Quantitative Proteomic Analysis of PCSK9 Gain of Function in Human

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Quantitative Proteomic Analysis of PCSK9 Gain of Function in Human Hepatic HuH7 Cells Nicholas Denis,† Heather Palmer-Smith,† Fred Elisma,† Alia Busuttil,† Theodore Glenn Wright,† Maroun Bou Khalil,† Annik Prat,‡ Nabil G. Seidah,‡ Michel Chretien,†,§ Janice Mayne,*,† and Daniel Figeys*,† †

Ottawa Institute of Systems Biology, University of Ottawa, Ontario, Canada Laboratory of Biochemical Neuroendocrinology, Clinical Research Institute of Montreal, University of Montreal, Montreal, Quebec, Canada § Chronic Disease Program, Ottawa Hospital Research Institute, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada ‡

bS Supporting Information ABSTRACT: Proprotein convertase subtilisin/kexin type 9 (PCSK9) plays an important role in cholesterol homeostasis, mediating degradation of the liver low-density lipoprotein receptor (LDLR). In fact, gain- and loss-of-function PCSK9 variations in human populations associate with hyper- or hypocholesterolemia, respectively. Exactly how PCSK9 promotes degradation of the LDLR, the identity of the other biomolecules involved in this process, and the global effect of PCSK9 on other proteins has not been thoroughly studied. Here we employ stable isotope labeling with amino acids in cell culture (SILAC) to present the first quantitative, subcellular proteomic study of proteins affected by the stable overexpression of a gain-offunction PCSK9 membrane-bound chimera (PCSK9-V5ACE2) in comparison to control, empty vector transfections in a human hepatocyte (HuH7) cell line. The expression level of 327 of 5790 peptides was modified by PCSK9-V5-ACE2 overexpression. Immunoblotting was carried out for the control transferrin receptor, shown to be unaffected in cells overexpressing PCSK9-V5-ACE2, thus validating our SILAC results. We also used immunoblotting to confirm the novel SILAC results of up- and down-regulation of several proteins in cells overexpressing PCSK9-V5-ACE2. Moreover, we documented the novel downregulation of the EH domain binding protein-1 (EHBP1) in a transgenic PCSK9 mouse model and its up-regulation in a PCSK9 knockout mouse model. KEYWORDS: PCSK9, LDLR, EHBP1, SILAC, quantitative proteomics, subcellular fractionation, LC-MS/MS

’ INTRODUCTION The proprotein convertases (PCs) are a family of endoproteolytic enzymes involved in a wide variety of cellular functions with clinical relevance.1 Proprotein convertase subtilisin/kexin type 9 (PCSK9) is the latest member of the proprotein convertase family.2 It has attracted attention due to its clinical relevance in hypercholesterolemia3-6 resulting from its involvement in the degradation of the low-density lipoprotein receptor (LDLR).7-14 Specifically, PCSK9 promotes the degradation of hepaocyte LDLR which results in increased circulating LDL particles and cholesterol levels.12-15 Moreover, gain- and loss-offunction variants of PCSK9 have been associated with hyper- and hypocholesterolemia, respectively.3-6,16-20 As a secreted glycoprotein, PCSK9 is transported from the endoplasmic reticulum (ER) to the Golgi network en route for secretion.2,7 The LDLR binds and internalizes LDL particles at the cell surface through endocytosis, and is then recycled back to the plasma membrane.21-25 PCSK9 interacts with cell surface LDLR, and the complex is internalized into endocytic r 2011 American Chemical Society

compartments.8-10,26 However, instead of promoting recycling of the LDLR, PCSK9 redirects LDLR transport to lysosomes, facilitating its degradation.9,12,26-28 Poirier and colleagues (2009) demonstrated that PCSK9 could also promote intracellular, presecretory degradation of LDLR by trafficking from the trans Golgi network (TGN) to lysosomes.28 In a separate study they showed that the levels of two other LDLR family members decreased in the presence of PCSK9, the very low density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2).29 Other studies suggest that PCSK9 may regulate pathways other than its well-established role in cholesterol metabolism. PCSK9 was shown to play a role in the retention and removal of nonacetylated nascent intermediates of β-site amyloid precursor protein cleaving enzyme 1 (BACE1).30 PCSK9 can also down-regulate a cell surface receptor (cluster of differentiation 81 (CD81)) involved in entry of the hepatitis C Received: January 4, 2011 Published: February 18, 2011 2011

dx.doi.org/10.1021/pr2000072 | J. Proteome Res. 2011, 10, 2011–2026

Journal of Proteome Research virus into hepatocytes.31 PCSK9 knockout mice exhibited necrotic lesions following partial hepatectomy implicating it in hepatic regeneration32 although these lesions could be a direct consequence of the role of PCSK9 in cholesterol metabolism. A recent microarray study has studied gene expression changes in the presence of a PCSK9 gain of function mutant (PCSK9D374Y6) that associates with hypercholesterolemia in the human population.33 This study showed that PCSK9 gain of function affected genes in biological pathways including protein ubiquitination, xenobiotic metabolism, cell cycle, inflammation and cellular stress response.33 While the role(s) of PCSK9 in different cellular pathways and processes is expanding, our understanding of its mechanism(s) of action and biological partners involved in these processes is limited. Studies in cells and animal models demonstrate that PCSK9 transits through several different subcellular locations (ER and TGN), is secreted and can be endocytosed with the LDLR; mediating its trafficking and degradation in a lysosomal compartment.7,9-12 To our knowledge, no one has studied global protein changes in the presence of PCSK9. Since PCSK9 has been implicated in several biological pathways, we were interested in determining protein changes associated with the presence of a gain of function PCSK9 mutant and within different subcellular compartments. We have utilized a quantitative mass spectrometry (MS) based approach coupled with stable isotope labeling by amino acids in cell culture (SILAC)34 to study the proteomic changes occurring in different subcellular compartments of the HuH7 human hepatic cell line following stable overexpression of a membrane-bound, gain of function, nonsecreted chimera of PCSK9, (PCSK9-V5-ACE2).31 This PCSK9 mutant favors localization of PCSK9 to the plasma membrane and endosomes.31 From our previous studies we have shown that is it sorted similarly to wildtype PCSK9;28 however, it is more active than secreted forms of PCSK9 because of its cell surface localization and its enhanced sorting toward the degradative pathway of endosomes/lysosomes. Of the 5790 peptides that were quantified in the lysosomal/endosomal, Golgi and ER compartments, the expression level of 327 peptides changed by greater than 2 fold following stable overexpression of PCSK9-V5ACE2 in comparison to control HuH7 cells transfected with empty vector. These proteins are involved in a variety of functions including membrane receptor recycling, cytoskeletal organization, vesicle transport, lipid and cholesterol homeostasis, protein folding and cell signaling events. The validation of several proteins regulated by PCSK9 and the biological significance of these results are reported herein.

