Oxidative Medicine and Cellular Longevity
Volume 2017 (2017), Article ID 5140360, 21 pages
https://doi.org/10.1155/2017/5140360

Research Article

Tubulin Beta-3 Chain as a New Candidate Protein Biomarker of Human Skin Aging: A Preliminary Study

Sylvia G. Lehmann,¹ Sandrine Bourgoin-Voillard,2,3,4 Michel Seve,2,3,4 and Walid Rachidi5,6

¹University Grenoble Alpes, ISTerre, CS 40700, 38058 Grenoble Cedex 9, France
²University Grenoble Alpes, LBFA et BEeSy, PROMETHEE Proteomic Platform, Grenoble, France
³Inserm, U1055, PROMETHEE Proteomic Platform, Grenoble, France
⁴CHU Grenoble Alpes, Institut de Biologie et de Pathologie, PROMETHEE Proteomic Platform, Grenoble, France
⁵University Grenoble Alpes, INAC, SyMMES, 38000 Grenoble, France
⁶CEA, INAC, SyMMES, 38054 Grenoble, France

Correspondence should be addressed to Sylvia G. Lehmann; sylvia.lehmann@univ-grenoble-alpes.fr

Received 1 December 2016; Revised 1 March 2017; Accepted 19 March 2017; Published 23 May 2017

Academic Editor: Antonio Ayala

Copyright © 2017 Sylvia G. Lehmann et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Skin aging is a complex process, and a lot of efforts have been made to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Several studies concerning skin aging have analyzed the changes in gene expression, and very few investigations have been performed at the protein level. Moreover, none of these proteomic studies has used a global quantitative labeled proteomic offgel approach that allows a more accurate description of aging phenotype. We applied such an approach on human primary keratinocytes obtained from sun-nonexposed skin biopsies of young and elderly women. A total of 517 unique proteins were identified, and 58 proteins were significantly differentially expressed with 40 that were downregulated and 18 upregulated with aging. Gene ontology and pathway analysis performed on these 58 putative biomarkers of skin aging evidenced that these dysregulated proteins were mostly involved in metabolism and cellular processes such as cell cycle and signaling pathways. Change of expression of tubulin beta-3 chain was confirmed by western blot on samples originated from several donors. Thus, this study suggested the tubulin beta-3 chain has a promising biomarker in skin aging.

1. Introduction

Life expectancy in developed countries over the past two centuries has considerably increased, and if this trend continues through the 21st century, most babies born since 2000 in such countries will reach 100 years. Also, it is expected that by 2030, one in eight people worldwide will be 65 or above and the global aging of the population will lead to several societal, economical, and medical challenges [1].

Aging is a complex process influenced by multiple genetic and environmental factors and is characterized by a progressive decline in multiple physiological functions. Skin like other organs is affected by aging that can be accelerated by environmental factors such as UV radiation. Intrinsic skin aging is observed in sun-nonexposed skin and reflects the aging process of the entire organism [2]. Thereby, skin is an interesting alternative approach to decipher the intrinsic aging process as it is easily accessible compared to internal organs or tissues. Skin undergoes several morphological and physiological changes with intrinsic aging such as fine wrinkle formation, thinning of the epidermis and dermis, increased vulnerability and fragility, dryness, loss of elasticity, and disturbed barrier function [2]. The underlying mechanisms of intrinsic aging are multiple: cellular senescence and decreased proliferative capacity; shortening of the telomeres; increase in DNA damage and reduction in DNA repair processes; mitochondrial and genomic DNA mutations; hormonal decline and oxidative stress [3, 4].

Over the last decade, several transcriptomic studies have investigated the effect of aging on gene expression in several organism models and in humans [5, 6]. Concerning skin aging, only few studies have been conducted in humans. The first showed that genes differently expressed in elderly and young human male skin were involved in various cellular processes such as metabolism, signal transduction, apoptosis, and regulation of transcription [7]. More recently, a study has compared the gene expression profile from sun-nonexposed skin in both genders depending on aging. There was a significant different response in both genders with aging, with only 39 genes commonly dysregulated and 4 of them regulated in the opposite manner in both genders. From these results, the WNT signaling pathway has emerged as the major downregulated pathway with aging in both sexes [8]. And lately, 75 differentially expressed genes were identified in human epidermis according to age status [9]. Pathway analysis revealed that these genes were mainly involved in cell migration, cancer, dermatological diseases, and cell proliferation. Also, genes involved in the development of the epidermis were significantly enriched, and an overall downregulation of keratinocytes differentiation was observed.

Proteins are the workhorses of the cell and the main effectors of numerous cellular processes. Quantitative mass spectrometry-based proteomics has proven its utility for the description of protein dynamics in order to decipher complex processes and to describe normal and pathological states [10–13]. Relatively few studies have used proteomic to investigate skin aging, and they all used a two-dimensional gel electrophoresis approach which leads to a lower coverage of the proteome than gel-free approaches that could provide a proteomic signature of aging [14–16].

Skin is composed of several cell layers, and previous studies have investigated the protein expression level in whole skin or in stratum corneum samples. But the different cell layers can behave very differently and exhibit a different response to aging. Keratinocytes are the major components of the epidermis which is the most superficial and accessible layer of the skin. Focusing on keratinocytes will help to gain a deeper insight into skin aging and to have access to the proliferative compartment of the epidermis. Skin structure differs between genders, mainly due to the role of androgens in skin morphology. In humans, male skin is thicker than female skin and female subcutaneous tissues are thicker than male’s one [17]. We then investigated the changes in the protein expression profile in human primary keratinocytes derived from sun-nonexposed skin obtained from young and elderly Caucasian women (mean age 62.5 years, , and 29.5 years, , resp.). Considering that the skin undergoes significant changes during menopause [18], the age categories were chosen so that the elderly women would have more probably reached menopause. Indeed, the average age where women reached menopause was 48.8 ± 4 years in a French cohort of women [19].

Our quantitative proteomic profiling, which expression was significantly dysregulated, of young and elderly primary human keratinocytes identified 58 proteins that are putative candidate biomarkers for intrinsic skin aging. Further western blot analysis on 14 donors confirms that tubulin beta-3 chain could be a biomarker of skin aging.

2. Material and Methods

2.1. Cell Culture

Human keratinocyte cultures were established by outgrowth from skin biopsies obtained after plastic mammary surgery (Centre Hospitalier Universitaire Grenoble Alpes, France) from healthy donors with their informed consent. Donors were Caucasian women aged 57–71 years () and 18–32 years () classified in two age groups designed hereafter elderly and young, respectively. Skin biopsies were from sun-nonexposed skin. Isolation and culture of primary keratinocytes in KSFM medium supplemented with 25 μg/mL bovine pituitary extract (BPE), 1.5 ng/mL EGF (Life Technologies), and 75 μg/mL Primocin™ (InvivoGen) were done as previously described [20]. To avoid replicative senescence, cells were used at passage 2 or 3.

2.2. Protein Extraction for MS Analysis

Cultured keratinocytes obtained from young (27 and 32 years) and elderly (60 and 65 years) donors were cultivated up to passage 2 and harvested by trypsinization. After two washes with PBS (Life Technologies), cell pellets were kept at −80°C up to the extraction. Frozen cell pellets were lysed for 30 minutes at 4°C in a solution containing 40 mM HEPES pH 7.4, 100 mM NaCl, 1 mM EDTA, 0.02% Triton, 0.02% sodium deoxycholate, 0.2 mM TCEP, and protease and phosphatase inhibitor cocktails (PhosSTOP) from Roche. Lysis was achieved by short sonication on ice, and the lysates were cleared by centrifugation at 14,000 rpm for 20 minutes at 4°C. The concentration of the protein extract was determined using BCA protein assay kit (Thermo Fisher Scientific, IL, USA).

2.3. Protein Digestion and iTRAQ Labeling

Protein samples were labeled with iTRAQ reagents according to the manufacturer’s instructions (iTRAQ Reagents 8 plex Applications kit; Sciex, Framingham, MA, USA). Briefly, equal amount of protein extract obtained from cells originated from young donors was pooled in order to achieve a total of 100 μg of proteins. The same procedure was applied for cells from elderly donors. The samples were reduced in 20 mM of TCEP (tris-(2-carboxyethyl)phosphine) at 37°C for 1 h, and cysteine residues were blocked in 10 mM of MMTS (methyl methanethiosulfonate) at room temperature for 10 min, followed by trypsin (Promega, Lyon, France) digestion at a ratio of 1 : 10 (trypsin : protein) at 37°C overnight. Each peptide solution was labeled with one iTRAQ reagent: iTRAQ reporter ions of m/z 113.1 for young and m/z 117.1 for elderly. iTRAQ labeling was verified for all reactions, and the samples were pooled in a ratio 1 : 1 and dried by vacuum centrifugation prior to the OFFGEL peptide fractionation.

