HTRA1 dependent cell cycle proteomics

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HTRA1 dependent cell cycle proteomics Jasmin Schillinger, Katharina Severin, Farnusch Kaschani, Markus Kaiser, and Michael Ehrmann J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00129 • Publication Date (Web): 04 Jun 2018 Downloaded from http://pubs.acs.org on June 4, 2018

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Journal of Proteome Research

HTRA1 dependent cell cycle proteomics

Jasmin Schillinger1, Katharina Severin1, Farnusch Kaschani1, Markus Kaiser1 and Michael Ehrmann1,2 * 1

Centre of Medical Biotechnology, Faculty of Biology, University Duisburg-Essen,

Universitaetsstrasse, 45141 Essen, Germany 2

School of Biosciences, Cardiff University, Cardiff CF10 3US, UK

*

Corresponding author:

Email: [email protected], Phone: +49-201-183 2949

Running title: Cell cycle proteomics

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ABBREVIATIONS Async

Ansynchronous

BrdU

Bromodeoxyuridine

CID

Collision-induced dissociation

CP-ISD

Complex Proteome and In-Solution Digest

EV

Empty vector

FA

Formic acid

FBS

Fetal bovine serum

FDR

False discovery rate

FTMS

Fourier Transform Mass Spectrometry

GOBP

Gene ontology biological process

GOCC

Gene ontology cell compartment

HCl

Hydrochloric acid

IAM

Iodoacetamide

ITMS

Ion Trap Mass Spectrometry

LFQ

Label-free quantification

PI

Propidiumiodide

UHPLC

Ultra high performance liquid chromatography


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ABSTRACT The HTRA1 gene encoding an evolutionary conserved protein quality control factor can be epigenetically silenced or inactivated by mutation under pathologic conditions such as cancer. Recent evidence suggests that loss of HTRA1 function causes multiple phenotypes including acceleration of cell growth, delayed onset of senescence, centrosome amplification and polyploidy suggesting an implication in the regulation of the cell cycle. To address this model, we performed a large-scale proteomics study to correlate the abundance of proteins and HTRA1 levels in various cell cycle phases using label-free quantification mass spectrometry. These data indicate that the levels of 4723 proteins fluctuated in a cell cycledependent, 2872 in a HTRA1-dependent and 1530 in a cell cycle- and HTRA1-dependent manner. The large number of proteins affected by the modulation of HTRA1 levels support its general role in protein homeostasis. Moreover, the detected changes in protein abundance in combination with pull down data implicate HTRA1 in various cell cycle events such as DNA replication, chromosome segregation and cell cycle dependent apoptosis. These results highlight the wide implications of HTRA1 in cellular physiology.

INTRODUCTION Human HTRA1 is a member of the widely conserved high-temperature requirement A (HtrA) family of homo-oligomeric serine proteases implicated in all aspects of protein quality control i.e. recognition of misfolded, mislocalized or fragmented proteins as well as their refolding and proteolytic degradation. The ubiquitously expressed HTRA1 consists of a signal sequence for secretion, a partial insulin like growth factor binding protein-7 domain of unknown function, a S1 serine protease domain and a C-terminal PDZ domain. The PDZ domain of HtrA proteases binds the four C-terminal residues of other proteins. This event can result in allosteric activation of protease activity or determine subcellular location. HTRA1 has at least three cellular locations. The extracytoplasmic pool is involved in the homeostasis ACS Paragon Plus Environment

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of the extracellular matrix while intracellular HTRA1 localizes to microtubules or to the nucleus (for review see(1)) Human HTRA1 is associated to severe pathologies including cancer, age-related macular degeneration, Alzheimer's disease, arthritis and familial ischemic cerebral smallvessel disease.(1) Interestingly, HTRA1 expression is downregulated in many tumors, often by epigenetic mechanisms.(2, 3) Correspondingly, forced reexpression interferes with proliferation of metastatic melanoma cells and cell migration.(4, 5) In addition, HTRA1 modulates cisplatin- and paclitaxel-induced cytotoxicity and low levels of HTRA1 correlate with a poor response to drug treatment while higher levels of HTRA1 correlate with a better response.(6) Moreover, loss of HTRA1 function in cells causes multiple phenotypes such as increased rates of proliferation, delayed onset of senescence, centrosome amplification and polyploidy.(7) These phenotypes suggest an implication of HTRA1 in the regulation of the cell cycle. To initially address the important question of mechanism, proteomic approaches were used to correlate the abundance of proteins to various cell cycle phases and HTRA1 levels.