’ MATERIALS AND METHODS Cell Culture and SILAC Labeling

HuH7 cells stably expressing PCSK9-V5-ACE2 and empty vector control cells were generated as previously described.9,29,31 HuH7 cells were maintained in Dulbecco’s Modified Eagle Medium (DMEM; Gibco, Invitrogen, Burlington, Ontario, Canada) supplemented with 10% (v/v) fetal bovine serum (FBS; Gibco, Invitrogen), 1 antimycotic antibiotic reagent (Gibco, Invitrogen) and 50 μg/mL G418 (selection agent; Sigma-Aldrich, Oakville, Ontario, Canada)) at 37 °C in a 5% CO2 humidified incubator. For SILAC labeling, HuH7 cells stably expressing PCSK9-V5-ACE2 were grown in SILAC “light” media, while empty vector control cells were grown in SILAC “heavy” media35 (Figure 1). Cells were grown in SILAC media

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for 10 doubling times. SILAC media kit was obtained from Invitrogen. Total cell lyses were carried out in 1 RIPA buffer (50 mM Tris (pH 7.6), 150 mM NaCl, 1% (v/v) NP-40, 0.5% (w/v) DOC, 0.1% (w/v) SDS) in the presence of Complete protease inhibitor cocktail (Roche, Laval, Quebec, Canada). Protein concentrations in total cell lysates (TCL) were determined by the Bradford dye-binding method using Bio-Rad’s Protein Assay Kit (Mississauga, Ontario, Canada). Cellular Fractionation

The subcellular fractionation was performed essentially as described in Tran et al. (2002).36 At the end of the SILAC labeling period, cells were washed twice with ice-cold phosphate buffered saline (PBS) and then harvested by scrapping. The collected cells were centrifuged at 2000 g for 5 min at 15 °C. The pellets representing equal number of cells from light and heavy labeled cells were combined and resuspended in membrane solubilization buffer (10 mm Tris-HCl (pH 7.4), 250 mM sucrose, Complete protease inhibitor cocktail, 5 μM ethylenediaminetetraacetic acid (EDTA; Sigma-Aldrich) and homogenized using ball bearing homogenization (Isobiotec, Heidelberg, Germany).36 The cell homogenate was then transferred to 15 mL Corex tubes and centrifuged at 10 000 g for 10 min at 5 °C to remove unbroken cells, debris, nuclei and mitochondria. The postnuclear supernatant (PNS) was fractionated into ER, cis/ medial Golgi, distal Golgi and endosomes/lysosomes using a Nycodenz gradient prepared essentially as described previously in Tran et al. (2002).36 The cellular supernatant was layered on top of the gradient and centrifuged at 37 000 g, for 1.5 h at 15 °C (SW41 rotor). Following ultracentrifugation, each tube was fractionated into 15-0.8 mL aliquots for liquid chromatography-mass spectrometry (LC-MS/MS) and immunoblotting analyses. HPLC-ESI-MS/MS

Each protein fraction was separated using Jule custom-made 15 cm 4-12% Tris-glycine precast denaturing gels (Jule, Inc., Milford, CT) and silver stained. Gels were first placed in 50% methanol, 2.5% acetic acid solution for 30 min at room temperature, rinsed twice in ddH2O, then finally again in ddH2O for 2 h. Gels were incubated in 0.02% sodium thiosulfate for 1 min, rinsed twice with ddH2O and incubated in 0.1% silver nitrate for 30 min. Gels were then rinsed twice more in ddH2O and developed with 0.01% formaldehyde, 2% sodium carbonate solution until protein bands appeared, before terminating the developing process by placing gels in 1% acetic acid. Gel lanes were cut into 15 separate 1 cm slices. Slices were excised from each gel lane, and digested with trypsin as previously described.37 All resulting peptide mixtures were analyzed by high-performance liquid chromatography/electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). The HPLC-ESIMS/MS consisted of an automated Agilent 1100 micro-HPLC system (Agilent Technologies, Santa Clara, CA) coupled with an ESI LTQ mass spectrometer from Thermo Scientific (Fisher Scientific). Briefly, each peptide mixture was reconstituted in 20 μL of 5% (v/v) formic acid and loaded on a 200 μm 50 mm fritted fused silica precolumn packed in-house with 5 cm of reverse phase Magic C18AQ resins (5 μm; 200-Å pore size; Michrom Bioresources; Auburn, CA). The separation of peptides was performed on an analytical column (75 μm i.d. 50 mm) packed with the same beads using a 90 min gradient of 580% acetonitrile (v/v) containing 0.1% formic acid (v/v) (JT Baker, Phillipsburg NJ) at an eluent flow rate of 200 nL/min after 2012

dx.doi.org/10.1021/pr2000072 |J. Proteome Res. 2011, 10, 2011–2026

Journal of Proteome Research

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Figure 1. Experimental work-flow for SILAC labeling, subcellular fractionation, protein separation and MS analyses. HuH7 cells stably expressing PCSK9-V5-ACE2 were grown in SILAC “light” media, while empty vector, control cells were grown in SILAC “heavy” media. Representative immunoblots of total cell lysates were carried out for anti-LDLR and -actin antibodies as described in Methods. Shown are LDLR levels from PCSK9-V5ACE2 cell lysates with LDLR levels from control cell lysates set as 1. Actin was used as a loading control. Cells were grown in SILAC media for 10 doubling times, mixed in a 1:1 ratio and homogenized using a ball bearing homogenizer. Fifteen fractions (F1-F15) were collected from the subcellular fractionation of the microsomal pellet by density gradient centrifugation. Each gradient fraction was further fractionated by SDS-PAGE and proteins visualized by silver staining. Gel bands were then excised, digested with trypsin and analyzed by LC-MS/MS. The resulting data were analyzed and quantitated using Insilicos Proteomic Pipeline (IPP).

in-line flow splitting. The HPLC was interfaced to an ESI LTQ linear ion trap mass spectrometer (Thermo Electron, Waltham, MA) operated in positive ion mode. A voltage of 1.8 kV was applied to generate the electrospray ionization. Data dependent analysis were performed in which a full scan MS was first performed to detect potential peptides which was then followed by 5 data-dependent MS/MS. Database Searching and Data Analysis

Peak lists were generated from the raw file using Mascot Distiller 2.0.0.0 (Matrix Science, London, U.K.) to export *mgf files. Tandem MS data were searched against the human NCBInr database Mascot 2.2.02 (Matrix Science Ltd., London, U.K.). The searches were performed using the following criteria: only tryptic peptides with up to two missed cleavage sites were allowed; the mass tolerance was set to 2 Da for MS and 0.8 Da for MS/MS fragment ions; carbamidomethyl was set as a static

modification; oxidation on methionine and 13C6-Lys from SILAC were specified as variable modifications. The false discovery rate of protein identification was limited by accepting only the results with a mascot score >30 (p < 0.05). Following peptide identification using Mascot, peptide and protein quantitation was carried out using Insilicos Proteomic Pipeline (IPP v1.0 rev.91, Build 200712031206, Institute for Systems Biology, Seattle, WA). Here, data files from Mascot search results were converted to pepXML files for downstream quantitation. Peptide prophet was used for peptide validation, accepting peptide results with p < 0.05. XPRESS was used for quantitation, setting SILAC “heavy” peptides to a value of 1 and varying SILAC “light” peptides relative levels. Once quantitative data from all LC-MS/MS runs were collected and compiled, all peptides that showed a greater than 2 fold change in relative abundance were subjected to manual validation. The MS scans for these peptides were manually validated based on peak intensities for coeluting light 2013



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Table 1. Antibodies used for Immunoblottinga antibody information antibody

dilution

catalog number

company

Rabbit anticalnexin

1/1000

SPA-860

Stressgen Bioreagents

Rabbit anti-TGN46

1/500

PA1-1069

Thermo Fisher Scientific

Mouse anti-MAN2A

1/1000

H00004124-M01

Novus Biologicals

Mouse anti-EEA1

1/1000

Ab18175

Abcam

Rabbit anti-Lamp1

1/1000

C54H11

Cell Signaling Technology

Goat anti-Lamin A/C

1/1000

SC-6215

Cell Signaling Technology

Mouse anti-Transferrin Receptor

1/1000

Ab38171

Abcam

Mouse anti-Actin Mouse anti-EHBP1

1/2000 1/1000

NB600-505 7383

Novus Biologicals American Diagnostic Inc.

