Enzymatic Approach To Study Tightly

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A combined enrichment/enzymatic approach to study tightly clustered multi-site phosphorylation on Ser-rich domains Evgeny Kanshin, Mirela Pascariu, Mike Tyers, Damien D'Amours, and Pierre Thibault J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00205 • Publication Date (Web): 31 Jul 2018 Downloaded from http://pubs.acs.org on August 1, 2018

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Journal of Proteome Research

A combined enrichment/enzymatic approach to study tightly clustered multi-site phosphorylation on Ser-rich domains

Evgeny Kanshin1, Mirela Pascariu1, Mike Tyers1,2, Damien D’Amours1,3 and Pierre Thibault1,4,*

1

Institute for Research in Immunology and Cancer, Université de Montréal, C.P. 6128, Succursale centreville, Montréal, Québec, H3C 3J7, Canada. 2

Department of Medicine, Université de Montréal, C.P. 6128, Succursale centre-ville, Montréal, Québec, H3C 3J7, Canada. 3

Ottawa Institute of Systems Biology, Department of Cellular and Molecular Medicine, University of Ottawa, Roger Guindon Hall, 451 Smyth Rd, Ottawa, ON, K1H 8M5, Canada

4

Department of Chemistry, Université de Montréal, C.P. 6128, Succursale centre-ville, Montréal, Québec, H3C 3J7, Canada.

*Correspondence should be addressed to PT (phone: 514-343-6910/fax: 514-343-6843/email: [email protected])

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ABSTRACT The regulation of protein function through phosphorylation is often dominated by allosteric interactions and conformational changes. However, alternative mechanisms involving electrostatic interactions also regulate protein function. In particular, phosphorylation of clusters of Ser/Thr residues can affect protein-plasma membrane/chromatin interactions by electrostatic interactions between phosphosites and phospholipids or histones. Currently, only a few examples of such mechanisms are reported, primarily because of the difficulties of detecting highly phosphorylated proteins and peptides, due in part to the low ionization efficiency and fragmentation yield of multi-phosphorylated peptides in mass spectrometry when using positive ion mode detection. This difficulty in detection has resulted in underreporting of such modified regions, which can be thought of as phosphoproteomic dark matter. Here, we present a novel approach that enriches for multisite-phosphorylated peptides that until now remained inaccessible by conventional phosphoproteomics. Our technique enables the identification of multisite-phosphorylated regions on more than 300 proteins in both yeast and human cells and can be used to profile changes in multisite phosphorylation upon cell stimulation. We further characterize the role of multisite phosphorylation for Ste20 in the yeast mating pheromone response. Mutagenesis experiments confirmed that multisite phosphorylation of Ser/Thr-rich regions plays an important role in the regulation of Ste20 activity during mating pheromone signaling. The ability to detect protein multisite phosphorylation opens new avenues to explore phosphoproteomic dark matter, and to study Ser-rich proteins that interact with binding partners through charge pairing mechanisms.

KEY WORDS Multisite phosphorylation, quantitative proteomics, phosphoproteomics, alkaline phosphatase


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INTRODUCTION Reversible protein phosphorylation is one of the most abundant and well-studied post-translational modifications (PTM). While previous estimates suggest that one-third of the expressed proteins are phosphorylated during their life cycle, the number of experimentally confirmed phosphosites in human cells indicate that this proportion could reach more than two-third of the human proteome

1, 2

. The

functional significance of this modification on protein substrates is important in view of its impact on their enzymatic activities, subcellular localization, and interactions with other proteins. Phosphorylation is one of the primary mechanisms of signal transduction in eukaryotic cells 3, 4. Many diseases, including cancers, are associated with dysregulation of protein phosphorylation

5-7

. Enzymes that catalyze

phosphorylation (kinases) are the primary targets of numerous drug discovery programs 8, 9. Our mechanistic understanding of protein regulation by reversible phosphorylation is partly explained through allosteric activation whereby the phosphorylated residue induces a change in protein conformation. Glycogen phosphorylase represents a classic example where phosphorylation results in a dramatic reorganization that facilitates access of the substrate to the catalytic site (Figure 1A)

10

.

Sometimes the effect of protein phosphorylation can be more subtle as for isocitrate dehydrogenase where phosphorylation inactivates the enzyme without any change in conformation (Figure 1B). Inhibition is achieved by electrostatic repulsion where the serine-phosphate partially occupies the site recognized by the negatively charged substrate, isocitrate, but does not make strong stabilizing interactions with positively charged residues in its vicinity as it impedes substrate binding

11, 12

. The

formation of Src homology 2 (SH2)-binding epitopes (Figure 1C) via the phosphorylation of tyrosine residues represent an important paradigm whereby sequence context affect most recognition events, and thus mutating or moving the phosphosite is rarely tolerated 13-15.



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Figure 1. Examples of protein regulation through allostery and bulk electrostatics. Protein phosphorylation change conformational state of glycogen phosphorylase from inactive b-form to active a –form (A). Alternatively, phosphorylation can simply block the enzyme active site as for isocitrate dehydrogenase (B). Tyrosine phosphorylation could create SH2-binding epitopes and affect proteinprotein interactions, like in the case of STAT1 signaling (C). An alternative mechanism involves creating negatively charged cluster on a protein surface that affects interactions with other charged macromolecule assemblies. Particularly, multi-phosphorylation of Ste5 can disrupt its interaction with the plasma membrane (D). Multisite phosphorylation of a sensor domain in the chromatic condensation factor Smc4 tend to increase its interaction with chromatin (E).

