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Metabolomics Profiling to Determine the Effect of Postmortem Aging on Color and Lipid Oxidative Stabilities of Different Bovine Muscles Danyi Ma, Yuan H. Brad Kim, Bruce R. Cooper, Ji-Hwan Oh, Hyonho Chun, Juhui Choe, J. P. Schoonmaker, Kolapo Matthew Ajuwon, and Byungrok Min J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b02175 • Publication Date (Web): 12 Jul 2017 Downloaded from http://pubs.acs.org on July 12, 2017

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Journal of Agricultural and Food Chemistry

Metabolomics Profiling to Determine the Effect of Postmortem Aging on Color and Lipid Oxidative Stabilities of Different Bovine Muscles Danyi. Ma, † Yuan H. Brad Kim*, † Bruce Cooper, § Ji–Hwan. Oh, ‡ Hyonho Chun, ‡ Ju–Hui Choe, † Jon P. Schoonmaker, † Kolapo Ajuwon, † Byungrok Min, # †

Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA. ‡ Department of Statistics, Purdue University, West Lafayette, IN 47907, USA. § Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA. # Food Science and Technology Program, University of Maryland Eastern Shore, Princess Anne, MD 21853, USA

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* To whom correspondence should be addressed. Phone: +1–765–496–1631; E–mail address: [email protected]

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ABSTRACT: The objective of this study was to identify the metabolites that could be associated

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with oxidative stability of aged bovine muscles. Three muscles (longissimus lumbrum (LL),

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semimembranosus (SM), and psoas major (PM)) from 7 beef carcasses at 1 day postmortem

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were divided into three sections and assigned to three aging periods (9, 16 and 23 days). While

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an increase in discoloration was found in all muscles with aging, LL was the most color/lipid

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oxidative stable, followed by SM and PM (P < 0.05). Lower myoglobin and non–heme iron

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contents were observed in LL compared to SM and PM (P < 0.05). The HPLC–ESI–MS based

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metabolomics analysis identified metabolites that were significantly responsive to aging and/or

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muscle type, such as acyl carnitines, free amino acids, nucleotides, nucleosides, and

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glucuronides. The results from the current study suggested that color and oxidative stability is

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inversely associated with aging, but is also muscle–specific. Further studies determining the

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exact role of the identified metabolites in color and oxidative stability of beef muscles should be

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warranted.

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KEYWORDS: Beef, aging, metabolomics, meat color, lipid oxidation 1 ACS Paragon Plus Environment

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INTRODUCTION

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Postmortem aging has been extensively practiced in the meat industry mainly due to its

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beneficial impacts on improving eating quality attributes. In particular, significant improvements

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in meat tenderness, flavor, or juiciness occur through muscle protein degradation by endogenous

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proteases during extended aging. However, prolonged postmortem aging may have an adverse

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impact on color and/or lipid oxidation. A few studies reported that long–term chilled meat

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products had inferior oxidative stability, resulting in a decrease in display shelf–life and an

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increase in rancid off–flavor development, when repackaged from vacuum packs into a retail

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display format

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on surface meat color to determine the degree of freshness for their meat purchasing decisions.

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Consumers would likely discriminate fresh meat products appearing brown–red color (due to

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formation of metmyoglobin; oxidized form of myoglobin) even if meat products have been

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chilled for long–term to enhance eating quality characteristics 3.

1-2

. This can be a significant economic problem because consumers heavily rely

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A few studies suggested that the accumulation of pro–oxidants, such as heme and non–

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heme iron 4, and/or the depletion of endogenous antioxidants 5-6 could be attributed to the aging–

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induced oxidation. Further, the extent of compounds or enzyme activities that impart antioxidant

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properties would be varied among specific muscle types 7-8, which could result in different levels

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of oxidative stability of muscles during postmortem aging. This postulation warrants further

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examination because understanding the underlying mechanisms of oxidative stability of beef

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muscles is a crucial step to develop a practical aging strategy to prevent oxidation–related quality

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defects, while maintaining beneficial aging impacts on eating quality attributes.