2.4. Peptide OFFGEL Isoelectrofocusing

Peptide fractionation according to their pI was performed with 3100 OFFGEL Fractionator and the OFFGEL Kit linear pH 3–10 (Agilent Technology, Les Ulis, France) in a 24-well setup following the manufacturer’s instructions. The device was set up for the 24-fraction separation by using a 24-cm-long IPG gel strip with a linear pH gradient ranging at 3–10. iTRAQ-labeled peptide mix was dried by vacuum centrifugation and resuspended in focusing OFFGEL buffer prior to loading in each of the 24 wells. Peptides were focused with a constant current of 50 μA until 50 kVh was reached. After complete fractionation, peptide samples were recovered from each well, dried in a vacuum concentrator, and then desalted using C18 ZipTips (Millipore, MA, USA).

2.5. Reversed Phase Nanoliquid Chromatography

Further peptide separation was performed on an Ultimate 3000 C18 reversed phase nanoliquid chromatography (RP-nanoLC) system (Ultimate 3000, Dionex/Thermo Scientific) controlled by Chromeleon v. 6.80 software (Dionex/Thermo Scientific/LC Packings, Amsterdam, The Netherlands) and coupled with a PROBOT MALDI spotting device controlled by the μCarrier 2.0 software (Dionex/Thermo Scientific/LC Packings, Amsterdam, The Netherlands). Vacuum dried fractions were resuspended in buffer A (98% water, 2% ACN, and 0.05% TFA) before injection on a nanotrapping column (C18, 3 μm, 100 Å pore size; LC Packing) in 2% ACN and 0.05% TFA at a flow rate of 20 μL/min for 5 min. Then, trapped peptides were separated by reversed phase chromatography (Acclaim PepMap300 75 μm, 15 cm, nanoViper C18, 3 μm, 100 Å pore size; Thermo Scientific) with a binary gradient of buffer A (2% ACN and 0.05% TFA) and buffer B (80% ACN and 0.04% TFA) at a flow rate of 0.3 μL/min. The entire run lasted 60 min, and the nanoLC gradient was set up as follows: 5–35 min, 8–42% B; 35–40 min, 42–58% B; 40–50 min, 58–90% B; and 50–60 min, 90% B. Fractions from eluted solution were collected and spotted on a MALDI sample plate (Sciex, Les Ulis, France) at a frequency of one spot per 15 seconds. The α-cyano-4-hydroxy-cinnamic acid matrix (HCCA, 2 mg/mL in 70% ACN and 0.1% TFA) was continuously added to the column effluent at a flow rate of 0.9 μL/min and, therefore, integrated in each spot of MALDI sample plate.

2.6. MALDI-TOF/TOF Analysis

MS and MS/MS analysis of nanoLC-off-line spotted peptide samples was performed using the 4800 MALDI-TOF/TOF mass spectrometer (Sciex, Les Ulis, France) controlled by the 4000 Series Explorer software v. 3.5. The mass spectrometer was operated in a positive reflector mode. Each spectrum was externally calibrated using the Peptide Calibration Standard II (Bruker Daltonics, Bremen, Germany), and the peptide mass tolerance was set to 50 ppm. MS spectra were acquired in a m/z 700–4000 range. Up to 30 of the most intense ions per spot position characterized by a S/N (signal/noise) ratio higher than 40 were chosen for MS/MS analysis. Selected ions were activated by using CID (collision-induced dissociation) in order to obtain the corresponding MS/MS spectrum.

2.7. Analysis of iTRAQ Data

MS and MS/MS spectra were used for identification and relative quantitation by using ProteinPilot™ software v 4.0 with the Paragon™ (Sciex, Les Ulis, France) and Mascot (Matrix Science, London, UK) search engines. The analysis was performed with the UniProtKB database released on June 2015, and the taxonomy was limited to Homo sapiens. Concerning Paragon search engine, the search effort was set to “Thorough ID” and the False Discovery Rate Analysis (FDR) of 1% was applied. For quantification, bias and background correction was applied and only quantified proteins with at least 1 peptide at the 95% peptide confidence level were included. For Mascot search engine, the FDR was set lower than 1% and only peptides with a score higher than 30 were considered. Data were merged at the peptide level after Paragon and Mascot analysis. In order to obtain a high-quality quantitative analysis, we analyzed our data with the R package Isobar [21] which allows the determination of statistical significance of protein/peptide regulation. A normal fit was used and only proteins which ratio had a value ratio and a value sample <0.05 are then considered as significantly differently expressed depending on age. For output of our quantitative iTRAQ results, all protein ratios were expressed as elderly over young (117 : 113) to present relative protein quantification ratios. A summary of the parameters applied for the mass data analysis is presented in Supplemental Data (Table S1) available online at https://doi.org/10.1155/2017/5140360.

2.8. Gene Ontology and Pathway Analysis

Gene ontology and protein function analysis were performed using PANTHER (http://www.pantherdb.org/) [22] by importing the list of dysregulated proteins. Each protein was classified into one or several categories regarding PANTHER family, protein class, GO-slim molecular function, biological process, cellular component, and pathway. This functional classification of proteins regarding biological process and protein class is graphically illustrated in a pie chart. Pathway enrichment analysis was performed with PathVisio 3.2.2 Revision: 4047 [23] by importing the list presented in Table S2. The following criteria have been used and the calculation method was pathway-centric. The top enriched pathways and their Z-scores are represented.

2.9. Western Blot Analysis

Human primary keratinocytes were harvested and cultivated as described previously from skin biopsies of 8 young (age: 18, 21, 24, 26, 27 (2 donors), 30, and 32) and 10 elderly donors (age: 57, 59, 60, 62 (2), 65 (2), 66, 68, and 71). At early passages (2 or 3, when cells are still proliferating), cells were lysed by vortexing in RIPA Buffer (Sigma-Aldrich) containing protease inhibitors (Complete Mini protease inhibitor cocktail, Roche, Switzerland), 1 mM DTT and 100 μM PMSF. Samples were then centrifuged for 15 minutes at 14,000 rpm and the supernatants collected. Protein concentration was determined with MicroBC Assay (Interchim), and 20 μg of total protein was loaded on TGX Stain-Free™ FastCast™ 12% Acrylamide gels (Biorad). Proteins were transferred onto a nitrocellulose membrane using Trans-Blot® Turbo™ Transfert System (Biorad). Membranes were blocked with TBS-Tween 0.5% containing 5% nonfat milk and incubated with the tubulin beta-3 chain antibody (MA1-118; Thermoscientific) at 1/1000 dilution in TBS-Tween 0.5% containing 5% nonfat milk overnight at 4°C. After washing in TBS-Tween 0.5%, membranes were incubated with HRP conjugated secondary antibodies (Amersham ECL anti-mouse IgG HRP-linked, whole antibody, GE Healthcare) for 1 h at RT. Membranes were then washed in TBS-Tween 0.5%, and blot images were acquired on Molecular Imager Gel Doc XR+ and Chemidoc XRS+ Systems (Biorad). Specific detected bands were quantified with Image LAb 2.0 Software (Biorad), and corresponding intensities were normalized with total protein content and expressed as a ratio.

Western blot results of tubulin beta-3 chain were illustrated by box plots, and receiver operating characteristic curve (ROC curve) was created by using GraphPad Prism version 7.00 for Windows (GraphPad Software, La Jolla California USA, http://www.graphpad.com).

