Proteomic assessment of the relevant factors affecting pork meat quality associated with longissimus dorsi muscles in Duroc pigs.
Variation in meat quality traits is a well-known problem. Meat quality traits are closely related to biological traits of live animal. Hence, biological sciences including genetics, physiology, cell biology, and biochemistry have been widely employed for decades to characterize the biological mechanisms behind major variability of meat quality traits (Bendixen, 2005). Basic knowledge of these mechanisms is essential to reduce the variation in meat quality traits such as tenderness, water-holding capacity, and color. They are also important to understand the physiology of meat animals, especially on muscle growth and development (Lametsch et al., 2002; Hwang et al., 2005). Understanding and changes related to physiochemical factors, genotypes, and many other factors influence postmortem metabolism (Monin et al., 1995; Brocks et al., 1998; Wheeler et al., 2005). Some previous studies have indicated that meat quality is determined by postmortem muscle metabolism (Pette, 2002; Spangenburg and Booth, 2003). At slaughter, muscles become deprived of oxygen as the circulatory system shuts down. This lack of oxygen results in a shift to glycolytic (anaerobic) metabolism and a buildup of lactic acid, causing a drop in muscle pH (Frisby et al., 2005). Accelerated postmortem glycolysis reduces pH and increases temperature within muscle, resulting in excessive protein denaturation and inferior meat quality (Julve et al., 2000). Although extensively researched, the underlying mechanisms of many different meat quality traits are far from well understood due to many factors affecting the quality of meat (Mullen et al., 2006; Hollung et al., 2007). The proteome expressed from the genome is influenced by environmental conditions. Proteome is the molecular link between the genome and the functional quality characteristics of the meat. Therefore, proteomics is a promising and powerful tool in meat science (Lametsch and Bendixen, 2001; Morzel et al., 2004; Jia et al., 2006; Sayd et al., 2006). However proteomics has been, and still are, used in numerous studies on skeletal muscle (Picard et al., 2010).
In this study, we focus on its use in the study of livestock muscle development and meat quality with a focus on the differential expression patterns of proteins and their interactions for the development of meat quality traits.
MATERIALS AND METHODS
Animals and sample collection
The meat quality characteristics were assessed from 200 randomly selected great grandparent Duroc pigs raised from October 2011 to March 2012 for one production cycle. The live weight ranged from 100 to 120 kg. The carcasses were kept in a freezer (0[degrees]C) for 24 h after slaughtering. The frozen carcasses were thawed, deboned, and trimmed. The left side loin was transferred to the laboratory and placed in a deep-freezer (-45[degrees]C) for analysis
Gel electrophoresis and silver staining
High quality longissimus dorsi muscles (HQLD) and low quality longissimus dorsi muscles (LQLD) tissues were collected from Duroc pigs. Total protein isolation was performed using PRO-PREP protein extraction solution (iNtRON biotechnology, Sungnam, Korea) according to the manufacturer's instructions. Concentrations of eluted proteins were measured using Pierce BCA Protein Assay Kit (Thermo scientific, Rockford, IL, USA). Equal amounts of protein samples were precipitated with cold acetone. Protein pellets dissolved in 1 x sodium dodecyl sulfate (SDS) sample buffer were separated by 8% and 12% SDS-polyacrylamide gel electrophoresis (PAGE). Following SDS-PAGE, protein spots were visualized using protocols described in PlusOne Silver staining kit (GE Healthcare Bio-Sciences, Uppsala, Sweden). The complete protocol was followed to analyze gels. To prepare gels, the protocol was modified so that glutaraldehyde was omitted from the sensitization step and formaldehyde was omitted from the silver reaction step (Yan et al., 2000). Silver-stained gels were scanned (UMAX PowerLook 2100KL Imaging system, UMAX, Taiwan) and protein profiles were compared.
