Highly Sensitive Phosphoproteomics by Tailoring Solid-Phase

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Highly sensitive phosphoproteomics by tailoring solid-phase extraction to electrostatic repulsion-hydrophilic interaction chromatography Stefan Loroch, René Peiman Zahedi, and Albert Sickmann Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/ac502708m • Publication Date (Web): 18 Nov 2014 Downloaded from http://pubs.acs.org on December 16, 2014

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Analytical Chemistry

Highly sensitive phosphoproteomics by tailoring solid-phase extraction to electrostatic repulsionhydrophilic interaction chromatography

Stefan Loroch1, René Peiman Zahedi1, Albert Sickmann1,2*

1

Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Otto-Hahn-Straße 6b, 44227 Dortmund, Germany

2

University of Aberdeen, School of Natural & Computing Sciences, Meston Building, Meston Walk, Old Aberdeen, AB24 3UE *email: [email protected], fax: 0049 – 231 – 1392 – 200

KEYWORDS Protein phosphorylation, Phosphoproteomics, LC-MS, RP, SCX, solid-phase extraction, Phosphopeptide enrichment

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ABSTRACT In the past decade, several strategies for comprehensive phosphoproteome analysis have been introduced. Most of them combine different phosphopeptide enrichment techniques and require starting material in the milligram range, as a consequence of their insufficient sensitivity. This limitation impairs the applicability of phosphoproteomics to a wide variety of clinical research, where sample material is highly limited. Here we introduce a highly sensitive and easy-toestablish 2D bottom-up strategy for µg-scale phosphoproteomics, based on electrostatic repulsion-hydrophilic interaction chromatography (ERLIC), a simple solid phase-extraction step by strong cation exchange (SCX) or reversed phase (RP) and LC-MS analysis. With only 100 µg of tryptic digested, non-stimulated HeLa protein and 45 h of LC-MS analysis time, we identified ≥ 7500 non-redundant and highly confident phosphorylation sites (per replicate). We assigned all phosphorylation sites to 3,013 phosphoproteins, covering the entire dynamic range from 107 down to a few copies per cell. Compared to affinity-based-enrichment methods using Ti4+, our ERLIC-based strategy enriched considerably longer and more acidic phosphopeptides and consequently, we identified 327 phosphorylated C-terminal peptides. The simplicity and high sensitivity

of

ERLIC-SCX/RP-LC-MS

render

its

future

promising

for

µg-scale-

phosphoproteomics in biological, biomedical and clinical research.

INTRODUCTION Protein phosphorylation is a key regulator of intra- and intercellular signaling events in biological systems. It enables cells to dynamically adapt to internal and external stimuli in the millisecond to second time range1. Since aberrant protein phosphorylation is connected to a wide variety of diseases and drug effects, the characterization of phosphoproteomes is one of the major tasks in clinical research2,3,4. Since the start of protein phosphorylation analysis by liquid chromatography coupled to mass spectrometry (LC-MS), technical developments have led to substantial improvements in phosphoproteomic characterizations5. Nowadays, large-scale bottom-up approaches aim at the comprehensive analysis of all protein phosphorylations in a biological system. These approaches are used to identify ten thousands of phosphorylation sites in a single sample but require large protein amounts (as summarized by Ficarro et al. 20116) from cells with artificially increased phosphorylation levels (by EGF, or phosphatase inhibitor treatment). This requirement is a

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consequence of low sensitivity, rendering large-scale approaches inapplicable for a wide range of clinical and biological research where sample amount is often highly limited. In the past ten years, promising strategies with higher sensitivities have been described, allowing thousands of phosphorylation site identifications (IDs) from less than 1 mg digested protein. Before LC-MS analysis, phosphopeptides are enriched via combinations of immobilized metal ion affinity chromatography7,8,9 (IMAC), metal oxide affinity chromatography10,11,12 (MOAC), hydrophilic interaction liquid chromatography13,14 (HILIC), or ion exchange chromatography15 (IEC). However, combinations of several different techniques are difficult to establish, prone to systematic bias and hard to automate. For simple and efficient large-scale phosphoproteomics, more specific and sensitive enrichment techniques have to be employed. Specificity and sensitivity is achieved when targeting all the physicochemical differences of a phosphopeptide compared to a non-phosphorylated one. The major differences of phosphopeptides are the lower net-charge at low pH (pH 2-3) and the higher hydrophilicity, two properties that are targeted in IEC and HILIC. Both retention mechanisms can be exploited by using an anion exchange column (AEX) in the HILIC mode in electrostatic repulsion-hydrophilic interaction chromatography16,17 (ERLIC). In ERLIC, the reduced net-charge of the phosphopeptide results in less electrostatic repulsion, while the higher hydrophilicity results in stronger hydrophilic interaction. This combination is exploited for selective retention. Consequently, ERLIC is ideal for peptide separation by charge and hydrophilicity. ERLIC has proven to be a versatile method, not only in phosphoproteomics, but also in glycoproteomics18,19 analysis of deamidated peptides20, fractionation of iTRAQ-labeled peptides21 and LC-MS coupling22. As a phosphoproteomics tool, ERLIC’s applicability in biochemical pathway elucidation has been successfully demonstrated23,24, as well as ERLICIMAC and ERLIC-MOAC applications24,25,26. As a stand-alone solid phase extraction (SPE) method, ERLIC with strong cation exchange (SCX) can be exploited to identify thousands of phosphopeptides from a complex sample27. However, all these studies were done with large protein amounts in the milligram range and the highly important question of sensitivity was left completely unexploited. In this study, we demonstrate for the first time, a highly sensitive ERLIC-based workflow for µgscale phosphoproteomics. To develop this improved strategy, we compared different SPE types to recover phosphopeptides after ERLIC and perform a final sample clean-up. Based on the


