# Postmortem proteolysis and its indicators vary within bovine muscles: Novel insights in muscles that differ in their contractile, metabolic, and connective tissue properties

Chandler Stafford, Mohammed Alruzzi, Mohammed Gagaoua, Sulaiman Matarneh

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## To cite this version:

Chandler Stafford, Mohammed Alruzzi, Mohammed Gagaoua, Sulaiman Matarneh. Postmortem proteolysis and its indicators vary within bovine muscles: Novel insights in muscles that differ in their contractile, metabolic, and connective tissue properties. Meat Science, 2025, 221, pp.109718. 10.1016/j.meatsci.2024.109718. hal-04821220

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Postmortem proteolysis and its indicators vary within bovine muscles: Novel insights in muscles that differ in their contractile, metabolic, and connective tissue properties

Chandler D. Stafford<fnref n="1" />, Mohammed A. Alruzzi<fnref n="1" />, Mohammed Gagaoua<fnref n="2" />, Sulaiman K. Matarneh<fnref n="1" />, *

<footnote n="1">¹ Department of Nutrition, Dietetics and Food Sciences, Utah State University, Logan, UT 84322, United States</footnote>

<footnote n="2">² PEGASE, INRAE, Institut Agro, 35590 Saint-Gilles, France</footnote>

<footnote>*Corresponding author</footnote>

<footnote>E-mail address: sulaiman.matarneh@usu.edu (Sulaiman K. Matarneh)</footnote>
**Abstract**

This study assessed postmortem proteolysis over 14 d in bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles. First, the metabolic, contractile, and connective tissue properties were characterized to establish their intrinsic differences. The MS contained the highest levels of oxidative markers and myosin heavy chain-I (MyHC-I), whereas the CT possessed the greatest glycolytic capacity, MyHC-IIx, and connective tissue proteins (*P* < 0.05). The LT had intermediate metabolic characteristics, a heterogeneous mixture of MyHC isoforms, and the lowest amount of connective tissue proteins (*P* < 0.05), confirming the muscles' intrinsic divergence. Proteolytic analysis revealed increased desmin and slow troponin-T (TT-slow) degradation, with a higher 110 kDa band intensity in the MS than in the CT (*P* < 0.05). In comparison, the CT exhibited greater TT-fast degradation and higher 30 kDa fragment intensity (*P* < 0.05). The LT demonstrated the greatest overall proteolysis, indicated by increased TT-fast and TT-slow degradation and the highest intensity of the 30 kDa band (*P* < 0.05). This is likely due to protease activity, as the LT and MS exhibited more calpain-1 autolysis and less calpastatin abundance than the CT (*P* < 0.05). However, caspase-3 activity was highest in the MS and lowest in the LT. A principal component analysis incorporating proteolytic indicators further demonstrated the distinct proteolytic profiles in the three muscles. Overall, findings suggest that the progression of postmortem proteolysis is muscle-specific and that a single proteolytic indicator does not sufficiently describe proteolysis when comparing muscles differing in contractile and metabolic properties.

**Keywords:** Beef; Muscle fiber types; Postmortem proteolysis; Proteolytic fragments; Calpain-1; Caspase-3.
# 1. Introduction

The skeletal muscle of adult cattle is composed of an assortment of muscle fibers that are classified based on the predominant myosin heavy chain (MyHC) isoforms (I, IIa, and IIx), which determine the contractile properties of the muscle (slow or fast) and its primary metabolism (glycolytic or oxidative) (Picard & Gagaoua, 2020). Slow-contracting fibers (type I) primarily rely on oxidative metabolism and typically demonstrate higher concentrations of oxidative enzymes (Rivero, Talmadge, & Edgerton 1998). Comparatively, fast-contracting fibers (type IIA and IIX) have a mixed oxido-glycolytic energy production and mostly correlate with higher glycolytic enzyme concentrations (Alev et al., 2009; Quiroz-Rothe & Rivero, 2004). However, type IIX fibers are more glycolytic than IIA. Muscles with heterogeneous fiber-type compositions perform as multifunctional tissues capable of prolonged bouts of activity in addition to quick movements (Schiaffino & Reggiani, 2011). Moreover, the variability in muscle fiber composition causes notable muscle-specific changes during the postmortem period and largely determines the quality of the meat (Choi & Kim, 2009; Lee, Joo, & Ryu, 2010; Matarneh, Silva, & Gerrard, 2021; Picard & Gagaoua, 2020).

Tenderness is a crucial eating quality attribute that is closely tied to the overall eating experience and satisfaction when consuming meat, especially beef (Destefanis, Brugiapaglia, Barge, & Dal Molin, 2008; Miller, Carr, Ramsey, Crocket, & Hoover, 2001; Santos et al., 2021). However, tenderness remains challenging to control and predict due to numerous influential factors (Koohmaraie, 1996; Warner et al., 2022). Indeed, postmortem proteolysis is the primary contributor to meat tenderness development, mainly through the action of calcium-dependent calpains and, to a lesser extent, the lysosomal cathepsins and the apoptotic caspases (Koohmaraie & Geesink, 2006; Kemp, Sensky, Bardsley, Buttery, & Parr, 2010; Ouali et al., 2013). In particular, calpain-1 is identified as the major contributor to postmortem proteolysis because the calcium
concentration threshold required for its activation is quickly achieved postmortem (Koohmaraie, 1996), unlike calpain-2 (Goll, Thompson, Li, Wei, & Cong, 2003). On the other hand, the cathepsins' contribution to proteolysis postmortem is limited due to their entrapment inside the lysosome (Koohmaraie, 1994; Robert, Briand, Taylor, & Briand, 1999). Meanwhile, the caspases, particularly caspase-3, are closely related to mitochondrial dysfunction (Dang et al., 2022) and have been shown to elicit the breakdown of key cytoskeletal proteins (Huang, Huang, Zhou, Xu, & Xue, 2011). Interestingly, the rate and extent of postmortem proteolysis vary among different muscles (Koohmaraie, Seideman, Schollmeyer, Dutson, & Babiker, 1988; Ramos et al., 2021), suggesting that the mechanisms dictating its progression are muscle-dependent.

The relationship between postmortem proteolysis and muscle fiber type is complex and often contradictory due to the heterogeneity of skeletal muscles. It has been previously demonstrated that a more glycolytic muscle fiber profile is associated with increased postmortem proteolysis in beef *Longissimus* (Dang, Buhler, Thornton, Legako, & Matarneh, 2020), faster activation of calpain-1 (Dang et al., 2020), and faster initiation of proteolysis (Ouali, 1990). These findings suggest that glycolytic fibers may experience superior postmortem proteolysis. In contrast, however, oxidative muscle fibers also possess characteristics that are favorable for the progression of postmortem proteolysis. For instance, muscles composed predominantly of oxidative fibers typically have higher protein turnover rates *in vivo* (Armstrong & Laughlin, 1985; Goodman et al., 2011) and greater calpain-1 activities postmortem (Koohmaraie, 1992b). Oxidative muscles also demonstrate greater apoptotic potential due to a greater abundance of mitochondria (Picard & Gagaoua, 2020), which subsequently promotes more caspase-3 activity (Stafford et al., 2024). These conflicting findings suggest that the relationship between postmortem proteolysis and muscle fiber type composition is not fully understood, necessitating further
research. Additionally, elucidating the biochemical factors contributing to muscle-specific variations in postmortem proteolysis would help predict tenderness amongst different bovine muscles. Therefore, the current study assessed the progression of postmortem proteolysis in three bovine muscles possessing different intrinsic characteristics using traditional biochemistry and high-throughput proteomic methods.

# Materials and Methods

## 2.1. Muscle sample collection

All cattle used in this study were of similar genetic backgrounds and were raised under the same feeding and management conditions. Five steers (28 ± 1 month, 615 ± 18 kg body weight) were harvested at the Utah State University animal harvest facility using standard commercial procedures and in accordance with USDA inspection. Within 30 min of exsanguination, the *Longissimus thoracis* (LT), *Cutaneous trunci* (CT), and *Masseter* (MS) muscles were excised from one side of each carcass and fabricated into three portions. One portion of each muscle was cut into cubes and immediately snap-frozen under liquid nitrogen (0 d), while the other two portions were vacuum packaged and aged at 4 °C for 7 or 14 d. Following the respective aging period, each portion of tissue was cut and stored similarly to the 0 d samples.

## 2.2. pH evaluation

The pH of each sample was determined as described by Bendall (1973). In brief, tissue samples were powdered under liquid nitrogen and homogenized at 1:8 (w/v) in ice-cold buffer (5 mM iodoacetic acid and 150 mM KCl, pH 7.0) using a bead-beating homogenizer (TissueLyser LT, Qiagen, Hilden, Germany). Tissue homogenates were centrifuged at 17,000 ×g for 5 min at room temperature before being measured using a pH electrode coupled to an Orion Star A214 pH/ISE
benchtop meter (Thermo Scientific, Pittsburgh, PA, USA). The pH electrode was calibrated at room temperature prior to each use with Orion pH 4, 7, and 10 buffer solutions.