EXPERIMENTAL PROCEDURES Cell Culture and Synchronization - SW480 and HeLa cells were maintained in RPMI-1640 and DMEM (Gibco), respectively, each supplemented with 10% (v/v) fetal bovine serum (FBS) and 100 units each of penicillin and streptomycin (Gibco) at 37°C in a 5% CO2humidified incubator. Generation and characterization of SW480 cell lines stably expressing various levels of HTRA1 were described previously.(7) For synchronization, SW480 cells were grown in 10 cm dishes to approximately 50% confluency and treated with 4 mM thymidine (Sigma) for 21 h (single thymidine block) or 24 h (double thymidine block). For both, M- and G1-phase cells, a single thymidine treatment was followed by a 4.5 h release


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and the addition of 100 ng/ml Nocodazole (Sigma). 14 h after Nocodazole addition, a “mitotic shake-off” was performed to isolate mitotic cells from the overall cell population. M-phase samples were collected immediately. For G1-phase samples, collected cells were re-plated after Nocodazole wash-out and harvested 4 h after release by the addition of trypsin-EDTA (Gibco) and transferred to LoBind microcentrifuge tubes (Eppendorf). For S- and G2-phase synchronization, cells were treated with a double thymidine block (two times 4 mM thymidine for 24 h with a 11 h release in between). 3 h after the release from the second thymidine treatment, S-phase cells were harvested by the addition of trypsin-EDTA, while G2-phase cells were then treated with 10 µM of the Cdk1 inhibitor RO-3306 (Sigma) for 9 h before harvesting the cells. To obtain a cell population consisting of all cell cycle phases except for S-phase (“All but S”), cells were released from Cdk1 inhibitor treatment for 3 h (shHTRA1 cell line) or 5 h (all other SW480 cell lines). For mass spectrometry analysis, four independent biological replicates were prepared for each cell cycle phase and cell line. Cell pellets were frozen in liquid nitrogen and stored at -80°C. One additional replicate was prepared for flow-cytometry analysis. For Western blot analyses, whole cell lysates were prepared by incubating cells in ice cold lysis buffer (50mM Tris HCl pH 7.4, 150mM NaCl, 1% NP4, 0,5% Na-deoxycholat (DOC), 0,1% SDS, 1 mM EDTA) containing cOmpleteTM Protease Inhibitor Cocktail (Roche) and Phosphatase Inhibitor Cocktails 2 and 3 (Sigma) for 20 min on ice prior to sedimentation of cell debris (16,000 g, 15 min, 4°C). To obtain HeLa cells for carrying out affinity enrichment experiments, for each sample and condition 2*106 cells were plated onto 15 cm dishes and grown for approximately 4 days to 80% confluency. After washing the cells three times with PBS (life technologies), the cells were carefully harvested with a cell scraper in PBS, transferred to a falcon tube and pelleted by centrifugation at 230 g for 5 min. Cells were resuspended in 1 ml PBS, transferred to an LoBind microcentrifuge tube (Eppendorf) and again pelleted by centrifugation. The


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supernatant was removed and the cell pellets were frozen in liquid nitrogen and stored at 80°C until they were used for pulldown experiments.

