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Glaucoma  |   June 2012
Proteomics Analyses of Activated Human Optic Nerve Head Lamina Cribrosa Cells following Biomechanical Strain
Author Affiliations & Notes
  • Ronan Rogers
    Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada;
    Vision Science Research Program, Toronto Western Research Institute, University Health Network, Toronto, Ontario, Canada; the
    Department of Ophthalmology and Vision Science, Toronto Western Hospital, Toronto, Ontario, Canada; the
  • Moyez Dharsee
    Department of Ophthalmology and Vision Science, Toronto Western Hospital, Toronto, Ontario, Canada; the
  • Suzanne Ackloo
    Department of Ophthalmology and Vision Science, Toronto Western Hospital, Toronto, Ontario, Canada; the
  • John G. Flanagan
    Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada;
    Vision Science Research Program, Toronto Western Research Institute, University Health Network, Toronto, Ontario, Canada; the
    Department of Ophthalmology and Vision Science, Toronto Western Hospital, Toronto, Ontario, Canada; the
    Ontario Cancer Biomarker Network, Toronto, Ontario, Canada; and the 5School of Optometry, University of Waterloo, Waterloo, Ontario, Canada.
  • Corresponding author: Ronan Rogers, Institute of Medical Science, University of Toronto, Department of Ophthalmology and Vision Science, Toronto Western Hospital, Ontario, Canada; ronan.rogers@utoronto.ca
Investigative Ophthalmology & Visual Science June 2012, Vol.53, 3806-3816. doi:10.1167/iovs.11-8480
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      Ronan Rogers, Moyez Dharsee, Suzanne Ackloo, John G. Flanagan; Proteomics Analyses of Activated Human Optic Nerve Head Lamina Cribrosa Cells following Biomechanical Strain. Invest. Ophthalmol. Vis. Sci. 2012;53(7):3806-3816. doi: 10.1167/iovs.11-8480.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose.: To determine protein regulation following activation of human, optic nerve head (ONH), lamina cribrosa (LC) cells in response to mechanical strain.

Methods.: LC cells were isolated and grown from donor tissue in specific media at 37°C and 5% CO2 humidified incubator. Cells were grown to confluence on collagen I–coated flexible-bottom culture plates, rinsed with Dulbecco's phosphate-buffered saline, and left for 24 hours in serum-free media. They were subjected to 3% or 12% cyclic equiaxial stretch for 2 or 24 hours using a commercial strain-unit system. Control cells were serum-deprived and incubated without stretch for 24 hours. Nano liquid chromatography–mass spectrometry analysis with isobaric tags for relative and absolute quantitation labeling was used to determine protein regulation.

Results.: In all, 526 proteins were discovered at a 95% confidence limit. Analysis of associated pathways and functional annotation indicated that the LC cells reacted in vitro to mechanical strain by activating pathways involved in protein synthesis, cellular movement, cell-to-cell signaling, and inflammation. These pathways indicated consistent major protein hubs across all stretch/time conditions involving transforming growth factor-β1 (TGFβ1), tumor necrosis factor (TNF), caspase-3 (CASP3), and tumor protein-p53 (p53). Among proteins of particular interest, also found in multiple stretch/time conditions, were bcl-2–associated athanogene 5 (BAG5), nucleolar protein 66 (NO66), and eukaryotic translation initiation factor 5A (eIF-5A).

Conclusions.: Pathway analysis identified major protein hubs (TGFβ1, TNF, CASP3, p53) and pathways all previously implicated in cellular activation and in the pathogenesis of glaucomatous optic neuropathy. Several specific proteins of interest (BAG5, NO66, eIF-5A) were identified for future investigation as to their role in ONH glial activation.

Introduction
The main characteristic of primary open-angle glaucoma (POAG) is the progressive death of retinal ganglion cells. Loss of vision results as these cells undergo apoptosis. A rise in intraocular pressure (IOP) is a known risk factor for glaucoma, 1,2 and reducing the pressure within the eye has been shown to be beneficial to the clinical management of the disease. 1,3,4 Currently, the basic mechanisms by which elevated IOP leads to the apoptotic death of retinal ganglion cells are poorly understood. 
Lamina cribrosa (LC) cells are one of the major glial cell types found within the optic nerve head (ONH), 57 and their primary role, although still not clearly understood, is thought to revolve around maintenance and protection of retinal ganglion cell function. 7 They are glial-like, with staining characteristics that are similar to those of astrocytes, that is, positive for neural cell adhesion molecule (NCAM), vimentin, desmin, and paired box gene−2 (Pax-2), but differ in that they stain negatively for glial acidic fibrillary protein (GFAP) (Fig. 1). They have been shown to react to cyclical strain by upregulating tumor growth factor-β1 (TGFβ1) and matrix metalloproteinase-2 (MMP2). 7,8 Release of these mediators indicates that these cells may have a mechanosensory function that responds to physical strain. It has been known for some time that LC cells are very similar in morphology and characterization to those of trabecular meshwork (TM) cells. 9,10 There has been a considerable amount of work published on the cytoskeleton and functional properties of TM cells, 1114 although there has been relatively little research concerning LC cells. 10 A sign of glaucoma is the loss of neural rim tissue in the ONH along with compression, stretching, and rearrangement of the cribriform plates of the lamina cribrosa. 1519 There are a number of connective tissues that are remodeled within the glaucomatous ONH, and the activation of the glial cells may be playing a role in this process. After injury, reactive glial cells have been shown to synthesize extracellular matrix (ECM) proteins such as tenascin, laminin, and chondroitin sulfate proteoglycan, which can remodel the microenvironment of the neural tissue, possibly providing boundaries to isolate damaged neurons or prevent the migration of inflammatory cells. 20 A number of immunohistochemical and molecular biological techniques have documented the changes in the macromolecular components of the ECM. These changes have been documented in various collagen types, basement membrane components, glycosaminoglycans, elastin, tenascin, and fibrillin, which are believed to be playing a role in the modification of the ONH. 2128 Actin has been shown to arrange in a polygonal nature, designated cross-linked actin networks (CLANS), as a possible precursor to the development of glaucoma. This has been particularly noted in the TM. 27 In an ongoing parallel study, we are looking into the modification of CLANS of the ONH following insult. The stress fibers of LC cells appear to have properties similar to those of the TM, in that they respond to and possibly resist the biomechanical strain that occurs in the normal and abnormal environment of the ONH. 29 The organization of all the tissues that make up the lamina cribrosa contribute to the ability of that tissue to adapt to normal changes in IOP, although this organization is disrupted in those with glaucomatous optic neuropathy. Lamina cribrosa cells, initially characterized by Hernandez et al., 5 were found to be flat and polygonal in shape, and grow in a monolayer. These differ from fibroblasts, which multilayer and have a much more prominent intracellular space. 5 They stain positive for vimentin and desmin, which differentiates them from desmin-negative staining fibroblasts. 30 For a recent review on glia refer to the supplemental issue in Nature Insight. 3135  
Figure 1. 
 