Mouse anti-ROCK1

1/500

Ab45171

Abcam

Rabbit anti-LDLR

1/250

10-L55A

Fitzgerald

Mouse Anti V5

1/2500

R961-25

Invitrogen

Anti Rabbit-HRP conjugated

1/5000

P0448

Dako

Anti Mouse-HRP conjugated

1/5000

P0557

Dako

a

Abcam (Cambridge, MA), Invitrogen (Burlington, ON, Canada), Cell Signaling Technology (Pickering, ON, Canada), American Diagnostic Inc. (Montreal, Quebec, Canada), Stressgen Bioreagents (Plymouth Meeting, PA), Abnova (Walnut, CA), Thermo Fisher Scientific (Ottawa, ON, Canada), Novus Biologicals (Littleton, CO), Santa Cruz (Santa Cruz, CA), Fitzgerald (Acton, MA), Dako (Burlington, ON, Canada).

and heavy peptide pairs. Labeled peptide pairs peak intensities not matching the relative quantitation reported by IPP were removed from the data set. The resulting quantitative peptide list was expressed according to the log2 SILAC ration Light:Heavy (L:H) to produce a log2 distribution curve. The Gene ID Conversion Tool from the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources version 6.7 was used to define the gene official symbol from the protein GI number.38,39 The gene official symbol was used to create the matrix for the heat map. Quantified peptides were subject to hierarchical clustering (UPGMA, Euclidean). Using Mayday Software version 2.10 the heat map cluster contained 1538 taxa.40,41 Animals

Liver-specific PCSK9 transgenic mice were generated as described in Zaid et al. (2008).32 Male PCSK9 heterozygous mice (129 Sv;C57BL/6) were purchased from the Jackson Laboratory (Bar Harbor, ME) and were backcrossed with B6 wildtype females for eight generations as described in Mbikay et al. (2009) to generate B6-N8 Pcsk9( incipient congenic mice.42 In both cases, heterozygotes were crossed to generate PCSK9 wildtype and PCSK9 transgenic or PCSK9 knockout littermates. Mice were treated according to guidelines of the Canadian Council on Animal Care under a protocol approved by an institutional Animal Care Committee. Mice were given access to standard mouse chow and water ad libitum, except when overnight fasting (12-16 h) was required. For liver harvesting, male mice were anesthetized and sacrificed by cervical dislocation. Livers were mechanically homogenized in ice cold 2 RIPA buffer containing 2 Roche’s Complete protease inhibitor cocktail. Protein concentrations in total liver lysates were determined by the Bradford dye-binding method using Bio-Rad’s Protein Assay Kit. Immunoblotting

Protein samples from total liver lysates were separated on NuPage 7% Tris-acetate precast gels (Invitrogen). Protein

samples from subcellular fractions and TCL were separated on NuPage 4-12% Bis-Tris precast gels (Invitrogen). Proteins were then transferred by electroblotting onto a nitrocellulose membrane (Bio-Rad) and immunoblotted following standard protocols. Membranes were blocked in 5% (w/v) skim milk in PBS (pH 7.6) and 0.5% (v/v) Tween-20 (PBS-Tw) overnight at 4 °C. Primary and secondary antibodies used and their dilutions are shown in Table 1. Antibodies were diluted in 5% (w/v) skim milk in PBS-Tw. Immunoblots were revealed by SuperSignal Chemiluminescent Substrate (Pierce, Fisher Scientific) on X-OMAT film (Kodak; VWR, Mississauga, Ontario, Canada). The signal was quantified by pixel quantitation using Adobe Photoshop version CS3. Briefly, high resolution scanned images are converted to greyscale and inverted. Using the lasso tool protein signals were outlined and the pixel area calculated from pixels area in histogram toolbox. The background was then subtracted within the same lane using the same area tool.

’ RESULTS AND DISCUSSION Subcellular Fractionation of SILAC Labeled HuH7 Cells Stably Over-Expressing a PCSK9 Gain of Function Chimera

PCSK9 is highly expressed in hepatocytes where it is involved in the post-translational regulation of LDLR levels.2,7 Moreover, gain- and loss- of function variants in human PCSK9 have been documented to impact the level of LDLR present at the cell surface and therefore the level of circulating LDL particles in the blood.3,7,11,14,43 Interestingly, the modulation of LDLR levels by PCSK9 offers an alternative target and strategy for the development of drugs to lower cholesterol levels beyond what is possible with statin (HMG-CoA reductase inhibitors) based therapies alone.14,16,44-48 Therefore, it is important to better understand the regulation and function of PCSK9 and its associated proteins, both in terms of its role in LDLR regulation, as well as any other physiological role(s) it may have. Although it is known that PCSK9 leads to the lysosomal degradation of the LDLR,12 the identity other proteins associated with PCSK9 and the LDLR, and/or are changing through this process are unknown. 2014



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Figure 2. Immunoblot detection using organelle-specific markers to illustrate enrichment of subcellular components by density gradient centrifugation. The 15 fractions collected from density gradient centrifugation of cellular lysates as described in Methods were subjected to immunoblot analysis with antibodies recognizing the following organelle markers: Calnexin (ER), TGN46 (Golgi), MAN2A (Golgi), EEA1 (early endosome), Lamp1 (lysosome), Lamin A/C (nucleus).