3. Results

3.1. Identification of Fifty-Eight Proteins Differentially Expressed with Aging by Proteomic Analysis

In order to obtain a quantitative proteomic map of elderly and young donor-derived keratinocyte cells, we used an iTRAQ labeling coupled with OFFGEL fractionation and off-line nanoLC/MS/MS as previously described [24]. The bioinformatics analysis with Paragon and Mascot search engines resulted in the identification of 517 unique proteins using a 1% FDR and considering only proteins with at least 1 peptide with confidence level ≥ 95% and score > 30. We performed a statistical analysis with the isobar package and quantified 446 proteins. Elderly keratinocytes were labeled with iTRAQ m/z 117 tag and young keratinocytes with iTRAQ m/z 113 tag. Thus, the ratio 117 : 113 (Elderly : Young) indicates the relative protein abundance between elderly and young cell samples. The complete list of identified proteins, including the UniProtKB accession number, ID, protein and gene name, peptide count, spectral count, sequence coverage, iTRAQ ratios with corresponding value ratio and value sample for elderly versus young cells are provided in Supplemental Data (Table S2). When the value ratio and the value sample were both <0.05, proteins were considered significantly differently expressed. Applying these criteria, we identified 58 proteins significantly differentially expressed depending on age status. From them, 40 were downregulated and 18 were upregulated with aging (Tables 1 and 2).

Table 1: List of proteins significantly downregulated in elderly versus young cells (iTRAQ ratio 117/113). Statistically significant iTRAQ ratios ( value ratio and value sample ≤ 0.05) for the 40 proteins that are downregulated.

Accession/variants
ID
Description
Gene
Peptide count
Spectral count
Sequence coverage (%)
Ratio [elderly/young]
value rat
value sample
Log10 ratio

O60814
H2B1K_HUMAN
Histone H2B type 1-K
HIST1H2BK
9
131
4.76
0.170
6.27E−05
4.36E−19
−0.769

O75334-[2-6]
LIPA2_HUMAN
Liprin-alpha-2
PPFIA2
2
2
0.64
0.295
3.83E−02
5.16E−10
−0.531

P20674
COX5A_HUMAN
Cytochrome c oxidase subunit 5A, mitochondrial
COX5A
2
3
9.33
0.309
1.56E−02
2.23E−09
−0.510

P04732
MT1E_HUMAN
Metallothionein-1E
MT1E
1
9
16.39
0.310
7.22E−13
2.40E−09
−0.509

P05204
HMGN2_HUMAN
Nonhistone chromosomal protein HMG-17
HMGN2
4
11
8.89
0.330
1.89E−02
1.50E−08
−0.482

Q15075
EEA1_HUMAN
Early endosome antigen 1
EEA1
2
3
0.64
0.331
1.71E−02
1.61E−08
−0.481

Q9UKY7-[2]
CDV3_HUMAN
Protein CDV3 homolog
CDV3
3
16
11.63
0.342
1.18E−03
4.11E−08
−0.466

O75152
ZC11A_HUMAN
Zinc finger CCCH domain-containing protein 11A
ZC3H11A
1
1
1.48
0.349
2.87E−02
7.18E−08
−0.457

P17096
HMGA1_HUMAN
High mobility group protein
HMG-I/HMG-Y
HMGA1
1
19
7.48
0.352
1.56E−02
8.83E−08
−0.454

P06454-[2]
PTMA_HUMAN
Prothymosin alpha [cleaved into:
prothymosin alpha, N-terminally
processed; thymosin alpha-1]
PTMA
5
24
12.61
0.357
4.01E−02
1.34E−07
−0.447

Q8NC51-[3]
PAIRB_HUMAN
Plasminogen activator inhibitor 1
RNA-binding protein
SERBP1
11
90
4.66
0.361
1.56E−02
1.82E−07
−0.442

Q13442
HAP28_HUMAN
28 kDa heat- and acid-stable phosphoprotein
PDAP1
1
1
7.18
0.363
1.23E−02
2.09E−07
−0.440

P63313
TYB10_HUMAN
Thymosin beta-10
TMSB10
2
35
13.64
0.364
1.30E−02
2.21E−07
−0.439

O00233
PSMD9_HUMAN
26S proteasome non-ATPase
regulatory subunit 9
PSMD9
1
6
5.38
0.383
2.34E−04
8.33E−07
−0.416

P05114
HMGN1_HUMAN
Nonhistone chromosomal protein HMG-14
HMGN1
3
13
8.00
0.384
1.20E−02
8.80E−07
−0.415

P62158
CALM_HUMAN
Calmodulin
CALM1
10
147
8.72
0.385
2.89E−02
9.13E−07
−0.415

P02795, P13640-[2], P80297
MT1G_HUMAN, MT1X_HUMAN, MT2_HUMAN
Metallothionein-1G, Metallothionein-1X, Metallothionein-2
MT1G, MT1X, MT2A
1
20
16.29
0.392
3.61E−03
1.47E−06
−0.406

P67936
TPM4_HUMAN
Tropomyosin alpha-4 chain
TPM4
5
48
3.23
0.401
3.64E−02
2.51E−06
−0.397

P22528
SPR1B_HUMAN
Cornifin-B
SPRR1B
4
56
8.99
0.405
2.54E−02
3.18E−06
−0.392

Q92538-[2,3]
GBF1_HUMAN
Golgi-specific brefeldin A-resistance guanine nucleotide exchange factor 1
GBF1
1
1
0.32
0.406
4.48E−02
3.34E−06
−0.391

P51858
HDGF_HUMAN
Hepatoma-derived growth factor
HDGF
4
12
3.75
0.429
2.37E−02
1.17E−05
−0.368

P61604
CH10_HUMAN
10 kDa heat shock protein, mitochondrial
HSPE1
12
121
7.84
0.455
2.20E−02
4.16E−05
−0.342

P07108-[2-5]
ACBP_HUMAN
Acyl-CoA-binding protein
DBI
4
50
9.20
0.460
1.86E−02
5.21E−05
−0.337

Q9C030-[2]
TRIM6_HUMAN
Tripartite motif-containing protein 6
TRIM6
2
8
1.23
0.463
1.10E−02
6.03E−05
−0.334

P20962
PTMS_HUMAN
Parathymosin
PTMS
4
11
8.82
0.468
1.44E−02
7.30E−05
−0.330

Q9GZP8
IMUP_HUMAN
Immortalization upregulated protein
IMUP
3
5
9.43
0.476
8.05E−03
1.05E−04
−0.322

Q9H299
SH3L3_HUMAN
SH3 domain-binding glutamic acid-rich-like protein 3
SH3BGRL3
3
36
10.75
0.490
1.62E−02
1.82E−04
−0.310

P62857
RS28_HUMAN
40S ribosomal protein S28
RPS28
3
20
17.39
0.491
9.21E−03
1.93E−04
−0.309

P16949-[2]
STMN1_HUMAN
Stathmin
STMN1
3
24
8.72
0.492
2.51E−02
2.00E−04
−0.308

P02765
FETUA_HUMAN
Alpha-2-HS-glycoprotein
AHSG
4
61
3.27
0.507
4.77E−02
3.38E−04
−0.295

O15212
PFD6_HUMAN
Prefoldin subunit 6
PFDN6
1
9
9.30
0.519
1.72E−02
5.20E−04
−0.285

P52926
HMGA2_HUMAN
High mobility group protein HMGI-C
HMGA2
3
8
11.93
0.528
1.02E−04
7.07E−04
−0.277

P61956
SUMO2_HUMAN
Small ubiquitin-related modifier 2
SUMO2
1
7
12.63
0.534
1.89E−02
8.65E−04
−0.272

Q9UHV9
PFD2_HUMAN
Prefoldin subunit 2
PFDN2
1
5
9.09
0.544
1.81E−02
1.16E−03
−0.265

P20929-[2,3]
NEBU_HUMAN
Nebulin
NEB
4
4
0.13
0.563
5.23E−06
2.03E−03
−0.250

P09429
HMGB1_HUMAN
High mobility group protein B1
HMGB1
5
33
5.58
0.563
9.96E−07
2.07E−03
−0.249

P62328
TYB4_HUMAN
Thymosin beta-4
TMSB4X
1
16
15.91
0.582
4.60E−03
3.41E−03
−0.235

P09497-[2]
CLCB_HUMAN
Clathrin light chain B
CLTB
7
24
3.49
0.593
1.87E−03
4.46E−03
−0.227

P35749-[2-4]
MYH11_HUMAN
Myosin-11
MYH11
1
5
0.56
0.649
4.13E−02
1.53E−02
−0.188

Q16629-[2-4]
SRSF7_HUMAN
Serine/arginine-rich splicing factor 7
SRSF7
2
13
3.78
0.651
3.09E−02
1.59E−02
−0.187

Table 2: List of proteins significantly upregulated in elderly versus young cells (iTRAQ ratio 117/113). Statistically significant iTRAQ ratios ( value ratio and value sample ≤ 0.05) for the 18 proteins that are upregulated.