LC cells, dissected from postmortem human optic nerves, were characterized and seeded onto flexible culture plates. These cells show positive staining for NCAM, vimentin, desmin, Pax-2, S-100, and a-smA. There is negative staining for GFAP and A2B5. This panel would indicate that these are not astrocytes based primarily on their lack of GFAP reactivity (×40).
Figure 1. 
 
LC cells, dissected from postmortem human optic nerves, were characterized and seeded onto flexible culture plates. These cells show positive staining for NCAM, vimentin, desmin, Pax-2, S-100, and a-smA. There is negative staining for GFAP and A2B5. This panel would indicate that these are not astrocytes based primarily on their lack of GFAP reactivity (×40).
We have developed models used to mimic the in vivo biomechanical environment in the LC by growing human ONH LC cells on flexible, silastic membranes and subjecting the cells to deformation. The level of strain used in these models was previously calculated by Sigal et al., 16,17,36 using finite element modeling, experienced by cells of the ONH depending on the level of IOP. This is accomplished using a commercial strain-unit system (Flexercell Tension Plus FX-4000T; Flexcell International Corp., Hillsborough, NC), which allows for the controlled cyclical stretch, between 1% and 12% deformation up to 1 Hz, for chosen periods of time. Higher degrees of deformation are possible but only at a lower frequency. We wanted to ensure that 1 Hz was used. Research similar to this has been conducted previously with the commercial system (Flexercell). 7,8 Other studies have analyzed the protein pathways of cells from the ONH following exposure to hydrostatic pressure, although it is not clear from a biomechanical perspective what type of stress hydrostatic pressure will induce. 22,37,38 Ethier et al. 39 compared the effects of hydrostatic pressure and gas tension within the culture medium on cell migration, morphology, and α-tubulin architecture. They reported that an increase in hydrostatic pressure had no effect, and that the biological effects previously reported were most likely artifacts due to hypoxia within the medium. We are confident that our approach of inducing biomechanical strain using equiaxial stretch is a more realistic model of the conditions found within the human lamina cribrosa.  
Proteomics research is a highly effective approach to the study of disease mechanisms. This is the first time that proteins from primary, ONH LC cells have been analyzed using isobaric tags for relative and absolute quantitation (iTRAQ)–based proteomics. 40 We have recently published research using this method to characterize biomarkers and pathways associated with ONH astrocytes. 41 Crabb and colleagues 42 have recently used iTRAQ to investigate the proteomic characterization of ganglion cells in a rat glaucoma model. An advantage of this technique is its ability to simultaneously determine the relative protein quantity of up to eight different samples, which makes it an ideal method for comparative studies. It has a large dynamic range, being able to detect both high- and low-abundance proteins. 43 The main disadvantages are the increase in mass spectrometry time required due to the increased number of peptides and the strict guidelines required for sample preparation. 44 The present work was performed in collaboration with the Ontario Cancer Biomarker Network (OCBN; Ontario, Canada). 
We present the total protein analysis of lamina cribrosa cells that had been stressed in a way to reproduce the level of strain predicted by our previous finite element models following a rise in IOP. The ultimate goal was to better understand, through protein analysis, the process of LC cell activation following biomechanical strain. 
Methods
The LC cells from three healthy human donors (ages 18, 19, 27 years) (Eye Bank of Canada, Ontario Division) were dissected into explants and grown in Dulbecco's modified Eagle's medium (DMEM)/F12 (4 mM l-glutamine; 1 g/L glucose; 1.5 g/L sodium bicarbonate; 10% fetal bovine serum; penicillin/streptomycin) until confluent, and in accordance with the human biosafety requirements of the University Health Network. When these cells reached confluence, they were split into T75 flasks and fed with a basic DMEM media. Cultures were maintained in sterile incubators at 37°C and 5% CO2 and media was changed twice a week. Morphologically, the LC cells are large, flat, and polygonal and grow in a monolayer. There was a high degree of cell purity 5,6 (>95% cell type). Cells were grown on 35-mm plates after the third passage for the purpose of characterization and allowed to grow to confluence, after which they were washed twice with Dulbecco's phosphate-buffered saline (plus Mg and Ca). The cells were then fixed in formalin, permeabilized in Triton-X, and specific primary and secondary antibodies were added. Primary human LC cells were characterized in a similar way to previous publications, 4548 with negative staining for GFAP and positive for α-smooth muscle actin (α-smA), Pax-2, vimentin, desmin, and S100. There was also negative staining for A2B5, which indicates that the cells are nonneuronal. However, these cells are distinct from myofibroblasts by having a positive stain for desmin. 49 They do not multilayer like scleral fibroblasts, which we have grown in our laboratory. They are distinct morphologically by being broad, flat, and polygonal, as opposed to stellate like the astrocytes (Fig. 1). 
Stretch Parameters
For the stretch experiments, cells at the fourth passage were seeded onto six-well, uncoated flexible-bottom culture plates (Flexcell International Corp., Hillsborough, NC), which were coated with collagen type I (Rat Tail Collagen; BD Biosciences, Franklin Lakes, NJ), and allowed to grow to confluence. Using a commercial strain-unit system (Flexercell Tension Plus FX-4000T System; Flexcell International), a programmable amount of equiaxial strain was applied to the cells through the use of a vacuum pump and a custom base plate. Four plates per experiment were stretched while four control plates were placed in the same incubator beside the base plate. All cells were serum deprived for 24 hours prior to stretching, which was performed at a 1-Hz cycle of 0% to 3%, or 0% to 12%, for either 2 or 24 hours. This produced six experimental results for each cell line. 
Protein Isolation
Total protein was isolated from experimental cells to be used in proteomics analyses through the use of a radioimmunoprecipitation assay (RIPA) buffer (20 mM Tris, pH 7.5; 150 mM sodium chloride [NaCl]; 1% Nonidet P-40; 0.5% sodium deoxycholate; 0.1% SDS; complete protease inhibitors [Roche Applied Science, Penzberg, Germany]). A volume of RIPA was added to each well (300 μL) and allowed to sit at room temperature for 15 minutes. The six wells from each plate were scraped down, combined into an Eppendorf tube, aspirated, and centrifuged at 10,000 rpm for 10 minutes. The cleared protein lysate was then prepared using a commercial total protein clean-up kit (Norgen Biotek Corp., Thorold, Ontario, Canada) according to the manufacturer's directions. 
Proteomics Analysis
Proteomics were performed by the OCBN. Six LC cell lysates were analyzed: a 2-hour control, a 24-hour control, a 3% for a 2-hour stretch, a 3% for a 24-hour stretch, a 12% for a 2-hour stretch, and a 12% for a 24-hour stretch (each lysate was a combination of the respective treatment from the three cell lines). Figure 2 represents the workflow of the iTRAQ analysis. 
Figure 2. 
 