Liquid chromatography-tandem mass spectrometry
The resulting tryptic peptides were separated and analyzed using reversed-phase capillary high-performance liquid chromatography directly coupled to a Thermo LTQ Orbitrap mass spectrometer using published procedure described by Zuo et al. (2001) with slight modifications. Briefly, a 0.075 x 20 mm trapping column and a 0.075 x 120 mm resolving column were packed with C18AQ 218MS low formic acid C18 beads (5 pm in size, 200[Angstrom] pore size; C18AQ, Michrom BioResources, Auburn, CA, USA) and placed in-line. Peptides were bound to the trapping column for 10 min with 2% (vol/vol) aqueous acetonitrile containing 0.1% (vol/vol) formic acid. The bound peptides were then eluted with a 67 min gradient of 2% to 90% (vol/vol) acetonitrile containing 0.1% (vol/vol) formic acid at a flow rate of 0.2 [micro]L/min. For tandem mass spectrometry, the full mass scan range mode was set at m/z = 50 to 2,000 Da. After determining the charge states of the ion zoom scans, product ion spectra were acquired in MS/MS mode with relative collision energy of 55%. The individual spectra from MS/MS were processed using Protein discoverer 2.1 software (Thermo scientific, USA). The generated peak list files were used to query either the MSDB or the NCBI database using the MASCOT program (http://www.matrixscience.com). We considered modifications of methionine and cysteine, peptide mass tolerance at 2 Da, MS/MS ion mass tolerance at 0.8 Da, allowance of missed cleavage at 2, and charge states (namely, +1, +2, and +3). Only significant hits as defined by MASCOT probability analysis were initially considered.
Mitotic C2C12 mouse myoblasts were obtained from Chonbuk University (Jeonju, Korea). C2C12 were passaged as subconfluent monolayers in growth medium (GM) using Dulbecco's modified Eagle's medium (Invitrogen, Grand Island, NY, USA) supplemented with 20% fetal bovine serum, 200 mM L-glutamine, 10 units/mL penicillin, and 10 [micro]g/mL streptomycin. Confluent (90%) myoblasts were differentiated into myotubes by culturing the cells in differentiation medium (DM) with Dulbecco's modified Eagle's medium supplemented with 2% horse serum.
3-(4, 5-dimethylthiazol-2-yl)-5-(3-carboxymethoxy-phenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) assay
The effects of [H.sub.2][O.sub.2] on cell viability were estimated using MTS Assay Kit (Promega, Madison, WI, USA). C2C12 cells were seeded into a 96-well plate for 24 h and treated with [H.sub.2][O.sub.2] (12.5 [micro]M to 1 mM) for 24 h or 48 h. MTS solution was added to the plates and incubated at 37[degrees]C with 5% C[O.sub.2] for 2 h. Absorbance at 490 nm was recorded using a GloMax-Multi Microplate Multimode Reader (Promega, USA).
To detect myosin heavy chain (MYH), myogenic differentiation (MyoD), and myogenin (Myog), cells were blocked with 1% bovine serum albumin and incubated with monoclonal anti-MYH (B-5), anti-MyoD (E-1), or anti-Myog (M-225) antibody at 4[degrees]C overnight (Santa Cruz Biotechnology, Santa Cruz, CA, USA). Probed cells were reacted with a 488-conjugated anti-mouse or 594-conjugated anti-rabbit secondary antibody. For nucleus staining, cells were treated with mounting medium with 4'6-diamidino-2-phenylindole (DAPI) (Vector Laboratories, Inc. Burlingame, CA, USA). The cells were visualized using a FluoView confocal laser microscope (Fluoview FV10i, Olympus Corporation, Tokyo, Japan).
Reverse transcription polymerase chain reaction and real-time polymerase chain reaction analysis
Total RNA isolation was performed using TRIzol reagent (Invitrogen, USA) according to the manufacturer's instructions. Briefly, total RNA levels were quantified by absorbance at 260 nm. RNA integrity was evaluated by 1.2% (w/v) agarose gel. Total RNA (2 [micro]g amounts) was reverse-transcribed into cDNA using QuantiTect Reverse Transcription Kit (Qiagen, Chatsworth, CA, USA) according to the manufacturer's instructions. Real-time polymerase chain reaction analysis (PCR) was performed with SYBR green Premix Ex Taq II (Takara, Dalian, China) using Applied Biosystems StepOne Plus Real-time PCR System (Applied Biosystems, Carlsbad, CA, USA). Relative quantification analysis was performed using the comparative Ct (2 [sup.(-[DELTA][DELTA]CT)]) method. The expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and [beta]-actin was used as endogenous control for the detection of mRNA expression levels. Primers used in the study were listed in Table 4.
Kinetic determination of LDH activity
Commercially available kits for lactate dehydrogenase (DLDH-100, QuantiChrom Lactate Dehydrogenase Kit, Gentaur Molecular, Hayward, CA, USA) were used according to the manufacturers' instructions (Stentz et al., 2010).
