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

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Technical Note

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., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00520 • Publication Date (Web): 08 Nov 2017 Downloaded from http://pubs.acs.org on November 10, 2017

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Journal of Proteome Research

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∗,†,‡ †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 E-mail: [email protected]; [email protected] Phone: 8610-61770004; 8610-61777071 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 hours 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 one milligram of protein as starting materials in less than 4 hours of

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MS measurement. In total, we identified and quantified 21,281 phosphosites in two cell lines with >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 post-translational 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 have facilitated the investigation of nearly the whole proteome encoded by the human genome, 4,5 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 low stoichiometry of phosphorylation is still a serious technical challenge. 8,9 Therefore, prefractionation and selective enrichment strategy of phosphopeptides are required for an in-depth phosphoproteome analysis. 10–12 Fractionation of peptides with low-pH strong cation exchange (SCX) chromatography, 2


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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, due to 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.

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the significant methodological advancement in enrichment and fractionation of phosphopeptides and novel developments in mass spectrometry, it’s achievable to identify thousands of unique phosphopeptides in a single experiment with fewer fractions and/or shorter MS measurement time. 24,25 Ruprecht et al. reported a method enriching phosphopeptides using a Fe3+ -IMAC in HPLC column format, which allowed identification of 4,000 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 ∼ 6,000 phosphosites by a 100 min LC-MS/MS measurement on QExactive Plus. 27 Recently, the Ti4+ -IMAC has been widely used in many labs, in combination with a 5 protease workflow, Heck group reported 37,771 phosphopeptides corresponding 18,430 phosphosites in Jukat T-cells. 28 Although significant improvement in mass spectrometry 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 time-consuming, the deep coverage of phosphoproteome come 3



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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 of samples. Recently, ‘post-fractionation’ methods such as multi-IMAC-HLB by Yue and Hummon, Schunter et al., 31,33 TiSH by Engholm-Keller et al., 34 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, generally 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 TiO2 /IMAC beads

have to undergo frequentative lyophilization, desalting and fractionation procedures, thus in most ‘post-fractionation’ methods, the processing of these procedures may lead to loss of phosphopeptides and impair the robustness in phosphopeptides quantification. What 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. 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 data recently published that obtained by the widely used phosphoproteomics 4


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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 of phosphopeptide preparation and MS measurement, phosphoproteome depth, specificity, throughput, qualitative and quantitative reproducibility etc.

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 100µg/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, 100mM 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 was removed by centrifugation at 14,000 x g 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 method 35 using the 30kDa 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 14,000 x g 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 store at -80°C. Following the first digestion, trypsin at a ratio of 1:100 were added into the filter units as a second digestion and incubated at 37°C for 6 hours. Hereafter, 5



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the peptides were collected by centrifugation, followed by twice washes with 100 µl 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 store 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 into liquid nitrogen, and ground with liquid nitrogen. 30 mg liver tissue was used and the protein extraction, protein digestion were performed with the same procedure as described above.

Phosphopeptide Enrichment and Fractionation by TAFT The phosphopeptides were enriched using titanium dioxide (TiO2 ) (Cat.No. 5020-75010, GL Sciences) beads and fractionated with tandem Hp-RP StageTips. TiO2 -StageTips , Hp-RPStageTips (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 Briefly, for both TiO2 StageTips and Hp-RP StageTips, a layer of C8 disk (Cat.No. 14-386, 3M) was plug into 200 µl tips. TiO2 beads were preconditioned by suspending in buffer A (0.4% TFA, 80% 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 buffer B (70% ACN, 5% TFA, 20% lactic acid (Cat.No. L6661-100ML, Sigma-Aldrich)) were added into the tubes, followed by rotation, centrifugation, and removal of supernatants. The TiO2 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), the slurry of the Hp-RP beads were dispersed and transferred into Hp-RP StageTips (1 mg Hp-RP beads per tip), washed and preconditioned with 50 µl 15% ammonia. The TiO2 beads, TiO2 StageTips and Hp-RP StageTips (stuffed with C18 beads) were stored at 4 °C. 6


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The protein digests were dissolved into tubes containing 5 mg TiO2 beads with 500 µl 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 800 x g 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 buffer B, transferred onto the TiO2 StageTips coupled with adapters (Cat.No. 5010-21514, GL Sciences), centrifuged at 400 x g for 5 min. The beads were washed with 150 µl buffer B four times, followed by washing with 150µl buffer C (0.5% TFA, 30% ACN) at 400 x g for 5 min, and twice additional washing with 100 µl buffer A with centrifugation at 350 x g until no liquid remained on the StageTips. All processing are 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 1 A), the bound peptides were eluted with 6 gradients of elution buffer. Briefly, Phosphopeptides were eluted respectively with 100 µl elution buffer 1 (15% ammonia) at 600 x g for 5 min, elution buffer 2 (15% ammonia, 2% ACN) at 900 x g for 5 min, elution buffer 3 (15% ammonia, 5% ACN) at 1,100 x g for 5 min, elution buffer 4 (15% ammonia, 8% ACN) at 1,400 x g for 5 min, elution buffer 5 (15% ammonia, 10% ACN) at 1,400 x g for 5 min and elution buffer 6 (15% ammonia, 40% ACN) at 1,400 x g for 5 min. The elutions were collected and fractions were combined into 3 subfractions as follows: fraction 1 with 6, fraction 2 with 4, and fraction 3 with 5. Thus 3 subfractions of eluted phosphopeptides were collected and instantaneously dried down in a SpeedVac at 45°C and store at -80 °C.

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Phosphopeptide Fractionation and Enrichment with HpRP-TiO2 Workflow Peptides extracted from 2 mg protein were separated by high-pH chromatographic separation strategy (HpRP). The HpRP chromatography gradient was adjusted from Mertins et al. 32 to generate 8 subfractions per sample. Peptides were reconstituted in 2% ACN solution, at pH 10 (pH was adjusted with ammonia). Briefly, HpRP chromatography was performed using an Agela Durasbell C18 column (150 Å, 5µm, 4.6×250 mm) on a RIGOL L-3000 HPLC instrument. Solvent A (2% acetonitrile (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℃, and the percentage of solvent B was increased over a nonlinear gradient (0% for 6min; 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 (1mL) fractions; fractions 2 to 14 were merged into 2 subfractions (2,3,6,7,10,11,14; 4,5,8,9,12,13), and fractions from 15 min to 60 min were merged into 6 subfractions (15,16,27,28,39,40,51,52; 17,18,29,30,41,42,53,54; etc.). The 8 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, excepted the fractionation procedure that was substituted to twice elution of phosphopeptides by 100 µl buffer 6 (15% ammonia, 40% ACN).