Workflow of the iTRAQ proteomic analysis. The six cell samples were labeled with their respective isobaric tag and analyzed by liquid chromatography–mass spectrometry (MS/MS). The peak MS/MS charge from each tag indicates which sample is being measured and its quantity. The subsequent MS/MS fragmentation pattern identifies the peptides.
Figure 2. 
 
Workflow of the iTRAQ proteomic analysis. The six cell samples were labeled with their respective isobaric tag and analyzed by liquid chromatography–mass spectrometry (MS/MS). The peak MS/MS charge from each tag indicates which sample is being measured and its quantity. The subsequent MS/MS fragmentation pattern identifies the peptides.
Digestion and Labeling
Protein was extracted from cell lysates using a commercial kit (Norgen Biotek). 43 The concentration was determined using a microbicinchoninic acid (BCA) assay kit (Thermo Fisher Scientific, Waltham, MA). Protein samples (100 μg) from each condition were processed for iTRAQ labeling using a 6-plex approach. 40,43 Briefly, the proteins from each condition were denatured, reduced, alkylated, trypsin digested, and then labeled with the appropriate iTRAQ tags. After labeling, the 100-μg aliquots were pooled into one sample. 
Strong-Cation Exchange Chromatography
Each pooled sample was fractionated using strong-cation exchange (SCX) chromatography column (use of a Thermo BioBasic SCX column; Thermo Hypersil-Keystone, Inc., Bellefonte, PA), with 0.2-mm internal diameter and 10-cm length. Each sample was diluted with the loading buffer (15 mM potassium dihydrogen phosphate [KH2PO4-] in 25% acetonitrile [CH3CN], pH 3.0) to a total volume of 2 mL and the pH adjusted to 3.0 with phosphoric acid. Samples were filtered using a 0.45-μm syringe filter (EMD Millipore, Mississauga, Ontario, Canada) before loading onto the column. A diluted sample of 2 mL was injected into the SCX system. Separation was performed using a linear binary gradient from 0% solvent B to 50% solvent B in 40 minutes (solvent B: 2% H2O, 98% CH3CN, and 0.1% formic acid). The gradient was ramped to 100% solvent B in 2 minutes and held for 60 minutes. Buffer A was identical in composition to the loading buffer, whereas Buffer B was the same as Buffer A but with the addition of 350 mM potassium chloride (KCl). After a 2-minute delay to evacuate the void volume, fractions were manually collected every 2 minutes to the end of the gradient. The last fraction was the 2-minute block after the ultraviolet signal returned to baseline. The fractions were dried by speed vacuuming and resuspended in 0.1% formic acid. The contents of each SCX fraction were resolved by C18 reversed-phase (RP) liquid chromatography. 
Reversed-Phase Chromatography
The nano liquid chromatography system (Nano LC Ultra; Eksigent Technologies, Dublin, CA) consists of a trap column (300 μm ID) and an analytical column (75 μm ID) packed with 5-μm colloidal silica microbeads (300-Å Zorbax SB-C18 beads; DuPont, Wilmington, DE). The analytical column is homemade at OCBN. Separation was performed using a linear binary gradient where solvent A is 98% H2O:2% CH3CN and 0.1% formic acid and solvent B is 2% H2O:98% CH3CN and 0.1% formic acid, and at a flow-rate of 300 nL/min with a 60-minute gradient to 30% B. The equivalent of 2 μg of protein was injected. 
Liquid Chromatography–Mass Spectrometry (LC/MS/MS)
The eluant from the nano liquid chromatography system was coupled to a quadrupole time-of-flight mass spectrometer (QSTAR Elite; AB SCIEX, Foster City, CA), through an electrospray ionization source equipped with a 15-μm ID emitter tip. After each survey scan, from m/z 400 to m/z 1500, three of the most intense ions with a charge state of 2 to 4 were selected for MS/MS analysis. These ions were then placed in a dynamic exclusion list for 3 minutes to avoid further selection of the same ions. The iTRAQ workflow used a commercial LC/MS/MS system software (Analyst QS Software; AB SCIEX), which is an integrated validation and quality control program found in the LC/MS/MS system. 
Data Processing and Analysis
Relative quantification and protein identification were performed with commercial software (ProteinPilot Software, version 2.0; AB SCIEX) using a suite of search algorithms (Paragon Algorithm; Applied Biosystems, Foster City, CA) as the search engine. Each MS/MS spectrum was searched against a concatenated forward and reverse database of human protein sequences (Swiss-Prot, 22/07/2008). The search parameters allowed for 8-plex iTRAQ labeling (QSTAR Elite Series; ESI Ergonomic Solutions, Mesa, AZ), trypsin digestion, cysteine modification by methyl methanethiosulfonate (MMTS), homo sapiens, and biological modifications programmed in the algorithm (which include phosphorylations, amidations, and semitryptic fragments). The detected protein threshold (unused protscore [confidence]) in the software was set to 0.05 to achieve 10% confidence, and identified proteins were grouped by algorithm (ProGroup algorithm; AB SCIEX) to minimize redundancy. A minimum protein confidence threshold of 10% was used for the database search (ProteinPilot) and only those proteins with at least 95% confidence and at most 5% false discovery rate (FDR) were considered in subsequent analysis of putative differential expression. The bias correction option was executed. Proteins without quantitative information (i.e., only one iTRAQ ratio) were deleted from the list of identified proteins. Differentially expressed proteins were defined as those showing an absolute fold-change of at least 1.5 relative to time-matched controls. A commercial model/analytical software system (Ingenuity Pathways Analysis [IPA], www.ingenuity.com, version 8.7; Ingenuity Systems, Redwood City, CA) was used to determine pathways and functions implicated in stretching the cells for the prescribed amount of time. For each condition, the core analysis feature (IPA) was used to construct molecular interaction networks based on relationships between observed proteins and with other molecules, as annotated in the program's knowledge base (Ingenuity Systems). The resulting networks were then merged (using the Merge Networks feature) through the introduction of additional relationships. This analysis also provided a mapping of observed proteins to known cellular functions and processes; a P value based on a right-tailed Fisher Exact Test was associated with each functional category found to be enriched in the expression data set. Pathways analyses such as these allow for the creation of networks based on specific cell and tissue types, such as neural or organ related. Unfortunately, at this time there is not a specific database for glial cells, which is a limitation of the method. These pathways represent the most current scientific literature available and are changing on a weekly basis as more research is published. The pathways constructed are the most up to date at the time of publication, but are liable to change as new literature becomes available. Gene ontology (GO) analysis was also used on the resulting proteins. This type of analysis allowed for the grouping of proteins into relevant functional groups that are pertinent to our research, specifically apoptosis, activation, neurodegeneration, DNA damage/repair, cellular remodeling, and/or stress responses. The importance of using this analysis was to reduce the large number of discovered proteins to those that were most likely the result of cell activation. 
iTRAQ Calibration
Before samples were analyzed, 5 fmol of a bovine serum albumin digest was used to determine the quality of the LC/MS/MS system. The sample was required to show at least 20% sequence coverage with peptide scores ≥ 20 (ProteinPilot 2.0). Protein sequence identification was assigned (ProteinPilot 2.0) using a concatenated database of target and decoy sequences. This method enabled the calculation of the FDR, and the number of proteins identified with greater than a 95% probability of being correct at an FDR of 0.05. A stringent error tolerance, represented by the minimum 95% protein confidence score, was used to identify proteins with a high likelihood of correct sequence identification. In addition, the decoy database search was conducted to derive a robust estimate of local FDR, as described in Tang et al. 50 From the results of this search, a numeric receiver operating characteristic (ROC) plot showing absolute numbers of correct and incorrect protein identifications was generated to indicate correctly identified sequences in relation to false-positive identifications. The false-positive rate was approximately 1 in 20. 
The database (ProteinPilot) reports a P value and an error factor associated with each protein ratio, and an error percentage associated with each peptide ratio. Since the protein ratio statistics were not provided for all proteins, the maximum peptide ratio error percentage associated with each protein as an estimate of protein quantification error was used. The peptide error percentage is a measure of the error in the calculated peptide ratio, derived from the error for each of the reporter ion peak areas used in the ratio calculation. 
Results
The database (ProteinPilot) search yielded 526 proteins identified at a 95% confidence level at an FDR threshold of 0.05. Differentially expressed proteins for each experimental condition were processed by IPA software to determine pathways and functions involved in a specific stretch. The distribution of the fold-changes for the top 20 differentially expressed proteins associated with known and unknown molecular interactions and functions for the 12% stretch for 2 hours are listed in Table 1. Table 2 lists proteins that were found in more than one stretch/time condition, and either met the GO criteria (involved in apoptosis, activation, neurodegeneration, DNA damage/repair, cellular remodeling, or stress responses) or did not. The Supplemental Material contains the top proteins discovered in all remaining time/stretch conditions (see Supplementary Materials and Supplementary Tables S1 and S2) as well as the entire list of found proteins (see Supplementary Material and Supplementary Protein List).  
Table 1.  
 