Antibodies – For Western blotting analyses the following antibodies were used: Actin (MP Biomedicals), ANXA1 and CDK6 (Cell Signaling), APC3 (lab collection), Mad1 (lab collection), PSME1 (Abcam), Septin-2 (Sigma), α−Tubulin (Sigma), β−Tubulin (Abcam), γ−Tubulin (Sigma). RNA purification and quantitative real-time-PCR analysis – RNA was purified from SW480 cells as described before. (Schmidt et al., 2017) All measured transcripts were normalized to the transcript of the “house-keeping” gene GAPDH by the Q-Gene software. (Simon, 2003) Flow-Cytometry - For cell cycle analyses, SW480 cells were pulsed with 10 µM Bromodeoxyuridine (BrdU, Sigma) 30 min prior to harvest under standard growth conditions. Cells were washed with PBS twice and collected by the addition of trypsin-EDTA (M-phase cells by “mitotic shake-off”). Subsequently, cells were resuspended in PBS. Cold methanol was added to a final concentration of 90% and samples were fixed at -20°C overnight. Methanol was removed and the cells were washed in cold PBS twice. To denature double stranded DNA, cells were incubated in 2 M Hydrochloric acid (HCl) solution with 0.5% Triton X-100 (Pierce) for 30 min at 37°C and 1000 rpm. Subsequently, samples were washed with PBS containing 0.01% Triton X-100 three times until the cell suspension was of neutral pH. Samples were incubated with an antibody solution containing anti-BrdU-FITC antibody (Pharmingen) in PBS with 0.01% Triton X-100 and 1% BSA (Sigma) for 1 h in the dark at 37°C. To estimate the overall DNA content, cells were stained with a Propidiumiodide (PI) solution (25 µg/ml PI (Sigma) in PBS, 0.01% Triton X-100 and 10 µg/ml RNase (Sigma)) for 30 min in the dark at 37°C and 1000 rpm. Cells were strained over a cell strainer (pore size 30 µM) and subjected to the MACSQuant VYB flow-cytometer. ACS Paragon Plus Environment

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For the analysis of programmed cell death, SW480 cells were treated with 15 µM 5fluoruracil (5-FU, Sigma), 10 µM Q-VD-OPh hydrate (Q-VD, Sigma) or DMSO for 72 h. Cells were washed with PBS and collected by the addition of trypsin-EDTA. All cells from the cell culture supernatant, the washing step and the trypsin-EDTA incubation were sedimented. To extract the cellular nuclei and stain the DNA, sedimented cells were incubated in a PI solution (50 µg/ml PI (Sigma), 0.1% Sodium citrate, 0.1% Triton X-100 and 100 µg/ml RNase (Sigma)) for 90 min in the dark at 4°C. Subsequently, cells were subjected to the MACSQuant VYB flow-cytometer. Data analysis was performed with FlowJo software (version 10.2). Only single cells were used for quantification. Percentages given correspond to the parental gate. Statistical analyses of flow-cytometry experiments were done using GraphPad Prism 5 software. Normal distribution and variance homogeneity were tested via a Komologrov Smirnov test (alpha=0.05). Normally distributed data sets showing variance homogeneity were analyzed via two-tailed student’s t-tests (2 groups) or One-Way-ANOVA with Tukey post-hoc-test (>2 groups). Other data sets were analyzed using a Mann-WhitneyUTest (2 groups) or Kruskal-Wallis with Dunns post-hoc-test (>2 groups).

In Vitro Proteolytic Digest – For proteolytic digests HTRA1 was recombinantly expressed in E. coli and purified as published.(8) Recombinant Annexin A1 (ANXA1) was obtained from Cellsciences (CSI17770B), CDK6 from Abnova (H00001021-P01). HTRA1 and ANXA1 were incubated at a molar substrate/protease ratio of 5:1 (2.5 µM:0.5 µM), CDK6 and HTRA1 at a ratio of 2.5:1 in 150 mM sodium phosphate pH 7.4, 380 mM NaCl at 37°C. Samples were taken at the indicated time points (Fig. 3C, Fig. S7) mixed with loading dye and 100 mM DTT, boiled for 2 min at 95°C and flash frozen in liquid nitrogen. Subsequently, samples were subjected to SDS-PAGE and Coomassie or silver staining.

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Complex Proteome and In-Solution Digest (CP-ISD) - From synchronized SW480 cell populations we generated whole cell lysates. For each cell line and phase, four biological replicates were prepared. Sedimented cells were resuspended in 100 µL phosphate buffered saline (PBS) containing 8 M urea and incubated on ice for 20 min. To break the cells, release the proteome and to shear the genomic DNA, the samples were lyzed by ultrasonification in a Bioruptor® (Diagenode) for 15 min (1 min pulse, 30 sec pause, high voltage, 4°C). Cell debris was removed by centrifugation (20 min, 16,000 g, 4°C) and the protein concentration of the lysates adjusted to 0.5 µg/µL. The proteins were reduced by addition of dithiothreitol (DTT, 5 mM, 37°C, 30 min) and secondly alkylated by the addition of iodoacetamide (IAM, 20 mM, 30°C, 30 min). To quench the excess IAM, we added more DTT to a final concentration of 25 mM. After this treatment 830 ng Lys-C were added (1:30; Wako Laboratory Chemicals) and the samples were incubated for 3 h at 37°C. The samples were next diluted with ABC solution to 25 mM ABC and 1.0 M urea. 830 ng sequencing grade trypsin (1/30; Promega) were added and the samples were incubated over night at 37°C while shaking. The digestion was stopped the next morning by adding formic acid (FA, final 0.5% v/v). Acidified tryptic digests were concentrated and desalted on home-made C18 StageTips as described.(9) On each 2 disc StageTip we loaded around 15 µg peptides (based on the initial protein concentration). After elution from the StageTips, samples were dried using a vacuum concentrator (Eppendorf) and the peptides were taken up in 10 µL 0.1% formic acid solution.

