SWATH-MS quantitative proteomic analysis of deer antler from two regenerating and mineralizing sections

biology Article SWATH-MS Quantitative Proteomic Analysis of Deer Antler from Two Regenerating and Mineralizing Sections María López-Pedrouso 1, JoséM. Lorenzo 2,3 , Tomás Landete-Castillejos 4, Louis Chonco 4, Francisco Javier Pérez-Barbería4, Andrés García4, María-Pilar López-Garrido 5and Daniel Franco 2,*   Citation: López-Pedrouso, M.; Lorenzo, J.M.; Landete-Castillejos, T.; Chonco, L.; Pérez-Barbería, F.J.; García, A.; López-Garrido, M.-P.; Franco, D. SWATH-MS Quantitative Proteomic Analysis of Deer Antler from Two Regenerating and Mineralizing Sections. Biology 2021, 10, 679. https://doi.org/10.3390/ biology10070679 Received: 20 June 2021 Accepted: 14 July 2021 Published: 17 July 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Department of Zoology, Genetics and Physical Anthropology, University of Santiago de Compostela, 15872 Santiago de Compostela, Spain; [email protected] 2Centro Tecnológico de la Carne de Galicia, Rúa Galicia Nº 4, Parque Tecnológico de Galicia, San Cibrao das Viñas, 32900 Ourense, Spain; jmlor[email protected] 3Área de Tecnología de los Alimentos, Facultad de Ciencias de Ourense, Universidad de Vigo, 32004 Ourense, Spain 4Instituto de Investigación en Recursos Cinegéticos (IREC) y Sec. Recursos Cinegéticos IDR, Universidad de Castilla-La Mancha (UCLM), 02071 Albacete, Spain; [email protected] (T.L.-C.); [email protected] (L.C.); fjavier[email protected] (F.J.P.-B.); [email protected] (A.G.) 5Laboratorio de Genética Médica, Instituto de Investigación en Discapacidades Neurológicas (IDINE), Facultad de Medicina, Universidad de Castilla-La Mancha (UCLM), 02071 Albacete, Spain; [email protected] *Correspondence: [email protected] Simple Summary: Deer antler is a unique and astonishing case of annual regeneration in mammalians. Several studies have pointed out the potential for use of velvet antler extract as a nutraceutical supplement, among others, because of its anti-cancer activity. The study of antler regeneration and growth allow us to identify the main proteins and regulatory pathways involved in cell differentiation and regeneration. For this purpose, two sections of antlers (tips and middle sections) using ribs as controls were analyzed from a proteomic point of view. A total of 259 proteins mainly associated with antioxidant mechanisms and Wnt signalling pathways could be responsible for deer antler regeneration and these proteins may be linked to human health benefits. Further studies should be focused on discovering which proteins from velvet antler extracts are associated with these beneficial effects. Abstract: Antlers are the only organ in the mammalian body that regenerates each year. They can reach growth rates of 1–3 cm/day in length and create more than 20 cm 2 /day of skin in the antler tips (their growth centers). Previous proteomic studies regarding antlers have focused on antler growth centers (tips) compared to the standard bone to detect the proteins involved in tissue growth. However, proteins of cell differentiation and regeneration will be more accurately detected considering more growing tissues. Thus, we set out to compare proteins expressed in antler tips (the highest metabolism rate and cell differentiation) vs. middle sections (moderate cell growth involving bone calcification), using ribs as controls. Samples were obtained in mid-June with antlers’ phenology corresponding to the middle of their growth period. Quantitative proteomic analysis identified 259 differentially abundant proteins mainly associated with antioxidant metabolic mechanisms, protein formation and Wnt signalling pathway, meanwhile, the mid antler section was linked to blood proteins. The high metabolic rate and subsequent risk of oxidative stress also seem to have resulted in strong antioxidant mechanisms. These results suggest that redox regulation of proteins is a key factor in the model of deer antler regeneration. Keywords: deer antlers; bone metabolism; oxidative stress; heat shock proteins; glutathione; mass spectrometry; gene ontology; bioinformatic analysis Biology 2021,10, 679. https://doi.org/10.3390/biology10070679 https://www.mdpi.com/journal/biology Biology 2021,10, 679 2 of 17 1. Introduction Deer antlers are bony cranial appendages which are renewed each year. In the case of red deer, the antlers grow in about 3.5 months in red deer [ 1 ]. They constitute the only case of full regeneration in mammalian organisms, and they show an enormous growth rate in the tips, growing up to 1–3 cm/day in length, and creating more than 20 cm 2 /day of skin [ 2 , 3 ]. Indeed, a recent study has shown that antlers have evolved a speed of growth faster than cancer based on the high expression of proto-oncogenes [ 4 ]. As a result, the study postulated that several tumor genes (e.g., TP53) could be suppressed to control the high risk of developing