RESULTS AND DISCUSSION
Animals and phenotypes
The average weight before and after slaughtering of the GGP pigs were 98.23 kg and 89.98 kg, respectively. Difference of 10 kg before and after slaughtering was recorded. Important economic traits such as lean percent and eye muscle area showed an average value of 54.74% and 26.03 [cm.sup.2], respectively (Table 1).
Protein profiles in HQLD and LQLD from Duroc pigs
Meat qualities were evaluated by Korea Institute for Animal Products Quality Evaluation (KAPE) authorized by South Korean government to perform animal products grading service. The normality test was applied to show normal distribution of the traits. The highest and lowest meat grades for pH and water holding capacity were identified from the sample which accounted for 10% (20 heads) of the total population (Table 2). To obtain a comprehensive overview of protein components in HQLD and LQLD from 12 individuals, protein profiles of whole lysate of HQLD and LQLD separated by 8% and 12% SDS-PAGE were assessed by silver-stained image analysis (Figure 1A). Patterns of total protein components in whole lysate of HQLD and LQLD were similar among the individual six groups. However, significantly fewer proteins (i.e. band a and b) were expressed in HQLD compared to in LQLD. Two different protein spots were identified by a mass spectrometric analysis. Myosin binding protein C (MYBPC2) expressed during skeletal muscle development (Gurnett et al., 2010) had higher expression in HQLD than in LQLD. However, lactate dehydrogenase A (LDHA) catalyzing the conversion of pyruvate to lactate during glycolysis (Fan et al., 2011) had higher expression in LQLD than in HQLD (Figure 1B).
Protein identification and gene ontological classification by LC-MS/MS-based proteomic analysis
Next, we performed liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomic analysis to elucidate the proteins involved in longissimus dorsi muscle (i.e. HQLD and LQLD) properties involved in meat quality. Among the total 24 proteins identified, 10 and 14 proteins were confirmed to be highly expressed in HQLD and LQLD, respectively. All identified proteins were clustered into the following seven categories (Figure 2A) based on information obtained from DAVID gene ontology (GO) database (http://david.abcc.ncifcrf.gov) and UniProt (http://www.uniprot.org): Catalytic activity (31%), ATPase activity (19%), oxidoreductase activity (13%), cytoskeletal protein binding (13%), actin binding (12%), calcium ion binding (6%) and structural constituent of muscle (6%) (Supplementary Table S1). The GO analysis was performed using DAVID Bioinformatics Resources 6.7 categories for both molecular function (MF) and biological process (BP). Depending on the MF in which the proteins were involved, they were categorized into the following three groups (Figure 2B): Cytoskeletal protein binding (40%), actin binding (40%), and structural constituent of muscle (20%) (Supplementary Table S2). Depending on the BP in which the proteins were involved, they were categorized into the following five groups (Figure 2C): Primary metabolic process (26%), cellular metabolic process (26%), catabolic process (18%), nitrogen compound metabolic process (19%), and oxidation reduction (11%) (Supplementary Table S3). The expression changes of the up- and down-regulated proteins in HQLD and LQLD of Duroc pigs were summarized in Table 3. LDHA was selected and subjected to further analysis by LDH activity assay and in vitro study of myogenesis under oxidative stress conditions.
Gross changes in C2C12 myoblasts in response to myogenic differentiation
C2C12 myoblasts serve as an experimentally tractable model system for investigating the molecular basis of skeletal muscle cell specification and development (Kislinger et al., 2005). A temporally well-defined myogenic differentiation program can be selectively triggered in cultured C2C12 myoblasts upon withdrawal of GM and mitogens (Gramolini and Jasmin, 1999). When switched to DM, mitotic C2C12 myoblasts rapidly cease proliferation and initiate a synchronously terminal differentiation program (Figure 3A). To investigate the patterns of protein expression and efficiency of myotube formation during myogenesis under oxidative stress condition, undifferentiation C2C12 cells were treated with various concentrations of [H.sub.2][O.sub.2] (12.5 [micro]M to 1 mM). Cytotoxicity was negligible with 200 gM H2O2. However, up to 1 mM H2O2 did reduce viability which was confirmed by 3-(4, 5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl) -2-(4-sulfophenyl)-2H-tetrazolium) (MTS) assay (Figure 3B). Control cells exhibited striking morphological changes over the course of 3 to 7 days, eventually fusing into mature multinucleated myotubes (i.e. by day 5). However, [H.sub.2][O.sub.2]-treated cells exhibited thread-like shape without fusing into mature multinucleated myotubes (Figure 3C). Myotubes were identified by immunocytochemistry with anti-myosin heavy chain (MYH) antibody (Figure 3D).
