TiO2 with Tandem Fractionation (TAFT): An Approach for Rapid, Deep

Nov 8, 2017 - Graduate School, Anhui Medical University, Hefei 230032, China ... HeLa and HepG2.2.15 cells to characterize the capability of TAFT ...
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TiO2 with Tandem Fractionation (TAFT): An Approach for Rapid, Deep, Reproducible, and High-Throughput Phosphoproteome Analysis Liangliang Ren,†,‡ Chaoying Li,†,‡ Wenli Shao,†,‡,§ Weiran Lin,†,‡ Fuchu He,*,†,‡ and Ying Jiang*,†,‡

J. Proteome Res. 2018.17:710-721. Downloaded from pubs.acs.org by EASTERN KENTUCKY UNIV on 01/16/19. For personal use only.



State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China ‡ Beijing Proteome Research Center, Beijing 102206, China § Graduate School, Anhui Medical University, Hefei 230032, China S Supporting Information *

ABSTRACT: Mass-spectrometry-based phosphoproteomic workflows traditionally require efficient prefractionation and enrichment of phosphopeptides to gain an in-depth, global, and unbiased systematic investigation of phosphoproteome. Here we present TiO2 with tandem fractionation (TAFT) approach, which combines titanium dioxide (TiO2) enrichment and tandem high-pH reverse-phase (HpRP) for phosphoproteome analysis in a high-throughput manner; the entire workflow takes only 3 h to complete without laborious phosphopeptide preparation. We applied this approach to HeLa and HepG2.2.15 cells to characterize the capability of TAFT approach, which enables deep identification and quantification of more than 14 000 unique phosphopeptides in a single sample from 1 mg of protein as starting materials in 91% selectivity and high quantitative reproducibility (average Pearson correlation is 0.90 between biological replicates). More generally, the presented approach enables rapid, deep, and reproducible phosphoproteome analysis in a high-throughput manner with low cost, which should facilitate our understanding of signaling networks in a wide range of biological systems or the process of clinical applications. KEYWORDS: TAFT, HpRP, phosphopeptide, phosphoproteome, titanium dioxide, enrichment, chromatography, fractionation, label-free, quantification



INTRODUCTION Protein phosphorylation is one of the most important posttranslational modifications (PTMs) for signaling in cellular networks, which is essential for the regulation of a large variety of biological events, such as proliferation, adhesion, apoptosis, and cell differentiation. Aberrant protein phosphorylation is believed to get involved in numerous diseases, especially tumors.1,2 Protein phosphorylation has been observed to affect at least three-quarters of a proteome in a recent study.3 Great technological progress in mass spectrometry (MS)-based proteomics has facilitated the investigation of nearly the whole proteome encoded by the human genome4,5 and thousands of PTMs in complex biological samples.3,6,7 A detailed measurement of protein phosphorylation in cells at any given time is critical to gain a global understanding of cellular signal transduction on the molecular level. However, the complexity of phosphoproteome, the highly dynamic nature, and the low stoichiometry of phosphorylation is still a serious technical challenge.8,9 Therefore, prefractionation and selective enrichment strategy of phosphopeptides are required for an indepth phosphoproteome analysis.10−12 © 2017 American Chemical Society

Fractionation of peptides with low-pH strong cation exchange (SCX) chromatography, which generally combines with IMAC/TiO2 enrichment, has been widely used as one of the most popular strategies in large-scale phosphoproteomics studies.13−19 However, because of the weak binding affinity of some phosphopeptides with the SCX resins, fractionation based on SCX and the following desalting step may lead to sample loss.10 Several chromatographic methods such as hydrophilic interaction chromatography (HILIC),20 electrostatic repulsion−hydrophilic interaction liquid chromatography (ERLIC),21,22 and strong anion exchange (SAX)23 have also been successfully applied to phosphopeptide separation. With the significant methodological advancement in enrichment and fractionation of phosphopeptides and novel developments in MS, it is achievable to identify thousands of unique phosphopeptides in a single experiment with fewer fractions or shorter MS measurement time.24,25 Received: July 23, 2017 Published: November 8, 2017 710

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Figure 1. Workflow of TAFT approach and conventional phosphoproteomics approaches. (A) Overview of workflow for phosphoproteome analysis with TAFT approach. The simple workflow needs only 1 mg of protein of starting materials; phosphopeptide preparation can be finished within 3 h, yielding three fractions from each sample for LC−MS/MS analysis. All samples resulting from the enrichment and fractionation of phosphopeptide were analyzed via LC−MS/MS measurement with a 75 min gradient on an Orbitrap Fusion. The workflow enables rapid quantification of deep phosphoproteome in a high-throughput manner. (B) Workflow of phosphoproteomics analysis with conventional approaches. Conventional phosphoproteomics approaches require large amounts of samples, laborious phosphopeptide preparation procedure, and extensive MS measurement time.

Ruprecht et al. reported a method enriching phosphopeptides using a Fe3+-IMAC in HPLC column format, which allowed the identification of 4000 phosphopeptides from 1 mg peptide in 4 h MS measurement and 15 000 phosphopeptides in 48 h of MS measurement for fractionated samples.26 Post et al. also performed Fe3+-IMAC on 200 μg peptides from HeLa cells and identified ∼6000 phosphosites by a 100 min LC−MS/ MS measurement on Q-Exactive Plus.27 Recently, the Ti4+IMAC has been widely used in many laboratories, in combination with a five protease workflow; Heck group reported 37 771 phosphopeptides corresponding 18 430 phosphosites in Jukat T-cells.28 Although significant improvement in MS has been achieved in the past few years, fractionation and enrichment of phosphopeptides are still essential to attain a considerable depth coverage of phosphoproteome. Recently, high-pH reverse-phase (HpRP) has shown great potential for the analysis of phosphopeptides.10,29−32 The high-pH RP system and the following low-pH RP system in line with the mass spectrometer highly improved the orthogonality of 2D-LC separation. However, the conventional phosphopeptide preparation process involving SCX, HILIC, ERLIC, or HpRP in extensive sample fractionation is generally laborious and timeconsuming; the deep coverage of phosphoproteome comes at the cost of significant acquisition time, limited robustness, throughput, and quantitative reproducibility, which also requires large amounts of starting sample. Additionally, the time in phosphopeptide preparation and MS measurement becomes a severe problem when the conventional approaches