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achieved results, a robust and efficient ERLIC-SCX/RP-LC-MS workflow was designed (figure 1). We demonstrate its sensitivity in an experiment with 100 µg of tryptic digested HeLa protein from completely unstimulated cells. Subsequent calculations of the identified phosphopeptides’ physicochemical properties revealed complementarity to Ti4+-IMAC-based strategies and coverage of the entire dynamic range of proteins within a cell. A benchmark with state-of-the-art phosphoproteomics strategies reveals ERLIC-SCX/RP-LC-MS to be among the most sensitive large-scale phosphoproteomics strategies to date.

FIGURE 1. Overview of our robust and sensitive workflow for µg-scale phosphoproteomics by ERLIC-SCX/RP-LC-MS. 100 µg of tryptic digested HeLa protein was fractionated by ERLIC in 21 fractions. The fractions 1-9 were subjected to SCX-SPE, the fractions 10-21 to RP-SPE followed by LC-MS/MS analysis.

EXPERIMENTAL PROCEDURES Cell culture equipment was purchased from PAA Laboratories (Pasching, Germany), chemicals from Sigma Aldrich (Munich, Germany) in p.A. grade and organic solvents from Biosolve (Valkenswaard, Netherlands) in ULC/MS grade.


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CELL CULTURE AND CELL LYSIS HeLa cells were cultured in Dulbecco's Modified Eagle medium, containing 10 % fetal calf serum, 1 % penicillin/streptomycin at 37 °C and 5 % CO2 in 75 cm2 culture flasks. Cells were harvested using cell scrapers in the presence of 1 % SDS with 1 tablet of PhosSTOP (Roche, Mannheim, Germany) per 10 mL buffer. The lysate was ultra-sonicated and centrifuged for 30 minutes at 20,000 g at 4 °C. The clear supernatant was transferred to a new tube.

PROTEIN DIGESTION Cysteines were reduced with 10 mM dithiothreitol at 56 °C for 30 min and alkylated with 20 mM iodoacetamide at room-temperature for 30 min in the dark. Proteins were precipitated by adding 9 volumes of ice-cold ethanol and incubation at -40 °C for 1 h, followed by centrifugation for 45 min at 20,000 g and 4 °C. The resulting pellet was resolubilized in 6 M guanidine hydrochloride, and the protein concentration of the solution was determined by a bicinchoninic acid assay (BCA, Thermo Scientific, Bremen, Germany) using BSA (0 - 250 µg / mL) for calibration. The sample concentration was determined in triplicates in a dilution series of 1:10, 1:20, 1:40, 1:80. For digestion, the solution was diluted 20-fold with 50 mM ammonium bicarbonate and 1 mM CaCl2. Trypsin (Sigma Aldrich, T-1426) was added in a 1:40 ratio (w/w) followed by a 15 h incubation at 37 °C with slight agitation. The reaction was stopped by adding formic acid (FA) to a final concentration of 5 %. Amino acid analysis revealed that 0.89 ± 0.08 µg digested peptide / µg protein (according to BCA) was obtained. Peptides were desalted using SPEC C18 AR 30 mg cartridges (Agilent, Boeblingen, Germany). The SPE eluate was dried in vacuo followed by three cycles of dissolving in 10 mL 50 % methanol and subsequent drying.

ERLIC FOR SPE-TESTS First, we optimized the recovery of phosphopeptides from ERLIC fractions using different SPE materials. Therefore, sets of ERLIC fractions were generated by separating 800 µg HeLa peptide with a Famos, Switchos, Ultimate HPLC (Thermo Scientific) using a PolyWAX LP column (4.6 x 100 mm, 5 µm, 300 Å, Poly LC, Columbia) with 20 mM sodium methylphosphonic acid, 70 % acetonitrile (ACN), pH 2 for buffer A and 200 mM triethylamine phosphate, 60 % ACN, pH 2 for buffer B16. The injection volume was 75 µL and the flow was set to 1 mL/min using the


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following gradient: Equilibration for 8 min with 100 % A, followed by 100 % A for 7 min, 0 % to 100 % B (linear) in 5 min, 100 % B for 15 min. Peptides were dissolved in 75 µL buffer A and 7 fractions were collected in total: fraction 1+2 for 3.5 min each, fractions 3-6 for 2 min each, fraction 7 for 12 min. Thus, the fractions 1-7 correspond to 0, 0, 20, 60, 95, 100, 100 % ERLIC B, respectively. In order to ensure homogeneity for our SPE-tests, corresponding fractions of 4 runs (800 µg/run) were pooled and split in 16 sets (4*800µg/16 = 200 µg/set). Afterward, all fractions were dried in vacuo.