In vitro model of myogenesis under oxidative stress condition
The expression of myogenic regulatory factors consisting of MyoD and Myog characterizes various phases of skeletal muscle development, including myoblast proliferation, cell-cycle exit, cell fusion, and the maturation of myotubes to form myofibers (Lee et al., 2014). MyoD, the chief regulatory molecule of myogenic differentiation (Langen et al., 2004), plays an important role in cell cycle exit of differentiating myoblasts (Guo et al., 1995; Halevy et al., 1995) Terminal differentiation of myoblast, driven by expression of Myog, is essential for the formation of functional multinucleated myofibers (Liu et al., 2012). In order to study the patterns of MyoD and Myog expression (gene and protein levels) depending on oxidative stress condition during myogenesis, we used western blot and RT-PCR analyses. Our data revealed that, among various genes subjected to comparison, MyoD had significant (p<0.0001) higher expression under oxidative stress condition than under normal condition on day 3. The expression of MyoD on day 3 was not significantly different from that on day 2 under oxidative stress condition. Myog had significant (p<0.0001) higher expression under normal condition than under oxidative stress condition at day 6. Under oxidative stress condition, the expression of Myog was significantly (p<0.05) decreased at day 6 compared to that at day 5 (Figure 3E). The mRNA expression levels for selected genes were analyzed by quantitative real-time PCR with specific primer (Table 4). Western blot analysis data revealed that, of different proteins subjected to comparison, MyoD had significantly (p<0.0001) higher expression under oxidative stress condition than under normal condition at day 2. Under oxidative stress condition, the expression of MyoD at 12 h was not significantly different from that at 6 h. Moreover, Myog had significantly (p<0.0001) higher expression under normal condition than under oxidative stress condition at day 4. Under oxidative stress condition, the expression of Myog was significantly more decreased (p = 0.0016) at day 4 than at day 3 (Figure 3F). These results indicate that [H.sub.2][O.sub.2]-induced oxidative stress inhibits myogenesis through the down-regulation of Myog and the continuous up-regulation of MyoD.
Relationships between LDHA gene expression and myogenesis
Previous studies reported that porcine myogenic differentiation 1 (MyoD1) gene has been mapped to swine chromosome 2p14-p17 which is involved in the regulation of the proliferation and differentiation of skeletal muscle cells. LDHA genes mapped close to MyoD are involved in energy metabolism and protein transport processes. LDHA genes might play important roles in muscle development (Qiu et al., 2010). However, little is known about porcine LDHA genes. Therefore, we determined the relationships between LDHA gene expression and myogenesis under normal and oxidative stress condition. To investigate whether oxidative stress regulated LDHA expression at genetic levels, we used quantitative real-time PCR. The mRNA expression levels of selected genes were subjected to quantitative real-time PCR with specific primers (Table 4). Figure 4A showed that LDHA genes were increased up to day 5 during myogenesis under normal and oxidative stress condition. LDHA expression was significantly (p = 0.0088) higher under oxidative stress condition. These results indicate that up-regulated LDHA genes induced by oxidative stress might play dysfunctional roles in myogenesis.
Antioxidant properties of resveratrol
Resveratrol (RSV), a well-known phytocompound and food component, has antioxidative and multifunctional bioactivities (Wu et al., 2013). Previous studies have reported that RSV in skeletal muscle acts on protein catabolism and muscle function and confers resistance against oxidative stress, injury, and cell death. However, its action mechanisms and protein targets in myogenesis process are not completely understood (Montesano et al., 2013). Therefore, we determined the effect of RSV on LDHA gene expression in myogenesis under oxidative stress condition. C2C12 cells were treated with various concentrations of RSV (6.25 [micro]M to 100 [micro]M). Cytotoxicity was negligible with RSV (25 [micro]M) under normal and oxidative stress conditions. However, up to 100 [micro]M RSV did reduce viability which was confirmed by MTS assay (Figure 4B). However, after RSV treatment, there was no significant difference in mRNA expression of LDHA between normal condition and oxidative stress condition (Figure 4C).