LC-MS/MS Analysis All peptides were reconstituted in 5% FA (vol/vol) and separated on an in-house-made C18 reverse phase column (15cm length × 75µm diameter, Michrom Bioresources, Inc., Auburn, CA) with C18 beads (1.9µm, Michrom Bioresources, Inc., Auburn, CA ) on an EASY-

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nano-LC1000 (Thermo Fisher Scientific, San Jose, CA, USA) 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 automated gain control (AGC) target of 5.0e5 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 3s. HCD fragmentation was performed at normalized collision energy was 32%. MS2 AGC target was set to 5.0e3 with a max injection time of 35ms and dynamic exclusion was set to 18s. 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 70000 at m/z 200. The isolation width was 3 m/z for precursor ion selection. The automatic gain control (AGC) was set to 3e6, 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 17500 at m/z 200, the AGC was set at 5e4 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 M S 2 was set at 27% for HCD.

Phosphoproteome Data Processing 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 9



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cells by TAFT, 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 datasets from the recently published work yielded by conventional SCX-TiO2 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 dataset 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 datasets mentioned above were used as to draw a comparison between the datasets 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, phosphorylation (STY) as variable modifications; an initial mass tolerance of 20 ppm and a final mass tolerance of 6 ppm for precursor mass; allowing max of three missed cleavages. Peptides, proteins, and phosphosites were set to a 1% false discovery rate, the minimum length allowed was 6 amino acids and a minimum Andromeda score of 40. The match between run (MBR) feature was enabled. The reverse hits and potential contaminants 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.gravy-calculator.de). The theoretical pI values were calculated by the ProMoST tool (http://proteomics.mcw.edu/promost.html).

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Results and Discussion Rapid Identification and Qualification of Deep Phosphoproteome in HeLa and HepG2.2.15 cells Recent advances in technology have 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 1 B). 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 1 A). Hence, we first characterized the performance of TAFT strategy by the time spent in phosphopeptides enrichment and fractionation, the capability for deep phosphoproteome analysis. Using one milligram of protein from HeLa and HepG2.2.15 cells respectively, the phosphopeptide preparation procedures can be completed within 3 hours in a high-throughput manner (Figure 1 A, Figure S1). Subsequently, three fractions of phosphopeptides from each sample were analyzed with a 75 min LC-MS/MS measurement. The measurement of the single sample only required less than 4 hours, which enabled rapid identification and quantification of more than 14,000 distinct phosphopeptides with corresponding ∼ 12,000 phosphosites in a sample (Figure 2 A). 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 2 B and 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 2 D, Figure S2), including 17,634 high-confident phosphorylation 11



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events (class I sites, Table S-3). The identified phosphopeptides and phosphosites table are provided in Table S-1 and S-2, and evaluation of the MS quality is shown in Figure S2. The MS signals of phosphopeptides we detected spanned over 5 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 S2 D). Remarkably, 90% were detected in 2 orders of magnitude (5.74 to 7.70), while the 5% with low abundance spanned over 1.7 order of magnitude, and 5% with high abundance spanned over 1.6 order of magnitude, demonstrating the capacity of deep coverage of phosphoproteome without compromising time spent on phosphopeptide preparation and measurement.

Specificity and Reproducibility of TAFT Techniques Next, We then evaluated the specificity of the TAFT technique. As a result, phosphopeptide selectivity exceeded over 91% in all cases (Figure 2 A), 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 over 79% found in all triple biological replicates in two cell lines, respectively (Figure 3 A). 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 3 B), 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 12


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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 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 1 B). 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, time-consuming 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 contains no salt and don’t need additional desalting procedures, thus are flexible to the following phosphopeptides enrichment procedure. One factor that strongly contributed to the performance 13



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of TAFT is the combination of TiO2 StageTips and HpRP StageTips. After enrichment of phosphopeptides, the non-phosphopeptides 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, 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 were collected in current subfractions and the phosphopeptides that have 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, that 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, HpRP-IMAC, and recently introduced ‘post-fractionation’ methods, 3,11,29,33,39,45–47 especially focusing on the work from the past 4 years (2014-2017) in which the datasets were generated by newer Thermo instruments (Q-Exactive and Orbitrap Fusion) . We also yielded a dataset 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 etc (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, en14


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richment of phosphopeptides. Even by the recently introduced ‘post-fractionation’ 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 ∼ two days in phosphopeptide preparation. Using the HpRP-TiO2 approach, 2 mg of mouse liver protein was used and generated 8 fractions of phosphopeptides, after 10 hours of MS measurement per sample, that yielded 11,758 phosphopeptides per sample (Table 1, Table S-4). 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 days 3,40,43 (Figure 1 B and Table 1). Relatively, our TAFT approach used less starting materials (one milligram of protein) and the phosphopeptide preparation procedure can be finished in only 3 hours, achieving deep coverage of phosphoproteome within only 3.75 hours of MS measurement, yielding an average identification of 3,800 unique phosphopeptides per MS hour (Table 1). More importantly, due to 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-TiO2 29 (Figure S4). As shown in Figure S4, phosphopeptides intensities correlations in datasets generated by conventional phosphoproteomics approaches varied from 0.80-0.90 between technical replicates, which became lower between biological replicates in cell line samples, that is in good agreement with the reported data in previous large-scale phosphoproteomic studies. 28 Reproducibility of phosphoproteomics approaches is one of the principal 15



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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 in amino acids cell culture (SILAC), dimethyl labeling, tandem mass tags (TMT) 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 approach was performed in different processes and pH values, that may lead to preference of phosphopeptides with different characteristics. Thus, we compared the HeLa datasets generated by TAFT with the recently published HeLa datasets generated by 2D-Ti4+ -IMAC-HILIC strategy 11 and SCX-TiO2 strategy. 3 To our surprise, only 10.5% of the phosphopeptides generated by TAFT were identified in dataset by 2D-Ti4+ -IMAC-HILIC . Additionally, when we compared our HeLa dataset with the current ultradeep HeLa datasets 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 phosphopeptides. 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 datasets by Sharma et al., indicating 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, pI of the distinct phosphopeptides from each approach (Figure 4 A ). We observed that the phosphopeptides exclusively found in TAFT were longer than the two other approaches with an average length of 19 amino acids, while 16 and 14 in phosphopeptides exclusively observed by SCX-TiO2 and 16


