Understanding the development of color and color stability of dark cutting beef based on mitochondrial proteomics

Journal Pre-proof Understanding the development of color and color stability of dark cutting beef based on mitochondrial proteomics

Shuang Wu, Xin Luo, Xiaoyin Yang, David L. Hopkins, Yanwei Mao, Yimin Zhang PII:

S0309-1740(19)31119-2

DOI:

https://doi.org/10.1016/j.meatsci.2020.108046

Reference:

MESC 108046

To appear in:

Meat Science

Received date:

19 November 2019

Revised date:

31 December 2019

Accepted date:

2 January 2020

Please cite this article as: S. Wu, X. Luo, X. Yang, et al., Understanding the development of color and color stability of dark cutting beef based on mitochondrial proteomics, Meat Science (2020), https://doi.org/10.1016/j.meatsci.2020.108046

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© 2020 Published by Elsevier.

Journal Pre-proof Understanding the development of color and color stability of dark cutting beef based on mitochondrial proteomics Shuang Wua, Xin Luoa, Xiaoyin Yanga, David L. Hopkinsa,b, Yanwei Maoa, Yimin Zhanga* a

Lab of Beef Processing and Quality Control, College of Food Science and

Engineering, Shandong Agricultural University, Taian, Shandong, 271018, P. R. China b

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NSW Department of Primary Industries, Centre for Red Meat and Sheep

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Development, PO Box 129, Cowra NSW 2794, Australia

*Corresponding author: Yimin Zhang

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Address:

Lab of Beef Processing and Quality Control

Shandong Agricultural University

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College of Food Science and Engineering

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61#, Daizong Street, Taian, Shandong, 271018, P. R. China

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Tel: (86) 538-8242745 & (86) 538-8248255; Fax: (86) 538-8242745

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Email: [email protected]

Journal Pre-proof Abstract: Label- free proteomics was applied to understand the color and color stability development of dark cutting beef (DC). The color traits of DC (pH = 6.86) and normal beef (pH = 5.49) were determined during 7 days of display. DC had a lower redness and greater color stability, which was attributed to its higher deoxy- myoglobin content,

greater oxygen consumption, as well as higher

metmyoglobin reducing activity and lower lipid oxidation. A total of 28 differentially expressed mitochondrial proteins (fold change >1.8) between the two groups were identified, with 21 proteins overexpressed in DC mainly involved in oxidative

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phosphorylation, generation of reducing equivalent, TCA cycle and chaperones. These enhance the level of mitochondrial respiration, the stability of reducing MetMb and

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myoglobin and mitochondria function, leading to color characteristics of DC.

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Moreover, Glutaryl-CoA dehydrogenase was for the first time reported to be significantly associated with color parameters and its direct relationship with meat

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color is worthy investigation.

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Keywords: Dark cutting beef; Color stability; Label-free; Mitochondria

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1. Introduction

Meat color is one of the most important quality traits influencing consumers decisions,

since

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purchasing

consumers

generally

evaluate

freshness

and

wholesomeness of meat through surface color (Mancini & Hunt, 2005), and consumers usually regard a bright cherry red color of meat as fresh and wholesome (Suman, Hunt, Nair, & Rentfrow, 2014). Dark cutting beef (DC), which exhibits a very dark color, is characteristically rejected by most consumers due to its appearance; moreover, high pH beef is more prone to microbe growth, which can severely shorten the shelf life of fresh meat (Gill & Newton, 1979). It was reported that the dark color of beef caused a loss of $165 -170 million to the US beef industry in 2000 (Smith, et al., 2000; McKenna, et al., 2002). However, DC shows better color stability compared with normal pH beef (English et al., 2016) and the underlying mechanisms at the molecular-level has not been clarified yet. DC is usually considered to be caused by the depletion of glycogen due to

Journal Pre-proof pre-slaughter stress, and the resulting high ultimate pH increases the water-holding capacity of muscle and mitochondrial activity, leading to a darker meat color (Ashmore, Doerr, Foster, & Carroll, 1971; Hughes, Clarke, Purslow, & Warner, 2017). Mitochondria are double- membrane-bound organelles composed of inner and outer membranes, and are the main site for cell respiration. The o uter membrane is a phospholipid bilayer that completely surrounds organelles, and allows ions and small molecules to easily pass through. The inner membrane contains electron transport complexes and proteins; the proteins can participate in specific carrie r transport of

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metabolites and intermediates, oxidative phosphorylation and ATP synthesis. The mitochondrial matrix contains many proteins involved in biochemical reactions such

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as the tricarboxylic acid cycle, lipid oxidation and amino acid degradation. I n vivo,

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myoglobin transports oxygen to mitochondria in the muscle for oxidative metabolism, providing energy for the body. In postmortem bovine cardiac muscle, mitochondria

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can still consume oxygen even after 60 days of storage at 4 o C under vacuum packaging (Tang et al., 2005a). Therefore, mitochondria play an important role in

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myoglobin redox, on the one hand, because increased mitochondrial activity enhances

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oxygen consumption causing darker muscle, and on the other hand, mitochondria can influence metmyoglobin reducing activity (Ramanathan & Mancini, 2018; Tang,

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Faustman, Mancini, Seyfert, & Hunt, 2005). Taken together, it is important to explore the underlying mechanisms of the development of the specific color and color stability of DC, in the perspective of mitochondria. In recent years, the application of proteomics in meat science has greatly promoted the understanding of complex biological mechanisms and the discovery of biomarkers related to quality traits (Picard, Lefèvre, & Lebret, 2012). Label- free quantitative proteomics technology is based on the use of liquid chromatography-mass spectrometry (LC-MS) for peptide mass spectrum analysis, which does not need to use expensive internal standards such as stable isotope labels, and it is known as a simple, convenient, reliable and cost-effective proteomic methodology, that has been applied to the meat science field. Previous studies have compared proteome changes during post- mortem storage (Yu et al., 2017) and within 24 h (Yu et al., 2018) to

Journal Pre-proof reveal muscle-specific color stability by the label- free strategy. Furthermore, label- free quantitative proteomics was applied to investigate the causes and consequences of beef variation in pHu (Poleti et al., 2018). However, the comparison of the mitochondrial proteome between DC and normal pH beef using label- free proteomic analysis has not been reported yet. Meanwhile, the underlying mechanism of the role of mitochondria in color stability is not completely clear. Therefore, the objective of the present stud y was to compare the difference in the mitochondrial proteome between DC and normal pH beef and to evaluate the

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relationship between meat color attributes and differentially expressed proteins to reveal their underlying association with the development of the typical meat color and

2. Material and methods

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2.1. Animal and sample preparation

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color stability of DC beef.