Top Differentially Expressed Proteins Associated with Known and Unknown Molecular Interactions (IPA Analysis) and Functions for 12% Stretch at 2 Hours
Table 1.  
 
Top Differentially Expressed Proteins Associated with Known and Unknown Molecular Interactions (IPA Analysis) and Functions for 12% Stretch at 2 Hours
Lamina Cribrosa Cells Insult Protein Name Abbreviation Protein Name Cellular Location Fold Ratio
Upregulated 12% for 2 hours IMPDH2 IMP (inosine monophosphate) dehydrogenase 2 Cytoplasm 2.834
NONO Non-POU domain containing, octamer-binding Nucleus 2.420
UBA3 Ubiquitin-like modifier activating enzyme 3 Cytoplasm 2.056
RBM28 RNA binding motif protein 28 Nucleus 1.988
ATP1A3 ATPase, Na+/K+ transporting, alpha 3 polypeptide Plasma membrane 1.954
SYCP1 Synaptonemal complex protein 1 Nucleus 1.839
ERGIC1 Endoplasmic reticulum-Golgi intermediate compartment 1 Cytoplasm 1.792
LAMA3 Laminin, alpha 3 Extracellular space 1.707
CMAS Cytidine monophosphate N-Acetylneuraminic acid synthetase Nucleus 1.676
TAGLN2 Transgelin 2 Cytoplasm 1.661
Downregulated PPME1 Protein phosphatase methylesterase 1 Unknown 2.889
LTBP2 Latent transforming growth factor beta binding protein 2 Extracellular space 2.265
CAPNS1 Calpain, small subunit 1 Cytoplasm 2.170
KTN1 Kinectin 1 Cytoplasm 2.134
RARS Arginyl-tRNA synthetase Cytoplasm 2.113
SERPINB6 Serpin peptidase inhibitor, clade B (ovalbumin), member 6 Cytoplasm 2.112
RPN2 Ribophorin II Cytoplasm 2.086
DNAJA1 DnaJ (Hsp40) homolog, subfamily A, member 1 Nucleus 2.085
NEDD4 Neural precursor cell expressed, developmentally down-regulated 4 Cytoplasm 2.046
GNAL Guanine nucleotide binding protein (G protein), alpha activating activity polypeptide Cytoplasm 2.001
Upregulated (Unknown) DYNC1LI2 Cytoplasmic dynein 1 light intermediate chain 2 Cytoplasm 2.458
ZNF527 Zinc finger protein 527 Nucleus 2.308
RALGPS2 Ras-specific guanine nucleotide-releasing factor RalGPS2 Cytoplasm 1.907
NEK1 Serine/threonine-protein kinase Nek1 Nucleus 1.819
Downregulated (Unknown) KIAA1843 Uncharacterized protein KIAA1843 Unknown 2.441
PROSC Proline synthetase co-transcribed bacterial homolog protein Cytoplasm 2.183
Table 2.  
 