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2D-Ti4+ -IMAC-HILIC, respectively. Interestingly, the difference should not be attributed to a higher missed cleavage ratio in TAFT dataset, for that the TAFT dataset has an average of 0.63 missed cleavage per phosphopeptide while 0.68 and 0.48 in the datasets of 2D-Ti4+ IMAC-HILIC and SCX-TiO2 , respectively. The phosphopeptides unique to TAFT were more hydrophilic than the phosphopeptides unique to 2D-Ti4+ -IMAC-HILIC, and even shows a slight advantage for the phosphopeptides with GRAVY values lower than -1.5 (moderately hydrophilic) compared to SCX-TiO2 (Figure 4 A ). The pI values of the unique phosphopeptides identified by each approach showed distinct distribution, the 2D-Ti4+ -IMAC-HILIC and SCX-TiO2 showed distinct preference in phosphopeptides with high pI values and low pI values respectively. While compared with the two other approaches, phosphopeptides exclusively identified by TAFT showed a distinct advantage for phosphopeptides with lower pI values than 5.0 (highly acidic) compared to 2D-Ti4+ -IMAC-HILIC, and also for phosphopeptides with higher pI values than 11.0 (highly basic) compared to SCX-TiO2 (Figure 4 A). Similarly, alike distributions were found when we further explored the GRAVY and pI values of the whole datasets 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 dataset identified with TAFT distributed differently with the two other approaches (Figure 4 C). All of the three approaches identified a comparable number of phosphopeptides in the 3+ charge state, while TAFT identified 19% of phosphopeptides with charge state more than 3 compared with 11% both in 2D-Ti4+ -IMAC-HILIC and SCX-TiO2 . Furthermore, the TAFT shows a dramatic improvement for identification of multiphosphorylated peptides, with 23% of the all identified phosphopeptides were multiphosphorylated, while only 12% and 15% by the 2D-Ti4+ -IMAC-HILIC and SCX-TiO2 , respectively. Multisite phosphorylation of proteins is an important and extremely common mechanism, which greatly increases the regulatory potential of proteins and considerably expand the repertoire for combinatorial 17



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regulation or fine-tuned regulation of switch properties, involving in a great variety of cellular processes. 49–52 Therefore, TAFT is an excellent alternative method to the 2D-Ti4+ -IMACHILIC and SCX-TiO2 for studies that mainly focus on multisite phosphorylation of proteins. Since 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 2D-Ti4+ -IMAC-HILIC approach, the peptides were desalted after the enrichment, 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 were collected and combined into 3 subfractions and each subfraction was analyzed on 240 min gradient of LC system in tandem with a Q-Exactive instrument, 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 to IMAC. 55–57 We observed that the TAFT and SCX-TiO2 indeed captured more highly acidic phosphopeptides (pI < 5) than the 2D-Ti4+ -IMAC-HILIC approach. A recent report by Xu et al. found that SCX chromatography outperformed RP chromatography in identification for basic peptides (pI 7∼ 10), 58 which is consistent with Figure 4 A. Moreover, variance in additive combinations of incubation buffers and elution conditions would lead to variance in physicochemical characteristics of phosphopeptides. Previous works have evaluated a wide range of loading and elution conditions on TiO2 chromatography, 59,60 they showed that distinct additive acids and difference in concentration of which in the incubation buffers resulted in the difference in specificity and composition of phosphopeptides. Ruprecht et al. found that the phosphopeptides captured by TiO2 column retained more strongly than the IMAC column. 26 In a recent study, Fukuda et al. used seven elution buffers at different pH to recovery the phosphopeptides enriched on TiO2 beads, they 18


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found that different elution buffers resulted in a distinct recovery of phosphopeptides in peptide length, hydrophobic properties and ratio of acidic amino acid contents. 61 In their study, the glycerol additive in the incubation buffers was found to yield high proportion of mono-phosphopeptides than the lactic acid additive by TiO2 chromatography. Interestingly, Herring et al. reported that TiO2 is more effective at enriching longer, multiply phosphorylated peptides than IMAC, 57 whereas Yue et al. reported the opposite results. 55 Ruprecht et al. also showed that loss of phosphopeptide identification is more likely due to limited binding capacity, biased or incomplete elution from IMAC or TiO2 beads. 26 Previous work by Thingholm et al. suggested that sequential elution from IMAC by pH gradient buffers significantly recovered the multiply phosphorylated peptides. 56 In our work, the incubation buffer used in TAFT is more acidic and contained high percentage of ACN (70% ACN, 5% TFA, 20% lactic acid in TAFT compared to 65% ACN/2% TFA/saturated by glutamic acid in Yue et al., 2 M lactic acid, 50% ACN, 0.1% TFA in Ruprecht et al.), and the variance in elution buffers (6 gradients of ACN/15% ammonia in TAFT compared to 300 mM NH4 OH/50% ACN, 500mM NH4 OH/50% ACN in Yue et al., 50 mM KH2 PO4 , 0.5% (v/v) NH4 OH, pH 11.3 in Ruprecht et al.) may contribute to different recovery of phosphopeptide populations in each method. We speculate that the high concentration of ACN and lactic acid in incubation buffer facilitated the binding of longer, highly charged, multiply phosphorylated peptides to the TiO2 beads by TAFT, and the sufficient elution by 6 gradients of ACN coupled with 15% ammonia promoted the recovery of these phosphopeptides. Taken together, the above analysis showed that TAFT yielded a different population of phosphopeptides compared with conventional IMAC-HILIC and SCX-TiO2 approaches.