Eight normal pH (ultimate pH = 5.4 - 5.8, n = 8) beef carcasses and the same

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number of dark cutting (ultimate pH > 6.1, n = 8) beef carcasses were selected from a

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commercial abattoir. Muscle pH was determined on the anterior surface of Longissmus lumborum (LL) between the 12 - 13th rib on the right side of each carcass

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using a portable pH meter (Senven2Go-S2, Mettler-Toledo, Switzerland). The LL were removed from the right side of the carcasses at 48 h postmortem (chilling at 0 4 °C), commercially vacuum packaged, and then transported to the laboratory on ice. Following overnight storage, each LL was cut into eight 2.5-cm-thick steaks, kept on foam trays with absorbent pads (DLS-25, Sealed Air Corp., Danbury, USA), overwrapped with Polyethylene (PE) film (water vapor permeability: 23.5 g/m2 /24h, oxygen transmission rate: 16654 cm3 /m2 /24h/atm, and then assigned randomly to days 0, 3, 5 and 7 for retail display (each day there were 2 duplicate steaks) at 2 ± 1°C under continuous lighting (1600 to 2000 lx, Leishi Warm Yellow Light-Emitting Diode Light; color temperature = 3000°K). All steaks were rotated daily to minimize the variance in light intensity or temperature caused by the location. pH value, color traits, relative myoglobin content, oxygen consumption, metmyoglobin reducing

Journal Pre-proof activity and lipid oxidation were evaluated on each display day. Samples obtained on day 0, were frozen and stored at -80 °C for mitochondrial proteome analyses. 2.2. pH pH values of each steak were measured directly using a portable pH meter with temperature compensation, and the probes were inserted into steak (about 2 cm depth) at four different locations and averaged. Calibration of the pH probe was conducted in buffers at pH 4.00 and 7.00 at 4 °C, before use. 2.3. Color attributes and relative myoglobin content

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The surface color of steaks on display day 0 (blooming for 2 h at 0 - 4 °C), days 3, 5 and 7 was measured by a colorimeter (Model SP62; 8 mm diameter aperture,

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Illuminant A, 10° observer; X-Rite, Inc., Grand Rapids, USA). The CIE L* (lightness), a* (redness) and b* (yellowness) values of each steak was measured four times and

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averaged. Chroma and hue values were calculated using the equation: [(a* 2 + b* 2 ) 0.5 ]

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and [(arctangent (b*/a*)], respectively. The reflected wavelengths of the instrument were recorded in the range of 400 - 700 nm at 10-nm intervals and the ratio of

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reflectance at 630 nm and 580 nm (R630/580) was used to directly evaluate the color

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stability during display. The reflectance (R) at 473, 525, 572 and 700 nm was converted to reflex attenuance (A) using the equation: A = log (1/R) and the relative

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percentage of three myoglobin redox forms was calculated following outlined equations (AMSA, 2012):

𝐴572−𝐴700

% MetMb= (1.395 − 𝐴525−𝐴700 ) × 100 A473 −A700

% DeoxyMb=[2.35 × (1 − 𝐴525 −𝐴700 )] × 100 % OxyMb=100 − (%MetMb + %DeoxyMb) 2.4. Metmyoglobin reducing activity and oxygen consumption MRA determination was conducted according to the method described by Sammel, Hunt, Kropf, Hachmeister, & Johnson, (2002) and Ramanathan, Hunt, English, Mafi, & VanOverbeke (2019) with minor modification. A cube (2.54 × 2.54 × 2.54 cm3 ) with no connective tissue or visible fat was removed from the central location of each steak. Then cube was bisected horizontally, resulting in two half pieces. The top piece

Journal Pre-proof (including the surface exposed light) was submerged in a 0.3 % (w/v) solution of sodium nitrite for 20 min at 20 °C, then was removed, blotted dry, vacuum packaged and the reflectance immediately measured on the sample surface using the colorimeter mentioned previously. The resistance to myoglobin oxidation was used as an indicator of MetMb reducing property, and it was reported as K/S572 ÷ K/S525. A greater K/S572 ÷ K/S525 ratio indicates lower MetMb formation, thus a greater MRA. According to Ramanathan et al. (2019), the K/S572 ÷ K/S525 ratio was converted to a relative percentage, in order to make the values easily visualized, and the highest

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numerical MRA ratio was considered as 100% and others were reported as relative to the highest MRA ratio.

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Muscle oxygen consumption was measured as described by Madhavi &

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Carpenter (1993) and McKeith, et al. (2016) with some modification. The freshly cut surface of the bottom half was covered with PE film previously mentioned and

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bloomed for 2 h at 2 °C, vacuum packaged, and the reflectance of bloomed surface immediately measured to determine initial OxyMb content by using K/S ratios and

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equations (AMSA, 2012). The packaged sample was incubated for 30 min at 30 °C

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and then measured again to determine the final OxyMb content. The OC was calculated following the equation: [(initial OxyMb % − final OxyMb %) / initial

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OxyMb%] × 100.

2.5. Lipid oxidation

Lipid oxidation was evaluated through 2-thiobarbituric acid reactive substances values according to a modified procedure of Siu & Draper, (1978). Four grams of sample randomly collected from both the surface and interior of the steak, was homogenized for 1 min in 20 ml of distilled water by an Ultra-Turrax T18 homogenizer (T18; IKA, Germany). Subsequently, 20 ml of 10 % (w/v) trichloroacetic acid was added to the homogenate and vortex blended, and filtered through a Whatman (#1) filter paper. Then 1 mL of 60 mM 2-thiobarbituric acid solution was mixed with 4 mL of filterate and incubated in a water bath at 80 °C for 90 min. After the mixture solution cooled down to room temperature, absorbance was measured using a microplate spectrophotometer (EpochT M 2, Bio Tek Instruments,

Journal Pre-proof USA) at 532 nm and calculated with a standard curve of Triethyl phosphate (TEP) solution (Sigma, USA). The results were expressed as A532nm values and 2-thiobarbituric acid reactive substances in Malondialdehhyde (MDA) equivalents (mg /kg meat), since thiobarbituric acid can also react with other aldehydes to yield a pink chromophore except MDA. 2.6. Proteomic analysis 2.6.1. Mitochondrial isolation Mitochondria were isolated from muscles using the method described by Lanari &

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Cassens (1991) with slight modification. Samples from DC and normal pH beef (10 g) were minced finely, and transferred to a beaker with 20 mL of mitochondrial

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suspension buffer (250 mM sucrose, 10 mM HEPES, pH 7.2). Trypsin was added to

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the suspension (trypsin/tissue, 1 mg/g) and this was hydrolyzed for 15 min. Then, the suspension buffer was diluted with mitochondrial isolation buffer (67 mM sucrose, 50

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mM Tris-HCl, 50 mM KCl, 10 mM EDTA and 0.2 % BSA) to 100 mL, and homogenized with a tissue grinder (DY89-II, Xinzhi, China). The homogenate was

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centrifuged for 15 min at 900 × g (5804R, Eppendorf, Germany), the supernatant

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decanted and centrifuged for 15 min at 14,000 × g. After that, the supernatant was discarded and the pellet was washed twice with mitochondrial suspension buffer.

