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Title: Modulation of the chromatin phosphoproteome by the Haspin protein kinase Alessio Maiolica1, Maria De Medina Redondo2, Erwin M. Schoof3, Apirat

Chaikuad4, Fabrizio Villa5, Marco Gatti6, Siva Jeganatgan7, Hua Jane Lou8,

Karel Novy1, Simon Hauri1, Umut H. Toprak2, Franz Herzog9 Patrick Meraldi2,

Lorenza Penengo6, Benjamin E. Turk8, Stefan Knapp4, Rune Linding3, Ruedi

Aebersold1,10 1Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland. 2Department of Physiology and Metabolism, Faculty of Medicine, University of Geneva, Geneva, Switzerland 3Cellular Signal Integration Group (C-SIG), Center for Biological Sequence Analysis (CBS), Department of Systems

Biology, Technical University of Denmark (DTU), Lyngby, Denmark. 4Oxford University, Nuffield Department of Clinical Medicine, Target Discovery Institute (TDI) and Structural

Genomics Consortium (SGC), Oxford OX3 7FZ, United Kingdom. 5Department of Experimental Oncology, European Institute of Oncology, Milan, Italy 6Department of Pharmaceutical Sciences, University of Piemonte Orientale “A. Avogadro” Novara, Italy 7Department of Mechanistic Cell Biology, Max Planck Institute of Molecular Physiology, Dortmund, Germany 8Yale University School of Medicine, Department of Pharmacology, New Haven, CT 06520, USA 9Gene Center Munich Ludwig-Maximilians-Universität München, Munich, Germany 10Faculty of Science, University of Zurich, Zurich, Switzerland

Running title: Chromatin phosphoproteome modulation by Haspin kinase Corresponding author: Prof. Ruedi Aebersold

Department of Biology,

Institute of Molecular Systems Biology

HPT E 51

Auguste-Piccard Court 1

CH- 8093 Zurich

SWITZERLAND

Fax: +41 44 633 10 51

E-Mail: aebersold@imsb.biol.ethz.ch

Keywords: Haspin, GSG2, kinase substrates, phosphoproteomic, in vitro kinase reaction

MCP Papers in Press. Published on April 14, 2014 as Manuscript M113.034819

Copyright 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

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Abstract

Recent discoveries have highlighted the importance of Haspin kinase activity

for the correct positioning of the kinase Aurora B at the centromere. Haspin

phosphorylates Thr3 of the histone H3 (H3), which provides a signal for

Aurora B to localize to the centromere of mitotic chromosomes. To date

histone H3 is the only confirmed Haspin substrate. We used a combination of

biochemical, pharmacological and mass spectrometric approaches to study

the consequences of Haspin inhibition in mitotic cells. We quantified 3964

phosphorylation sites on chromatin-associated proteins and identified a

Haspin protein-protein interaction network. We determined the Haspin

consensus motif and the co-crystal structure of the kinase with the histone H3

tail. The structure revealed a unique bent substrate binding mode positioning

the histone H3 residues Arg2 and Lys4 adjacent to the Haspin phosphorylated

threonine into acidic binding pockets. This unique conformation of the kinase-

substrate complex explains the reported modulation of Haspin activity by

methylation of Lys4 of the histone H3. In addition, the identification of the

structural basis of substrate recognition and the amino acid sequence

preferences of Haspin aided the identification of novel candidate Haspin

substrates. In particular, we validated the phosphorylation of Ser137 of the

histone variant macroH2A as a target of Haspin kinase activity. MacroH2A

Ser137 resides in a basic stretch of about 40 amino acids that is required to

stabilize extranucleosomal DNA, suggesting that phosphorylation of Ser137

might regulate the interactions of macroH2A and DNA. Overall, our data

suggest that Haspin activity affects the phosphorylation state of proteins

involved in gene expression regulation and splicing.

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Introduction

Eukaryotic protein kinases (ePK) constitute a large family of enzymes that

coordinate virtually any cellular processes by the phosphorylation of their

target proteins at specific sites (1, 2). Active kinases often modulate the

activity other enzymes, including other kinases, thus amplifying and extending

an initial signal that affect sometimes thousands of proteins (3). This creates a

highly complex network of feedback and forward loops where multiple kinases

can mutually influence each other’s activity. Kinases adopt three molecular

strategies to select and specifically phosphorylate their substrates in the

crowded environment of a cell (2). First, tight control of cellular kinase

localization assures that only proteins present in the close proximity of the

kinase can be phosphorylated; second, the kinase specific activity can be

regulated via post-translational modifications or the recruitment of cofactor

molecules; and third, the recognition of specific consensus motifs on

substrates ensures that phosphorylation only occurs at the intended site/s (2).

The Haspin kinase is a member of the ePK family that structurally diverges

from most ePK’s (1, 4). The Haspin kinase domain displays structural features

that have never been observed in other ePK family members (5, 6).

Specifically, the possibility of activation loop phosphorylation, a frequent

regulatory mechanisms to control kinase activity, is absent in Haspin (5).

Haspin is characterized by an active conformation that is stabilized by a

hydrophobic lock of the helix aC inducing a stable S conformation of the

structurally unique activation segment. These specific structural features also

create a structurally diverse substrate binding site comprising a highly

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electronegative cleft for the histone H3 basic tails (5). Interestingly, the

recognition of H3 has been shown to be modulated by methylation at H3

residue Lys4, thus coupling Haspin activity with epigenetic mechanisms of

chromatin regulation (5). Histone H3 which is phosphorylated at Thr3 is so far

the only well-characterized Haspin substrate (7). H3Thr3 phosphorylation

(H3Thr3ph) is required for the localization of Aurora B at the centromere (8-10).

Inactivation of Haspin catalytic activity by ATP mimetic inhibitors induces

Aurora B centromeric delocalization, leading to a loss of phosphorylation in

chromatin associated Aurora B substrates (11, 12). To date, apart from this

well-characterized centromeric function of Haspin activity, the broader cellular

functions of the kinase and the phosphorylation events that control these

remain essentially unknown.

In this study we used an integrated biochemical, proteomic, pharmacologic

and structural biology approach to study the Haspin kinase, its substrates and

the cellular consequences of its activity. Specifically, we determined a new

mode of kinase substrate binding and identified a Haspin kinase substrate

recognition motif. We identified 3964 phosphorylation sites in chromatin-

associated proteins, quantified their response to Haspin inhibition, and verified

the mitotic phosphorylation of MacroH2A Ser137 (13) as directly dependent by

Haspin activity. Altogether our data suggest that Haspin regulates the

phosphorylation of proteins involved in mechanisms that control gene

expression, including the modifications of histones, and provide evidence for

novel molecular effects of Haspin activity on mitotic chromatin.

Experimental Procedures

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Reagents

Chemicals of the highest available purity were purchased from Sigma- Aldrich

unless otherwise stated. The Haspin inhibitor 5-iodotubercidin (5-ITu) (5, 6)

was obtained from Cayman Chemical.

Haspin and CENP-T proteins production and purification

Haspin452–798 catalytic domain fragment was purified as previously reported

(5).

Sequence encoding N-terminal CENP T fragment (2–101) was PCR amplified

and cloned in the first cassette of pGEX-6P-2rbs, a di- cistronic derivative of

pGEX-6P vector generated in-house. The veracity of construct was confirmed

by sequencing. For the protein expression, BL21(DE3) Rossetta cells

containing the pGEX CENP T101 plasmid were grown in Terrific broth at 37°C

to an OD600 of ∼0.8. Cells were induced for expression with the addition of

0.25 mM ITPG at 20°C, and were incubated overnight. Cell pellets were

resuspended in buffer A (25 mM Tris/HCl, pH 8.0, 300 mM NaCl, 10% [vol/vol]

glycerol, and 2 mM dithioerythritol) plus protease inhibitor cocktail. Then, cells

were lysed by sonication, and cleared by centrifugation at 85,000 g for 60 min.

The cleared lysate was incubated with GST beads (GE Healthcare) pre-

equilibrated with buffer A and incubated for ~4 h. Beads were washed 3 times

with buffer A and the bound protein was cleaved from GST fusion with

overnight incubation of PreScission protase. The eluate was applied to a

Heparin HP (GE Healthcare) column preequilibrated in the same buffer.

Elution of bound protein was achieved by a linear gradient from 300 to 1000

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mM NaCl in 20 bed column volumes. The protein fractions were pooled and

concentrated in 3-kD molecular mass cut-off Vivaspin concentrators

(Sartorius). The concentrated protein was subjected to final purification step

on a Superdex 200 10/300 column (GE Healthcare) equilibrated in size-

exclusion chromatography buffer (25 mM Tris/HCl, pH 8.0, 150 mM NaCl, and

1 mM DTE). Eluted protein fractions were analyzed by SDS-gel and fractions

containg CENP T101 were pooled, concentrated, flash-frozen in liquid N2, and

stored at !80°C.

Cell culture

HeLa cells used for chromatin purification were grown in Dulbecco’s modified

Eagle’s medium (DMEM, Invitrogen) supplemented with 10% fetal bovine

serum (FBS, Hyclone) and antibiotics. 293T cells were grown in DMEM

supplemented with 10% fetal bovine serum (GIBCO) and 2 mM L-Glutamine.

Nocodazole was used at concentrations of 3.3 µM and 0.33 µM, for 1-hour

arrest or 16-hours arrest, respectively.

