Introduction
Color and tenderness are the main quality attributes that determine consumers’ decisions to purchase and consume beef; thus, they play a significant role in the economics and sustainability of the beef industry (Suman and Joseph, 2013; Suman et al., 2023). Color influences consumers’ willingness to purchase beef at retail, whereas tenderness is determined at the eating time with more tender meat resulting in repetitive purchases (Picard and Gagaoua, 2020; Suman et al., 2023). Numerous studies have explored the proteome of beef to understand the underlying biochemical processes that determine color and tenderness (Nair et al., 2018; Bonnet et al., 2020; Gagaoua et al., 2020a; Antonelo et al., 2022). Notably, meat color and tenderness share several proteins and biological pathways in the skeletal muscle proteome, but the degree to which they are expressed and utilized in various functions differs (Gagaoua et al., 2020b; Picard and Gagaoua, 2020; Suman et al., 2023). The quantity of these proteins in the skeletal muscle proteome undergoes substantial and continuous changes throughout ante-, peri-, and postmortem meat production and processing phases (Carvalho et al., 2019; Picard and Gagaoua, 2020; Antonelo et al., 2022).
Dietary composition has been reported as a major determinant of meat proteome profile during the antemortem phase (Picard and Gagaoua, 2020; Antonelo et al., 2022; Suman et al., 2023). Dietary protein and energy contents dictate growth rate and glycogen reserves which are the main factors that influence changes in meat color and tenderness postmortem (Picard and Gagaoua, 2020; Antonelo et al., 2022). More so, dietary bioactive phytochemicals such as polyphenolic compounds can potentially be assimilated into the meat (Zhong et al., 2016; Orzuna-Orzuna et al., 2021) and tend to retard/inhibit enzyme activities involved in glycogen metabolism (i.e., glycogen phosphorylase and lactate dehydrogenase) (Kamiyama et al., 2010; Han et al., 2023) and myofibrillar protein degradation (i.e., calpains) (Louis et al., 2014), consequently altering meat color and tenderness postmortem (Purslow et al., 2021; Suman et al., 2023). Thus, assessing variations in the meat proteome profile of beef fed diets containing bioactive phytochemicals is paramount for high product quality.
Sorghum contains up to 30 g/kg dry matter (DM) tannins and it has been widely utilized in beef feedlot finisher diets to curb the ever-increasing prices of maize as an energy source (Mccuistion et al., 2019; Osman et al., 2022). Studies have reported variable color changes and increased shear force values when beef is finished with sorghum-based diets and attribute the changes to the effects of tannins on myofibrillar degradation, fat deposition, and oxidation (Zhong et al., 2016; Sun et al., 2018; Orzuna-Orzuna et al., 2021). However, little is still known about the biochemistry of underlying processes and the major proteins involved in meat color and tenderness changes when finisher diets containing sorghum are fed.
On one hand, meat color variations on the surface are a product of myoglobin redox forms (i.e., deoxymyoglobin, oxymyoglobin, and metmyoglobin) that are strongly linked to oxygen consumption and reductive enzyme activity which are influenced by pH in the postmortem muscle (Nair et al., 2018; Gagaoua et al., 2020b; Antonelo et al., 2022). On the other hand, meat tenderness is mostly influenced by structural and metabolic activities, reflecting muscle restructuring in response to proteolysis of muscle myofibrillar and cytoskeletal proteins, regulated by endogenous calcium-dependent calpain system postmortem (Zamaratskaia and Li, 2017; Picard and Gagaoua, 2020). To the authors’ knowledge, no study has explored the proteome changes resulting from finishing steers with sorghum-based diets. Thus, the current study objective was to identify proteins and biochemical pathways associated with beef color and tenderness from Angus steers fed graded levels of sorghum-based finisher diets.
Materials and Methods
Between February and June 2022, a feeding trial was executed at Mariendahl Research Farm, Cape Town, South Africa. Ethical approval for the care and use of animals was permitted by Stellenbosch University (ACU-2020-17090) as guided by South African National Standards (SANS 10386:2008).
Experimental diets, animal management, and design
Whole red grain sorghum was sourced from a commercial producer (AGT, Cape Town, South Africa) and milled through a 0.5 mm sieve. Three pelleted (5 mm × 30 mm; 45°C) maize-lucerne-based complete diets containing either 0 (SGD-0), 200 (SGD-200), or 400 (SGD-400) g/kg DM of sorghum grain substituting white maize grain sourced from Perdigon Proprietary Limited, Paarl, South Africa as a primary energy source were formulated by commercial feed producer. The diets were isoenergetic and met the nutritional requirements of growing steers (Tables 1 and 2; National Research Council, 2016). Though the diets were not isonitrogenous, findings from a companion study (Njisane et al., submitted) shows that protein intake was similar (P > 0.05) across diets. Twenty-one Angus steers (7 mo; 230 ± 28 kg) were purchased from a single commercial producer, and each steer was housed in an individual concrete floor pen (2 m × 4 m) covered with straw. The steers were adapted for 21 d followed by 90 d of feeding.
