, No. 10, 2006 2797

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Ndassa et al.

Table 1. IMAC Protocol for Poros MC-20 Resin Packed in Fused Silica Column Format step #

descriptiona

flow rate (µL/min)

1 2 3 4 5 6 7 8 9

rinse with 20 CV of 100 mM EDTA rinse with 5 CV of deionized water charge with 20 CV with 100 mM FeCl3 rinse with 20 CV RB load sample rinse with 2 CV of RB rinse with 20 CV of RB rinse with 2 CV 0.01% acetic acid elute with 50-70 µL of 50 mM PO4 buffer

10-20 10-20 10-20 10-20 1-2 1-2 10-20 10-20 10-20

a RB, reconstitution buffer (33:33:33 acetonirile/methanol/water, 0.01% acetic acid); CV, column volume.

isotope-elution buffer combinations described above. For further confirmation, we replicated this experiment on phosphopeptides enriched from K562 cellular lysate; as with the analysis of phosphopeptide standards under these conditions, we observed an average precursor intensity ratio (across a representative distribution of singly and multiply phosphorylated peptides) of 1.6, indicating no significant improvement in capture of phosphopeptides on reversed phase sorbents as a function of IMAC elution buffer pH (data not shown). We note that these data have important implications for successful use of still-larger IMAC columns (for higher sample capacity) requiring concomitantly larger elution volumes, with relatively small reversed phase precolumns (preferred for superior LCMS performance). It is likely that these column configurations may be used without penalty of diminished phosphopeptide capture on reversed phase sorbents. More generally, our results imply that careful control of IMAC column capacity, along with sample reconstitution and wash buffers, impact data quality more so that conditions associated with IMAC elution.

4. Concluding Remarks To the best of our knowledge, this report represents the most comprehensive analysis to date of the IMAC approach for phosphoproteomics applications. We establish conditions for significantly improved IMAC-based enrichment of phosphopeptides (see Table 1) and, in the process, also provide a high resolution description of key variables that significantly influence the outcome of IMAC-based phosphoproteomics studies. The overall consistency of our data confirms that under appropriately controlled circumstances an IMAC-based approach for phosphoproteomics offers several advantageous analytical figures of merit. For example, the potential of incorporating this technique into gel-based or gel-free analyses, a simple, 2-step derivatization strategy to provide high specificity enrichment of phosphopeptides, and the ability to scaleup the experiment without introducing significant bias with respect to the distribution of observed phosphopeptides, collectively provide compelling evidence in favor of IMACbased phosphopeptide enrichment for proteomics applications. We note that previous studies have applied other phosphopeptide enrichment schemes and reported higher numbers of phosphopeptide sequences compared to what we observe herein.9,30 These reports employ a combination of multidimensional fractionation and approximately 5-fold9 and 20-fold30 greater quantity of purified protein, respectively, compared to the one-dimension LC-MS protocol used in this work. In each case, the authors rely on strong cation exchange (SCX) as a fractionation9 or enrichment30 strategy, and they note that 2798


including SCX may introduce a strong bias against recovery of multiply phosphorylated peptides. Hence, although direct comparison of these various approaches to our own is difficult, we nonetheless speculate that overcoming the described bias of SCX (against multiply phosphorylated peptides)9,30 is likely to be more problematic compared to the solutions described herein to offset analogous (but mechanistically different) biases encountered with IMAC-based phosphopeptide enrichment. In fact, based on the data herein, we propose that SCX after IMAC may be a relatively simple method to achieve efficient, overall phosphopeptide enrichment (IMAC) followed by fractionation of singly and multiply phosphorylated peptides (SCX). Similarly, we expect that a recently described protocol28 for phosphoprotein fractionation followed by enzymatic digestion and IMAC-based phosphopeptide enrichment may also benefit from the use of our optimized IMAC conditions. Finally, we note that a very recent paper by Moser20 demonstrated improved recoveries of singly phosphorylated peptides from purified hepatic proteins by use of a larger-capacity IMAC columns; although not as thoroughly characterized as our own, these data nonetheless agree well with those described herein with respect to biases introduced by limited column capacity and we speculate that these authors would realize even greater gains by use of our optimized buffer system. The field of phosphoproteomics is enjoying increased attention and rapid growth and will continue to thrive, driven generally by the critical role of phosphorylation in normal physiology and more specifically by the importance of aberrant signaling in many pathological states. For example, the therapeutic potential of small molecule-based therapeutics targeted against oncogenic kinases31,32 is one particularly promising area that will benefit from comprehensive phosphoproteomics analyses. Our in-depth approach to characterizing IMAC-based phosphopeptide enrichment provides for significantly improved performance and serves as a valuable resource for the growing community of researchers pursuing proteomics-based phosphorylation studies.