cancer. In this sense, several studies have found in vitro and in vivo anti-cancer effects of deer antler velvet extract in human tumors such as glioblastoma [ 5 ], prostate [ 6 , 7 ], colon [ 8 ] and breast [ 9 ]. Velvet antler has been used as traditional medicine for over 2000 years and it is recognized in the pharmacopoeias of China, Korea and Japan. Furthermore, it has been claimed as a nutraceutical supplement in New Zealand, the USA and Canada [ 10 ]. In this sense, it has been reported that polypeptides and proteins are the main bioactive components of the deer antler velvet [ 11 ], suggesting that the anti-cancer activity of velvet antler extract is mainly due to their proteins or peptides. Furthermore, the peptide extracts from the antler growth center have protective effects against oxidative stress. Thus, some studies found that differentially expressed proteins are involved in the regulation of several pathways such as oxidative phosphorylation, ribosome or extracellular matrix interaction [ 12 ], whereas others found a tetrapeptide (YNVK) that exhibited strong antioxidant activity [13]. Recently, proteomic analysis has been used to examine which proteins may be responsible for the fast growth and regenerative capacity of velvet antler [ 11 , 12 , 14 , 15 ]. The regenerative capacity of the antlers comes from the pedicle periosteum (PP) and the resident cells. Antler regeneration involves a process from dormant to potentiated active state due to stem cells [ 14 ]. Additionally, plasma membrane proteins are of key importance to different cellular processes. The proteome of plasma membrane proteins of stem cells in the PP compared to control cells from the skull (facial periosteal cells) showed differences in external stimuli, signal transduction, membrane transport, regulation of tissue regeneration and protein modification processes [ 16 ]. Similarly, a quantitative proteomic analysis of antlerogenic periosteal cells compared with the facial periosteal cells from yearling deer was performed. Overexpressed extracellular proteins in antlerogenic periosteal cells were found and these proteins are involved in cell proliferation, angiogenesis and neurogenesis. The comparison of extracellular and intracellular proteomes suggested secreted proteins that might regulate antler formation and regeneration, such as SFRP4 and LUM [ 11 ]. Beyond this, two different antler systems harvested from red deer and sika deer were analyzed. More abundant proteins were found in sika deer than red deer and these proteins are involved in oxidative phosphorylation, ribosome, extracellular matrix interaction and the PI3K-Akt pathway. For a better understanding, several antler sections with different growth rates should be compared. Thus, the proteomes in several sections of the antler assessed stem cells under different stages of activation [17]: dormant pedicle periosteum at the base of the antler, the antler growth center in the tip and mid sections of the antler beam periosteum. The authors found the greatest number of unique proteins (87) in the growth center of antler tips which could be associated with the activation of antler stem cells. Despite being a fast-growing tissue, studies about velvet antlers are rather scarce. Most proteomic and transcriptomic studies have examined the growth center (tip) compared with the antler base or even the bones of the skull. These studies compare two confounding factors: fast growth in the tip, but also a differentiating center, with antler base or skull bone which is not very active. This study aims to compare the proteome of two sections of the antler with different metabolism rates, using deer ribs as controls: the antler tip (growth center), which has a highest metabolism and differentiating tissue, and the middle section of the antler, which also has a high metabolism, but due to its intensely mineralizing section and differentiated bone. Biology 2021,10, 679 3 of 17 2. Materials and Methods 2.1. Sample Collection of the Deer Antler In this study, we examined deer antlers from wild individuals in a stage of growth phenotypically corresponding to the mid-growth period. Within each antler, we examined the proteome of the antler tip (growth center) as compared with that of the middle sections (corresponding to intensely mineralizing antler bone). As a control, we examined the ribs of the same individuals. We used samples from six adult males, selected from a larger group that were hunted to reduce population density (for game management purposes) in a deer private game state in Ciudad Real (Spain) according to existing legal regulations. The slaughter of the hunted animals was regulated by the Regional Hunting Law of Castilla la Mancha [ 18 ]. Of the animals hunted, the six selected had antlers in the phenotypical aspect of being in the middle of their growth period (approximately 60 days of growth), based on antler velvet grading of Deer