Top Proteins of Interest Found in Multiple Stretch/Time Conditions (Confirmed and Unconfirmed) Using Gene Ontology Analysis
Table 2.  
 
Top Proteins of Interest Found in Multiple Stretch/Time Conditions (Confirmed and Unconfirmed) Using Gene Ontology Analysis
Protein GO ID Cellular Location Stretch Regulation
Met GO criteria
 Inosine-5-monophosphate dehydrogenase 2 P12268 Cytoplasm 3% for 2 hours +2.76
12% for 2 hours +2.83
 Nucleolar protein 66 Q9H6W3 Nucleus 3% for 2 hours +1.84
12% for 2 hours +1.57
 Clathrin heavy chain 2 P53675 Plasma membrane 3% for 2 hours +1.70
3% for 24 hours +1.58
 26S protease regulatory subunit 6B P43686 Nucleus 3% for 2 hours –1.92
12% for 2 hours –1.94
12% for 24 hours +1.63
 Calpain-1 catalytic subunit P07384 Cytoplasm 3% for 2 hours –1.93
12% for 2 hours –1.55
 Calpain small subunit 1 P04632 Cytoplasm 3% for 2 hours –1.96
12% for 2 hours –2.12
 BAG family molecular chaperone regulator 5 Q9UL15 Unknown 3% for 24 hours +2.26
12% for 24 hours +2.18
 Thioredoxin domain-containing protein 4 Q9BS26 Cytoplasm 3% for 24 hours +2.11
12% for 24 hours +1.59
 Protein S100-A6 P06703 Cytoplasm 3% for 24 hours –1.70
12% for 24 hours –2.32
 Eukaryotic translation initiation factor 5A-1 P63241 Cytoplasm 12% for 2 hours –1.59
12% for 24 hours –3.79
Did not meet GO criteria
 Serine/threonine-protein kinase Nek1 Q96PY6 Nucleus 3% for 2 hours +2.55
3% for 24 hours –3.42
12% for 2 hours +1.82
 Transcription elongation factor A protein-like 3 Q969E4 Unknown 3% for 2 hours +2.12
3% for 24 hours –1.68
12% for 24 hours –2.01
 Elongation factor 1-delta P29692 Cytoplasm 3% for 2 hours +1.56
3% for 24 hours –3.10
12% for 24 hours –1.75
 Guanine nucleotide-binding protein G(o) subunit alpha P09471 Plasma membrane 3% for 2 hours –1.50
12% for 2 hours –1.56
12% for 24 hours –1.66
 Low-density lipoprotein receptor-related protein 6 O75581 Plasma membrane 3% for 2 hours –1.80
3% for 24 hours +1.81
12% for 24 hours +1.89
 ATP-dependent RNA helicase DDX54 Q8TDD1 Nucleus 3% for 2 hours –1.83
12% for 2 hours –1.51
12% for 24 hours –2.35
 26S protease regulatory subunit 6B P43686 Nucleus 3% for 2 hours –1.92
12% for 2 hours –1.94
12% for 24 hours +1.63
 Prothrombin P00734 Extracellular space 3% for 2 hours +1.74
3% for 24 hours +1.56
12% for 24 hours +2.06
 Nucleoporin SEH1-like Q96EE3 Cytoplasm 3% for 24 hours +1.54
12% for 2 hours –1.71
12% for 24 hours +1.61
 Ubiquitin carboxyl-terminal hydrolase 4 Q13107 Nucleus 3% for 2 hours –1.63
12% for 2 hours –1.85
12% for 24 hours +1.56
The top cellular functions that were discovered from the pathways of each time/stretch point identified various cellular reactions to stress (Fig. 3). The relationship of the specific function charts indicated what was occurring on a cellular level as time or intensity was increased. These functions are the result of our discovered iTRAQ proteins that are associated with specific trends based on peer-reviewed publications. These trends are automatically compiled and given confidence values from IPA software. A trend of increasing protein synthesis can be seen as the cells were subjected to greater degrees of stretch as well as longer times of exposure. A similar trend is seen regarding cellular movement, indicating that proteins discovered were involved in physical reorganization. Cell-to-cell signaling and the inflammatory response are slightly different in that they exhibit a greater response during the 24-hour stretch compared with the 2-hour stretch. 
Figure 3. 
 
Values (−log [P]) representing trends in major protein pathways discovered by genomic pathway analysis (IPA). Protein synthesis and cellular movement pathways increased as the intensity of the stretch/time was increased. Cell-to-cell signaling interaction and inflammation had a greater response for 24 hours vs. 2 hours as opposed to strain level.
Figure 3. 
 
Values (−log [P]) representing trends in major protein pathways discovered by genomic pathway analysis (IPA). Protein synthesis and cellular movement pathways increased as the intensity of the stretch/time was increased. Cell-to-cell signaling interaction and inflammation had a greater response for 24 hours vs. 2 hours as opposed to strain level.
The results for the LC cells at the 3% for 2-hour stretch showed the top scoring network included a number of proteins that were either up- or downregulated with interactions concentrated around tumor necrosis factor (TNF) and tumor protein 53 (p53). Of all differentially regulated proteins in this stretch, 9 were specific to the stretch, 13 were found in two stretches, whereas 2 were found in three of the stretch conditions. Proteins found in multiple conditions were further analyzed using GO annotation, and highlighted if known to be involved in apoptosis, activation, neurodegeneration, DNA damage/repair, cellular remodeling, or stress response. 
The results of the 3% stretch for 24 hours produced networks primarily interacting with TNF and p53. A total of 22 proteins were found to be specific to this stretch; 11 were found in 2 stretch conditions and 2 were found in 3 stretch conditions. 
The 12% stretch for 2 hours generated merged networks that indicated transforming growth factor beta 1 (TGFβ1), TNF, p53, and caspase-3 (CASP3) continue to play a significant role (Fig. 4); 20 proteins were unique to this stretch, whereas 13 were found in 2 conditions and 2 were found in 3 distinct stretch conditions. 
Figure 4. 
 