## 2.3. Protein extraction for SDS-PAGE and western blotting

Sample preparation for succinate dehydrogenase (SDH), lactate dehydrogenase (LDH), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), and myoglobin abundance was done as described by Ramos et al. (2020). In short, 0 d (30 min postmortem) muscle samples were homogenized 1:10 (w/v) in a solubilization buffer (100 mM Tris-base [pH 8.3], 10 mM EDTA, 10% [v/v] glycerol, 0.1% [v/v] 2-mercaptoethanol, and 2% [v/v] protease inhibitor cocktail [Cat# P8340, Millipore Sigma, St. Louis, MO, USA]) and incubated on ice for 20 min. Afterward, the samples were centrifuged at 20,000 ×g for 20 min at 4 °C. The resulting supernatants were collected, and protein concentration was determined using a Pierce BCA protein assay kit (Thermo Scientific, Rockford, IL, USA) following the manufacturer's instructions. The samples were then diluted with 5× Laemmli buffer (final concentration: 40 mM Tris-base, 100 mM DTT, 2% [w/v] SDS, 0.05% [w/v] bromophenol blue, and 2% [v/v] glycerol) to yield equal protein concentrations. The samples were then heated at 60 °C for 10 min, equilibrated to room temperature, and stored at −80 °C until loaded in gels.

For the analysis of calpain-1 autolysis, calpastatin abundance, the appearance of proteolytic fragments (110 and 30 kDa protein bands), and the degradation of desmin and troponin-T (TT) fast (TT-fast) and slow (TT-slow) isoforms, muscle tissue from all time points was powdered under liquid nitrogen and solubilized at a 1:10 ratio in a buffer containing 2 M thiourea, 8 M urea, 75 mM DTT, 3% (w/v) SDS, and 50 mM Tris-HCl (pH 6.8) using a bead-beating homogenizer (Warren, Krzesinski, & Greaser, 2003). The samples were heated at 60 °C for 10 min, centrifuged at 17,000 ×g at room temperature, and then the supernatants were transferred to new tubes. The protein
concentration of the supernatant was measured with an RC DC assay kit (BioRad Laboratories, Hercules, CA, USA), and samples were diluted to equal protein concentrations with the same solubilization buffer described above dyed blue with 0.05% (w/v) bromophenol blue. Samples were stored at -80 °C until separated using SDS-PAGE.

## 2.4. *Separation of the muscle protein extracts with SDS-PAGE and immunoblotting*

Samples were thawed at room temperature and heated at 60 °C for 5 min in a dry heating block prior to being loaded into self-cast polyacrylamide gels with the addition of a 10–250 kDa protein molecular weight standard (Cat #161-0374, Bio-Rad Laboratories, Hercules, CA, USA). Proteins were separated at room temperature in a Mini-ProTEAN Tetra electrophoresis cell (BioRad Laboratories, Hercules, CA, USA) and then transferred to nitrocellulose membranes and reversibly stained with Ponceau S to evaluate the total protein within each lane. Images of the stained membranes were captured using a UVP Chemstudio Imaging System and software (Analytik Jena, Upland, CA, USA). The membranes were then destained and blocked for 1 h at room temperature with a 1.5% (w/v) casein dissolved in phosphate-buffered saline and 0.1% (v/v) Tween-20 (PBS-T) and then incubated overnight at 4 °C with primary antibodies diluted with PBS-T. The primary antibodies were diluted as follows: desmin, 1:5000 (Cat# D1033, Millipore Sigma, St. Louis, MO, USA); TT-fast isoform, 1:20,000 (Cat# T6277, Millipore Sigma, St. Louis, MO, USA); TT-slow isoform, 0.25 µg/mL (Cat# CT3-c, Developmental Studies Hybridoma Bank, Iowa City, IA, USA); calpastatin, 1:2000 (Cat# MA3-944, Thermo Scientific, Rockford, IL, USA); calpain-1, 1:2000 (Cat# MA3-940, Thermo Scientific, Rockford, IL, USA); SDH, 1:2000 (Cat# 459200, Thermo Scientific, Rockford, IL, USA); GAPDH, 1:2000 (Cat# 437000, Thermo Scientific, Rockford, IL, USA); LDH, 1:5000 (Cat# NBP1-48336, Novus Biologicals, Littleton, CO, USA); and myoglobin, 1:750 (Cat# SC393020, Santa Cruz Biotechnology, Dallas, TX, USA). The following
morning, membranes were washed in PBS-T for 5 min 3 times and incubated with an HRP-
conjugated secondary antibody (Cat# 20401, Biotium Inc., Fremont, CA, USA) diluted 1:10,000
in PBS-T. Membranes were allowed to incubate at room temperature for 1 h and were subsequently
washed 3 more times with PBS-T. After washing, membranes were incubated with Immobilon
Western Chemiluminescent HRP Substrate (Cat# WBKLS0100, Millipore Sigma, Burlington,
MA, USA) for 3 min at room temp, and the visualization of bands was performed using the
previously mentioned imaging system.

Band intensities were quantified and normalized to their respective total protein intensities (acquired following Ponceau S staining). Calpain-1 autolysis was quantified by dividing the intensity of the 76 kDa band by the total signal intensity (sum of 80, 78, and 76 kDa bands). Desmin, TT-fast, and TT-slow degradation were evaluated by calculating the ratio of the degraded products divided by the total signal intensity (intact bands + degradation products). The intensity of the 135 kDa bands was used to quantify calpastatin abundance, while the 70, 35, 37, and 17 kDa bands were used to quantify SDH, LDH, GAPDH, and myoglobin abundances, respectively.

2.5. *Analysis of the appearance of the 110 and 30 kDa proteolytic fragments*

The appearance of proteolytic products over time was evaluated using the 110 and 30 kDa protein
bands as described by Gagaoua, Troy, & Mullen (2021). Samples were thawed at room
temperature and subsequently heated at 60 °C for 5 min in a dry heating block prior to separation.
Then, 21 µg of protein was loaded into each well of a 12% self-casted one-dimensional gel and
was subjected to SDS-PAGE separation. The same protein molecular weight standard mentioned
above was included in the first well of each gel for proper protein weight determination.
Subsequently, the gels were stained with a Coomassie Brilliant Blue G-250 solution (45% [v/v]
methanol, 10% [v/v] acetic acid, and 0.1% [w/v] Coomassie Brilliant Blue G-250) for 4 h at room
temperature, the gels were placed in a destaining solution (10% acetic acid [v/v] and 20% [v/v] methanol) until the protein bands were clearly observed. Images of the gels were captured, and the intensity of the 110 kDa and 30 kDa proteolytic fragment bands was determined and expressed in arbitrary units.

## 2.6. Myosin heavy chain separation

MyHC isoform separation was carried out according to the methods of Scheffler, Leitner, & Wright (2018) and Talmadge & Roy (1993), with some modifications. Approximately ~ 100 mg of powdered tissue was weighed and diluted in 1 mL of extraction buffer containing 10 mM sodium phosphate (pH 7.0) and 10% (w/v) SDS. Samples were homogenized and centrifuged at 10,000 ×g for 10 min at room temperature. Supernatants were transferred to new tubes, and the protein concentration was determined using a Pierce BCA assay kit. Samples were then diluted to 1 mg/mL with a high-glycerol Laemmli buffer consisting of 83.5 mM Tris (pH 6.8), 2.67% (w/v) SDS, 6.7% (v/v) β-mercaptoethanol, 50% (v/v) glycerol, and 0.01% (w/v) bromophenol blue. Samples were heated at 95 °C for 5 min, allowed to cool down, and stored at -80 °C.

Prior to protein separation, samples were thawed at room temperature and then heated at 60 °C for 5 min before being loaded into a high-glycerol polyacrylamide gel. The gels were run for 48 h at 70 v in a cold room using an upper chamber buffer of 150 mM glycine, 0.1% (w/v) SDS, and 100 mM tris base. The lower chamber buffer was the same as the upper chamber but diluted 1:1 with distilled water. Following separation, the gels were washed with deionized water for 5 min, stained with Coomassie Brilliant Blue G-250 solution, and then destained as described previously. The gels were subsequently washed with deionized water for 5 min before imaging.
MyHC isoforms (I, IIa, or IIx) were quantified and expressed as a percentage of the total signal (intensity of MyHC type I + IIa + IIx).
## 2.7. Caspase-3 activity

The EnzChek Caspase-3 assay kit #1 (Molecular Probes, Invitrogen, Carlsbad, CA, USA) was used to evaluate the activity of caspase-3 according to the manufacturer's protocol. Aliquots from each muscle sample were homogenized at 1:5 in a lysis buffer (100 mM NaCl, 1 mM EDTA, 0.01% [v/v] Triton X-100, and 10 mM Tris-HCl [pH 7.5]) and centrifuged at 12,000 ×g at 4 °C for 5 min. Subsequently, 100 µL of supernatant was taken from each sample and transferred in triplicate to an opaque 96-well microplate with or without 1 µL of 1 M Ac-DEVD-CHO (caspase-3 inhibitor) and incubated for 5 min at room temperature. To each well, 50 µL of 10 µM Z-Devd-AMC was added and incubated for 30 min at room temperature. Caspase-3 activation was evaluated using a fluorescence spectrophotometer (Synergy H1, BioTek, Winooski, VT, USA) at an excitation and emission wavelength of 342 and 441 nm, respectively. Caspase-3 activity was expressed as µM of substrate cleaved/min/mg protein.