Confirmation of lactate dehydrogenase activity
Elevation of plasmatic LDH levels are characteristic responses to strenuous exercise which are often used as indicators of muscle damage (Kanter et al., 1988; Bouzid et al., 2014). However, difference of LDH activity between HQLD and LQLD of Duroc pigs is not well determined. Our data showed that LDH activity was significantly (p = 0.0003) higher in LQLD than in HQLD of Duroc pigs (Figure 5A). Moreover, higher LDH activity was positively correlated with in vitro model of myogenesis under oxidative stress condition. In addition, LDH activity was significantly reduced by RSV treatment (Figure 5B). We also confirmed the patterns of MyoD and Myog expression under oxidative stress condition and RSV treatment during myogenesis by immunocytochemistry. Oxidative stress induced down-regulation of Myog and continuous upregulation of MyoD. The down-regulation induced by oxidative stress was recovered by RSV treatment. The upregulation of MyoD induced by the oxidative stress was reduced by the treatment of RSV in myogenesis (Figure 5C). In addition, there was a significant correlation between MyoD and Myog expression (gene and protein levels) under oxidative stress condition during myogenesis (Figure 5D). These results indicate that high activity of LDH by oxidative stress will result in dysfunction of myogenesis and that RSV treatment will result in its functional recovery.
In conclusion, our data demonstrated that up- or down regulation of genes and proteins are involved in muscle development, muscle function, actin organization, oxidative stress, cell proliferation, cell differentiation, and cell growth. In this paper, differential expression patterns of genes and their interaction are found to be important for the development of meat quality traits. Our proteome data provided valuable information on differentially expressed genes (LDHA) and activity of LDH in HQLD and LQLD from Duroc pigs, which may aid in the regulation of muscle development. Our study provided experimental evidence for RSV as an important regulator to improve meat quality grades in porcine. However, further study is required to determine the relationship between differential expression of genes or proteins and their direct effects on meat quality.
CONFLICT OF INTEREST
We certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.
This work was carried out with the support of "Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ011682)" Rural Development Administration, Republic of Korea.
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Jin Hyoung Cho (1,a), Ra Ham Lee (1,a), Young-Joo Jeon (1,2), Seon-Min Park (3), Jae-Cheon Shin (3), Seok-Ho Kim (4), Jin Young Jeong (5), Hyun-sung Kang (6), Nag-Jin Choi (7), Kang Seok Seo (6), Young Sik Cho (8), MinSeok S. Kim (9), Sungho Ko (10), Jae-Min Seo (11), Seung-Youp Lee (12), Jung-Hyun Shim (13,14), *, and Jung-Il Chae (1), *
(1) Department of Dental Pharmacology, School of Dentistry and Institute of Dental Bioscience, BK21 plus, Chonbuk National University, Jeonju 651-756, Korea
* Corresponding Authors: Jung-Hyun Shim. Tel: +82-61-450-2684, Fax: +82-61-450-2684, E-mail: email@example.com / Jung-Il Chae. Tel: +82-63-270-4024, Fax: +82-63-270-4037, E-mail: firstname.lastname@example.org
(2) National Marine Biodiversity Institute of Korea, Seocheon 33662, Korea.
(3) Pohang Center for Evaluation of Biomaterials, Pohang 37668, Korea.
(4) Aging Research Institute, Korea Research Institute of Bioscience & BioTechnology, Daejeon 34141, Korea.
(5) Division of Animal Genomics and Bioinformatics, National Institute of Animal science, Rural Development Administration, Suwon, 441-706, Korea.
(6) Department of Animal Science and Technology, Sunchon National University, Suncheon 540-742, Korea.
(7) Department of Animal Science, College of Agricultural and Life Science, Chonbuk National University, Jeonju 651-756, Korea.
(8) Department of Pharmacy, Keimyung University, Daegu 704-701, Korea.
(9) Department of Biomedical Engineering, Konyang University, Daejeon 35365, Korea.
(10) Department of Applied Bioscience, CHA University, Seongnam 463-836, Korea.
(11) Department of Prosthodontics, School of Dentistry and Institute of Oral Bio-Science and Research Institute of Clinical Medicine, Chonbuk National University, Jeonju 561-756, Korea.
(12) Cluster for Craniofacial Development and Regeneration Research, Institute of Oral Biosciences and School of Dentistry, Chonbuk National University, Jeonju 561-756, Korea.
(13) Department of Pharmacy, College of Pharmacy and Natural Medicine Research Institute, Mokpo National University, Mokpo 534-729, Korea.