ERLIC FOR HIGHLY SENSITIVE, LARGE-SCALE PHOSPHOPROTEOMICS ERLIC was performed as described with the following changes: 100 µg HeLa peptides were dissolved in 20 µL mobile phase A and separated with the following gradient: Equilibration for 10 min at 100 % A, injection, 100 % A for 5 min, 0 to 100 % B (linear) in 15 min, 100 % B for 10 min. 21 fractions were collected in total: fraction 1 for 2 min, fraction 2-19 for 1 min each and fraction 20+21 for 5 min each.

SOLID PHASE EXTRACTION All SPE steps were performed with 100 µL buffer volume using Hypersep SpinTips 10-200 µL (Thermo Scientific). Tips were equilibrated and washed at ~ 400 g and sample loading and elution was done at ~ 200 g. In some cases, especially in SCX-SPE, adjustment of centrifugation force up to ~ 1,000 g was necessary since the residual of ERLIC mobile phase B gave high backpressure. All used buffers and elution schemes are shown in table 1. After elution, all samples were completely dried in vacuo.

TABLE 1. Buffers and elution schemes for SPE after ERLIC (ACN, acetonitrile; TFA, trifluoroacetic acid) SPE type

BUFFER A

BUFFER B

Elution scheme

RP

0.1 % TFA

50 % ACN

HILIC

15 mM ammonium acetate, 85 % ACN, pH 3.5

15 mM ammonium acetate, pH 3.5

HYPERCARB

0.1 % TFA

50 % ACN

3x 100 µl B, 3x 100 µl A, 2x loading in 100µl A (for Hypercarb SPE: sample adjusted to pH 8 using 2% NH4OH), washing with 3x 100 µl A, elution with 4x 100 µl B


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SCX (flowthrough used))

20 mM KH2PO4, 20 % ACN, pH 2.7

20 mM KH2PO4, 800 mM KCl, 20 % ACN

3x100µl B, 3x 100µl A, 2x loading and flow-through collected, 2x 100µl A and flow through collected

LC-MS/MS For SPE-tests, the dried samples were dissolved in 30 µL of 0.1 % TFA and 15 µL were subjected to nanoHPLC-ESI-MS/MS using an LTQ Orbitrap Velos or LTQ Orbitrap Velos Pro mass spectrometer, online coupled to a U3000 nanoHPLC (Thermo Scientific). Injected samples were loaded onto a C18 trap-column (100 µm x 2 cm) at a flow rate of 20 µL/min in 0.1 % TFA. After 10 min, the trap column was switched in-line with the C18 main column (75 µm x 25 cm) and separation was done, using a binary gradient at 300 nL/min and 60 °C. For the SPE-tests, separation was done using a 55, 65 or 180 min linear gradient (depending on the complexity of the fraction) with either 5-50 % B or 3-35 % B of mobile phase A: 0.1 % FA and mobile phase B: 0.1 % FA, 84 % ACN. The column effluent was introduced to the MS by a nano-ESI source using a silica coated PicoTip (360 µm outer- and 10 µm inner-diameter, New Objective, USA) operated at 1.5 kV and 275 °C transfer tube temperature. Data dependent acquisition was performed using a top15 collision induced dissociation method. Survey scans were acquired in the Orbitrap (300-1500 m/z) with a resolution of 60,000 at m/z = 400 using a target value of 106 (maximum fill time 100 ms). The most intense ions with a charge of ≥ 2+ were isolated and fragmented in the linear ion trap (target value 104, maximum fill time 100 ms) using 35 % normalized collision energy. Fragmented ions were excluded from fragmentation for 10 seconds. The lock mass 371.101236 m/z was used for internal calibration. For the large-scale experiment, nanoHPLC-ESI-MS/MS was performed with the following changes: fraction 1 was dissolved in 100 µL 0.1 % TFA and only 1 % was analyzed, all other fractions were dissolved in 32 µl and 50 % was analyzed. LC-MS was done using a binary gradient of 3-35 % B with the following lengths: fractions 1 and 4-18 in 130 min, fractions 2+3 in 185 min and fractions 20+21 in 65 min.

DATABASE SEARCH AND PHOSPHORYLATION SITE DETERMINATION Raw data were processed and searched using Mascot v2.4.1 (Matrix science, London, UK) implemented in Proteome Discoverer v1.4.0 (Thermo Scientific) against the Uniprot human