## 2.8. High-throughput proteomic analysis using tandem mass tag (TMT) labeling coupled with mass spectrometry

To identify and quantify certain matrisome proteoforms (collagens and proteoglycans), the 0 d muscle samples were powdered under liquid nitrogen, and ~100 mg of tissue was placed in centrifuge tubes with stainless steel beads, RIPA buffer, protease inhibitors, and DTT (details are given in the Supplementary file). The samples were then homogenized and centrifuged, and then the supernatants were incubated to reduce disulfide bonds. The protein concentration was determined, and samples were then treated with iodoacetamide for alkylation. Samples were subsequently quenched with DTT and precipitated with acetone overnight. The resulting pellets were dissolved, digested with Lys-C and trypsin, acidified, dried, and derivatized with TMT-16-plex reagents. Afterward, each sample was labeled, acidified, and desalted before sub-fractionation using high pH reverse phase chromatography. Samples were then recombined to obtain a total of
12 fractions. Each fraction underwent LC-MS/MS analysis, with peptides separated and analyzed by FAIMS and Orbitrap mass spectrometry. Data were acquired using the SPS-MS3 method and processed with Proteome Discoverer 2.4 software. Proteins were quantified by peak intensity and normalized, with protein ratios obtained from the group protein abundances calculated as the median abundance values of all replicates. The quantitative proteomics data were then processed as previously described by Lamri, Malva, Djenane, Albenzio & Gagaoua (2023).

## 2.9. Statistical analysis

Data were analyzed using the mixed model of JMP (SAS Institute Inc., Cary, NC, USA) with animal as the experimental unit. The statistical model included the fixed effects of muscle (MS, LT, and CT), time (0, 7, and 14 d), and their interaction along with the random effect of animal. For pH, calpain-1 autolysis, intensity of the 110 and 30 kDa proteolytic fragments bands, desmin and TT (fast and slow) proteolysis, and caspase-3 activity, the "slice" function was used to evaluate muscle effect at individual time points and time effect for each muscle. Tukey-Kramer multiple comparison post-hoc tests were used to evaluate differences between muscles for LDH, SDH, GAPDH, myoglobin, and calpastatin abundances, as only data collected at 0 d were considered. Differences between means were considered significant at *P* ≤ 0.05. All data are presented as least-squares means ± SE.

The connective tissue variables (collagen and proteoglycan proteoforms) at 0 d postmortem were first compared using a one-way ANOVA at a significance level of *P* ≤ 0.05. Significant proteins were then used for hierarchical clustering analysis visualized in a heatmap based on Euclidean distance and Ward linkage.

To examine the relationships among the contractile, metabolic, and connective tissue properties at 0 d postmortem and their potential to discriminate the three muscles, a Principal
Component Analysis (PCA) was conducted using XLSTAT 2022.4.1 software (AddinSoft, Paris, France). A second PCA was conducted using the proteolysis indicators over the course of postmortem aging.

**3. Results**

**3.1. Muscle characterization and validation of the divergencies within the contractile, metabolic, and connective tissue properties**

To effectively characterize each of the three muscles, we evaluated their contractile, metabolic, and connective tissue properties. MyHC isoforms of the 0 d MS, LT, and CT muscles were separated using SDS-PAGE to characterize the contractile properties of the muscles. The relative percentages of type I, IIa, and IIx isoforms were calculated and depicted in Fig. 1. As expected, differences in the proportions of the three MyHC isoforms were observed among the three muscles (*P* < 0.001). MyHC-I was highest in the MS and lowest in the CT (*P* < 0.001), whereas the opposite pattern was detected for MyHC-IIa and MyHC-IIx (*P* < 0.001). The LT had more MyHC-I than the CT and more MyHC-IIa and MyHC-IIx than the MS.

The abundance of GAPDH, LDH, SDH, and myoglobin was only evaluated on the 0 d muscle samples to better characterize the metabolic properties of the muscles (Fig. 2). The abundance of all tested proteins differed significantly across the three muscles (*P* ≤ 0.009). The CT muscle exhibited greater levels of glycolytic proteins (GAPDH and LDH) compared to the LT and MS (*P* ≤ 0.001; Fig. 2A and 2B, respectively). There was no difference in the abundance of GAPDH between the LT and MS, but the LT had greater LDH content than the MS (*P* < 0.001). On the other hand, MS samples had the highest abundances of the SDH and myoglobin proteins (*P* ≤ 0.009; Fig. 2C and 2D, respectively), while the CT and LT did not differ. Overall, the three muscles
were characterized as being oxidative for MS, glycolytic for CT, and oxido-glycolytic (intermediate) for LT.

The pH values of the MS, LT, and CT muscles at 0, 7, and 14 d postmortem are presented in Fig. 3. At 0 d (30 min postmortem), a lower pH value was observed for the CT compared to the MS and LT (P < 0.001). As expected, the pH decreased over time in all three muscles (P < 0.001); however, the extent of decline varied among them. The LT had the lowest pH at 7 and 14 d (P < 0.001), whereas the MS maintained the highest (P < 0.001).

We further examined the intrinsic properties of the three muscles at 0 d using proteomic analysis, targeting the relative abundances of connective tissue proteoforms, including collagens and proteoglycans. Twenty-one proteoforms were identified (Fig. 4A), 16 of which were differentially abundant (P ≤ 0.05). These 16 proteins are visually depicted in a hierarchal heatmap clustering (Fig. 4B). The CT and MS exhibited the greatest abundance of collagens and proteoglycans, while the LT maintained the least. Although the CT generally maintained slightly higher concentrations of proteoforms than the MS, the two muscles were comparable overall. Interestingly, lower abundances of VCAN (proteoglycan) and COL1A1 (collagen) were indicated in the MS and LT samples compared to the CT samples (P ≤ 0.05).

In addition to the characterizing measures presented above, we performed a PCA using data collected at 0 d only (Fig. 5) to illustrate the overall separation between the intrinsic characteristics of the three selected muscles. The first two principal components (PC1 and PC2) accounted for 67.2% of the variance among the data set and allowed a distinct separation among the three muscles (Fig. 5-bottom right). This depicts the biological differences in the contractile, metabolic, and connective tissue properties of the muscles tested herein.
## 3.2. Proteolysis

Proteolysis was evaluated by assessing the degradation of desmin and TT (TT-fast and TT-slow) as well as the appearance of the 110 and 30 kDa proteolytic fragments. Desmin degradation was affected by muscle, time, and muscle × time interaction (P < 0.001, Fig. 6). No differences were observed between the three muscles at 0 d. However, at 7 and 14 d, the MS muscle demonstrated the greatest level of desmin degradation, while CT had the lowest (P < 0.001). Degradation of both TT-fast and TT-slow isoforms was also evaluated, as they are differentially expressed within glycolytic and oxidative muscles and could degrade specific to muscle type. The two TT isoforms were both affected by muscle, time, and their interaction (P < 0.001, Fig. 7). The CT samples demonstrated the greatest degradation of the TT-fast isoform at the 0-d time point (P < 0.006, Fig. 7A). At 7 and 14 d; however, the LT muscle experienced the greatest level of degradation, while the MS had the least (P < 0.001). In contrast, the MS and LT samples had greater TT-slow isoform degradation at 7 and 14 d compared to the CT (P < 0.001, Fig. 7B).

To further investigate the proteolytic patterns of the MS, LT, and CT muscles, total muscle protein extracts were separated via SDS-PAGE, and the intensity of the 110 and 30 kDa fragments was monitored at each timepoint (Fig. 8). Muscle, time, and muscle × time interaction effects were observed for the 110 kDa (Fig. 8B) and 30 kDa (Fig 8C) fragments (P < 0.001). Minimal appearance of the 110 kDa band was observed in all muscles at 0 d. Yet, the intensity of the 110 kDa band increased over time (P < 0.001), with the MS and LT demonstrating greater intensities at 7 and 14 d compared to the CT (P < 0.001). The appearance of the 30 kDa band also increased over time (P < 0.001). Although no differences in intensity were observed between the muscles at 0 d, the LT displayed the greatest 30 kDa band intensity at 7 and 14 d, while MS had the least (P ≤ 0.004).
### 3.3. Calpain autolysis, calpastatin abundance, and caspase-3 activity

To gain a better understanding of the observed differences in proteolysis across the three divergent muscles, we quantified calpain-1 autolysis (Fig. 9A), calpastatin abundance (Fig. 9B), and caspase-3 activity (Fig. 10). Calpain-1 autolysis was affected by the interaction between muscle and time (P = 0.008). Although the appearance of the 76 kDa band was negligible at 0 d in all muscles, greater calpain-1 autolysis was observed in the MS and LT muscles at 7 and 14 d postmortem compared to that of the CT (P < 0.001). The abundance of calpastatin was evaluated at all time points in the current study. However, only the 0-d results are presented herein, as calpastatin was degraded entirely in all three muscles at 7 and 14 d. The CT muscle had the highest level of calpastatin (P = 0.009), with no difference between the MS and LT muscles. As shown in Fig. 9, the activity of caspase-3 was influenced by muscle and time (P < 0.001). The results indicate a general decline in activity over time in all muscles. However, within each time point, the MS muscle exhibited greater caspase-3 activity than the LT (P ≤ 0.02). The CT muscle had activity levels similar to the MS at 0 and 14 d but lower at 7 d (P = 0.009). On the other hand, the CT exhibited greater caspase-3 activity than the LT at 0 d only (P < 0.001).