are applied to attain in-depth phosphoproteome in large-scale samples. Recently, “postfractionation” methods such as multiIMAC-HLB by Yue and Hummon, Schunter et al.,31,33 TiSH by Engholm-Keller et al.,34 and 2D-Ti4+-IMAC-HILIC by Zhou et al.11 were introduced and resulted in a high number of phosphopeptide identification, which were performed in a relatively simpler manner. However, in general, the elution of phosphopeptides from the TiO2/IMAC beads and fractionation of phosphopeptides were performed in independent procedures in most of these methods. When combining these methods with label-free quantification, the whole eluted phosphopeptides from the TiO 2 /IMAC beads have to undergo frequentative lyophilization, desalting, and fractionation procedures, and thus in most “postfractionation” methods the processing of these procedures may lead to loss of phosphopeptides and impair the robustness in phosphopeptide quantification. What is similar to the conventional methods is the quantitative reproducibility of these methods that challenged the application of them in label-free quantitative phosphoproteome studies.31,33 Many of the studies attempted to relieve the dilemma in the effort and cost in phosphoproteome analysis; however, most of these only partially addressed the issue. Therefore, efficient, simple, and highly reproducible approaches are needed to simplify the phosphopeptide preparation procedure to shorten the time in both phosphopeptide preparation and MS measurement while yielding high quantitative reproducibility and deep coverage of phosphoproteome in studies. 711

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fractionated with tandem Hp-RP StageTips. TiO2−StageTips and Hp-RP-StageTips (in tandem with TiO2−StageTips for fractionation of phosphopeptides) were prepared as described from the protocol of Rappsilber et al. and stored at room temperature.36 In brief, for both TiO2 StageTips and Hp-RP StageTips a layer of C8 disk (cat. no. 14-386, 3M) was plugged into 200 μL tips. TiO2 beads were preconditioned by suspending in buffer A (0.4% TFA, 80% acetonitrile (ACN)) and dispersed into tubes (5 mg TiO2 beads per tube); the beads were rotated for 1 min and quickly spun down. The supernatants were removed, and 50 μL of buffer B (70% ACN, 5% TFA, 20% lactic acid (cat. no. L6661-100 ML, SigmaAldrich)) was added to the tubes, followed by rotation, centrifugation, and removal of supernatants. The TiO 2 StageTips were preconditioned by the same buffers as TiO2 beads. Similarly, Hp-RP beads (C18 beads) (Durashell RP, cat. no DS930010-0, Agela Technologies) were preconditioned by resuspending in 15% ammonia (cat. no. 013-23355, Wako), and the slurry of the Hp-RP beads was dispersed and transferred to Hp-RP StageTips (1 mg Hp-RP beads per tip), washed, and preconditioned with 50 μL of 15% ammonia. The TiO2 beads, TiO2 StageTips, and Hp-RP StageTips (stuffed with C18 beads) were stored at 4 °C. The protein digests were dissolved into tubes containing 5 mg TiO2 beads with 500 μL of buffer B, which were then incubated with gentle rotation at room temperature (30 min at 20 rpm). Subsequently, the TiO2 beads were spun down at 800g for 3 min, and the supernatants were transferred to fresh tubes and incubated with a second round of TiO2 beads as described above. The two round of incubated beads were mixed and resuspended with 200 μL of buffer B, transferred onto the TiO2 StageTips coupled with adapters (cat. no. 5010-21514, GL Sciences), and centrifuged at 400g for 5 min. The beads were washed with 150 μL of buffer B four times, followed by washing with 150 μL of buffer C (0.5% TFA, 30% ACN) at 400g for 5 min and twice additional washing with 100 μL of buffer A with centrifugation at 350g until no liquid remained on the StageTips. All processing was performed via centrifugation at room temperature. The TiO2 StageTips were subsequently transferred and plugged onto the Hp-RP StageTips (which formed the TiO2 with tandem fractionation by Hp-RP (TAFT) StageTips,) to fractionate the phosphopeptides (Figure S1, Figure 1A), and the bound peptides were eluted with six gradients of elution buffer. In brief, phosphopeptides were eluted, respectively, with 100 μL of elution buffer 1 (15% ammonia) at 600g for 5 min, elution buffer 2 (15% ammonia, 2% ACN) at 900g for 5 min, elution buffer 3 (15% ammonia, 5% ACN) at 1100g for 5 min, elution buffer 4 (15% ammonia, 8% ACN) at 1400g for 5 min, elution buffer 5 (15% ammonia, 10% ACN) at 1400g for 5 min, and elution buffer 6 (15% ammonia, 40% ACN) at 1400g for 5 min. The elutions were collected and fractions were combined into three subfractions as follows: fraction 1 with 6, fraction 2 with 4, and fraction 3 with 5. Thus three subfractions of eluted phosphopeptides were collected and instantaneously dried down in a SpeedVac at 45 °C and store at −80 °C.

Here we present TiO2 with tandem fractionation (TAFT) (Figure 1 A), a rapid, robust but simple strategy for deep phosphoproteome analysis with TiO2 enrichment in tandem with fractionation by high-pH RP of phosphopeptides in a StageTip-based chromatography. We applied it to the sample of HeLa and HepG2.2.15 cells to assess the performance of TAFT. By comparing recently published data that were obtained by the widely used phosphoproteomics approaches, data yielded by HpRP-TiO2 approach, and data yielded by TAFT in this study, we further evaluated the capability of TAFT approach in starting materials, time spent on phosphopeptide preparation and MS measurement, phosphoproteome depth, specificity, throughput, qualitative and quantitative reproducibility, and so on.