Sorghum inclusion level in the diet | |||
---|---|---|---|
Ingredients (g/kg DM) | 0 | 200 | 400 |
White maize | 400 | 200 | 0 |
Sorghum | 0 | 200 | 400 |
Wheat bran | 235.5 | 235.5 | 235.5 |
Lucerne hay | 110 | 110 | 110 |
Wheat straw | 90 | 90 | 90 |
Soybean meal | 75.6 | 75.6 | 75t.6 |
Molasses | 70 | 70 | 70 |
Feed lime | 13 | 13 | 13 |
Coarse salt | 2.7 | 2.7 | 2.7 |
Urea | 2 | 2 | 2 |
Vitamin-mineral premix* | 0.6 | 0.6 | 0.6 |
Ammonium sulfate | 0.5 | 0.5 | 0.5 |
Zinc amino acid complex | 0.1 | 0.1 | 0.1 |
The composition of the vitamin/premix was not included because of a non-disclosure agreement with the feed manufacturer.
Chemical composition (g/kg DM unless stated) | Maize | Sorghum | SEM1 | Inclusion level (g/kg DM) | P-value | |||
---|---|---|---|---|---|---|---|---|
0 | 200 | 400 | SEM1 | Diet | ||||
Dry matter (DM) | 875.3 | 871.2 | 1.84 | 887.7 | 890.7 | 891.0 | 0.65 | 0.001 |
Ash | 8.6 | 11.4 | 0.45 | 53.0 | 52.8 | 52.4 | 0.39 | 0.512 |
Crude protein (CP) | 49.3 | 69.6 | 0.90 | 97.6 | 106.7 | 111.9 | 0.80 | 0.001 |
Ether extract (EE) | 27.8 | 24.1 | 0.22 | 23.3 | 23.1 | 23.0 | 0.35 | 0.793 |
Neutral detergent fiber (aNDFom)2 | 76.6 | 94.7 | 7.53 | 182.6 | 194.2 | 195.6 | 3.63 | 0.045 |
Acid detergent fiber (ADFom)3 | 22.1 | 24.9 | 1.44 | 90.8 | 94.5 | 93.0 | 1.61 | 0.284 |
Lignin (sa)4 | 3.4 | 6.1 | 0.58 | 18.2 | 18.3 | 18.3 | 0.73 | 0.997 |
Metabolizable energy (MJ/kg)5 | 12.8 | 13.0 | 0.11 | 12.1 | 12.1 | 12.1 | 0.02 | 0.477 |
Non-fibrous carbohydrates (NFC)6 | 794.0 | 791.4 | 8.28 | 643.5 | 623.2 | 617.3 | 3.88 | 0.001 |
Total phenols (g GAE/kg DM)7 | 0.7 | 1.0 | 0.02 | 1.6 | 1.6 | 1.9 | 0.03 | 0.001 |
Tannins (g GAE/kg DM)7 | 0.5 | 0.9 | 0.03 | 1.1 | 1.1 | 1.2 | 0.03 | 0.007 |
Proanthocyanidin (g GAE/kg DM)7 | 0.1 | 0.3 | 0.01 | 0.5 | 0.7 | 1.0 | 0.08 | 0.001 |
Fatty acids (g/100 g total FA) | ||||||||
C16:0 | 13.9 | 15.1 | 0.11 | 17.7 | 18.2 | 22.0 | 0.13 | 0.001 |
C18:0 | 2.5 | 1.4 | 0.03 | 2.9 | 2.8 | 2.5 | 0.03 | 0.001 |
C18:1n-9 | 30.4 | 28.7 | 0.08 | 25.5 | 23.3 | 22.4 | 0.12 | 0.001 |
C18:2n-6 | 50.8 | 51.7 | 0.12 | 50.7 | 50.8 | 49.5 | 0.11 | 0.001 |
C18:3n-3 | 0.8 | 1.6 | 0.02 | 2.5 | 2.9 | 3.1 | 0.03 | 0.001 |
All chemical analyses were analyzed in triplicate with 5 replicates per sample.
SEM: Standard error of means.
aNDFom: Neutral detergent fiber analyzed with a heat-stable amylase and reported without ash.
ADFom: Acid detergent fiber reported without ash.
Lignin (sa.): Lignin analyzed by solubilization of cellulose with sulfuric acid.
Calculated according to (Freer et al., 2019).