A less explored mechanism of transferring changes in phosphorylation into changes in protein functions is through bulk electrostatics

16

. Multisite phosphorylation of protein regions associated with the

plasma membrane could disrupt this interaction by simple electrostatic repulsion between the negatively charged membrane and the phosphate residues (Figure 1D). For example, the phosphorylation of a cluster of eight poorly conserved Ser/Thr residues near the polybasic membranebinding domain of Ste5 disrupts its binding to the plasma membrane and prevents signal activation 17. Effective inhibition of Ste5 signaling requires multiple phosphorylation sites and a substantial


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accumulation of negative charge, which suggests that Ste5 acts as a sensor for high G1 CDK activity. When Ste5 cannot be phosphorylated, pheromone triggers an aberrant arrest of cells outside G1. Another example of multisite phosphorylation is shown in Figure 1E for the conserved chromatin condensation factor, Smc4. The multisite phosphorylation of a sensor domain in this protein integrates the activation state of Cdk1 with the dynamic binding of the condensation machinery to chromatin 18. Abrogation of this event leads to chromosome segregation defects and lethality, while moderate reduction reveals the existence of a novel chromatin transition state specific to mitosis, the "intertwist" configuration. Upon phosphorylation by Cdk1, condensin binding to the bulk of chromatin becomes less dynamic relative to the non-phosphorylated enzyme and thus allows extended interactions with mitotic recruiters to promote condensation. The overall negative charge of Smc4 may enhance the stability of the interaction between condensin and the positively charged residues of chromatin proteins, such as the N-terminal tails of histones 19. In contrast to allostery, bulk electrostatics seems simple, robust, and easy to evolve. Ion pairing through phosphorylated residues should allow for the generation of a decisive, ultrasensitive switch without the requirement for classical cooperativity 20-22. Notably, the global distribution of phosphorylated residues on a given protein domain, rather than the exact position of the phosphosite, would be important in defining the interaction. At present, there is little information on the extent to which this regulation is used in cells due to the lack of enrichment methods enabling the identification of multi-phosphorylated regions in proteins where peptides can contain more than two phosphorylation sites. Over the last decade, mass-spectrometry (MS) became a tool of choice to study protein phosphorylation. Its major strength lies in its ability to simultaneously identify and quantify tens of thousands phosphorylation sites from a minute amount of material

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. Standard "bottom-up"

approaches involve enzymatic digestion of proteins into smaller peptides, subsequent affinity 5 ACS Paragon Plus Environment


purification of phosphorylated peptides

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and their analysis by MS. These conventional experiments

mostly result in the identification of singly-phosphorylated and doubly-phosphorylated peptides with a small proportion of peptides containing three or more phosphosites. While other techniques enabled more efficient detection of multi-phosphorylated peptides

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, these have been mostly limited to the

detection of doubly- and triply- phosphorylated peptides. As conventional phosphoproteomic approaches do not typically detect multi-phosphorylated protein regions, our global understanding of bulk electrostatic interactions in cell signaling is limited to only few well-characterized examples. In this context, multisite phosphorylation may be thought of as phosphoproteomic dark matter that is likely to exist but eludes detection. Two major problems need to be addressed to detect multi-phosphorylated peptides. First, their lower abundance compared to mono- and doubly-phosphorylated peptides requires the development of an appropriate enrichment strategy. Secondly, the high number of phosphorylated residues present on the same peptide decreases their isoelectric point and renders the detection and MS sequencing of positively charged peptide ions significantly more challenging. Thus, even if we were able to purify multi-phosphorylated peptides, the propensity of multi-phosphorylated peptides to form negatively charged ions would prevent their successful large-scale identification by MS. In the present study, we develop a novel method for large-scale detection of multi-phosphorylated peptides that addresses both enrichment and MS-detection issues. Our strategy exploits a biphasic column that combines strong cation (SCX) and anion (SAX) exchange media to separate different populations of multi-phosphorylated peptides. This approach enables the separation of singly-, doubly and multi-phosphorylated peptides that can be subsequently dephosphorylated by alkaline phosphatase to facilitate detection by MS. We use this method to identify multisite phosphorylated regions on more


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than 300 proteins in the yeast and human proteome, and demonstrate a new role of multisite phosphorylation in the yeast mating pheromone response. EXPERIMENTAL SECTION Construction of yeast strains expressing ste20 phosphomutants The general strategy to construct the yeast strain expressing ste20-24D-HA from its endogenous locus is outlined in Ratsima et al.