Mitotic chromatin preparation

Chromatin samples were prepared as previously reported (14). Briefly, HeLa

cells were arrested in mitosis with 0.33 µM nocodazole for 16 hours and

successively treated with the proteasome inhibitor MG132 for 30 min. The

Haspin inhibitor 5-ITu was added for 1.5 hours and successively mitotic cells

were harvested by mitotic shake-off in cell growing medium. Cells were

centrifuged at 1000 rpm 3 minutes, resuspend in 10 mL of cold PBS and

placed on ice for 45 minutes. The cell suspension was then centrifuged at

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3000 rpm for 10 minutes in a 4 ºC cold centrifuge. The cell pellet was

resuspended in a hypotonic buffer containing 50 mM NaCl, 5 mM HEPES pH

7.4, 5 mM MgCl2, 0.5 mM CaCl2, 0.1 mM PMSF and phosphatase and

protease inhibitors (Roche). After, the cell suspension was immediately

centrifuged for 10 min and the cell pellet was lysed in 4 ml of the hypotonic

buffer with the addition of 0.5% NP-40 and 1 mM PMSF. Cell lysis was

achieved using homogenizer (15 mL Wheaton) and 12 gentle complete

strokes. Sodium deoxycholate (to 0.1% final concentration) was successively

added to the cell solution and other 24 additional strokes were performed. The

cell extract was then transferred to a 15 ml tube (BD, Biosciences) and spun

down at 400 rpm for 10 minutes at 4ºC. The supernatant was collected and

centrifuged through 4 mL of 40% sucrose cushion at 2400 rpm for 30 min in a

4 ºC cold centrifuge. The mitotic chromosomes present in the pellet were first

washed three times with 500 µl of lysis buffer and, successively resuspended

in a solution containing 8M UREA and 0.1% RapiGest (Waters) and sonicated

at 4 ºC three times for 1 min with 3 min pause.

Immunofluorescence and antibodies

For immunofluorescence (IF) analysis HeLa cells were plated onto acid-

treated coverslips. Chromatin sample preparations for IF analysis were

centrifuged at 2500 rpm for 30 minutes over a 2.5 mL, 40% sucrose solution

onto an acid-treated coverslip.

Samples were fixed at room temperature for 10 min in PTEMF buffer (0.25%

TritonX-100, 20 mM PIPES pH 6.8, 1 mM MgCl2, 10 mM EGTA and 4%

formaldehyde). The following antibodies were used: human CREST (1/400;

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Antibodies Incorportated). Mouse anti-phospho-H3 Ser10 (1/1000, Abcam)

rabbit monoclonal anti-phospho CENP-A Ser7 (1/2000; Upstate

Biotechnology), rabbit anti-AuroraB (1/2000)(15). Cross-adsorbed secondary

antibodies (Invitrogen) were used. 3D image stacks of mitotic cells were

acquired in 0.2 µm steps using a 60x oil-immersion NA 1.3 objective on an

Olympus DeltaVision microscope (Applied Precision, LLC) equipped with a

DAPI/FITC/Rhod/CY5 filter set (Chroma) and a CoolSNAP HQ camera

(Roper-Scientific). The three dimensional image stacks were deconvolved

with SoftWorx (Applied Precision, LLC).

Histone acidic extraction and Western Blot

293T cells used for acidic extraction of nucleosomal histones were transfected

both with Haspin and empty plasmids using calcium phosphate method as

reported before (16). Cellular extracts (80 to 150 µg) were separated on SDS–

polyacrylamide gel electrophoresis and transferred overnight at 4°C onto a

polyvinylidene difluoride membrane (Amersham Pharmacia Biotech).

Membranes were blocked for 40 min in 5% dry milk in Tween–tris-buffered

saline (TTBS) and incubated overnight at 4°C with a primary antibody diluted

in TTBS containing 1% bovine serum albumin.

Identification of Haspin consensus motif

Phosphorylation motif determination by peptide library array screening was

performed as described by Mok et al. (17). The array consisted of 200

peptides with the general sequence YAXXXXX-S/T-XXXXAGKK(biotin),

where X is an equimolar mixture of the 17 amino acids excluding Cys, Ser

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and Thr, arrayed in a microtiter plate. In each well, the peptide mixture had

one of the X positions fixed as one of the 20 unmodified amino acids or

phosphoThr or phosphoTyr. Peptides (50 "M) were incubated with 200 or 400

nM Haspin in 50 mM Tris (pH 7.5), 10 mM MgCl2, 150 mM NaCl, 1 mM

EDTA, 1 DTT, 0.1% Tween 20, and 50 "M ATP with 0.03 "Ci/"l [g-33P]ATP

for 2 hours at 30 ºC. Aliquots (200 nl) were then spotted onto a streptavidin

membrane, which was washed, dried and exposed to a phosphor screen as

described. Radiolabel incorporation into peptides was quantified using

QuantityOne software (BioRad). Date from two runs were normalized and

averaged to generate the position-specific scoring matrix for use with

NetPhorest.

Computational prediction of Haspin substrates with the NetPhorest

algorithm

For the computational predictions of possible Haspin targets, we deployed an

updated version of the NetPhorest algorithm, which can predict substrates for

222 kinases in the human kinome (17). As input data for the predictions, we

used an in-house curated database (KinomeXplorer-DB), which collects

known phosphorylation sites from public resources such as Phospho.ELM

(18), PhosphoSitePlus (19) and PhosphoGRID (http://www.phosphogrid.org/).

In the current version, there are 64,232 phosphorylation sites available, for

each of which we predicted the most likely phosphorylating kinases. From

these predicted kinases, we filtered the phosphorylation sites for which

Haspin was a predicted kinase, and set a probability cutoff of 0.1, which

should equate to a false-positive rate of maximum 10%. These results were

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subsequently used as input for follow-up experiments. From the perturbation

experiments, the observed and quantified phosphorylation sites were used as

input for NetPhorest predictions, in order to determine which phosphorylation

sites are potential Haspin substrate sites based on their sequence motif.

Again, predictions were filtered for best scoring kinases and a cutoff of 0.1

was applied to maintain high accuracy.

In vitro kinase assays

Kinase reactions were carried out in a solution containing 50 mM Tris (pH

7.6), 10 mM MgCl2, 150 mM NaCl, 1 mM EDTA, 1 mM DTT. The peptides

used as Haspin substrates were chemically synthetized by On-SPOT

synthesis (JPT) (20), histones H3 and H2A were obtained form Roche and

New England BioLabs, respectively.

Final substrate concentrations in the assay were 250 µM ATP (5 µCi of #-

32ATP for SDS page only), 5 µM of histones H3 and H2A (Roche), and 5 nM

Haspin kinase. Reaction were initiated by the addition of ATP and carried out

at 30 °C for 15 min and finally terminated by adding SDS/PAGE loading buffer

or UREA 8M for the protein samples that were successively analyzed by

mass spectrometry. Assay reactions were then separated on a 15%

SDS/PAGE gel and the amount of transferred phosphate was visualized by

autoradiography or processed for mass spectrometry analysis.

Crystallization, data collection and structure determination

Recombinant Haspin (aa 465-798) was purified as described (6). The protein

was concentrated to 15 mg/mL for crystallization studies. The protein was pre-

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incubated with 1 mM iodotubercidin and 3 mM histone H3 peptide (aa 1-11;

ARTKQTARKSTY), and the complex was crystallized by sitting drop vapour

diffusion at 4 ˚C using the reservoir condition containing 20% PEG 3350, 0.2

M KSCN. Suitable crystals were cryo-protected with mother liquor

supplemented with 20% ethylene glycol and 2.2 mM peptide before flash-

cooled in liquid nitrogen. Diffraction data were collected in-house on a Rigaku

FRE SuperBright source, and processed and scaled with MOSFLM and Scala

from CCP4 suite (21). The complex crystals belonged to a primitive

orthorhombic P212121 spacegroup with a unit cell dimension of a = 50.5, b =

79.1, c = 100.8 Å, $=%=#= 90˚. Structure determination was achieved by

molecular replacement using PHASER (22) and the previously published

Haspin coordinates (6) as a search model. The structure was subjected to

iterative cycles of manual model re-building in COOT (23) alternated with

refinement using REFMAC (24). Geometric correctness of the final model was

verified with MOLPROBITY (25). Data collection and refinement statistics are

summarized in table S8.

Sample preparation for mass spectrometry analysis

For each condition, ten 15-cm dishes of Hela cells were grown to ~80%

confluence and treated with 1 µM 5-ITu. Chromatin proteins were prepared as

described before.

Protein digestion

Disulfide bonds were reduced with TCEP (Thermo) at a final concentration of

10 mM at room temperature for 1 hour. Free thiols were alkylated with 10 mM

iodoacetamide at room temperature for 30 min in the dark. The solution was

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subsequently diluted with 50 mM ammonium bicarbonate (AMBIC) (pH 8.3) to

a final concentration of 1.0 M urea, 0.1% RapiGest (Waters) and digested

overnight at 37°C with sequencing-grade modified trypsin (Promega) at a

protein-to-enzyme ratio of 50:1. Peptides were desalted on a C18 Sep-Pak

cartridge (Waters) and dried under vacuum. Phosphopeptides were isolated

from 300-500 µg of total peptide mass with TiO2 as described previously (26).

Briefly, the dried peptides were dissolved in an 80% acetonitrile (ACN) 3.5%

trifluoroacetic acid (TFA) solution saturated with phthalic acid. The peptides

were eluted twice with 150 µl 1% NH4OH.