Accession/variants
ID
Description
Gene
Peptide count
Spectral count
Sequence
coverage (%)
Ratio [elderly/young]
value ratio
value sample
Log10 ratio

P26373
RL13_HUMAN
60S ribosomal protein L13
RPL13
4
15
4.27
1.455
2.54E−03
3.04E−02
0.163

P01861
IGHG4_HUMAN
Ig gamma-4 chain C region
IGHG4
1
4
4.89
1.482
2.00E−02
2.46E−02
0.171

Q13200
PSMD2_HUMAN
26S proteasome non-ATPase regulatory
subunit 2
PSMD2
1
5
1.65
1.511
4.13E−02
1.96E−02
0.179

P13797
PLST_HUMAN
Plastin-3
PLS3
5
13
1.90
1.584
2.13E−02
1.08E−02
0.200

P49721
PSB2_HUMAN
Proteasome subunit beta type-2
PSMB2
1
22
5.47
1.635
1.82E−03
7.01E−03
0.214

P48643
TCPE_HUMAN
T-complex protein 1 subunit epsilon
CCT5
6
35
1.29
1.696
2.17E−03
4.15E−03
0.229

P11166
GTR1_HUMAN
Solute carrier family 2, facilitated glucose transporter member 1
SLC2A1
4
46
2.03
1.891
2.60E−02
7.28E−04
0.277

P61158
ARP3_HUMAN
Actin-related protein 3
ACTR3
6
26
2.63
2.040
3.21E−02
1.84E−04
0.310

P09211
GSTP1_HUMAN
Glutathione S-transferase P
GSTP1
10
117
7.62
2.308
3.65E−02
1.47E−05
0.363

P78417
GSTO1_HUMAN
Glutathione S-transferase omega-1
GSTO1
4
25
5.81
2.482
2.89E−10
2.77E−06
0.395

P13667
PDIA4_HUMAN
Protein disulfide-isomerase A4
PDIA4
3
4
1.09
2.633
2.99E−02
6.60E−07
0.420

P62277
RS13_HUMAN
40S ribosomal protein S13
RPS13
1
1
7.95
2.638
2.88E−02
6.27E−07
0.421

Q13509
TBB3_HUMAN
Tubulin beta-3 chain
TUBB3
4
19
4.00
2.664
4.21E−04
4.87E−07
0.426

P30048
PRDX3_HUMAN
Thioredoxin-dependent peroxide reductase, mitochondrial
PRDX3
1
1
5.47
2.769
3.86E−02
1.80E−07
0.442

Q01813-[2]
PFKAP_HUMAN
ATP-dependent 6-phosphofructokinase,
platelet type
PFKP
2
3
2.68
3.116
3.23E−02
6.75E−09
0.494

P50213
IDH3A_HUMAN
Isocitrate dehydrogenase [NAD] subunit alpha, mitochondrial
IDH3A
3
3
2.19
3.239
6.67E−03
2.14E−09
0.510

Q9Y6N5
SQRD_HUMAN
Sulfide:quinone oxidoreductase, mitochondrial
SQRDL
1
2
2.22
3.487
8.97E−03
2.17E−10
0.543

P38606-[2]
VATA_HUMAN
V-type proton ATPase catalytic subunit A
ATP6V1A
2
2
2.43
4.833
1.38E−02
1.75E−15
0.684

3.2. Gene Ontology Analysis

The 58 proteins previously identified were analyzed using PANTHER [22]. Their classifications into gene ontology and PANTHER categories are as follows: protein family, protein class, molecular function, biological process, cellular component, and pathway is listed in Table 3. This functional classification of biological process and PANTHER protein class is graphically illustrated in Figure 1. The main represented biological process categories are metabolism (30%); cellular process including cell cycle/cell signaling pathways/cell component movement (21%); cellular component organization/biological regulation (10%); localization/developmental process (8%); response to stimuli (4%); multicellular organismal process/immune system process (3%); and biological adhesion (1%). Concerning protein class, dysregulated proteins belong to the main following protein classes: nucleic acid binding (25%); cytoskeletal protein (13%); enzyme modulator (12%); oxidoreductase and signaling molecules (8%); chaperone (6%); transferase/transcription factor (4%); and extracellular matrix protein/hydrolase/carrier protein/membrane traffic protein/cell junction protein/kinase/isomerase/receptor (2%).

Table 3: List of proteins identified as differently expressed with age status and their functional classification relating to protein family, protein class, molecular function, biological process, cellular component, and pathway according to PANTHER and the GO database.

Accession
ID
Description
Gene
PANTHER
family/subfamily
PANTHER protein class
PANTHER GO-slim
molecular function
PANTHER GO-slim biological process
PANTHER GO-slim
cellular component
Pathway

P61158
ARP3_
HUMAN
Actin-related
protein 3
ACTR3
Actin-related protein 3
(PTHR11937:SF175)
Actin and actin-related
protein(PC00085)
Structural constituent
of cytoskeleton
(GO:0005198)
Cytokinesis(GO:0009987);
mitosis(GO:0000910);
cellular component
morphogenesis(GO:0007049);
intracellular protein
transport(GO:0007067);
exocytosis(GO:0032502);
endocytosis(GO:0009653);
cellular component
organization(GO:0032989)
Actin cytoskeleton(GO:0043226);
intracellular(GO:0005856)

P02765
FETUA_
HUMAN
Alpha-2-HS-glycoprotein
AHSG
Alpha-2-HS-glycoprotein
(PTHR13814:SF6)
Extracellular matrix
glycoprotein(PC00102);
cysteine protease
inhibitor(PC00100)
Cysteine-type peptidase
activity(GO:0003824);
protein binding (GO:0016787); cysteine-type
endopeptidase inhibitor
activity (GO:0008233)
Immune system
process(GO:0002376);
proteolysis(GO:0008152);
mesoderm
development(GO:0044238);
skeletal system
development(GO:0019538);
regulation of catalytic
activity (GO:0006508)
Extracellular region
(GO:0005576);
extracellular matrix
(GO:0031012)

P38606
VATA_
HUMAN
V-type proton
ATPase catalytic
subunit A
ATP6V1A
V-type proton atpase
catalytic subunit A
(PTHR15184:SF7)
ATP synthase(PC00227); anion channel (PC00068); ligand-gated ion channel (PC00002); ligand-gated ion channel (PC00133); DNA-binding protein (PC00049); hydrolase
(PC00141)
Hydrolase activity
(GO:0003824); receptor
activity (GO:0016787);
anion channel activity (GO:0004872);
ligand-gated ion channel
activity (GO:0005215);
cation transmembrane
transporter activity
(GO:0022857);
proton-transporting
ATP synthase activity,
rotational mechanism (GO:0005216);
single-stranded DNA
binding (GO:0005253)
Respiratory electron
transport chain
(GO:0008152);
purine nucleobase
metabolic process
(GO:0006091); cation
transport (GO:0022904)
Proton-transporting
ATP synthase complex
(GO:0032991); intracellular
(GO:0043234)

P62158
CALM_
HUMAN
Calmodulin
CALM1
Calmodulin
(PTHR23050:SF216)
Calmodulin (PC00060)
Calcium ion binding (GO:0005488);
calmodulin binding
(GO:0005509)
Cellular component
movement (GO:0009987);
cell cycle (GO:0006928);
cell communication
(GO:0007049)

CCKR signaling
map→CaM; B cell
activation→calmodulin;
heterotrimeric
G-protein signaling
pathway-rod
outer segment
phototransduction→
calmodulin; T
cell activation→
calmodulin

P48643
TCPE_
HUMAN
T-complex
protein 1
subunit epsilon
CCT5
T-complex protein
1 subunit epsilon (PTHR11353:SF94)
Chaperonin (PC00072)

Protein folding
(GO:0008152);
protein complex
assembly (GO:0044238);
protein complex
biogenesis (GO:0019538)

Q9UKY7
CDV3_
HUMAN
Protein CDV3
homolog
CDV3
Protein CDV3 homolog (PTHR16284:SF13)

P09497
CLCB_
HUMAN
Clathrin light
chain B
CLTB
Clathrin light
chain B (PTHR10639:SF2)
Vesicle coat
protein (PC00150)

Intracellular protein
transport (GO:0051179);
receptor-mediated
endocytosis (GO:0006810)
Vesicle coat (GO:0032991);
cytoplasm (GO:0043234)
Heterotrimeric
G-protein signaling
pathway-Gq alpha and
Go alpha-mediated
pathway→clathrin;
heterotrimeric
G-protein signaling
pathway-Gi alpha and
Gs alpha-mediated
pathway→clathrin;
Huntington
disease→clathrin