(14) The China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan 127, China.
(a) These authors contributed equally to this work.
Submitted Jan. 19, 2016; Revised Feb. 21, 2016; Accepted Mar. 29, 2016
Table 1. Phenotypic record of meat quality traits in Duroc pigs Traits N Mean Min Max Eye muscle area ([cm.sup.2]) 199 28.13 20.99 33.00 Age at 90 kg (d) 199 142.97 123 171 Average daily gain (g) 199 643.34 493.30 780.00 Backfat thickness (mm) 199 14.78 10.26 24.23 Loin depth (mm) 199 55.61 50.40 60.40 Weight at end of test day (kg) 199 99.18 75.00 120.00 Meat quality characteristics pH 24h 199 5.71 5.43 6.03 Brightness 199 54.50 46.71 62.25 Redness 199 16.98 9.75 21.10 Yellowness 199 11.31 5.45 16.29 Water holding capacity 199 73.55 56.99 89.04 Cooking loss 199 14.53 6.65 22.95 Moisture 199 72.76 63.67 79.33 Color, sensory test 199 5.37 2.50 7.50 Flavor, sensory test 199 5.28 1.25 8.00 Tenderness, sensory test 199 5.28 1.25 8.50 Juiciness, sensory test 199 5.10 1.25 9.75 Palatability, sensory test 199 5.13 1.25 8.50 Shear force 199 6.24 2.46 12.94 Biochemical measures Palmitic acid 199 25.58 22.74 28.08 Oleic acid 199 35.89 10.89 44.91 Stearic acid 199 17.19 9.72 43.71 Linolenic acid 199 8.42 5.31 13.06 Traits Median Std Eye muscle area ([cm.sup.2]) 28.15 0.218 Age at 90 kg (d) 142 0.960 Average daily gain (g) 641.75 5.806 Backfat thickness (mm) 14.48 0.184 Loin depth (mm) 55.80 0.189 Weight at end of test day (kg) 100.00 0.861 Meat quality characteristics pH 24h 5.71 0.109 Brightness 54.40 2.981 Redness 17.27 1.984 Yellowness 11.52 2.076 Water holding capacity 72.80 6.874 Cooking loss 14.64 2.998 Moisture 73.00 1.922 Color, sensory test 5.42 0.873 Flavor, sensory test 5.33 1.187 Tenderness, sensory test 5.33 1.450 Juiciness, sensory test 5.25 1.506 Palatability, sensory test 5.25 1.491 Shear force 5.63 2.215 Biochemical measures Palmitic acid 25.68 1.044 Oleic acid 40.00 10.118 Stearic acid 13.17 9.799 Linolenic acid 8.06 1.743 Table 2. High-or low-meat quality traits of longissimus dorsi muscles in Duroc pigs Traits N Mean Min High quality of longissimus dorsi muscles pH 24h 20 5.82 5.73 Water holding capacity 20 73.96 65.60 Cooking loss 20 14.40 7.30 Moisture 20 72.95 70.17 Shear force 20 6.44 3.83 Low quality of longissimus dorsi muscles pH 24h 20 5.60 5.55 Water holding capacity 20 73.76 62.33 Cooking loss 20 15.39 9.27 Moisture 20 72.74 68.00 Shear force 20 6.14 2.46 Traits Max Median Std High quality of longissimus dorsi muscles pH 24h 6.03 5.80 0.083 Water holding capacity 85.75 73.42 5.699 Cooking loss 21.45 13.82 3.457 Moisture 75.33 72.67 1.369 Shear force 10.55 6.02 2.229 Low quality of longissimus dorsi muscles pH 24h 5.64 5.60 0.031 Water holding capacity 87.35 72.60 7.135 Cooking loss 22.95 15.41 2.850 Moisture 75.00 73.00 1.713 Shear force 10.29 5.60 2.036 Table 3. List of differentially expressed genes on high-and low quality of longissimus dorsi muscles in duroc pigs No UniProt (1) UniGene (2) Protein identified Highly expressed genes in HQLD 1 Q5S1S4 Ssc.10960 Carbonic anhydrase 3 2 F1RKI3 Ssc:100518898 