Sample preparation for phosphoproteomics

Chromatographic separation of peptides was carried out with an Eksigent

(Eksigent Technologies) and Proxeon (Proxeon Biosystems) NanoLC system

connected to a 15-cm fused-silica emitter with 75-µm inner diameter (BGB

Analytik) packed in-house with a Magic C18 AQ 3-µm resin (Michrom

BioResources). The phosphopeptide samples were analyzed by LC–tandem

MS (LC- MS/MS) run with a linear gradient ranging from 95% solvent A (98%

H20,2% acetonitrile, 0.1% formic acid) to 35% solvent B (98% acetonitrile, 2%

H2O, 0.1% formic acid) over 90 min at a flow rate of 300 nl/min. Shorter

gradients of 60 min were instead used for, identification of Haspin binding

partners and in vitro kinase reactions on peptide and proteins. Mass

spectrometric analysis was performed with a LTQ-Orbitrap XL mass

spectrometer (Thermo Scientific) equipped with a nanoelectrospray ion

source (Thermo Scientific). Mass spectra were acquired in a data-dependent

manner, with an automatic switch between MS and MS/MS scans. High-

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resolution MS scans were acquired in the Orbitrap (60,000 FWHM, target

value 106) to monitor peptide ions in the mass range of 350–1,650 m/z,

followed by collision-induced dissociation MS/MS scans in the ion trap

(minimum signal threshold 150, target value 104, isolation width 2 m/z) of the

five most intense precursor ions. The precursor ion masses of scanned ions

were dynamically excluded from MS/MS analysis for 10 s. Singly charged ions

and ions with unassigned charge states were excluded from triggering MS2

events

Database searching

Raw data were converted to the open mzXML format with ReAdW (version

4.3.1). mzXML files were searched by the SEQUEST via Sorcerer Software

4.2.0 and Mascot (version: 2.4.1) against UniProtKB/Swiss-Prot protein

databases (release 2012_11, containing 20,243 proteins) concatenated with

reverse sequences. For in silico digestion, trypsin was used as the protease

and was assumed to cleave after lysine (K) and arginine (R) unless followed

by proline (P). Three missed cleavage sites and one non- tryptic terminus

were allowed per peptide. The precursor ion tolerance was set to 50 parts per

million (ppm), and fragment ion tolerance was set to 0.5 dalton. The data were

searched allowing phosphorylation (+79.9663 daltons) of serine, threonine,

and tyrosine as a variable modification and carboxy-amidomethylation of

cysteine (+57.0214 daltons) residues as a fixed modification. Finally, The

identification results were statistically analyzed with the PeptideProphet

algorithm (v 4.6) (27) and the results combined using the iProphet algorithm

(28). In all the datasets presented the FDR was maintained below 1%, this

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was based on the number of the decoy hits at the PeptideProphet cut-off

score used. Accuracy of phosphorylation site location was determined by

PTMprophet algorithm, the same mass accuracy specified for the database

search was also used for the calculation of phosphorylation site localization

probabilities.

The annotated spectra provided in figure S8 were generated using an in

house developed python script and SpectraST (29) to create consensus

spectra for all the identified phosphorylated peptides. Only fragment

assignments with a mass error below or equal to 0.5 Da were annotated in

each spectrum.

Label-free quantification

For label-free quantification of the identified peptides, mzXML files were

processed with OpenMS (30) suite to detect and extract ion signals. Each

signal feature was matched with the best peptide assignment obtained after

database searching. The generated intensity maps contained all aligned

features together with the corresponding peptide sequences. The intensities

maps of 3 different replicate experiments were analyzed to generate final fold-

change ratios in peptide amounts between treated and untreated samples.

Each experiment consisted of two consecutive injections for each cellular

condition (treated with 5-ITu and not treated cells). Feature intensity values

that were missing in the data matrix were addressed as follow. All peptide

identifications with three or one missing value for each condition were

excluded for further analysis. When instead two missing values were absent

in the same biological condition we set a nominal lower bound values

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consisting in the minimum measured intensity peak over the background ions;

we used 5*104. For the statistical analysis, the intensities for peptide features

were log-transformed; the fold change and the confidence of phosphopeptides

regulation was calculated by a linear model using the publicly available R-

based Limma package (31). The calculated P-values were adjusted for

multiple comparisons using Benjamini and Hochberg correction.

Functional annotation

For functional annotation and Gene Ontology (GO) enrichment analysis of

protein sets, we used the annotation tools GOrilla (32). The P-values were

calculated after FDR correction for multiple testing (Benjamini-Hochberg).

STRING database (version 9.05) was used to predicted protein-protein

interaction within Haspin binding partners (33). The STRING predictions were

based on: experiment and databases; the minimum STRING score was set to

0.4. The protein networks were represented using in Cytoscape (v. 2.6.2)

(34).

Kinase-substrate relationship prediction

To predict protein kinases affected by 5-ITu treatment, we used iGPS (version

1.0) and NetworKIN algorithms (version 2.0). Enrichment tests used the

hypergeometric distribution as previously shown (35). As a background in

these tests, we used peptide identifications that were not affected by 5-ITu

treatments (-3<FC<3, P-value <0.05). The P-value cutoff for enrichment was

set at 5 & 10!5.

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Generation of cell lines stably expressing Haspin and Haspin pull down

Open reading frames (ORFs) of Haspin were retrieved from the Gateway (Life

Technologies) adapted human ORF collection (horfeome v5.1, Open

Biosystems, www.openbiosystems.com). ORFs were introduced by LR

recombination into a destination vector that was constructed by ligating the

Gateway recombination cassette and an N-terminal His6-HA-StrepII-tag into

the polylinker of the pcDNA5/FRT/TO vector (Life Technologies).

HEK293 cells were grown in DMEM supplemented with 10% FBS (PAA

Laboratories), 0.2 mM L-glutamine, 100 µg/ml hygromycin B and 15 µg/ml

blasticidin S (all Life Technologies) and were plated on 15 mm cell culture

dishes (Nunc). Protein expression was induced in medium lacking hygromycin

and blasticidin by the addition of 1 µg/ml tetracycline 24 hours prior to harvest.

Cells were detached by pipetting, washed twice with ice-cold PBS and cell

pellets were frozen in liquid nitrogen.

For each pull-down we used a cell pellet deriving from 10 & 15–cm 80%

confluent both from cycling and prometaphase-arrested cells (0.33 µM

nocodazole for 16 hours). The cells were harvested and washed twice with

PBS. The cell pellets obtained were lysed on ice in 2 volumes of lysis buffer

(LB, 50 mM HEPES, pH 7.5, 150 mM NaCl, 5 mM EDTA, 0.1% NP-40,

phosphatase and protease inhibitor cocktail, Roche). Insoluble material was

removed by centrifugation at 13,000 r.p.m. for 30 min at 4 °C. Strep-Tactin

Sepharose beads (1200 µL, slurry) were transferred to a Bio-Spin

chromatography column and washed twice with 1.5 mL of LB. The cell lysates

were loaded two consecutive times on the Strep-Tactin columns. The beads

were washed with 3 & 1 mL lysis buffer, and bound proteins were eluted with

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3 & 300 µL freshly prepared 2 mM D-biotin in LB. Anti-HA agarose beads (80

µL) were washed with 2 & 1 mL LB buffer and centrifuged at 1,000 r.p.m. for 1

min at 4 °C. The supernatant was removed and the beads resuspended in

100 µL LB buffer. The anti-HA agarose beads were added to the biotin eluate

and rotated for 1 h at 4 °C. The anti-HA agarose beads were washed with 3 &

1 mL LB buffer and then with 3 & 1 mL LB buffer without detergent and

protease inhibitors. Retained proteins were eluted twice with 200 µL of 100

mM glycine, pH 2.5. The pH in the sample was adjusted using AMBIC 1M pH

8 and successively trypsin. The peptides originated were purified and

analyzed by mass spectrometry as previously described. To identify specific

Haspin binding partners we used a strategy based on spectral counts and

control pull downs. The dataset of control pull-downs consisted of 80 different

protein purifications either performed form cell expressing GFP or cells

transfected with an empty vector. We retrieved spectral counts for every

identified protein using the ABACUS software (36). For the set of proteins

identified in the control pull-downs we selected the highest five spectral count

values between all the 80 analyses performed. We estimated the probability

for each identified protein of being Haspin specific interactors using SAINT

(37). The SAINT algorithm creates separate distributions for true and false

interactions and assigns the probability of a bona fide protein-protein

interaction to each identified proteins in the dataset. We considered Haspin

specific interacting partners only proteins i) with spectral counts seven times

higher than the average values of the negative controls and ii) protein

interactions with the highest possible SAINT probability (SAINT probability=1).

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Results

Generation of a dataset of Haspin modulated, chromatin associated

phosphorylation events.

A robust cellular assay to detect chromosomal Haspin activity

We employed the small-molecule inhibitor 5-iodotubercidin (5-ITu) (fig. S1) to

inhibit Haspin kinase activity and to study the effect of its inhibition in human

mitotic HeLa cells. A specificity screen performed on a panel of 138 kinases in

vitro revealed the selectivity of 5-ITu towards Haspin and the members of Clk

kinase family (11). To confirm efficient Haspin inhibition in cells, we monitored

the phosphorylation of Thr3 of histone H3 by immunofluorescence (IF) (fig.

S2). Briefly, the cells were arrested in mitosis with nocodazole and after 16

hours the proteasome inhibitor MG132 was added to the medium to prevent

exit from mitosis. Finally, the cells were treated for 1.5 hours with 5-ITu

concentrations ranging from 0.1 to 10 µM (fig. S2). In agreement with

previously published studies (38), we observed a drastic reduction of H3Thr3ph

in cells treated with as little as 1µM 5-ITu (5) (fig. S2, fig. 1A-B). The loss of

H3Thr3ph is thought to prevent the recruitment of Aurora B to the centromere

(fig. 1A). However, under the experimental conditions used, centromeric

phosphorylation of the Aurora B substrate CENP-A at Ser7 (fig. 1C) was not

affected. This was probably due to incomplete Aurora B delocalization from

the centromeres (9, 11, 12, 39).