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database (www.uniprot.org, 2012-07-30, 20,232 target entries) with trypsin as protease. The mass error tolerances were 10 ppm and 0.5 Da for precursor and fragment ions, respectively. Carbamidomethyl

on

cysteine

was

set

as

fixed

modification,

phosphorylation

of

serine/threonine/tyrosine, acetylation of protein N-termini and oxidation of methionine as variable modifications. Resulting matches were filtered for high confidence (corresponding to ≤ 1 % false discovery rate for peptide spectrum matches) and only search engine rank 1 matches were considered. Phosphorylation site localization was done using phosphoRS v3.128, and only peptides with a phosphorylation site probability ≥ 90 % for all sites were considered, unless otherwise stated. All PSMs were grouped to unique, non-redundant peptides and all detected phosphorylation sites were assigned to the respective proteins. We used in-house build VBAand R-scripts to calculate isoelectrical points29, sequence lengths and amino acid compositions. Peptides were considered as non-redundant if they differed either in amino acid sequence, in phosphorylation state or in phosphorylation pattern (at a 90 % phosphoRS confidence level). All identified and confident phosphopeptides are listed in the supporting files I-III. All raw files and search result files (pep.xml) were submitted to ProteomeXchange via the PRIDE database. The data is currently private and can be accessed via: http://tinyurl.com/q2jp8qg, username: [email protected], Password: YEkhzpQq

RESULTS SPE-TESTS To optimize phosphopeptide identification in ERLIC approaches, we used four different ERLIC fractions (0, 20, 60, 95 % ERLIC mobile phase B) to benchmark RP-, HILIC-, Hypercarb- and SCX-SPE for final sample clean-up before LC-MS. The SPE types were compared with respect to phosphopeptide IDs, the ID-based coefficient of variation (CV = standard deviation divided by mean) and compatibility with LC-MS. For RP-, HILIC- and Hypercarb-SPE, we loaded the samples, followed by washing and elution. For SCX-SPE, we used the flow-through for LC-MSanalysis since phosphorylated peptides were expected to be not retained or only weakly retained30,31. To verify this assumption we eluted retained peptides from the SCX-material using SCX buffer B, desalted the obtained samples using RP followed by LC-MS analysis. HILIC and Hypercarb showed the lowest phosphopeptide IDs, and poor reproducibility (figure 2A) and especially with Hypercarb-SPE we observed ≥ 100 % CV for three out of four fractions.


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Notably, SPE-tests of the replicates 1+2 were performed at different time points, whereas the replicates 3+4 were processed in parallel for all 4 SPE types. However, poor reproducibility was observed for HILIC and Hypercarb, independent of parallel or non-parallel processing (figure S1). In contrast, RP and SCX performed best with respect to phosphopeptide identification and CVs ≤ 20 %. To determine the most efficient SPE type, depending on the ERLIC mobile phase composition, we directly compared RP- and SCX-SPE for an entire 7-fraction ERLIC run (figure 2B, 2C). Overall, RP performed slightly better with 2,189 and 2,057 unique phosphopeptides compared to SCX with 1,745 and 1,951 phosphopeptides for replicate 1 and 2, respectively. In terms of reproducibility, both methods performed similarly with 67 % and 68 % overlap between replicates. Combining the results of RP- and SCX-SPE, we identified 3230 unique and confident phosphopeptides with an overlap of 47 %, demonstrating complementarity for the recovery of phosphopeptides.


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FIGURE 2. Comparison of four SPE types (RP, HILIC, Hypercarb and SCX) for phosphopeptide recovery from selected ERLIC fractions (A). The most promising SPE types, RP and SCX, were compared in an entire ERLIC run of seven fractions with respect to phosphopeptide identification (B) and reproducibility (C). Using SCX-SPE, the vast majority of phosphopeptides were identified in the SCX flow-through (SCX-FT), whereas non-phosphorylated peptides were retained on the phase (D).

In all SPE-tests, SCX performed better for the early fractions 1 and 2, whereas RP seemed more beneficial for the later fractions 4-7 (figure 2A, 2B). Notably, the higher CVs of the fractions 5-7 made the determination of the more suitable SPE type difficult (figure 2C). However, RP was clearly more convenient with respect to costs and compatibility to LC-MS analysis. In contrast SCX-SPE was difficult in processing, with high backpressure when processing the later fractions (>60 % ERLIC B). Additionally, the employed SCX SpinTips demonstrated a clear tendency to


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co-enrich polymers (figure S-2). However, phosphorylation state analysis revealed a clear tendency of SCX to favor purification of lower charged phosphopeptides (figure S-3C). Since the majority of lower charged phosphopeptides were detected in the early fractions, higher phosphopeptide percentages were observed in the fractions 2-4 when using SCX-SPE (figure S3B). Especially for early fractions (e.g. fraction 2), where phosphorylated and nonphosphorylated peptides co-elute, SCX allows the depletion of the latter species that mostly remained on the SCX phase, as revealed by LC-MS analysis of a subsequent high-salt elution step. In contrast, ~80% of all identified phosphopeptides were in the SCX flow-through (figure 2D). Notably, this distribution is directly affected by digestion efficiency and therefore suboptimal digestion conditions can promote the presence of missed clevages, thus hampering the impact of this SCX-based clean-up. In summary, SCX demonstrated enhanced phosphopeptide identification when used for early fractions (0 to 20 % ERLIC buffer B), whereas RP-SPE demonstrated to be more favorable for the later fractions. The achieved results were used to design a 21-fraction large-scale ERLIC-SCX/RP-LC-MS experiment

for

maximal

phosphopeptide

identification,

reproducibility

and

LC-MS

compatibility.