Integration of the identified proteins into the canonical pathways for LC cell stretch of 12% for 2 hours using IPA. Proteins were identified as being within the nucleus, the cell membrane, extracellular, or intracellular. A solid line indicates a direct protein–protein interaction; a dashed line indicates an indirect interaction; a dotted line indicates a protein–DNA or protein–RNA interaction. Direct interactions involving observed proteins were displayed as bold lines. Red molecules are upregulated and green molecules are downregulated. White-colored molecules were not observed in the experiments, but were incorporated into the network through relationships with observed proteins. Of particular note were the network hubs centered on TGFβ, TNF, p53, and CASP3.
Figure 4. 
 
Integration of the identified proteins into the canonical pathways for LC cell stretch of 12% for 2 hours using IPA. Proteins were identified as being within the nucleus, the cell membrane, extracellular, or intracellular. A solid line indicates a direct protein–protein interaction; a dashed line indicates an indirect interaction; a dotted line indicates a protein–DNA or protein–RNA interaction. Direct interactions involving observed proteins were displayed as bold lines. Red molecules are upregulated and green molecules are downregulated. White-colored molecules were not observed in the experiments, but were incorporated into the network through relationships with observed proteins. Of particular note were the network hubs centered on TGFβ, TNF, p53, and CASP3.
Molecular and cellular functions from the 12% stretch for 24 hours once again centered on TNF, TGFβ1, and p53. A total of 21 proteins were found to be unique to this condition; 9 were found in 2 conditions and 3 were found in 3 conditions. 
Discussion
iTRAQ-based proteomics analyses enables researchers to identify potential biomarkers and to better understand disease mechanisms using relative quantification and multiplexing approaches. 38,5153 This study, in conjunction with our previously published research 41 is the first time that a global protein analysis using this technique has been used to examine stress-induced glial cell activation. In this study we investigated the differential protein expression of ONH lamina cribrosa cells that were stretched by either 3% or 12% for 2 or 24 hours. 
Over 1600 proteins were found in each stretch/time combination, of which 526 were discovered outside the 95% confidence limit. Of the top proteins found for the lamina cribrosa cells within each test condition, based on highest fold-change and confidence, most were located within the cytoplasm, whereas a few were nuclear or were bound to the plasma membrane. The remaining were either in the extracellular space or the location was not clearly annotated. These results are most likely due to our use of cell lysate rather than cellular media and the analysis of secreted proteins. The ROC plot depicting true and false positive protein identification rates for the iTRAQ technique indicated a high level of sensitivity and specificity, supporting its use and the experimental design of our study. 
A number of proteins expressed could be considered potential indicators of cellular activation. Here we focus on the proteins that satisfied the GO-based functional refinement procedure (Table 2) and their putative involvement in the activation of the surrounding astrocytes and the remodeling of the lamina cribrosa. The protein bcl-2–associated athanogene 5 (BAG5) is of interest and was upregulated 2.2-fold in the 3% and 12% stretch for 24 hours. This protein is a member of the family of molecular chaperone regulators that affect numerous cellular pathways, 54 and has been shown to enhance dopaminergic neuronal degeneration in tandem with the chaperone activity of heat shock protein 70 (HSP70). 55 Specifically, it interacts with HSP70 by inhibiting its ability to refold misfolded proteins. One of the most significant findings from the Kalia et al. study 55 is that overexpression of this protein significantly enhances cell death of neurons within specific areas of the affected brain. It has also been implicated in other neurodegenerative diseases such as Parkinson's. 55,56  
Nucleolar protein 66 (NO66) was upregulated 1.8- and 1.5-fold in the 3% and 12% for 2 hours stretch conditions, respectively. This protein is found in the nucleolus and has been shown through various proteomics studies to be highly conserved and play a role in the biogenesis of ribosomes, and in the replication or silencing of certain heterochromatic regions. 57  
Eukaryotic translation initiation factor 5A (eIF-5A) was the most downregulated signal within the 12% for 24-hour stretch condition, at −3.8-fold. eIF5A is the only cellular protein that contains the amino acid hypusine. 58,59 Vertebrates carry two genes that encode two eIF5A isoforms, eIF5A-1 and eIF5A-2, which, in humans, are 84% identical. 60 It is highly conserved in mammals 61 and has been implicated in numerous disease processes including cancer, 60,62 dengue fever, 63 diabetes, 64 and HIV. 65 We have previously shown an association between eIF-5A and apoptosis 66 and, more recently, that apoptosis induction by eIF-5A involves activation of the intrinsic mitochondrial pathway. 67  
An important finding through all time and stretch combinations constituted the primary protein hubs involved in all pathways. The lack of an astrocyte-specific database for use in the pathways analyses is a limitation, and the resulting connections may be modified as further astrocyte proteomic data are published. These pathways are also a static representation of a dynamic environment, and the results of maps such as these, as described by Vidal et al. 68 need to follow four critical parameters: completeness, assay sensitivity, sampling sensitivity, and precision. Consideration of these parameters relative to this study shows a high degree of completeness and accuracy. However, by sampling at a single time point, certain interactions between proteins may be missing from the results. This is a problem regarding all analyses of protein networks because they are dynamic by nature. TGFβ1, tumor protein 53 (p53), TNF-α, and caspase-3 connected the majority of the discovered proteins. These hubs have previously been linked to inflammatory conditions and matrix remodeling. These hubs were also significant in our study examining the effect of these stressors on ONH astrocytes. 41 TGFβ1 has been found to be differentially regulated in glaucomatous lamina cribrosa tissue 69 and is known to play a significant role in the synthesis, degradation, or modification of the extracellular matrix of the trabecular meshwork. 12 Thrombospondin is thought to be involved in modulating this protein, 12 and was downregulated 2-fold in the 12% for 2-hour stretch. TGFβ1 mRNA levels were measured in lamina cribrosa cells 7 using a stretch model similar to the one presented here. They found significant increases after both 12 and 24 hours of stretch. Another major protein hub was p53. Gene expression of this protein was found to be significantly upregulated in the rat retina in an ischemia/reperfusion model. 70 They also found caspase-3, another major hub in the 12% for a 2-hour stretch, to be upregulated. 70 Caspase-3 was found to be upregulated in the retina at both the protein and gene levels, again following an ischemic–reperfusion model. 71 Tezel and Wax 72 reported how the apoptotic process involved the caspase-3 pathway, and used caspase inhibitors to block the apoptotic cascade. They also proposed that TNFα was associated with retinal ganglion cell death. 7375 All of the major protein hubs listed have been shown to play an important role in the apoptotic cascade that results in glaucoma in the retinal ganglion cells and their axons. 
Figure 3 illustrates the changes in pathway activity experienced by the LC cells with an increase in time or magnitude of strain. The level of protein synthesis increased logarithmically from the initial 3% stretch for 2 hours, up to the 12% stretch for 24 hours. A number of the proteins associated with this trend relate to the metabolism, biosynthesis, and translation of the protein. Specifically, several eukaryotic translation initiation factors were involved, which have a direct role in regulating proteolysis and are likely to increase with stress. 7678 The level of proteins associated with cellular movement increased in a similar manner, with the highest level seen in the 12% for a 24-hour stretch. The cells are likely attempting to accommodate to the increased levels of insult by producing proteins that will allow them to mitigate the stresses being exerted upon them. Specific proteins such as thrombin, insulinlike growth factor binding protein, and integrin alpha have previously been associated with this type of activity. 79,80 Within our study, the protein prothrombin was found in three of the four stretches. A slightly different trend was seen for both the cell-to-cell signaling and inflammatory response. The highest levels of change were seen in both the 24-hour stretches as compared with the 2-hour stretches, regardless of the magnitude. It is possible that the cells that are stressed for a longer period of time are more likely to produce proteins that are associated with both of these pathways. In particular, a number of coagulation factors and integrins, associated with cell signaling and cell adhesion, were upregulated. 81,82 More time points with the same percentage of stretch will be analyzed in the future to better visualize the trends and interactions that are occurring. 
We examined the stress response induced by stretch of different magnitude and time course, on human lamina cribrosa cells cultured in vivo from the human optic nerve head. Lysates from four stress conditions were prepared as part of a 6-plex iTRAQ quantitative proteomic analysis, with the goal of better understanding LC remodeling and activation. These cells are an important part of the structural anatomy of the optic nerve head, and how they respond to mechanical strain is potentially important in understanding the early pathogenesis of glaucoma. 29 Determining the role of proteins implicated in this response may lead to a greater understanding of the mechanisms involved in the apoptotic death of the retinal ganglion cells and the remodeling of the lamina cribrosa. We have identified 17 proteins of potential interest, of which we propose BAG5, NO66, and eIF-5A to be of particular interest in the pathogenesis of glaucoma, the second leading cause of blindness in the world. 
Supplementary Materials
References
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Footnotes
 Supported in part by grants from the Canadian Institutes of Health Research, the American Health Assistance Foundation, the Glaucoma Research Society of Canada, and scholarships from the Peterborough K.M. Hunter Studentship and the Vision Science Research Program of the Toronto Western Research Institute (RR).
Footnotes
 Disclosure: R. Rogers, None; M. Dharsee, None; S. Ackloo, None; J.G. Flanagan, None
Figure 1. 
 