### 3.4. The progression of postmortem proteolysis within the three divergent muscles

For an overview of the proteolysis rate and the proteolytic differences among the three muscles, we performed a PCA analysis by incorporating the 0, 7, and 14 d proteolytic indicators. These included calpain-1 autolysis, caspase-3 activity, pH, desmin and TT (fast and slow) proteolysis, as well as the abundances of the 30 and 110 kDa proteolytic fragments data (Fig. 11A). PCA enables the visualization of data points clustering, which helps to identify which indicators are more closely related to each muscle group and better understand the relationships among variables. PC1 contributed to the majority of the variance (65.3%) and separated the aging times, whereas PC2
accounted for 16% and distinguished the muscles from one another. The bi-plot (Fig. 11B) shows the distinct proteolysis rate of each muscle over the aging period, along with a clear separation between the three muscles within each time point. It demonstrates that the CT muscle has a slower rate of proteolysis compared to LT, whereas the MS seems to reside in between. Additionally, the MS muscle samples were positioned in the bottom part of the bi-plot, whereas LT and CT muscle samples were positioned primarily in the upper quadrants. This separation seems to be related to the projection of the proteolytic indicators (Fig. 11A), as the LT and CT have the highest content of the TT-fast and 30 kDa fragment, while MS maintained a higher abundance of desmin, TT-slow, and the 110 kDa fragment.

# 4. Discussion

## 4.1. Intrinsic muscle characteristics

Variation among bovine skeletal muscles is largely dependent upon their respective metabolic, contractile, structural, and connective tissue properties (Gagaoua & Picard, 2022). However, the interrelations between these intrinsic attributes correlate with specific muscle fiber type compositions and have been used for their categorization (Peter, Barnard, Edgerton, Gillespie, & Stempel, 1972; Picard & Gagaoua, 2020). In the present study, three muscles with distinct intrinsic characteristics and fiber type compositions (MS, LT, and CT) were selected and examined for variations in postmortem proteolysis over a 14-d aging period. To confirm that the three muscles are indeed inherently different, we characterized their respective MyHC composition (Fig. 1), metabolic properties (Fig. 2), pH (Fig. 3), and connective tissue profiles (i.e., collagens and proteoglycans proteoforms; Fig. 4B). In addition, we subjected the muscle characterization data to a PCA to better visualize the relationships between the measured parameters and their ability to distinguish the muscles investigated (Fig. 5).
Data suggests that the MS is predominantly an oxidative muscle. It was characterized by ~97% MyHC-I, abundant oxidative protein markers (SDH and myoglobin), and an elevated ultimate pH. In contrast, the CT muscle contained ~66% MyHC-IIx, greater levels of glycolytic enzymes (LDH and GAPDH), lower levels of SDH and myoglobin, along with lower initial and ultimate pH values. The LT muscle exhibited a heterogeneous but intermediate mixture of type I (~36% MyHC-I), IIA (~15% MyHC-IIa), and IIX (~48% MyHC-IIx) muscle fibers compared to MS and CT. GAPDH level in the LT was similar to that in the MS, while SDH and myoglobin levels were comparable to those in the CT, thereby classifying the LT muscle as having intermediate characteristics to that of the CT and MS. Therefore, the collective results demonstrate the distinctive characteristics of each muscle and resemble those discussed in the literature (Astruc & Vénien, 2017; Johnston, Moody, Boling, & Bradley, 1981; Jurie, Picard, & Geay, 1998; Kirchofer, Caulkins, & Gwartney, 2002; Vaskoska et al., 2021)

The matrisome is a network of genes that encode extracellular matrix proteins (e.g., collagens and proteoglycans), which form the intermyofibrillar connective tissue lattice (Hynes & Naba, 2012). Previous research demonstrates that the MS and CT muscles are abundant in collagen proteoforms (Listrat et al., 2000; Vaskoska et al., 2021), mainly because of their locomotive functions. This includes the MS's role in mastication and CT's involvement in twitching the animal's trunk (Bogucka, Bogucki, & Nowicki, 2015; Van Metre, Callan, & Garry, 2001). On the other hand, the LT typically contains a lower collagen content (Rusman, Soeparno, Setiyono, & Suzuki, 2003; Torrescano, Sánchez-Escalante, Gimenéz, Roncalés, & Beltrán, 2003), as it serves as a stabilizer muscle (Bakkum & Cramer, 2014). Herein, the collagens were found to be more abundant in the MS and CT samples in comparison to the LT (Fig. 4B). The collagen proteoforms COL14A1, COL18A1, COL15A1, and COL6A3 were greater in abundance in the MS, whereas
the COL6A6, COL6A1, COL3A1, and COL1A1 were more abundant in the CT. Greater abundances of the proteoglycans DCN, HSPG2, and VCAN were also found in the CT compared to the MS and LT. On the other hand, the LT had the lowest abundances in nearly all indicated collagens and proteoglycans. Although little is known about the influence of proteoglycans on fresh meat quality, recent research has investigated possible links to tenderness and sensory qualities (Listrat et al., 2020a, 2020b). Nonetheless, their evaluation further distinguishes the three muscles in the current study.

To effectively consider the muscles' inherent characteristics and interrelationships, a PCA was performed to better visualize the variability amongst the 0-d dataset and to highlight the degree of disparity among the three muscles. Considering the different contractile, metabolic, and connective tissue properties, our PCA confirmed the divergencies among the muscles (see bi-plot of Fig. 5-bottom right). Based on these results, we can confirm that these three muscles are inherently different.

## 4.2. *Differences in postmortem proteolysis*

Proteolysis is the primary contributor to beef tenderization during aging (Koohmaraie & Geesink, 2006). It involves the activation of endogenous enzymes that ultimately weaken the myofibrillar structure (Koohmaraie, 1994). Evaluating the level of degradation of key protein markers and the appearance of proteolytic fragments can be used as indicators of the progression of proteolysis throughout the postmortem period. Commonly evaluated proteins include titin, actin, desmin, and TT (Huff-Lonergan et al., 1996; Koohmaraie & Geesink, 2006). Hence, the current study assessed the proteolysis of desmin (Fig. 6) and TT (Fig. 7). Our data demonstrated differences in desmin degradation among the three muscles over time. The MS had the highest, and CT had the lowest levels of desmin proteolysis, indicating that desmin degradation increased with increasing the
oxidative capacity of the muscle. This degradation pattern could be due to greater protein oxidation occurring within oxidative muscles (Smuder, Kavazis, Hudson, Nelson, & Powers, 2010; Xue, Huang, F., Huang, M., & Zhou, 2012). The greater abundance of mitochondria in oxidative muscles makes them more prone to protein oxidation as well as increased caspase-3 activity (Bai et al., 2022; Ramos et al., 2021). In this regard, Chen, Huang, Huang, Huang, & Zhou (2014) found that oxidized desmin protein is more susceptible to caspase-3 degradation, which may partially explain the accentuated degradation pattern observed in muscles with more type I (MS) fibers compared to those with more type II (CT).

The anti-TT-fast isoform antibody was initially utilized in this study to evaluate TT proteolysis (Fig. 7A). Our results indicated that the LT muscle generally experienced the greatest TT-fast proteolysis over time. However, intact TT-fast isoform and its degradation products were virtually undetected in the MS muscle, which explains why its proteolysis did not change over time. However, it is important to note that the indicated degradation patterns are relative and are calculated based on the ratio of measured degradation products over the total signal. Similar to our findings, Muroya, Nakajima, Oe, & Chikuni (2006) observed negligible amounts of TT-fast isoform in the MS muscle, with more pronounced overall degradation in muscles with increased type II fiber composition. This research group also suggested that TT isoform composition is muscle-dependent and related to the muscle's metabolic and contractile properties (Muroya, Nakajima, & Chikuni, 2003). In light of this, we also targeted the slow isoform of TT using an anti-TT-slow antibody and evaluated its degradation over time (Fig. 7B). The results indicated that the MS and LT samples had similar proteolysis patterns and were both greater than that of the CT. However, the CT samples demonstrated relatively little band intensity across time points, resembling the trend observed in the TT-fast measurements of the MS samples. This is most likely
due to the lack of the TT-slow isoform in the CT muscle (Muroya et al., 2006). Given that muscles
with varying fiber type compositions have different proportions of TT-fast and TT-slow isoforms
(Muroya et al., 2003), measuring the degradation of only one TT isoform may not be sufficient for
evaluating postmortem proteolysis across different muscles (i.e., oxidative vs glycolytic). For this
reason, we suggest that TT should not be the sole protein indicator of postmortem proteolysis when
proteolysis is compared between different muscles. Additionally, the three muscles exhibited a
relatively similar abundance of desmin at 0 d, suggesting that desmin could be a more consistent
marker of proteolysis, especially when comparing proteolysis among different muscles.