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Metabolomics is an emerging technique to analyze small molecule compounds (M.W. less

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than 1 kDa) in complex biological systems such as cell, tissue or bio–fluids 9. Mass spectrometry 2 ACS Paragon Plus Environment

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(MS)–based metabolomics, in particular, is gaining wide acceptance in the food science

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discipline due to its potential in analyzing molecular composition, safety and quality properties,

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and health and nutritional properties of food matrix 10. In muscle foods, several studies have been

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recently published in obtaining metabolome profiles of meat samples including beef, pork,

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chicken and lamb. Those studies determined effects of various pre–and post–harvest factors on

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meat metabolites, such as packaging

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type

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have been conducted to identify muscle–specific metabolites associated with oxidative stability

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of different muscles during postmortem aging.

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11

, chilling

and postmortem processing conditions

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, feed authentication

11, 16

13

, genetics

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, muscle

. However, there is little or no studies that

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Therefore, the objectives of the current study were to determine the effect of postmortem

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aging on color and lipid oxidative stability of different bovine muscles, and to identify the

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metabolites that were related to oxidation during postmortem aging. In the current study, three

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beef muscles including longissimus lumborum (LL), semimembranosus (SM), and psoas major

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(PM) were selected, because those muscles were known to have distinct differences in fiber

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composition, color and lipid oxidative stability 7.

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MATERIALS AND METHODS

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Materials. Seven beef steers (Angus x Simmental crossbred steers, 14 months of age,

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average slaughter weight 624 kg), which were fed a high concentrate feedlot diet (about 10%

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forage), were slaughtered at Purdue University Meat Laboratory. At one day postmortem, three

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muscles (LL, SM, and PM) were separated from one side of each carcass. Each muscle was

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divided into three equal sections, vacuum packaged, and randomly assigned to three aging

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periods (9, 16, and 23 days postmortem) at 1 °C. After the assigned aging period, one thin slice

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cut (about 1 mm) of each section was chopped, snap-frozen, powdered, vacuum packaged, and

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stored at –80 °C until sample extraction for metabolomics profiling;

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thickness) was cut from each section, placed on a plastic tray, packaged with oxygen permeable

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polyvinylchloride film (23,000 cm3 O2/m2/24h at 23 °C) and displayed under fluorescent white

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light (approximately 1,450 lx, Color temperature = 3,500 K) for 7 days at 2.5 °C. For SM, the

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deep portion (the medial inner 1/4 closest to the femur) and the superficial portion (the lateral

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outer 1/4 closest to the surface of the carcass) of the muscle were cut and discarded. The

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remaining portion of SM steak was used in order to limit any confounding locational effects on

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quality and/or chemical attributes within the muscle 17. The packaged steaks were relocated on a

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display table on a daily basis to minimize any confounding effect associated with different

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display location. After display, the steak samples were vacuum packaged and stored at –80 °C

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until further chemical analyses.

one steak (2.54 cm

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Color Measurement. During the simulated retail display, instrumental color characteristics

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of the steak surface were measured using a Minolta CR–400 colorimeter (D65, 1 cm diameter

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aperture 2° standard observer; Konica Minolta Photo Imaging Inc., Tokyo, Japan) at display

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days 1, 4, and 7. Calibration was performed using a standard white tile (CIE L*=97.06, CIE

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a*=0.41, CIE b*=1.72) prior to the color measurement. CIE L*, a* and b* values were obtained

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by the average of 3 spot measurements per steak. Chroma [(a*2+b*2)1/2] and hue angle [(b*/a*)

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tan–1] values were estimated from CIE L*, a* and b* values 18.