ERLIC FOR HIGHLY SENSITIVE, LARGE-SCALE PHOSPHOPROTEOMICS To explore the sensitivity of ERLIC-SCX/RP-LC-MS in a large-scale experiment (figure 1) we used only 100 µg of tryptic HeLa peptides. 21 fractions were collected in a 30-minute ERLIC run (figure 3A). Fractions 1-9 were cleaned with SCX-, fractions 10-21 with RP-SPE. 50 % of each fraction was subjected to LC-MS (but only 1 % of fraction 1, due to the huge excess of unphosphorylated peptides) and measured in 45 h of total LC-MS analysis time per replicate. As depicted in figure 3B and 3C, phosphorylated peptides were successfully retained. The nonphosphorylated peptides were mainly identified in the fractions 1+2, the majority of singly phosphorylated

peptides

was

identified

in

the

fractions

2-10,

followed

by

the

multiphosphorylated peptides in the later fractions 8-18. Calculation of ID-based overlaps for corresponding fractions of two replicates revealed lower reproducibility for multiphosphorylated peptides and for later fractions 15-20 (figure S-4).


11


1500

ERLIC chromatogram

100% B

500

Replicate 2 Replicate 1 100% A

Blank

0

Absorption @ 214 nm

A

0

10

20

30

40

RT (min)

5. 5%

0. 7%

15 .6 % 10 .5 %

27 %

81 .5 % 80 .5 % 70 .9 % 78 .3 % 86 .8 %

67 %

53 .7 %

4000

78 .7 % 85 .4 % 91 .5 % 79 .5 % 69 .8 % 46 .7 % 28 .7 %

phosphorylated non phosphorylated

22 .5 %

8000

0. 1%

Distribution of peptides in ERLIC

F20

F21

0

# unique peptides

B

F1

F2

F3

F4

F5

F6

F7

F8

F9

F10

F11

F12

F13

F14

F15

F16

F17

F18

F19

Distribution of phosphopeptides @ 90% confidence (phosphoRS) singly phosphorylated multiphosphorylated total phosphopeptides

0

500

1500

C # unique phosphopeptides

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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5

10

15

20

Fraction

FIGURE 3. A 21-fraction ERLIC-SCX/RP-LC-MS experiment with 100 µg digested HeLa protein. Depicted are the UV traces of the ERLIC-fractionation (A), the numbers of identified unique peptides and phosphopeptides (phosphopeptide portions are given in percent) (B) and the distribution of unique phosphopeptides (C)

In total, we identified 7,579 (replicate 1) and 8,087 (replicate 2) unique phosphopeptides (phosphoRS ≥ 90 %) of which ~30 % were doubly and ~2 % more than doubly phosphorylated. With these peptides, we could assign 7,291 (replicate 1) and 7,715 (replicate 2) confident and non-redundant protein phosphorylation sites. Taken together, 8,998 could be assigned in two replicates with an overlap of 66.8 % (figure 4A). All phosphorylation site identifications derived from 7,546 different amino acid sequences of 3,013 different phosphoproteins with an average of 3 sites per protein and a maximum of 135 (figure S-5).


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According to the phosphoRS site localization algorithm28, we found 4,922 highly confident phosphorylation sites (all sites at 100 % probability), 4,076 confident sites (90- < 100 % probability) and 980 with lower confidence (75- < 90 % probability). Figure 4B depicts the phosphopeptide identification as a function of phosphoRS probability to give an idea how quality and quantity is connected in a large scale experiment. Supporting table S-1 gives a detailed overview of the results of our ERLIC-SCX/RP-LC-MS strategy. In total we identified 75 phosphorylation sites per µg sample and 167 phosphorylation sites per hour LC-MS time. The amino acid stoichiometry was 83.3 % phosphoserine, 14.6 % phosphothreonine and 2.0 % phosphotyrosine.

FIGURE 4. Identified phosphorylation sites (phosphoRS ≥ 90 %) in a duplicate ERLICexperiment using 100 µg HeLa peptides (A) and phosphopeptide identification (unique only) as a function of phosphoRS probability threshold (B).