P20674
COX5A_
HUMAN
Cytochrome C
oxidase subunit
5A, mitochondrial
COX5A
Cytochrome C
oxidase subunit 5A,
mitochondrial
(PTHR14200:SF11)
Oxidase(PC00176)
Oxidoreductase
activity (GO:0003824)
Oxidative phosphorylation
(GO:0008152); respiratory
electron transport
chain (GO:0006091)

P07108
ACBP_
HUMAN
Acyl-CoA-binding
protein
DBI
Acyl-CoA-binding
protein
(PTHR23310:SF54)
Transfer/carrier
protein (PC00219);
enzyme modulator
(PC00095)
Catalytic activity
(GO:0003824);
protein binding (GO:0005488);
enzyme inhibitor
activity (GO:0005515)
Lipid metabolic
process (GO:0008152);
lipid transport
(GO:0044238); regulation
of catalytic activity
(GO:0006629)

Q15075
EEA1_
HUMAN
Early endosome
antigen 1
EEA1
Early endosome
antigen 1
(PTHR23164:SF6)

Q92538
GBF1_
HUMAN
Golgi-specific
brefeldin
A-resistance
guanine nucleotide
exchange factor 1
GBF1
Golgi-specific brefeldin
A-resistance guanine
nucleotide exchange
factor 1
(PTHR10663:SF138)
Signaling molecule
(PC00207);
guanyl-nucleotide
exchange factor
(PC00095); cytoskeletal
protein (PC00022)
GTPase activity
(GO:0003824);
pyrophosphatase
activity (GO:0016787);
nucleotide binding
(GO:0003924); small
GTPase regulator
activity (GO:0016462);
guanyl-nucleotide
exchange factor
activity (GO:0005488)
Phosphate-containing
compound metabolic
process (GO:0008152);
nitrogen compound
metabolic process
(GO:0006796); catabolic
process (GO:0006807);
nucleobase-containing
compound metabolic
process (GO:0009056);
cellular process
(GO:0044238); transport
(GO:0006139); regulation
of biological process
(GO:0009987); regulation
of catalytic activity
(GO:0051179)
Organelle (GO:0043226);
intracellular(GO:0044464)

P78417
GSTO1_
HUMAN
Glutathione
S-transferase
omega-1
GSTO1
Glutathione
S-transferase omega-1 (PTHR11260:SF323)
Transferase (PC00220);
signaling molecule
(PC00207); reductase
(PC00176); translation
elongation factor
(PC00198); epimerase/
racemase (PC00171);
cytoskeletal protein
(PC00031)
Oxidoreductase
activity (GO:0003824);
transferase activity
(GO:0016491);
racemase and
epimerase activity
(GO:0016740);
structural constituent
of cytoskeleton
(GO:0016853); translation
elongation factor
activity (GO:0016854);
translation elongation
factor activity
(GO:0005198); receptor
binding (GO:0005200);
translation elongation
factor activity
(GO:0005488)
Immune system
process (GO:0002376);
translation (GO:0008152);
cell communication
(GO:0044238); response
to toxic substance
(GO:0019538); regulation
of translation (GO:0006412)
Cytoskeleton (GO:0043226);
intracellular (GO:0005856)

P09211
GSTP1_
HUMAN
Glutathione
S-transferase P
GSTP1
Glutathione S-transferase P
(PTHR11571:SF141)

P51858
HDGF_
HUMAN
Hepatoma-derived
growth factor
HDGF
Hepatoma-derived
growth factor (PTHR12550:SF41)
Transcription
cofactor (PC00218);
growth factor (PC00217)
Transcription
cofactor activity
(GO:0000988);
sequence-specific
DNA-binding
transcription factor
activity (GO:0000989); sequence-specific
DNA-binding
transcription factor
activity (GO:0003712);
growth factor
activity (GO:0001071)
Immune system
process (GO:0002376);
transcription from
RNA polymerase II
promoter (GO:0008152);
cell-cell signaling (GO:0044238); regulation
of transcription from
RNA polymerase II
promoter (GO:0006139)

O60814
H2B1K_
HUMAN
Histone H2B
type 1-K
HIST1H2BK
Histone H2B type 1-K
(PTHR23428:SF23)
Histone (PC00171)
Nucleic acid
binding
(GO:0005488)
Nitrogen compound
metabolic process
(GO:0008152);
DNA metabolic
process (GO:0006807);
cellular process
(GO:0044238); chromatin
organization (GO:0006139);
chromatin assembly
(GO:0006259); cellular
component biogenesis
(GO:0009987)
Protein DNA complex
(GO:0032991); nucleus
(GO:0032993);
nuclear chromosome
(GO:0043226); intracellular
(GO:0005634)

P17096
HMGA1_
HUMAN
High mobility
group protein
HMG-I/HMG-Y
HMGA1
High mobility group
protein HMG-I/HMG-Y
(PTHR23341:SF1)
DNA-binding
protein (PC00171)
Nucleic acid-binding
transcription factor
activity (GO:0001071);
lyase activity
(GO:0003824); DNA
binding (GO:0016829)
Nitrogen compound
metabolic process
(GO:0008152);
biosynthetic process
(GO:0006807); DNA repair
(GO:0009058); transcription,
DNA-dependent (GO:0044238); cellular
process (GO:0006139);
response to stress
(GO:0006259); regulation
of nucleobase-containing
compound metabolic
process (GO:0006281)
Organelle (GO:0043226);
intracellular (GO:0044464)

P52926
HMGA2_
HUMAN
High mobility
group protein
HMGI-C
HMGA2
High mobility group
protein HMGI-C
(PTHR23341:SF4)
DNA-binding
protein (PC00171)
Nucleic acid-binding
transcription factor
activity (GO:0001071);
lyase activity (GO:0003824);
DNA binding (GO:0016829)
Nitrogen compound
metabolic process
(GO:0008152); biosynthetic
process (GO:0006807);
DNA repair (GO:0009058);
transcription,
DNA-dependent (GO:0044238); cellular
process (GO:0006139);
response to stress
(GO:0006259); regulation
of nucleobase-containing
compound metabolic
process 2(GO:0006281)
Organelle (GO:0043226);
intracellular (GO:0044464)

P09429
HMGB1_
HUMAN
High mobility
group
protein B1
HMGB1
High mobility group
protein B1-related
(PTHR13711:SF164)
HMG box transcription
factor (PC00218);
signaling molecule
(PC00024); chromatin/
chromatin-binding
protein (PC00207)

p53 pathway→high
mobility group
protein 1

P05114
HMGN1_
HUMAN
Nonhistone
chromosomal
protein HMG-14
HMGN1
Nonhistone
chromosomal protein HMG-14 (PTHR23087:SF12)
Chromatin/
chromatin-
binding protein (PC00171)
Nucleic acid
binding (GO:0005488);
chromatin binding
(GO:0003676)
DNA replication
(GO:0008152); transcription
from RNA polymerase
II promoter (GO:0044238);
cell cycle (GO:0006139)

P05204
HMGN2_
HUMAN
Nonhistone
chromosomal
protein HMG-17
HMGN2
Nonhistone
chromosomal
protein HMG-17 (PTHR23087:SF13)
Chromatin/chromatin-
binding protein (PC00171)
Nucleic acid binding (GO:0005488);
chromatin binding
(GO:0003676)
DNA replication
(GO:0008152);
transcription from RNA
polymerase II promoter
(GO:0044238); cell
cycle (GO:0006139)

P61604
CH10_
HUMAN
10 kDa heat
shock protein,
mitochondrial
HSPE1
10 kDa heat shock
protein, mitochondrial
(PTHR10772:SF16)
Chaperonin (PC00072)

Protein metabolic
process (GO:0008152)

P50213
IDH3A_
HUMAN
Isocitrate
dehydrogenase
[NAD]
subunit alpha,
mitochondrial
IDH3A
Isocitrate dehydrogenase
[NAD] subunit alpha,
mitochondrial
(PTHR11835:SF34)
Dehydrogenase
(PC00176)
Oxidoreductase
activity (GO:0003824)
Generation of precursor
metabolites and
energy (GO:0008152);
carbohydrate metabolic
process (GO:0006091);
tricarboxylic acid
cycle (GO:0044238)