Researchers have traditionally relied on evaluating the breakdown of specific protein
markers to assess postmortem proteolysis. However, analyzing the overall protein fragmentation
pattern could contribute to a deeper understanding of the proteolytic progression in postmortem
muscle. Different patterns of protein degradation can be distinguished by observing the appearance
of certain protein fragments during postmortem aging (Young, Graafhuis, & Davey, 1980). In this
context, the 110 and 30 kDa proteolytic fragments have been used as reliable indicators of
postmortem proteolysis, containing proteins previously identified as markers of beef tenderness
(Gagaoua et al., 2021; Koohmaraie, Kennick, Elgasim, & Anglemier, 1984; White, O'Sullivan,
Troy, O'Neill, 2006; Young et al., 1980). For instance, fragments of proteins associated with
muscle contraction and myofibrillar structure, including myosin, α-actinin, and nebulin, were
found in the 110 kDa band (Gagaoua et al., 2021), whereas fragments related to actin (Ouali et al.,
2013), myosin light chain 1 (Gagaoua et al., 2021), and TT-fast (Negishi, Yamamoto, & Kuwata,
1996) were identified in the 30 kDa band. As such, comparing the appearance of the 110 and 30
kDa provides deeper insights into the variability of postmortem proteolysis across different
muscles. In the current study, greater 110 kDa fragment intensity was observed for the MS and LT
samples at 7 and 14 d (Fig. 8B), while relatively little was detected for the CT. This could be
attributed to the more oxidative nature of the MS and LT muscles compared to the CT, which has
been shown to positively correlate with higher apoptotic and lysosomal protease activities (Bechet,
Tassa, Taillandier, Combaret, & Attaix, 2005; Ramos et al., 2021). The action of these two
proteases on nebulin, α-actinin, and myosin results in the accumulation of large protein fragments
and contributes to the appearance of the 110 kDa band (Huang et al., 2011; Mikami, Whiting,
Taylor, Maciewicz, & Etherington 1987; Sentandreu, Coulis, & Ouali, 2002). Moreover, the 110
kDa fragment is mainly composed of slow-contracting proteins (e.g., myosin binding protein C1;
Gagaoua et al., 2021), which aligns with the findings described above for the slow-TT isoform.
The intensity of the 30 kDa band increased with time in the LT and CT muscles, being the most
prominent in the LT (Fig. 8C). However, it was almost undetectable in the MS at all time points.
This result was unsurprising as the 30 kDa fragment is mainly attributed to the degradation of the
TT-fast isoform (Negishi et al., 1996), which corresponds with our TT-fast proteolysis data (Fig.
7A). Collectively, the data suggests that proteolysis is muscle-dependent, and the evaluation of
specific protein markers may not fully represent their respective proteolytic progressions.
However, muscle's metabolic and contractile attributes can influence protease activity (O'Halloran,
Troy, & Buckley, 1997; Song et al., 2022; Veiseth-Kent, Pedersen, Rønning, & Rødbotten, 2018),
which could help explain their distinct degradation patterns.

4.3. *Protease activity and proteolytic monitoring*

Postmortem proteolysis is primarily driven by endogenous proteases that degrade and
compromise the myofibrillar structure (Ertbjerg, 2022; Koohmaraie, 1996). This process relies on
several endogenous proteases, such as calpain-1 and caspase-3 (Kemp et al., 2010; Koohmaraie &
Geesink, 2006). Calpain-1 undergoes a self-degrading process (autolysis) in the presence of
calcium (Goll et al., 2003), in which the catalytic subunit autolyzes from 80 kDa to its 76 kDa active form (Zimmerman & Schlaepfer, 1991). The degree of autolysis is commonly evaluated as an indication of calpain-1 activation. In the current study, we measured the relative intensity of the 76 kDa and found that the MS and LT demonstrated greater calpain-1 autolysis than the CT at 7 and 14 d (Fig. 9A). This was surprising since glycolytic muscles generally contain a more abundant and developed sarcoplasmic reticulum compared to oxidative muscles (Hochachka, Emmett, & Suarez, 1988; Murgia et al., 2021), which could accelerate the increase of cytosolic calcium and subsequent calpain-1 activation. However, the CT demonstrated greater calpastatin abundance than the MS and LT (Fig. 9B), likely contributing to its slower calpain-1 autolysis (Hyatt & Powers, 2020; Koohmaraie, 1992a). In agreement with our data, Motter, Corva, & Soria (2021) found that the *Semitendinosus* muscle, which is predominantly composed of type IIX fibers (Kirchofer et al., 2002; Lang et al., 2020), maintained higher calpastatin activity and CAST gene expression than *Infraspinatus* and *Triceps brachii*, which contain more type I fibers.

Caspases are a family of apoptotic proteases activated in postmortem muscle primarily through an intrinsic mitochondrial pathway (Kemp and Parr, 2012). During mitochondrial dysfunction, cytochrome c is released into the cytosol, where it binds to other apoptosis-related proteins to form a complex known as the apoptosome (Borutaite, Jekabsone, Morkuniene, & Brown, 2003; Ouali et al., 2013). This complex subsequently activates initiator caspase-9 and leads to the cleavage of caspase-3, thereby activating its proteolytic function (Loeffler & Kroemer, 2000). Herein, we assessed caspase-3 activity and found that the MS muscle generally maintained the highest activity (Fig. 10). This is probably because this muscle contains a greater mitochondrial content than the LT and CT, thereby increasing the muscle's capacity to activate caspase-3 (Stafford et al., 2024). The increase in caspase-3 activity in the MS may also help explain the MS's
observed increase in desmin proteolysis (Fig. 6). Indeed, a previous study has shown a positive association between caspase-3 activity and desmin proteolysis *in vitro* (Chen et al., 2014). Curiously, the CT showed greater caspase-3 activity than the LT, even though the LT exhibited higher oxidative capacity. This could be due to a faster pH decline in the CT, as evidenced by its lower pH value at the 0 d time point (30 min postmortem). It has been previously reported that greater caspase-3 activity is correlated with faster rates of pH decline (Ma, Yu, & Han, 2022). Meanwhile, the slower pH decline and intermediate abundance of mitochondria in the LT compared to the other two muscles possibly explain its lower observed caspase-3 activity. Although the LT showed the lowest caspase-3 activity, it generally exhibited the highest level of proteolysis, suggesting that caspase-3 plays a less significant role in proteolysis compared to calpain-1. All in all, these results support that postmortem proteolysis is muscle-specific as protease activities also vary among muscles with different properties.

Proteolysis is a complex process as it incorporates a multitude of factors that contribute to its progression in postmortem muscle. Collectively, our findings highlight specific proteolytic patterns that are correlated with the inherent differences within the contractile, metabolic, and connective tissue properties of the LT, CT, and MS muscles. As such, a second PCA considering the proteolytic indicators measured herein was used to monitor the proteolytic progression in the three muscles. This PCA analysis confirmed that the rate of proteolysis is different among the three muscles and demonstrated that the CT muscle had the slowest rate of proteolysis compared to LT and MS. Additionally, in Fig. 11B, the MS and CT muscle samples were positioned below and above those of the LT, respectively, thereby signifying their divergence. This patterning aligns with the distributions of the proteolysis indicators. Taken together, the PCA allowed the combination of several proteolytic indicators with the objective of using them in a combined index
to understand the inherent differences among muscles and to study the dynamic changes occurring postmortem. It also enabled a better understanding of muscle-specific tenderization signatures.

**5. Conclusions**

Data from the current study demonstrates that the MS, LT, and CT muscles are metabolically and compositionally different and that they maintain distinct proteolytic patterns. Interestingly, muscles composed primarily of type I (MS) or type IIX (CT) fibers seemed to experience less proteolysis than those with a heterogeneous mixture of type I, IIA, and IIX fibers (LT). This can be attributed, in part, to differences in protease activity, as higher levels of calpain-1 autolysis and lower amounts of calpastatin were observed in the LT and MS samples compared to the CT. Caspase-3 activity, however, was highest in the MS and lowest in the LT despite the LT having greater proteolysis, thereby indicating that caspase-3 contributes less to proteolysis than calpain-1. Additionally, our multivariate PCA analysis demonstrated distinct patterns in the proteolytic data among the three muscles over time, reflecting different rates of proteolysis. These data imply that postmortem proteolysis occurs uniquely in bovine muscles that maintain different intrinsic characteristics. This study also evidenced that a single proteolytic indicator does not sufficiently describe proteolysis when comparing different muscles, and a holistic approach using appropriate oxidative and glycolytic protein markers is needed. Moreover, each muscle should be evaluated considering its inherent biochemical characteristics, as some parameters indicative of proteolysis may not be uniformly shared across all muscles. For instance, TT degradation measurements depend upon which isoform is evaluated (fast or slow). Collectively, these findings improve our understanding of the progression of postmortem proteolysis among intrinsically different muscles in terms of their contractile, metabolic, and connective tissue properties, further elucidating muscle-to-muscle variations in tenderness development. These insights can be leveraged for
practical applications within the meat industry, where targeted interventions can be developed to enhance tenderness in fresh meat. However, this work also warrants further molecular exploration using omics methods to decipher the biochemical mechanisms at play within the divergent muscles utilized in this study.

**Declaration of Competing Interest**

The authors declare no conflicts of interest.

**Acknowledgments**

The authors thank Emerson Nolasco and Dr. Kaustav Majumder for their contribution to the study.
This research was supported by Agriculture and Food Research Initiative Competitive Grant no.
2019-67017-29177, and Hatch Capacity Grant Project no. UTA-01383 from the USDA National
Institute of Food and Agriculture and was approved as journal paper number 9818.
## References

Alev, K., Kaasik, P., Pehme, A., Aru, M., Parring, A. M., Elart, A., & Seene, T. (2009). Physiological role of myosin light and heavy chain isoforms in fast-and slow-twitch muscles: effect of exercise. *Biology of Sport, 26*(3).

Armstrong, R. B., & Laughlin, M. H. (1985). Metabolic indicators of fibre recruitment in mammalian muscles during locomotion. *Journal of Experimental Biology*.115, 0-1.