Balance on Starting Material, Time Spent, Separation, Depth, Reproducibility and Throughput of Phosphoproteome Analysis Although at least one-third of all cellular proteins can be modified with protein phosphorylation on at least one residue, 62 and in a recent work this was estimated up to 75% of the 19



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whole proteome. 3 However, despite the improvements in speed and sensitivity in MS-based approaches, which have remarkably boosted the investigation into roles of protein phosphorylation under various biological context, 63–65 comprehensive characterization of phosphoproteome continue to present challenges due to the low stoichiometry and dynamics of protein phosphorylation. 9,40,66 Thus, to increase sampling depth of the phosphoproteome, optimization efforts have focused on phosphopeptide preparation strategy, especially the phosphopeptide enrichment strategy and fractionation technique. 40 In the meantime, relatively low amounts of starting material is still an obstacle for interrogation of deep phosphoproteome, especially for clinical samples. Zhou et al. introduced a 2D-Ti4+ -IMAC-HILIC strategy to achieve a balance between materials, robustness and instrument acquisition time, they managed to identify ∼ 17,000 phosphopeptides using 1 mg of HeLa material in two days of MS measurement. However, the benefit still incurred extensive fractionation and significant cost in data acquisition time. A majority dilemma in phosphoproteome phosphopeptide preparation is either analyzing more samples, taking more fractions, and running longer gradient to achieve a deeper coverage of phosphoproteome, or getting a moderate phosphoproteome coverage at the benefit of a few hours of measurement for a single sample. 40 However, the former strategy has the limitations with the cost of extensive MS measurement time, laborious pre-fractionation, or weakening the throughput and the reproducibility. Moreover, it is a whole new ball game when the strategy is applied for studies with treatment over multiple time-points or drug doses under biological replicates or large scale of clinical samples. To achieve a good balance among the expenditure of time, depth, and throughput, we optimized the TAFT strategy for analyzing phosphoproteome in one milligram of sample . As a result of using TiO2 enrichment and tandem HpRP fractionation of phosphopeptides, rather than the traditional fractionation of peptides on HPLC instrument, the strategy significantly shortened the phosphopeptide preparation time, leads to a minimum time of 3 hours to complete phosphopeptide preparation, without diminishing the coverage of phosphoproteome. Furthermore, each sample with this strategy generates 3 fractions of phos20


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phopeptides, which can be analyzed within 4 hours MS measurement. In all cases, we were able to quantify over 14,000 distinct phosphopeptides from one milligram of sample. Generally, analyzing phosphopeptides on a longer analytical column, running longer LC gradient and MS measurement time, that would lead to deeper identification coverage of phosphoproteome. Zhou et al. managed to identify over 3,000 unique phosphopeptides from 125 µg peptide of K562 sample in 60 min LC-MS/MS analysis on a 35 cm long analytical column with Q-Exactive, while 5,600 unique phosphopeptides could be identified in 120 min LCMS/MS analysis. 67 Thus, if provided with sufficient MS measurement time, it’s 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, that led to an average identification and quantification of 9,589, 8,303, 8,206 unique phosphopeptides in each fraction, respectively ( Figure 3 C). There were ∼ 50% of the observed phosphopeptides identified only in 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 2 B and 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 3 D), 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 21



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depth of phosphoproteome analysis, however, most strategies only partially addressed the problem. 40 As the rising demands in high-throughput and high reproducibility of phosphoproteomics analysis, especially for large-scale of 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. Since that all the procedure of phosphopeptide enrichment and fractionation were performed on bench-top centrifuge machine(s) (Figure S1), that 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 large-scale of clinical samples. In short, the strategy we described is relatively timeefficient, low-cost, simple and highly reproducible, which can be applied for large-scale of deep phosphoproteome analysis in a high-throughput manner.

Conclusion Although great advances in mass spectrometry-based phosphoproteomics have been achieved in the last 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 deep phosphoproteome analysis. By introducing the TiO2 chromatography and tandem HpRP chromatography technique, the phosphoproteome can be identified with relatively deep coverage (>21,000 phosphosites in total) and high reproducibility in a high-throughput manner within just 3 hours. 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’s probable to attain a deeper phosphoproteome. Compared with conventional phosphoproteomics approaches, TAFT identified distinct phosphopeptides and provided an easy and efficient

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approach to identify and quantify the phosphoproteome with higher robustness in reproducibility. As a result of rapid, robust, deep phosphoproteome analysis from one milligram of samples by TAFT strategy, it’s 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, to characterize patient-specific phosphoproteome portrait in large-scale of 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.

Acknowledgement 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 ).

Disclosure The authors declare no competing financial interest.

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Supporting Information Available • Supplementary Information Table S1: Phosphopeptides of HeLa and HepG2.1.15 cells identified in this study. (XLSX) • Supplementary Information Table S2: Phosphosites of HeLa and HepG2.1.15 cells identified in this study. (XLSX) • Supplementary Information Table S3: Class I phosphorylation events of HeLa and HepG2.1.15 cells identified in this study. (XLSX) • Supplementary Information Table S4: Phosphopeptides of mouse liver identified in this study. (XLSX) • Supplementary Information Figure 1: Materials used for TAFT StageTip preparation. • Supplementary Information Figure 2: Evaluation and assessment of MS data quality. • Supplementary Information Figure 3: Reproducibility evaluation of fractionation procedure with TAFT approach. • Supplementary Information Figure 4: Reproducibility of conventional phosphoproteomics approaches that were adopted in recently published work. • Supplementary Information Figure 5: 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., SCX-TiO2 from Sharma et al. approaches. The RAW data of mass spectrometry consisting of 18 RAW files from HeLa and HepG2.2.15 cells, 16 RAW files from mouse liver. The RAW files and MaxQuant output files have been deposited in iPROX with the identifier IPX0000939000 ( http://www.iprox.org/page/ PSV023.html;?url=15008053603246dcK, password for reviewers: frXF ). This material is available free of charge via the Internet at http://pubs.acs.org/. 24


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References (1) Blume-Jensen, P.; Hunter, T. Oncogenic kinase signalling. Nature 2001, 411, 355–65. (2) Hanahan, D.; Weinberg, R. A. The hallmarks of cancer. Cell 2000, 100, 57–70. (3) Sharma, K.; D’Souza, R. C.; Tyanova, S.; Schaab, C.; Wiśniewski, J. R.; Cox, J.; Mann, M. Ultradeep Human Phosphoproteome Reveals a Distinct Regulatory Nature of Tyr and Ser/Thr-Based Signaling. Cell Reports 2014, 8, 1583–1594. (4) Wilhelm, M. et al. Mass-spectrometry-based draft of the human proteome. Nature 2014, 509, 582–587. (5) Kim, M.-S. et al. A draft map of the human proteome. Nature 2014, 509, 575–581. (6) Bian, Y.; Li, L.; Dong, M.; Liu, X.; Kaneko, T.; Cheng, K.; Liu, H.; Voss, C.; Cao, X.; Wang, Y.; Litchfield, D.; Ye, M.; Li, S. S.-C.; Zou, H. Ultra-deep tyrosine phosphoproteomics enabled by a phosphotyrosine superbinder. Nature Chemical Biology 2016, 12, 1–10. (7) Lundby, A.; Lage, K.; Weinert, B. T.; Bekker-Jensen, D. B.; Secher, A.; Skovgaard, T.; Kelstrup, C. D.; Dmytriyev, A.; Choudhary, C.; Lundby, C.; Olsen, J. V. Proteomic Analysis of Lysine Acetylation Sites in Rat Tissues Reveals Organ Specificity and Subcellular Patterns. Cell Reports 2012, 2, 419–431. (8) Lemeer, S.; Heck, A. J. The phosphoproteomics data explosion. Current Opinion in Chemical Biology 2009, 13, 414–420. (9) Olsen, J. V.; Mann, M. Status of Large-scale Analysis of Post-translational Modifications by Mass Spectrometry. Molecular & Cellular Proteomics 2013, 12, 3444–3452. (10) Song, C.; Ye, M.; Han, G.; Jiang, X.; Wang, F.; Yu, Z.; Chen, R.; Zou, H. Reversedphase-reversed-phase liquid chromatography approach with high orthogonality for multidimensional separation of phosphopeptides. Analytical Chemistry 2010, 82, 53–56. 25