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2.6.2. Mitochondrial proteins extraction and digestion Mitochondrial proteins were extracted from mitochondria according to Wiśniewski, Zougman, Nagaraj, & Mann (2009). The mitochondrial pellet was sonicated in sodium dithionite (SDT) lysis buffer (4 % SDS, 100 mM Tris‐HCl, 1 mM DTT, pH 7.6) for 100 s using an ultrasonic cell disruptor (JY92-II, Xinzhi, China) and boiled for 15 min. After being centrifuged at 14,000 × g for 40 min, the protein content of the supernatant was quantified using a BCA Protein Assay Kit (Bio-Rad, USA). Then 200 μg of protein from each sample was incorporated into 30 μl SDT buffer (4% SDS, 100 mM DTT, 150 mM Tris-HCl pH 8.0). The detergent, DTT and other low- molecular-weight components were removed using UA buffer (8 M Urea, 150 mM Tris-HCl pH 8.0) by repeated ultrafiltration (Microcon units, 10 kD). Then 100 μl iodoacetamide (100 mM IAA in UA buffer) was added to block reduced cysteine

Journal Pre-proof residues and the samples were incubated for 30 min in darkness. The filters were washed with 100 μl UA buffer three times and then with 100 μl 25 mM NH4 HCO 3 buffer twice. Finally, the protein suspensions were digested with 4 μg trypsin (Promega) in 40 μl 25mM NH4 HCO 3 buffer overnight at 37 °C, and the resulting peptides were collected as a filtrate. The peptides of each sample were desalted on C18 Cartridges (Empore™ SPE Cartridges C18 (standard density), bed I.D. 7 mm, volume 3 ml, Sigma), concentrated by vacuum centrifugation and reconstituted in 40 µl of 0.1% (v/v) formic acid. The peptide content was estimated by UV light spectral

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density at 280 nm using an extinction coefficient of 1.1 of 0.1% (g/l) solution that was calculated on the basis of the frequency of tryptophan and tyrosine in vertebrate

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proteins.

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2.6.3. HPLC-MS/MS analysis

Digested peptides of each sample were analyzed by nano LC-MS/MS analysis. The

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peptide mixture was loaded onto a reverse phase trap column (Thermo Scientific Acclaim PepMap100, 100 μm*2 cm, nanoViper C18) connected to the C18-reverse

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phase analytical column (Thermo Scientific Easy Column, 10 cm long, 75 μm inner

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diameter, 3 μm resin) in buffer A (0.1% Formic acid) and separated with a linear gradient of buffer B (84% acetonitrile and 0.1% Formic acid) at a flow rate of 300

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nl/min controlled by IntelliFlow technology. The linear gradient was 0.55 % buffer B for 110 min, 55-100 % buffer B for 5 min, hold in 100 % buffer B for 5 min. LC-MS/MS analysis was performed on a Q Exactive mass spectrometer (Thermo Scientific) that was coupled to an Easy nLC (Proxeon Biosystems, now Thermo Fisher Scientific) for 120 min. The mass spectrometer was operated in positive ion mode. MS data was acquired using a data-dependent top10 method dynamically choosing the most abundant precursor ions from the survey scan (300-1800 m/z) for HCD fragmentation. Automatic gain control (AGC) target was set to 3e6, and maximum inject time to 10 ms. Dynamic exclusion duration was 40.0 s. Survey scans were acquired at a resolution of 70,000 at m/z 200 and resolution for HCD spectra was set to 17,500 at m/z 200, and isolation width was 2 m/z. Normalized collision energy was 30 eV and the underfill ratio, which specifies the minimum percentage of

Journal Pre-proof the target value likely to be reached at maximum fill time, was defined as 0.1 %. The instrument was run with peptide recognition mode enabled. 2.6.4. Data analysis The MS data were analyzed using MaxQuant software version1.5.3.17 (Max Planck Institute of Biochemistry in Martinsried, Germany) and searched in Uniprot database for Bos taurus (uniprot-bovin_170221.fasta). The following parameters included the trypsin used as the enzyme, two max missed cleavages, following the main search of 6 ppm, first search of 20 ppm and MS/MS tolerance of 20 ppm.

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Carbamidomethylation of cysteine was used as fixed modification and oxidation of methionine, and acetylation of N-term protein as variable modifications. The filtering

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criteria of both peptide and protein was a false discovery rate (FDR) ≤0.01 and

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protein quantification was performed by razor and unique peptides. A hierarchical cluster analysis (HCA) and volcano plot combined with fold-change analysis and

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t-tests were performed. The differentially expressed proteins were identified based on the proteins with a minimum fold change of 1.5 (dark cutting group/normal pH group,

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ratio > 1.5 or < 0.6667, P < 0.05), and the overexpressed protein mentioned in the text

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was in reference to those proteins which had a high LFQ (lable free quantification)

above 1.5.

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intensity in the dark cutting group relative to the normal pH group, with the ratio

2.6.5. Bioinformatics analysis The

Kyoto

Encyclopedia

of

Genes

and

Genomes

(KEGG)

database

(http://www.genome.jp/kegg/) was used to retrieve the pathways. To further explore the impact of differentially expressed protein in cell physiological processes and discover internal relations between differentially expressed proteins, KEGG pathway enrichment analyses were applied based on the Fisher’ exact test and protein-protein interactions (PPI) were analyzed using STRING data (http://string-db.org/). 2.7. Statistical analysis In this experiment, statistical analysis was performed using the MIXED procedure (SAS, Version 9.0). The pH values, color attributes, relative content of myoglobin, MRA, OC and lipid oxidation were analyzed, with ultimate pH (normal pH and dark

Journal Pre-proof cutting), display time and their interactions as fixed factors and carcasses as a random factor. Predicted means for protected F-tests were separated by using the diff option and were considered significant at P < 0.05. Stepwise multiple linear regression was used to assess the relationship between differentially expressed proteins and color traits (across pH groups). A significance level at P < 0.05 for both entry and removal of variables was applied in the models (SPSS 18.0).

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3. Results and discussion

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3.1. Instrumental color and color stability

pH value plays a critical role in meat quality, which can affect meat color through

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influencing oxygen consumption and metmyoglobin reducing activity (Ramanathan &

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Mancini, 2018). No interaction effect (P > 0.05) of ultimate pH (pHu) and display time was found for pH values (Table 1), while pHu had a significant effect on pH

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value. As expected, the pH value of (Dark cutting beef) DC (6.86) was much greater (P < 0.05) than that of normal pH beef (5.49).