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with small modifications. We introduced a HA tag on ste20-24D to further

investigate its biological impact in a separate study. Briefly, the ste20-24D allele was created by custom gene synthesis of a region of STE20 encoding residues 151 to 939 (Bio Basic Inc) and introduced as a BsiWI–PacI fragment into the corresponding sites of the pFA6a::3xHA::TADH1::HIS3MX6 plasmid 27. This gene-modifying construct was amplified by PCR using primers carrying 40 nt of homology to the endogenous STE20 locus 27 and introduced into wild-type W303 yeast by transformation. The ste20-24DHA allele carries the following mutations: S187D, S188D, T189D, S192D, S195D, S196D, T197D, T203D, S206D, T207D, S214D, T217D, T218D, S320D, S321D, S322D, S323D, S326D, S327D, S328D, S329D, S330D, T332D, and T333D. The ste20-24A mutant strain was created by consecutive rounds of integration of phosphosite mutations in the yeast genome (round 1: integration of S320A, S321A, S322A, S323A, S326A, S327A, S328A, S329A, S330A, T332A, T333A mutations / round 2: integration of S187A, S188A, T189A, S192A, S195A, S196A, T197A, T203A, S206A, T207A, S214A, T217A, T218A mutations). This was accomplished using STE20::TADH1::HIS3MX6 (round 1) and ste20-11A::TADH1::HIS3MX6 (round 2) selection cassettes as templates for PCR amplification and transformation of yeast. Phosphosite mutations were included in the sequence of the PCR primers. Integration of the ste20-24D-HA and ste20-24A mutations in the yeast genome was confirmed by sequencing the entire open reading frame (ORF) at the endogenous locus. Cell culture 7 ACS Paragon Plus Environment


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For mass spectrometry analyses, yeast cells (LYS1Δ::kanMX; ARG4Δ::kanMX strain) were grown in synthetic dextrose (SD, 0.17% yeast nitrogen base without amino acids, 0.5% ammonium sulfate 2% glucose and appropriate amino acids) supplemented with either light (Lys0/Arg0), medium (Lys4/Arg6) or heavy (Lys8/Arg10) lysine (30 mg/L) and arginine (20 mg/L) (Silantes GmbH). All cultures were grown to a density of OD600=0.7 prior to treatments/harvesting. Osmotic shock was performed over a period of 15 min by adding 1M NaCl to the cell culture to reach a final salt concentration of 0.4M, whereas control cultures were treated with vehicle (SD media). Cells were harvested by adding trichloro acetic acid (TCA) to a final concentration of 10% and centrifugation at 5,000 x g for 10 min. Subsequently cells were washed with ice-cold PBS and the SILAC channels were combined before cell lysis. HeLa cells were cultured in high glucose DMEM (Hyclone SH30081.02) supplemented with 10% fetal bovine serum, 1% L-glutamine and pyruvate until cells reached 95% confluency. Cells were harvested by centrifugation for 5 min at 2000 × g at 4 °C, washed in ice-cold phosphate buffered saline (PBS), snap frozen in liquid nitrogen and stored at −80 °C unMl further analysis. Cell cycle analysis Yeast cells were grown in liquid YPD medium at 23°C until they reached an OD600 of ~0.3. α factor (Bio Basic Inc) was then added to 50 ng/mL and cells were allowed to grow for an additional 180 min at 23°C and 37°C. Samples of cells were collected by centrifugation and the presence of buds on yeast cells was quantified on a Nikon Eclipse 50i microscope, as previously described

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. Differential interference

contrast (DIC) images of yeast cells were acquired on a Leica DM5500B microscope using Volocity software (Improvision, UK). Protein extraction and enzymatic digestion


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Cell pellets were resuspended in lysis buffer (8M urea, 40 mM CAA, 10 mM TCEP, 100 mM TRIS pH=8.5, supplemented with HALT phosphatase inhibitor cocktail (Thermo Fisher Scientific). Yeast cells were broken by bead beating for 1 x 5 min cycle. HeLa cells were sonicated. Lysates were centrifuged at 40,000 x g for 10 min, and the supernatants were transferred into clean tubes prior to determination of protein concentrations by BCA-RC assay (Thermo Fisher Scientific). Disulfide bonds were reduced by adding dithiothreitol to a final concentration of 5 mM and samples were incubated at 56 °C for 30 minutes. Reduced cysteines were alkylated by adding iodoacetamide to 15 mM and incubating for 30 minutes in the dark at room temperature. Alkylation was quenched with 5 mM dithiothreitol for 15 minutes. Samples were diluted 6-fold with 20 mM TRIS, pH 8.5 containing 1 mM CaCl2 prior to overnight digestion at 37oC with trypsin (Sigma-Aldrich) using an enzyme to substrate ratio of 1:100 (w/w). Tryptic digests were acidified with trifluoroacetic acid (TFA) to final 0.5% (v/v), centrifuged (20,000 x g 10 min) and desalted on Oasis HLB cartridges (Waters) according to manufacturer instructions. Peptide eluates were snap-frozen in liquid nitrogen, lyophilized in a speedvac centrifuge and stored at -80oC. Phosphopeptide isolation Tryptic digests were subjected to enrichment on TiO2 beads as described previously 28. Sample loading, washing, and elution steps were performed using custom StageTips

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made from 200 µL pipette tips

containing a C18 membrane (3M) frit and filled with TiO2 beads. We equilibrate TiO2 material in 250 mM lactic acid 70% acetonitrile (ACN) 3% TFA, the same buffer is used for sample loading. After extensive washing steps retained phosphopeptides were displaced from TiO2 with 500 mM phosphate buffer at pH:7. Peptides were desalted in 50 µL of 1% FA directly on C18 frits and subsequently eluted using 30 µL of 50% ACN 1% formic acid (FA). Eluates were dried in a speedvac and stored at -80oC. Fractionation of phosphopeptides on biphasic SCX/SAX columns.