Astruc, T & Vénien, A. (2017). Muscle fibre types and beef quality. *Ensuring safety and quality in the production of beef*, (2) 59-82. Burleigh Dodds Science Publishing.

Bai, X., Yin, F., Ru, A., Tian, W., Li, J., Zhang, G., Chen, Q., Chai, R., Xiao, K., Zhu, C., & Zhao, G. (2022). Muscle fiber composition affects the postmortem redox characteristics of yak beef. *Food Chemistry*, 397, 133797.

Bakkum, B. W., & Cramer, G. D. (2014). Muscles that influence the spine. *Clinical Anatomy of the Spine, Spinal Cord, and ANS*, 98-134.

Bechet, D., Tassa, A., Taillandier, D., Combaret, L., & Attaix, D. (2005). Lysosomal proteolysis in skeletal muscle. *The International Journal of Biochemistry & Cell Biology*, 37(10), 2098-2114.

Bendall, J. R. (1973). Postmortem changes in muscle. G.H. Borune (Ed.), *The structure and function of muscle*. Academic Press, 2(Part 1), 243-309.

Bogucka, J., Bogucki, M., & Nowicki, T. (2015). Intramuscular fat content in the masseter muscle (musculus masseter) of cattle depending on sex and age. *Acta Scientiarum Polonorum. Zootechnica*, 14(4), 15-24.

Borutaite, V., Jekabsone, A., Morkuniene, R., & Brown, G. C. (2003). Inhibition of mitochondrial permeability transition prevents mitochondrial dysfunction, cytochrome c release and apoptosis induced by heart ischemia. *Journal of Molecular and Cellular Cardiology*, 35(4), 357-366.

Chen, Q., Huang, J., Huang, F., Huang, M., & Zhou, G. (2014). Influence of oxidation on the susceptibility of purified desmin to degradation by µ-calpain, caspase-3 and -6. *Food Chemistry*, 150, 220-226.

Choi, Y. M., & Kim, B. C. (2009). Muscle fiber characteristics, myofibrillar protein isoforms, and meat quality. *Livestock Science*, 122(2-3), 105-118.

Dang, D. S., Buhler, J. F., Thornton, K. J., Legako, J. F., & Matarneh, S. K. (2020). Myosin heavy chain isoform and metabolic profile differ in beef steaks varying in tenderness. *Meat Science*, 170, 108266.

Dang, D. S., Buhler, J. F., Davis, H. T., Thornton, K. J., Scheffler, T. L., & Matarneh, S. K. (2020). Inhibition of mitochondrial calcium uniporter enhances postmortem proteolysis and tenderness in beef cattle. *Meat science*, 162, 108039.

Dang, D. S., Stafford, C. D., Taylor, M. J., Buhler, J. F., Thornton, K. J., & Matarneh, S. K. (2022). Ultrasonication of beef improves calpain-1 autolysis and caspase-3 activity by elevating cytosolic calcium and inducing mitochondrial dysfunction. *Meat science*, 183, 108646.

Destefanis, G., Brugiapaglia, A., Barge, M. T., & Dal Molin, E. (2008). Relationship between beef consumer tenderness perception and Warner-Bratzler shear force. *Meat Science*, 78(3), 153-156.

Ertbjerg, P. (2022). Current understanding on the role of proteolysis on meat quality. *In New Aspects of Meat Quality* (pp. 95-114). Woodhead Publishing.

Gagaoua, M., & Picard, B. (2022). Proteomics to explain and predict meat quality. *New Aspects of Meat Quality*. Woodhead Publishing, 393-431.
Gagaoua, M., Troy, D., & Mullen, A. M. (2021). The extent and rate of the appearance of the major 110 and 30 kda proteolytic fragments during post-mortem aging of beef depend on the glycolysing rate of the muscle and aging time: an LC-MS/MS approach to decipher their proteome and associated pathways. *Journal of Agricultural and Food Chemistry*, 69(1), 602–614.

Goll, D. E., Thompson, V. F., Li, H., Wei, W., & Cong, J. (2003). The calpain system. *Physiological Reviews*, 83(3), 731–801.

Goodman, C. A., Mabrey, D. M., Frey, J. W., Miu, M. H., Schmidt, E. K., Pierre, P., & Hornberger, T. A. (2011). Novel insights into the regulation of skeletal muscle protein synthesis as revealed by a new nonradioactive *in vivo* technique. *The FASEB Journal*, 25(3), 1028.

Hochachka, P. W., Emmett, B., & Suarez, R. K. (1988). Limits and constraints in the scaling of oxidative and glycolytic enzymes in homeotherms. *Canadian Journal of Zoology*, 66(5), 1128-1138.

Huang, F., Huang, M., Zhou, G., Xu, X., & Xue, M. (2011). *In vitro* proteolysis of myofibrillar proteins from beef skeletal muscle by caspase-3 and caspase-6. *Journal of Agricultural and Food Chemistry*, 59(17), 9658–9663.

Huff-Lonergan, E., Mitsuhashi, T., Beekman, D. D., Parrish, F. C., Olson, D. G., & Robson, R. M. (1996). Proteolysis of specific muscle structural proteins by µ-calpain at low pH and temperature is similar to degradation in postmortem bovine muscle. *Journal of Animal Science*, 74(5), 993–1008.

Hyatt, H. W., & Powers, S. K. (2020). The role of calpains in skeletal muscle remodeling with exercise and inactivity-induced atrophy. *International Journal of Sports Medicine*, 41(14), 994-1008.

Hynes, R. O., & Naba, A. (2012). Overview of the matrisome—an inventory of extracellular matrix constituents and functions. *Cold Spring Harbor Perspectives in Biology*, 4(1), a004903.

Johnston, D. M., Moody, W. G., Boling, J. A., & Bradley, N. W. (1981). Influence of breed type, sex, feeding systems, and muscle bundle size on bovine fiber type characteristics. *Journal of Food Science*, 46(6), 1760-1765.

Jurie, C., Picard, B., & Geay, Y. (1998). Influences of the method of housing bulls on their body composition and muscle fibre types. *Meat Science*, 50(4), 457-469.

Kemp, C. M., & Parr, T. (2012). Advances in apoptotic mediated proteolysis in meat tenderization. *Meat Science*, 92(3), 252-259.

Kemp, C. M., Sensky, P. L., Bardsley, R. G., Buttery, P. J., & Parr, T. (2010). Tenderness – an enzymatic view. *Meat Science*, 84(2), 248–256.

Kirchofer, K. S., Calkins, C. R., & Gwartney, B. L. (2002). Fiber-type composition of muscles of the beef chuck and round. *Journal of Animal Science*, 80(11), 2872–2878.

Koohmaraie, M. (1992a). Effect of pH, temperature, and inhibitors on autolysis and catalytic activity of bovine skeletal muscle mu-calpain. *Journal of Animal Science*, 70(10), 3071-3080.

Koohmaraie, M. (1992b). Effects of lamb age, muscle type, and 24-hour activity of endogenous proteinases on postmortem proteolysis. *Journal of Animal Science*, 70(3), 798-804.

Koohmaraie, M. (1994). Muscle proteinases and meat aging. *Meat Science*, 36(1–2), 93–104.

Koohmaraie, M. (1996). Biochemical factors regulating the toughening and tenderization processes of meat. *Meat Science*, 43, 193–201.
Koohmaraie, M., & Geesink, G. H. (2006). Contribution of postmortem muscle biochemistry to the delivery of consistent meat quality with particular focus on the calpain system. *Meat Science*, 74(1), 34–43.

Koohmaraie, M., Kennick, W. H., Elgasim, E. A., & Anglemier, A. F. (1984). Effects of postmortem storage on muscle protein degradation: analysis by SDS-polyacrylamide gel electrophoresis. *Journal of Food Science*, 49(1), 292–293.

Koohmaraie, M., Seideman, S. C., Schollmeyer, J. E., Dutson, T. R., & Babiker, A. S. (1988). Factors associated with the tenderness of three bovine muscles. *Journal of Food Science*, 53(2), 407–410.

Lang, Y., Zhang, S., Xie, P., Yang, X., Sun, B., & Yang, H. (2020). Muscle fiber characteristics and postmortem quality of longissimus thoracis, psoas major and semitendinosus from Chinese Simmental bulls. *Food Science & Nutrition*, 8(11), 6083-6094.

Lamri, M., Della Malva, A., Djenane, D., Albenzio, M., & Gagaoua, M. (2023). First insights into the dynamic protein changes in goat Semitendinosus muscle during the post-mortem period using high-throughput proteomics. *Meat Science*, 202, 109207.

Lee, S. H., Joo, S. T., & Ryu, Y. C. (2010). Skeletal muscle fiber type and myofibrillar proteins in relation to meat quality. *Meat Science*, 86(1), 166–170.

Listrat, A., Lethias, C., Hocquette, J. F., Renand, G., Ménissier, F., Geay, Y., & Picard, B. (2000). Age-related changes and location of types I, III, XII and XIV collagens during development of skeletal muscles from genetically different animals. *Histochemical Journal*, 32(6), 349–356.

Listrat, A., Gagaoua, M., Normand, J., Gruffat, D., Andueza, D., Mairesse, G., Mourot, BP., Chesneau, G., Gobert, C., & Picard, B. (2020a). Contribution of connective tissue components, muscle fibres and marbling to beef tenderness variability in longissimus thoracis, rectus abdominis, semimembranosus and semitendinosus muscles. *Journal of the Science of Food and Agriculture*, 100(6), 2502-2511.