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The pHu had an effect on L* value (P < 0.05), and L* values of DC beef were

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lower (P < 0.05) than normal pH beef, which was supported by several studies

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(English et al., 2016; Holman & Hopkins, 2019; Mahmood, Turchinsky, Paradis, Dixon, & Bruce, 2018; Wulf, Emnett, Leheska, & Moeller, 2002). As pH values increase, the water holding capacity of muscle proteins becomes greater which can cause swelling of fibers and shrinkage of the space between muscle fibrils. This decreases light scattering and increases light absorption by myoglobin and as a consequence, the muscle surface color appears darker (Hughes et al., 2017; Ponnampalam et al., 2017). A significant interaction of pHu × display time occurred for a*, b*, Chroma and hue values (Table 1). The a*, b* and Chroma values of normal pH beef exhibited a broad trend to decrease (P < 0.05) with display time, while DC beef showed a trend to increase (P < 0.05) as display time extended. However, a*, b* and Chroma values of DC were lower than that of normal pH beef throughout display time (P < 0.05). These

Journal Pre-proof results are in agreement with some previous studies (Abril et al., 2001; Apple, Sawyer, Meullenet, Yancey, & Wharton, 2011). The hue values of both groups increased as samples were displayed from day 1 to day 7, and DC exhibited lower values, indicating less discoloration of DC beef (Ramanathan et al., 2019). In addition, R630/580 can be used to indicate the surface color changes especially during retail display, in which a greater ratio means a lesser amount of metmyoglobin (MMb) and thus a greater color stability (AMSA, 2012). Although DC had a lower R630/580 than normal pH beef, R630/580 of normal pH beef decreased (P < 0.05) over time while

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that of DC remained stable, indicating the DC beef was more color stable than normal pH beef.

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Myoglobin and its three redox forms determine meat color. There was an

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interaction of pHu × display time (P < 0.05) on % Deoxymyoglobin (DMb), % Oxymyoglobin (OMb) and % Metmyoglobin (MMb) (Fig. 1). The initial % DMb and %

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OMb of DC was significantly greater and lower than normal pH beef, respectively, which can partially explain the reason why the redness of DC was lower compared

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with normal pH beef. The % DMb of DC dropped significantly from 35.5 % to 16.1%,

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meanwhile the % OMb increased significantly, which was responsible for the increased redness during display time, and which indicates that DC can still bloom

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during display. With display time prolonged, the % OMb of normal pH beef decreased (P < 0.05), and the % MMb of both pHu beef increased (P < 0.05), while the % MMb accumulation was faster in normal pH beef than DC beef. This was in agreement with the results of redness in normal pH beef, which decreased as display time extended. MRA (metmyoglobin reducing ability) is the ability of muscle to reduce metmyoglobin, which is crucial for meat color shelf life. There was an interaction between pHu × display (P < 0.05) for the relative MRA (%) (Table 2). DC exhibited greater (P < 0.05) MRA compared with normal pH beef. As display time extended, the reducing ability of beef in both pH groups decreased. This is consistent with the results that obtained by Ramanathan et al. (2019), who investigated the relative MRA of normal and high pH beef with three packaging methods during 62 days of aging. Similar to MRA, DC showed greater oxygen consumption (OC) than normal pH beef

Journal Pre-proof over time. Meanwhile, as display time extended, OC decreased for both pHu beef groups (P < 0.05). Some studies have reported that DC had a greater % DMb than normal pH beef, due to enhanced mitochondrial respiration, leaving less oxygen available for the surface myoglobin leading to more DMb formation (Cornforth & Egbert, 1985; English et al., 2016). In fact, a proper OC is essential for color stability. A very low OC leads to low reducing equivalents (NADH) generation, which transfers an electron to the ferric iron of MMb leading to reduced MMb, and high OC enhances the capacity of mitochondria to compete for available oxygen with

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myoglobin, resulting in more DMb or MMb formation (Sammel et al., 2002; Seyfert et al., 2006).

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Lipid oxidation is one of the most important factors affecting meat color

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deterioration during postmortem storage or display time. The TBARS value of normal pH beef significantly increased (from 0.16 to 0.55 of MDA equivalents, and from 0.07

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to 0.12 of Absorbance at 532 nm) during display, while the TBARS value of DC increased (P > 0.05) slightly, with normal pH beef exhibiting greater (P < 0.05)

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TBARS values than DC beef after 7 days of display (Table 2). This may be caused by

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the slightly higher (P < 0.05) fat content (data not shown) in normal pH beef, as English et al. (2016) and Ramanathan et al. (2019) also found a lower fat content and

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higher moisture content in dark cutting beef, hence a higher TBARS in dark cutting beef. Purohit, Singh, Kerr, & Mohan, (2015) found a strong and negative correlation (-0.93) in LL between TBARS values and pH, supporting the observed results of our study. The lower level of TBARS of DC may attribute to the high level of the mitochondrial respiration, leading to less oxygen available for lipid oxidation. 3.2. Mitochondrial protein identification and proteomic profile In the present study, a total of 1,319 proteins were identified using label free mass spectrometry. The protein spots in the volcano plot (Fig. 2) were completely separated, indicating differentially expressed intensity of these proteins. A total of 321 proteins were significantly different between the DC and normal pH group, and 132 proteins located in the upper left region of volcano plots were overexpressed in normal pH beef (DC group/normal pH group < 0.667, P < 0.05) and 189 proteins located in the

Journal Pre-proof upper right region of volcano plots were overexpressed in DC (DC group/normal pH group > 1.5, P < 0.05). By subcellular localization of these identified proteins, a total of 63 mitochondrial proteins were identified, including 9 proteins overexpressed in the normal pH group, with 50 proteins overexpressed in the DC group and 4 proteins exclusively expressed in this same group. In order to intuitively compare the expressed intensity of differentially expressed proteins of different samples, a hierarchical cluster analysis (HCA) was performed (Fig. 3). A protein from different samples, but within the same

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group (DC or normal pH beef) almost displayed a similar color, and displayed a different color if the samples were from different sample groups, which indicated that

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the biological repetition was good and these differentially expressed mitochondrial

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proteins may be the intrinsic cause of the quality difference between DC and normal pH beef.

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All differentially expressed mitochondrial proteins (54 overexpressed in DC group and 9 in normal pH) can be classified into six categories according to their functions,

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including metabolic enzymes, oxidoredutase, electron transfer protein, chaperone,

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porins and others (www.unitprot.org). And in Table 3, only the proteins with the differential ratio of the expressed proteins (DC group/normal pH group) above 1.80 (n

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= 21) or below 0.556 (n = 7) were listed. 3.2.1. Metabolic enzymes

Amongst nine metabolic enzymes, only one (Lactate dehydrogenase D (LDHD)) was overabundant in the normal pH group, and eight were overabundant in DC group (Table 3). Most of those metabolic enzymes were directly or indirectly involved in energy

metabolism

(Inorganic

pyrophosphatase

2

(PPA2),

ATP-dependent

6-phosphofructokinase (PFKM), Pyruvate dehydrogenase kinase 4 (PDK4)), fatty acid

metabolism/degradation

(3-hydroxyisobutyryl-CoA

hydrolase

(HIBCH),

Enoyl-CoA hydratase (ECHS1), 2,4-dienoyl-CoA reductase 1 (DECR1)), amino acid metabolism/degradation (HIBCH, Aspartate aminotransferase (GOT2)), or TCA cycle (Aconitate hydratase (ACO2), PDK4, LDHD). PPA2, PFKM and PDK4 are all involved in the phosphorylation process, of which

Journal Pre-proof PPA2 catalyzes the conversion of pyrophosphate to two phosphate ions, in a highly exergonic reaction, and it plays a critical role in lipid metabolism and other biochemical transformations. PFKM catalyzes the phosphorylation of D- fructose 6-phosphate to fructose 1,6-bisphosphate by ATP, which is the first committing step of glycolysis. While PDK4 is part of the pyruvate dehydrogenase complex, and acts to inactivate the enzyme pyruvate dehydrogenase by phosphorylating it using ATP, this enzyme also participates in pyruvate metabolism and produces acetyl coenzyme A that is an indispensable substrate for TCA (www.unitprot.org; Gao, Wu, Ma, Li, &

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Dai, 2016). The higher expression of those energy metabolism related enzymes in the DC group indicates the higher energy utilization rate in DC beef compared with

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normal pH beef, although DC beef has less energy storage. This results in a higher

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respiratory rate in DC, leading to less available oxygen binding to myoglobin, and thus the development of a dark appearance.