EXPERIMENTAL SECTION

Protein Preparation and Peptide Extraction

HeLa and HepG2.2.15 cells were grown on plates until confluence in DMEM medium supplemented with 10% FBS, 1% 100 U/mL penicillin, and 100 μg/mL streptomycin at 37 °C in a humidified atmosphere containing 5% CO2. Cell lysates were collected in triple biological replicates. Before harvesting, the medium was removed and cells were washed twice with PBS; then, cells were lysed with lysis buffer containing phosphatase inhibitors (4% SDS, 100 mM Tris/HCl pH 7.6, 0.1 M DTT, 5 mM sodium fluoride, 50 mM β-glycerophosphate, 1 mM sodium orthovanadate, supplemented with HALT protease and phosphatase inhibitor cocktail (Thermo Fisher Scientific, cat. no. 78441)). The lysates were incubated at 95 °C for 4 min and then subjected to ultrasonication to shear DNA. Subsequently, cell debris were removed by centrifugation at 14 000g for 10 min. The protein in lysates was quantified relative to bovine serum albumin (BSA) controls. One milligram of protein lysates from three biological replicates (HeLa cells, HepG2.2.15 cells) was digested with MED-FASP method35 using the 30 kDa Microcon centrifugal filter unit (cat. no. YM-30, Millipore). The proteins were first digested with Trypsin (sequencing grade, Promega) at a ratio of 1:100 overnight (37 °C). Subsequently, the filter units were centrifuged at 14 000g for 10 min, and the peptide digests was collected into a fresh tube. The digestions were quenched by lowering pH ∼2 with trifluoroacetic acid (TFA), and peptides were dried in a SpeedVac centrifuge at 45 °C and stored at −80 °C. Following the first digestion, trypsin at a ratio of 1:100 was added to the filter units as a second digestion and incubated at 37 °C for 6 h. Hereafter, the peptides were collected by centrifugation, followed by two washes with 100 μL of water, and collected by centrifugation. Trypsin digestion was quenched by acidification with TFA. The collected peptides were combined with the peptides from first digestion and dried in a SpeedVac centrifuge at 45 °C and stored at −80 °C for further use. The study was approved by the institute research ethics committee at the Beijing Institute of Radiation Medicine. Mouse liver was surgically dissected from male mouse (C57BL6, 8 weeks old) and immediately transferred to liquid nitrogen and ground with liquid nitrogen. Thirty mg liver tissue was used, and the protein extraction and protein digestion were performed with the same procedure as described above.

Phosphopeptide Fractionation and Enrichment with HpRP-TiO2 Workflow

Peptides extracted from 2 mg protein were separated by highpH chromatographic separation strategy (HpRP). The HpRP chromatography gradient was adjusted from Mertins et al.32 to generate eight subfractions per sample. Peptides were

Phosphopeptide Enrichment and Fractionation by TAFT

The phosphopeptides were enriched using titanium dioxide (TiO2) (cat. no. 5020-75010, GL Sciences) beads and 712

DOI: 10.1021/acs.jproteome.7b00520 J. Proteome Res. 2018, 17, 710−721

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reconstituted in 2% ACN solution at pH 10 (pH was adjusted with ammonia). In brief, HpRP chromatography was performed using an Agela Durasbell C18 column (150 Å, 5 μm, 4.6 × 250 mm) on a RIGOL L-3000 HPLC instrument. Solvent A (2% ACN, pH 10, adjusted with ammonia solution) and solvent B (98% ACN, pH 10, adjusted with ammonia solution) were used to separate peptides based on the hydrophobicity of peptides. The flow rate of peptides separation was set to 1.0 mL/min, 45 °C, and the percentage of solvent B was increased over a nonlinear gradient (0% for 6 min; 0 to 6% for 2.66 min; 6 to 8% for 4.67 min; 8 to 18% for 17 min; 18 to 32% for 17.97 min; 32 to 55% for 5.7 min; 55% for 3 min). The collection of eluted peptides began at the second minute in 1 min (1 mL) fractions; fractions 2 to 14 were merged into two subfractions (2, 3, 6, 7, 10, 11, 14; 4, 5, 8, 9, 12, 13), and fractions from 15 to 60 min were merged into six subfractions (15, 16, 27, 28, 39, 40, 51, 52; 17, 18, 29, 30, 41, 42, 53, 54; etc.). The eight subfractions were transferred into clear tubes and dried in a speedvac, then subjected to phosphopeptide enrichment. The phosphopeptide enrichment in each subfraction was performed by the same procedure described in TAFT, except for the fractionation procedure that was substituted to twice elution of phosphopeptides by 100 μL of buffer 6 (15% ammonia, 40% ACN).

The MS RAW data were processed with MaxQuant software (version 1.5.1.2)37 with the integrated Andromeda search engine.38 The MS RAW data derived from HeLa and HepG2.2.15 cells by TAFT and the MS RAW data from mouse liver yielded by HpRP-TiO2 approach were searched against a concatenated forward-decoy UniProt human database (v.20140903, containing 89 034 sequences) or mouse database (v.20140903, containing 51 551 sequences). Three data sets from the recently published work yielded by conventional SCXTiO2 and HpRP-TiO2 approaches by Sharma et al.3 and Batth et al.29 were collected in triplicate technical/biological replicates and searched in a single experiment with MaxQuant against the corresponding concatenated forward-decoy UniProt human or mouse database, respectively. A data set from rat liver in recently published work yielded by HILIC-IMAC by Zappacosta et al.39 was collected; the MaxQuant output files together with the data sets mentioned above were used to draw a comparison between the data sets yielded by TAFT. All MS/MS spectra were searched with the following parameters: Cysteine carbamidomethylation was set as fixed modification and protein N-terminus acetylation, methionine oxidation, and phosphorylation (STY) as variable modifications; an initial mass tolerance of 20 ppm and a final mass tolerance of 6 ppm for precursor mass; and a maximum of three allowed missed cleavages. Peptides, proteins, and phosphosites were set to a 1% false discovery rate, the minimum length allowed was six amino acids with a minimum Andromeda score of 40. The match between run (MBR) feature was enabled. The reverse hits and potential contaminant hits were removed for further analysis. Data analysis was performed with Perseus and R software environment. The GRAVY index values were calculated by the GRAVY Calculator (http://www.gravycalculator.de). The theoretical pI values were calculated by the ProMoST tool (http://proteomics.mcw.edu/promost. html).