LC cells, dissected from postmortem human optic nerves, were characterized and seeded onto flexible culture plates. These cells show positive staining for NCAM, vimentin, desmin, Pax-2, S-100, and a-smA. There is negative staining for GFAP and A2B5. This panel would indicate that these are not astrocytes based primarily on their lack of GFAP reactivity (×40).
Figure 1. 
 
LC cells, dissected from postmortem human optic nerves, were characterized and seeded onto flexible culture plates. These cells show positive staining for NCAM, vimentin, desmin, Pax-2, S-100, and a-smA. There is negative staining for GFAP and A2B5. This panel would indicate that these are not astrocytes based primarily on their lack of GFAP reactivity (×40).
Figure 2. 
 
Workflow of the iTRAQ proteomic analysis. The six cell samples were labeled with their respective isobaric tag and analyzed by liquid chromatography–mass spectrometry (MS/MS). The peak MS/MS charge from each tag indicates which sample is being measured and its quantity. The subsequent MS/MS fragmentation pattern identifies the peptides.
Figure 2. 
 
Workflow of the iTRAQ proteomic analysis. The six cell samples were labeled with their respective isobaric tag and analyzed by liquid chromatography–mass spectrometry (MS/MS). The peak MS/MS charge from each tag indicates which sample is being measured and its quantity. The subsequent MS/MS fragmentation pattern identifies the peptides.
Figure 3. 
 
Values (−log [P]) representing trends in major protein pathways discovered by genomic pathway analysis (IPA). Protein synthesis and cellular movement pathways increased as the intensity of the stretch/time was increased. Cell-to-cell signaling interaction and inflammation had a greater response for 24 hours vs. 2 hours as opposed to strain level.
Figure 3. 
 
Values (−log [P]) representing trends in major protein pathways discovered by genomic pathway analysis (IPA). Protein synthesis and cellular movement pathways increased as the intensity of the stretch/time was increased. Cell-to-cell signaling interaction and inflammation had a greater response for 24 hours vs. 2 hours as opposed to strain level.
Figure 4. 
 
Integration of the identified proteins into the canonical pathways for LC cell stretch of 12% for 2 hours using IPA. Proteins were identified as being within the nucleus, the cell membrane, extracellular, or intracellular. A solid line indicates a direct protein–protein interaction; a dashed line indicates an indirect interaction; a dotted line indicates a protein–DNA or protein–RNA interaction. Direct interactions involving observed proteins were displayed as bold lines. Red molecules are upregulated and green molecules are downregulated. White-colored molecules were not observed in the experiments, but were incorporated into the network through relationships with observed proteins. Of particular note were the network hubs centered on TGFβ, TNF, p53, and CASP3.
Figure 4. 
 
Integration of the identified proteins into the canonical pathways for LC cell stretch of 12% for 2 hours using IPA. Proteins were identified as being within the nucleus, the cell membrane, extracellular, or intracellular. A solid line indicates a direct protein–protein interaction; a dashed line indicates an indirect interaction; a dotted line indicates a protein–DNA or protein–RNA interaction. Direct interactions involving observed proteins were displayed as bold lines. Red molecules are upregulated and green molecules are downregulated. White-colored molecules were not observed in the experiments, but were incorporated into the network through relationships with observed proteins. Of particular note were the network hubs centered on TGFβ, TNF, p53, and CASP3.
Table 1.  
 