Industry New Zealand (https://www.pggwrightson.co.nz/-/media/ Corporate/Documents/Velvet/Velvet-DINZ-Grading-Guidelines.pdf?la=en, accessed on 15 July 2021). Immediately after death, antlers were cut off using a mechanical saw and stored frozen at − 20 ◦ C. No blood or skin were removed because, depending on the protocol to extract the blood, different amounts could remain, increasing the variability of results. The antlers were sampled in two sections: (1) the tip (considered as the 2.5 cm top section of the main beam) and a section of 5 cm in the middle of the antler. The same process was conducted for middle sections of floating ribs of 5 cm. Each sample was lyophilized, homogenized by trituration in an ultracentrifuge mill (Retsch ZM-100) and the triturate was lyophilized again and stored in plastic containers at − 20 ◦ C for later analysis. 2.2. Protein Extraction and Tryptic Digestion The deer antler powder (50 mg) was dissolved in RIPA buffer (200 mmol/L Tris/HClpH 7.4, 130 mmol/L NaCl, 10%-v/v glycerol, 0.1%-v/v SDS, 1%-v/v Triton X-100, 10 mmol/L MgCl 2 ) and anti-proteases and anti-phosphatases (Sigma-Aldrich, St. Louis, MO, USA). A homogenization was prepared using TissueLyser II (Qiagen, Tokyo, Japan) and then centrifuged at 14,000 × g(4 ◦ C, 20 min). An RC-DC kit (Biorad Lab., Hercules, CA, USA) was employed to assess the protein concentration according to its instructions. A total amount of 100 µ g was loaded on 10% SDS-PAGE to concentrate the proteins in a gel single band. Thus, the band was excised into pieces and washed with Milli-Q water, followed by 50 mM ammonium bicarbonate in 50% methanol. The dehydration of gel material was carried out with a vacuum centrifuge. Afterwards, the protein sample was reduced by 10 mM DTT and 50 mM ammonium bicarbonate solution at 60 ◦ C for 30 min followed by the alkylation by 55 mM iodoacetamide and 50 mM ammonium bicarbonate solution at room temperature for 30 min in darkness. Finally, digestion by 20 ng/ µ L trypsin (Promega, Madison, WI, USA) in 20 mM ammonium bicarbonate incubating at 37 ◦ C was used on the final solution. The resulting peptides were dissolved in 0.1% formic acid and stored at −20 ◦C for later analysis. 2.3. Protein Identification and Reference Spectral Library Building A composite sample for the two groups was prepared to mix 4 µ g of protein from each sample. The resulting solution was then assessed by analysis by shotgun data-dependent acquisition (DDA) employing micro-LC system Ekspert nLC425 (Eksigen, Dublin, CA, USA) using a YCM-TriartC18 column (150 mm × 0.3 mm i.d., 12 nm pore size, 3 µ m particle size) (YMC CO., Kyoto, Japan). The solvents were: solvent A (water, 0.1% formic acid) and solvent B (ACN, 0.1% formic acid). The gradient consisted of 5–95% B for 30 min, 5 min at 90% B and finally other 5 min at 5% B for column equilibration, for a total time of 40 min using a flow rate of 5 µ L/min. The detection was carried out by a hybrid quadrupole-TOF mass spectrometer, model Triple TOF 6600 (SCIEX, Framingham, MA, USA) operating with a data-dependent acquisition system in positive ion mode. The working parameters were 250 ms survey scan from 400 to 1250 m/z followed by MS/MS experiments from 100 to 1500 Biology 2021,10, 679 4 of 17 m/z (25 ms acquisition time) for a total cycle time of 2.8 s. The fragmented precursors were added to the dynamic exclusion list for 15 s, any ion with charge +1 was excluded from the MS/MS analysis. The comparison of mass spectral data and databases was performed by ProteinPilot software v.5.0.1. (SCIEX, Framingham, MA, USA). The used database was the Uniprot Swiss-Prot database for Cervus elaphus hippelaphus (European red deer) using a false discovery rate (FDR) below 0.01 for peptides and proteins and a confidence score above 99%. 2.4. Protein Quantification by SWATH-MS SWATH-MS (sequential window acquisition of all theoretical mass spectra) acquisition was performed using the data-independent acquisition (DIA) method. Six samples of both groups of deer antler (tip and middle section) and six from ribs with two technical replicates were assessed. An amount of 4 µ g of protein was analyzed by LC under the above conditions. Regarding the MS/MS analysis, an acquisition time of 50 ms in a total cycle time of 6.3 s was performed. A cycle consisted of the acquisition of 65 scans per SWATH window of variable width (1 m/z overlap) covering the 400–1250 m/z mass range. The spectral alignment and targeted data extraction were performed by PeakView v.2.2. (SCIEX, Framingham, MA, USA) matching the reference spectral library. The DIA files considered were an extraction window of 5 min (a width of 30 ppm) using the settings: ten peptides/protein, seven fragments/peptide, excluded shared and modified peptides and FDR below 0.01. The final quantification was measured by adding the quantitative outputs from the peaks for fragments. Two comparisons were performed to identify differentially