We designed a proteomic experiment to study the impact of PCSK9 gain of function overexpression on protein levels in different subcellular compartments of hepatic cells as outlined in Figure 1. Briefly, control HuH7 cell lines expressing an empty vector were grown in SILAC “heavy” media while a PCSK9-V5ACE2 construct that favors the localization of PCSK9 to the plasma membrane and the endosome9,29,31 was stably overexpressed in human hepatic HuH7 cells grown in SILAC “light” media. We used this cell membrane associated PCSK9 chimera28,31 since it is sorted more efficiently to endosomal and degradation pathways while PCSK9 is normally secreted into the media with only 1-2% binding to the cell surface.26 And although we cannot exclude that membrane-bound PCSK9 may lead to other changes protein expression than a secreted PCSK9, it is sorted similarly to WT PCSK928,31 and acts as a PCSK9 “gain of function” at the level expressed in our stable cell line. The immunoblot inset in Figure 1 shows that LDLR levels are decreased in PCSK9-V5-ACE2 cell lysates in comparison to control cell lysates, confirming the gain of function phenotype in this stable overexpressing cell line used for subsequent experiments. To ensure full incorporation of the “light” and “heavy” SILAC amino acids, cells were grown for at least 10 passages in labeled media. Following SILAC labeling, cells were mixed in a 1:1 ratio and subjected to subcellular fractionation using a Histodenz gradient protocol as described in Methods.36 Each fraction was divided into two and then separated by gel electrophoresis for either ingel trypsin digestion followed by LC-MS/MS analysis and quantification or subjected to immunoblotting for specific subcellular markers (Figure 2). In general, high density fractions (7-15) were enriched in larger organelles (endoplasmic reticulum (ER)), while midrange density fractions (4-9) contained smaller organelles (Golgi) and low density fractions (2-6) were

enriched in small vesicles (endosomes/lysosomes). Although, subcellular fractionation does not provide high resolution separation, it is sufficient to enrich fractions in large, medium, and small organelles as accessed by immunoblotting for specific subcellular markers (Figure 2). Indeed the ER-resident protein calnexin was found predominantly in the high density fractions (7-15). The late and early Golgi network proteins (trans Golgi network 46; TGN46 and alpha-mannosidase II; MAN2A, respectively) were found predominantly to overlap in midrange density fractions (4-9). The early endosome marker (early endosome antigen 1 protein; EEA1) and lysosome marker (lysosomal-associated membrane protein 1; LAMP1) were found predominantly in the low density fractions (2-6). A nuclear envelope marker, Lamin A/C, was present in the high density fraction 15 (Figure 2). Quantitation of SILAC Labeled Cells

The subcellular enrichment initially provided by density gradient centrifugation was further enhanced by coupling it with another separation approach. Briefly, proteins in each subcellular fraction were then separated based on their molecular weight by SDS-PAGE (Figure 1). The proteins were visualized by silver staining and each gel lane was cut into 15 separate 1 cm gel fractions that were subjected to in-gel tryptic digestion.37 The peptide mixtures from each gel lane were subjected to a third round of separation by reverse phase HPLC (high performance liquid chromatography) coupled to an ESI MS/MS (electrospray ionization tandem mass spectrometry) for analysis. All experiments were performed in duplicate leading to the quantitation of 5790 peptides (n1=2975, n2=2815). As shown in Figure 3 the data for the peptides quantified from both experiments followed a normal distribution curve when expressed as Log2 for the SILAC L:H ratio (PCSK9-V5-ACE2:control). As well, each data 2015



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Figure 3. Log2 distribution of the Light:Heavy ratio of peptides quantified follow a normal distribution. All light and heavy labeled peptides detected in all 15 fractions collected from density gradient centrifugation of cellular lysates and subjected to SDS-PAGE fractionation followed by MS analyses as described in Methods were quantified using Insilicos Proteomic Pipeline quantitation software. Relative quantitation ratios (Light:Heavy) were expressed in terms of log2 values, and then plotted to show their distribution for n = 2 experiments. n1 = red; n2 = blue.

set centered at the Log2 value of zero, suggesting most peptides (proteins) levels were unaffected by the overexpression of PCSK9-V5-ACE2 in HuH7 cells, with 5.7% of the proteins quantified being significantly affected by its overexpression at the 95% confidence level. Trends in Clustered Data within Subcellular Fractions

We first set out to determine trends in the quantified proteins across the subcellular fractions. Proteins with peptides quantified in two or more subcellular fractions were subjected to hierarchical clustering based on similarity of quantitation results across the Histodenz fractions from each experiment as shown in the resulting heat map (Figure 4). Regions of the heat map were analyzed to determine if the quantified proteins that clustered to specific Histodenz fractions, and that overlap with a particular subcellular marker, contained proteins that were expected to be found in such fractions. As shown in Figure 4, the clustered region corresponding to ER marker-enriched fractions 14 and 15 was found to be comprised almost solely of ER resident proteins, including two components of the ER signal sequence recognition receptor complex (signal sequence receptor, A subunit and signal recognition particle receptor, B subunit), proteins involved in protein folding (protein disulfide isomerase A4, calreticulin isoform 2), and other resident ER membrane and luminal proteins (dehydrogenase/reductase SDR family member 7B, neutral cholesterol ester hydrolase, ribosome binding protein 1). These results demonstrate our ability to identify proteins within their respective subcellular compartments based on distinct organelle size/density enrichment.

Trends in Clustered Data in Quantified Proteins Across Subcellular Fractions

Next we studied trends in the clustered quantitation data across subcellular fractions. Clustered data should follow smooth trends and have fairly constant SILAC quantitation ratios among

fractions for proteins occupying or transiting through several subcellular components and whose level is unaffected by PCSK9 overexpression. Our data showed this for the transferrin receptor (L:H ranges between 1.0 and 1.16 from fractions F4 to F9; Supplemental Table S1, Supporting Information) a membrane receptor that is recycled to the cell surface following internalization of its ligand and whose levels are unaffected by PCSK9 overexpression in both cell and animal models.8,12,31 Another example is the HDL binding protein with L:H ranges between 0.88 and 1.26 from fractions F3 to F15 (Supplemental Table S1, Supporting Information). By looking for trends displayed in the heat map where a protein’s relative quantitation may increase or decrease directionally throughout the fractions, or within a signal fraction, we can identify proteins affected by PCSK9 overexpression. Of the 5790 peptides quantified, approximately 5.7% were determined to be significantly up- or down-regulated in HuH7 cells stably overexpressing PCSK9-V5-ACE2 in comparison to cells transfected with control, empty vector. An entire list of quantified peptides is found in Supplementary Table S1, Supporting Information. Table 2 is a list of non-nuclear proteins significantly up- or down-regulated by PCSK9-V5-ACE2 and divided into the following categories; cytoskeleton organization/vesicle and organelle transport, lipid/cholesterol homeostasis and metabolic proteins, proteins of the protease/proteasome, proteins involved in post-translational modification, folding/chaperone proteins, cell adhesion and membrane proteins and other proteins (Table 2). Thus far, no information is available on the exact mechanism (and proteins) involved in PCSK9-mediated degradation of cell surface LDLR; this includes lack of recycling to the cell surface for endocytic vesicle containing PCSK9:LDLR complexes, and fusion of these in late endocytic compartments with lysosomes.11,28 These events are both affected by cytoskeletal organizing proteins, and proteins that function in directing 2016



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Figure 4. Heat map clustering of quantified SILAC fractionation data. The number of peptides identified per protein across fractions was used for the hierarchical clustering. The left axis represents different proteins identified by their gene name while the right axis represents the cluster tree. The top axis is the fraction number and the SILAC ratio is represented by a color code from white to yellow (L:H ratio; 0->3). Inset shows ER resident proteins identified in clustered region corresponding to ER marker-enriched fractions 14 and 15.