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Fatty acid metabolism, especially fatty acid β-oxidation, is an important pathway of energy metabolism. Three enzymes, including Enoyl-CoA hydratase (ECHS1), hydrolase

(HIBCH),

2,4-dienoyl-CoA

reductase

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3-hydroxyisobutyryl-CoA

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(DECR1), participate in fatty acid metabolism (Heath, Su, Murphy, & Rock, 2000; www.unitprot.org) and were overexpressed in the DC group. HIBCH is involved in

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L-valine degradation and fatty acid β-oxidation, and DECR1 is an important enzyme for the fatty acid beta-oxidation of unsaturated fatty acids (www.unitprot.org). The fatty acid metabolic enzymes in the present study mainly participate in fatty acid β-oxidation that demand more oxygen when producing ATP (Yu et al., 2018), which indicates greater fatty β-oxidation in the DC group. Previous study reported that enzymes of fatty β-oxidation in PM (psoas major, Poxidative muscles) were more overabundant than in LL (glycolytic muscles) (Yu et al., 2018). The tricarboxylic acid (TCA) cycle is an important pathway of energy and substance metabolism, accompanied by the production of energy and reduction equivalents (NADH and FADH2 ) that promote mitochondrial electron transfer chains and influence beef color stability during storage or display period. Aspartate aminotransferase (GOT2) plays a key role in amino acid metabolism, and produces

Journal Pre-proof oxaloacetate that is necessary for the TCA cycle (www.unitprot.org). Pyruvate dehydrogenase kinase 4 (PDK4) participates in pyruvate metabolism and produces acetyl coenzyme A that is an indispensable substrate for TCA (www.unitprot.org; Gao, Wu, Ma, Li, & Dai, 2016). Aconitate hydratase (ACO2) and Malate dehydrogenase (MDH2) are the key enzymes for TCA, and they can catalyze the substrates to generate ATP and NADH. Mohan et al. (2010) reported that malate-NAD malate dehydrogenase increased NADH formation in beef. In support, ma late increased mitochondrial oxygen consumption in vitro (Ramanathan & Mancini, 2010). However,

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f

Lactate dehydrogenase D (LDHD) was found less-abundant in the DC group, and Ramanathan et al. (2011) assumed the pyruvate-mediated discoloration was related

pr

with the oxidization of NADH by pyruvate, but the underlying mechanisms still need

e-

further exploration.

Further, the high-energy electrons produced by TCA produce energy through

Pr

oxidative phosphorylation with the assistance of NADH and FADH2 . Previous studies reported that enzymes participating in the TCA cycle were overexpressed in PM due

al

to more abundant mitochondria and myoglobin in PM (Yu et al., 2018; Yu et al., 2017).

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These proteins were overexpressed in the DC group in this study. Howeve r, PM is considered a color- labile beef muscle, while dark cutting LL showed a more stable

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color than normal pH LL, which may be attributed to muscle fiber type differences and more antioxidant proteins in the LL of DC. It is reported that proteins participating in TCA cycle and energy metabolism were overexpressed more in dark pork compared with light pork (Sayd et al., 2006). Most of these proteins may facilitate the TCA cycle and mitochondrial respiration, which enhances the generation of NADH and electron transfer in electron transfer chains, thus these proteins contribute the reducing of metmyoglobin and oxygen consumption (Tang et al., 2005b), leading to greater MRA and a darkening color (Myoglobin is predominantly deoxymyoglobin). These results can partially explain the difference of meat color stability between DC and normal pH beef. 3.2.2. Oxidoreductase Glutaryl-CoA dehydrogenase (GCDH), Dehydrogenase/reductase SDR family

Journal Pre-proof member

7B

(DHRS7B),

Enoyl-[acyl-carrier-protein]

reductase

(MECR),

short/branched chain specific acyl-CoA dehydrogenase (ACADSB), isovaleryl-CoA dehydrogenase (IVD) and MDH2 can use oxidized electron-transfer flavoprotein (FAD), nicotinamide adenine dinucleotide phosphate (NADP) or Nicotinamide adenine dinucleotide (NAD+), as substrates to produec reduced electron-transfer flavoprotein (FADH2 ), NADPH or NADH (www.unitprot.org). NADH and FADH2 as reducing equivalents play an important role in the electron transfer chain, which promotes mitochondrial respiration and metmyoglobin reduction (Tang et al., 2005b),

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and further influences color and color stability. During storage or the display period, meat color stability decreased due to the depletion of NADH, which caused the

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accumulation of MetMb and meat discoloration (AMSA, 2012). Therefore, the

e-

overexpression of these oxidoreductase proteins in the DC group contributed to its color stability. Meanwhile, NADH can also protect the integrity of the mitochondria,

Pr

being beneficial to the respiration of the DC group (Ramanathan & Mancini, 2018). DHRS7B, a member of the SDR family, is a NAD-/NADP-dependent oxidoreductase

al

and it can promote the metabolism of exogenous carbonyl (Stambergova, Skarydova,

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Dunford, & Wsol, 2014), thus the overexpression of this protein may also be beneficial to reduce the toxicity of carbonyl to cells.