Acknowledgment. We thank Steven Gygi for his generous loan of the LCQ mass spectrometer used for analysis of phosphopeptide standards. We also thank Yi Zhang and Rositsa Koleva for valuable discussions and Eric Smith for valuable assistance in preparation of the manuscript. Generous financial support for this work was provided by the Dana-Farber Cancer Institute. Support for Y.N. is provided by a Howard Hughes Medical Institute Pre-Doctoral Fellowship. Supporting Information Available: Lists of representative phosphopeptide sequences along with precursor m/z, scores, and phosphorylation site are included in Supporting Information Tables 1, 2, 3, and 4. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) (2) (3) (4) (5)

Venter, J. C., et al. Science 2001, 291, 1304-1351. Peng, J.; Gygi, S. P. J. Mass Spectrom. 2001, 36, 1083-1091. Aebersold, R.; Mann, M. Nature (London) 2003, 422, 198-207. Blume-Jensen, P.; Hunter, T. Nature (London) 2001, 411, 355-365. Manning, G.; Whyte, D. B.; Martinez, R.; Hunter, T.; Sudarsanam, S. Science 2002, 298, 1912-1934. (6) Ficarro, S. B.; McCleland, M. L.; Stukenberg, P. T.; Burke, D. J.; Ross, M. M.; Shabanowitz, J.; Hunt, D. F.; White, F. M. Nat. Biotechnol. 2002, 20, 301-305. (7) Brill, L. M.; Salomon, A. R.; Ficarro, S. B.; Mukherji, M.; StettlerGill, M.; Peters, E. C. Anal. Chem. 2004, 76, 2763-2772.

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(22) Lee, B. H.; Min, X.; Heise, C. J.; Xu, B. E.; Chen, S.; Shu, H.; LubyPhelps, K.; Goldsmith, E. J.; Cobb, M. H. Mol. Cell 2004, 15, 741751. (23) Neubauer, G.; Mann, M. Anal. Chem. 1999, 71, 235-242. (24) Dass, C.; Mahalakshmi, P.; Grandberry, D. J. Chromatogr. A 1994, 678, 249-257. (25) Wilson, K. J.; Honegger, A.; Stotzel, R. P.; Hughes, G. J. Biochem. J. 1981, 199, 31-41. (26) Mahoney, W. C.; Hermodson, M. A. J. Biol. Chem. 1980, 255, 11199-11203. (27) Nuhse, T. S.; Stensballe, A.; Jensen, O. N.; Peck, S. C. Mol. Cell. Proteomics 2003, 2, 1234-1243. (28) Collins, M. O.; Yu, L.; Coba, M. P.; Husi, H.; Campuzano, I.; Blackstock, W. P.; Choudhary, J. S.; Grant, S. G. J. Biol. Chem. 2005, 280, 5972-5982. (29) Salomon, A. R., et al. Proc. Natl. Acad. Sci. U.S.A. 2003, 100, 443-448. (30) Beausoleil, S. A.; Jedrychowski, M.; Schwartz, D.; Elias, J. E.; Villen, J.; Li, J.; Cohn, M. A.; Cantley, L. C.; Gygi, S. P. Proc. Natl. Acad. Sci. U.S.A. 2004, 101, 12130-12135. (31) Sawyers, C. L. Curr. Opin. Genet. Dev. 2002, 12, 111-115. (32) Wadleigh, M.; DeAngelo, D. J.; Griffin, J. D.; Stone, R. M. Blood 2005, 105, 22-30.

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