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

(11) Zhou, H.; Di Palma, S.; Preisinger, C.; Peng, M.; Polat, A. N.; Heck, A. J. R.; Mohammed, S. Toward a Comprehensive Characterization of a Human Cancer Cell Phosphoproteome. Journal of Proteome Research 2013, 12, 260–271. (12) Zarei, M.; Sprenger, A.; Rackiewicz, M.; Dengjel, J. Fast and easy phosphopeptide fractionation by combinatorial ERLIC-SCX solid-phase extraction for in-depth phosphoproteome analysis. Nature Protocols 2015, 11, 37–45. (13) Beausoleil, S. a.; Jedrychowski, M.; Schwartz, D.; Elias, J. E.; Villen, J.; Li, J.; Cohn, M. a.; Cantley, L. C.; Gygi, S. P. Large-scale characterization of HeLa cell nuclear phosphoproteins. Proceedings of the National Academy of Sciences 2004, 101, 12130–12135. (14) Ballif, B. A.; Villén, J.; Beausoleil, S. A.; Schwartz, D.; Gygi, S. P. Phosphoproteomic Analysis of the Developing Mouse Brain. Molecular & Cellular Proteomics 2004, 3, 1093–1101. (15) Pinkse, M. W. H.; Uitto, P. M.; Hilhorst, M. J.; Ooms, B.; Heck, A. J. R. Selective Isolation at the Femtomole Level of Phosphopeptides from Proteolytic Digests Using 2D-NanoLC-ESI-MS/MS and Titanium Oxide Precolumns. Analytical Chemistry 2004, 76, 3935–3943. (16) SANO, A.; NAKAMURA, H. Titania as a Chemo-affinity Support for the Columnswitching HPLC Analysis of Phosphopeptides: Application to the Characterization of Phosphorylation Sites in Proteins by Combination with Protease Digestion and Electrospray Ionization Mass Spectrometry. Analytical Sciences 2004, 20, 861–864. (17) Andersson, L.; Porath, J. Isolation of phosphoproteins by immobilized metal (Fe3+) affinity chromatography. Analytical Biochemistry 1986, 154, 250–254. (18) Posewitz, M. C.; Tempst, P. Immobilized gallium(III) affinity chromatography of phosphopeptides. Analytical Chemistry 1999, 71, 2883–2892. 26


Page 26 of 40

Page 27 of 40

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


(19) Villén, J.; Gygi, S. P. The SCX/IMAC enrichment approach for global phosphorylation analysis by mass spectrometry. Nature Protocols 2008, 3, 1630–1638. (20) McNulty, D. E.; Annan, R. S. Hydrophilic Interaction Chromatography Reduces the Complexity of the Phosphoproteome and Improves Global Phosphopeptide Isolation and Detection. Molecular & Cellular Proteomics 2008, 7, 971–980. (21) Alpert, A. J. Electrostatic repulsion hydrophilic interaction chromatography for isocratic separation of charged solutes and selective isolation of phosphopeptides. Analytical Chemistry 2008, 80, 62–76. (22) Gan, C. S.; Guo, T.; Zhang, H.; Lim, S. K.; Sze, S. K. A comparative study of electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) versus SCX-IMACbased methods for phosphopeptide isolation/enrichment. Journal of Proteome Research 2008, 7, 4869–4877. (23) Han, G.; Ye, M.; Zhou, H.; Jiang, X.; Feng, S.; Jiang, X.; Tian, R.; Wan, D.; Zou, H.; Gu, J. Large-scale phosphoproteome analysis of human liver tissue by enrichment and fractionation of phosphopeptides with strong anion exchange chromatography. PROTEOMICS 2008, 8, 1346–1361. (24) Zarei, M.; Sprenger, A.; Gretzmeier, C.; Dengjel, J. Rapid combinatorial ERLIC-SCX solid-phase extraction for in-depth phosphoproteome analysis. Journal of Proteome Research 2013, 12, 5989–5995. (25) Zarei, M.; Sprenger, A.; Metzger, F.; Gretzmeier, C.; Dengjel, J. Comparison of ERLICTiO 2 , HILICTiO 2 , and SCXTiO 2 for Global Phosphoproteomics Approaches. Journal of Proteome Research 2011, 10, 3474–3483. (26) Ruprecht, B.; Koch, H.; Medard, G.; Mundt, M.; Kuster, B.; Lemeer, S. Comprehensive and Reproducible Phosphopeptide Enrichment Using Iron Immobilized Metal Ion