Top Differentially Expressed Proteins Associated with Known and Unknown Molecular Interactions (IPA Analysis) and Functions for 12% Stretch at 2 Hours
Table 1.  
 
Top Differentially Expressed Proteins Associated with Known and Unknown Molecular Interactions (IPA Analysis) and Functions for 12% Stretch at 2 Hours
Lamina Cribrosa Cells Insult Protein Name Abbreviation Protein Name Cellular Location Fold Ratio
Upregulated 12% for 2 hours IMPDH2 IMP (inosine monophosphate) dehydrogenase 2 Cytoplasm 2.834
NONO Non-POU domain containing, octamer-binding Nucleus 2.420
UBA3 Ubiquitin-like modifier activating enzyme 3 Cytoplasm 2.056
RBM28 RNA binding motif protein 28 Nucleus 1.988
ATP1A3 ATPase, Na+/K+ transporting, alpha 3 polypeptide Plasma membrane 1.954
SYCP1 Synaptonemal complex protein 1 Nucleus 1.839
ERGIC1 Endoplasmic reticulum-Golgi intermediate compartment 1 Cytoplasm 1.792
LAMA3 Laminin, alpha 3 Extracellular space 1.707
CMAS Cytidine monophosphate N-Acetylneuraminic acid synthetase Nucleus 1.676
TAGLN2 Transgelin 2 Cytoplasm 1.661
Downregulated PPME1 Protein phosphatase methylesterase 1 Unknown 2.889
LTBP2 Latent transforming growth factor beta binding protein 2 Extracellular space 2.265
CAPNS1 Calpain, small subunit 1 Cytoplasm 2.170
KTN1 Kinectin 1 Cytoplasm 2.134
RARS Arginyl-tRNA synthetase Cytoplasm 2.113
SERPINB6 Serpin peptidase inhibitor, clade B (ovalbumin), member 6 Cytoplasm 2.112
RPN2 Ribophorin II Cytoplasm 2.086
DNAJA1 DnaJ (Hsp40) homolog, subfamily A, member 1 Nucleus 2.085
NEDD4 Neural precursor cell expressed, developmentally down-regulated 4 Cytoplasm 2.046
GNAL Guanine nucleotide binding protein (G protein), alpha activating activity polypeptide Cytoplasm 2.001
Upregulated (Unknown) DYNC1LI2 Cytoplasmic dynein 1 light intermediate chain 2 Cytoplasm 2.458
ZNF527 Zinc finger protein 527 Nucleus 2.308
RALGPS2 Ras-specific guanine nucleotide-releasing factor RalGPS2 Cytoplasm 1.907
NEK1 Serine/threonine-protein kinase Nek1 Nucleus 1.819
Downregulated (Unknown) KIAA1843 Uncharacterized protein KIAA1843 Unknown 2.441
PROSC Proline synthetase co-transcribed bacterial homolog protein Cytoplasm 2.183
Table 2.  
 
Top Proteins of Interest Found in Multiple Stretch/Time Conditions (Confirmed and Unconfirmed) Using Gene Ontology Analysis
Table 2.  
 
Top Proteins of Interest Found in Multiple Stretch/Time Conditions (Confirmed and Unconfirmed) Using Gene Ontology Analysis
Protein GO ID Cellular Location Stretch Regulation
Met GO criteria
 Inosine-5-monophosphate dehydrogenase 2 P12268 Cytoplasm 3% for 2 hours +2.76
12% for 2 hours +2.83
 Nucleolar protein 66 Q9H6W3 Nucleus 3% for 2 hours +1.84
12% for 2 hours +1.57
 Clathrin heavy chain 2 P53675 Plasma membrane 3% for 2 hours +1.70
3% for 24 hours +1.58
 26S protease regulatory subunit 6B P43686 Nucleus 3% for 2 hours –1.92
12% for 2 hours –1.94
12% for 24 hours +1.63
 Calpain-1 catalytic subunit P07384 Cytoplasm 3% for 2 hours –1.93
12% for 2 hours –1.55
 Calpain small subunit 1 P04632 Cytoplasm 3% for 2 hours –1.96
12% for 2 hours –2.12
 BAG family molecular chaperone regulator 5 Q9UL15 Unknown 3% for 24 hours +2.26
12% for 24 hours +2.18
 Thioredoxin domain-containing protein 4 Q9BS26 Cytoplasm 3% for 24 hours +2.11
12% for 24 hours +1.59
 Protein S100-A6 P06703 Cytoplasm 3% for 24 hours –1.70
12% for 24 hours –2.32
 Eukaryotic translation initiation factor 5A-1 P63241 Cytoplasm 12% for 2 hours –1.59
12% for 24 hours –3.79
Did not meet GO criteria
 Serine/threonine-protein kinase Nek1 Q96PY6 Nucleus 3% for 2 hours +2.55
3% for 24 hours –3.42
12% for 2 hours +1.82
 Transcription elongation factor A protein-like 3 Q969E4 Unknown 3% for 2 hours +2.12
3% for 24 hours –1.68
12% for 24 hours –2.01
 Elongation factor 1-delta P29692 Cytoplasm 3% for 2 hours +1.56
3% for 24 hours –3.10
12% for 24 hours –1.75
 Guanine nucleotide-binding protein G(o) subunit alpha P09471 Plasma membrane 3% for 2 hours –1.50
12% for 2 hours –1.56
12% for 24 hours –1.66
 Low-density lipoprotein receptor-related protein 6 O75581 Plasma membrane 3% for 2 hours –1.80
3% for 24 hours +1.81
12% for 24 hours +1.89
 ATP-dependent RNA helicase DDX54 Q8TDD1 Nucleus 3% for 2 hours –1.83
12% for 2 hours –1.51
12% for 24 hours –2.35
 26S protease regulatory subunit 6B P43686 Nucleus 3% for 2 hours –1.92
12% for 2 hours –1.94
12% for 24 hours +1.63
 Prothrombin P00734 Extracellular space 3% for 2 hours +1.74
3% for 24 hours +1.56
12% for 24 hours +2.06
 Nucleoporin SEH1-like Q96EE3 Cytoplasm 3% for 24 hours +1.54
12% for 2 hours –1.71
12% for 24 hours +1.61
 Ubiquitin carboxyl-terminal hydrolase 4 Q13107 Nucleus 3% for 2 hours –1.63
12% for 2 hours –1.85
12% for 24 hours +1.56
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