Non-fibrous carbohydrates: calculated as: 1000 − (aNDFom + crude protein + ether extract + ash; g/kg).
GAE: Gallic acid equivalent.
The table components listed mirror the proportions reported by Njisane et al. (Submitted).
Slaughter procedures and meat sampling
The steers were slaughtered at a commercial abattoir, 64 km from the experimental farm. During slaughter, steers were stunned using a non-penetrating captive-bolt and exsanguinated according to South African meat law (South African Government Gazette, 2000). Twenty-four h postmortem, the pH of all carcasses was measured using a mobile pH meter with a built-in Pt1000 temperature sensor for automatic temperature compensation (CrisonTM pH meter PH 25+, Lasec, South Africa) in the 12th and 13th right rib region. Then, the left longissimus thoracis et lumborum (LTL) muscle was removed from each carcass from the 9th to 13th rib. Thereafter, a two-gram cube was sampled from 3 loins per treatment, dipped in liquid nitrogen, and stored (−80 °C) in 15 ml tubes until proteomic analysis.
Color and shear force assays
Muscle color samples were allowed to bloom for 30 min, and 3 readings were taken per sample. Color coordinates (L*, lightness; a*, redness; b*, yellowness) were measured using a BYK-209 Gardner GmbH (Gerestried, Germany) colorimeter set to sample mode and calibrated with D65/10° against black and white tiles using observer settings and an 11-mm diameter aperture (AMSA, 2012). Warner-Bratzler shear force (WBSF) was determined using a ≈100 g meat sample cooked in a water bath at 80°C to an internal temperature of 75°C (AMSA, 2015). A thermocouple probe affixed onto a digital monitor (Testo 176T4, South Africa) was injected into the center of an individual sample (n = 5) to monitor internal temperature throughout the cooking process.
Proteomic characterization
Sample preparation, protein extraction and quantification. Frozen samples were ground into a fine powder using liquid nitrogen in a stainless-steel blender. The ground material (0.5 g) was resuspended in 1 mL extraction buffer (4 M Urea, 2 M Thiourea; 2.5 mM Ethylenediaminetetraacetic acid [EDTA]; 5 mM 1,4 Dithiothreitol [DTT]; 2% glycerol), thoroughly vortexed for 30 s, incubated 40 min at −20°C, and centrifuged at 15,000 × g for 20 min at 4°C. The supernatant containing the protein extract was transferred to clean tubes, and protein concentration was quantified using the Bradford assay with bovine serum albumin as a standard (Kruger, 2009). All the samples were extracted in triplicate.
SDS-PAGE protein visualization and quantitation. The sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) protocol was deployed to determine the quality and purity of the extracted proteins. Briefly, proteins (30 μg) were prepared and incubated as described in Mahlare et al. (2023). Proteins were heated at 70°C for 10 min and resolved as described by Mahlare et al. (2023). Following a 12% SDS-PAGE gel electrophoresis, proteins were visualized using Coomassie brilliant blue stain, and the gels were also processed as defined by Mahlare et al. (2023). Protein expression densitometric analysis of bands was performed using AlphaEase FC software (AlphaImager™ IS-2200 for Windows 2000/XP; Version 4), and default background subtraction for relative intensity correction was activated to only record analyte signals. The protein band intensities were expressed as integrated density values (IDV), presented as averages of 3 technical replicates.
In-gel digest, peptide extraction, and clean-up. Protein bands of interest were excised excluding strongly stained bands (Figure 1), and gel lanes of interest were uniformly cut into smaller gel cubes (≈ 1.0 mm × 1.0 mm) using a surgical blade and an A4 cutting board with a 20 cm aluminum ruler, and de-stained using 50% acetonitrile in 100 mM Ammonium Bicarbonate (NH4HCO3) until clear, and dehydrated with 100% acetonitrile for 5 min, with shaking. Dehydrated gel cubes were then reduced in 2 mM tris 2-carboxyethyl phosphine (TCEP) in 25 mM NH4HCO3 at room temperature (RT) for 15 min. Alkylation was conducted with 20 mM iodoacetamide in 25 mM NH4HCO3 for 30 min in the dark at RT. Following this, the gel cubes were dehydrated with 100% acetonitrile before rehydration with trypsin solution (10 ng/μl in 25 mM NH4HCO3) for 45 min at 4°C. After rehydration, excess trypsin solution was aspirated, and the gel cubes incubated in 50 μl 25 mM NH4HCO3 to enable overnight digestion at 37°C. Peptides were extracted from the gel cubes with 100 μl milli Q water by vortexing for 45 min. The supernatant was transferred to 1.5 ml Lo-bind Eppendorf tubes and the extracts dried down in a Centrivap Benchtop Vacuum Concentrator (Centrivap; Labconco Corporations, Kansas City, MO, USA) at RT before resuspension in 0.1% formic acid (FA). Samples were further purified and desalted as described by Mahlare et al. (2023) with slight modification. StageTips were conditioned with 10 μL of acetonitrile and equilibrated using 10 μL Buffer A (2% ACN/0.1% FA). Samples were then loaded onto and passed through the StageTip once before the tip was washed using 10 μL Buffer A. Peptides were eluted in 10 μL Buffer B (50% ACN/0.1% FA) and the peptide extracts pooled before the eluates were evaporated in a Centrivap at RT. Before liquid chromatography analysis, the dried peptide eluates were reconstituted in 15 μl Buffer A for liquid chromatography analysis.