DYNAMIC RANGE AND COMPLEMENTARITY OF ERLIC-SCX/RP


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To explore the accessible dynamic range of our approach, we calculated the abundance distribution of the identified phosphoproteins with respect to copy numbers per cell, based on the quantitative HeLa proteome published by Nagaraj et al.32. Furthermore, we made a comparison of our results with the recently published 2D-Ti4+-IMAC-HILIC strategy by Zhou et al.9, who used 250 µg HeLa peptides for phosphopeptide enrichment. 2,834 of our proteins and 2,812 proteins of the Zhou dataset could be assigned with copy numbers. As depicted in figure 5A, both strategies provide an unbiased coverage of the entire dynamic range of proteins from 108 down to a few copies per cell. For further comparison of our results with state-of-the-art enrichment strategies, we calculated the overlap of our phosphopeptide sequences and the sequences of the entire Zhou dataset (of HeLa cells). This dataset contains 15,768 unique phosphopeptide sequences (after removal of redundant entries) as a result of various IMAC-based strategies. Surprisingly, we could not find 2,960 (~40 %) of our 7,546 sequences. Subsequent calculations of the physicochemical properties revealed that the sequences exclusively found with ERLIC have an average length of 22 amino acids, whereas the 11,182 sequences exclusively present in the Zhou dataset are considerably shorter, with 15 amino acids in average (figure 5B). Notably, this is not accompanied by a higher missed cleavages rate, since the ERLIC subset has an average of 0.4 and the Zhou subset an average of 0.6 missed cleavages per sequence. Besides length, sequences exclusively found with ERLIC are significantly more acidic, with an average pI of 5.1 and 4.1 acidic amino acids (glutamic or aspartic acid) per sequence, whereas the sequences exclusively present in the Zhou subset have an average pI of 7.1 and 2.1 acidic amino acids per sequence (figure 5C). Thus, ERLIC-SCX/RP enriches phosphopeptides with considerably different physicochemical properties than IMAC-based techniques. The tendency to enrich acidic sequences is further reflected by the higher share of phosphopeptide sequences without a C-terminal basic amino acid (lysine or arginine). With the utilized search parameters (trypsin, cleavage at the C-terminus of lysine or arginine), such sequences can only derive from protein C-termini. Using ERLIC-SCX/RP, we found 372 sequences (4.9 % of total) without C-terminal lysine or arginine. In contrast, the Zhou dataset contains only 269 such sequences (1.7 % of the total), of which 127 sequences (25 %) are shared between the datasets. Thus, ERLIC-SCX/RP has an ability to enrich C-terminal phosphopeptides, reflecting its tendency to enrich more acidic sequences.


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A

Dynamic range / Abundance distribution

0.4 0.0

0.2

Density

0.6

HeLa Proteome - Nagaraj et al 2011 Phosphoproteome - Zhou 2013 - IMAC-HILIC Phosphoproteome - ERLIC-SCX/RP

8

6

4

2

0

Log10 (copies per cell)

Length distribution only in ERLIC only in Zhou et al 2013 Overlap

0.08

Mean length

0.04

ERLIC-SCX/RP: 21.6 Zhou et al 2013: 14.8

0.00

Density

B

0

10

20

30

40

length (amino acids)

C

pI distribution only in ERLIC only in Zhou et al 2013 Overlap

ERLIC-SCX/RP: 5.1 Zhou et al 2013: 7.1

0.10

Density

0.20

Mean pI

0.00

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0

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12

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theoretical pI

FIGURE 5. Comparison of ERLIC-SCX/RP-LC-MS and the recently published 2D strategy of Ti4+-IMAC-HILIC (Zhou et al.9). The protein abundance distribution (A) demonstrates accessibility of the entire dynamic range of proteins in a cell (based on estimated copy numbers by Nagaraj et al. 201132). Peptides exclusively found by ERLIC (2,960 sequences) show a considerably different distribution with respect to pI (B) and length (C) compared to the sequences of the Zhou dataset not found by ERLIC (11,182 sequences). Values and dashed vertical lines give the mean values of sequences exclusively found in one of the datasets.

DISCUSSION We have developed a sensitive, highly efficient and easy-to-implement phosphopeptide enrichment method, based on optimized ERLIC fractionation, well-chosen SPE and LC-MS/MS analysis.

SPE-TESTS In the SPE-tests, we compared different SPE types for phosphopeptide purification after ERLIC. Hypercarb and HILIC demonstrated low phosphopeptide recovery with respect to identification rates and CVs. Although HPLC-based HILIC has often been used to fractionate phosphopeptides


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after IMAC or MOAC11,12,33,34, our ERLIC-HILIC-SPE approach was not promising. This is consistent with Chen et al., who found HILIC to be inferior to SCX for phosphopeptide identification35. In accordance with the results of the Dengjel lab31,27, we found ERLIC-SCX to be an efficient combination, especially for early fractions (≤ 20 % ERLIC mobile phase B) where the majority of non-phosphorylated peptides elute (figure 2, 3, S-3A). In these fractions, SCX can provide further enrichment of the lower-charged phosphopeptides, resulting in higher phosphopeptide percentages (figure 2D, S-3). Unfortunately, in our hands the employed SCX tips co-enriched polymers (figure S-2), that might reduce the HPLC column’s life time and should be removed by additional wash steps of the LC-MS system after measuring ERLIC-SCXsamples. In contrast, the gold standard for peptide purification, RP with C18 material in presence of an ion-pairing reagent (TFA), showed the best overall results and was found to be optimal in costs, handling and compatibility with LC-MS. We clearly recommend RP-SPE if all fractions are to be purified simultaneously using only one SPE material. The observed complementarity of RP- and SCX-SPE can be exploited further to enhance the number of identifications by ~50 %. Thus, more comprehensive results can be achieved without the necessity of employing other enrichment strategies, using additional LC-MS time and using more sample material. In all experiments, the later ERLIC fractions were found to be less reproducible (figure 2, S-1, S4). Beside difficulties in processing, identification in these fractions is hampered by the low abundance of the multiphosphorylated peptides in these fractions, their lower ionization efficiency (a matter of controversy)36,37 and their lower chances of passing our strict phosphoRS site validation (each site had to pass the 90% probability)38. However, EDTA as a sample additive (or column wash solution)39 might facilitate a more reproducible detection of multiphosphorylated peptides in the later fractions. In contrast, the early ERLIC fractions (CV < 30% for the fraction 2-5, figure 2C), where the vast majority of phosphorylated peptides (~90 %) have been identified, showed a higher level of reproducibility.