Listrat, A., Gagaoua, M., Andueza, D., Gruffat, D., Normand, J., Mairesse, G., Picard, B., & Hocquette, J. F. (2020b). What are the drivers of beef sensory quality using metadata of intramuscular connective tissue, fatty acids and muscle fiber characteristics?. *Livestock Science*, 240, 104209.

Loeffler, M., & Kroemer, G. (2000). The mitochondrion in cell death control: certainties and incognita. *Experimental Cell Research*, 256(1), 19–26.

Ma, J., Yu, Q., & Han, L. (2022). The effect of postmortem pH decline rate on caspase-3 activation and tenderness of bovine skeletal muscle during aging. *Journal of food biochemistry*, 46(9), e14215.

Matarneh, S. K., Silva, S. L., & Gerrard, D. E. (2021). New insights in muscle biology that alter meat quality. *Annual Review of Animal Biosciences*, 9(1), 355-377.

Mikami, M., Whiting, A. H., Taylor, M. A. J., Maciewicz, R. A., & Etherington, D. J. (1987). Degradation of myofibrils from rabbit, chicken and beef by cathepsin l and lysosomal lysates. *Meat Science*, 21(2), 81–97.

Miller, M. F., Carr, M. A., Ramsey, C. B., Crockett, K. L., & Hoover, L. C. (2001). Consumer thresholds for establishing the value of beef tenderness. *Journal of Animal Science*, 79, 3062–3068.

Motter, M. M., Corva, P. M., & Soria, L. A. (2021). Expression of calpastatin isoforms in three skeletal muscles of Angus steers and their association with fiber type composition and proteolytic potential. *Meat Science*, 171, 108267.
Murgia, M., Nogara, L., Baraldo, M., Reggiani, C., Mann, M., & Schiaffino, S. (2021). Protein profile of fiber types in human skeletal muscle: a single-fiber proteomics study. *Skeletal muscle*, 11, 1-19.

Muroya, S., Nakajima, I., & Chikuni, K. (2003). Amino acid sequences of multiple fast and slow troponin T isoforms expressed in adult bovine skeletal muscles. *Journal of Animal Science*, 81(5), 1185-1192.

Muroya, S., Nakajima, I., Oe, M., & Chikuni, K. (2006). Difference in postmortem degradation pattern among troponin T isoforms expressed in bovine longissimus, diaphragm, and masseter muscles. *Meat Science*, 72(2), 245-251.

Negishi, H., Yamamoto, E., & Kuwata, T. (1996). The origin of the 30 kDa component appearing during post-mortem ageing of bovine muscle. *Meat Science*, 42(3), 289-303.

O'Halloran, G. R., Troy, D. J., & Buckley, D. J. (1997). The relationship between early post-mortem pH and the tenderisation of beef muscles. *Meat Science*, 45(2), 239-251.

Ouali, A. (1990). Meat tenderization: possible causes and mechanisms. A review. *Journal of Muscle Foods*, 1(2), 129-165.

Ouali, A., Gagaoua, M., Boudida, Y., Becila, S., Boudjellal, A., Herrera-Mendez, C. H., & Sentandreu, M. A. (2013). Biomarkers of meat tenderness: Present knowledge and perspectives in regards to our current understanding of the mechanisms involved. *Meat Science*, 95(4), 854-870.

Peter, J. B., Barnard, R. J., Edgerton, V. R., Gillespie, C. A., & Stempel, K. E. (1972). Metabolic profiles of three fiber types of skeletal muscle in guinea pigs and rabbits. *Biochemistry*, 11(14), 2627-2633.

Picard, B., & Gagaoua, M. (2020). Muscle fiber properties in cattle and their relationships with meat qualities: an overview. *Journal of Agricultural and Food Chemistry*, 68(22), 6021-6039.

Quiroz-Rothe, E., & Rivero, J. L. L. (2004). Coordinated expression of myosin heavy chains, metabolic enzymes, and morphological features of porcine skeletal muscle fiber types. *Microscopy Research and Technique*, 65(1-2), 43-61.

Ramos, P. M., Pedrão, M. R., Bell, L. C., Scheffler, T. L., Ramos, P. M., Pedrão, M. R., Bell, L. C., & Scheffler, T. L. (2021). Early postmortem metabolism and protease activation in fast glycolytic and slow oxidative bovine muscles. *Meat and Muscle Biology*, 5(1), 44-45.

Ramos, P. M., Wright, S. A., Delgado, E. F., van Santen, E., Johnson, D. D., Scheffler, J. M., Elzo, M. A., Carr, C. C., & Scheffler, T. L. (2020). Resistance to pH decline and slower calpain-1 autolysis are associated with higher energy availability early postmortem in Bos taurus indicus cattle. *Meat Science*, 159, 107925.

Rivero, J. L. L., Talmadge, R. J., & Edgerton, V. R. (1998). Fibre size and metabolic properties of myosin heavy chain-based fibre types in rat skeletal muscle. *Journal of Muscle Research and Cell Motility*, 19(7), 733-742.

Robert, N., Briand, M., Taylor, R., & Briand, Y. (1999). The effect of proteasome on myofibrillar structures in bovine skeletal muscle. *Meat Science*, 51(2), 149-153.

Rusman, Soeparno, Setiyono, & Suzuki, A. (2003). Characteristics of Biceps femoris and Longissimus thoracis muscles of five cattle breeds grown in a feedlot system. *Animal Science Journal*, 74(1), 59-65.

Santos, D., Monteiro, M. J., Voss, H. P., Komora, N., Teixeira, P., & Pintado, M. (2021). The most important attributes of beef sensory quality and production variables that can affect it: A review. *Livestock Science*, 250, 104573.
Scheffler, T. L., Leitner, M. B., & Wright, S. A. (2018). Technical note: Protocol for electrophoretic separation of bovine myosin heavy chain isoforms and comparison to immunohistochemistry analysis. *Journal of Animal Science*, 96(10), 4306–4312.

Schiaffino, S., & Reggiani, C. (2011). Fiber types in mammalian skeletal muscles. *Physiological Reviews*, 91(4), 1447–1531.

Sentandreu, M. A., Coulis, G., & Ouali, A. (2002). Role of muscle endopeptidases and their inhibitors in meat tenderness. *Trends in Food Science & Technology*, 13(12), 400–421.

Smuder, A. J., Kavazis, A. N., Hudson, M. B., Nelson, W. B., & Powers, S. K. (2010). Oxidation enhances myofibrillar protein degradation via calpain and caspase-3. *Free Radical Biology and Medicine*, 49(7), 1152–1160.

Song, S., Park, J., Im, C., Cheng, H., Jung, E. Y., Park, T. S., & Kim, G. D. (2022). Muscle fiber type-specific proteome distribution and protease activity in relation to proteolysis trends in beef striploin (M. longissimus lumborum) and tenderloin (M. psoas major). *LWT*, 171, 114098.

Stafford, C. D., Taylor, M. J., Buhler, J. F., Dang, D. S., Thornton, K. J., Gerrard, D. E., & Matarneh, S. K. (2024). Muscle proteolysis is differentially influenced by mitochondrial intactness. *Meat Science*, 207, 109368.

Talmadge, R. J., & Roy, R. R. (1993). Electrophoretic separation of rat skeletal muscle myosin heavy-chain isoforms. *Journal of Applied Physiology*, 75(5), 2337-2340.

Torrescano, G., Sánchez-Escalante, A., Giménez, B., Roncalés, P., & Beltrán, J. A. (2003). Shear values of raw samples of 14 bovine muscles and their relation to muscle collagen characteristics. *Meat Science*, 64(1), 85–91.

Van Metre, D. C., Callan, R. J., & Garry, F. B. (2001). Examination of the musculoskeletal system in recumbent cattle. *Compendium*, 23(2), S5-S24.

Vaskoska, R., Vénien, A., Ha, M., White, J. D., Unnithan, R. R., Astruc, T., & Warner, R. D. (2021). Thermal denaturation of proteins in the muscle fibre and connective tissue from bovine muscles composed of type I (masseter) or type II (cutaneous trunci) fibres: DSC and FTIR microspectroscopy study. *Food Chemistry*, 343, 128544.

Veiseth-Kent, E., Pedersen, M. E., Rønning, S. B., & Rødbotten, R. (2018). Can postmortem proteolysis explain tenderness differences in various bovine muscles? *Meat Science*, 137, 114–122.

Warner, R., Miller, R., Ha, M., Wheeler, T. L., Dunshea, F., Li, X., Vaskoska, R., & Wheeler, T. (2021). Meat tenderness: Underlying mechanisms, instrumental measurement, and sensory assessment. *Meat and Muscle Biology*, 4(2).

Warren, C. M., Krzesinski, P. R., & Greaser, M. L. (2003). Vertical agarose gel electrophoresis and electroblotting of high-molecular-weight proteins. *Electrophoresis*, 24(11), 1695–1702.

White, A., O'Sullivan, A., Troy, D. J., & O'Neill, E. E. (2006). Manipulation of the pre-rigor glycolytic behaviour of bovine M. longissimus dorsi in order to identify causes of inconsistencies in tenderness. *Meat Science*, 73(1), 151–156.