It has been reported in the literature that Haspin also localizes to condensed

chromatin during mitosis (7), implying that its direct substrates and the Haspin

dependent signaling cascade might affect the phosphorylation state of

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chromatin-associated proteins beside H3Thr3ph. To investigate the effect of

Haspin inhibition on the state of phosphorylation of chromatin-associated

proteins, we developed a robust protocol for the mass spectrometric

identification and quantification of phosphorylated peptides on a chromatin

fraction purified from mitotic cells (fig. 1D-E). First we established conditions

that prevented detectable de-phosphorylation of phosphoproteins during

sample workup. Phosphorylated proteins can be rapidly dephosphorylated by

phosphatases after cell lysis, if phosphatase inhibitors or denaturing

conditions are not employed. To determine whether phosphatases affected

the phosphorylation state of the samples during the chromatin enrichment

protocol we monitored the phosphorylation state of H3Thr3ph by IF. Chromatin

samples purified from Haspin inhibited mitotic cells and from cells mock

treated with DMSO, respectively, were gently centrifuged onto microscopy

slides and the specific protein epitopes were detected with antibodies (fig. 1D-

E). Mock treated cells substantially preserved the H3Thr3ph signal, while

phosphorylation of the Haspin histone H3 target in mitotic cells treated with 5-

ITu was barely detectable, validating the applied protocol (fig. 1D).

Interestingly, while centromere staining of Aurora B was strongly reduced

upon Haspin inhibition, its localization on chromosome arms remained

unchanged (fig. 1E). In conclusion, we established and validated a protocol

for the purification of mitotic chromatin from cells subjected to different

pharmacological regimens in a state that largely preserves the

phosphorylation state of the proteins. This allowed us to directly study the

effect of Haspin inhibition by 5-ITu on substrate phosphorylation in human

cells.

! #+!

Identification of sites of phosphorylation of chromatin associated proteins

We used quantitative mass spectrometry to identity Haspin modulated

phosphorylation sites on chromatin-associated proteins. Purified mitotic

chromatin samples from cells treated with the Haspin inhibitor 5-ITu and

untreated cells, respectively, were prepared using the conditions optimized

above, digested with trypsin and the phosphorylated peptides were enriched

using immobilized metal affinity chromatography prior to analysis by LC-

MS/MS (fig. 2A). We identified 5,822 phosphorylated sites on 1,347 proteins

(fig. 2B, table S1) at 1% FDR. Phosphorylation site localization probability was

controlled using the PTMprophet algorithm (table S1). The distributions of the

individual phosphorylated residues across the different hydroxyl amino acids

and the number of phosphorylation sites per peptide identified on chromatin

proteins were similar to those observed in other phosphoproteomic studies

focusing on different cellular sub-compartments (fig. 2B) (35, 40). Further, we

identified 1,217 previously unreported phosphorylation sites in the

PhosphoSitePlus database (19), corresponding to approximately 10% of

phosphosites identified in this study. To estimate the limit of detection of our

phosphopeptide measurements we related the identified phosphoproteins to

estimates of their cellular concentration (41). The results indicate that the

identified phosphoproteins spanned a range of abundance from over a million

to less than 500 copies per cell (table S1). More than 40% of the

phosphoproteins identified in this study are core components of mitotic

chromatin (42). Detailed analysis of the kinetochore, a macromolecular

structure larger than 1 MDa that assemble on the centromere of mitotic

! #"!

chromosomes, indicated that the gentle conditions used for the purification of

mitotic chromatin (Material and Methods) preserved even labile protein-

protein interactions (43, 44) and thus retained even loosely associated

proteins in the chromatin fraction. The kinetochore consists of more than 80

proteins (44). It has traditionally been sub-divided into three distinct structural

layers: i) the inner kinetochore which hosts proteins in close contact with the

centromere proteins and the DNA, ii) the outer kinetochore that functions as a

bridging platform between the inner kinetochore and the corona, iii) the

corona where the proteins transiently localize (43). In this study we identified

phosphorylation sites on proteins localized in all three layers, including the

kinase Aurora B and several CENP proteins that localize to the inner

kinetochore, Ndc80 and the kinases Plk1 and Mps1 along with structural

components of the outer kinetochore and Cdc20 and CENP-E, BUBR1,

proteins of the corona (fig. 2C; table S1).

In conclusion, we established and applied a strategy for the mass

spectrometric detection of proteins and their phosphorylation sites from

purified mitotic chromatin. To the best of our knowledge, this is the largest

existing dataset of phosphorylation sites on chromatin proteins in human cells.

Quantification of phosphorylation sites in chromatin-associated proteins

To identify phosphorylation sites modulated by 5-ITu treatment in the dataset

acquired above we related the precursor ion intensities of phosphopetides in

5-ITu treated and non-treated mitotic chromatin samples. We used the

OpenMS quantification tool (30) and statistically evaluated the data as

indicated in (45). To achieve robust phosphorylation site quantification we

! ##!

eliminated from further analysis those phosphopeptides that were

inconsistently detected in replicate analyses of the same sample (described in

the Material and Methods section). We confidently quantified 3,964

phosphorylation sites from 1,125 proteins (table S2). We considered

phosphopeptides as regulated if they showed a larger than six fold change in

signal intensities between inhibitor treated and not treated cells and a P-value

lower or equal to 0.05. Using these criteria we identified 258 and 324

phosphosites belonging to 338 proteins that were down- or upregulated,

respectively, in response to 5-ITu treatment (fig. 2D, table S2). To gain

insights in the cellular functions affected by the Haspin inhibitor treatment, we

performed gene ontology (GO) analysis using the GOrilla software (32) which

indicated 66 GO terms significantly (p-value <1E-7) enriched in the 338

phosphoregulated proteins (table S3, fig. 3E). We manually inspected the

function of the proteins grouped under each enriched GO term. In total we

could identify three major functional clusters of Haspin modulated

phosphoproteins: i) mitotic proteins, ii) RNA processing proteins and iii)

histones and chromatin modifier proteins (fig 2E, table S3).

Among the 574 phosphorylation sites modulated by Haspin inhibition, 25 sites

mapped to mitotic proteins localizing to the centromere. These included:

MIS18BP1, NSL1, CENP-E, CENP-F, Hec1, Borealin, INCENP (table S2-3)

as well as BUB1 and Aurora B kinases and, the BUBR1 pseudokinase. As

expected, we observed downregulation of phospho-sites on three of the four-

chromosome passenger complex (CPC) protein subunits identified in this

study: Aurora B, Borealin, and INCENP (9, 39). These data are consistent

with the notion that the absence of H3Thr3ph caused by 5-ITu treatment

! #$!

reduces both Aurora B localization at the centromere and the localization of

the other subunits of the CPC complex (fig. 1A-E). Interestingly, the

phosphorylation sites Ser593 and Thr601 on the BUB1 kinase were also

strongly downregulated upon 5-ITu treatment. Furthermore, about half of the

phosphorylation sites we quantified after Haspin inhibition were increased

compared to non treated cells, suggesting indirect or compensatory effects.

Upregulated sites include Ser69 and Ser62 on the Ndc80 protein as well as

phosphorylation sites on three proteins required for cytokinesis, namely

Septin 7 and Septin 9 and Anillin.

The “RNA processing cluster” included subunits of the splicesome,

ribonucleproteins, RNA binding proteins and transcription factors.

Interestingly, we identified induced or reduced phosphorylation in several

components of the splicesome including, SRSF1, SRSF2, SRSF3, SRSF6,

SRSF7, SRSF9. The phosphorylation sites Ser199 and Ser201 on SRSF1 were

downregulated, while the phosphorylations on Ser234 and Ser238 on the same

protein were upregulated. Further, the data indicated that all the quantified

sites on SRSF6, SRSF7, SRSF9, were upregulated. In contrast

phosphorylation sites on SRSF2 and SRSF3 were downregulated. The

complex regulation of phosphorylation on splicing proteins is likely due to a

combination of direct and indirect effects of Haspin inactivation.

The “chromatin modifier” cluster contained proteins involved in enzymatic

processing of DNA such as DNA and RNA helicases and polymerases, as

well as methyl and acetyl transferases (table S2, 3) and proteins that bind

specific post translationally modified histones. Interestingly, we observed

phosphorylation changes on a number of chromobox proteins, such as CBX1,

! #%!

CBX3 and CBX8 (table S2; 3). These proteins control epigenetic repression of

chromatin by affecting PTMs on histones (46). In addition, we observed

significant downregulation of the phosphorylation sites on several histone

isoforms upon 5-ITu treatment (table S2; 3). In contrast, Ser122 of the H2AX

and H4 Ser48 (47) were upregulated upon inhibitor treatment (fig 2E, table

S2).

Phosphorylation at Ser137 of the histone macroH2A was strongly

downregulated upon 5-ITu treatment (fig 3A). Recently, it has been reported

that the macro domain of histone macroH2A controls the phosphorylation

levels of Ser10 and Thr3 of histone H3 in human cells (48). To test whether

macroH2A Ser137 phosphorylation was directly dependent on Haspin activity,

we over-expressed Haspin in the presence or absence of the inhibitor 5-ITu

and quantified Ser137 phosphorylation using a phospho specific antibody (fig.

3B). The results showed a drastic reduction of macroH2A phosphorylation in

Hek293 cells upon treatment with 5-ITu (fig. 3B). In contrast, Haspin over-

expression led to a significant increase in macroH2A Ser137 and histone H3

Ser10 phosphorylation that again diminished upon 5-ITu treatment (fig. 3B). In

combination these results strongly suggest a direct dependence of histone

macroH2A Ser137 phosphorylation on Haspin catalytic activity (fig. 3B). In

summary, mass spectrometric quantification of phosphorylation sites on

chromatin-associated proteins upon 5-ITu treatment confirmed the importance

of Haspin kinase activity towards the phosphorylation of centromeric proteins.