ERLIC FOR HIGHLY SENSITIVE, LARGE-SCALE PHOSPHOPROTEOMICS In the large-scale experiment, we aimed to maximize phosphopeptide identifications with a minimum of sample material and LC-MS time by combining ERLIC fractionation with SCXand RP-SPE. With this strategy, we identified ~7500 confident and non-redundant phosphorylation sites in 45 h of LC-MS time, starting with only 100 µg of non-stimulated HeLa


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peptides. With a stoichiometry of 83:15:2 for phosphoserine, phosphothreonine and phosphotyrosine (pTyr), the pTyr share of our experiment was higher than in other ERLIC-based studies. The Dengjel lab26,31 reported pTyr to be around ~0.5 %, and Gan et al.23 around ~1 %. The higher share of these low-abundant phosphopeptide species34,40 further demonstrates the sensitivity of our system. Since pTyr peptides do not exhibit dominant neutral-losses in CID41, we expected pTyr to have higher site localization probabilities, but when setting the phosphoRS site probability threshold to 100 % (instead of ≥ 90 %) the relative percentage of pTyr decreased significantly to 1.2 %. (data not shown). This might be either explained by a higher false positive rate for pTyr at lower probability thresholds or by lower spectra quality as a consequence of their sub-stoichiometric nature42. Consistent with other ERLIC-based studies, we observed separation of non-phosphorylated, singly phosphorylated and multiphosphorylated peptides (figure 3). Notably, we identified > 1,000 singly phosphorylated peptides in each of the early fractions 2-5, reflecting an excellent separation from the non-phosphorylated peptides in the first minutes of the ERLIC run. This was achieved by minimizing the dead and injection volumes of the HPLC in order to prevent coelution of singly phosphorylated and the vast majority of non-phosphorylated peptides. We recommend careful monitoring of the first fractions in ERLIC experiments in order to avoid quenching effects by the presence of co-eluted non-phosphorylated peptides. The narrow retention time windows of non-phosphorylated and singly phosphorylated peptides might account for reports that ERLIC enriches high percentages of multiphosphorylated peptides23. In an ERLIC-based enrichment, insufficient resolution in the first minutes will lead to a substantial loss of singly phosphorylated species and biases the percentages toward the multiphosphorylated ones.

DYNAMIC RANGE AND COMPLEMENTARITY Our comparison with the 2D Ti4+-IMAC-HILIC-strategy from Zhou et al. demonstrated that the accessible dynamic range of ERLIC-SCX/RP-LC-MS is comparable to other state-of-the-art strategies and provides coverage of the entire dynamic range of proteins in a cell (figure 5A). Our phosphopeptide set was appreciably complementary with the Zhou dataset, as a result of ERLIC’s tendency to enrich more acidic sequences (pI 5.1 vs 7.1, figure 5B), an observation


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consistent with Gan et al.23, and the tendency to enrich longer phosphopeptides (21 vs 14 amino acids in length, 5C). Thus, ERLIC offers the possibility to explore phosphoproteome subsets that are not yet covered by large scale IMAC-based approaches, unless materials such as Ga3+ are used43. As a consequence, our dataset includes a high share of C-terminal phosphopeptides (327 out of 3,013 total phosphoproteins), suggesting that ERLIC may be useful for studying signaling events in C-terminal cytoplasmic domains. Thus, ERLIC might make a contribution to the emerging field of C-terminomics44.

BENCHMARKING ERLIC-SPE-LC-MS Three years ago, most large-scale phosphopeptide enrichment strategies were in the range of 0.1 to 10 phosphorylation sites per µg starting material of a cell lysate (summarized by Ficarro et al. 20116). A very sensitive strategy using MOAC-IMAC-HILIC (named TiSH) was published in 201212 and was reported to enable the identification of 22 phosphopeptides per µg (6600 IDs / 300 µg). The most sensitive large-scale phosphoproteomics approaches to date are in the range of 10-50 IDs per µg. The Zhou dataset9 is a result of IMAC based 1D-, 2D- and 3D strategies (tested with HeLa) with efficiencies between 5 and 31 phosphorylation sites per µg. The continuous improvement in phosphoproteomics is a combination of continuous improving sample preparation45,46, LC-MS instrumentation47 and data interpretation48. With ~75 sites per µg starting material, ERLIC-SCX/RP-LC-MS is now among the most sensitive large-scale phosphoproteomics strategies to date. The identification might even be extended by the use of state-of-the-art MS instruments such as the Orbitrap Fusion Tribrid. Nevertheless, our LTQ Orbitrap Velos Pro was completely sufficient to demonstrate the excellent sensitivity of our method.