organelle and vasicular transport, specifically receptor recycling.49-51 Indeed, a number of proteins directly implicated in such events were affected by PCSK9-V5-ACE2 overexpression (Table 1). Down-Regulated Proteins. Proteins down-regulated included Rho associated, coiled-coil containing protein kinase 1 (ROCK1;L:H 0.28), receptor mediated endocytosis-8 protein (RME-8; L:H 0.30) and the EH-domain binding protein 1 (EHBP-1; L:H 0.40). ROCK-1 is a Rho-associated protein kinase that regulates actin cytoskeleton distribution/transport of endosomes and lysosomes in human breast cell lines.52 In mice, a deficiency of ROCK1 in bone marrow-derived cells protected LDLR knock out mice from developing atherosclerosis. RME-8 plays a role in receptor-mediated endocytosis, endosome to Golgi retromer mediated transport, and when down-regulated through siRNA expression is known to drastically increase epidermal growth factor receptor (EGFR) degradation, as well as decrease LDLR levels by 30%.53-55 EHBP-1 is a protein that interacts with EH-domain containing proteins that bind cell surface receptors and regulate their recycling to membranes and couples endocytosis to actin cytoskeleton.56,57 Interestingly, the

mRNA of this gene was up-regulated by 2.5 fold in a recent microarray study of genes affected by overexpression of the gain of function PCSK9 mutant D374Y in the human hepatocyte cell line HepG233 suggesting a negative feedback reaction for opposite changes occurring at the protein level observed in the present study. The level of other families of proteins that play roles during secretion, endocytosis and recycling were both up- and downregulated by PCSK9-V5-ACE2 overexpression in HuH7 cells. These included several members of the Rab family of GTPases that bind to various membrane networks and regulate cytoskeleton dynamics and vesicle transport:58-60 Rab1b (L:H 3.78), Rab2a (L:H 0.317), Rab33a (L:H 0.305), Rab35 (L:H 4.64). Rab2a plays a role in membrane internalization and retrograde cargo transport,61 Rab33a autophagosome formation,62 Rab1b functions during vesicle transport throughout the secretory pathway, as well as transport and maturation of nascent LDLR63-65 and Rab35 in receptor recycling.66 Up-Regulated Proteins. Several proteins were significantly upregulated by PCSK9-V5-ACE2 overexpression (Table 2): Actin related protein 2/3 (Arp2/3; L:H 9.41-4.16), A-kinase 2017



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Table 2. Partial List of Down-Regulated and Up-Regulated Non-nuclear Proteins and Their Biological Functionsa PCSK9: protein

gi accession

Mascot

Ctrl

peptide

Functional class: cytoskeleton organization/vesicle and organelle transport Actin related protein 2\3 complex subunit 1b gi| 9.4 TWKPTLVILR

N F

score

N1F4

48

14043135 A-kinase anchor protein-12

gi|

8.5

GSSSDEEGGPKAMGGDHQK

N1F6

32

8.0

IILIGDSNVGK

N2F9

31

5.5

TWKPTLVILR

N2F5

53

55959051 Rab19b

gi| 51094782

Actin related protein 2/3 complex subunit 1b

gi| 14043135

phospholipase C, beta 3

gi|836665

5.2

LVAGQQQVLQQLAEEEPK

N2F5

31

Myoneurin

gi|

5.2

AGAMPQAQK

N1F4

36

4.6

LLIIGDSGVGK

N2F15

60

18448935 Rab35

gi| 54696910

transmembrane emp24 domain-containing protein 10 precursor

gi|4885697

4.6

IPDQLVILDMK

N1F14

38


gi| 14043135

4.5

TWKPTLVILR

N2F3

49

FERM and PDZ domain containing 4

gi|

4.4

VYLENGQTK

N2F9

32

4.2

TWKPTLVILR

N1F3

48

3.8

IQTIELDGK

N1F8

40

109731127 Actin related protein 2\3 complex subunit 1b

gi| 14043135

Rab1b

gi| 89029141

Kinesin light chain 3

gi| 91825557

3.7

GEAAAGAAGMKR

N1F3

40

Scribble

gi|

3.3

SERGLGFSIAGGK

N1F8

32

3.3

DKYTPVPDTPILIR

N2F14

32

32812252 Nebulin

gi| 19856971

Fibronectin leucine rich transmembrane protein 3

gi|7529605

3.1

KTITITVK

N2F4

39


gi|

3.1

TWKPTLVILR

N2F6

34

FERM and PDZ domain containing 4

14043135 gi|

2.9

VYLENGQTK

N1F9

32

2.9

FLILNPSKR

N2F4

30

0.5

KLLEELLNK

N1F9

41

109731127 MAP\microtubule affinity-regulating kinase 2

gi| 86990437

Sec5

gi| 15982242

dynein light chain-A

gi|5531813

0.5

NVLLLGEDGAGK

N2F7

35

echinoderm microtubule associated protein like 6

gi| 223005862

0.5

QVTEAVVIEK

N2F6

37

kalirin, RhoGEF kinase

gi|

0.4

GSLTPGYMFKR

N2F10

34

0.4

NLQGFLEQPK

N1F3

31

0.4

VMAGALEGDIFIGPK

N2F6

41

gi| 21739555

0.4

KAPAPPVLSPK

N2F10

31

gi|

0.4

SIATLAITTLLK

N1F3

89

148839466 retinoblastoma-associated factor 600

gi| 82659109

Actin related protein 1

gi| 119570071

EH domain binding protein1 coat protein gamma2-COP

51094839

2018



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Table 2. Continued PCSK9: protein Rab2

gi accession

Ctrl

gi|

0.3

Mascot peptide

N F

score

TASNVEEAFINTAK

N1F15

91

0.3

TVEIEGEK

N2F15

31

0.3

LLEFELAQLTK

N1F4

72

14286264 Rab33a

gi| 14603037

ROCK1

gi| 47605999

FMR1 interacting protein 1 isoform 3

gi|

0.2

LADQIFAYYK

N1F4

49

receptor mediated endocytosis 8

57545144 gi|

0.3

SEETNQQEVANSLAK

N2F10

52

215274246

GAPDH

Functional class: lipid/cholesterol homeostasis and metabolic proteins gi|603211 5.1 IISNASCTTNCLAPLAK