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Visual color evaluation of steak samples was conducted according to the AMSA Color 18

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Measurement Guideline

. The sensory color panelists (n=10), who passed a Farnsworth—

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Munsell 100 Hue screening test, were trained multiple–times. The extent of lean color change

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was evaluated using eight scale points (1=extremely dark red, 2=dark red, 3=moderately dark

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red, 4=slightly dark red, 5=slightly bright red, 6=moderately bright red, 7=bright red, and

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8=extremely bright red). The extent of discoloration was assessed based on seven scale points

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(1=no discoloration (0%), 2=slight discoloration (1–19%), 3=small discoloration (20–39%),

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4=modest

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discoloration (80–99%), 7=total discoloration (100%)).

discoloration

(40–59%),

5=moderate

discoloration

(60–79%),

6=extensive

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Lipid Oxidation: Conjugated diene (CD) and TBARS. The extent of diene conjugation

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(primary lipid oxidation product) was determined after 7 days of retail display of beef samples

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by following the procedure as described by Srinivasan, Xiong, and Decker

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modifications. In duplicate, 0.5 g of meat sample was homogenized with 5 ml of distilled water.

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Then, 0.5 ml of homogenate was mixed with 5 ml of extraction solution (isopropanol and

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hexane, 3:1 ratio) and centrifuged at 2,000 × g for 5 min. The absorbance of the supernatant at

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233 nm was measured against a blank (extraction solution) using a spectrophotometer (Epoch,

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BioTek Instrument Inc.) in a 1cm quartz cuvette. The concentration of CD was calculated using a

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molar extinction coefficient of 25,200 M–1cm–1 and the results were expressed as µmol/mg meat

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lipid sample.

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with minor

The extent of secondary lipid oxidation products was measured in duplicate, following 2– 20

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thiobarbituric reactive substances acid (TBARS) assay

. Beef samples displayed for 7 days

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were frozen powdered and homogenized in distilled water (1:3 ratio) with butylated hydroxyl

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anisole (BHA) solution (10% v/v with 90% ethanol solution) using an Ultra Turrax (Ultra–

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Turrax T25, Janke & Kunkel IKA–Labortechnik, Staufen, Germany) at 6,000 rpm for 30s and

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centrifuged at 2,000 × g for 10 min at 4 °C. The supernatant (2 ml) was mixed with 4 ml of

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TBA/TCA reagent (20 mmol TBA with 15% trichloroacetic acid solution), heated for 15 min in

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a water bath (80°C) to develop the chromogen, then cooled for 10 min in ice water. The

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absorbance of each sample at 538 nm was measured using a microplate spectrophotometer

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(Epoch, BioTek Instrumrtnts Inc.) against a blank (2 ml distilled water + 4 ml TCA/TBA

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solution). TBARS value was expressed as mg malondialdehyde (MDA)/kg muscle.

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Myoglobin Content and Non–Heme Iron. Myoglobin contents of beef samples were

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measured in duplicate by following the procedure of Warris, Trout, and Rickansrud and

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Henrickson

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mmol potassium phosphate buffer (pH 6.8) and held on ice for 1 h. After centrifuging the

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homogenates at 35,000 × g for 30 min at 4 °C, supernatant was collected and filtered. The

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filtered supernatant was scanned in a cuvette for the absorbance spectra at 400 to 700 nm

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measured by VWR UV–1600 PC spectrophotometer (VWR International, San Francisco, CA).

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The myoglobin concentration (mg/g meat) was calculated using the absorbance difference

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between 525 nm and 700 nm multiplied by 2.303 and a dilution factor.

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21-23

with a few modifications. In brief, samples (2.5 g) were homogenized in 40

Non–heme iron content was determined following the described procedure

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with minor

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modifications. Powdered meat samples from steaks displayed for 7 day were homogenized in 0.1

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M citrate–phosphate buffer (pH 5.5), mixed with ascorbic acid (1% in 0.2 N HCl, w/v) and

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11.3% TCA solution (w/v, 1 ml) and held for 5 min at room temperature. The mixture was

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centrifuged at 3,000 × g for 15 min at 20 °C, and supernatant was mixed with 10% ammonium

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acetate (w/v) and ferrozine at 22 °C for 10 min for color development. The absorbance was

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determined at 562 nm against a blank. The non–heme iron content was expressed as mg non–

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heme iron per 100 gram of meat.