abundant proteins (DAPs) using paired Student’s t-test and considering only p-values above 0.05 and fold change of 1.5 as the cut-off: (1) A comparison between the tip and middle section of deer antler (fastest-growing section vs. mineralizing one) and; (2) middle section of the antler vs. ribs (fast mineralization vs. standard bone metabolism). To evaluate the relationship among the three locations, a factorial analysis of the common DAP (p< 0.05) in the three tissues was carried out. Principal component analysis (PCA) was used as the method for extraction, and it was performed on the correlation matrix. A varimax rotation was carried out to minimize the number of variables that influence each factor, and thus, to facilitate the interpretation and discussion of the results. A KMO value of 0.767 was obtained. XLSTAT 2018.5.52745 software (Addinsoft, NY, USA) was used. Gene Ontology (GO) and KEGG (Kyoto Encyclopaedia of Genes and Genomes) analyses of differentially abundant proteins were performed using the enrichment analysis tool, FunRich (Functional Enrichment analysis tool, http://www.funrich.org, accessed on 15 May 2021) [19]. 2.5. ELISA Procedure for IGF-1 and IFN-γDetermination Deer antler velvet powder (1 g) was weighed and soaked with 10 mL distilled water. The liquid mixture was incubated at 4 ◦ C overnight with continuous stirring and then centrifuged at 2700 × gfor 20 min. The supernatant was freeze-dried and dissolved into 2 mL phosphate buffered saline (PBS, Lonza BioWhittaker). Samples were frozen at −80 ◦C and to carry out any further assay, samples were thawed, passed through a 0.22 µ m filter (PES membrane, MERCKMILLIPORE, Molsheim, France) and centrifuged at 5600×g for 3 min. According to the manufacturer’s recommendations, deer IGF-1 ELISA kit (Catalog Number. CSBE12644, CUSABIO) and deer IFNγ (Catalog No: EK11988, SAB) were performed. 3. Results 3.1. Comparisons of Deer Proteomes Tip vs. Middle Antler, and Middle Antler vs. Ribs In this study, 259 proteins were identified and quantified by SWATH-MS from two comparisons: tip and middle sections of deer antler velvet (Table 1) and, the middle antler section and the ribs (Table 2). The antler proteins from the tip and middle section and those Biology 2021,10, 679 5 of 17 from ribs were analyzed by PCA. According to PCA results, there were two components explaining 65.06% of the total variance. The two principal components can distinguish between the two sections of deer antler and the ribs. The first principal component (PC1) explained the higher percentage of variance (41.75%). The second principal component (PC2) accounted for 23.31% of the total variability indicated differences between middle section and tip of antler samples. The PCA figure shows that tip samples are more clustered, showing greater homogeneity than those that belong to the middle section resulting in more dispersal from the center of the cluster (Figure 1). Table 1. List of differential abundant proteins (mean value ± standard error of mean) of the antler samples of red deer (Cervus elaphus) from a native Iberian population of the two locations (tip and middle), gene names and fold change (FC) between both locations. Items Protein Name Gene Names Middle Section Tip FC Mean ±SE Mean ±SE Hemoglobin subunit alpha HBA/SCN2A 2,563,475.0 ±869,235.6 155,785.3 ±39,216.0 16.46 Adult beta-globin 1 HBB 45,176,500.0 ±16,757,107.7 3,050,606.7 ±1,088,464.0 14.81 Adult beta-globin 2 HBB 13,515,916.7 ±4,092,463.0 1,083,311.7 ±331,202.8 12.48 Creatine kinase B-type CKB 311,250.0 ±37,004.7 40,426.8 ±3039.0 7.70 Alpha-2-macroglobulin (A2MG) A2M 316,528.3 ±77,031.0 52,790.2 ±5947.1 6.00 Inter-alpha-trypsin inhibitor heavy chain H1 ITIH1 165,838.3 ±53,177.3 30,431.5 ±1875.7 5.45 Amiloride-sensitive amine oxidase AOC1 39,327.2 ±6441.8 9712.9 ±1135.1 4.05 Carbonic anhydrase (CAH3) CA3 22,310.6 ±5010.6 5560.7 ±1178.0 4.01 Alkaline phosphatase (PPBN) ALPG 15,993.0 ±1618.5 4000.0 ±467.9 4.00 Inter-alpha-trypsin inhibitor heavy chain H2 ITIH2 87,390.0 ±17,580.9 24,580.3 ±2302.8 3.56 Peroxiredoxin-2 PRDX2 37,583.5 ±4204.3 11,079.8 ±510.7 3.39 Apolipoprotein A-II APOA2 60,995.7 ±16,710.0 18,302.5 ±1743.9 3.33 Alpha-amylase 1A AMY1A 22,315.3 ±4160.5 6740.0 ±955.1 3.31 Plasminogen (PLMN) PLG 37,045.7 ±9978.9 11,666.0 ±644.5 3.18 Glutathione S-transferase Mu 1 GSTM1 94,826.5 ±25,325.8 30,432.3 ±2409.7 3.12 Complement C3 C3 712,043.3 ±109,393.3 252,156.7 ±27,537.1 2.82 Afamin (AFAM) AFM 25,198.7 ±5103.3 9541.6 ±1423.6 2.64 Serpin 3-6 Serpin 378,931.7 ±87,373.6 145,784.2 ±24,405.9 2.60 Mimecan (MIME) OGN 55,036.5 ±9328.6 21,511.8 ±2205.4 2.56 Alpha-1B-glycoprotein A1BG 2,213,076.7 ±441,457.5 866,086.7 ±63,588.4 2.56 Fetuin-B (FETUB) Fetuin-B 56,124.7 ±8673.8 22,155.8 ±2673.3 2.53 Alpha-2-antiplasmin (A2AP) SERPINF2 24,572.3 ±4954.9 9877.7 ±579.0 2.49 Complement factor B (CFAB) CFB 90,554.5 ±16,717.9 36,896.7 ±2915.5 2.45 Heparin cofactor 2 (HEP2) SERPIND1 19,863.8 ±3310.1 8067.4 ±843.7 2.46 Retinol-binding protein 4 (RET4) RBP4 20,127.3 ±4240.2 8274.5 ±783.4 2.43 Annexin A2 ANXA2 52,405.0 ±7452.6 22,504.7 ±1287.2 2.33 Beta-N-acetylhexosaminidase HEXB 4104.9 ±607.5 1851.1 ±250.1 2.22 Lactotransferrin LTF 1444,530.0 ±231,686.6 659,118.3 ±34,072.7 2.19 Hemopexin (fragment) HPX 173,172.2 ±38,801.3 80,237.7 ±9734.1 2.16 Antithrombin-III (ANT3) SERPINC1 64,056.0 ±10,572.3 30,005.0 ±1717.2 2.13 40S ribosomal protein S27a (RS27A) RPS27A 78,794.3 ±10,336.1 38,137.8 ±4586.8 2.07 Apolipoprotein A-I APOA1 4,144,766.7 ±798,136.1 2,013,133.3 ±167,607.1 2.06 Alpha-1-acid glycoprotein 1 (A1AG1) ORM1 95,798.0 ±18,143.9 47,375.3 ±3783.3 2.02 Hemopexin (HEMO) HPX 346,240.0 ±72,507.6 172,841.7 ±15,826.5 2.00 Actin-depolymerizing factor GSN 78,246.3 ±13,025.7 39,946.8 ±1462.5 1.96 Serotransferrin (TRFE) TF 2,125,016.7 ±347,685.8 1,096,858.3 ±76,391.0 1.94 Adenosylhomocysteinase (SAHH) AHCY 9665.6 ±765.9 5004.9 ±1092.1 1.93 Lumican LUM 206,390.0 ±30,250.1 109,842.0 ±11,393.3 1.88 ATP synthase subunit beta (ATPB) ATP5F1B 163,660.0 ±11,615.0 87,713.2 ±3889.4 1.87 Cu/Zn superoxide dismutase (SODC) SOD1 69,312.8 ±7322.5 37,554.7 ±3418.6 1.85 Peroxiredoxin-6 PRDX6 88,053.3 ±12,976.1 47,894.5 ±2267.1 1.84 Cystatin-B (CSTB) Cystatin-B 26,072.0 ±4123.7 14,697.6 ±1446.9 1.77 Transaldolase (TALDO) TALDO1 12,790.6 ±1895.0 7283.0 ±1154.7 1.76 Plastin-3 PLS3 32,357.3 ±3587.1 18,817.3 ±869.4 1.72 Biology 2021,10, 679 6 of 17 Table 1. Cont. Items Protein Name Gene Names Middle Section Tip FC Mean ±SE Mean ±SE Pyruvate kinase (KPYM) PKM 171,291.7 ±19,236.7 264,250.0 ±9462.0 0.65 L-lactate dehydrogenase LDHB 100,577.0 ±9101.6 155,815.0 ±8110.5 0.65 Polyadenylate-binding protein (PABP2) PABPN1 5875.5 ±1150.7 9190.6 ±365.0 0.64 Chloride intracellular channel protein 1 CLIC1 9348.2 ±1694.4 14,520.7 ±453.0 0.64 Heat shock 70kDa protein 5 HSPA5 186,508.3 ±33,958.7 301,630.0 ±5751.1 0.62 Heterogeneous nuclear ribonucleoprotein MHNRNPM 10,044.3 ±1370.7 16,531.0 ±530.7 0.61 Eukaryotic translation initiation factor 5A (IF5A1) EIF5A 19,182.3 ±3339.0 32,350.0 ±3133.9 0.59 Aggrecan core protein (PGCA) ACAN 49,556.0 ±4794.4 85,088.7 ±5985.1 0.58 Glutathione S-transferase P GSTP1 24,142.5 ±2739.0 44,152.7 ±8435.2 0.55 Peptidylprolyl isomerase PPWD1 3916.0 ±800.8 7129.1 ±562.9 0.55 Proteasome endopeptidase complex/PSB PSMB 2137.7 ±470.8 3933.2 ±136.7 0.54 Olfactomedin-like protein 3 (OLFL3) OLFML3 9038.2 ±1023.4 17,887.7 ±2661.1 0.51 Putative ATP-dependent RNA helicase DHX57 3944.2 ±1136.7 7865.7 ±679.4 0.50 Protein disulfide-isomerase PDIA6 178,383.3 ±22,517.8 390,683.3 ±12,154.9 0.46 Calponin CNN2 3543.7 ±896.7 8039.1 ±1697.6 0.44 Septin-7 (SEPT7) SEPTIN7 3874.0 ±1053.9 9256.4 ±506.5 0.42 Thrombospondin-1 (TSP1) THBS1 8282.2 ±2059.1 20,655.8 ±2272.9 0.40 Heterogeneous nuclear ribonucleoprotein (HNRPK) HNRNPK 9548.3 ±1725.5 24,761.2 ±969.2 0.39 Collagen alpha-1(II) chain (CO2A1) COL2A1 26,222.3 ±7333.0 67,945.7 ±7406.7 0.39 Glucosidase 2 subunit beta (GLU2B) PRKCSH 2971.2 ±894.4 8639.6 ±737.5 0.34 Protein disulfide-isomerase (fragment) PDIA6 105,751.3 ±16,292.9 334,988.3 ±8084.2 0.32 Heterogeneous nuclear ribonucleoproteins C1/C2 HNRNPC 1700.7 ±405.7 6226.1 ±350.6 0.27 Hyaluronan and proteoglycan link protein 1 (HPLN1) HAPLN1 63,678.3 ±6588.1 235,995.0 ±14,162.8 0.27 Elongation factor 1-gamma (EF1G) EEF1G 6767.1 ±1803.8 25,447.8 ±1352.1 0.27 60S acidic ribosomal protein P1 (RLA1) RPLP1 3699.7 ±955.8 15,261.1 ±1570.3 0.24 60S acidic ribosomal protein P2 (RLA2) RPLP2 8009.4 ±1102.0 35,171.8 ±3258.9 0.23 Ribosome-associated molecular chaperone SSB1 SSB1 2193.3 ±778.7 10,186.9 ±346.4 0.22 Elongation factor 1-delta (EF1D) EEF1D 6809.5 ±1064.5 32,352.3 ±928.9 0.21 Protein disulfide-isomerase A4 PDIA4 15,204.7 ±2296.0 77,964.3 ±3747.7 0.20 Peptidyl-prolyl cis-trans isomerase (PIN4) PIN4 25,527.3 ±9262.3 132,480.8 ±21,660.1 0.19 Hsc70-interacting protein (F10A1) ST13 2395.8 ±725.3 14,398.3 ±804.9 0.17 Y-box-binding protein 1 (YBOX1) YBX1 1189.9 ±396.4 7032.0 ±683.7 0.17 60S acidic ribosomal protein P0 (RLA0) RPLP0 1920.2 ±265.3 12,717.7 ±779.5 0.15 Endoplasmin (ENPL) HSP90B1 27,822.7 ±4283.1 243,358.3 ±8040.5 0.11 Proteins overexpressed in middle section and tip of antler are indicated in the table by red and blue color, respectively. Table 2. List of differential abundant proteins (mean value ± standard error of mean) of the antler samples (middle section) of red deer (Cervus elaphus) from a native Iberian population compared to rib, gene names and fold change (FC) between both locations. Protein Name Gene Names Rib Middle Section Mean ±SE Mean ±SE FC Collagen alpha-2(I) chain (CO1Aa) COL1A2 23,664,457.4 ±4,097,670.2 481,201.8 ±110,505.6 49.17 Fatty acid-binding protein, adipocyte FABP4 477,239.0 ±58,119.2 40,306.7 ±5080.5 11.84 40S ribosomal protein S12 29,511.2 ±7966.9 2719.0 ±682.7 10.85 Keratin, type II cytoskeletal 6A KRT6A 340,515.4 ±68,869.3 53,010.4 ±16,401.4 6.42 Fructose-bisphosphate