Cyclophilin A

gi|

5.1

N1F3

116

XSELFADK

N1F15

50

51702775 gamma-butyrobetaine hydroxylase

gi|3746805

4.9

MKTGNMACTIQK

N2F4

33

Cyclophilin A

gi| 51702775

4.6

XSFELFADK

N1F9

54

gi|

4.0

XSFELFADK

N2F5

49

3.8

ETLMDLSTK

N1F15

36

Cyclophilin A

51702775 Carbamyl phosphatesynthetase I

gi| 62822412

Hydroxysteroid (17-beta) dehydrogenase 12

gi|7705855

3.4

GVFVQSVLPYFVATK

N1F14

37

ATP citrate lyase isoform 2

gi|

3.4

KAKPAMPQGK

N2F14

32

Cyclophilin A

38569423 gi|

3.2

XSFELFADK

N1F3

54

3.2

RSPPIPLAK

N1F15

40

3.1

RSPPIPLAK

N1F9

40

51702775 Protein disulfide isomerase family A, member 4

gi| 37674412

Protein disulfide isomerase family A, member 4

gi| 37674412

Malate deydrogenase 2

gi|6648067

3.0

IQEAGTEVVKAK

N1F4

37

7-dehydrocholesterol reductase Alpha enolase

gi|4581759 gi|

3.0 2.9

FLPGYVGGIQEGAVTPAGVVNK DATNVGDEGGFAPNILENKEGLELLK

N2F15 N1F4

141 48

2.8

MVVESAYEVIK

N1F3

35

0.4

FYALSASFEPFSNK

N1F14

96

12804749 Lactate dehydrogenase B

gi| 12803117

Calreticulin

gi| 12803363

Methylenetetrahydrofolate dehydrogenase 1

gi|

0.4

YVVVTGITPTPLGEGK

N2F7

38

Triosephosphate isomerase

14602585 gi|

0.3

VVLAYEPVWAIGTGK

N1F5

34

0.2

KITIADCGQLE

N2F3

51

14043688 Cyclophilin A

gi| 51702775

Plasminogen Proteasome 26S non-ATPase subunit13 isoform 1

Functional class: protease/proteasome gi|387026 6.1 LSSPADITDK gi|

N1F4

38

3.7

YYQTIGNHASYYK

N2F4

60

3.6 3.3

LMSSILTSIDASKPWSK LYQTDPSGTYHAWK

N1F7 N1F4

33 47

12654533 ADAMTS5 Proteasome subunit, alpha type, 8

gi|6049180 gi| 20379541

2019



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Table 2. Continued PCSK9: protein Proteasome subunit, alpha type, 2

gi accession

Ctrl

gi|

3.2

Mascot peptide

N F

score

GYSFSLTTFSPSGK

N1F3

89

3.2

LYQVEYAFK

N1F3

64

3.1

ALYQSLKTK

N1F4

34

50881968 Proteasome alpha 6 subunit

gi| 82571777

Transmembrane protease, serine 11F

gi| 34527807

Headpin

gi|

3.1

DLFPDGSISSSTK

N2F3

37

Proteasome 26S subunit, non-ATPase, 3

12643252 gi|

0.4

LQLDSPEDAEFIVAK

N1F3

104

13436065 Proteasome beta 7 subunit proprotein

gi|1531533

0.3

LDFLRPYTVPNK

N2F5

35

Proteasome 26S non-ATPase subunit 7

gi|

0.3

VVGVLLGSWQK

N2F6

65

0.2

CKVLMLGGSALNHNYR

N2F15

34

N2F4

45

KAQGGSRPR

N2F9

34

15214948 PAPP-A

gi| 38045915

Protein tyrosine phosphatase

Functional class: post-translational modification gi| 5.3 MEKGDDINIK 16876892

Heparan sulfate 3-O-sulfotransferase 6

gi|

5.1

14336772 Cullin 7

gi|2833262

4.8

NLLNCLIVRILK

N2F4

34

Retinoblastoma binding protein 6 isoform 1

gi|

4.8

ISKLEVTEIVKPSPK

N2F9

32

N2F15

37

74762440 Tssk4

gi| 83405295

4.7

RATILDIIK

E1A binding protein p400

gi|

4.3

AIQPQAAQGPAAVQQKITAQQITTPGAQQKN1F7

31

4.2

RATILDIIK

40

56549696 Tssk4

gi|

N1F5

83405295 Cullin 7

gi|2833262

3.7

NLLNCLIVRILK

N2F5

33

Ubiquitin specific protease 4 isoform b

gi|

3.3

ADTIATIEK

N2F3

31

Protein tyrosine kinase

40795667 gi|515871

3.1

TGAFEDLKENLIR

N2F4

41

TIP120 protein

gi|

0.5

EGPAVVGQFIQDVK

N1F5

34

0.5

GSETDSAQDQPVKMNSLPAER

N2F6

37

0.4

AGFSGGMVVDYPNSAK

N1F7

54

76661742 N-myristoyltransferase 1

gi| 10835073

Putative methyltransferase WBMT

gi| 23831505

Janus kinase 1

gi| 62087694

0.4

MQLPELPKDISYK

N2F4

31

Ring finger protein 20

gi|

0.3

LQELTDLLQEK

N1F5

52

0.3

NQEGPGEMGK

N2F10

39

0.2

VLVYELLLGK

N2F6

35

N1F15

38

N1F7

32

83405148 Polypeptide GalNAc transferase 13

gi| 27530993

NOL1\NOP2\Sun domain family, member 5

gi| 37674386

Reticulon 4 Heat shock protein 90Ad

Functional class: protein folding/chaperone gi| 6.1 LFLVDDLVDSLK 20070662 gi|

4.4

EPHISLIPNK

61104905

2020



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Table 2. Continued PCSK9: protein Histocompatibility (minor) 13

gi accession

Ctrl

gi|

4.0

Mascot peptide

N F

score

LVFPQDLLEK

N2F15

38

0.3

DVITHVVCTK

N1F3

33

0.2

TVIIEQSWGSPK

N1F3

71

14286316 Peptidylprolyl isomerase domain and WD repeat containing 1

gi| 24308049

Chaperonin

gi| 41399285

Chaperonin containing TCP1, subunit 4 (delta)

gi|

0.1

DALSDLALHFLNK

N2F15

37

Signal sequence receptor, alpha

76827901 gi|

3.0

FLVGFTNK

N1F14

42

N2F5

31

119575608

BAI1-associated protein 3

Functional class: cell adhesion and membrane proteins gi| 4.5 ILNDKSPR 14336746

Aggrecan core protein

gi|129886

4.6

GSVILXVKP

N1F4

39

Solute carrier family 25, member 3

gi|

4.4

FGFYEVFK

N1F15

38

Translocase of inner mitochondrial membrane 44 homologue

15079648 gi|

4.4

ILDIDNVDLAXGK

N1F9

32

3.6

VVERTQNVTEK

N2F11

36

3.5

GLLKEIANK

N1F15

39

62897685 Potassium voltage-gated channel, subfamily H, member 6 isoform 1

gi| 11878259

Transient receptor potential cation channel, subfamily M, member 8

gi| 72537227

Semaphorin receptor

gi|6010211

3.1

FRYLVPGSNGQLTFDSGFEK

N1F9

33

GPAD9366

gi| 73619948

0.5

MVTFYCTTK

N1F7

34

Cadherin 8, type 2

gi|6483315

0.5

HKNEPLIIK

N1F4

33

N1F7

36

Fibroblast growth factor 11

Functional class: signaling/cell cycle gi| 5.6 SLCQKQLLILLSK 20160215

cell division cycle 2-like 6 (CDK8-like)

gi|

3.7

DLKPANILVMGEGPER

N2F3

34

57209410 Rotatin

gi|

3.4

KSAAEQLAVIMQDIK

N2F14

31

Cytokine induced protein 29 kDa

145046269 gi|

3.3

FGIVTSSAGTGTTEDTEAK

N2F5

91

0.4

ILGPQGNTIK

N2F6

43

0.3

EIKILQLLK

N2F4

33

GGDPGLMHGK

N1F14

35

109097133 KH domain containing, RNA binding, signal transduction associated 1

gi| 12653853

Cyclin-dependent kinase 9

gi| 12805029

Retinol dehydrogenase 14 (all-trans\9-cis\11-cis)