Liquid chromatography with tandem mass spectrometry. The applied liquid chromatography with tandem mass spectrometry (LC-MS/MS) proteomic investigation was adapted from Hooijberg et al. (2018). The detailed procedures employed for peptide separation, protein quantification and characterizing, respectively achieved by liquid chromatography and mass spectrometer, are described in Mahlare et al. (2023). Briefly, peptide separation was initiated using loading solvents (Solvent A: 2% acetonitrile: water, 0.1% FA; Solvent B:100 acetonitrile: water, respectively) to deposit the samples into the trap column then onto the analytical column, and chromatography was performed at 40°C (Thermo Scientific UltiMate 3000 HPLC; Thermo Scientific, Rockford, IL, USA). The outflow was emitted onto the MS (Thermo Scientific Fusion MS:Nanospray Flex ionization source; Thermo Scientific, Rockford, IL, USA) for quantifying and characterizing, and the data attained as a weighted average of the mass peak (centroid mode).
Data processing, protein identification, and bioinformatics analysis. The raw data files were exported using Thermo Proteome Discoverer 1.4 (2012 Thermo Fisher Scientific Inc., Thermo Scientific, United States), and the Sequest and Amanda algorithms were applied for further processing. The resultant files were interrogated with reference to the Universal Protein (uniport) “Bos Taurus reviewed” concatenated database as detailed in Mahlare et al. (2023). Further validation was achieved in Scaffold Q+ (Settings: 95% Protein identification probability, 1% false discovery rate [FDR] protein threshold, 2 minimum number of peptides; www.proteomesoftware.com; accessed 14 August 2023). The functions of the identified proteins were assessed by mapping to Uniprot Resource (https://www.uniprot.org/id-mapping; accessed 14 August 2023). The bioinformatics webtool was used to visualize the common proteins identified in each diet (http://bioinformatics.psb.ugent.be/webtools/Venn/; accessed 14 August 2023).
Gene ontology (GO) and annotation enrichment analysis were done using the GO resource (http://geneontology.org/; accessed 14 August 2023), Panther classification system (https://pantherdb.org/; accessed 14 August 2023), String (https://string-db.org/; accessed 14 August 2023), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Fisher’s exact test was applied to determine the significance level of the protein enrichment of a specified GO term (FDR; P < 0.05). For protein-protein interactions (PPI), default settings (i.e., medium confidence of 0.4 and active interaction sources: text-mining, experiments, databases, co-expression, neighborhood, gene fusion, and co-occurrence) were used. The PPI networks were further clustered using the Markov cluster algorithm (MCL), with the inflation parameter set at 2 and PPI enrichment value at P < 0.05, while also retaining the floating proteins. To categorize the proteins intrinsic in beef tenderness and color development, the identified protein gene names were compared with published literature data for tenderness and color elaborated by Picard and Gagaoua (2020) and Gagaoua et al. (2020b), respectively.
Statistical analysis
The GLIMMIX procedure of SAS (version 9.4; SAS Institute Inc. Cary, NC, USA) was used to analyze physical attribute data with diet as fixed effect and animal a random factor. All data were subjected to the Shapiro-Wilk test (Shapiro & Wilk, 1965) for normality. A Tukey’s test was used to qualify the least-squares means as significantly different at P ≤ 0.05 and tendencies at 0.05 < P ≤ 0.10.
Results
Physical attributes, proteomic bioinformatics, and protein expression
The inclusion of sorghum in beef finisher diets exhibited a tendency (P = 0.083) to increase ultimate pH and linearly increased (P < 0.05) WBSF values but had no effect (P > 0.05) on color (Table 3). Protein loading appeared consistently even, with no visible protein streaking in the meat protein extracts (Figure 1). The explored data incorporate details of the molecular weight and the quantity of protein extract of each treatment. The molecular weight of the protein bands ranged between 10 to 250 kDa for all the treatment extracts. Myosin heavy chain (MHC; ≈230 kDa) and actin (≈42 kDa) were the most dominant bands across all treatments. The intensity protein bands were similar (P > 0.05) across diets as shown by the IDV and area (Figure 1).