HTRA1 Affinity Enrichment and In-Solution Digest (AE-ISD) - Frozen HeLa cell pellets from 15 cm dishes were thawed in 500 µl ice-cold lysis buffer (50 mM HEPES, pH 7.4, 150 mM NaCl, 0.5% (v/v) IGEPAL, containing cOmpleteTM Protease Inhibitor Cocktail (Roche) and Phosphatase Inhibitor Cocktails 2 and 3 (Sigma) on ice and resuspended with a pipet until the suspension was homogenous. After incubating on ice for 10 min, the cell lysates were ACS Paragon Plus Environment

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centrifuged at 16,000 g at 4°C for 15 min. The cleared lysates were added to 100 µl of PureCube HiCap StrepTactin® MagBeads (Cube Biotech) that were pre-washed in lysis buffer and pre-incubated with 70 µg of different Strep-tagged HTRA1 variants (HTRA1 S328A, ∆PDZ HTRA1 S328A) or buffer alone (Control) in LoBind microcentrifuge tubes (Eppendorf) for 1 h at 4°C and the samples were again incubated on a rotating wheel for 1 h at 4°C. After discarding the supernatants, the beads were washed once with 500 µl lysis buffer and four times with 500 µl wash buffer (50 mM HEPES, pH 7.4, 150 mM NaCl). Proteins were eluted by incubating with 180 µl of elution buffer (50 mM HEPES, pH 7.4, 150 mM NaCl, 10 mM Biotin) for 10 min on a rotating wheel at 4°C. The eluates were transferred to new LoBind microcentrifuge tubes. 30 µl of each sample were used for analysis with SDS-PAGE followed by silver staining. The remaining sample was processed for mass spectrometry analysis. Alternatively, the eluates were obtained by boiling the beads in 50 µl 1x SDS sample buffer and used for Western blot analysis. Samples for mass spectrometry analysis were precipitated with trichloroacetic acid (TCA). Protein pellets were resuspended in 50 µl denaturing buffer (50 mM NH4HCO3, pH 7.8, 8 M urea), reduced with 5 mM TCEP, alkylated with 10 mM iodoacetamide, and diluted to 1.5 M urea. Each sample was incubated with 5 µg sequencing grade modified trypsin (Promega) at 37°C for 18 h. Formic acid was added to a final concentration of 0.5% (v/v).

LC-MS/MS Analysis - Experiments were performed on an Orbitrap Elite instrument (Thermo, (10)) that was coupled to an EASY-nLC 1000 liquid chromatography (LC) system (Thermo). The LC was operated in the one-column mode. The analytical column was a fused silica capillary (75 µm × 420 cm for CP-ISD and 75 µm × 380 cm for AE-ISD) with an integrated PicoFrit emitter (New Objective) packed in-house with Reprosil-Pur 120 C18-AQ 1.9 µm resin (Dr. Maisch). The analytical column was encased by a column oven (Sonation) and ACS Paragon Plus Environment