Functional class: other gi| 5.9 10190746

GTP-binding protein NGB

gi|4191616

4.1

SSFINKVTR

N2F9

32

HLA-B associated transcript 1

gi|

3.2

GLAITFVSDENDAK

N1F3

80

3.1

HPQPGAVELAAK

N1F6

32

56207984 Carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, andgi| dihydroorotase

50403731

Ribosomal protein L29

gi|

3.0

AQAAAPASVPAQAPK

N1F5

88

Alpha-fetoprotein

60656425 gi|31351

0.5

GYQELLEK

N1F15

31

A kinase (PRKA) anchor protein 8-like

gi|6688138

0.3

QTADFLQEYVTNK

N1F3

42

2021



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Table 2. Continued PCSK9: protein J-type cochaperone HSC20

gi accession

Ctrl

gi|

0.2

Mascot peptide QFLIEIMEINEK

N F

score

N1F3

44

41388876 a

PCSK9:Ctrl, SILAC ratio of peptides from cells overexpressing PCSK9 to control and manually validated; N, Experiment; F, Fraction; X, Mascot assigned ambiguous residue.

anchor protein-12 (AKAP-12; L:H 8.52) and protein tyrosine phosphatase, nonreceptor type 2 (PTPN2) (L:H 6.18). Arp2/3 plays a role during actin polymerization near cellular membranes and mediates the transport of early endosomes toward late/mature endosomes.67,68 Additionally, Arp2/3 can be regulated by Protein Kinase C delta to enclose F-actin around early endosomes, thus preventing the recycling of EGFR containing vesicles to the cell surface and thereby promoting EGFR degradation.67,69 AKAP-12 is a scaffold protein that can promote the internalization, resensitization and recycling of the β-2andrenergic receptor through calcium-dependent interactions.70 Additionally, its overexpression leads to a subsequent up-regulation of SREBP-2 activity (sterol regulatory element binding protein; a transcription factor involved in the regulation of genes important for cholesterol homeostasis) and increases cholesterol efflux from the cell.71 GAPDH, sometimes used as a “loading control” or “house keeping gene/protein”, was upregulated in subcellular fraction 3 representing endosomal/lysosomal enriched fractions. This would reflect a small portion of total cell GAPDH and would not affect total cell levels. In Supplemental Table 1 (Supporting Information), GAPDH was found in several other subcellular fractions and in these fractions it was not changing significantly. However the change of a particular protein in a subcellular compartment can be of biological significance. For instance Raje et al. (2007) show that cell surface GAPDH is a novel transferrin receptor whose expression is regulated by the availability of iron.72 The cytoplasmic protein phosphatase PTPN2 is shown to affect EGFR signaling in intestinal epithelial cells.73 In the microarray study from Ranheim and colleagues (2010) of genes affected by overexpression of the gain of function PCSK9 mutant D374Y in the human hepatocyte cell line HepG2, PTPN2 mRNA was upregulated ∼2.1 fold, and in this case reflecting the change we see in protein levels by SILAC and MS analysis.33 Validation of SILAC Data by Immunoblotting

We verified the MS analyses of our SILAC experiments by immunoblotting for several proteins for which antibodies are commercially available and whose levels were unchanged, upregulated, or downregulated in our data set. Shown in Figure 5 are the immuno-signals from total cell lysates of HuH7 cells overexpressing PCSK9-V5-ACE2 in comparison to control cells overexpressing an empty vector, their densitometry and the SILAC ratio for comparison. The selected antigens included the transferrin receptor (unchanged), ARP2/3 (upregulated) and EHBP-1 and ROCK-1 (downregulated). Our SILAC data (Supplemental Table S1, Supporting Information) showed no significant changes in transferrin receptor and this is consistent with our immunoblotting results in Figure 5. In previous studies this receptor was shown to be unaffected by PCSK9 overexpression. Immunoblotting confirmed the novel observations of upregulation of ARP2/3 and downregulation of both EHBP-1

Figure 5. Immunoblotting for selected proteins identified from SILAC data and MS analyses. Total cell lysates from HuH7 cells overexpressing either PCSK9-V5-ACE2 or control, empty vector were immunoblotted with the indicated antibodies. n = 3, data represent the average. Actin was used as a loading control for all immunoblots and for relative levels, the signal from control cell lysates were set as 1. The SILAC ratio for each of these proteins is also indicated. ns = peptide not seen in MS analyses for SILAC ratio.

and ROCK-1 in HuH7 cells overexpressing PCSK9-V5-ACE2 in comparison to control cells overexpressing an empty vector (Figure 5). EHBP1 and its Effects on LDLR

We were particularly interested in the effect of overexpression of PCSK9-V5-ACE2 on the levels of the EH-domain binding protein 1 (EHBP1) which binds EH domain-containing proteins and plays important roles in receptor recycling from internal vesicles back to the cell surface.56,57,74 The down-regulation of EHBP1 at the protein level upon PCSK9 overexpression in our SILAC study contrasts its upregulation at the gene level in a recent microarray study.33 In that study they used a nonmembrane bound and secreted gain-of-function PCSK9-D374Y mutant.33 To directly compare our respective results, we stably transfected HuH7 cells with the same PCSK9-D374Y mutant. In Figure 6, panel A we show that EHBP-1 levels are significantly decreased in these cells by immunoblotting of total cell lysates in comparison to controls (cells expressing the empty vector), suggesting that this down-regulation by PCSK9 is not due to the presence of the ACE2 transmembrane and cytoplasmic domains in the PCSK9-V5-ACE2 mutant we used for the SILAC experiments. In fact, we show that this protein is also significantly down-regulated at the protein level in livers from PCSK9 transgenic mice (Figure 6, panel B) while significantly upregulated at the protein level in livers from PCSK9 knockout mice (panel B). That the microarray data revealed an opposing effect at the mRNA level suggests a potential negative feedback loop, as EHBP-1 is down-regulated at the protein level upon PCSK9 overexpression. The cells may be tempering changes in EHBP-1 protein levels, since it plays an important role in the general cellular transport mechanisms. As a protein responsible 2022



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Figure 6. EHBP-1 is down-regulated in HuH7 cells overexpressing the PCSK9 D374Y mutant and in livers of transgenic mice overexpressing mouse PCSK9 (mPCSK9), but is up-regulated in livers of PCSK9 knockout mice. (A) Cell lysates from HuH7 cells overexpressing either PCSK9-D374Y-V5 or control, empty vector were immunoblotted with the indicated antibodies. (B) Liver lysates from PCSK9 transgenic mice and wildtype littermates were immunoblotted with the indicated antibodies. (C) Liver lysates from PCSK9 knockout mice and wildtype littermates were immunoblotted with the indicated antibodies. Actin was used as a loading control for all immunoblots and for relative levels, the signal from control cell lysates were set as 1. Immuno-signals were quantified by densitometry using Adobe Photoshop CS3 as described in Methods. All values are presented as mean ( SEM (n = 3). Data were analyzed by Student’s t test with significance defined as *p < 0.05, **p < 0.005, ***p < 0.0005.

for receptor recycling, EHBP-1’s down regulation in PCSK9 expressing cells may reflect its presence along the pathway that results in decreased recycling of the LDLR and its redirection to the late endosome and lysosome for degradation.