CONCLUSION ERLIC-SCX/RP-LC-MS is a highly sensitive strategy for protein phosphorylation analysis, even with limited sample amounts and unstimulated cells. It is an excellent stand-alone strategy for µg-scale phosphoproteomics with a robust workflow and potential for fully automatized sample preparation. The complementarity to IMAC-based strategies can be exploited to explore new phosphoproteome subsets and might complement large-scale phosphoproteomics approaches. In


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summary, the strategy has the power to become a phosphoproteomics key method in biological, biomedical and clinical research.

SUPPORTING INFORMATION AVAILABLE Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org. AUTHOR INFORMATION Corresponding author Albert Sickmann, Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Otto-HahnStraße 6b, 44227 Dortmund, Germany Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Funding Sources The financial support by the Ministerium für Innovation, Wissenschaft und Forschung des Landes Nordrhein-Westfalen is gratefully acknowledged. ACKNOWLEDGMENT We thank our colleagues from ISAS, especially Fiorella Solari, Clarissa Dickhut and Oliver Pagel for valuable discussion and further Ingo Feldmann and Laxmikanth Kollipara for support in LC-MS analysis. We further would like to thank Lisa Weilnboeck and Christian Huber from the University of Salzburg for valuable discussions.


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ABBREVIATIONS ACN, acetonitrile, ID, identification; IEC, ion exchange chromatography, ERLIC, electrostatic repulsion-hydrophilic interaction chromatography; FA, formic acid; HILIC, hydrophilic interaction chromatography; IMAC, immobilized metal ion affinity chromatography; MOAC, metal oxide affinity chromatography; MS/MS, tandem mass spectrum; pI, isoelectrical point PSM, peptide spectrum match; RP, reversed phase; SCX, strong cation exchange; SPE, solid phase extraction; TFA, trifluoroacetic acid; WAX, weak anion exchange; REFERENCES 1. J. Dengjel, V. Akimov, J. V. Olsen, J. Bunkenborg, M. Mann, B. Blagoev, J. S. Andersen, Nature biotechnology 2007, 25. 566-8, DOI: 10.1038/nbt1301. 2. D. K. Schweppe, J. R. Rigas, S. A. Gerber, Journal of proteomics 2013, 91. 286-96, DOI: 10.1016/j.jprot.2013.07.023. 3. P. Palmowski, A. Rogowska-Wrzesinska, J. Williamson, H. C. Beck, J. D. Mikkelsen, H. H. Hansen, O. N. Jensen, Journal of proteome research 2014. DOI: 10.1021/pr4010794. 4. F. V. Winck, M. Belloni, B. A. Pauletti, L. Zanella Jde, R. R. Domingues, N. E. Sherman, A. F. Paes Leme, Journal of proteomics 2014, 96. 67-81, DOI: 10.1016/j.jprot.2013.10.039. 5. S. Loroch, C. Dickhut, R. P. Zahedi, A. Sickmann, Electrophoresis 2013, 34. 1483-92, DOI: 10.1002/elps.201200710. 6. S. B. Ficarro, Y. Zhang, M. J. Carrasco-Alfonso, B. Garg, G. Adelmant, J. T. Webber, C. J. Luckey, J. A. Marto, Molecular & cellular proteomics : MCP 2011, 10. O111 011064, DOI: 10.1074/mcp.O111.011064. 7. S. B. Ficarro, M. L. McCleland, P. T. Stukenberg, D. J. Burke, M. M. Ross, J. Shabanowitz, D. F. Hunt, F. M. White, Nat Biotechnol 2002, 20. 301-5. 8. L. M. Brill, A. R. Salomon, S. B. Ficarro, M. Mukherji, M. Stettler-Gill, E. C. Peters, Analytical chemistry 2004, 76. 2763-72, DOI: 10.1021/ac035352d. 9. H. Zhou, S. Di Palma, C. Preisinger, M. Peng, A. N. Polat, A. J. Heck, S. Mohammed, Journal of proteome research 2013, 12. 260-71, DOI: 10.1021/pr300630k. 10. M. W. Pinkse, S. Mohammed, J. W. Gouw, B. van Breukelen, H. R. Vos, A. J. Heck, Journal of proteome research 2008, 7. 687-97, DOI: 10.1021/pr700605z. 11. K. Engholm-Keller, T. A. Hansen, G. Palmisano, M. R. Larsen, Journal of proteome research 2011, 10. 5383-97, DOI: 10.1021/pr200641x. 12. K. Engholm-Keller, P. Birck, J. Storling, F. Pociot, T. Mandrup-Poulsen, M. R. Larsen, Journal of proteomics 2012, 75. 5749-61, DOI: 10.1016/j.jprot.2012.08.007. 13. N. Dephoure, C. Zhou, J. Villen, S. A. Beausoleil, C. E. Bakalarski, S. J. Elledge, S. P. Gygi, Proceedings of the National Academy of Sciences of the United States of America 2008, 105. 10762-7, DOI: 10.1073/pnas.0805139105.


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47x26mm (300 x 300 DPI)


Highly Sensitive Phosphoproteomics by Tailoring Solid-Phase

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