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Biphasic columns were prepared by combining two StageTips containing four 14-gauge layers of SCX and two 14-gauge layers of SAX membranes (see Figure 2B). Prior to peptide fractionation the biphasic column was equilibrated with 30 uL 50% ACN 1% FA and 30 uL of 1M NaCl in loading buffer (10% ACN 0.2% FA) and 2x30 uL of loading buffer. Phosphopeptides were resuspended in 50 uL of loading buffer and loaded on the column, and washed with 30 uL of loading buffer. Flow through containing uncharged peptides was collected, dried on a speedvac and resuspended in 100 uL of 50 mM ammonium bicarbonate (ABC). The biphasic column was separated into SCX and SAX parts. SAX-retained peptides were eluted in 20 uL of 150 mM NaCl in loading buffer. SCX retained peptides were eluted in 20 uL of 50 mM ABC. SAX and SCX retained peptide fractions were diluted with 80 uL of 50 mM ABC. For enzymatic dephosphorylation each collected fraction was separated into two equal parts (2x50 uL). One part was treated with 10 units of alkaline phosphatase whereas the other part was used as a control. Dephosphorylation was performed for 4h at 37oC, samples were acidified with FA, desalted on StageTips containing C18 membranes and peptides were lyophilized on a speedvac centrifuge. β-elimination The procedure was adapted from Kyono et al

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. Briefly, all peptide samples collected after SCX/SAX

fractionation were dried on a speedvac, resuspended in 100 mM NaOH saturated with Ba(OH)2 and incubated for 1h at 37oC. Samples were acidified with FA and peptides were desalted on C18 StageTips. Prior to MS analyses eluates were dried on speedvac and resolubilized in 0.2% FA. Mass spectrometry Peptides were analyzed by LC-MS/MS using a Proxeon nanoflow HPLC system coupled to either tribrid Fusion or a Q-Exactive HF mass spectrometers (Thermo Fisher Scientific). Each sample was loaded and separated on a reverse-phase analytical column (18 cm length, 150 µm i.d.) packed manually with Jupiter C18, 3µm, 300 Å (Phenomenex). LC separations were performed at a flow rate of 0.6 μL/min using 10 ACS Paragon Plus Environment

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a linear gradient of 5-30 % aqueous ACN (0.2% FA) in 106 minutes. MS spectra were acquired with a resolution of 120,000 (AGC target 1e6, max fill time 200 ms). A top10 method was used for data dependent scans on the 10 most intense ions using high energy dissociation (HCD). AGC target values for MS and MS/MS scans were set to 1e6 (max fill time 200 ms). The precursor isolation window was set to m/z 1.6 with a HCD normalized collision energy of 25. The dynamic exclusion window was set to 40s. Data processing and analysis MS data were analyzed using MaxQuant

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software version 1.5.5.1 and searched against the

SwissProt subset of the S. cerevisiae/H. sapiens uniprot database (http://www.uniprot.org/) containing 6,630 /26,186 entries (June 2016). A list of 248 common laboratory contaminants included in MaxQuant was also added to the database as well as reversed versions of all sequences. The enzyme specificity was set to trypsin with a maximum number of missed cleavages set to 2. Peptide identification was performed with an initial precursor mass deviation up to 7 ppm and a fragment mass deviation of 20 ppm with subsequent non-linear mass re-calibration

33

. Phosphorylation of serine, threonine and

tyrosine residues was searched as variable modification; carbamidomethylation of cysteines was searched as a fixed modification. The false discovery rate (FDR) for peptide, protein, and site identification was set to 1% and was calculated using a decoy database approach. The minimum peptide length was set to 6, and the ‘peptide requantification’ function was enabled. The option match between runs (1 min time tolerance) was enabled to correlate identification and quantitation results across different runs. In addition to a FDR of 1% set for peptide, protein and phosphosite identification levels, we considered only phosphosites for which localization confidence was higher than 75%, except for multi-phosphorylated peptides detected after dephosphorylation. Relative quantification of the peptides against their heavy-labeled counterparts was performed with MaxQuant using area under 3D feature peak shapes.



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GO and PPI network analyses Gene ontology enrichment analyses were performed against whole S. cerevisiae/human proteomes as background using DAVID bioinformatics resources 34. All protein-protein interaction networks were built in STRING

35

. All interaction predictions were based on experimental evidences with the minimal

confidence score of 0.9, which is considered as the highest confidence filter in STRING. Results were visualized using Cytoscape 36. Data Availability The mass spectrometry raw data from this publication have been submitted to the Peptide Atlas database (http://www.peptideatlas.org/) and assigned the identifier PASS01164 (Password: GR962sm).