Inclusion level (g/kg DM) | SEM | P-value | |||
---|---|---|---|---|---|
Parameters | 0 | 200 | 400 | ||
Ultimate pH | 5.7 | 5.9 | 5.8 | 0.04 | 0.082 |
Lightness (L*) | 41.6 | 41.1 | 40.6 | 0.58 | 0.510 |
Redness (a*) | 14.6 | 14.3 | 14.6 | 0.47 | 0.931 |
Yellowness (b*) | 12.4 | 12.0 | 12.4 | 0.34 | 0.592 |
WBSF (N) | 55.8b | 60.6ab | 65.2a | 2.18 | 0.013 |
SEM, standard error of means; WBSF, Warner-Bratzler shear force.
Means within a row with different superscripts are different (P < 0.05).
A total of 692 bovine proteins were identified, and 108 were common to all diets, while 74, 60, and 56 were respectively unique to treatments SGD-0, SGD-200, and SGD-400 (Figure 2). Of 108 common proteins, 11 were differentially expressed of which 7 edit to 8 (PYGM, PYGM, MYH1, MYH8, HSPA8, CAPZB, HSPB6, and PEBP1) are associated with both tenderness and color while 4 edit to 3 (PARP6, HSPOAA1, and GYS1) are only associated with color (Table 4). A total of 8 tenderness-regulating proteins were identified to be unique to diets, with 3 for SGD-0 (RABGGTA, HSPA5, and APOBEC2), 2 for SGD-200 (MYL3 and YWHAE), and 3 for SGD-400 (HSPA9, PDIA3, and ANKRD2). A sum of 9 color-regulating proteins were unique to diets, with 3 in SGD-0 (OXCT1, HSPA5, and MYH7), 4 in SGD-200 (MYH2, PDHX, LAP3, and P4HB), and 2 in SGD-400 (MYH1 and HSPA9). Of the 11 differentially expressed proteins (Table 4), 6 (MYH8, MYH1, HSP90AA1, GSY1, HSPB6, and HSPA8) were downregulated (P < 0.05) by sorghum diets (SGD-200 and SGD-400). Proteins PARP6 and PYGM were only downregulated (P < 0.05) in SGD-400. The CAPZB was only upregulated (P < 0.05) in SGD-400, while PEBP1 was upregulated in sorghum diets.
Accessions | Entry | Gene names | Protein names | Mass (kDa) | Inclusion level (g/kg DM) | ||
---|---|---|---|---|---|---|---|
0 | 200 | 400 | |||||
Differentially expressed proteins associated with tenderness and color | |||||||
A0A4W2ERW4_BOBOX | A0A4W2ERW4 | PARP6 | Multifunctional fusion protein (polymerase & pyruvate kinase) | 102.5 | Up | Up | Down |
B0JYK6_BOVIN | B0JYK6 | PYGM | Alpha-1,4 glucan phosphorylase | 97.3 | Up | Up | Down |
PYGM_BOVIN | P79334 | PYGM | Glycogen phosphorylase, muscle form (myophosphorylase) | 97.3 | Up | Up | Down |
A0A3Q1LYQ9_BOVIN | A0A3Q1LYQ9 | MYH1 | Myosin heavy chain 1 | 220.8 | Up | Down | Down |
A0A4W2C7P3_BOBOX | A0A4W2C7P3 | MYH8 | Myosin-8 | 222.8 | Up | Down | Down |
A0A4W2FK20_BOBOX | A0A4W2FK20 | HSPA8 | Heat shock protein family A (Hsp70) member 8 | 72.3 | Up | Down | Down |
A0A4W2C816_BOBOX | A0A4W2C816 | HSP90AA1 | Heat shock protein 90 alpha family class A member 1 | 89.1 | Up | Down | Down |
PEBP1_BOVIN | P13696 | PEBP1 | Phosphatidylethanolamine-binding protein 1 (PEBP-1) | 21.0 | Down | Up | Up |
A0A4W2CJ22_BOBOX | A0A4W2CJ22 | GYS1 | Glycogen synthase | 76.5 | Up | Down | Down |
A0A3Q1LZP7_BOVIN | A0A3Q1LZP7 | CAPZB | F-actin-capping protein subunit beta | 32.2 | Down | Down | Up |
A0A0U2YDA7_BOBOX | A0A0U2YDA7 | HSPB6 | Heat shock protein | 17.5 | Up | Down | Down |
Uniquely expressed proteins associated with beef tenderness | |||||||
PGTA_BOVIN | Q5EA80 | RABGGTA | Geranylgeranyl transferase type-2 subunit alpha | 64.9 | Unique | ||
A0A4W2EIV7_BOBOX | A0A4W2EIV7 | HSPA5 | Heat shock protein 70 family protein 5 | 72.4 | Unique | ||