27



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Affinity Chromatography (Fe-IMAC) Columns. Molecular & Cellular Proteomics 2015, 14, 205–215. (27) Post, H.; Penning, R.; Fitzpatrick, M. A.; Garrigues, L. B.; Wu, W.; MacGillavry, H. D.; Hoogenraad, C. C.; Heck, A. J. R.; Altelaar, A. F. M. Robust, Sensitive, and Automated Phosphopeptide Enrichment Optimized for Low Sample Amounts Applied to Primary Hippocampal Neurons. Journal of Proteome Research 2017, 16, 728–737. (28) Giansanti, P.; Aye, T. T.; van den Toorn, H.; Peng, M.; van Breukelen, B.; Heck, A. J. R. An Augmented Multiple-Protease-Based Human Phosphopeptide Atlas. Cell Reports 2015, 11, 1834–1843. (29) Batth, T. S.; Francavilla, C.; Olsen, J. V. Off-line high-pH reversed-phase fractionation for in-depth phosphoproteomics. Journal of Proteome Research 2014, 13, 6176–6186. (30) Koch, H.; Wilhelm, M.; Ruprecht, B.; Beck, S.; Frejno, M.; Klaeger, S.; Kuster, B. Phosphoproteome Profiling Reveals Molecular Mechanisms of Growth-Factor-Mediated Kinase Inhibitor Resistance in EGFR-Overexpressing Cancer Cells. Journal of Proteome Research 2016, 15, 4490–4504. (31) Yue, X. S.; Hummon, A. B. Combination of multistep IMAC enrichment with high-pH reverse phase separation for in-depth phosphoproteomic profiling. Journal of Proteome Research 2013, 12, 4176–4186. (32) Mertins, P.; Qiao, J. W.; Patel, J.; Udeshi, N. D.; Clauser, K. R.; Mani, D. R.; Burgess, M. W.; Gillette, M. A.; Jaffe, J. D.; Carr, S. A. Integrated proteomic analysis of post-translational modifications by serial enrichment. Nature methods 2013, 10, 634–637. (33) Schunter, A. J.; Yue, X.; Hummon, A. B. Phosphoproteomics of colon cancer metastasis: comparative mass spectrometric analysis of the isogenic primary and metastatic cell

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lines SW480 and SW620. Analytical and Bioanalytical Chemistry 2017, 409, 1749– 1763. (34) Engholm-Keller, K.; Birck, P.; Størling, J.; Pociot, F.; Mandrup-Poulsen, T.; Larsen, M. R. TiSH - a robust and sensitive global phosphoproteomics strategy employing a combination of TiO2, SIMAC, and HILIC. Journal of Proteomics 2012, 75, 5749–5761. (35) Wiśniewski, J. R.; Mann, M. Consecutive Proteolytic Digestion in an Enzyme Reactor Increases Depth of Proteomic and Phosphoproteomic Analysis. Analytical Chemistry 2012, 84, 2631–2637. (36) Rappsilber, J.; Mann, M.; Ishihama, Y. Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nature Protocols 2007, 2, 1896–1906. (37) Cox, J.; Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nature Biotechnology 2008, 26, 1367–1372. (38) Cox, J.; Neuhauser, N.; Michalski, A.; Scheltema, R. A.; Olsen, J. V.; Mann, M. Andromeda: A peptide search engine integrated into the MaxQuant environment. Journal of Proteome Research 2011, 10, 1794–1805. (39) Zappacosta, F.; Scott, G. F.; Huddleston, M. J.; Annan, R. S. An optimized platform for hydrophilic interaction chromatography-immobilized metal affinity chromatography enables deep coverage of the rat liver phosphoproteome. Journal of Proteome Research 2015, 14, 997–1009. (40) Riley, N. M.; Coon, J. J. Phosphoproteomics in the Age of Rapid and Deep Proteome Profiling. Analytical Chemistry 2016, 88, 74–94.

29



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

(41) de Graaf, E. L.; Giansanti, P.; Altelaar, a. F. M.; Heck, A. J. R. Single step enrichment by Ti4+-IMAC and label free quantitation enables in-depth monitoring of phosphorylation dynamics with high reproducibility and temporal resolution. Molecular & cellular proteomics : MCP 2014, 1–28. (42) Humphrey, S. J.; Azimifar, S. B.; Mann, M. High-throughput phosphoproteomics reveals in vivo insulin signaling dynamics. Nature Biotechnology 2015, 33, 990–995. (43) Humphrey, S. J.; Yang, G.; Yang, P.; Fazakerley, D. J.; Stöckli, J.; Yang, J. Y.; James, D. E. Dynamic adipocyte phosphoproteome reveals that akt directly regulates mTORC2. Cell Metabolism 2013, 17, 1009–1020. (44) Lundby, A.; Secher, A.; Lage, K.; Nordsborg, N. B.; Dmytriyev, A.; Lundby, C.; Olsen, J. V. Quantitative maps of protein phosphorylation sites across 14 different rat organs and tissues. Nature Communications 2012, 3, 876. (45) Park, J.-M.; Park, J.-H.; Mun, D.-G.; Bae, J.; Jung, J. H.; Back, S.; Lee, H.; Kim, H.; Jung, H.-J.; Kim, H. K.; Lee, H.; Kim, K. P.; Hwang, D.; Lee, S.-W. Integrated analysis of global proteome, phosphoproteome, and glycoproteome enables complementary interpretation of disease-related protein networks. Scientific Reports 2015, 5, 18189. (46) Minard, A. Y.; Tan, S. X.; Yang, P.; Fazakerley, D. J.; Domanova, W.; Parker, B. L.; Humphrey, S. J.; Jothi, R.; Stöckli, J.; James, D. E. mTORC1 Is a Major Regulatory Node in the FGF21 Signaling Network in Adipocytes. Cell Reports 2016, 17, 29–36. (47) Roumeliotis, T. I. et al. Genomic Determinants of Protein Abundance Variation in Colorectal Cancer Cells. Cell Reports 2017, 20, 2201–2214. (48) Solari, F. a.; Dell’Aica, M.; Sickmann, A.; Zahedi, R. P. Why phosphoproteomics is still a challenge. Mol. BioSyst. 2015, 11, 1487–1493.

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Page 30 of 40

Page 31 of 40

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


(49) Cohen, P. The regulation of protein function by multisite phosphorylation–a 25 year update. Trends in biochemical sciences 2000, 25, 596–601. (50) Holmberg, C. I.; Tran, S. E.; Eriksson, J. E.; Sistonen, L. Multisite phosphorylation provides sophisticated regulation of transcription factors. Trends in Biochemical Sciences 2002, 27, 619–627. (51) Yang, X.-J. Multisite protein modification and intramolecular signaling. Oncogene 2005, 24, 1653–1662. (52) Salazar, C.; Höfer, T. Multisite protein phosphorylation - From molecular mechanisms to kinetic models. FEBS Journal 2009, 276, 3177–3198. (53) Udeshi, N. D.; Mertins, P.; Svinkina, T.; Carr, S. A. Large-scale identification of ubiquitination sites by mass spectrometry. Nature Protocols 2013, 8, 1950–1960. (54) Abbatiello, S. E. et al. Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure CancerRelevant Proteins in Plasma. Molecular & Cellular Proteomics 2015, 14, 2357–2374. (55) Yue, X.; Schunter, A.; Hummon, A. B. Comparing Multistep Immobilized Metal Affinity Chromatography and Multistep TiO 2 Methods for Phosphopeptide Enrichment. Analytical Chemistry 2015, 87, 8837–8844. (56) Thingholm, T. E.; Jensen, O. N.; Robinson, P. J.; Larsen, M. R. SIMAC (Sequential Elution from IMAC), a Phosphoproteomics Strategy for the Rapid Separation of Monophosphorylated from Multiply Phosphorylated Peptides. Molecular & Cellular Proteomics 2008, 7, 661–671. (57) Herring, L. E.; Grant, K. G.; Blackburn, K.; Haugh, J. M.; Goshe, M. B. Development of a tandem affinity phosphoproteomic method with motif selectivity and its application