aldolase ALDOA 515,078.4 ±93,413.7 81,491.0 ±7750.3 6.32 Carbonic anhydrase (CAH3) CA3 128,113.8 ±21,821.4 22,310.6 ±5010.6 5.74 Cellular retinoic acid-binding protein 2 CRABP2 14,697.1 ±3304.0 2776.5 ±616.7 5.29 Hsc70-interacting protein (F10A1) ST13 12,672.4 ±1992.2 2395.8 ±725.3 5.28 Keratin, type I cytoskeletal 10 KRT10 360,962.0 ±76,985.9 70,201.7 ±19,902.1 5.14 Transaldolase (TALDO) TALDO1 60,475.7 ±6149.7 12,790.6 ±1895.0 4.72 Y-box-binding protein 1 (YBOX1) YBX1 5441.0 ±1179.4 1189.9 ±396.4 4.57 Annexin A2 (fragment) ANXA2 5372.1 ±764.6 1182.3 ±309.8 4.54 Heterogeneous nuclear ribonucleoproteins C1/C2 HNRNPC 7177.4 ±1158.7 1700.7 ±405.7 4.22 Alpha-amylase 1A AMY1A 92,107.7 ±12,024.1 22,315.3 ±4160.5 4.13 Protein disulfide-isomerase A4 PDIA4 61,477.6 ±5982.7 15,204.7 ±2296.0 4.04 40S ribosomal protein S27a (RS27A) RPS27A 308,538.6 ±23,001.6 78,794.3 ±10,336.1 3.92 Biology 2021,10, 679 7 of 17 Table 2. Cont. Protein Name Gene Names Rib Middle Section Mean ±SE Mean ±SE FC Glutathione S-transferase Mu 1 GSTM1 349,396.0 ±39,083.3 94,826.5 ±25,325.8 3.68 Glucose-6-phosphate isomerase GPI 56,018.1 ±7541.4 15,638.1 ±1216.3 3.58 Heterogeneous nuclear ribonucleoprotein K(HNRPK) HNRNPK 33,963.0 ±5938.7 9548.3 ±1725.5 3.56 L-lactate dehydrogenase LDHB 339,487.1 ±68,674.4 100,577.0 ±9101.6 3.38 Polyadenylate-binding protein (PABP2) (fragment) PABPN1 14,151.0 ±3025.1 4320.8 ±740.8 3.28 Olfactomedin-like protein 3 (OLFL3) OLFML3 28,187.8 ±2177.8 9038.2 ±1023.4 3.12 Polypyrimidine tract-binding protein 1 PTBP1 12,884.6 ±1449.8 4236.4 ±382.5 3.04 Putative ATP-dependent RNA helicase DHX57 11,623.6 ±2252.4 3944.2 ±1136.7 2.95 Tetranectin CLEC3B 31,409.1 ±5411.8 10,775.4 ±2341.5 2.91 60S acidic ribosomal protein P0 (RLA0) RPLP0 5587.1 ±730.0 1920.2 ±265.3 2.91 Triosephosphate isomerase TPI1 548,662.6 ±54,009.9 192,349.8 ±28.673,1 2.85 Ubiquitin-conjugating enzyme E2 variant 2 UBE2V2 14,901.8 ±2303.7 5305.7 ±1703.4 2.81 6-phosphogluconate dehydrogenase decarboxylating PGD 30,659.1 ±3472.5 10,972.5 ±2533.0 2.79 Lupus La protein SSB 6042.3 ±964.5 2193.3 ±781.8 2.75 UDP-glucose 6-dehydrogenase UGDH 8707.4 ±1631.5 3215.2 ±674.1 2.71 Malate dehydrogenase, cytoplasmic MDH1 11,937.7 ±2189.3 4467.4 ±1815.3 2.67 Decorin DCN 203,457.1 ±19,766.6 78,507.4 ±9628.3 2.59 Phosphoglycerate kinase 1 PGK1 102,757.0 ±15,094.9 39,944.3 ±3442.8 2.57 Peroxiredoxin-6 PRDX6 226,238.3 ±16,359.3 88,053.3 ±12,976.1 2.57 Cu/Zn superoxide dismutase (SODC) SOD1 173,733.6 ±23,314.9 69,312.8 ±7322.5 2.51 Biglycan BGN 100,093.6 ±13,826.5 41,794.6 ±5319,2 2.39 Elongation factor 1-gamma (EF1G) EEF1G 15,255.3 ±2163.9 6767.1 ±1803.8 2.25 Glutathione S-transferase P GSTP1 54,208.3 ±5030.5 24,142.5 ±2739.0 2.25 Glucosidase 2 subunit beta (GLU2B) PRKCSH 6611.3 ±939.7 2971.2 ±894.4 2.23 Chloride intracellular channel protein 1 CLIC1 20,704.72 ±3379.9 9348.2 ±1694.4 2.21 Glutathione S-transferase P (fragment) GSTP1 42,414.8 ±7016.7 19,194.5 ±5.535.9 2.21 60S acidic ribosomal protein P2 (RLA2) RPLP2 17,289.1 ±1634.2 8009.4 ±1102.0 2.16 Alpha-2-HS-glycoprotein AHSG 274,143.4 ±36,049.6 129,638.6 ±29,231.7 2.11 Transgelin TAGLN 84,419.6 ±10,442.4 40,987.1 ±5652.8 2.06 Transgelin (fragment) TAGLN 37,823.7 ±3877.1 18,390.6 ±2628.0 2.06 Calponin CNN2 7285.9 ±849.1 3543.7 ±896.7 2.06 Polyadenylate-binding protein (PABP2) PABPN1 11,923.6 ±887.0 5875.5 ±1150.7 2.03 Phosphatidylethanolamine-binding protein 1 PEBP1 17,399.2 ±2682.0 8613.4 ±1756.9 2.02 Fatty acid-binding protein 5 FABP5 7163.9 ±843.8 3625.2 ±699.1 1.98 Heterogeneous nuclear ribonucleoprotein H HNRNPH1 31,298.3 ±2793.2 16,102.7 ±1632.7 1.94 Endoplasmin (ENPL) HSP90B1 51,370.1 ±3589.4 27,822.7 ±4283.1 1.85 Lumican LUM 380,040.3 ±43,044.1 206,390.0 ±30,250.1 1.84 Transitional endoplasmic reticulum ATPase VCP 68,467.5 ±8692.5 39,195.5 ±4453.9 1.75 Phosphatidylethanolamine-binding protein 1 PEBP1 42,253.9 ±5040.5 24,291.3 ±4633.2 1.74 Peptidyl-prolyl cis-trans isomerase (PIN4) PIN4 375,942.8 ±29,644.9 25,527.3 ±9262.3 1.61 UMP-CMP kinase CMPK1 6599.5 ±647.2 4105.2 ±500.7 1.61 Pyruvate kinase (KPYM) PKM 261,337.6 ±27,813.7 171,291.7 ±19,236.7 1.53 Galectin 1 LGALS1 49,839.4 ±5621.5 76,707.49 ±10,793.0 0.65 Nucleobindin-1 NUCB1 24,434.2 ±3012.5 38,920.5 ±4924.8 0.63 Heparin cofactor 2 (HEP2) SERPIND1 11,873.5 ±1969.7 19,863.8 ±3310.1 0.60 Elongation factor 2 EEF2 51,547.7 ±4948.4 86,627.3 ±12,626.1 0.60 Plastin-3 PLS3 18,711.7 ±2677.2 32,357.3 ±3587.1 0.58 Heat shock protein 70 1A HSPA1A 65,543.3 ±8657.8 114,598.05 ±8998.6 0.57 Serotransferrin (TRFE) TF 1,215,178.8 ±193,911.2 2,125,016.7 ±347,685.8 0.57 Inter-alpha-trypsin inhibitor heavy chain H2 ITIH2 47,937.9 ±5216.0 87,390.0 ±17,580.9 0.55 Apolipoprotein A-IV APOA4 45,231.5 ±4775.7 85,435.1 ±9548.5 0.53 Nucleoside diphosphate kinase mitochondrial NME4 67,760.2 ±5520.7 129,968.3 ±14,280.8 0.52 Fibrinogen alpha chain FGA 135,860.8 ±21,986.1 291,686.2 ±55,713.2 0.47 Vimentin VIM 156,778.7 ±17,997.7 341,121.7 ±67,935.6 0.46 