ABEC2_BOVIN | Q3SYR3 | APOBEC2 | Probable C->U-editing enzyme APOBEC-2 (mRNA cytosine deaminase 2) | 26.0 | Unique | ||
A0A4W2IAK2_BOBOX | A0A4W2IAK2 | MYL3 | Myosin light chain 3 | 27.2 | Unique | ||
1433E_BOVIN | P62261 | YWHAE | 14-3-3 protein epsilon (14-3-3E) | 29.2 | Unique | ||
A0A4W2FQ02_BOBOX | A0A4W2FQ02 | HSPA9 | Heat shock 70 kDa protein 9 | 71.2 | Unique | ||
A0A4W2CAQ4_BOBOX | A0A4W2CAQ4 | PDIA3 | Protein disulfide-isomerase | 51.9 | Unique | ||
A0A4W2FD13_BOBOX | A0A4W2FD13 | ANKRD2 | Ankyrin repeat domain 2 | 39.3 | Unique | ||
Uniquely expressed proteins associated with beef color | |||||||
A0A3Q1LIX4_BOVIN | A0A3Q1LIX4 | OXCT1 | Succinyl-CoA:3-ketoacid-coenzyme A transferase | 56.8 | Unique | ||
A0A4W2EIV7_BOBOX | A0A4W2EIV7 | HSPA5 | 78 kDa glucose-regulated protein | 72.4 | Unique | ||
F1MM07_BOVIN | F1MM07 | MYH7 | Myosin heavy chain 7 | 223.2 | Unique | ||
A0A4W2HXW2_BOBOX | A0A4W2HXW2 | MYH2 | Myosin-2 | 223.3 | Unique | ||
A0A3Q1LKL1_BOVIN | A0A3Q1LKL1 | PDHX | Dihydrolipoamide acetyltransferase | 50.8 | Unique | ||
AMPL_BOVIN | P00727 | LAP3 | Cytosol aminopeptidase (leucine aminopeptidase 3; LAP-3) | 56.3 | Unique | ||
A0A4W2FY74_BOBOX | A0A4W2FY74 | P4HB | Prolyl 4-hydroxylase | 63.3 | Unique | ||
MYH1_BOVIN | Q9BE40 | MYH1 | Myosin-1 (myosin heavy chain 1) | 223.0 | Unique | ||
A0A4W2FQ02_BOBOX | A0A4W2FQ02 | HSPA9 | Stress-70 protein (heat shock 70 kDa protein 9) | 71.2 | Unique |
Gene ontology functional and pathway enrichment analyses
The differentially expressed as well as diet-unique proteins for tenderness and color were clustered into biological processes, molecular function, and cellular component (Figure 3). The cellular anatomical entity, cellular process, catalytic activity, and binding activities dominated the biological function, molecular function, and cellular component GO clusters, in that order (Figure 3). The GO clustering of diet-specific proteins revealed that the biological process function group was dominated by cellular process with SGD-0, SGD-200, and SGD-400 having 38%, 36%, and 38%, respectively (Figure 4). The binding (48%, 44%, and 53%, respectively) and catalytic activities (40%, 42%, and 37%, respectively) were highly represented in the molecular functions (Figure 4). Cellular anatomical entity (72%, 71%, and 81%, respectively) predominated the cellular component category (Figure 4). The pathways were dominated by HSPA8, HSPA9, HSPA5, and YWHAE clustered under Parkinson disease (Figure 5). Chaperones contributed 36% of the protein classes with differentially expressed HSPB6, HSP90AA1, HSPA8, and diet-specific HSPA5 (SGD-0), P4HB (SGD-200), PDIA3, and HSPA9 (SGD-400; Figure 5). Cytoskeletal proteins (32%) included differentially expressed MYH1 and CAPZB, as well as MYH7 (SGD-0), MYH2, and MYL3 (SGD-200; Figure 5). Metabolic interconversion enzymes (18%) included differentially expressed PYGM along with RABGGTA and OXCT1 (SGD-0), and PDHX (SGD-200; Figure 5). The extensive pathways were cytoskeletal regulation by Rho GTPase (16%), signaling pathway (16%), inflammation mediated by chemokine and cytokine signaling pathway (16%), and nicotinic acetylcholine receptor signaling pathway (16%).