LC−MS/MS Analysis

All peptides were reconstituted in 5% FA (v/v) and separated on an in-house-made C18 reverse-phase column (15 cm length × 75 μm diameter, Michrom Bioresources, Auburn, CA) with C18 beads (1.9 μm, Michrom Bioresources, Auburn, CA) on an EASY-nano-LC1000 (Thermo Fisher Scientific, San Jose, CA) coupled to Thermo Fisher Orbitrap Fusion or Q-Exactive Orbitrap. Peptides separation of HeLa and HepG2.2.15 cells was achieved using a 75 min gradient (buffer A: 0.1% formic acid (FA) in water, buffer B: 0.1% FA in ACN) at a flow rate of 380 nL/min (0−16 min, 3−10% B, 16−51 min, 10−22% B, 51−66 min, 22−30% B, 66−67 min, 30−95% B, 67−75 min, 95% B), then analyzed by Orbitrap Fusion. The Orbitrap Fusion mass spectrometer (Thermo Fisher) was operated in positive ion mode with ion transfer tube temperature 320 °C. The positive ion spray voltage was 2.0 kV. Full MS survey scan resolution was set to 120 000 with an automatic gain control (AGC) target of 5.0 × 105 for a scan range of 300−1400 m/z and a max injection time of 50 ms. The instrument was run in top speed mode with a cycle time of 3 s. HCD fragmentation performed at normalized collision energy was 32%. MS2 AGC target was set to 5.0 × 103 with a max injection time of 35 ms, and dynamic exclusion was set to 18 s. Phosphopeptides yielded by HpRP-TiO2 were separated using a 78 min gradient (buffer A: 0.1% formic acid (FA) in water, buffer B: 0.1% FA in ACN) at a flow rate of 0.6 μL/min (0−71 min, 5 to 30% B, 71−72 min, 30 to 95% B, 72−72 min, 95% B), then analyzed by Q-Exactive Orbitrap. The MS survey scan was analyzed over a mass range of 300−1400 Da with a resolution of 70 000 at m/z 200. The isolation width was 3 m/z for precursor ion selection. The AGC was set to 3 × 106, and the maximum injection time (MIT) was 60 ms. The MS2 was analyzed using data-dependent mode searching for the 20 most intense ions fragmented in the HCD. For each scan with a resolution of 17 500 at m/z 200, the AGC was set at 5 × 104 and the MIT was 80 ms. The dynamic exclusion was set at 18 s to suppress the repeated detection of the same fragment ion peaks. The relative collision energy for MS2 was set at 27% for HCD.



RESULTS AND DISCUSSION

Rapid Identification and Qualification of Deep Phosphoproteome in HeLa and HepG2.2.15 Cells

Recent advances in technology have been facilitated to characterize tens of thousands of phosphopeptides from an experiment in adequate acquisition time.40 However, conventional phosphoproteomics approaches require laborious phosphopeptide preparation and extensive time in both sample processing and MS measurement to identify a relatively deep phosphoproteome of samples, and the frequentative lyophilization and desalting of samples is a source of sample loss, which weakens both the sensitivity and reproducibility of the approaches (Figure 1B). Aiming to improve the efficiency of phosphopeptide preparation procedure and sensitive identification and quantification of phosphoproteomics for relatively low amounts of samples, we developed the TAFT strategy (Figure 1A). Hence, we first characterized the performance of TAFT strategy by the time spent in phosphopeptides enrichment and fractionation and the capability for deep phosphoproteome analysis. Using 1 mg of protein from HeLa and HepG2.2.15 cells, respectively, the phosphopeptide preparation procedures can be completed within 3 h in a high-throughput manner (Figure 1A, Figure S1). Subsequently, three fractions of phosphopeptides from each sample were analyzed with a 75 min LC−MS/MS measurement. The 713

DOI: 10.1021/acs.jproteome.7b00520 J. Proteome Res. 2018, 17, 710−721

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Figure 2. Phosphoproteome analysis of HeLa and HepG2.2.15 cells. (A) Summary of phosphopeptide preparation time, LC−MS/MS measurement time, the identified and quantified phosphoproteins, phosphopeptides, phosphosites, and enrichment specificity in each sample analysis. (B) Cumulative number of distinct quantified phosphopeptides in HeLa cells from the triple biological replicates. (C) Cumulative number of distinct quantified phosphopeptides in HepG2.2.15 cells from the triple biological replicates. (D) Cumulative number of distinct quantified phosphopeptides in HeLa group and HepG2.2.15 group.