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attached to a nanospray flex ion source (Thermo). The column oven temperature was adjusted to 45°C during data acquisition and in all other modi at 30°C. The LC was equipped with two mobile phases: solvent A (0.1% formic acid, FA, in water) and solvent B (0.1% FA in acetonitrile, ACN). All solvents were of UHPLC (ultra high performance liquid chromatography) grade (Sigma). Peptides were directly loaded onto the analytical column with a maximum flow rate that would not exceed the set pressure limit of 980 bar (usually around 0.4 – 0.6 µL/min). Peptides from CP-ISD experiments were subsequently separated on the analytical column by running a 240 min gradient of solvent A and solvent B (start with 7% B; gradient 7% to 35% B for 220 min; gradient 35% to 100% B for 10 min and 100% B for 10 min) at a flow rate of 300 nl/min. Peptides from AE-ISD experiments were separated on the analytical column by running a 90 min gradient of solvent A and solvent B (start with 7% B; gradient 7% to 35% B for 80 min; gradient 35% to 100% B for 5 min and 100% B for 5 min) at a flow rate of 300 nl/min. The mass spectrometer was operated using Xcalibur software (version 2.2 SP1.48). The mass spectrometer was set in the positive ion mode. Precursor ion scanning was performed in the Orbitrap analyzer (FTMS; Fourier Transform Mass Spectrometry) in the scan range of m/z 300-1800 and at a resolution of 60000 with the internal lock mass option turned on (lock mass was 445.120025 m/z, polysiloxane).(11) Product ion spectra were recorded in a data dependent fashion in the ion trap (ITMS; Ion Trap Mass Spectrometry) in a variable scan range and at a rapid scan rate. The ionization potential (spray voltage) was set to 1.8 kV. Peptides were analyzed using a repeating cycle consisting of a full precursor ion scan (3.0 × 106 ions or 50 ms) followed by 12 (AE-ISD) or 15 (CPISD) product ion scans (1.0 × 104 ions or 50 ms) where peptides are isolated based on their intensity in the full survey scan (threshold of 500 counts) for tandem mass spectrum (MS2) generation that permits peptide sequencing and identification. CID (collision-induced dissociation) collision energy was set to 35% for the generation of MS2 spectra. During MS2 data acquisition dynamic ion exclusion was set to 60 seconds with a maximum list of ACS Paragon Plus Environment

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excluded ions consisting of 500 members and a repeat count of one. Ion injection time prediction, preview mode for the FTMS, monoisotopic precursor selection and charge state screening were enabled. Only charge states higher than 1 were considered for fragmentation.

Data Analysis - RAW spectra were submitted to an Andromeda (12) search in MaxQuant (version 1.5.3.30) using the default settings.(13) Label-free quantification and matchbetween-runs was activated.(14) MS/MS spectra data were searched against the UniProt reference H. sapiens database (UP000005640_9606.fasta; 70244 entries). All searches included a contaminants database (as implemented in MaxQuant, 245 sequences). The contaminants database contains known MS contaminants and was included to estimate the level of contamination. Andromeda searches allowed oxidation of methionine residues (16 Da) and acetylation of protein N-terminus (42 Da) as dynamic modification and the static modification of cysteine (57 Da, alkylation with iodoacetamide). Digestion mode was set to “specific”, enzyme specificity was set to “Trypsin/P” with 2 missed cleavages allowed. The instrument type in Andromeda searches was set to Orbitrap and the precursor mass tolerance was set to ±20 ppm (first search) and ±4.5 ppm (main search). The MS/MS match tolerance was set to ±0.5 Da. The peptide spectrum match FDR and the protein FDR were set to 0.01 (based on target-decoy approach). Minimum peptide length was 7 amino acids. For protein quantification, unique and razor peptides were allowed. Modified peptides were allowed for quantification. The minimum score for modified peptides was 40. Resulting data sets were analyzed using PERSEUS computational platform (version 1.5.6.0.).(15) Proteins identified as contaminants, present in the reversed database or only by site were excluded from analysis. Proteins identified in at least 3 out of four replicates and in at least one cell cycle phase were kept, to not omit proteins that change their abundance in only one cell cycle phase. Comparison of protein group quantities (relative quantification) between different MS runs is based solely on the LFQ’s as calculated by MaxQuant (MaxLFQ algorithm). Briefly, LabelACS Paragon Plus Environment

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free protein quantification was switched on and unique and razor peptides were considered for quantification with a minimum ratio count of 2. Retention times were recalibrated based on the built-in nonlinear time-rescaling algorithm. MS/MS identifications were transferred between LC-MS/MS runs with the “Match between runs” option in which the maximal match time window was set to 0.7 min and the alignment time window set to 20 min. The quantification is based on the “value at maximum” of the extracted ion current. At least two quantitation events were required for a quantifiable protein.(14) Imputation of LFQ intensities was performed according to a normal distribution and intensities were logarithmized (base 2). Statistical analysis was performed with Perseus. GO-term analysis was performed with Perseus software or the GOrilla online tool.(16) Data availability – The mass spectrometry proteomics data have been deposited to the ProteomeXchange

Consortium

via

the

PRIDE

partner

repository

(https://www.ebi.ac.uk/pride/archive/) (17) with the dataset identifier PXD007079. During the review process the data can be accessed via a reviewer account (PXD007079: Username: [email protected]; Password: kbE9Ji6H.