Furthermore our data indicate potential novel connections between Haspin-

dependent signaling and processes involved in gene transcription.

! #&!

Kinase-substrate enrichment analysis (KSEA) reveals inactivation of

Aurora B, CLK and RSK kinases upon 5-iTu treatment

To gain functional insights into the phosphorylation sites regulated in the

quantitative phosphoproteomic dataset described above we performed a

kinase-substrate enrichment analysis (KSEA) (35, 49). Specifically, we first

used the iGPS (50) and NetworKin (51) kinase-substrate prediction algorithms

to identify those kinases that have predicted substrate phosphorylation sites

among the 3,964 quantified phosphorylation sites. We then further statistically

filtered this initial kinase-substrate matrix to determine those kinases that

were significantly associated with the 5-ITu modulated phosphorylation sites.

Substrates downregulated upon 5-ITu treatment implied that the activity of the

respective kinase(s) were reduced, e.g. by the inactivation of Haspin or the

direct Haspin dependent inactivation of a downstream kinase. Conversely,

upregulation of the phosphorylation sites would suggest that the activity of

specific kinases is increased upon 5-ITu treatment.

Both the iGPS and Networkin algorithms did not detect a significant

association between the upregulated sites and specific kinases. In contrast,

for the downregulated sites the two algorithms identified three kinase families

that were significantly associated (P-value lower than 0.0005) with the

phosphopeptides in that group: i) the Aurora family comprising Aurora B,

Aurora A, and Aurora C kinases (P-value 2.79*10-6), ii) the CLK family

consisting of the kinases Clk1, Clk2 and Clk3 (P-value 2.86*10-5) and iii) the

RSK family consisting of p90RSK, RSK2 and RSK3 kinases (P-value 1.7*10-4)

(fig. 4A, table S4). The downregulation of Aurora B substrates was expected

because 5-ITu treatment prevents Aurora B localization to the centromere

! #'!

(see above), thus preventing its activity at the centromere (fig. 4B, table S5).

CLKs are dual specificity protein kinases involved in pre-mRNA processing

(52). Inhibition of CLK family kinases can be interpreted as a direct effect of 5-

ITu treatment as reported by a specificity screen showing that 5-ITu inhibits in

vitro Clk2 (94% of the kinase activity) and less efficiently Clk3 (50% of the

kinase activity) kinases (11). 18 phosphorylation sites were predicted as CLK

substrates; more than 50% of those were from proteins involved in gene

expression and splicing mechanisms (fig. 4B, table S6).

The RSK family consists of a group of highly conserved Ser/Thr kinases that

regulate a range of cellular processes, including cell growth, cell motility, cell

survival and cell proliferation (53). Interestingly, substrate prediction

suggested that RSK activity mostly targets the histones and histone

associated (fig. 4B, table S7). The inhibition of RSK is unlikely to be caused

by off-target 5-ITu inhibition, since the concentration of the inhibitor used in

this study does not significantly affect RSK kinases activity in vitro (1 µM 5-ITu

reduces only of the 3% RSKs kinase activities) (11). Therefore, we consider

the downregulation of predicted RSK substrates as an indirect effect of

Haspin inhibition.

In summary, KSEA after Haspin inhibition correctly highlighted down-stream

effects of 5-iTU treatments such as the inhibition of both Aurora B and CLK

family kinases (9, 11, 39). Furthermore our data also shows a significant

downregulation of the RSK predicted substrates.

Identification of a Haspin consensus motif by positional scanning

oriented peptide library screening (PS-OPLS)

! #(!

Substrate recognition by kinases depends on different factors, including

spatial proximity, site accessibility and the amino acid sequence motifs

surrounding the phosphorylation sites (2). We determined a preferred Haspin

substrate motif by positional scanning oriented peptide library screening (fig.

5A) as described in (54).

We purified a recombinantly expressed Haspin kinase domain and used it for

the in vitro kinase reaction on degenerated peptide libraries. The

autoradiography pattern indicated a preference for poly-threonine compared

to poly-serine peptides (bottom left fig. 5A) suggesting a preference of Haspin

for threonine residues. Also, the phosphorylation of peptides carrying

threonine residues in the different positions tested could be explained by the

preference of Haspin for threonine residues (squared in blue fig. 5A). Haspin

was most strongly selective for peptides having an Arg residue at position P -

1, and displayed a substantial preference for Ala and Val at the P -2 position

and for Lys at the P +1 position. We therefore defined the preferred

recognition motif for Haspin as A/V-R-T/S-K-(X-noD/E) (fig. 5A). Strikingly,

this motif is in complete agreement with the only presently known Haspin

phosphorylation sequence centered around Thr3 of the histone H3 (fig. S3). In

addition, we also noted that acidic amino acids were strongly disfavored by

Haspin at multiple positions near the phosphorylation site (fig. 5A squared in

red). This observation is consistent with the negative net charge within the

Haspin active site (fig. S4) which likely creates ionic electrostatic repulsions

with acidic substrates. In summary, the positional scanning oriented peptide

library screening identified a preferred recognition sequence for Haspin that

matches with the Haspin phosphorylation site on histone H3 tail.

! #)!

Structural mechanisms of substrate recognition

To gain structural insights on the basis of the Haspin substrate recognition

motif identified, we co-crystallized the kinase catalytic domain with the H3 tail

substrate sequence. The structure was refined to 1.9 Å resolution (fig. 5B, S4

table S8). The kinase domain adopted a similar conformation when compared

to the apo-structure (5). The first 7 residues were modeled into the

experimental density revealing that three substrate residues Ala1 (position -2

in the PS-OPLS), Arg2 (-1) and phosphoacceptor site Thr3 (0) were anchored

deep within the substrate pocket. Surprisingly, the bound peptide adopted an

unusually sharp 180˚ turn at Lys4 (+1) projecting the C-terminal tail outward

(fig. 5B). This is in contrast to binding modes of substrates of other kinase-

substrate complexes, which typically exhibit an elongated linear conformation.

As a consequence of this unique substrate conformation, residues Arg2 (-1)

and Lys4 (+1) are positioned into deep hydrophilic pockets explaining the

strong selection for these two residues and position -1 and +1 in the

degenerated library peptide array. The only other residue preferentially

selected in position +1 was a tyrosine, which may functionally replace the

lysine forming a hydrogen bond with Asp707. The structure explains also the

strong selection for small hydrophobic residues at position -2 in the PS-OPLS

experiment. In this position the amino acid side chain is oriented towards a

small surface cavity excluding residues with bulkier groups than alanine or

valine.

Prediction and in vitro phosphorylation of potential Haspin substrates

! #*!

The strength of the interactions that stabilizes the binding of the substrates

with the kinase reflect the signal intensities of the phosphorylated peptides

measured in the PS-OPLS array and indicate the residues in the recognition

sequences that are particularly important in Hapin substrates. This

information, in turn is useful to predict substrates of a kinase (55, 56).

We used the NetPhorest algorithm to identify candidate Haspin direct

substrates in the fraction of the downregulated phosphorylation sites

measured on the chromatin associated proteins. The results were filtered

based on NetPhorest probability higher than 0.1, which led to a false positive

rate (FPR) of the Haspin substrate predictions lower than 10%. Using this

score cut-off we identified 11 candidate sites phosphorylated by Haspin (table

S9). These proteins include the splicing factors SRSF1, SRSF2 SRSF10, and

the PRP4 kinase, which controls RNA splicing (table S9). To extend Haspin

substrate prediction to proteins that were not identified in the chromatin

dataset presented here, we used the newly established Haspin consensus

recognition motif to computationally predict potential Haspin substrates from

phosphorylation sites identified in the literature. We employed the NetPhorest

algorithm to query a large collection of more than 64,000 identified

phosphorylation sites (Material and Methods). From these the algorithm

predicted 2,926 sites with a NetPhorest probability higher than 0.1 and a FPR

less 10% (table S10). We tested specificity of Haspin activity on 101 predicted

substrates sites (fig. S5) using an in vitro phosphorylation experiment. We

chemically synthetized 101 peptide sequences selected within the predicted

sites where Haspin was among the top 10 % most likely upstream kinases

and, tested them as Haspin substrates by in vitro phosphorylation experiment

! $+!

(fig. S5, table S11). We detected the newly formed phosphorylation sites on

the peptide sequences by shotgun mass spectrometry. More than 90% of the

peptides in the library contained at least two hydroxyl amino acids (table S11).

A kinase with poor substrate specificity would be expected to randomly

phosphorylate in vitro every site available on the peptide substrates. In the

experiment, Haspin showed high specificity for the selection of the substrate.

The kinase phosphorylated 96 sites within the peptide library (table S12). 35

of these were confidently assigned to specific sites when multiple hydroxyl

amino acids were present (PTMProphet probability equal to 1) and all of these

confirmed sites matched the predictions. On average about 80% of all

fragment ion spectra identified the predicted sites, confirming the specificity of

the kinase reaction and the accuracy of the NetPhorest predictions (fig. S5,

table S12). We further validated the phosphorylation sites associated with

CENP-T (NetPhorest probability 0.23) and histone H2A (NetPhorest

probability 0.11) by phosphorylating the respective proteins in vitro (fig. 5C-

D). We selected CENP-T because of its role in kinetochore assembly and

likely co-localization with Haspin (57). We selected histone H2A because of

the high degree of sequence conservation around the predicted Haspin

phosphorylation sites between H2AThr16 and macroH2ASer137 (fig. 5C) and,

because macroH2ASer137ph is reduced after Haspin inhibition. Specifically, a

fragment encompassing residues 1-101 of CENP-T, histone H2A and histone

H3, respectively were incubated with Haspin kinase domain in the presence of

32P ATP (fig. 5C-D). We found that Haspin very efficiently phosphorylated

both CENP-T and histone H2A in vitro (fig. 5C-D). To determine the number

of phosphorylated residues on CENP-T and histone H2A, respectively, we

! $"!

determined the intact molecular weight of the proteins by mass spectrometry.