Specificity and Reproducibility of TAFT Techniques

measurement of the single sample only required 14 000 distinct phosphopeptides with corresponding ∼12 000 phosphosites in a sample (Figure 2A). With our TAFT strategy, we successfully identified and quantified 16 731 and 17 241 unique phosphopeptides with corresponding 15 161 and 15 193 phosphosites in HeLa and HepG2.2.15 cells, respectively (Figure 2B,C). In total, this resulted in identification and quantification of ∼20 000 distinct phosphopeptides and corresponding 21 281 phosphosites from 216 045 phospho-PSMs with high quality in the two cell lines (Figure 2D, Figure S2), including 17 634 high-confident phosphorylation events (class I sites, Table S3). The identified phosphopeptides and phosphosites table are provided in Tables S1 and S2, and evaluation of the MS quality is shown in Figure S2. The MS signals of phosphopeptides we detected spanned over five orders of magnitude and produced approximately normally distributed intensities, indicating a considerable sensitivity of this strategy for phosphopeptides with high abundance and low abundance (Figure S2D). Remarkably, 90% were detected in two orders of magnitude (5.74 to 7.70), whereas the 5% with low abundance spanned over 1.7 orders of magnitude, and 5% with high abundance spanned over 1.6 orders of magnitude, demonstrating the capacity of deep coverage of phosphoproteome without compromising time spent on phosphopeptide preparation and measurement.

We then evaluated the specificity of the TAFT technique. As a result, phosphopeptide selectivity exceeded 91% in all cases (Figure 2A), demonstrating that enrichments for phosphopeptides were highly specific. The reproducibility of the TAFT was evaluated through qualitative and quantitative analysis of phosphopeptides from three biological replicates in the HeLa and HepG2.2.15 cells. The depth of phosphoproteome coverage usually comes with the cost of MS measurement time, the throughput, and the capability of reproducibility. On average, the experiment yielded over-identification of 14 000 unique phosphopeptides in each single sample, and the overlap of observed phosphopeptides between biological was significantly high, with >79% found in all triple biological replicates in two cell lines, respectively (Figure 3A). More importantly, the quantitative reproducibility between the different biological replicates is very high. Even with the accumulation of biological variance and workflow variance, the TAFT strategy achieved an average Pearson correlation of 0.90 between biological replicates in each group (Figure 3B), comparable to the correlation observed in technical replicate LC−MS/MS runs.41,42 Given the high reproducibility between biological replicates of samples, we next assessed the reproducibility of each fraction in samples from the biological replicates. As expected, the median correlation of R in corresponding fractions of the replicates in each group is 0.88 (Figure S3), indicating high reproducibility of the fractionation procedure in 714

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Figure 3. High reproducibility and robust fractionation efficiency of TAFT approach. (A) The high overlap in Venn diagrams of quantified phosphopeptides in three biological replicates indicates high qualitative reproducibility of TAFT strategy. (B) Comparison of phosphopeptide intensity for the three biological replicates suggests highly accurate quantitative reproducibility of the TAFT strategy even with the cumulation of workflow variance and biological variance. (C) Average number of distinct phosphopeptides quantified in the three fractions yielded by the TAFT strategy in each sample. (D) PCA analysis of three fractions resulting from TAFT in all samples of HepG2.2.15 group and HeLa group, revealing high efficiency and reliability of phosphopeptides fractionation.

no salt and do not need additional desalting procedures and thus are flexible to the following phosphopeptide enrichment procedure. One factor that strongly contributed to the performance of TAFT is the combination of TiO2 StageTips and HpRP StageTips. After enrichment of phosphopeptides, the nonphosphopeptides were washed away from the TiO2 StageTips; then, the TiO2 StageTips were transferred and plugged onto the HpRP StageTips, which formed the TAFT (combined TiO2−C18 columns) StageTips, and thus the elution and fractionation were performed on the combined TiO2−C18 columns rather than only on the C18 columns. During the procedure in elution and fractionation of phosphopeptides, the phosphopeptides eluted by sequential high-pH elution buffers in different gradient ACN from TiO2 columns were further automatically loaded onto the C18 columns; the flow through was collected in current subfractions and the phosphopeptides that had been loaded onto the C18 columns were further fractionated by following high-pH elution buffers, which were collected in the following subfractions, respectively. The combined TiO2−C18 columns highly contribute to further extend the fractionation topology of chromatography, and together with the following low-pH LC system promoted TAFT to attain a deeper phosphoproteome coverage of samples. To assess the capability of TAFT in details, we made a comprehensive comparison of TAFT to the representative conventional approaches including SCX-TiO2, HpRP-TiO2, HILIC-IMAC, and HpRP-IMAC and recently introduced “postfractionation” methods,3,11,29,33,39,45−47 especially focusing on the work from the past 4 years (2014−2017), in which the data sets were generated by newer Thermo instruments (Q-

the TAFT strategy, which spurred deep phosphoproteome without sacrificing the reproducibility. The robust reproducibility in phosphorylation quantification should be credited in large part to the rapid, simple phosphopeptides preparation without desalting or extensive fractionation. Using the here-presented TAFT strategy, we managed to identify deep phosphoproteome (>15 000 phosphosites in individual cell lines, >21 000 phosphosites in total) in a quantitatively reproducible manner (average R 0.90 between biological replicates). Comparison of TAFT with Conventional Phosphoproteomics Approaches

The conventional methods for phosphoproteome analysis generally include two major steps, the chromatographic fractionation of peptides and the following enrichment of phosphopeptides (Figure 1B). The former step includes the popularly used SCX, HILIC, ERLIC, and HpRP strategies, and IMAC and TiO2 are two most prevalent strategies in the later step.40 Many studies reported impressive depth coverage of phosphoproteome by the conventional approaches in cell lines or animal tissues.3,29,43,44 However, the whole procedure of phosphopeptide preparation is generally laborious and timeconsuming and can hardly be multiplexed processed. Additionally, the frequentative desalting and lyophilization procedure in conventional workflow can lead to sample loss and weaken the reproducibility. Moreover, the MS measurement time in each of these studies becomes a real considerable cost to identify a relatively deep phosphoproteome. HpRP fractionation approach was recently showed superior to SCX that greatly increased the depth coverage of phosphoproteome.29,32,40 The RP fractionated samples contain 715