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3.2.3. Electron transfer protein

In addition, two proteins (Electron transfer flavoprotein subunit alpha, ETFA; Electron transfer flavoprotein subunit beta, ETFB) are involved in the electron transport chain. Both proteins can receive electrons from several mitochondrial dehydrogenases and transfer the electrons to the main mitochondrial respiratory chain. Both enzymes were overexpressed in the DC group, once again, implying a greater level of mitochondrial respiration, more content generation of reducing equivalent, as well as stonger oxidative stress in the muscle. 3.2.4. Chaperone The cellular proteins stability during cell stress is crucial to the survival and viability of cells. The maintaince of protein stability during cell stress is achieved by the stress- induced expression of chaperone proteins. 70 kDa Heat shock proteins

Journal Pre-proof (HSP70) participate in many different cellular processes, such as protecting unfold proteins from aggregation and dissoluting of protein agrregation and refolding (Dekker & Pfanner, 1997; Rüngeling, Laufen, & Bahl, 1999), futher protecting the integrity of cell function. GrpE protein homolog 1 (GRPEL1) and DnaJ homolog subfamily C member 11(DNAJC11) are the members of the HSP70 family, which can assist HSP70 family proteins to produce a marked effect (Mayer & Bukau, 2005). The increased expression of heat shock proteins in postmortem muscle may be a response to stress, and HSP70 plays a significant role in maintainning the integrity of cells and

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f

repairing denatured proteins (Picard & Gagaoua, 2017). GRPEL1 and DNAJC11 were overesxpressed in the DC group, and their chaperone function could reduce the

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damage of stress to cells, which may be neutralize the strong oxidative stress of DC

e-

and contribute to color stability. 3.2.5. Porin

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Voltage-dependent anion-selective channel protein 2 (VDAC2) is porin and can form a channel through the mitochondrial outer membrane and plasma membrane.

al

The channel at the outer mitochondrial membrane allows diffusion of small

rn

hydrophilic molecules achieving the exchanges of anion and metabolites between cytoplasm and mitochondria (Noskov, Rostovtseva, Chamberlin, Teijido, Jiang, &

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Bezrukov, 2016). In addition, it may participate in the release of mitochondrial products that trigger apoptosis (www.unitprot.org). Thus, VDAC2 possess the role in negative regulation of the intrinsic apoptotic signaling pathway. Poleti et al., (2018) found that there were differences in the expression of voltage-dependent anion-selective channel protein 3 between low pH and high pH beef. The over-expression of this protein in the DC group may suggest a higher anti-apoptotic activity of mitochondria in dark cutting beef. 3.2.6. Others Eukaryotic translation initiation factor 2 subunit 3 (EIF2S3) is a subunit of eukaryotic initiation factor 2 (eIF2), and involved in the early steps of protein synthesis (www.unitprot.org). Single-stranded DNA-binding protein (SSBP1) has the molecular function of binding single-stranded DNA and is involved in mitochondrial

Journal Pre-proof DNA relication (www.unitprot.org). Histidine triad nucleotide-binding protein 2 (HINT2) has adenosine phosphoramidase activity, and may play a role in apoptosis. Serine-tRNA ligase (SARS2) participates the seryl-tRNA aminoacylation process, and IARS2 protein (Fragment) (IARS2) is involved in the molecular function of aminoacyl-tRNA synthetase. FLOT1 protein (Fragment) (FLOT1), a lipid rafts protein, has been shown to regulate cell proliferation and signal transduction by receptor tyrosine kinases (Jang, Kwon, Choi, Lee, & Pak, 2019) and was overexpressed in normal pH group compared with the DC group. However, the specific functions of

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these proteins that promote the differences of meat color stability between DC and normal pH beef are yet unclear.

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Myozenin 3 (MYOZ3) and Myomesin (M-protein) 2, 165kDa (MYOM2) are both

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related with the structure of the myofibril, and MYOZ3 may serve as intracellular binding proteins involved in linking Z-disk proteins, while MYOM2 is an end line

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protein that is part of the M line. Both proteins were o ver-expressed in normal pH beef, which indicates that there were more myofibril fragmentations in normal pH

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beef compared with DC group, and the integrity of myofibril might be better in DC.

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3.3. Bioinformatics analyses

3.3.1. protein-protein interaction

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Meat is a complex system, and every biological process needs protein-protein interaction to complete. Therefore, the study of the protein-protein interaction network is of great significance to explain the function of proteins. The protein-protein interaction of the differentially expressed proteins between dark cutting and normal pH group were analyzed using the web STRING 11.0 (Fig. 4). In general, the greater the degree of protein connectivity (the number of proteins directly interacting with a protein in the network), the more important the role of the protein in the network and the thicker the connection line, the stronger the protein-protein interactions. Proteins which participate in electron transfer chains (ETFA, ETFB, ACADSB, GCDH and ECHS1) interact closely with each other and are located in the center of the network. Oxidoreductase (GCDH, MECR, MDH2, ACADSB, IVD) that are related with the generation of NADH and FADH2 interacted strongly with each

Journal Pre-proof other. In addition, chaperone and porins interacted with metabolic enzymes (mainly TCA cycle, pyruvate metabolism, electron transfer chains). TCA cycle, oxidative phosphorylation and oxidoreductase play a crucial role in meat color during storage or display, which influence the meat color and co lor stability through oxygen consumption and MetMb

reducing activity.

Meanwhile, chaperone protect

mitochondria and myoglobin from the damage of oxidative stress that is produced by the strong oxidative metabolism of DC, as well as, porins which can retard the apoptosis of mitochondria. Therefore, these proteins that play an important role in

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protein-protein interaction networks can be considered as the intrinsic reason for the difference in color stability between DC and normal pH beef.

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3.3.2. Relationship between differentially abundant proteins and meat color traits

e-

To further identify the significant differentially expressed proteins that associate with the meat color traits, we conducted regression analyses between differentially

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expressed proteins and meat color traits (pH, a* value, hue, MRA, OC and the relative content of OMb and DMb) (Table 4). The regression models used color traits as

al

dependent variables and corresponding differentially expressed proteins (listed in

rn

Table 3) related with meat color traits as independent variables. All the models were significant (P < 0.05). Among those proteins, GCDH and

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FLOT1 were highlighted, since GCDH was retained in all regression models except the OC model, and FLOT1 did not appear in the models of MRA and OC. GCDH was negative in the models of pH, DMb and MRA, while it was positive in the models of a*, hue and OMb, which indicates GCDH is overexpressed in normal pH beef, and this is in agreement with the results listed in Table 3. In the protein-protein interaction networks, this protein directly interacts with oxidoreductases (i.e. ACADSB and IVD), electron transfer chain enzymes (i.e. ETFB, ETFA) and fatty acid β-oxidation enzymes (i.e. ECHS1), which indicates GCDH play an important role in causing the redness difference between DC and normal pH beef. Theoretically, GCDH catalyzes the oxidative decarboxylation of glutaryl-CoA to crotonly in the degradative pathways of amino acids (i.e. L- lysine) metabolism, and the production of FADH2 contributes to electron transfer and metmyoglobin reducing (www.uniprot.org). However, its

Journal Pre-proof overexpression in normal pH group was not supported by the theory that the NADH or FADH2 can be used as substrates for mitochondria enzyme complexes (complex I and complex II, respectively) within the electron transport chain, resulting in increased mitochondrial oxygen consumption and meat darkening (Ramanathan & Mancini, 2018; Ramanathan, Mancini, Joseph, & Suman, 2013). GCDH is firstly reported to be related with meat quality, especially meat color, in the current study. Therefore, its direct relationship with meat color, especially the role of mitochondrial complex II that involved FADH2 is of interest in future studies.