Hemopexin HPX 79,373.2 ±11,927.3 173,172.2 ±38,801.3 0.46 Afamin (AFAM) AFM 10,596.6 ±1972.3 25,198.7 ±5103.3 0.42 Alpha-1B-glycoprotein A1BG 878,594.0 ±101,549.5 2,213,076.7 ±441,457.5 0.40 Thioredoxin domain-containing protein 5 TXNDC5 47,903.8 ±6878.6 121,210.10 ±10,595.2 0.40 Eukaryotic translation initiation factor 5A (IF5A1) EIF5A 7520.5 ±1315.2 19,182.3 ±3339.0 0.39 Transthyretin TTR 98,470.6 ±19,719.4 251,207.1 ±73,458.0 0.39 Apolipoprotein A-I APOA1 1,599,381.1 ±272,199.7 4,144,766.7 ±798,136.1 0.39 Creatine kinase B-type CKB 119,883.7 ±15,308.5 311,250.0 ±37,004.7 0.39 Biology 2021,10, 679 8 of 17 Table 2. Cont. Protein Name Gene Names Rib Middle Section Mean ±SE Mean ±SE FC Amiloride-sensitive amine oxidase AOC1 14,519.1 ±3374.7 39,327.2 ±6441.8 0.37 Hemoglobin subunit alpha HBA/SCN2A 905,083.4 ±296,103.9 2,563,475.0 ±869.235.6 0.35 Antithrombin-III (ANT3) SERPINC1 22,535.4 ±2287.5 64,056.0 ±10,572.3 0.35 Apolipoprotein A-II APOA2 20,745.2 ±5114.2 60,995.7 ±16,710.0 0.34 Collagen alpha-1(I) chain COL1A1 87,968.2 ±11,426.9 275,756.5 ±54,450.2 0.32 Complement factor B (CFAB) CFB 27,628.1 ±3354.1 90,554.5 ±16,717.9 0.31 Histidine-rich glycoprotein HRG 46,388.9 ±4259.7 159,018.1 ±45,430.2 0.29 Albumin ALB 4,096,318.3 ±713,885.6 19,510,270.2 ± 3,628,081.0 0.21 Plasminogen (PLMN) PLG 7232.5 ±2021.8 37,045.7 ±9978.9 0.20 Complement C3 C3 131,933.9 ±14,398.5 712,043.3 ±109,393.3 0.19 Proteins overexpressed in rib and middle section of antler are indicated in the table by green and red color, respectively. Biology 2021, 10, x FOR PEER REVIEW 8 of 16 Alpha-1B-glycoprotein A1BG 878,594.0 ± 101,549.5 2,213,076.7 ± 441,457.5 0.40 Thioredoxin domain-containing protein 5 TXNDC5 47,903.8 ± 6878.6 121,210.10 ± 10,595.2 0.40 Eukaryotic translation initiation factor 5A (IF5A1) EIF5A 7520.5 ± 1315.2 19,182.3 ± 3339.0 0.39 Transthyretin TTR 98,470.6 ± 19,719.4 251,207.1 ± 73,458.0 0.39 Apolipoprotein A-I APOA1 1,599,381.1 ± 272,199.7 4,144,766.7 ± 798,136.1 0.39 Creatine kinase B-type CKB 119,883.7 ± 15,308.5 311,250.0 ± 37,004.7 0.39 Amiloride-sensitive amine oxidase AOC1 14,519.1 ± 3374.7 39,327.2 ± 6441.8 0.37 Hemoglobin subunit alpha HBA/SCN2A 905,083.4 ± 296,103.9 2,563,475.0 ± 869.235.6 0.35 Antithrombin-III (ANT3) SERPINC1 22,535.4 ± 2287.5 64,056.0 ± 10,572.3 0.35 Apolipoprotein A-II APOA2 20,745.2 ± 5114.2 60,995.7 ± 16,710.0 0.34 Collagen alpha-1(I) chain COL1A1 87,968.2 ± 11,426.9 275,756.5 ± 54,450.2 0.32 Complement factor B (CFAB) CFB 27,628.1 ± 3354.1 90,554.5 ± 16,717.9 0.31 Histidine-rich glycoprotein HRG 46,388.9 ± 4259.7 159,018.1 ± 45,430.2 0.29 Albumin ALB 4,096,318.3 ± 713,885.6 19,510,270.2 ± 3,628,081.0 0.21 Plasminogen (PLMN) PLG 7232.5 ± 2021.8 37,045.7 ± 9978.9 0.20 Complement C3 C3 131,933.9 ± 14,398.5 712,043.3 ± 109,393.3 0.19 Proteins overexpressed in rib and middle section of antler are indicated in the table by green and red color, respectively. Figure 1. Projection of the antler samples of Iberian red deer (Cervus elaphus) of the three locations (tip, middle and rib) in the plane defined by the first two principal components. 3.1.1. Comparison Tip vs. Middle Antler From the total proteins identified and quantified as DAP by SWATH-MS, those that exhibit a 1.5-fold between the two groups and a Student’s t-test with 5% statistical significance (p < 0.05) were considered as differentially abundant. In the comparison within the antler between the growth center (tip) and mineralizing section (middle), 34 proteins were overabundant in the tip (color blue) with 17 unidentified proteins (data not shown) and 44 proteins were overabundant in the middle section (color red) with 6 unidentified deer antler proteins (Table 1). The high number of unidentified proteins in both antler sections demonstrates the lack of knowledge of the proteomic profile of this tissue, especially in the tip section where 32.7% of the total DAPs were unidentified. In a previous study by our group on deer meat (longisimus thoracis et lumborum), the number of unidentified proteins, employing the same database, was lower [20], suggesting that the major constraint could be in the tissue of deer antler. This fact indicates that antler is not studied enough Rib_2 Rib_3 Rib_4 Rib_5 Rib_6 Rib_1 Tip_1 Tip_2 Middle section_1 Tip_3 Tip_4 Middle section_2 Tip_5 Middle section_3 Middle section_4 Tip_6 Middle section_5 Middle section_6 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 -1.5 -1 -0.5 0 0.5 1 1.5 2 PC2 (23.31 %) PC1 (41.75 %) Figure 1. Projection of the antler samples of Iberian red deer (Cervus elaphus) of the three locations (tip, middle and rib) in the plane defined by the first two principal components. 