The data showed that Haspin phosphorylated CENP-T preferentially on three

or four sites, whereas histone H2A was predominantly phosphorylated at a

single site (fig. 5C-D). Mass spectrometric analysis of tryptic digests of the

respective phosphoproteins identified Thr14/27/57 and Ser72, for CENP-T 1-101

and Thr16 for H2A as the phosphorylated residues. (fig. 5C-D). In summary,

using computational predictions based on the newly identified Haspin

consensus motif and mass spectrometric validation of the predictions we

identified novel bona fide Haspin substrates. This study extends the number

of putative Haspin substrates from 1 to 38.

Identification of Haspin protein interaction network

We next performed affinity purification-mass spectrometry (AP-MS) analysis

of the Haspin kinase to test whether some of the predicted substrates or other

proteins physically associated with the Haspin kinase. Haspin was expressed

as affinity tagged bait protein in FLP-in HEK293 cells using established

protocols (58) and the purified complex was analyzed by standard LC-MS/MS

(fig. 6A). To distinguish true interactors from proteins non-specifically

associating with the isolated complexes we generated data from control

samples using unrelated bait proteins (GFP) (36) and statistically filtered the

data (37) (Material and Methods). The results identified 50 proteins that

passed the filtering criteria and that were thus considered true interactors (fig.

6A). About 70% of these (33 of 50) were implicated with transcriptional

regulation and 50% (25 of 50) were previously reported to co-purify with

components of the spliceosome (http://spliceosomedb.ucsc.edu/) (fig. 6A)

! $#!

Indeed, STRING analysis of the identified proteins reported a highly

interconnected network of interactions between the spliceosome-associated

subset of Haspin interactors (fig. 6A, pink subgroup). Interestingly, in the

chromatin dataset 75 phosphorylation sites were observed on 18 of the 50

identified Haspin interactors. Ten phosphorylation sites mapping to 5 proteins

were significantly regulated upon 5-ITu treatment (table S14). However, none

of sites identified on Haspin binding partners matched the Haspin consensus

motif, suggesting that other kinases are responsible of these phosphorylation

events. Although none of the interactors was scored as a possible Haspin

substrate, we asked whether the protein complex could instead mediate the

interaction between Haspin and its predicted high confidence substrates.

Indeed, out of the 29 highly ranked predicted substrates 11 were previously

shown to physically interact with one or more of the Haspin binding partners,

(fig. 6B) suggesting that Haspin binding partners could physically mediated

the interaction between Haspin and its substrates. In conclusion, the

identification of a Haspin interaction network, both reinforces and

complements our substrate predictions; about 50% of the most confidently

predicted Haspin substrates physically interact with Haspin binding partners,

suggesting that Haspin might in vivo phosphorylate components of this

complex network of interactors on the predicted sites.

Discussion

In this study we used the ATP analogue 5-ITu to investigate the role of Haspin

catalytic activity in mitotic cells. A specificity screen performed on a panel of

138 kinases in vitro revealed a tight selectivity of 5-ITu towards Haspin and

! $$!

the members of Clk kinase family (11). We developed an efficient and robust

protocol to identify phosphorylation changes on chromatin associated proteins

as a result of treatment with 5-ITu (fig. 2A). We identified and quantified by

mass spectrometry, 3,964 phosphorylation sites mapping on 1,125 proteins

(fig. 2B-2D, table S2). As far as we are aware this represents the largest

dataset of phospho-sites available on chromatin proteins.

The vast majority of changes in phosphorylation state that we observed in

response to 5-ITu treatment affected mainly three classes of proteins: i)

proteins involved in mitotic regulation, ii) proteins involved in RNA processing

and iii) histones and chromatin processing proteins (fig. 2E). KSEA analysis of

the phosphorylation sites down regulated upon 5-ITu treatment of mitotic cells

indicated that Haspin and the three kinase families Aurora, CLK, and RSK,

were affected (fig. 4). This could either be due a direct inhibition mediated by

the 5-ITu, or due to indirect effects secondary to Haspin or CLK inhibition.

One known indirect effects of Haspin inactivation is the release of the CPC

complex (AuroraB, Incenp, Borealin, Survivin) from the centromere (fig. 1A).

In agreement with the literature we found that the phosphorylation sites

identified on CPC complex components are down regulated after 5-ITu

treatment (Fig 2D, table S2). It has been described previously that

centromeric enrichment of the CPC complex lead to an increased catalytic

activity of Aurora B (8). It is thus not surprising that we measured a strong

downregulation of Aurora B dependent phosphosites on CPC members (fig.

4B, table S5). Interestingly, we found that the Aurora B substrate Hec-1Ser69

is strongly upregulated upon 5-ITu treatment (table S2). This unexpected

result suggests the existence of a delicate equilibrium at the centromere,

! $%!

between phosphorylation and dephosphorylation of proteins that likely

involves, in addition to kinases as well as protein phosphatases (11).

While phosphorylation sites linked to mitosis could be confidently attributed to

both Haspin and Aurora B activities, the phosphorylation of proteins

implicated in the control of gene expression mechanisms cannot be

unambiguously assigned to any specific kinase highlighted by the KSEA.

Indeed, there are several lines of evidence that Aurora B, CLKs, RSKs and

Haspin kinase activities can affect, either directly or indirectly, the

mechanisms that control gene expression (9, 39, 59-74). To predict Haspin

direct substrates within the downregulated sites we determined the kinase’s

consensus motif. The results of PS-OPLS reveled a strong preference for Ala

in position P-2, Arg in P-1 and Lys in P+1 (fig. 5A) as also recently reported by

Kettenbach at al. (75). The Haspin preference for these residues finds a

structural explanation in the co-crystal structure of Haspin with the histone H3

tail added as substrate (fig. 5B-S4). This indicates a so far unique substrate-

binding mode, where the substrate backbone formed a 180∘ turn in the Haspin

active site placing residues Arg2 (P-1) and Lys4 (P+1), which are important for

consensus motif recognition, into deep hydrophilic pockets. Interestingly,

these two residues flanking the substrate Thr3 in histone H3 are a hotspot of

post-translational modifications such as methylation and acetylation, and thus

have key regulatory function for chromatin structure and transcription.

Previous studies showed that increased Lys4 methylation had an inhibitory

effect on Haspin substrate recognition (6). Lys4 forms an ion-pair network with

the two acidic residues Asp707 and Asp709. Lys4 methylation sterically hinders

substrate binding. Based on the structure and the data measured on

! $&!

trimethylated Lys4 we predict that Lys4 acetylation will also weaken H3

substrate recognition by Haspin, and therefore phosphorylation of the Thr3.

The identification of the Haspin consensus motif and the structural details of

the kinase-substrate interaction guided the identification of potential novel

substrates. We identified 11 bona fide novel Haspin substrates including

several splicing proteins (table S9). Ser137 of histone macroH2A was strongly

downregulated upon 5-ITu treatment. Even though the NetPhorest probability

was below the threshold set in this study we followed up on this

phosphorylation site as a potential Haspin substrate because it was recently

shown to be important for the phosphorylation of Ser10 and Thr3 of the histone

H3 (48). Histone macroH2A is a histone variant originally found enriched in

the inactive X chromosome of female mammals (76). Several studies

demonstrate that histone macroH2A functions both as positive and as

negative regulator of gene transcription (77). MacroH2A histone variant is

about three time larger than other canonical histone proteins and it is

composed of three segments: i) a histone like domain, 64% protein sequence

identical to histone H2A; ii) a highly positively charged flexible loop linking the

histone fold to the macro domain; and iii) a macro domain that is exposed to

the nucleoplasm (77). The DNA-linker interactions are stabilized by ionic

bonds involving the DNA negative charges and the positive charges of the

basic macroH2A stretch Thr120-Pro160 (78, 79), and these interactions are

likely to be important for the control of chromatin condensation (78, 79).

Interestingly, we noted that the consensus motif around Thr16 of histone H2

and Ser137 of histone macroH2A are conserved except for the residue in

position +1. In that position histone H2A contains an arginine (Arg17) whereas

! $'!

histone macroH2A has a proline residue (Pro138) (fig. 5E). Our data clearly

demonstrate that macroH2A Ser137 phosphorylation is dependent on the

Haspin kinase (fig. 3) and we speculate that this site is a Haspin direct

substrate in vivo whose phosphorylation could modulate the degree of

chromatin condensation and control DNA transcription. We validated CENP-

T Thr57 as bona fide Haspin substrate by in vitro kinase reaction of the CENP-

T protein fragment 1-101 (fig. 5C-D). CENP-T is a component of the CCAN

(constitutive centromere associated network) that plays a central role in the

kinetochore assembly, mitotic progression and chromosome segregation (57).

Haspin phosphorylates in vitro four CENP-T sites, Thr14/27/57 and Ser72 (fig.

5C-S6). Recently, it has been demonstrated that the tight control of CENP-T

phosphorylation, primarily by cyclin-dependent kinase (CDK), is important for

the assembly and the disassembly of the kinetochores (80) during mitosis. In

particular, CDK-dependent phosphorylation of CENP-T recruits Ndc80

complex to the kinetochore (80). It is therefore likely that Haspin activity could

assist CDK kinase in the control of protein recruitment at the kinetochores

during the different mitotic stages.