Ascorbate
degradation→
L-xylulose-5-phosphate-
3-epimerase; leucine
biosynthesis→
3-isopropylmalate
dehydrogenase

P01861
IGHG4_
HUMAN
Ig gamma-4
chain C region
IGHG4
IG gamma-1 chain c
region-related
(PTHR23266:SF83)

Q9GZP8
IMUP_
HUMAN
Immortalization
upregulated
protein
IMUP
Immortalization
upregulated protein
(PTHR21830:SF0)

P04732
MT1E_
HUMAN
Metallothionein-1E
MT1E
Metallothionein-1E (PTHR23299:SF2)

P13640
MT1G_
HUMAN,
MT1X_
HUMAN,
MT2_
HUMAN
Metallothionein-1G,
metallothionein-1X, metallothionein-2
MT1G
Metallothionein-1G (PTHR23299:SF3)

P35749
MYH11_
HUMAN
Myosin-11
MYH11
Myosin-11
(PTHR13140:SF335)
G-protein modulator
(PC00095);
actin-binding
motor protein (PC00022); cell
junction protein
(PC00085)
Motor activity
(GO:0003824); structural
constituent of cytoskeleton (GO:0016787); protein
binding (GO:0016462);
enzyme regulator
activity (GO:0003774)
Metabolic process
(GO:0008152);
cytokinesis (GO:0009987);
cellular component
movement (GO:0000910);
mitosis (GO:0006928);
cell communication
(GO:0007049); muscle
contraction (GO:0007067);
sensory perception
of sound (GO:0007154);
sensory perception (GO:0032501);
mesoderm development
(GO:0044707); anatomical
structure morphogenesis
(GO:0003008); muscle organ
development (GO:0006936);
intracellular protein
transport (GO:0007605);
vesicle-mediated transport (GO:0050877); regulation
of catalytic activity
(GO:0007600); cellular
component organization
(GO:0032502)
Plasma membrane
(GO:0016020); actin
cytoskeleton
(GO:0005886); intracellular
(GO:0043226)
Inflammation mediated
by chemokine and
cytokine signaling
pathway→myosin;
nicotinic acetylcholine
receptor signaling
pathway→myosin;
cytoskeletal regulation
by Rho
GTPase→myosin
light chain

P20929
NEBU_
HUMAN
Nebulin
NEB
Nebulin (PTHR11039:SF37)

Q13442
HAP28_
HUMAN
28 kDa heat-
and acid-stable
phosphoprotein
PDAP1
28 kDa heat- and
acid-stable
phosphoprotein
(PTHR22055:SF0)

P13667
PDIA4_
HUMAN
Protein disulfide-
isomerase A4
PDIA4
Protein
disulfide-isomerase A4 (PTHR18929:SF110)

Isomerase activity
(GO:0003824)
Protein folding (GO:0008152);
cellular process (GO:0044238);
response to stress
(GO:0019538)
Organelle (GO:0043226);
cytoplasm (GO:0044464)

Q9UHV9
PFD2_
HUMAN
Prefoldin subunit 2
PFDN2
PREFOLDIN
SUBUNIT 2
(PTHR13303:SF0)
Chaperone (PC00072)

protein folding
(GO:0008152)

O15212
PFD6_
HUMAN
Prefoldin subunit 6
PFDN6
Prefoldin subunit 6 (PTHR21431:SF0)

Protein binding
(GO:0005488)
Protein complex
assembly (GO:0008152);
cellular process
(GO:0044238); cellular
component organization
(GO:0019538); protein
complex biogenesis
(GO:0006461)
Protein complex
(GO:0032991); cytosol
(GO:0043234)

Q01813
PFKAP_
HUMAN
ATP-dependent
6-phosphofructoki
nase, platelet type
PFKP
6-Phosphofructokinase
type C
(PTHR13697:SF5)
Carbohydrate kinase
(PC00220); carbohydrate
kinase (PC00137)
Carbohydrate kinase
activity (GO:0003824)
Glycolysis (GO:0008152);
glycolysis (GO:0006091)

P13797
PLST_
HUMAN
Plastin-3
PLS3
Plastin-3 (PTHR19961:SF32)
Nonmotor actin-binding protein (PC00085)
Structural constituent of
cytoskeleton (GO:0005198);
actin binding (GO:0005200)
Cellular process
(GO:0009987); cellular
component morphogenesis
(GO:0032502); cellular
component organization
(GO:0009653)
Actin cytoskeleton
(GO:0043226); intracellular
(GO:0005856)

O75334
LIPA2_
HUMAN
Liprin-alpha-2
PPFIA2
Liprin-alpha-2 (PTHR12587:SF6)

Cellular process
(GO:0009987);
cell adhesion (GO:0022610);
ectoderm development
(GO:0007155); nervous
system development
(GO:0032502)

P30048
PRDX3_
HUMAN
Thioredoxin-
dependent
peroxide
reductase, mitochondrial
PRDX3
Thioredoxin-dependent
peroxide reductase,
mitochondrial
(PTHR10681:SF22)
Peroxidase (PC00176)
Oxidoreductase activity
(GO:0003824); peroxidase
activity (GO:0016491)
Metabolic process
(GO:0008152)

P49721
PSB2_
HUMAN
Proteasome
subunit beta
type-2
PSMB2
Proteasome subunit
beta type-2 (PTHR11599:SF6)

Q13200
PSMD2_
HUMAN
26S proteasome
non-ATPase
regulatory
subunit 2
PSMD2
26S proteasome
non-ATPase regulatory
subunit 2 (PTHR10943:SF1)
Enzyme modulator (PC00095)
Catalytic activity
(GO:0003824); protein
binding (GO:0005488); enzyme regulator
activity (GO:0005515)
Proteolysis (GO:0008152);
cell cycle (GO:0044238);
regulation of catalytic
activity (GO:0019538)

Ubiquitin proteasome
pathway→26S
proteasome;

O00233
PSMD9_
HUMAN
26S proteasome
non-ATPase
regulatory
subunit 9
PSMD9
26S proteasome
non-ATPase regulatory
subunit 9 (PTHR12651:SF1)
Enzyme modulator (PC00095)

Protein complex
assembly (GO:0008152);
cellular component
organization (GO:0044238);
protein complex
biogenesis (GO:0019538)
Protein complex
(GO:0032991); organelle
(GO:0043234); intracellular
(GO:0043226)
Ubiquitin proteasome
pathway→26S
proteasome;

P06454
PTMA_
HUMAN
Prothymosin
alpha [cleaved
into:
prothymosin
alpha,
N-terminally
processed;
thymosin
alpha-1]
PTMA
Prothymosin alpha (PTHR22745:SF0)

Nucleobase-containing
compound metabolic
process (GO:0008152)

P20962
PTMS_
HUMAN
Parathymosin
PTMS
Parathymosin
(PTHR22745:SF3)

Nucleobase-containing
compound metabolic
process (GO:0008152)

P26373
RL13_
HUMAN
60S ribosomal
protein L13
RPL13
60S ribosomal protein
L13 (PTHR11722:SF0)
Ribosomal protein (PC00171)
Structural constituent
of ribosome (GO:0005198);
nucleic acid binding
(GO:0003735)
Translation (GO:0008152)

P62277
RS13_
HUMAN
40S ribosomal
protein S13
RPS13
40S ribosomal protein S13
(PTHR11885:SF6)
Ribosomal protein (PC00171)
Structural constituent of ribosome (GO:0005198);
nucleic acid binding
(GO:0003735)
Protein metabolic
process (GO:0008152)

P62857
RS28_
HUMAN
40S ribosomal
protein S28
RPS28
40S ribosomal
protein S28 (PTHR10769:SF4)
Ribosomal protein (PC00171)
Structural molecule
activity (GO:0005198)
Cellular process
(GO:0009987);
RNA localization
(GO:0051179);
nucleobase-containing
compound transport
(GO:0006403); nuclear
transport (GO:0006810);
cellular component
biogenesis (GO:0015931)
Ribosome (GO:0032991);
organelle (GO:0030529);
cytosol (GO:0005840)

Q8NC51
PAIRB_
HUMAN
Plasminogen
activator inhibitor
1 RNA-binding
protein
SERBP1
Plasminogen
activator inhibitor 1
RNA-binding protein (PTHR12299:SF29)
RNA-binding protein (PC00171)
RNA binding
(GO:0005488)
Primary metabolic
process (GO:0008152)