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RESULTS The pleiotropic phenotypes of HTRA1 null cells including accelerated cell growth, delayed onset of senescence, centrosome amplification and polyploidy suggest an implication of HTRA1 in the regulation of the cell cycle. This is of particular interest in the context of tumorigenesis as HTRA1 expression is often epigenetically downregulated in cancer cells. However, the molecular mechanisms underlying pleiotropic phenotypes are often complex i.e. the result of a combination of direct and indirect effects and cellular adaptations to deregulation. As HTRA1 protease is a widely conserved protein quality control factor, protein abundance and protein-protein interactions are considered critical components of underlying mechanisms. These events are best addressed by powerful proteomic approaches.(18-20) We therefore performed cell cycle-dependent proteome analyses of colon cancer SW480 cells in which HTRA1 was either stably downregulated via a shRNA or upregulated via plasmid, and the corresponding empty vector controls (Fig. S1).(7) HTRA1 levels of these cells have been published previously.(7) Note that in contrast to e.g. trypsin, HTRA1 is a conformation specific but not a sequence specific protease. Therefore, the overproduction of HTRA1 should be not detrimental and have a rather mild effect on the abundance of target proteins. This notion is supported by the analyzed proteome data set (see below). Briefly, following synchronization, cells were lyzed and cytosolic fractions were digested with Lys-C and trypsin. The generated peptides were subjected to stage tipping and analyzed by nano LC-MS. Subsequently, data were analyzed using MaxQuant and Perseus software (Fig. 1A).

Profiling cell cycle phase enrichment of synchronized SW480 cells - To perform proteome analysis during the cell cycle, SW480 cells were synchronized to enrich populations of cells from distinct cell cycle phases. Asynchronous cells served as a control. For each cell line and phase, four biological replicates were prepared. Flow-cytometry analysis was performed to determine the fraction of single cells enriched in a distinct phase of the cell cycle. Cells were ACS Paragon Plus Environment

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synchronized in G1- and M-phase using a single thymidine block followed by a 4.5 h release and subsequent addition of 100 ng/ml Nocodazole. “Mitotic shake-off” was performed 14 h after Nocodazole addition to isolate mitotic cells. M-phase cells were immediately collected for MS or flow-cytometry analysis. To obtain G1-phase samples, cells were re-plated after Nocodazole wash out and harvested 4 h after release. This procedure resulted in a yield of >96% M-phase and 60 – 72% G1-phase cells (Fig. 1A, Fig. S2). For S- and G2-phase synchronization, cells were treated with a double thymidine block. 3 h after thymidine release, S-cells were harvested. For G2-phase synchronization, cells were additionally treated with a cyclin-dependent kinase (Cdk) 1 inhibitor for 9 h. Synchronized cell populations showed an enrichment of 68 – 80% S-phase and 61 – 67% G2-phase cells (Fig. 1A, Fig. S2). An additional cell population was generated, termed “all but S”, consisting of all cell cycle phases except for S-phase (release after Cdk1 inhibitor treatment), to provide an additional data set for underrepresented cell cycle phases. The remaining number of S-cells in this condition was 11 - 26%. Note, that “all but S-phase” samples were collected at different time points, to gain the lowest number of S-phase cells possible (shHTRA1 cells 3 h after release, all other cell lines 5 h after release from Cdk1 inhibitor).

Analysis of the SW480 proteome during the cell cycle - To analyze the proteomes of the four cell lines at various stages of the cell cycle, total protein from synchronized cells was reduced and alkylated under denaturing conditions and digested with LysC and trypsin. The resulting peptides were desalted on stagetips and subsequently separated by reversed phase UPLC and on-line analyzed by mass spectrometry. In total, we obtained 96 RAW files (4 cell lines × 6 cell states × 4 biological replicates) which were submitted to simultaneous database search in MaxQuant. MaxQuant determined the label-free quantification (LFQ) intensities for the identified proteins. The initially identified 6864 proteins were checked for contaminants, the presence in the reversed database or identification only by site. The unfiltered search results ACS Paragon Plus Environment