’ CONCLUSIONS In this study we used SILAC and MS analyses to screen for proteins affected by PCSK9 overexpression in a hepatocyte cell line, namely HuH7. The subcellular enrichment of SILAC peptides prior to MS analysis allows one to identify proteins that change in a particular subcellular compartment which gives an additional level of information over SILAC analyses carried out on total cell lysates. We also demonstrate the utility of this technique for studying global proteomic changes and the benefit of such studies to complement microarray studies that document changes at the mRNA level. Indeed changes at the transcript level can be subject to both positive and negative feedback from the cell and do not always reflect protein changes. Other mRNAs may not change, while their protein levels vary significantly. This is the case for the LDLR which is significantly down-regulated post-translationally in the presence of PCSK9. However in both cell and mouse models of PCSK9 overexpression or knockout, no significant changes were noted at the mRNA level for LDLR.11,14,75 In this study 219 proteins were up-regulated and 108 were down-regulated, most of which were uncharacterized effector proteins. Validation of these changes may provide insight into

some novel functions and pathways affected by PCSK9 and unrelated to LDLR processing. Finally, we validated changes from a functionally interesting protein from our SILAC data set, EHBP-1 in our PCSK9 gain of function cells and in PCSK9 transgenic mice, while in contrast the loss-of-function PCSK9 knockout mice showed the opposite result. This is the first endosomal-related protein shown to be affected by PCSK9. This type of proteomic analysis could potentially point researchers toward a new target (or targets) to down-regulate PCSK9 “activity” and a drug therapy to complement the lipid-lowering therapies currently on the market.

’ ASSOCIATED CONTENT

bS

Supporting Information Supplementary Table 1: Total list of quantified proteins. This material is available free of charge via the Internet at http://pubs. acs.org.

’ AUTHOR INFORMATION Corresponding Author

*Drs. Daniel Figeys and Janice Mayne, Ottawa Institute of Systems Biology, University of Ottawa. DF e-mail: dfigeys@ uottawa.ca. Tel: 613-562-5800 ext 8674. Fax 613-562-5655. JM e-mail: [email protected]. Tel: 613-562-5800 ext 8073. Fax 613-562-5655. 2023



’ ACKNOWLEDGMENT This work was funded by the Canadian Institutes of Health Research Grants (CIHR; CTP-82946 and MOP-102741), The Richard and Edith Strauss Foundation, and The Fondation J.Louis Levesque. D.F. is CIHR Canada Research Chair in Proteomics and Systems Biology. ’ ABBREVIATIONS: ApoER2, apolipoprotein E receptor 2; BACE, 1β-site amyloid precursor protein cleaving enzyme 1; CD 81, cluster of differentiation 81; EDTA, ethylenediaminetetraacetic acid; EEA1, early endosome antigen 1 protein; EHBP-1, EH-domain binding protein 1; ER, endoplasmic reticulum; ESI-MS/MS, electrospray ionization tandem mass spectrometry; HPLCESI-MS/MS, high-performance liquid chromatography/electrospray ionization tandem mass spectrometry; IPP, insilicos proteomic pipeline; LAMP1, lysosomal-associated membrane protein 1; LDLR, low-density lipoprotein receptor; MAN2A, alpha-mannosidase II; MS, mass spectrometry; PBS, phosphate buffered saline; PCSK9, proprotein convertase subtilisin/ kexin type 9; PNS, postnuclear supernatant; RME-8, receptor mediated endocytosis-8 protein; ROCK, rho associated, coiledcoil containing protein kinase 1; SDS-PAGE, sodium dodecyl sulfate - polyacrlyamide gel electrophoresis; SILAC, stable isotope labeling with amino acids in cell culture; SREBP-2, sterol regulatory element binding protein -2; TCL, total cell lysates; TGN, trans golgi network; TGN46, trans golgi network 46; VLDLR, very low density lipoprotein receptor. ’ REFERENCES (1) Chretien, M.; Seidah, N. G.; Basak, A.; Mbikay, M. Proprotein convertases as therapeutic targets. Expert Opin. Ther. Targets 2008, 12 (10), 1289–300. (2) Seidah, N. G.; Benjannet, S.; Wickham, L.; Marcinkiewicz, J.; Jasmin, S. B.; Stifani, S.; Basak, A.; Prat, A.; Chretien, M. The secretory proprotein convertase neural apoptosis-regulated convertase 1 (NARC-1): liver regeneration and neuronal differentiation. Proc. Natl. Acad. Sci. U.S.A. 2003, 100 (3), 928–33. (3) Abifadel, M.; Varret, M.; Rabes, J. P.; Allard, D.; Ouguerram, K.; Devillers, M.; Cruaud, C.; Benjannet, S.; Wickham, L.; Erlich, D.; Derre, A.; Villeger, L.; Farnier, M.; Beucler, I.; Bruckert, E.; Chambaz, J.; Chanu, B.; Lecerf, J. M.; Luc, G.; Moulin, P.; Weissenbach, J.; Prat, A.; Krempf, M.; Junien, C.; Seidah, N. G.; Boileau, C. Mutations in PCSK9 cause autosomal dominant hypercholesterolemia. Nat. Genet. 2003, 34 (2), 154–6. (4) Allard, D.; Amsellem, S.; Abifadel, M.; Trillard, M.; Devillers, M.; Luc, G.; Krempf, M.; Reznik, Y.; Girardet, J. P.; Fredenrich, A.; Junien, C.; Varret, M.; Boileau, C.; Benlian, P.; Rabes, J. P. Novel mutations of the PCSK9 gene cause variable phenotype of autosomal dominant hypercholesterolemia. Hum. Mutat. 2005, 26 (5), 497. (5) Naoumova, R. P.; Tosi, I.; Patel, D.; Neuwirth, C.; Horswell, S. D.; Marais, A. D.; van Heyningen, C.; Soutar, A. K. Severe hypercholesterolemia in four British families with the D374Y mutation in the PCSK9 gene: long-term follow-up and treatment response. Arterioscler. Thromb. Vasc. Biol. 2005, 25 (12), 2654–60. (6) Timms, K. M.; Wagner, S.; Samuels, M. E.; Forbey, K.; Goldfine, H.; Jammulapati, S.; Skolnick, M. H.; Hopkins, P. N.; Hunt, S. C.; Shattuck, D. M. A mutation in PCSK9 causing autosomal-dominant hypercholesterolemia in a Utah pedigree. Hum. Genet. 2004, 114 (4), 349–53. (7) Benjannet, S.; Rhainds, D.; Essalmani, R.; Mayne, J.; Wickham, L.; Jin, W.; Asselin, M. C.; Hamelin, J.; Varret, M.; Allard, D.; Trillard, M.; Abifadel, M.; Tebon, A.; Attie, A. D.; Rader, D. J.; Boileau, C.;

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Quantitative Proteomic Analysis of PCSK9 Gain of Function in Human

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