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Metabolomics Sample Preparation and Extraction. Protein removal and sample 25

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extraction were performed using a Bligh–Dyer extraction protocol

. Chloroform (200 uL)

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mixed with an equal volume of methanol was added to 100 mg of meat powder. Samples were

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extracted in a Precellys 24 tissue homogenizer. Two hundreds microliter of water was mixed

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with the extract and was centrifuged at 16,000 × g for 8 minutes. The upper methanol and water

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phase contained the polar metabolites, which was transferred to separate vials and were

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evaporated to dryness in a SpeedVac Concentrator. The dried polar fraction was reconstituted in

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50 uL of a diluent composed of 95% water and 5% acetonitrile containing 0.1% formic acid.

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HPLC–MS Analysis. Separations were performed on an Agilent 1100 system (Palo Alto,

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CA), with a mobile phase flow rate of 0.3 mL/min. The metabolites were assayed using a Waters

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Atlantis T3 column (3 µm, 2.1 × 50 mm), where the mobile phase A and B were 0.1% formic

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acid in ddH2O and acetonitrile, respectively. Initial conditions were 100:0 A:B, held for 1

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minute, followed by a linear gradient to 5:95 at 21 min and was held until 26 min. Column re–

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equilibration was performed by returning to 100:0 A:B at 30 minutes, and holding until 35

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minutes. The mass spectrometry chromatograms were obtained using an Agilent MSD–TOF

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spectrometer with ESI capillary voltage 3.5 kV, nitrogen gas temperature 350 °C, drying gas

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flow rate 9.0 L/min, nebulizer gas pressure 35 psig, fragmentor voltage 135 V, skimmer 60 V,

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and OCT RF 250 V. Mass data (from m/z 70–1100) were collected using Agilent MassHunter

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Acquisition software (v. B.03). Mass accuracy was improved by infusing Agilent Reference

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Mass Correction Solution.

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Peak deconvolution was performed using Agilent MassHunter Qualitative Analysis (v.

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B.06). Chromatographic peaks were aligned across all samples. Peak areas were normalized by

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sample weights, converting to log2 and applying a 75% percentile shift. Peak annotations were

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performed based on mass assignment and retention behavior using the METLIN

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(www.metlin.scripps.edu) and HMDB (www.hmdb.ca) metabolite databases with a mass error of

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less than 10 ppm.

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Statistical Analysis. The experimental design of this study was split–split plot design, with

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muscle type effect (LL, SM and PM) as the whole plot and aging time effect (9, 16 and 23 days

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of aging) as a subplot. For color characteristics, the display effect (1, 4, and 7) was set as sub–

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sub plot. Animals were considered as a random effect. Color characteristics, pH, lipid oxidation

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(CD and TBARS), and non–heme iron were analyzed by the PROC MIXED procedure of SAS

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9.4 software (SAS Institute Inc.).

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For the metabolomics profiling, statistical analysis was performed by using split–plot

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ANOVA or Kruskal–Wallis test (KWT) via R software (www.r–project.org) with Benjamini–

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Hochberg FDR correction. Metabolites with P < 0.05 were considered as significantly affected

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by aging or muscle type effect. Then the data were further analyzed collectively via principal

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component analysis (PCA) using R software. The corresponding false discovery rate (FDR)

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values were reported as further reference. Associations of metabolites and color characteristics,

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lipid oxidation, non–heme iron and myoglobin content were analyzed by using Spearman’s rank

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correlation. Correlation with statistical significance (P < 0.05) was considered for further

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biological interpretation.