Xue, M., Huang, F., Huang, M., & Zhou, G. (2012). Influence of oxidation on myofibrillar proteins degradation from bovine via µ-calpain. *Food Chemistry*, 134(1), 106–112.

Young, O. A., Graafhuis, A. E., & Davey, C. L. (1980). Post-mortem changes in cytoskeletal proteins of muscle. *Meat Science*, 5(1), 41–55.
Zimmerman, U. J. P., & Schlaepfer, W. W. (1991). Two-stage autolysis of the catalytic subunit initiates activation of calpain I. *Biochimica et Biophysica Acta (BBA) - Protein Structure and Molecular Enzymology*, **1078**(2), 192–198.
**Figure legends:**

**Fig. 1.** Representative SDS-PAGE gel of myosin heavy chain (MyHC) isoforms (top) and relative band intensity of MyHC-I, MyHC-IIa, and MyHC-IIx (bottom) in bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles. Data are least-squares means ± SE. <sup>a-c</sup>Means lacking a common letter differ significantly within each isoform (*P* ≤ 0.05).

**Fig. 2.** Relative abundance and comparison of metabolic indicators (protein markers) between bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles. A) representative western blot (top) and relative band intensity (bottom) of glyceraldehyde 3-phosphate dehydrogenase (GAPDH, glycolytic enzyme), B) representative western blot (top) and relative band intensity (bottom) of lactate dehydrogenase (LDH, glycolytic enzyme), C) representative western blot (top) and relative band intensity (bottom) of succinate dehydrogenase (SDH, oxidative enzyme), and D) representative western blot (top) and relative band intensity (bottom) of myoglobin (Mb, oxidative biomarker). Data are least-squares means ± SE. <sup>a-c</sup>Means lacking a common letter differ significantly (*P* ≤ 0.05).

**Fig. 3.** Evolution of pH in bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles at 0, 7, and 14 d postmortem. Data are least-squares means ± SE. Level of significance: ***, *P* ≤ 0.001.

**Fig. 4.** A) list of 21 collagen and proteoglycan proteoforms that were identified in the three muscles. B) heatmap clustering (Euclidean distance and ward clustering) highlighting the individual abundances of the 16 significantly different collagens (green) and proteoglycans (orange) from the 21 that were identified among the three muscle types (*P* ≤ 0.05). Lower protein abundances are in blue, and higher abundances are in red.

**Fig. 5.** Principal component analysis (PCA) highlighting the distribution of bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles based on the relationships among their respective intrinsic characteristics evaluated at 30 min postmortem utilizing both traditional biochemistry methods and targeted proteomics. An inserted bi-plot (bottom right) is given to show the extent of separation of the three muscles.

**Fig. 6.** Representative western blot of desmin proteolysis (top) and relative intensity of degraded desmin products (bottom) in bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles at 0, 7, and 14 d postmortem. Data are least-squares means ± SE. <sup>a-c</sup>Means lacking a common letter differ significantly within a time point (*P* ≤ 0.05). <sup>x-z</sup>Means lacking a common letter differ across time points within the same muscle (*P* ≤ 0.05).

**Fig. 7.** A) representative western blot of troponin-T-fast isoform (TT-fast) proteolysis (top) and relative intensity of degraded TT-fast products (bottom) in bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles at 0, 7, and 14 d postmortem. B) representative western blot of troponin-T-slow isoform (TT-slow) proteolysis (top) and relative intensity of degraded TT-slow products (bottom) in bovine MS, LT, and CT muscles at 0, 7, and 14 d postmortem. Data are least-squares means ± SE. <sup>a-c</sup>Means lacking a common letter differ significantly within a time point (*P* ≤ 0.05). <sup>x-z</sup>Means lacking a common letter differ across time points within the same muscle (*P* ≤ 0.05).
**Fig. 8.** A) representative SDS-PAGE gel of total protein separation profiles in bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles at 0, 7, and 14 d postmortem. The first lane (farthest left) represents the molecular weights (Mw) of the protein standard in kilodaltons (kDa). B and C) relative intensity of the proteolytic degradation fragments at the 110 kDa and 30 kDa protein bands, respectively. Data are least-squares means ± SE.
*Indicates means differ significantly within a time point. Level of significance: ***, *P* ≤ 0.001; **, *P* ≤ 0.01; *, *P* ≤ 0.05; ns, not significant (*P* > 0.05).

**Fig. 9.** A) representative western blot of calpain-1 autolysis (top) and relative band intensity of the 76 kDa subunit of calpain-1 (bottom) in bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles at 0, 7, and 14 d postmortem. B) representative western blot of calpastatin abundance in bovine MS, LT, and CT muscles at 0 d. Data are least-squares means ± SE. a,bMeans lacking a common letter differ significantly within a time point (*P* ≤ 0.05). x-zMeans lacking a common letter differ across time points within the same muscle (*P* ≤ 0.05).

**Fig. 10.** Caspase-3 activity (µM cleaved substrate/min/mg protein) in bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles at 0, 7, and 14 d postmortem. Data are least-squares means ± SE. *Indicates means differ significantly within a time point. Level of significance: ***, *P* ≤ 0.001; *, *P* ≤ 0.05.

**Fig. 11.** A) principal component analysis (PCA) demonstrating the progression of postmortem proteolysis considering desmin and troponin-T (fast and slow) degradation, calpain-1 autolysis, caspase-3 activity, and the intensity of the 30 and 110 kDa proteolytic fragments in bovine *Masseter* (MS), *Longissimus thoracis* (LT), and *Cutaneous trunci* (CT) muscles during the 14-d aging period. B) bi-plot highlighting the distribution and separation of the three muscles over the two aging times (7 d [♦] and 14 d [▲]) compared to the sampled taken 0 d (●) postmortem.
<figure><img src="image_3.png" /><figcaption>Fig. 1</figcaption></figure>
A

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

B

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

C

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

D

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /><figcaption>Fig. 2</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>Fig. 3</figcaption></figure>
A

<table><thead><tr><th>Uniprot ID</th><th>Gene name</th><th>Full protein name</th><th>Core matrisome component</th></tr></thead><tbody><tr><td>F1N401</td><td>COL12A1</td><td>Collagen type XII alpha 1 chain</td><td rowspan="8">Collagens</td></tr><tr><td>E1BA17</td><td>COL14A1</td><td>Collagen type XIV alpha 1 chain</td></tr><tr><td>F1MUC5</td><td>COL15A1</td><td>Collagen type XV alpha 1 chain</td></tr><tr><td>F1N6W9</td><td>COL18A1</td><td>Collagen type XVIII alpha 1 chain</td></tr><tr><td>P02453</td><td>COL1A1</td><td>Collagen alpha-1(I) chain</td></tr><tr><td>P02465</td><td>COL1A2</td><td>Collagen alpha-2(I) chain</td></tr><tr><td>Q08E14</td><td>COL3A1</td><td>Collagen type III alpha 1 chain</td></tr><tr><td>E1BI98</td><td>COL6A1</td><td>Collagen type VI alpha 1 chain</td></tr><tr><td>F1MKG2</td><td>COL6A2</td><td>Collagen type VI alpha 2 chain</td><td rowspan="5">Proteoglycans</td></tr><tr><td>E1BB91</td><td>COL6A3</td><td>Collagen type VI alpha 3 chain</td></tr><tr><td>F1MD40</td><td>COL6A6</td><td>Collagen type VI alpha 6 chain</td></tr><tr><td>Q3ZBN5</td><td>ASPN</td><td>Asporin</td></tr><tr><td>P21809</td><td>BGN</td><td>Biglycan</td></tr><tr><td>P21793</td><td>DCN</td><td>Decorin</td><td></td></tr><tr><td>F1MER7</td><td>HSPG2</td><td>Heparan sulfate proteoglycan 2</td><td></td></tr><tr><td>O62702</td><td>KERA</td><td>Keratocan</td><td></td></tr><tr><td>Q05443</td><td>LUM</td><td>Lumican</td><td></td></tr><tr><td>P19879</td><td>OGN</td><td>Mimecan</td><td></td></tr><tr><td>E1BHH6</td><td>PODN</td><td>Podocan</td><td></td></tr><tr><td>A6QQQ3</td><td>PRELP</td><td>Prolargin</td><td></td></tr><tr><td>P81282</td><td>VCAN</td><td>Versican core protein</td><td></td></tr></tbody></table>

B

<figure><img src="image_13.png" /><figcaption>Fig. 4</figcaption></figure>
<figure><img src="image_14.png" /><figcaption>Fig. 5</figcaption></figure>
<figure><img src="image_15.png" /><figcaption>Fig. 6</figcaption></figure>
A

<figure><img src="image_16.png" /><figcaption>Fig. 7</figcaption></figure>

B

<figure><img src="image_17.png" /></figure>
A

<figure><img src="image_18.png" /></figure>

B

<figure><img src="image_19.png" /></figure>

C

<figure><img src="image_20.png" /><figcaption>Fig. 8</figcaption></figure>
A

<figure><img src="image_21.png" /><figcaption>Fig. 9</figcaption></figure>

B

<figure><img src="image_22.png" /></figure>
<figure><img src="image_23.png" /><figcaption>Fig. 10</figcaption></figure>
A

<figure><img src="image_24.png" /></figure>

B

<figure><img src="image_25.png" /><figcaption>Fig. 11</figcaption></figure>