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(proteinGroups.txt and peptide.txt) were uploaded to the PRIDE repository (access PXD007079). Of the remaining 6529 proteins, we kept those that were identified in at least 3 out of four replicates and in at least one cell cycle phase. This setting was required, to not omit proteins that change their abundance in only one cell cycle phase, which is a known event in cell division. Applying this filter, this analysis yielded 5639 proteins, 3441 and 5036 of which were identified in all 96 LC-MS (100%) or 48 LC-MS runs (50%), respectively. LFQ intensities were imputed according to a normal distribution and logarithmized (base 2). As an internal quality control, we first analyzed the Pearson product-moment correlation coefficients for all samples. The coefficient within a set of biological replicates was always >0.983, indicating similar datasets. The coefficient between samples from different treatments was >0.850, indicating, that the treatments affected the respective proteomes, as expected (Fig. S3). To verify the correct synchronization of SW480 cells, the abundance of wellestablished cell cycle regulators was monitored over all cell cycle phases (Fig. 1B). Indeed, cyclins A, B1/B2 and D fluctuated during the cell cycle in an expected manner.(21) Note that cyclin E abundance could not be evaluated because this protein was not identified in any of the 96 LC-MS experiments. Two independent statistical strategies were employed to obtain a first indication how protein abundancies vary in a cell cycle and/or HTRA1 dependent manner, and which biological processes are particularly affected. First, Z-scores were calculated for the whole data set, biological replicates were averaged and hierarchical clustering of cell cycle phases was performed using Perseus software. This analysis was performed for each cell line separately. As expected, large variances in protein abundance were observed over the cell cycle in all cell lines (Fig. 2A, Fig. S4). This observation was supported by two-tailed student’s t-tests (FDR 0.05, S0 0.1) comparing synchronized samples to the asynchronous controls. The subsequent quantification of differentially abundant proteins in the distinct cell cycle phases yielded up to 3972 significant hits (Fig. 2B). The analysis was performed for each cell line separately ACS Paragon Plus Environment

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followed by GO-term enrichment analyses (Fisher exact test, Benjamini-Hochberg FDR 0.02). As a control, data were screened for GOBP-terms commonly associated with distinct cell cycle phases to confirm a successful implementation of the analysis. For S-phase, the GO-term “DNA replication” was enriched in all cell lines (p-values between 1e-09 and 2e04). All M-phase samples showed an enrichment of GOBP (Gene Ontology Biological Process)-terms associated with mitosis and mitotic cell cycle (p-values between 4e-09 and 4e04). Note that the strongest changes were observed in M-phase cells, probably because these are underrepresented in an asynchronous cell population. Moreover, hierarchical clustering led to the identification of five protein clusters (Fig. 2A, Fig S3). The enrichment of Gene ontology term annotations referring to biological processes was analyzed by Fisher exact tests of the protein clusters (Benjamini-Hochberg FDR 0.02). The first four clusters contained similar GOBP-terms in all cell lines. However, the patterns of protein levels within individual clusters differed between cell lines (Fig. S4). To further analyze these differences, hierarchical clustering was repeated. In contrast to the first analysis, the four cell lines were clustered for each cell cycle stage. These results confirm major differences between shHTRA1, pHTRA1 and EV cells in a cell cycle depended manner (Fig. S5). Differences were most striking in G2- and S-phase, suggesting a particular role of HTRA1 in these cell cycle stages. Note that shHTRA1 cells always clustered separately and showed higher variance compared to the EV controls than pHTRA1 cells, suggesting that overexpression of HTRA1 has fewer consequences compared to loss of HTRA1. This view might be best explained by the model that native protease levels are sufficient to modulate target protein abundance. For a closer inspection of differential protein abundance, we performed a Two-way ANOVA statistical analysis including the logarithmic label-free quantification (LFQ) intensities of all synchronized samples, thereby correlating protein abundance with cell cycle stage and HTRA1 level, respectively (Fig. 3A). To allow comparison of protein abundancies in defined cell cycle stages asynchronous controls were not included. Three datasets were obtained: ACS Paragon Plus Environment

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protein levels fluctuating (i) in a cell cycle dependent manner, (ii) in an HTRA1-dendent manner and (iii) in both, a cell cycle and HTRA1 dependent manner. (i) 4723 proteins exhibited different abundancies between the various cell cycle phases (p-value

HTRA1 dependent cell cycle proteomics

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