Altogether, the results presented here greatly expanded the number of Haspin

bona fide direct substrate in cells and clarified the structural mechanisms of

Haspin-substrate binding. Furthermore, a novel link between Haspin kinase

activity and phosphorylation of proteins involved in the regulation of gene

expression is presented.

For over half a century it has been assumed that transcription is globally

silenced during mitosis. Recently, new unexpected links between mitosis and

the general mechanisms that regulate gene transcriptions have been

! $(!

emerging (81-84). There is evidence of active transcription of centromere

satellite regions during mitosis and suggestions that such enzymatic activity is

essential to guarantee chromosome stability (84). Recently, It has been

shown that specific RNA transcripts interact with CENPA nucleosomes, and

that such proteins-RNA binding controls Aurora B localization and its activity

at the kinetochore (85). Our data indicate that Haspin might regulate

transcription by direct or indirect phosphorylation of splicing and transcription

factors, subunits of the transcription machineries, as well as histones. It is

therefore likely that Haspin controls the recruitment of Aurora B to the

kinetochore by the synergistic effect of its enzymatic activity, first

phosphorylating the histone H3 Thr3 (9, 39) and second by maintaining an

active RNA transcription during mitosis. This novel function should be

considered in future studies and take into account for a comprehensive

understanding of Haspin role in mitosis and more in general for a better

understanding of the molecular mechanisms that link DNA transcription and

cell cycle progression in human cells.

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Notes:

Acknowledgements: We thank members of the Aebersold, Gstaiger and

Wollscheid laboratories at IMSB for helpful discussions. Dr. Chris Barnes and

Dr. Martin Junger for critical reading of the manuscript. Funding: AM is

supported by EMBO long-term fellowship. Work in the Aebersold laboratory is

supported by the European Research Council (ERC) advanced proteomics

grant v3.0’ (grant#233266) and the PhosphoNetX program from SystemsX.ch.

Work in the Meraldi lab is supported by an SNF project grant, the Swiss

Cancer League and the Novartis Foundation. SK is grateful for support from

the SGC, a registered charity (number 1097737) that receives funds from

AbbVie, Boehringer Ingelheim, the Canada Foundation for Innovation, the

Canadian Institutes for Health Research, Genome Canada, GlaxoSmithKline,

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Janssen, Lilly Canada, the Novartis Research Foundation, the Ontario

Ministry of Economic Development and Innovation, Pfizer, Takeda, and the

Wellcome Trust [092809/Z/10/Z]. AC is supported by the European Union FP7

Grant No. 278568 "PRIMES". Author contributions: AM coordinated the

project, conducted most of the experimental work, and the data analysis.

MDM performed immunofluorescence experiments and contributed to set up

the purification of the chromatin samples for phosphorylation analysis, EMS

performed Haspin substrates prediction, AC crystallized Haspin-histoneH3 tail

complex, MG performed acidic extraction of the macroH2A from chromatin

samples, SJ purified CENP-T, HJL performed PS-OPLS experiment. AM, FV,

MDM, RA participated in the experimental design. KN, SKH, UHT, EMS

contributed to the data analysis. AM and RA wrote the manuscript with further

contribution from SK and FV. Competing interests: The authors declare that

they have no competing interests.

Figure legends:

Fig 1. Immunofluorescence analysis of the mitotic cells and the purified

mitotic chromatin.

(A) Schematic representation of AuroraB recruitment at centromeres.

Haspin phosphorylates Thr3 of the histone H3 (H3Thr3) at the

centromere. Survivin a component of the CPC recognize H3Thr3ph

and recruits other subunits of the complex including Aurora B

(adapted form (11)).

(B) 5-iTu has been shown to in inhibit phosphorylation of H3Thr3 at

concentration 1uM. HeLa cells were arrested in mitosis for 16

! %(!

hours with nocodazole (0.33 µM) and successively 10µ MG132

was added for 15 min to prevent mitotic exit. The cells were treated

with 1 µM 5-iTU to block Haspin activity. After 1,5 hours the mitotic

cells were isolated by shake-off and successively processed for

immunofluorescence. The cells were stained with DAPI (DNA,

blue), CREST sera (kinetochores, red), H3Thr3ph (green).

(C) Hela cells were treated as in B and stained with DAPI (DNA, blue),

CREST sera (kinetochores, red), CENP-A Ser7 phosphorylation

(green)

(D) Hela cells were prepared as in B and the mitotic chromatin purified.

Mitotic chromatin samples were gently centrifuged and stained with

DAPI (DNA, blue), CREST sera (kinetochores, red), H3Thr3ph

(green)

(E) Mitotic chromatin samples were prepared as in D and stained with

DAPI (DNA, blue), CREST sera (kinetochores, red), AuroraB

(green)

Fig 2. Inhibition of Haspin activity affects the phosphorylation status of

chromatin associate proteins.

,- Workflow describing the mass spectrometry approach used for

quantification of phosphorylation sites on chromatin proteins.

Chromatin samples were prepared as in figure 1D and the

phosphorylated peptides were enriched by titanium dioxide

chromatography (TiO2).

.- Overview of the identified phosphorylated sites on chromatin proteins.

! %)!

/- The protocol used for the purification of chromatin preserves protein-

protein interactions within the kinetochore. We identified several

phosphorylated proteins that are stably associated to the centromere

as well as proteins that just transiently localize to the corona of the

kinetochore. Either individual proteins or subunits of protein complexes

identified in this study are labeled in orange some of the other known

constituents of the kinetochore are colored in grey.

0- Volcano plot representing quantification of the phosphorylated

peptides. Logarithmic ratio of phosphorylated peptide intensities is

plotted against the negative logarithmic P-value. Blue and red circles

represent phosphorylation sites up- or down-regulated respectively

(log2FC '-3 and ( 3 and a p-value ' 0.05).

1- Functional classifications of the regulated phosphorylated proteins.

GOrilla algorithm (32) was used to retrieve statistically significant

enriched Gene Ontology (GO) terms within the set of regulated

phosphorylated proteins. Numbers on top of each bar indicate the

number of proteins in each identified GO cluster. Full list of the

enriched GO terms is available in table SS3.

Fig 3. The phosphorylation of histone macroH2A Ser137 depends by

the Haspin activity

,- Mass spectrometry quantification of the histone macroH2A doubly

charged phosphorylated peptide 135-AKS(Phospho)PSQKKPVSK-146

in chromatin samples upon Haspin inhibitor treatment. Areas of the

MS1 peaks were extracted using Skyline (86).

! %*!

.- HEK293 cells were either transfected with a cDNA encoding Haspin

(lanes 2 and 3) or the empty vector (Lane 1). Samples in lanes 3 and

4 were treated with the Haspin inhibitor 5-ITu (10uM) for 1,5 hours

before cell lysis. Protein extract were subjected to acid extraction and

analyzed by SDS-PAGE and immunodecorated with anti

phosphorylated-Ser137 of histone macroH2A, anti macroH2A, anti HA

or anti phosphorylated-Ser10 of the histone H3.

Fig 4. Kinase substrate enrichment analysis (KSEA) of the down-

regulated phosphorylated sites upon 5-iTu treatment.

,- Kinases inhibited by the 5-ITu treatment. Kinase targets were

predicted both with the Netphorest and GPS algorithms (17, 50). We

calculate the confidence of the kinase enrichments using the

hypergeometryc test distribution. The P-value cut-off was set at 5 x 10-

4 (table S4 contain the full list of kinase prediction).

.- Pie charts describing the substrates perditions for Aurora, CLK and

RSK kinases (tables S5-7 show the full list of substrates).

Fig 5. Identification of Haspin consensus motif and Haspin substrates

prediction

,- Identification of Haspin motif by positional scanning oriented peptide

library screening. Haspin reveals a strong selection for Ala in the

Ser/Thr -2, Arg in -1 and, Lys in +1 positions. Blue squared signals

denote Haspin preferences towards threonine rather than serine

residues. Negatively charged residues in the peptide substrate

! &+!

sequences prevent their phosphorylation (red squared region).

Abbreviations for the amino acid residues are as follows: A, Ala; C,

Cys; D, Asp; E, Glu; F, Phe; G, Gly; H, His; I, Ile; K, Lys; L, Leu; M,

Met; N, Asn; P, Pro; Q, Gln; R, Arg; S, Ser; T, Thr; V, Val; W, Trp; and

Y, Tyr.

.- Stabilization of the histone H3 peptide within the Haspin active site of

the Histone H3 is achieved through several direct or water-mediated

interactions.

/- In vitro kinase reaction of histone H2A full-length protein. Sequence

alignment of the Histone H2A and macroH2A sequence show good

conservation around the phosphorylation sites H2AThr16 and

macroH2A-Ser137 (bottom). Phosphorylation of Histone H3 and H2A

was detected by autoradiography 32P. Phosphorylated Histone H2A

was subjected to intact molecular weight determination by mass

spectrometry. The inset shows that Haspin preferentially

phosphorylates the histone on one site. The phosphorylated histone

H2A was digested with Arg-C protease and the peptides mixture

analyzed by LC-MS/MS. Fragmentation spectrum of the

phosphorylated peptide with sequence

AKAKT(Pho)RSSRAGLQFPVGR.

0- In vitro kinase reaction of CENP-T fragment encompassing residues 1-

101. Phosphorylation of CENP-T and histone H3 was detected by

autoradiography. Phosphorylated CENP-T 1-101 was subjected to

intact molecular weight determination by mass spectrometry. The inset

shows that Haspin preferentially phosphorylates the protein on three

! &"!

and four residues respectively. The phosphorylated CENP-T 1-101

protein fragment was digested with Arg-C protease and the peptide

mixture analyzed by LC-MS/MS. We identified phosphorylation events

on Thr14/27/57 and Ser72 residues. The spectrum shows the

fragmentation of the peptide sequence

ALLETASPRKLSGQTRT(Pho)IAR.