DOI: 10.1021/acs.jproteome.7b00520 J. Proteome Res. 2018, 17, 710−721

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Table 1. Summary of Phosphopeptides Identification with TAFT and with Conventional Phosphoproteomics Workflowsa study this study this study Zappacosta et al.39 Yue et al.31 Zhou et al.11 Zarei et al.24 Batth et al.29 Batth et al.29 Schunter et al.33 Sharma et al.3 Park et al.45 Minard et al.46 Roumeliotis et al.47

tissue/cell HepG2.2.15 HeLa cells mouse liver rat liver MCF-10A cells HeLa cells HeLa cells NIH/3T3 cells NIH/3T3 cells SW480/SW620 cells HeLa cells stomach cancer tissue 3T3-L1 fibroblasts colorectal cancer cells

phosphopeptide preparation time

MS measurement time

workflow and fractions

starting materials

TAFT/3

1 mg protein

3h

3.8 hFus

HpRP-TiO2/8 HILIC-IMAC/14 multiIMAC-HLB/12 IMAC-HILIC/20 ERLIC-SCX-TiO2/13 HpRP-TiO2/14 SCX-TiO2/14 IMAC/TiO2-HLB/8 SCX-TiO2/9 mRP-IMAC/12 SCX-TiO2/10 HpRP-IMAC/10

2 mg protein 5 mg protein 3 mg protein 125 μg peptide 6 mg protein 2−3 mg protein 2−3 mg protein 3.5 mg protein 6 mg peptide 14 mg protein NA 1 mg protein

>1 day >1 day >1 day >1 day >1 day 1 day >1 day 1 day >1 day >1 day >1 day >1 day

10.4 25.7 14.6 40.0 32.0 18.7 18.7 12.0 24.0 48.0 25.0 20.0

hQE hVP hQE hVelos hXL hQE hQE hQE hQE hQE hQE hFus

phosphopeptides identified per sample

multiplexed sample processing

14 590

yes

11 758 13 132 8969 9066 9952 17 225 5518 4331/6567 19 476 18 846 8201 11 000

no no no no no no no no no no no no

a

MS RAW data of triplicate technical or biological replicates in recently published work were searched with the same parameters against corresponding databases with MaxQuant in this study. The tight thresholds in current MaxQuant version may lead to a reduction in the number of identified phosphopeptides compared with previously reported. For the information of samples not presented in the work, it was annotated with “NA”. The abbreviations of instruments annotated in column “MS Measurement Time” are QE, Q-Exactive; Fus, Orbitrap Fusion; VP, Velos Pro; XL, and LTQ Orbitrap XL.

Exactive and Orbitrap Fusion). We also yielded a data set of mouse liver by HpRP-TiO2 approach; together with recently published data we evaluated the capability of TAFT in workflow procedure, starting materials, time in phosphopeptide preparation and MS measurement, depth of phosphoproteome, throughput and technical replicates reproducibility, and so on (Table 1). Recently published studies adopted conventional phosphoproteomics approaches to achieve deeper phosphoproteome analysis of samples. The depth coverage of these studies generally required at least 1 to 2 days to process phosphopeptide preparation, including extensive fractionation of peptides, frequentative lyophilization and desalting of peptides, and enrichment of phosphopeptides. Even by the recently introduced “postfractionation” methods,3,11,29,33,39,45−47 the whole processing of enrichment, lyophilization, desalting, and fractionation, would take at least a half day in producing fractionated phosphopeptides from peptides (Table 1). Comparably, HpRP-TiO2 approach eliminated the desalting process and shortened the whole procedure to ∼2 days in phosphopeptide preparation. Using the HpRP-TiO2 approach, 2 mg of mouse liver protein was used and generated eight fractions of phosphopeptides, after 10 h of MS measurement per sample, which yielded 11 758 phosphopeptides per sample (Table 1, Table S4). In general, the conventional approaches need a large amount of starting materials, and the phosphopeptide preparation procedures are laborious, time-consuming, and limited in throughput. Moreover, the price of deep phosphoproteome in these studies required considerable MS data acquisition time, from dozens of hours to days3,40,43 (Figure 1 B and Table 1). Relatively, our TAFT approach used less starting materials (1 mg of protein), and the phosphopeptide preparation procedure can be finished in only 3 h, achieving deep coverage of phosphoproteome within only 3.75 h of MS measurement, yielding an average identification of 3800 unique phosphopeptides per MS hour (Table 1). More importantly, because of a simpler and rapid sample processing procedure, the TAFT approach can be performed in a high-throughput manner (Figure S1).

The robustness of phosphoproteomics workflow directly determines the quantification accuracy in phosphoproteome analysis. Thus we next compared the reproducibility of HpRPTiO2 with data generated in this study and data generated by conventional approaches that were adopted in recently published work, including HILIC-IMAC,39 SCX-TiO2,29 and HpRP-TiO 2 29 (Figure S4). As shown in Figure S4, phosphopeptide intensity correlations in data sets generated by conventional phosphoproteomics approaches varied from 0.80 to 0.90 between technical replicates, which became lower between biological replicates in cell line samples, which is in good agreement with the reported data in previous large-scale phosphoproteomic studies.28 Reproducibility of phosphoproteomics approaches is one of the principal challenges in phosphoproteomics studies with label-free quantification strategy.48 In comparison with conventional approaches, the TAFT approach presented a relatively high reproducibility comparable to the correlation observed in technical replicate LC−MS/MS runs.41,42 Moreover, the TAFT approach is flexible with quantitative proteomics technologies such as stable isotope labeling methods, including stable isotope labeling with amino acids cell culture (SILAC), dimethyl labeling, tandem mass tags (TMTs), and isobaric tag for relative and absolute quantification (iTRAQ). Physicochemical Characteristics of Phosphopeptides Identified by TAFT