histidine triad nucleotide-binding protein 1 3 Q9TSX9 Ssc.2979 Peroxiredoxin-6 4 D3GGC9 Ssc.3835 Actinin-associated LIM protein 3 5 F1RGK5 Ssc.51787 Tropomyosin alpha-3 chain 6 P34930 Ssc.5145 Heat shock 70 kDa protein 1A 7 Q04967 Ssc.114 Heat shock 70 kDa protein 6 8 F1SEN8 Ssc.97236 LIM domain-binding protein 3 9 F1RH20 Ssc.83876 Myosin-binding protein C, fast-type 10 F1SMN5 Ssc.46794 Filamin-C Highly expressed genes in LQLD 11 P00355 Ssc.16135 Glyceraldehyde-3-phosphate dehydrogenase 12 P00339 Ssc.50275 L-lactate dehydrogenase A 13 F1SKJ8 Ssc.26154 Parvalbumin 1 14 F1SLA0 Ssc.279 ATP synthase subunit beta 15 Q9GJT2 Ssc.217 S-formylglutathione hydrolase 16 F1RFH9 Ssc.55270 Sarcoplasmic/endoplasmic reticulum calcium ATPase 1 17 Q06AA5 Ssc.26272 Tetraspanin-9 18 F1S6Q7 Ssc:100523423 ATP synthase subunit delta, mitochondrial -like 19 A1X898 Ssc.97027 Procollagen-proline 2-oxoglutarate-4-dioxygenase 20 F1RFU5 Ssc.3588 Aspartate aminotransferase 21 E7EBY5 Ssc.26469 MACRO domain containing protein 1 22 Q2XQV4 Ssc.11147 Aldehyde dehydrogenase, mitochondrial 23 I3LL15 Ssc.16302 Uricase 24 F1SLR6 Ssc.5041 Putative ribosomal RNA methyltransferase NOP2 No UniProt (1) UniGene (2) Gene name pI MW (kDa) Highly expressed genes in HQLD 1 Q5S1S4 Ssc.10960 CA3 7.85 29.4 2 F1RKI3 Ssc:100518898 LOC100518898 6.87 13.7 3 Q9TSX9 Ssc.2979 PRDX6 6.01 25 4 D3GGC9 Ssc.3835 PDLIM3 8.12 30.5 5 F1RGK5 Ssc.51787 TPM3 4.75 28.9 6 P34930 Ssc.5145 HSPA1A 5.73 70 7 Q04967 Ssc.114 HSPA6 6.06 71.1 8 F1SEN8 Ssc.97236 LDB3 7.78 75.8 9 F1RH20 Ssc.83876 MYBPC2 6.55 127.6 10 F1SMN5 Ssc.46794 FLNC 5.96 290.2 Highly expressed genes in LQLD 11 P00355 Ssc.16135 GAPDH 8.35 35.8 12 P00339 Ssc.50275 LDHA 8.07 36.6 13 F1SKJ8 Ssc.26154 PVALB1 5.07 12.1 14 F1SLA0 Ssc.279 ATP5B 5.27 56.3 15 Q9GJT2 Ssc.217 ESD 7.02 31.5 16 F1RFH9 Ssc.55270 ATP2A1 5.29 109.1 17 Q06AA5 Ssc.26272 TSPAN9 7.44 26.8 18 F1S6Q7 Ssc:100523423 LOC100523423 5.25 17.5 19 A1X898 Ssc.97027 P4HA1 6.01 60.9 20 F1RFU5 Ssc.3588 GOT2 8.73 24.1 21 E7EBY5 Ssc.26469 MACROD1 9.22 35.1 22 Q2XQV4 Ssc.11147 ALDH2 6.87 56.9 23 I3LL15 Ssc.16302 UOX 8.32 34.9 24 F1SLR6 Ssc.5041 NOP2 9.06 90.2 Individual ion score (3) No UniProt (1) UniGene (2) Seq. HQLD LQLD Cov (%) Highly expressed genes in HQLD 1 Q5S1S4 Ssc.10960 53.46 150.33 82.96 2 F1RKI3 Ssc:100518898 11.11 3.48 0 3 Q9TSX9 Ssc.2979 7.59 2.67 0 4 D3GGC9 Ssc.3835 5.42 5.96 2.24 5 F1RGK5 Ssc.51787 5.24 7.13 0 6 P34930 Ssc.5145 3.12 12.17 4.39 7 Q04967 Ssc.114 2.95 9.69 3.98 8 F1SEN8 Ssc.97236 1.68 2.83 2.13 9 F1RH20 Ssc.83876 1.58 2.57 0 10 F1SMN5 Ssc.46794 0.44 4.59 0 Highly expressed genes in LQLD 11 P00355 Ssc.16135 46.85 81.05 447.46 12 P00339 Ssc.50275 39.76 129.85 230.24 13 F1SKJ8 Ssc.26154 20.91 15.89 22.65 14 F1SLA0 Ssc.279 8.71 0 4.89 15 Q9GJT2 Ssc.217 7.45 0 2.32 16 F1RFH9 Ssc.55270 6.45 1.96 21.11 17 Q06AA5 Ssc.26272 6.28 0 2.32 18 F1S6Q7 Ssc:100523423 5.36 0 4.15 19 A1X898 Ssc.97027 4.49 0 2.47 20 F1RFU5 Ssc.3588 3.72 0 4.7 21 E7EBY5 Ssc.26469 3.69 2.39 4.3 22 Q2XQV4 Ssc.11147 3.26 3.59 4.95 23 I3LL15 Ssc.16302 2.63 1.78 4.37 24 F1SLR6 Ssc.5041 1.95 0 6.07 