31



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

Page 32 of 40

in analysis of signal transduction networks. Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences 2015, 988, 166–174. (58) Xu, J.; Gao, J.; Yu, C.; He, H.; Yang, Y.; Figeys, D.; Zhou, H. Development of Online pH Gradient-Eluted Strong Cation Exchange Nanoelectrospray-Tandem Mass Spectrometry for Proteomic Analysis Facilitating Basic and Histidine-Containing Peptides Identification. Analytical Chemistry 2016, 88, 583–591. (59) Sugiyama, N.; Masuda, T.; Shinoda, K.; Nakamura, A.; Tomita, M.; Ishihama, Y. Phosphopeptide Enrichment by Aliphatic Hydroxy Acid-modified Metal Oxide Chromatography for Nano-LC-MS/MS in Proteomics Applications. Molecular & Cellular Proteomics 2007, 6, 1103–1109. (60) Aryal, U. K.; Ross, A. R. S. Enrichment and analysis of phosphopeptides under different experimental conditions using titanium dioxide affinity chromatography and mass spectrometry. Rapid Communications in Mass Spectrometry 2010, 24, 219–231. (61) Fukuda, I.; Hirabayashi-Ishioka, Y.; Sakikawa, I.; Ota, T.; Yokoyama, M.; Uchiumi, T.; Morita, A. Optimization of Enrichment Conditions on TiO 2 Chromatography Using Glycerol As an Additive Reagent for Effective Phosphoproteomic Analysis. Journal of Proteome Research 2013, 12, 5587–5597. (62) Ubersax, J. A.; Ferrell Jr, J. E. Mechanisms of specificity in protein phosphorylation. Nature Reviews Molecular Cell Biology 2007, 8, 530–541. (63) Olsen, J. V.; Vermeulen, M.; Santamaria, A.; Kumar, C.; Miller, M. L.; Jensen, L. J.; Gnad, F.; Cox, J.; Jensen, T. S.; Nigg, E. a.; Brunak, S.; Mann, M. Quantitative Phosphoproteomics Reveals Widespread Full Phosphorylation Site Occupancy During Mitosis. Science Signaling 2010, 3, ra3–ra3. (64) Sacco, F.; Silvestri, A.; Posca, D.; Pirrò, S.; Gherardini, P. F.; Castagnoli, L.; Mann, M.;

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Cesareni, G. Deep proteomics of breast cancer cells reveals that metformin rewires signaling networks away from a pro-growth state. Cell Systems 2016, 2, 159–171. (65) Drake, J. M. et al. Phosphoproteome Integration Reveals Patient- Specific Networks in Prostate Cancer Resource Phosphoproteome Integration Reveals Patient-Specific Networks in Prostate Cancer. Cell 2016, 166, 1–14. (66) Nilsson, C. L. Advances in Quantitative Phosphoproteomics. Analytical Chemistry 2012, 84, 735–746. (67) Zhou, H.; Ye, M.; Dong, J.; Corradini, E.; Cristobal, A.; Heck, A. J. R.; Zou, H.; Mohammed, S. Robust phosphoproteome enrichment using monodisperse microspherebased immobilized titanium (IV) ion affinity chromatography. Nature Protocols 2013, 8, 461–480. (68) Ferries, S.; Perkins, S.; Brownridge, P. J.; Campbell, A.; Eyers, P. A.; Jones, A. R.; Eyers, C. E. Evaluation of Parameters for Confident Phosphorylation Site Localization Using an Orbitrap Fusion Tribrid Mass Spectrometer. Journal of Proteome Research 2017, 16, 3448–3459.

Graphics and Tables

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Page 34 of 40

A 1 mg protein

Incubation

Elution and fractionation

Washing

HpRP Buffer Fraction 1

a

b

c

d

e

f

Fraction 2

TiO2 adsorbent

Phosphopepties

Nonphosphopepties

P

Empore C8 disk

TiO2 beads

Empore C8 disk Fraction 3

P

Protein digestion

75 min ×3 LC-MS/MS

C18 beads

P

Enrichment and fractionation of phosphopeptides

LC-MS/MS

~4h

3 h

B

5-10 mg protein

Fractionation with HPLC/SCX

Lyophilization and desalting Enrichment of phosphopeptides

LC-MS/MS

LC-MS/MS * (8-15)

Protein digestion

8-15 fractions

IMAC/TiO2

10h-days

2-3days

Figure 1: Workflow of TAFT approach and conventional phosphoproteomics approaches. (A) Overview of workflow for phosphoproteome analysis with TAFT approach. The simple workflow only needs 1 mg of protein of starting materials , phosphopeptide preparation can be finished within 3 hours, 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.

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HepG2.215

HeLa

A

1

2

3

1

2

3

Biological replicates Phosphopeptide preparation

3h 75 min × 3

75 min × 3

75 min × 3

75 min × 3

75 min × 3

3,503

3,401

3,387

3,522

3,477

3,395

Peptides

16,019

15,869

15,624

16,057

16,186

15,452

Phosphopeptides

14,702

14,465

14,243

14,714

14,703

14,178

Phosphosites

12,346

12,120

12,020

12,323

12,106

11,611

92%

91%

91%

92%

91%

92%

LC-MS/MS time Phosphoproteins

75 min × 3

Specificity

HepG2.2.15

18000

16000

14000

12000

D Number of Phosphopeptides

HeLa

C Number of Phosphopeptides

B

Number of 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


18000

16000

14000

12000

1

2

20000

18000

16000

14000

12000

1

3

2

HepG2.2.15 group

HeLa group

3

2

4

6

Samples measured of two groups

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) The cumulative number of distinct quantified phosphopeptides in HeLa cells from the triple biological replicates. (C) The cumulative number of distinct quantified phosphopeptides in HepG2.2.15 cells from the triple biological replicates. (D) The cumulative number of distinct quantified phosphopeptides in HeLa group and HepG2.2.15 group.