The fractionation of peptides in TAFT and conventional IMAC or SCX-TiO2 approaches was performed in different processes and pH values, which may lead to preference of phosphopeptides for different characteristics. Thus we compared the HeLa data sets generated by TAFT with the recently published HeLa data sets generated by 2D-Ti4+-IMAC-HILIC strategy11 and SCX-TiO2 strategy.3 To our surprise, only 10.5% of the phosphopeptides generated by TAFT were identified in data set by 2D-Ti4+-IMAC-HILIC. Additionally, when we compared our HeLa data set with the current ultradeep HeLa data sets from Sharma et al.,3 the analysis produced ∼270 LC−MS/MS measurement over 40 days of data acquisition time, identifying 38 229 phosphosites from over 50 000 unique phosphopep716

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Journal of Proteome Research

Figure 4. Comparison of phosphopeptide characteristics in HeLa cells identified by TAFT or by recently published 2D-Ti4+-IMAC-HILIC from Zhou et al.11 and SCX-TiO2 from Sharma et al.3 approaches. (A) Phosphopeptides exclusively identified in HeLa cells by TAFT show a distinct frequency plots of peptide length, GRAVY index, and pI compared with the data set by Zhou et al. and Sharma et al. (B) Percentage of phosphopeptides with different charge states in the whole HeLa data set identified by TAFT, 2D-Ti4+-IMAC-HILIC (Zhou et al.), and SCXTiO2(Sharma et al.) approaches. (C) Percentage of phosphopeptides with different degree of phosphorylation sites identified in the whole HeLa data set by TAFT, 2D-Ti4+-IMAC-HILIC (Zhou et al.), and SCX-TiO2 (Sharma et al.) approaches.

respectively, whereas compared with the two other approaches, phosphopeptides exclusively identified by TAFT showed a distinct advantage for phosphopeptides with pI values 11.0 (highly basic) compared with SCX-TiO2 (Figure 4A). Similarly, alike distributions were found when we further explored the GRAVY and pI values of the whole data sets identified by each approach (Figure S5), suggesting that TAFT identified a proportion of phosphopeptides that may differ in physicochemical characteristics with the two other approaches. In addition, we observed that the charge states of the whole data set identified with TAFT distributed differently with the two other approaches (Figure 4C). All three of the approaches identified a comparable number of phosphopeptides in the 3+ charge state, whereas TAFT identified 19% of phosphopeptides with charge state more than 3 compared with 11% both in 2DTi4+-IMAC-HILIC and SCX-TiO2. Furthermore, for the TAFT multiphosphorylated peptides, 23% of all identified phosphopeptides were multiphosphorylated, whereas only 12 and 15% were multiphosphorylated by the 2D-Ti4+-IMAC-HILIC and SCX-TiO2, respectively. Multisite phosphorylation of proteins is an important and common mechanism, which greatly increases the regulatory potential of proteins and considerably expands the repertoire for combinatorial regulation or finetuned regulation of switch properties, involving a great variety of cellular processes.49−52 Therefore, TAFT is a valuable

tides. At such a depth coverage of HeLa cell, we are surprised to observe that only 58% of the phosphosites generated by TAFT were identified in data sets by Sharma et al., indicating the complementarity of TAFT to the conventional methods. To explore the physicochemical characteristics of the phosphopeptides identified exclusively by each approach, we compared the peptide length, hydropathicity, and pI of the distinct phosphopeptides from each approach (Figure 4A). We observed that the phosphopeptides exclusively found in TAFT were longer than the two other approaches with an average length of 19 amino acids, whereas 16 and 14 in phosphopeptides were exclusively observed by SCX-TiO2 and 2D-Ti4+IMAC-HILIC, respectively. Interestingly, the difference should not be attributed to a higher missed cleavage ratio in TAFT data set; for that the TAFT data set has an average of 0.63 missed cleavages per phosphopeptide versus 0.68 and 0.48 in the data sets of 2D-Ti4+-IMAC-HILIC and SCX-TiO2, respectively. The phosphopeptides unique to TAFT were more hydrophilic than the phosphopeptides unique to 2D-Ti4+-IMACHILIC and even show a slight advantage for the phosphopeptides with GRAVY values lower than −1.5 (moderately hydrophilic) compared with SCX-TiO2 (Figure 4A). The pI values of the unique phosphopeptides identified by each approach showed distinct distribution, and the 2D-Ti4+-IMACHILIC and SCX-TiO 2 showed distinct preference for phosphopeptides with high pI values and low pI values, 717

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Journal of Proteome Research alternative method to the 2D-Ti4+-IMAC-HILIC and SCXTiO2 for studies that mainly focus on multisite phosphorylation of proteins. Because there was no desalting procedure performed during the phosphopeptide preparation by TAFT, which largely contributed to the recovery of hydrophilic phosphopeptides in samples. Desalting during phosphopeptide preparation may lead to sample loss of peptides from 5 to >20%.53,54 In the 2DTi4+-IMAC-HILIC approach, the peptides were desalted after the enrichment, and a considerable amount of hydrophilic phosphopeptides may be washed away during the desalting procedure and that resulted in an identification of less hydrophilic phosphopeptides compared with TAFT. By contrast, in the study by Sharma et al., the flow through of SCX was collected and combined into three subfractions, and each subfraction was analyzed on a 240 min gradient of LC system in tandem with a Q-Exactive instrument, and thus the very hydrophilic phosphopeptides should be retained as much as possible, and the GRAVY index of SCX-TiO2 distributed more similarly to TAFT. Previous works have found that TiO2 was likely to have higher affinity for acidic phosphopeptides compared with IMAC.55−57 We observed that the TAFT and SCX-TiO2 indeed captured more highly acidic phosphopeptides (pI 21 000 phosphosites in total) and high reproducibility in a high-throughput manner within just 3 h. As shown by Zhou et al. and Ferries et al., extending the MS measurement time or optimizing the parameters of MS instruments,67,68 it is probable to attain a deeper phosphoproteome. Compared with conventional phosphoproteomics approaches, TAFT identified distinct phosphopeptides and provided an easy and efficient approach to identify and quantify the phosphoproteome with higher robustness in reproducibility. As a result of rapid, robust, deep phosphoproteome analysis from 1 mg of samples by TAFT strategy, it is feasible to monitor the temporal cellular dynamic changes of phosphoproteome under certain biological contexts to screen novel drug targets and their effectors upon drug treatments, to identify predictive, prognostic, and therapeutic biomarkers in clinical samples, and to characterize patient-specific phosphoproteome portrait in large-scale clinical specimens for individualized treatment in high-throughput manner. We believe that the rapid development in phosphoproteomics will facilitate the progress of application to fundamental as well as clinical researches.