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RESULTS & DISCUSSION Enrichment of multi-phosphorylated peptides The detection of phosphorylated peptides from complex cell extracts is hampered by the presence of an overwhelming amount of non-phosphorylated peptides, and their successful identification requires prior sample enrichment

37, 38

. Similarly, abundant mono- and doubly-phosphopeptides must be depleted to

enhance the detection of multi-phosphorylated peptides. When using TiO2-affinity media, the number of identified peptides containing more than two phosphorylation sites in human and yeast cell extracts is typically 5% (Table S-1), consistent with that found in other studies (Figure S-1A). Current techniques targeting the enrichment of multi-phosphorylated peptides, such as SIMAC

25, 39

, mostly increase the

proportion of doubly-phosphorylated peptides (Figure S-1B). Our approach exploits the difference in peptide charge state to separate peptides into different populations of multiply-phosphorylated peptides (Figure 2A). In a simple charge counting model, tryptic peptides will typically be doubly-protonated at pH 3 with the charge localized at the N-terminal amino group and the C-terminal lysine or arginine residue. The introduction of a single phosphate group will decrease the net charge by 1. Thus, we can expect mono-phosphorylated peptides to be positively charged, doubly-phosphorylated peptides to be neutral and peptides containing three and more phosphosites to have a net negative charge. The presence of histidine residues or miscleavages can increase the charge state of the tryptic peptides while acetylation of amino groups (e.g. N-term acetylation) will reduce charge. However, for the large majority of peptides we can assume that fractionation on ion exchange media will be mostly affected by the number of phosphorylated residues.



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Figure 2. Enrichment of multi-phosphorylated peptides. (A) Scheme of the experimental workflow. After TiO2 phosphopeptide enrichment, desalted phosphopeptides are resolubilized in water-based buffer at acidic pH, and applied onto a biphasic column containing SCX and SAX media. Peptides with a positive net charge are retained on SCX beads, negatively-charged peptides are retained on SAX beads and peptides with no net charge are collected in the flow-through. Peptides are eluted from SAX and SCX with high-salt buffer and analyzed by LC-MS/MS either directly or after enzymatic dephosphorylation. (B) Biphasic spin column combine two StageTips with SCX and SAX frits that can be easily assembled. This design also allows for a seamless separation of SCX/SAX units for subsequent peptide elution.

Prior to ion exchange fractionation, phosphopeptides are desalted and resolubilized in 20% ACN solution containing 0.2% FA (pH 3). Subsequently, peptides are loaded on a biphasic column where positively charged ions are retained on the SCX beads, while negatively charged peptides including multiphosphorylated peptides are retained on the SAX beads, and peptides with no net charge are collected in the flow-through (FT). SCX and SAX microcolumns are separated, and captured peptides are eluted with a solution of increasing salt concentration. We use a StageTip 40, 41 approach whereby the two spin columns are inserted into each other (Figure 2B), allowing the flow through from SCX to be immediately transferred to the SAX column. This setup does not require expensive equipment and the entire procedure can be completed within ~30 min.


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We applied this method to expand the repertoire of the yeast phosphoproteome. We observed the highest number of identification in the SCX-retained fraction that contained mostly singlyphosphorylated peptides followed by FT and SAX fractions (Table S-2). Direct LC-MS/MS analysis of peptides retained on the SAX material indicated that the majority of identified peptides contained doubly- and triply-phosphorylation sites with a few peptides containing more than 3 phosphate groups (Figure 3A). The distribution of phosphorylated residues per peptide across the fractions (Figure 3B) and their corresponding charge state (Figure 3C) indicated a preferential retention of negatively charged species on the SAX beads. Similar results were obtained for the human HEK293 cell line (Table S-3 and Figure S-2) and casein peptides (Table S-4). Several of the multi-phosphorylated peptides were also confirmed by performing β-elimination under alkaline conditions to form the corresponding dehydro derivatives that were readily detectable by LC-MS/MS (Table S-2).



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Figure 3. SCX/SAX fractionation of phosphopeptides from S. cerevisiae cells. (A) The distribution of phosphosites in peptides retained on SAX material shows the enrichment of peptides with multiple phosphorylation sites but does not reveal peptides with > 5 phosphosites. The distribution of peptides across SCX, SAX and FT fractions based on the number of phosphosites (B) or their estimated net charge (C) shows the efficiency of SCX/SAX-based fractionation.

Enzymatic dephosphorylation obviates ionization/fragmentation issues that prevent the detection of multi-phosphorylated peptides. Although we observed the relative enrichment of doubly- and triply-phosphorylated peptides on SAX material, mass spectrometric analyses of these fractions did not identify a significant number of multiphosphorylated peptides. This can be explained in part by the reduced ionization efficiency of positivelycharged peptides containing multiple phosphorylation sites and their corresponding changes in retention on reverse phase media 37, 42. Furthermore, we also noticed that the mean identification score


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of phosphopeptides gradually decreased with the number of phosphorylation sites adding to the difficulty of identifying multi-phosphorylated peptides (Figure S-3). The different phosphopeptide fractions obtained from the SCX/SAX fractionation were next treated with alkaline phosphatase. While enzymatic dephosphorylation slightly increased the number of identifications for SCX and FT fractions, we observed a 3-fold increase in the number of identified peptides retained on the SAX column (Figure 4A and Table 1). Table 1. Number of identified peptides across SCX, SAX and FT fractions before (ctrl)/after dephosphorylation with alkaline phosphatase (ap). pSites p0 p1 p2 p3 p4 p5 Total:

SCX_ap 5679 215 15 2 0 0

SCX_ctrl 244 3273 1575 415 63 9

FT_ap 1151 55 2 1 0 0

FT_ctrl 400 260 295 21 1 0

SAX_ap 1952 190 10 4 0 0

SAX_ctrl 114 174 258 223 38 2

5911

5579

1209

977

2156

809

These new identifications likely arose from phosphorylated peptides retained on both TiO2 beads and SAX media although they were not efficiently detected by LC-MS/MS in positive ion mode unless treated with alkaline phosphatase. These results suggest the presence of highly phosphorylated peptides in the SAX fraction. Importantly, peptides detected only after enzymatic dephosphorylation contained Ser/Thrrich regions, a feature that was not observed for peptides obtained from dephosphorylated SCX and FT fractions (Figure 4B). GO-term analysis of SAX peptides released upon alkaline phosphatase revealed an enrichment in proteins associated with the plasma membrane and proteins interacting with RNA and DNA, consistent with the notion of bulk electrostatic interactions expected from these protein groups (Figure 4C). Similar results were also observed for phosphopeptides from HEK293 cells fractionated by SCX/SAX and treated with alkaline phosphatase (Figure S-4). 17 ACS Paragon Plus Environment


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Figure 4. Alkaline phosphatase treatment of phosphopeptides from SCX/SAX-fractions of S. cerevisiae. (A) Dephosphorylation of peptides retained on SCX and FT fractions resulted in a small increase in new identification in contrast to peptides retained on SAX beads. (B) Newly identified peptide sequences upon dephosphorylation of SAX-retained fraction contained a significantly higher number of serine and threonine residues compared to peptides identified by MS prior to dephosphorylation. These serine and threonine residues tend to form large clusters. (C) Gene ontology enrichment analysis shows that the corresponding protein targets are enriched in terms associated with interactions with plasma membranes and DNA/RNA-related processes.


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In order to estimate the proportion of serine regions in the proteome identified with our approach we performed an in silico digestion of the yeast proteome (Figure S-5). In our experiment, we were able to detect 267 Ser/Thr-rich peptides whereas in-silico digestion resulted in 1018 Ser/Thr-rich peptides (Ser+Thr >10). The fact that we captured ~ 30 % of all Ser/Thr-rich peptides was promising as we expected that not all Ser/Thr -rich regions would be phosphorylated and therefore not amenable to our fractionation. We also observed that identified multi-phosphorylated protein targets are of higher abundance compared to the distribution of all Uniprot entries containing Ser/Thr-rich regions (Figure S6). Multisite phosphorylation events in cell signaling To determine if the regulation of multisite phosphorylation was affected by environmental stimuli we performed quantitative phosphoproteomic analyses on yeast cells following osmotic shock. Changes in the phosphoproteome were quantified after 15 min treatment with 0.4M NaCl. After protein digestion and enrichment on TiO2 resin, phosphopeptides were fractionated on the biphasic SCX/SAX columns and treated with alkaline phosphatase to quantify changes in the abundance of mono (SCX) and multiphosphorylated (SAX) phosphopeptide pools. All experiments were performed with six independent treatments and used SILAC for accurate quantification (Table S-5). These analyses revealed that the percentage of peptides significantly affected by the treatment was comparable between mono- and multi-phosphorylated peptides, supporting the notion that both phosphopeptide groups were affected similarly by the treatment (Figure 5A). Interestingly, the overlap in identification between both groups of phosphopeptides was relatively small suggesting that complementary groups of proteins were affected (Figure 5B and Figure S-7). Therefore detection of multi-phosphorylated peptides can uncover additional biological targets that would be missed by conventional phosphoproteomic approaches.



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Figure 5. Dynamics of yeast phosphoproteome upon osmotic shock. (A) Proportion of regulated phosphopeptides are similar between mono (SCX) and multi-phosphorylated (SAX) groups suggesting that osmotic shock affects these two groups in a comparable manner. (B) Network of regulated phosphoproteins revealed that the overlap of protein targets affected by osmotic shock is different amongst mono (SCX) and multi-phosphorylated (SAX) groups and suggests that complementary targets are identified by this approach. 20 ACS Paragon Plus Environment

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The majority of the multi-phosphorylated protein targets affected by osmotic stress are known membrane interactors. Particularly, we observed the dephosphorylation of adenylate cyclase Cyr1 required for cAMP-dependent signaling 43. Previously, we showed that osmotic stress affects clathrinmediated endocytosis, CME 44. Our approach enabled the detection of several key mediators of CME (Ede1, Pan1, Sec16, Pal1, Sfb3) that are regulated by multisite phosphorylation 45. We also identified several putative multi-phosphorylated targets involved in septin formation and cytokinesis such as the kinase Kic1

46, 47

from the PAK/Ste20 family, required for cell integrity. This kinase physically interacts

with Cdc31 (centrin), a component of the spindle pole body, to promote its phosphorylation. We also noted the dephosphorylation of protein phosphatase Z (Ppz2) upon osmotic shock. Ppz2 is involved in the regulation of potassium transport, which affects osmotic stability, and is essential for the maintenance of cell size and integrity in response to osmotic stress 48-50.