Q9H299
SH3L3_
HUMAN
SH3 domain-
binding glutamic
acid-rich-like
protein 3
SH3BGRL3
SH3 domain-binding
glutamic acid-rich-like
protein 3
(PTHR12232:SF3)

P11166
GTR1_
HUMAN
Solute carrier
family 2, facilitated
glucose transporter
member 1
SLC2A1
Solute carrier family 2,
facilitated glucose
transporter member 1
(PTHR23503:SF51)

Gonadotropin releasing
hormone receptor
pathway→Glut1;
gonadotropin releasing
hormone receptor
pathway→Glut1;
gonadotropin releasing
hormone receptor
pathway→Glut1

P22528
SPR1B_
HUMAN
Cornifin-B
SPRR1B
Cornifin-B
(PTHR23263:SF47)

Q9Y6N5
SQRD_
HUMAN
Sulfide:quinone
oxidoreductase,
mitochondrial
SQRDL
Sulfide:quinone
oxidoreductase,
mitochondrial
(PTHR10632:SF2)

Q16629
SRSF7_
HUMAN
Serine/arginine-
rich splicing
factor 7
SRSF7

P16949
STMN1_
HUMAN
Stathmin
STMN1
Stathmin
(PTHR10104:SF5)

Cytoskeletal protein
binding (GO:0005488)
Cellular process
(GO:0009987);
single-multicellular
organism process
(GO:0032501); cell
differentiation (GO:0044707);
nervous system
development (GO:0032502);
regulation of biological
process (GO:0030154);
cytoskeleton organization
(GO:0048731)
Intracellular (GO:0044464);
cell projection (GO:0005622)
Cytoskeletal regulation
by Rho
GTPase→stathmin

P61956
SUMO2_
HUMAN
Small
ubiquitin-related
modifier 2
SUMO2
Small ubiquitin-related
modifier 2-related
(PTHR10562:SF11)

Cellular protein
modification process
(GO:0008152); cell cycle
(GO:0044238)

P63313
TYB10_
HUMAN
Thymosin beta-10
TMSB10
Thymosin beta-10
(PTHR12021:SF10)

P62328
TYB4_
HUMAN
Thymosin beta-4
TMSB4X
Thymosin beta-4
(PTHR12021:SF13)

P67936
TPM4_
HUMAN
Tropomyosin
alpha-4 chain
TPM4
Tropomyosin
alpha-4 chain
(PTHR19269:SF40)
Actin-binding motor protein (PC00085)
Motor activity
(GO:0003824);
structural constituent
of cytoskeleton
(GO:0016787)
Metabolic process
(GO:0008152); cellular
component movement
(GO:0009987); muscle
contraction (GO:0006928);
ectoderm development
(GO:0032501); mesoderm
development (GO:0044707);
cellular component
morphogenesis (GO:0003008);
nervous system development
(GO:0006936); muscle organ
development (GO:0032502);
cellular component
organization (GO:0007398)
Actin cytoskeleton
(GO:0043226); intracellular
(GO:0005856)

Q9C030
TRIM6_
HUMAN
Tripartite
motif-containing
protein 6
TRIM6
Tripartite
motif-containing
protein 6
(PTHR24103:SF348)

Q13509
TBB3_
HUMAN
Tubulin beta-3
chain
TUBB3
Tubulin beta-3 chain (PTHR11588:SF43)
Tubulin (PC00085)
Structural constituent
of cytoskeleton
(GO:0005198)
Cell cycle (GO:0009987);
anatomical structure
morphogenesis (GO:0007049);
intracellular protein
transport (GO:0032502)
Protein complex
(GO:0032991); intracellular
(GO:0043234)
Huntington
disease→beta-tubulin; Huntington
disease→microtubule;
cytoskeletal regulation
by Rho GTPase→tubulin

O75152
ZC11A_
HUMAN
Zinc finger
CCCH domain-
containing
protein 11A
ZC3H11A
Zinc finger CCCH
domain-containing
protein 11A
(PTHR15725:SF2)
Nucleic acid binding (PC00171)
Nucleic
acid binding
(GO:0005488)

(a)

(b)

Figure 1: Functional distribution of the 58 proteins identified as dysregulated with aging according to biological processes (a) and PANTHER protein class (b) categories. Assignments were made with PANTHER tool. The numbers in brackets correspond to the percentage of identified proteins classified in the category. If a protein is classified into 2 ontology terms that are not parent or child to each other, it counts in the 2 classes.

Pathway enrichment analysis was performed using PathVisio [23], and the top enriched pathways are listed in Table 4. Metal homeostasis is in the top enriched pathways, as well as histone modifications, DNA replication, oxidative stress, and electron transport chain pathways.

Table 4: List of top enriched pathways provided after overrepresentation analysis with PathVisio. Positive (r) is the number of genes in the pathway meeting the criterion. Measured (n) is the number of genes in the pathway measured in the experiment. Total is the total number of elements in the pathway. Z-score is the score calculated for overrepresentation analysis. Pathways with a high Z-score have more significantly up- or downregulated genes than expected.

Pathway
Positive (r)
Measured (n)
Total
%
Z-score
value (permuted)

Zinc homeostasis
4
4
39
100.00%
3.30
0.000

Copper homeostasis
5
6
58
83.33%
3.13
0.000

Arachidonate epoxygenase/epoxide hydrolase
2
2
17
100.00%
2.33
0.001

DNA replication
2
2
50
100.00%
2.33
0.009

Retinoblastoma (RB) in cancer
2
2
98
100.00%
2.33
0.012

Histone modifications
11
25
69
44.00%
1.98
0.027

Aryl hydrocarbon receptor
1
1
51
100.00%
1.65
0.048

Cardiac hypertrophic response
1
1
60
100.00%
1.65
0.063

Constitutive androstane receptor pathway
1
1
34
100.00%
1.65
0.029

Dual hijack model of Vif in HIV infection
1
1
9
100.00%
1.65
0.007

Endochondral ossification
1
1
69
100.00%
1.65
0.072

Endothelin pathways
1
1
47
100.00%
1.65
0.047

Gastric cancer network 1
1
1
32
100.00%
1.65
0.027

Melatonin metabolism and effects
1
1
55
100.00%
1.65
0.057

NOTCH1 regulation of human endothelial cell calcification
1
1
18
100.00%
1.65
0.014

Notch signaling pathway
1
1
62
100.00%
1.65
0.058

RalA downstream regulated genes
1
1
13
100.00%
1.65
0.015

T-cell receptor and costimulatory signaling
1
1
45
100.00%
1.65
0.050

TarBasePathway
1
1
19
100.00%
1.65
0.019

Type II interferon signaling (IFNG)
1
1
38
100.00%
1.65
0.043

Metapathway biotransformation
2
3
189
66.67%
1.55
0.120

Cytoplasmic ribosomal proteins
13
34
89
38.24%
1.54
0.121

Circadian rythm-related genes
5
11
210
45.45%
1.40
0.146

Apoptosis modulation and signaling
3
6
97
50.00%
1.28
0.190

Alzheimers disease
4
9
163
44.44%
1.19
0.259

Electron transport chain
4
9
118
44.44%
1.19
0.252

Oxidative stress
2
4
32
50.00%
1.04
0.232

Preimplantation embryo
2
4
60
50.00%
1.04
0.299

Vitamin B12 metabolism
2
4
118
50.00%
1.04
0.337

TNF alpha signaling pathway
3
7
97
42.86%
0.95
0.340

3.3. Western Blot Analysis of Tubulin Beta-3 Chain, a Promising Candidate Protein Biomarker of Aging

In proteomic quantitation analysis, tubulin beta-3 chain was evidenced as a promising candidate protein biomarker of aging. Indeed, tubulin beta-3 chain was upregulated in elderly donors with an iTRAQ ratio of protein expression level of 2.66 (elderly versus young) and significant values ( value ratio of 4.21 × 10⁻⁴ and a value sample of 4.87 × 10⁻⁷). Thus, tubulin beta-3 chain was further analyzed by western blot on human primary keratinocyte cells from the same donors but also from at least fourteen other donors in order to exclude the interindividual variability and to figure out whether or not these proteins were dysregulated in other donors. For this western blot analysis, total protein quantification was used as a control of gel loading and relative intensity of the specific antibodies on the membrane versus the amount of protein loaded on the gel was calculated and represented on box-plot diagram. Representative western blot images and results of quantification are shown in Figure 2. The trend of dysregulation of tubulin beta-3 chain was confirmed, and a similar ratio was obtained by western blot quantification and with our proteomic workflow. Moreover, receiver operating characteristic curve (ROC curve) confirmed the specificity and the sensitivity of tubulin beta-3 chain expression level for determination of age status with an area under the ROC curve of 0.9048 and a value of 0.0152.