Protein-protein interaction networks and KEGG pathways
The PPI revealed that GYS1, PYGM, MYH1 and MYH8 were interconnected within the energy metabolism and muscle activity pathway, while HSPB6, HSPA8, HSP90AA1, and CAPZB were interlinked in the cellular response to stress and modification pathways (Figure 6A). The aforementioned pathways remained distinct when PPI of differentially expressed and diet-unique proteins were analyzed (Figure 6B, 6C, and 6D) with only 2 extra pathways (muscle contraction: MYH2, MYL3, MYH1, and MYH8; uncategorized network: PARP6 and PDHX) in the SGD-200 diet. Three enzymes (PYGM, GYS1, and PARP6) were identified to be linked to the glycolytic pathway, with PYGM and GYS1 being involved in glucose metabolism (Figure 7A) and PARP6 in the pyruvate pathway (Figure 7B). Two enzymes are involved in protein degradation; LAP3 breaks down peptides to proline (Figure 7C) and OXCT1 is linked to the interconversion of acetoacetate to acetoacetyl-Coa in the degradation of valine, leucine, and isoleucine (Figure 7D).
Discussion
The downregulation of structural proteins such as heavy chain myosin (MYH1 and MYH8) in SGD could be ascribed to the over-expression of CAPZB which provides binding sites for μ-calpain that breaks down myosin chains (Picard and Gagaoua, 2017; Bhat et al., 2018; Gagaoua et al., 2021). The over-expressed CAPZB in sorghum diets might be accredited to the slightly lower calcium content in sorghum (9.9 g/100g) vs maize (10.7 g/100g) that reduces the abundance of phosphatidylinositol (4,5) bisphosphate, which inhibits CAPZB capping activity (Maiti and Bamburg, 2013; Jocelyne et al., 2020; Katan and Cockcroft, 2020). Thus, the downregulation of structural proteins (MYH1 and MYH8) in sorghum diets could be indicative of less tender LTL beef. Specifically, MYH1 was described as a good biomarker for tenderness in the more glycolytic muscles such as the LTL from Angus cattle and young bulls (Gagaoua et al., 2020a; Picard and Gagaoua, 2020; Gagaoua et al., 2021). Structural proteins in general have been identified as the key contributors to beef tenderness development through activating proteolysis, weakening and/or loosening the myofibrillar structure and cytoskeletal proteins (Gagaoua et al., 2020a; Gagaoua et al., 2021; Ding et al., 2022). Structural proteins are interlinked through tropomyosin-actin and actomyosin interactions in striated muscle. Thus, denaturing myosin heads or troponin destroys the PPI, breaking the thin filaments in the sarcomeric I band, where proteolysis is initiated (Gagaoua et al., 2020a; Ding et al., 2022). MYL3 contractile protein in SGD-200 could be associated with less tender beef as it indicates less myosin head enzymatic degradation (Franco et al., 2015; Ding et al., 2022).
Glycolytic enzymes have been identified as the second major contributor to beef tenderness and color (Gobert et al., 2014; Gagaoua et al., 2021; Suman et al., 2023). Glycolytic enzymes are involved in the generation of ATP and lactic acid from glycogen thus affecting the rate of protein phosphorylation and pH decline, which directly or indirectly influence meat tenderness and color (Gagaoua et al., 2021; Suman et al., 2023). Generally, the differentially expressed glycolytic enzymes (i.e., PYGM: Glycogen phosphorylase; PARP6: polymerase and Pyruvate kinase; PEBP1: Phosphatidylethanolamine-binding protein 1; and GYS1: Glycogen synthase) are involved in the guanine nucleotide-binding protein (G-protein) pathway catalyzing and regulating metabolic processes. Thus, the lowered expression of GYS1 in both sorghum-based beef diets and PYGM and PARP6 in SGD-400 beef could be attributed to dietary tannins’ inhibitory effects on glycolytic protein expression and replenishment of glycogen reserves (Chung et al., 1998; Antonelo et al., 2022; Fang et al., 2022; Xu et al., 2022), which may result in less tender and darker meat. More so, the downregulation of PYGM reduces cell antioxidant capacity by limiting energy, which promotes the conversion of more glycolytic to slow glycolytic skeletal muscles, thereby reducing meat tenderness (Severino et al., 2022; Xu et al., 2022). The GYS1 protein has been positively associated with high pH, dark and less tender pork loin (Zuo et al., 2007; Lei et al., 2015), but little is known regarding its association with beef quality, and this merits investigation. The abundance of PEBP1, a serine protease inhibitor and calpain substrate in SGD-400, suggests a decrease in tenderness, lightness, and redness of beef though the mechanism of action is still unexplored (Mahmood et al., 2018; Gagaoua et al., 2020b; Severino et al., 2022). Of importance, PPI networks did not show any interaction between PEBP1 and other proteins and this could limit its influence on either color or tenderness of beef.