Multisite phosphorylation of Ste20 negatively regulates signaling in the mating pheromone pathway To provide further functional insights into the role of multisite phosphorylation of identified targets we conducted site-directed mutagenesis on Ste20. This protein is a member of the p21-activated kinase (PAK) family of serine/threonine protein kinases that also includes Cla4, and Skm1. PAK kinases play important roles in signal transduction, polarized growth, and cell cycle control 51, 52. Ste20 is perhaps the best understood effector of Cdc42, a small GTPase involved in the regulation of cellular polarity in eukaryotic cells

53, 54

. In yeast, Ste20 regulates multiple mitogen-activated protein kinase (MAPK)

pathways that control mating, filamentous growth, the osmotic stress response, cell polarization and cell cycle control

51, 52

. In the mating pathway, Ste20 activates the MAPK cascade signaling when the

mating pheromones α-factor and a-factor bind to G protein coupled receptors Ste2 and Ste3 respectively in the plasma membrane 55. The receptor-activated Gβγ dimer binds Ste20

56

and recruits



Page 22 of 33

the scaffold protein Ste5 to the plasma membrane57, allowing Ste20 to be phosphorylated by Ste5associated kinases that eventually trigger cell cycle arrest, transcription of mating genes, and polarized morphogenesis. Ste20 is recruited to sites of polarized cell growth, such as the tips of buds and mating projections, via binding of its CRIB domain to Cdc42 58-60. Localization and function of Ste20 is critically dependent on a short membrane-binding basic rich domain (BR) in the Ste20 N-terminus that promotes the proper polarized localization of Ste20 61. This membrane-binding domain is required for Cdc42-dependent regulation of Ste20 and for the in vivo function of the kinase in both MAPK-dependent and -independent pathways. Intriguingly, our dataset revealed the existence of a previously unrecognized phosphorylation-rich region in Ste20, adjacent to its BR domain (Figure 6A). We hypothesized that multisite phosphorylation of this region could affect Ste20 interaction with the plasma membrane either through electrostatic repulsion or intramolecular occlusion of the BR domain.


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Figure 6. Multisite phosphorylation of Ste20 and regulation of the pheromone signaling pathway. (A) Cartoon depiction of Ste20 regulation at the plasma membrane. Different domains of Ste20 are colorcoded to facilitate visualization, and boxed residues indicate Ser/Thr rich regions. (B) Morphology of STE20 and ste20-24D cells after exposure to α factor (50 ng/ml for 180 min). (C) Quantification of cell morphology in cultures of yeast expressing wild-type (D6310, D6311) and phosphomimetic (D6289, D6291) alleles of STE20-HA. Exponential cultures of yeast cells were treated with α factor for 180 min at the indicated temperatures prior to morphology assessment. Two independent clones were analysed for each genotype and experiments were conducted in triplicates. (D) Phospho-ablating mutations in STE20 have no detectable effects on α factor-induced cell cycle arrest. Quantification of cell morphology and α factor treatment are the same as in panel C. Strains used are D4107 (STE20) and D6171 (ste20-24A). For all experiments, n = 100 cells per condition and error bars represent S.D. Note that differences in the extent of cell cycle arrest observed with wild-type strains in panels C and D reflect the fact that HAtagged alleles were used in panel C, which partially reduces Ste20 activity.

To test this hypothesis, we constructed a phosphomimetic mutant of Ste20 where all the phosphorylatable residues in the serine-rich region adjacent to its BR domain were changed to aspartic acid residues. Cells carrying this allele, ste20-24D, were then tested for their ability to transduce signal in the mating pheromone pathway. To achieve this, exponential cultures of STE20-HA and ste20-24D-HA



Page 24 of 33

cultures were exposed to α factor (50 ng/ml) for 180 min and cell morphology was monitored by light microscopy at 23°C and 37°C. Cells that efficiently respond to the α factor signal induce a cell cycle arrest in G1 and acquire a typical unbudded morphology associated with a mating projection, termed a shmoo

62

. This cell cycle arrest leads to a dramatic reduction in the fraction of budded cells in the

population, as we observed in a culture of cells carrying wild-type STE20-HA (Figures 6B-C). While exposure of ste20-24D-HA mutants to α factor resulted in a normal response to mating pheromone at 23°C (i.e., < 10% budded cells; Figures 6B-C), we observed a striking defect in the ability of the phosphomimetic mutant to induce cell cycle arrest at 37°C. The temperature-sensitive behavior of ste20-24D likely reflects the fact that the mutant protein has enough basal activity to maintain pheromone signaling at 23°C, but challenging cells with a temperature stress further inactivates the mutant protein below a minimal activity threshold required to maintain cellular function. Indeed, the ste20-24D-HA cell population continued cycling at 37°C despite the presence of α factor in the culture medium and showed a 50-60% fraction of budded cells under this condition, a figure close to that normally seen in an exponentially-growing culture of yeast cells (Figure 6B-C). These results suggest that phosphomimetic substitutions adjacent to the BR domain of Ste20 compromise its ability to transduce signal in the mating pheromone pathway. However, it is also possible that mutation of these 24 Ser residues does not act by mimicking phosphorylation, but affect instead Ste20 activity in a non-specific manner at 37°C. If this hypothesis is correct, one would predict that mutating the same amino acid positions of Ste20 to alanine –a residue similar in size to aspartic acid but lacking phosphomimetic properties– should phenocopy ste20-24D-HA behavior. To test this notion, we constructed a ste20-24A mutant and monitored its ability to respond to α factor at 23°C and 37°C. This mutant induced a strong cell cycle arrest following exposure to α factor, as evidenced by the accumulation of cells in G1 (and corresponding reduction in the budded fraction, Figure 6D). Importantly, the α factor-induced cell cycle arrest of the ste20-24A mutant occurred at both 23°C and 37°C, indicating that it is not temperature 24 ACS Paragon Plus Environment