Fig 6. A Haspin protein-protein interaction network

A) Haspin was expressed in Hek293 cell as strep-HA fusion protein. The

complex was purified from nococazole-arrested cells as well as cycling

cells. Only high confidence protein interactions are displayed (see

material and methods). The violet square groups proteins identified

being part of the splicesome complex (www. spliceosomedb.ucsc.edu).

The Green square groups proteins involved in the regulation of gene

transcription. Blue edges indicate protein-protein interactions annotated

in the STRING database with confidence score ( 0.4. Only

“experiments” and “databases” were considered as prediction methods

in STRING.

B) STRING interaction network of top scoring Haspin predicted substrate

proteins (green squares) and Haspin interacting partners. Blue edges

represent protein-protein interaction as described in (A)

16  hrs  33  nM

0.5  hrs  10  uM

1.5  hrs  1  uM

 

Figure  1

EC

BA

Control

1  M  5-­iTU

Control

1  M  5-­iTU

DControl

1  M  5-­iTU

Control

1  M  5-­iTU

CREST H3-­T3Ph isolated  DNA Merge

CREST AurB isolated  DNA Merge

CREST H3-­T3Ph CREST  H3-­T3Ph Overlay

CREST CenpA-­S7Ph CREST  CenpA-­S7Ph Overlay

Nocodazole IFMG132   5-­ITu  

16  hrs  33  nM

0.5  hrs  10  uM

1.5  hrs  1  uM

 Nocodazole IFMG132   5-­ITu   Chromatin  purification

Haspin

Inhibitor

Aurk B

Sur

INCE

NP

BOR

P

5-iTu

Thr3

H3

H2A H2B

H4

 Control

LC-­MS/MSIdentification  and  quantification

Mitotic  Chromatin  purification  

A

B

C

D E

 Haspin  inhibitor5-­Iodo  tubercidin

Mitotic  Chromatin  purification  

Phosphorylated  peptidesenrichment

9   188  

1287  

6537  

4  Phosphorylation  sites  3  Phosphorylation  sites  2  Phosphorylation  sites  1  Phosphorylation  sites  

4605  

1217  

0  

1000  

2000  

3000  

4000  

5000  

6000  

7000   NovelPhosphorylation  sites  KnownPhosphorylatiion  sites  

1.00E-­30  

1.00E-­27  

1.00E-­24  

1.00E-­21  

1.00E-­18  

1.00E-­15  

1.00E-­12  

1.00E-­09  

1.00E-­06  

1.00E-­03  

1.00E+00  

chromosome  organization  

RNA  processing  

RNA  splicing  

chromatin  organization  

cell  cycle  process  

chromatin  modification  

regulation  of  RNA  splicing  

regulation  of  gene  expression  

chromosome  segregation  

mitosis  

DNA  packaging  

Log10  P-­value  

Kinetochoremicrotubules

CentromereCENP-­A  nucleosomes

DLGAP5

RanGAPRanBP2

LIS1

CRM1 Nup  107-­160complex APC/C

Dynein/dynactin

Mtw1Mis12complex

Spc105/KNL1

CENP-­P CENP-­Q CENP-­UCENP-­O

CENP-­I

CENP-­K CENP-­R

ZWINT

CENP-­L CENP-­M

CENP-­H

CENP-­S CENP-­X CENP-­W

PLK1

MPS1

PLK1

Ndc  80HEC

complex

KIF23

KIF23

Fibrous  corona

Outer  kinetochore

Inner  kinetochore

AurB

SURINCENP

BORAurB

SURINCENP

BOR MCAK

BUB1

BUB3

MPS1

MAD2

CENP-­F

RZZ

MAD1

MCAK

Spindly

CENP-­TCENP-­C CENP-­N

SGOL1

ch-­TOG1  dimer

BUB3

HASP

EB1  dimer

CLASP1

CENP-­E

BUBR1

Cdc20

Cdc20

Cdc20Cdc20

Soluble  Cdc20  pool

CLIP

170

CLASP2

Nde1Ndel1

CENP-­B

Kif2b

Ska1Ska2

1289  

4375  

158  

Thr  PhosphorylationsSer  PhosphorylationsTyr  Phosphorylations

64

57

3844

56

31

12 108 12 18 9

Log2 Fold Change

V

0

5

10

15

20

25

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Figure  2

0.1  

1  

10  

100  

Log10  of  Peak  Area  

AKS(Pho)PSQKKPVSK  Ser137  macroH2A    

Control  

5-­iTu  

A

B

 

Anti  histone  

macroH2A  Ser137ph

Anti  histone  

macroH2A  

Anti  histone

 H3  Ser10ph

Anti  HA  Tag

(Haspin-­HA  tagged)

35  KDa  

55  KDa  

40  KDa  

35  KDa  

40  KDa  

Haspin -

-

- - - -

- +

+

+

+

+-

- -

Inhibitor

Empty vector

15  KDa

1.5  hrs    

Haspin  transfection

HEK293  cells

Histones  

acidc  extraction

WB

Cell  lysis  

5-­ITu  

Figure  3

A

B

AUR

Aurorapredicted  substrates

CLKpredicted  substrates

RSKpredicted  substrates

2.79E-­06CLK_group 2.86E-­05AGC.RSK 0.00017791

4  

14  

8   Other  

Mitosis  

Histon  

10  5  

3  

Gene  expression/Splicing  factor  

Microtubles  stabilization  and  organization  

Other  4  

2  

4  

1  

Regulation  of  transcription    

Figure  4

Other  

Histon    associated  protein

Histon  

Figure  5

poly Ser/Thr peptides

786.4198

791.7550

805

800

795

790

785

780

775

3P15+781.0904

P

P

5P

13871303

12221143

1067993

922854

788725

665

100

0

Histone H

3Hist

one H2A

Haspin

b9 -98968.6

y9944.5

y16++906

y15++870.5

y7816.5

b15 -98++791.5

b14 -98++742.9

y13++715.9

b12++654.4

y16+++604.3

b11++597.8

y11++594.3

y10++550.8b14 -98+++495.6b5-98

482.3

y4428.3

b4=399.3

y2232.1

b2200.1

200 400 600 800 1000 1200 1400 m/z

Inte

nsity

AKAKT(Pho)RSSRAGLQFPVGR, Charge 3 H2A1-Thr 16

100

0

P

663

660

657

672

669

666

678

675

21+665.2790

21+669.0863

21+672.8868

P

950900

850800

1000

100

0

y ++1 0 3 2 . 5

y79 2 5 . 4y1 5 -9 8 ++

8 1 2 . 1

b1 4 ++7 2 6 . 8

b76 8 5 . 9

y1 1 ++6 5 6 . 6

y5 -9 85 9 8 . 7

pre c u rso r -9 8 ++++5 3 8 . 8

y9 ++5 3 5 . 9

b9 ++4 7 0 . 6

b44 2 7 6b7 ++

3 4 4

b32 9 7 . 9

y22 4 6 . 4

b21 8 4 . 9

200 400 600 800 1000 1200 m/z

Inte

nsity

1 8

ALLETASPRKLSGQTRT(Pho)IAR, Charge 4 CENPT-Thr54

Histone H

3CEN

P T 1-101

Haspin

Histone_H2A1              11    RAKAKTRSSRAGL  -­23Histone_macro-­H2A  132    AKKAKSPSQKKPV  -­144

A

C D

B

P G A C S T V I L M F Y WH K R Q N D E-5-4-3-2-1

+1+2+3+4

Fixed residue

Fixe

d po

sitio

n

0- S T

pTpY

Y-A-X-X-X-X-X-S/T-X-X-X-X-A-G-K-K(biotin)-5 -4 -3 -2 -1 +1+2+3+40

-1

A1R2 T3 K4

Q5E613

hinge

!AS

Q718

activationloop

!F

D649 (HRD)

"1

!-uIH-"5loop

W652

D714

D707

D709L710

N588N522

E492

"7

2.8

2.9

2.7

2.9

2.6

2.8

2.93.0

3.02.7

2.9

2.7

2.8

2.8

2.8

3.02.6

5-iTU

-2 0 +1

+2

A B

Haspin  Strep-­HA

Purification  

 Hek293

cell

Haspin interacting partners

Haspin interacting partners Haspin top scoring predicted substrates

LC-MS/MSIdenti!cation of

Haspin Binding partners

PSMD2 TCOF

RL37A

MYO1B

SHRM3

EIF3J

LG3BP

C1TC

DNJA1

U520

RUVB2

HNRL1

DDB1

RBMX

CHIP

HNRPC

H2B1J

RS15

G3BP1

FBRL

H13

IPO5

TBB6

K1967 SF3B1

PRP8

UBR5

U5S1

DHX15

LC7L2

SF3B2

RTCBHNRPF

TBB4A

TBA1C

RS5MUC5A

DNJA2

SEMG1 IQGA2

STIP1

PSME3

RUVB1

HNRPQ

ROA0

PRP19

HS90A

SF3B3

H2A1

Splicing  Database

Regulation  of  Genes

trascription

LAP2 TRA2A

CLK2

NPAT

PRP4B

SF3B3

U520

U5S1

HNRL1

SF3B2

ROA0HS90A

RUVB2

PRP8

HNRPC

DDB1

K1967

CHIP

UBR5

STIP1

SRSF7

TRA2B

SRS11

NUP93 SRSF2

SRSF1

HNRPF

PRP19

RUVB1 RBMX

DNJA1

FBRL

DHX15DNJA2

SF3B1

Figure  6