The PARP6 metabolic enzyme, associated with the irreversible conversion of phosphoenolpyruvate to pyruvate, was downregulated in the SGD-400 diet. The reduction in PARP6 could indicate reduced pyruvate accumulation, which is positively correlated with redness stability in beef (Ramanathan et al., 2012; Yang and Liu, 2021). Pyruvate achieves this by increasing meat acidity thus limiting accumulation of metmyoglobin and stabilizing myoglobin redox forms (Ramanathan et al., 2011; Yang and Liu, 2021). However, accumulation of pyruvate postmortem is limited as it is rapidly converted to lactic acid (Zelentsova et al., 2016). Hence, the association of PARP6 to beef color is doubtable and this could further be explained by its lack of connection with other proteins in the PPI network reported in the current study. Dihydrolipoamide acetyltransferase (PDHX) and proteolytic enzyme (LAP3) unique to SGD-200 diet, which degrades and hydrolyses peptides to proline, is positively associated with beef tenderness and redness (Wu et al., 2015; Wu et al., 2016; Malheiros et al., 2021).
The downregulation of Hsp70 (HSPA8), Hsp90 (HSP90AA1), and small heat shock protein (sHsp: HSPB6) in the sorghum-based beef and the presence of Hsp70 (HSPA9) and co-chaperones (PDIA3, YWHAE, and P4HB) in the SGD-400 could be associated with tender meat. This is due to the ability of HSP to inhibit myofibrillar protein degradation by limiting chaperone activities, thus reducing tenderness (Picard et al., 2014; Oh et al., 2019; Gagaoua et al., 2020a). Numerous studies have reported an increase in meat tenderness when HSP declined (Carvalho et al., 2019; Malheiros et al., 2021; Sentandreu et al., 2021). The downregulation of HSP in sorghum diets could be attributed to the enhanced antioxidative ability provided by tannins, thus reducing oxidative stress, which is a major precursor for HSP (Hu et al., 2022). All the differentially expressed HSP interacted with CAPZB in all diets, a structural protein abundant in the Angus breed, responsible for regulating actin myofilament contractility and thus tenderizing beef (Picard et al., 2014; Gagaoua et al., 2021). HSPA8 and HSPA9 are positively correlated with beef loin color traits such as redness and yellowness (Gagaoua et al., 2020b; Suman et al., 2023). However, HSPA8 and HSPA9 have a negative influence on beef lightness (L*) as they provide a protective activity on structural proteins including myosin (MYH and MYL) thereby reducing available disintegrated protein aggregates and free myowater (Gagaoua et al., 2020b; Pearce et al., 2011; Purslow et al., 2020). Hence, less light is allowed to scatter and reflect on the muscle.
Based on the present findings, differentially and uniquely expressed (DUE) structural proteins and glycolytic enzymes suggest that the inclusion of sorghum in beef finisher diets could be associated with less tender beef. Interestingly, DUE structural proteins and glycolytic enzymes results align with instrumental tenderness (i.e., WBSF values) results, confirming their role as key proteomic biomarkers of beef tenderness. The increase in instrumental tenderness with addition of sorghum to the diet could be linked to dietary polyphenols which exhibited the same trend. Polyphenols have been reported to inhibit calpains which are responsible myofibrillar protein degradation (Louis et al., 2014). However, downregulation of the DUE HSP and co-chaperones in the sorghum diets did not correspond with the instrumental tenderness, which could suggest that the expression of the former proteins was not high enough to elicit significant changes in beef tenderness. Of importance, the cytoprotective role of HSP in myofibrillar degradation generally relies on ATP generated by the glycolytic pathway (Grubbs et al., 2014; Picard et al., 2018; Carvalho et al., 2019). This further confirms that structural and glycolytic proteins are the main contributors to beef tenderness and HSP are not a reliable proteomic biomarker for tenderness. With regards to color, DUE structural proteins, glycolytic enzymes, and HSP all indicate that feeding sorghum diets could increase beef redness, but their expression was not strong enough to prompt changes in instrumental redness. Thus, it may not influence beef purchase decisions at the point of purchase.
Conclusions
DUE structural proteins, glycolytic enzymes, and HSP suggest that the inclusion of sorghum beef finisher diets could produce beef of less desirable tenderness. The study findings could be applied to cattle nutritional programs to produce beef of desirable tenderness. Further research is important to determine if the changes in DUE proteomic biomarkers of beef color and tenderness found when feeding sorghum diets would positively influence consumers’ purchase and repurchase decisions.
Acknowledgments
Research funds and author Yonela Z. Njisane’s postdoctoral fellowship were funded by the Department of Trade, Industry and Competition (DTIC)’s Technology and Human Resources for Industry Programme (THRIP) administered by Chumani Water Solutions. Dr. L. Husselmann and Mr. Xola Bomela are acknowledged for their assistance with proteomics bioinformatics training and procurement of feed resources, respectively.
Conflict of interest statement: The authors have no conflicts of interest to declare.
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