3.1.1. Comparison Tip vs. Middle Antler From the total proteins identified and quantified as DAP by SWATH-MS, those that exhibit a 1.5-fold between the two groups and a Student’s t-test with 5% statistical significance (p< 0.05) were considered as differentially abundant. In the comparison within the antler between the growth center (tip) and mineralizing section (middle), 34 proteins were overabundant in the tip (color blue) with 17 unidentified proteins (data not shown) and 44 proteins were overabundant in the middle section (color red) with 6 unidentified deer antler proteins (Table 1). The high number of unidentified proteins in both antler sections demonstrates the lack of knowledge of the proteomic profile of this tissue, especially in the tip section where 32.7% of the total DAPs were unidentified. In a previous study by our group on deer meat (longisimus thoracis et lumborum), the number of unidentified proteins, employing the same database, was lower [ 20 ], suggesting that the major constraint could be in the tissue of deer antler. This fact indicates that antler is not studied enough in terms of protein profile. In the middle section, the most abundant proteins (>10 5 ) were hemoglobin subunit alpha, adult beta-globin 1, adult beta-globin 2, apolipoprotein A-II, alpha-1B-glycoprotein, serotransferrin, lactotransferrin and several unidentified proteins. Biology 2021,10, 679 9 of 17 3.1.2. Comparison Middle Section of Antler vs. Rib In the comparison between the mineralizing section of the antler (middle section) and the ribs, 30 proteins were overabundant in the middle section (color red) with 6 unidentified proteins (data not shown), and 58 proteins were overabundant in the ribs (color green) with 26 unidentified deer antler proteins (data not shown) (Table 2). Among the majority of overexpressed proteins in the rib, the most abundant was the collagen alpha-2(I) chain (CO1Aa) with a fold change of 49, corresponding to gene COL1A2. There is a set of proteins related to oxidative stress (chaperones, heat shock proteins and other types) overexpressed in the ribs compared to the mineralizing section of the antler. CAH3, glutathione S-transferase Mu 1, F10A1, protein disulfide-isomerase A4, SODC, glutathione S-transferase P, peroxiredoxin-6 and EF1G are the most relevant. 3.2. Comprehensive Analysis of Deer Antler Proteome Deer antler contains several proteins with distinctive functions as can be concluded from Figure 2. The functional enrichment analysis for GO was performed using FunRich from DAPs between the tip and middle section. Biological process and molecular function were considered to carry out GO analysis of annotated proteins. Regarding biological processes, the more abundant categories were the lipoprotein metabolic process (GO:0042157), protein oxidation (GO:0018158), peptidyl methionine modification (GO:0018206), removal of superoxide radicals (GO:0019430), glutathione metabolic process (GO:0006749) and lipid transport (GO:0006869). Biology 2021, 10, x FOR PEER REVIEW 9 of 17 in terms of protein profile. In the middle section, the most abundant proteins (>10 5 ) were hemoglobin subunit alpha, adult beta-globin 1, adult beta-globin 2, apolipoprotein A-II, alpha-1B-glycoprotein, serotransferrin, lactotransferrin and several unidentified proteins. 3.1.2. Comparison Middle Section of Antler vs. Rib In the comparison between the mineralizing section of the antler (middle section) and the ribs, 30 proteins were overabundant in the middle section (color red) with 6 unidentified proteins (data not shown), and 58 proteins were overabundant in the ribs (color green) with 26 unidentified deer antler proteins (data not shown) (Table 2). Among the majority of overexpressed proteins in the rib, the most abundant was the collagen alpha2(I) chain (CO1Aa) with a fold change of 49, corresponding to gene COL1A2. There is a set of proteins related to oxidative stress (chaperones, heat shock proteins and other types) overexpressed in the ribs compared to the mineralizing section of the antler. CAH3, glutathione S-transferase Mu 1, F10A1, protein disulfide-isomerase A4, SODC, glutathione S-transferase P, peroxiredoxin-6 and EF1G are the most relevant. 3.2. Comprehensive Analysis of Deer Antler Proteome Deer antler contains several proteins with distinctive functions as can be concluded from Figure 2. The functional enrichment analysis for GO was performed using FunRich from DAPs between the tip and middle section. Biological process and molecular function were considered to carry out GO analysis of annotated proteins. Regarding biological processes, the more abundant categories were the lipoprotein metabolic process (GO:0042157), protein oxidation (GO:0018158), peptidyl methionine modification (GO:0018206), removal of superoxide radicals (GO:0019430), glutathione metabolic process (GO:0006749) and lipid transport (GO:0006869). Figure 2. Cont. Biology 2021,10, 679 16 of 17 16. Wang, D.; Ba, H.; Li, C.; Zhao, Q.; Li, C. Proteomic analysis of plasma membrane proteins of antler stem cells using label-free LC-MS/MS. Int. J. Mol. Sci. 2018,19, 3477. [CrossRef] [PubMed] 17. Dong, Z.; Haines, S.; Coates, D. 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