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f

FLOT1 was negatively related with pH and DMb, and positively related with a*, hue and OMb. It indicates that the elevated expression of this protein will be

pr

beneficial to beef color. To our knowledge this is the first report of the relationship

e-

between FLOT1 and meat color. This protein has been linked with human disease, especially carcinoma, and may act as a scaffolding protein with caveolar membranes,

Pr

functionally participating in the formation of caveolae or caveolae- like vesicles (www.uniprot.org).

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PFKM, one of the energy metabolism related enzymes, was found positively

rn

associated with DMb, while negatively with OC. PFKM is the speed- limiting enzyme for the glycolysis process. This protein is ATP dependent, such that the higher

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expression of this protein means a faster glycolysis process if there is sufficient energy. However, this enzyme was overabundant in the DC group, which means the residual energy is limited for its activity. Consistent with our result, PFKM was reported up-regulated in stressed muscle (Zhou, Shen, Liu, Wang, & Shen, 2019). GRPEL1 was negative in the model of DMb. As a chaperone it could reduce the damage of stress to cell together with HSP70 family (Mayer & Bukau, 2005), and in the protein-protein interaction networks, GRPEL1 is strongly interacted with 10 kDa heat shock protein (HSPE1), which is implicated in mitochondrial protein import and macromolecular assembly. Therefore the overexpress of GRPEL1 in DC group could protect myoglobin and mitochondria from oxidative stress, leading to greater color stability. DECR1, IARS2 and PDK4 were also found related with hue, OMb, or OC. However the roles of those proteins play in meat quality has not been reported yet.

Journal Pre-proof

4. Conclusions The results of the present study showed that DC exhibited lower a* values, greater OC and better color stability compared with normal pH beef. Label- free proteomics analysis demonstrated that the mitochondrial proteome between DC group and normal pH group was different. A total of 28 proteins were identified as differentially expressed proteins (fold change >1.8, P < 0.05), and among them, most of these metabolic enzymes are directly or indirectly involved in energy metabolism, fatty acid

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f

metabolism/degradation, amino acid metabolism/degradation, or TCA cycle and were overexpressed in the DC group, as well as the oxidoreductases, chaperone and porin.

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It indicates that DC beef still exhibits a high respiration activity and metabolism

activity and thus, darkened color.

e-

activity, which results in the high oxygen consumption and high metmyoglobin

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However, unfortunately, the differential proteins we found did not logically form a complete network as expected. Ideally, all the enzymes in the one of the electron

al

transfer chains or all the oxidoreductases would be highly expressed in DC beef. In

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further work, it may be better to incorporate the results obtained from sarcoplasmic and myofibrillar proteomes, to see whether an entire pathway network can be built.

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Further, for the first time a protein, GCDH, was found related to meat color and its real contribution to meat color is worthy of investigation in further studies.

Acknowledgements

This work was supported by National Natural Science Foundation of China (31601528), University outstanding youth innovation team in Shandong Province (2019KJF019), earmarked fund for China Agriculture Research System-beef (CARS-37), and special fund for innovation team of modern agricultural industrial technology system in Shandong Province (SDAIT-09-09).

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Journal Pre-proof Table 1

Instrumental color and pH value o f dark cutting beef (p Hu 6.86) and normal pH beef (pHu 5.49) during display for 7 d.

Traits

Ultimate pH

Display time (day)

P-value

(pHu) 0

3

5

7

SE

pHu

time

pHu × time

Chroma

hue

R630/580 a-c

5.58y

Dark cutting

6.86x

6.89x

6.97x

6.97x

Normal pH

42.90bx

44.80ax

45.00ax

44.90ax

Dark cutting

30.60by

31.90aby

32.30ay

32.40ay

Normal pH

27.00abx

27.17ax

25.97bx

Dark cutting

15.95by

15.99by

17.70ay

Normal pH

18.88bx

19.81ax

19.03abx

Dark cutting

8.49cy

9.40by

10.74ay

10.99ay

Normal pH

32.96abx

33.94ax

32.20bx

31.15cx

Dark cutting

18.07cy

18.55cy

34.89

ax

bx

Dark cutting

27.92

ay

Normal pH

4.82ax

4.29bx

3.81cx

3.76cx

Dark cutting

3.34ay

3.20ay

3.21ay

3.43ay

Normal pH

36.31bx

by

cy

30.49

31.15

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Significance of P-value: ***, P < 0.001; **, P < 0.001; *, P < 0.05.

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*

0.85

***

***

0.91

0.48

***

0.84

***

0.40

***

**

***

0.71

***

***

***

0.30

***

***

***

0.10

***

***

***

0.60

oo

36.20

M eans in the columns with different letters differ at P < 0.05.

SE = Standard error.

18.44bx

21.21ay

by

***

18.13ay

bx

M eans in the rows with different letters differ at P < 0.05.

x-y

25.09cx

20.71by

36.06

0.04

f

5.53y

pr

b*

5.50y

e-

a*

5.49y

Pr

L*

Normal pH

al

pH

31.25

Journal Pre-proof Table 2

Relative met myoglobin reducing activity, o xygen consumption and lipid o xidation level of dark cutting (pHu 6.86) and normal pH beef (pHu 5.49) during display for 7 d.

Display time (day) Traits

Ultimate pH

0

3

5

P-value

7

SE

pHu

time

pHu ×

Relative M RA (%)

83.5ax

83.1ax

83.0ax

82.6ax

Dark cutting

97.9ay

93.6by

95.0by

94.6by

Normal pH

0.62ay

0.58aby

0.56bcy

0.52cy

Dark cutting

0.70ax

0.65abx

0.62bcx

0.58cx

TBARS

Normal pH

0.07cx

0.08bcx

0.09bx

0.12ax

A 532nm

Dark cutting

0.07ax

0.08ax

0.07ax

M DA equivalents

Normal pH

0.16cx

0.25bcx

0.34bx

(mg /kg)

Dark cutting

0.18ax

0.21ax

0.21ax

***

***

*

0.02

***

***

0.98

0.008

*

**

0.06

*

**

0.06

0.08ay

0.55ax

0.07

0.27ay

pr

OC

0.87

f

Normal pH

oo

time

e-

a-b M eans within a pH with different letters differ at P < 0.05.

x-y M eans within a time with different letters differ at P < 0.05.

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SE = Standard error.

Significance of P-value: ***, P < 0.001; **, P < 0.001; *, P < 0.05. Relative M RA (%): M RA was calculated as resistance to form metmyoglobin after immersing in nitrite solution

OC: oxygen consumption.

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(Ramanathan et al., 2019).

TBARS: thiobarbituric acid– reactive substances.

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M DA: M alondialdehhyde

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A 532nm: Absorbance at 532 nm.