time would lead to deeper identification coverage of phosphoproteome. Zhou et al. managed to identify over 3000 unique phosphopeptides from 125 μg peptide of K562 sample in 60 min of LC−MS/MS analysis on a 35 cm long analytical column with Q-Exactive, while 5600 unique phosphopeptides could be identified in 120 min of LC−MS/MS analysis.67 Thus if provided with sufficient MS measurement time, it is probable to identify more phosphopeptides with TAFT from 1 mg of protein. Additionally, as shown in the Figure 3, the orthogonality of the high-pH RP system and the following low-pH RP system in line with the mass spectrometer highly improved the efficiency of phosphopeptides separation, which led to an average identification and quantification of 9589, 8303, and 8206 unique phosphopeptides in each fraction, respectively (Figure 3C). There were ∼50% of the observed phosphopeptides identified in only one fraction of each sample. Consequently, the three fractions resulted in the identification and quantification of over 14 000 unique phosphopeptides in a single sample, and the number accumulated to ∼17 000 from triple biological replicates for each group (Figure 2B,C). Thus the simple fractionation procedure enhanced the depth of phosphoproteome significantly. This is further exemplified by a principal component analysis of between the fractions of each sample. The PCA analysis of all fractions in the samples yielded distinctive clustering of three clusters in which the individual fractions can be distinguished from the adjacent fractions (Figure 3D), together demonstrating the high efficiency of TAFT in phosphopeptides fractionation to gain a considerable phosphoproteome depth. Recently, high-throughput single-shot approaches were introduced to the community,27,41,42 which were also performed in StageTips-manner. Thus our TAFT is applicable to these approaches to identify deep phosphoproteome with simple fractionation procedure without compromising throughput. Many of studies attempt to mitigate the dilemma in reproducibility, throughput, and depth of phosphoproteome analysis; however, most strategies only partially addressed the problem,40 as the rising demands high-throughput and high reproducibility of phosphoproteomics analysis, especially for large-scale clinically relevant samples. There is an urgent need for strategies with relatively simple and manageable depth and throughput capabilities. As described above, the fractionation with TAFT managed to achieve high reproducibility and considerable phosphoproteomic depth. The entire procedure of phosphopeptide enrichment and fractionation was performed on benchtop centrifuge machine(s) (Figure S1), which allowed us to observe the phosphoproteome of multiple samples at the same time in a high-throughput manner, which can be applied to monitor time-resolved cellular signaling transduction or to characterize patient-specific phosphoproteome portrait in largescale clinical samples. In short, the strategy we described is relatively time-efficient, low-cost, simple, and highly reproducible, which can be applied for large-scale of deep phosphoproteome analysis in a high-throughput manner.



ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jproteome.7b00520. Table S1: Phosphopeptides of HeLa and HepG2.1.15 cells identified in this study. (XLSX) Table S2: Phosphosites of HeLa and HepG2.1.15 cells identified in this study. (XLSX) Table S3: Class I phosphorylation events of HeLa and HepG2.1.15 cells identified in this study.(XLSX) Table S4: Phosphopeptides of mouse liver identified in this study. (XLSX) Figure S1: Materials used for TAFT StageTip preparation. Figure S2: Evaluation and assessment of MS data quality. Figure S3: Reproducibility evaluation of fractionation procedure with TAFT approach. Figure S4: Reproducibility of conventional phosphoproteomics approaches that were adopted in recently published work. Figure S5: Frequency plots showing the distribution of physicochemical characteristics of the all phosphopeptides identified by TAFT or by recently published 2D-Ti4+-IMAC-HILIC from Zhou et al. and SCX-TiO2 from Sharma et al. approaches. (PDF)



AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. Tel: 8610-61770004 *E-mail: [email protected]. Tel: 8610-61777071.



CONCLUSIONS Although great advances in mass-spectrometry-based phosphoproteomics have been achieved in the past decade, the balance among starting material, phosphopeptide preparation time, phosphopeptide enrichment and separation, depth, throughput, and reproducibility of phosphoproteome analysis is still a majority dilemma. Here we assessed the TAFT strategy for

ORCID

Ying Jiang: 0000-0002-4809-0258 Notes

The authors declare no competing financial interest. The RAW data of mass spectrometry consist of 18 RAW files from HeLa and HepG2.2.15 cells and 16 RAW files from 719

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Technical Note

Journal of Proteome Research mouse liver. The RAW files and MaxQuant output files have been deposited in iPROX with the identifier IPX0000939000.

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ACKNOWLEDGMENTS We thank Prof. Xiaohong Qian and Prof. Jun Qin for the critical consultations. This work was partially supported by Chinese State Key Projects for Basic Research (“973 Program”, nos. 2014CBA02001 and 2013CB910502), National Key Research and Development Project (2016YFC0902400, 2017YFC0906603), National Natural Science Foundation of China (81123001 and 81570526), Innovation project (16CXZ027), Chinese State High-tech Program (“863 Program”) (nos. 2012AA020204 and 2014AA020906), the Program of International S&T Cooperation (2014DFB30020, 2014DFB30010), Natural Science Foundation of Beijing (7152036), and Open Project Program of the State Key Laboratory of Proteomics (Academy of Military Medical Sciences, SKLP-O201509).



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DOI: 10.1021/acs.jproteome.7b00520 J. Proteome Res. 2018, 17, 710−721