pI, isoelectric point of the protein; MW, molecular weight of the protein; Seq. Cov, percentage of sequence coverage; HQLD, high quality of longissimus dorsi muscles; LQLD, low quality of longissimus dorsi muscles. (1) UniProt, Accession number in the UniProt database. (2) UniGene, UniGene number from NCBI (National Center for Biotechnology Information) database. (3) Individual ion score, TurboSEQUEST or gMASCOT score. Table 4. Primer sequences used to generate templates for reverse transcription polymerase chain reaction Gene name Symbol GenBank ID Myogenic MyoD NM_010866 differentiation Myogenin Myog NM 031189 Glyceraldehyde-3-phosphate GAPDH NM 008084 dehydrogenase Gene name Primer sequence Size (5' [right arrow] 3') (bp) Myogenic F: GAT GGC ATG ATG GAT TAC AGC 528 differentiation R: GAC TAT GTC CTT TCT TTG GGG Myogenin F: GCT CAG CTC CCT CAA CCA G 424 R: ATG TGAATG GGG AGT GGG GA Glyceraldehyde-3-phosphate F: ACC ACA GTC CAT GCC ATC AC 452 dehydrogenase R: TAC AGC AAC AGG GTG GTG GA Figure 1. Protein profiles of high quality longissimus dorsi muscles (HQLD) and low quality longissimus dorsi muscles (LQLD) from Duroc pigs by image analysis. (A) The overall patterns of total protein bands from individuals. All gels were visualized by sliver staining. (B) Two different protein spots were identified by a mass spectrometric analysis. a *: MYBPC2, myosin binding protein C; b #: LDHA, lactate dehydrogenase A. B Band Accession UniGene Gene Protein MW Score no. ID name name (kDa) a * F1rH20 Ssc.83876 MYBPC2 Myosin 127.6 120.82 binding protein C b # P00339 Ssc.50275 LDHA Lactate 36.6 58.91 dehydrogenase A Figure 2. Ontological classifications of differentially regulated proteins in high quality longissimus dorsi muscles (HQLD) and low quality longissimus dorsi muscles (LQLD) from Duroc pigs. Of the total 24 identified proteins, 10 and 14 proteins were highly expressed in HQLD and LQLD, respectively. (A) The identified proteins were clustered into 7 categories based on information obtained from DAVID gene ontology (GO) database; (B) The identified proteins were clustered into 3 categories based on their molecular function; (C) The identified proteins were clustered into 5 categories based on their biological processes. A ATPase activity 19% oxidoreductase activity 13% cytoskeletal protein binding 13% actin binding 12% Structural consttuent of muscle 6% calcium ion binding 6% catalytic activity 31% B Actin binding 40% Structurral consituent of muscle 20% Cytoskeletal protein binding 40% C Cellublar metabolic process 26% Primary metabolic process 26% Catabolic process 18% Nitrogen compound metabolic process 19% Oxidation reduction 11% Note: Table made from pie chart.
Please note: Some tables or figures were omitted from this article.
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|Author:||Cho, Jin Hyoung; Lee, Ra Ham; Jeon, Young-Joo; Park, Seon-Min; Shin, Jae-Cheon; Kim, Seok-Ho; Jeong,|
|Publication:||Asian - Australasian Journal of Animal Sciences|
|Date:||Nov 1, 2016|
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