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Table 3

Information of differentially exp ressed mitochondrial proteins of dark cutting (p Hu 6.86) and normal pH beef (pHu 5.49) longissimus lumborum. Accession number

Coverage

M olWeight

Ratioa

PPA2

43.4

36.96

2.16

PFKM

60.5

85.29

1.90

Protein name

M etabolic enzyme Q2KIV7 Q0IIG5

Inorganic pyrophosphatase 2 (PPA2) ATP-dependent 6-phosphofructokinase

f

(PFKM )

Q2HJ73

(PDK4) 3-hydroxyisobutyryl-CoA hydrolase

PDK4

30.5

46.16

7.54

HIBCH

44.8

43.35

2.96

ECHS1

76.9

31.24

2.08

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(HIBCH) Enoyl-CoA hydratase (ECHS1)

2,4-dienoyl-CoA reductase 1 (DECR1)

DECR1

39.5

35.35

2.10

Q148K4

Lactate dehydrogenase D (LDHD)

LDHD

14.7

54.95

0.39

P12344

Aspartate aminotransferase (GOT2)

GOT2

77.4

47.51

2.02

P20004

Aconitate hydratase (ACO2)

ACO2

63.5

85.36

1.81

Glutaryl-CoA dehydrogenase (GCDH)

GCDH

32

48.47

0.44

DHRS7B

34.2

35.03

4.30

M ECR

22.5

40.22

2.61

M alate dehydrogenase (M DH2)

M DH2

70.7

35.67

1.92

ACADSB

30.1

47.12

1.80

IVD

29.6

46.50

1.87

ETFB

61.2

27.70

1.84

ETFA

70.6

34.96

1.83

GRPEL1

42.4

24.31

2.46

DNAJC11

20.6

63.24

1.88

VDAC2

61.9

31.62

1.94

Pr

e-

F1N5J8

rn

Q58DM 8

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Pyruvate dehydrogenase kinase 4 A6QR49

Q2KHZ9

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Oxidoreductase

Dehydrogenase/reductase SDR family Q3T0R4

F1M EY2

member 7B (DHRS7B)

Enoyl-[acyl-carrier-protein] reductase

Q32LG3

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(M ECR)

Short/branched chain specific acyl-CoA

Q5EAD4 Q3SZI8

dehydrogenase (ACADSB) Isovaleryl-CoA dehydrogenase (IVD)

Electron transfer protein Electron transfer flavoprotein subunit Q2TBV3

F1M WR3

beta (ETFB) Electron transfer flavoprotein subunit alpha, mitochondrial (ETFA)

Chaperone Q3SZC1 Q2NL21

GrpE protein homolog 1 (GRPEL1) DnaJ homolog subfamily C member 11(DNAJC11)

Porin P68002

Voltage-dependent anion-selective

Journal Pre-proof channel protein 2 (VDAC2) Others Histidine triad nucleotide-binding Q8SQ21

Q32PB0

protein 2 (HINT2) Single-stranded DNA-binding protein

HINT2

41.7

17.15

1.80

SSBP1

42.6

17.21

2.01

SARS2

16.6

34.08

0.53

EIF2S3

30.9

51.06

3.12

IARS2

25.1

56.14

0.47

(SSBP1) Q58CS4

Serine--tRNA ligase (SARS2) Eukaryotic translation initiation factor 2

Q2KHU8

subunit 3 (EIF2S3)

Q3SZJ1

IARS2 protein (Fragment) (IARS2)

Q3M HZ0

FLOT1 protein (Fragment) (FLOT1)

FLOT1

35.1

46.45

0.43

M yozenin 3 (M YOZ3)

M YOZ3

27.8

26.98

0.46

104.09

0.30

Q08DI7

M YOM 2

(M YOM 2)

63

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a

f

M yomesin (M -protein) 2, 165kDa Q32LP3

Dark cutting / normal pH group.

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↑Indicates differential proteins overexpressed in dark cutting group.

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↓Indicates differential proteins overexpressed in normal pH group.

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Pr

“--” Indicates differential proteins exclusive in dark cutting group.

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Table 4

Dependent

adj-R2

Entered independent varilable

Coefficient

Standard error

P-value

0.925**

GCDH

-2.273

0.366

< 0.001

FLOT1

-1.284

0.326

0.002

GCDH

16.144

3.198

0.009

FLOT1

12.834

2.852

0.001

GCDH

8.695

1.603

< 0.001

FLOT1

9.055

1.225

< 0.001

2.226

0.724

0.011

-3.657

1.455

0.029

-0.615

3.936

< 0.001

0.304

3.601

0.006

IARSA

-2.03

2.322

0.047

Pr

Regression models between differentially expressed proteins and pH values and color related values of beef steaks

IARS2

-0.098

0.028

0.004

PDK4

0.074

0.018

0.002

PFKM

-0.119

0.049

0.031

GCDH

26.329

6.370

0.002

FLOT1

32.381

4.867

< 0.001

PFKM

-18.817

5.778

0.008

DECR1

6.630

2.876

0.042

GCDH

-25.007

6.092

0.002

FLOT1

-28.338

4.550

< 0.001

PFKM

17.515

5.171

0.006

GRPEL1

-9.645

3.668

0.230

a*

hue

0.916**

0.964**

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pH

f

variable

PFKM 0.919**

GCDH IVD

0.957**

DM b

a

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OM b

0.788**

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OC

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M RA

0.952**

Significance of the models: **, P < 0.01.

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DECR1

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f

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Fig. 1 Relative content of three myoglobin forms (including Deoxymyoglobin (DMb), Oxymyoglobin (OMb) and Metmyoglobin (MMb)) of dark cutting (pHu 6.86) and normal pH beef (pHu 5.49) during

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display for 7 d.

Fig. 2 The volcano plots of the label-free quantity intensity rate of dark cutting (pHu 6.86) and normal pH groups (pHu 5.49). Note: The points located in the top left corner of plots represented the proteins overexpressed in normal pH group (dark cutting / normal pH group < 0.667, P < 0.05), while in the right of spots were overexpressed in dark cutting group (dark cutting / normal pH group > 1.5, P < 0.05.

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Fig. 3 Hierarchical cluster analysis (HCA) of differentially expressed mitochondrial proteins. Note: Each row in the heatmap represents a sample (sample in formation was shown in the horizontal

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ordinate), and each column represents a protein (differentially expressed proteins were shown in the longitudinal coordinate). Different color intensity represents different protein exp ression intensity, red

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represents the proteins with significantly up-regulated expression, blue represents proteins with

information.

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significantly down-regulated exp ression, and gray represents the proteins without quantitative

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Fig. 4 Protein-protein interaction networks of differentially expressed proteins between dark cutting

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(pHu 6.86) and normal pH groups (pHu 5.49).

Journal Pre-proof Conflict of interest No conflict of interest exits in the submission of this manuscript, and this manuscript has been approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described has not been published previously, and it is not under consideration

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for publication elsewhere.

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CRediT author statement Shuang Wu: Validation, Data curation, Writing- Original draft preparation Xin Luo: Conceptualization, Supervision, Funding acquisition Xiaoyin Yang: Methodology, Validation, Formal analysis David Hopkins: Supervision, Writing- Reviewing and Editing

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Yanwei Mao: Formal analysis, Investigation Yimin Zhang: Conceptualization,Writing- Reviewing and Editing,

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Funding acquisition

Figure 1

Figure 2

Figure 3

Figure 4