35



A

C HeLa_2 (14,465)

HepG2.2.15_1 (14,714)

10000 9589 8303 8206

HepG2.2.15_2 (14,703)

Number of phosphopeptides

HeLa_1 (14,702)

overlap (11,624)

overlap (12,074)

HepG2.2.15_3 (14,178)

HeLa_3 (14,243)

B

7500

5000

2500

0

Fraction F1

Pearson correlation coefficients for biological replicates

F2

F3

D

0.2

1 0.8

HeLa.1

HepG2.2.15.1

0.6 0.4 0.2

0.91

0.93

HepG2.2.15.2

HeLa.2

0

PC2

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

Page 36 of 40

0.0

Fraction1 Fraction2 Fraction3

−0.2 −0.4

0.85

0.90

HepG2.2.15.3

0.91

0.93

HeLa.3

0.2

−0.6 −0.8 −1

0.2

0.0

0.2

PC1

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.

36


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B

A Density

0.08

9%

9%

0.06

43%

47%

46%

42%

0.04

IMAC-HILIC

SCX-TiO2

0.02

0.00

0

10

20

30

40

2+

15%

Peptide length (aa)

3+

35%

Density

0.6

4+ 46%

only in Sharma et al. 2014 (SCX−TiO2)

0.4

TAFT

only in TAFT only in Zhou et al. 2013 (IMAC-HILIC)

0.2

C

0.0

−2

0

11%

13%

2

GRAVY index

85%

0.6

88%

SCX-TiO2

Density

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


IMAC-HILIC

0.4

18%

0.2

77%

0.0

5.0

7.5

10.0

12.5

TAFT

Theoretical pI

1p 2p 3p 4p 5p

Figure 4: Comparison of phosphopeptides characteristics in HeLa cells identified by TAFT or by recently published 2D-Ti4+ -IMAC-HILIC from Zhou et al., 11 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 to dataset by Zhou et al. and Sharma et al.. (B) Percentage of phosphopeptides with different charge states in the whole HeLa dataset 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 dataset by TAFT, 2D-Ti4+ -IMAC-HILIC (Zhou et al.) and SCX-TiO2 (Sharma et al.) approaches.

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Page 38 of 40

Table 1: Summary of phosphopeptides identification with TAFT and with conventional phosphoproteomics workflows. The MS RAW data of triplicate technical or biological replicates in recently published work were searched with 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 to previously reported. For the information of samples not presented in the work, it was annotated with ‘NA’. The abbreviation of instruments annotated in column “MS Measurement Time” are: QE, Q-Exactive; Fus, Orbitrap Fusion; VP, Velos Pro; XL, LTQ Orbitrap XL.

Study

Tissue/Cell

This study

HepG2.2.15 HeLa cells

This study

mouse liver

Workflow &Fractions

Starting Materials

Phosphopeptide Preparation Time

TAFT/ 3

1 mg protein

3 h

HpRP-TiO2 / 8

2 mg protein

>1 day

MS Measurement Time

Phosphopeptide identified per sample

Multiplexed Sample Processing

3.8 hF us

14,590

Yes

QE

11,758

No

VP

10.4 h

Zappacosta et al. 39

rat liver

HILIC-IMAC/ 14

5 mg protein

>1 day

13,132

No

Yue et al. 31 Zhou et al. 11 Zarei et al. 24

MCF-10A cells HeLa cells HeLa cells

multiIMAC-HLB/ 12 IMAC-HILIC/ 20 ERLIC-SCX-TiO2 / 13

3 mg protein 125 µg peptide 6 mg protein

>1 day >1 day >1 day

14.6 hQE 40.0 hV elos 32.0 hXL

8,969 9,066 9,952

No No No

Batth et al. 29

NIH/3T3 cells

HpRP-TiO2 / 14

2-3 mg protein

1 day

18.7 hQE

17,225

No

29

NIH/3T3 cells

SCX-TiO2 / 14

2-3 mg protein

>1 day

18.7 hQE

5,518

No

SW480/SW620 cells

IMAC/TiO2 -HLB/ 8

3.5 mg protein

1 day

12.0 hQE

4,331/6,567

No

HeLa cells

SCX-TiO2 / 9

6 mg peptide

>1 day

24.0 hQE

19,476

No

Park et al. 45

Stomach cancer tissue

mRP-IMAC/ 12

14 mg protein

>1 day

48.0 hQE

18,846

No

Minard et al. 46

3T3-L1 fibroblasts

SCX-TiO2 / 10

NA

>1 day

25.0 hQE

8,201

No

Roumeliotis et al. 47

Colorectal cancer cells

HpRP-IMAC/ 10

1 mg protein

>1 day

20.0 hF us

11,000

No

Batth et al.

Schunter et al. 33 Sharma et al.

3

38


25.7 h

0.39 0.87 0.13 0.38 215.2.F2

Page 39 of 40

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

0.55 0.89 0.18 0.59


HeLa.2.F2

0.47 0.11 0.91 0.55 0.12 215.2.F3

0.53 0.18 0.91 0.48 0.21

0.77 0.5 0.48 0.84 0.49 0.47 215.3.F1

0.88 0.55 0.55 0.9 0.57 0.56

0.39 0.83 0.17 0.46 0.84 0.15 0.55 215.3.F2

0.54 0.88 0.15 0.59 0.92 0.2 0.57

HeLa.2.F3

HeLa.3.F1

H

0.5 0.18 0.83 0.59 0.22 0.84 0.510.22 215.3.F3 0.53 0.18 0.88 0.49 0.22 0.92 0.540

Figure S3: Heatmap of pearson intensity correlation of all fractions showing ducibility in phosphopeptides quantification of corresponding fractions bet replicates.

Graphical TOC Entry Tissue Cell

TAFT StageTips

75 min ×3 LC-MS/MS

HpRP Buffers

1mg protein

>14,000 phosphopeptides/sample ~12,000 phosphosites/sample 21,281 phosphosites/in total

3h

~4h


S-3


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

Graphical TOC Entry Tissue Cell

TAFT StageTips

75 min ×3 LC-MS/MS

HpRP Buffers

1mg protein

>14,000 phosphopeptides/sample ~12,000 phosphosites/sample 21,281 phosphosites/in total

3h

~4h

S3


Page 40 of 40

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

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