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sensitive like the phosphomimetic allele. Taken together, these results indicate that the phenotype of the ste20-24D mutant reflects the phospho-mimetic nature of the amino-acid substitutions in this protein, and that the physiological role of Ste20 multisite phosphorylation is to negatively regulate signaling in the mating pheromone pathway.



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CONCLUSION This study highlights the development of a simple affinity method that can be seamlessly integrated into any conventional phosphoproteomic workflow to facilitate the large-scale detection of peptides that contain multi-phosphorylated regions. We showed the broad applicability of this approach to both human and yeast phosphoproteomes, and demonstrated that this strategy can also be applied to quantitative phosphoproteomics to profile changes in the abundance of multi-phosphorylated proteins, such as that shown here for osmotic shock. While the alkaline phosphatase treatment of fractions containing

multi-phosphorylated

peptides

enhance

the

detection

of

their

corresponding

dephosphorylated counterparts, it is important to note that the precise number and location of modified residues cannot be established with certainty. The assignment of phosphorylated residues from these Ser/Thr-rich regions would require alternative approaches such as β-elimination/Michael addition 63, 64. A comparison of our putative multi-phosphorylated peptides with in silico digestion of the yeast Uniprot database indicated that our dataset contains close to 30% of all the peptides containing Ser/Thr-rich regions. Since not all Ser/Thr-rich regions are anticipated to be phosphorylated, the enhanced detection of multi-phosphorylated peptides using a biphasic column provides a meaningful approach to explore unchartered territories in phosphoproteomics. We expect that further enhancement of multiphosphorylated peptides detection could be achieved through off-line fractionation (e.g. high pH-RP, or preparative SAX fractionation) prior to LC-MS/MS analysis. Importantly, our study unveiled the unsuspected multisite phosphorylation of plasma membrane proteins and proteins interacting with RNA and DNA where bulk electrostatic interactions are likely to play important roles in regulation of protein interactions. We further demonstrated the role of multisite phosphorylation in Ste20, a member of the PAK family proteins required for the mating pheromone 26 ACS Paragon Plus Environment

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response in yeast. Mutagenesis experiments with Ala and Asp substitutions on C-terminus Ser/Thr-rich regions next to the short membrane-binding basic rich domain confirmed that multisite phosphorylation of Ste20 negatively regulate signaling in the mating pheromone pathway. We anticipate that this approach will expand the breath of phosphoproteome analyses, and will shed light on phosphophoproteomic “dark matter” to gain further insights into the biological role of bulk electrostatic interactions.



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Supporting Information Supporting information contains Figures S1-7 and Tables S1-5. The following supporting information is available free of charge at ACS website http://pubs.acs.org Figure S1. Detection of protein multiphosphorylation by MS. Figure S2. Phosphopeptide SCX/SAX fractionation from HEK293 cells. Figure S3. Variation of Andromeda identification score for phosphopeptides. Figure S4. Dephosphorylation of phosphopeptides from SCX/SAX-fractions of protein extracts from HEK293 cells using alkaline phosphatase. Figure S5. Detection of ST-rich peptides: in-silico vs. experiment. Figure S6. Abundance of detected multi-phosphorylated protein targets vs. proteome. Figure S7. Overlap in protein targets regulated by monophosphorylation (SCX) and multiphosphorylation (SAX). Table S1. Representative results of conventional phosphoproteomics. Table S2. SCX/SAX fractionation of S. cerevisiae peptides. Table S3. SCX/SAX fractionation of HEK293 peptides. Table S4. SCX/SAX fractionation of casein peptides. Table S5. SCX/SAX fractionation and SILAC quantification of S. cerevisiae peptides from the cells stimulated with osmotic stress.


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ACKNOWLEDGMENTS This work was supported by Canada Research Chairs in Proteomics and bioanalytical mass spectrometry (PT), in Systems and Synthetic Biology (MT) and in Chromatin Dynamics & Genome Architecture (DD), and by grants from the Genome Canada Genomics innovation network (PT,MT); the National Science and Engineering Research Council (311598, PT); the Canadian Institutes for Health Research (MOP 119572 to MT, MOP 82912 & 136788 to DD, PJT 148969 to DD and PT). The Institute for Research in Immunology and Cancer (IRIC) receives infrastructure support from IRICoR, the Canadian Foundation for Innovation, and the Fonds de Recherche du Québec - Santé (FRQS).

Conflict of Interest Disclosure The authors declare no competing financial interest.

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