(a)

(b)

(c)

Figure 2: (a) Western blot analysis of protein extract from young and elderly keratinocytes with tubulin beta-3 chain. (b) Box plots of relative protein expression of tubulin beta-3 chain in young and elderly donors (based on western blot data by considering the relative intensity of the specific antibodies on the membrane versus the amount of protein loaded on the gel for young and elderly donors, significant value < 0.05 ( value 0.0152)). (c) Receiver operating characteristic curve (ROC curve) with an AUC of 0.9048.

4. Discussion

Skin aging is a complex process with multifactorial origins that can decipher using new technological approach such as global quantitative proteomics. We carried out an iTRAQ-MALDI-TOF/TOF MS and MS/MS analysis to identify and quantify changes in human primary keratinocyte proteomes from young and elderly donors. 517 proteins were identified including proteins found mainly in keratinocytes such as cornifin-B and keratin-2E which are associated with keratinocyte activation, proliferation, and keratinization [25]. After applying robust statistical analysis, 58 proteins were found significantly differentially expressed depending on age status with 40 that were downregulated and 18 upregulated with aging.

Comparison of our results with previous gene and protein expression studies of skin aging shows some similarities. We found that more proteins are downregulated (40) than upregulated (18) with aging which is consistent with the previous results from a gene expression study in women [8]. The majority of proteins which expression is affected by age are nucleic acid-binding proteins (25%), cytoskeletal proteins (13%), and enzyme modulators (12%). These proteins are mostly involved in metabolism (30%) or cellular process (21%) such as cell cycle and cell signaling pathways. Similar results have been observed in a previous transcriptomic study [7]. Pathway enrichment analysis reveals metal (zinc and copper) homeostasis as one of the most enriched pathways which is consistent with the observed dysregulation of several metallothionein proteins that bind diverse types of metal and also participated in oxidative stress response [26]. Oxidative stress and electron transport chain pathways are also in the enriched pathways’ list, and this is consistent with the increase of reactive oxygen species (ROS) production with aging [3].

In this work, tubulin beta-3 chain expression is upregulated with aging in our proteomic experiment and also in western blot analyses on samples from several donors. Statistical analysis of these data has shown that tubulin beta-3 chain may discriminate age status. Tubulin beta-3 chain is a component of the microtubules that are complex polymers composed of tandem repeats of α- and β-tubulin heterodimers. In humans, six β-tubulin isoforms have been described and the isoform composition of the microtubule is determining its behavior. For example, it has been shown that in vitro purified microtubules enriched in tubulin beta-3 chain are more dynamic compared to microtubules containing other β-tubulin isoforms [27]. Tubulin beta-3 chain mutations have been linked in humans to different types of neurological disorders with abnormal axon guidance [28, 29]. Tubulin beta-3 was also reported as a biomarker for melanocyte lineage and as involved in melanocyte differentiation and melanogenesis [30], and it has been shown that tubulin beta-3 expression is decreased in senescent melanocytes [31]. Locher et al. [30] also reported that tubulin beta-3 may play a substantial role in melanosome transport which is regulated by proteins (such as kinesin and dynein) using microtubule tracks. Moreover, melanosomes may be transferred from melanocytes to keratinocytes through the shedding vesicle system [32], but the cellular process is still unclear and no data was reported concerning ageing aspects. Interestingly, tubulin beta-3 was identified as a direct downstream protein of human melanocortin 1 receptor (MC1R) [33], a protein associated to skin pigmentation, ultraviolet radiation, and to other aspects such as skin cancers [34]. High level of tubulin beta-3 chain has been linked to resistance to antitubulin agents such as taxanes and vinorelbine and lower overall survival in nonsmall cell lung cancer (NSCLC) [35–37] and prostate tumor patients [38]. But the prognostic value of tubulin beta-3 chain is still debated in cutaneous malignant melanoma prognosis [39]. The high expression of tubulin beta-3 chain in NSCLC has been shown to be regulated by ras, PI3/akt, and MAP kinase-ERK signaling [40]. Tubulin beta-3 chain has also been described to be a prognostic marker for bladder urothelial carcinoma with patients showing a higher level of tubulin beta-3 chain presenting a shorter disease-free survival [41]. To date, no publication reported tubulin beta-3 chain protein as a candidate biomarker for aging and there is no known mechanism of tubulin beta-3 chain dysregulation in skin aging. But it is interesting to notice that alterations of the cytoskeleton have been reported with aging [7] and that mutations in lamin genes (type V intermediate filaments) are responsible for some premature aging diseases such as the Hutchinson-Gilford progeria syndrome (HGPS) [42].

In our study, we identified other dysregulated proteins such as peroxiredoxin 3, 6-phosphofructokinase, platelet type, and cornifin-B. Thioredoxin-dependent peroxide reductase, mitochondrial, also known as peroxiredoxin 3 (PrxIII), a mitochondrial member of the antioxidant family of thioredoxin (Trx) peroxidases, was found upregulated with aging in our study. Two other family members, peroxiredoxins 1 and 2, were also upregulated in a previous report [14]. Peroxiredoxins are important cellular antioxidant; indeed, they act as hydrogen peroxide and organic hydroperoxide scavengers [43]. It is well established that with age, there is an increase in reactive oxygen species (ROS) production and a decrease in antioxidant activity both contributing to chronological aging [3]. In oxidative stress conditions, PrxIII undergoes overoxidation and subsequent irreversible inactivation. And it has been shown that in rats, this modified PrxIII form accumulates with aging [44]. In our analysis, we did not identify the peptide containing the cysteine that is overoxidized to sulfonic acid and we then cannot discriminate between the two forms, explaining why, in consequence, we observed a global upregulation of the protein. Concerning 6-phosphofructokinase, platelet type (ATP-PFK) which is upregulated with aging in our study, this enzyme catalyzes the phosphorylation of D-fructose 6-phosphate to fructose 1,6-bisphosphate by ATP, the first committing step of glycolysis. It has been shown that human primary keratinocytes derived from elderly donors showed higher glucose uptake and increased lactate production, which are the indicators of a shift in metabolism towards increased glycolysis [45]. Thus, the observed upregulation of ATP-PFK is correlated with the increased glycolysis in primary keratinocytes. Interestingly, cornifin-B is a marker of keratinocyte differentiation [46] and two transcriptomic studies reported that cornifin-B was downregulated with aging using women epidermis [9] and skin biopsies [47]. Our study is in concordance with this view as our proteomic study showed a downregulation of cornifin-B expression with aging (iTRAQ ratio erlderly versus young of 0.405 with a value ratio of 2.54 × 10⁻² and a value sample of 3.18 × 10⁻⁶).

Comparing our results with other studies aimed at identifying biomarkers of skin aging shows some differences that may be explained by different type/origin of skin samples, gender, difference in sample processing all along the workflow, and the variable correlation between mRNA and protein expression levels [48]. But using different and complementary approaches is interesting as it can lead to the identification of even more candidate biomarkers than with a single method. Also, considering the occurrence of oxidative stress during aging and the subsequent induced altered posttranslational modifications (PTMs) of proteins such as carbonylation, 3-nitrityrosilation, emphasis must be placed on the study of PTMs with aging in future proteomic experiment concerning skin aging [49].

5. Conclusions

Defining the differential protein signature with aging even if these changes could be initiating adaptive or compensatory events is crucial to further increase our knowledge of skin aging. Our aim was to identify some biomarker candidates for skin aging from human primary keratinocyte culture. 58 proteins were dysregulated with aging, and from this, tubulin beta-3 chain was also observed dysregulated in western blot analysis of keratinocyte extracts isolated from multiple donors. Statistical analysis has confirmed especially that an increase in tubulin beta-3 chain is associated with aging. Further studies will be needed in order to evaluate the effect of this change of expression on the complex process of aging.

This study brings a new effort to reach a better understanding of the biology of skin aging and to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Indeed, emerging diagnostic tools now require a combination of multiple biomarkers to achieve a better accuracy, and we propose that tubulin beta-3 chain could be one of these.

Conflicts of Interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

Acknowledgments

The authors would like to thank Valérie Cunin, Sylvie Michelland, and David Beal for providing their help and technical assistance and Friederike Ehrhart for the help with PathVisio.

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