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RESULTS

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Color, Oxidative Stability and Pro–Oxidant Species. Instrumental color (CIE L*, a*, b*,

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chroma and hue angle) and visual color (lean color and discoloration) attributes were assessed to

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determine the effects of postmortem aging on color and color stability of different beef muscles.

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In general, LL and SM maintained higher redness, color intensity, and lower hue angle values

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compared to PM throughout display (P < 0.05) irrespective of aging periods (Table 1), which

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was consistent with the visual color evaluation. Furthermore, postmortem aging significantly

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affected color and color stability of beef muscles. As aging time increased, a decrease in redness

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of surface beef color was found as indicated by a*, chroma, and visual lean color (P < 0.05;

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Table 2).

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In particular, a significant interaction of muscle by aging was found in hue angle and

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discoloration, where PM showed significantly higher discoloration and hue angle values after 16

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days of aging, while LL and SM maintained the similar values throughout the whole postmortem

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aging (P < 0.05). There was a significant aging × display interaction in a*, chroma, hue angle,

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lean color and discoloration (Table 2). No significant interactions between muscle, aging and

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display duration were found in L* values (lightness). The lightness values were only affected by

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muscle (P < 0.05), where SM had the highest L* values (lightest) followed by LL and PM

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(darkest) (Table 1).

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Changes in primary oxidation (CD formation) and secondary lipid oxidation (TBARS)

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were assessed after 7 days of the simulated retail display. There were no significant interactions

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between muscle and aging on CD and TBARS. CD concentration was significantly affected by

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muscle type (P < 0.001), but not aging (P = 0.1; Table 3). LL maintained lower CD value than

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SM and PM after display, regardless of aging treatment. Conversely, TBARS was significantly

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affected by both aging time (P < 0.05) and muscle type (P < 0.01). An increase in TBARS was

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observed in the 23 day aged group compared with 9 and 16 day aged beef samples, and the

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highest TBARS was found in the SM muscle, followed by PM and LL (Table 3). A trend of

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aging × muscle interaction (P=0.06) showed that LL was lower in TBARS value than the other

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two muscles in 9 and 16 day aged groups (data not shown).

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There were no significant interactions between muscle and aging in myoglobin content and

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non-heme iron. Myoglobin content was affected by muscle type (P < 0.05), but not postmortem

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aging (P > 0.05; Table 3). Myoglobin content was significantly higher in PM compared with LL

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and SM (P < 0.001), which was likely due to high content of type I red muscle fiber in PM

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muscle. Non–heme iron was significantly affected by muscle type (P < 0.001) and postmortem

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aging (P < 0.001). Non–heme iron was lowest at 9 day of aging, and accumulated as aging time

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prolonged. LL maintained the lowest non–heme iron level followed by SM and PM, regardless

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of the aging treatment (Table 3).

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The chemical attributes related to oxidative stability were correlated to color

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characteristics of beef samples (Table 4). CD was moderately correlated to all the color

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characteristics except CIE L* value (Table 4), suggesting a potential involvement of primary

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oxidation in meat color deterioration. Myoglobin and non–heme iron content were strongly

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correlated with CD (r= 0.78 and 0.66 respectively, P < 0.001) and also exhibited significant

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correlations with color characteristics including CIE a* (r = -0.49 and -0.76, P < 0.001), hue

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angle (r = 0.59 and 0.63, P < 0.01), lean color score (r = 0.57 and -0.7, P < 0.001), and

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discoloration score (r = 0.57 and 0.73, P < 0.001).

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Metabolome Profiles. The untargeted metabolome profiling initially detected 1695

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different compounds in meat samples. Metabolites were checked with the assumption of equal

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variance and normality of error term to determine the applicability of conducting ANOVA,

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where 702 metabolites that satisfied the two assumptions were tested for ANOVA, and the

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remaining metabolites were tested using the Kruskal–Wallis method (KWT).

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For the effect of aging, 222 out of 702 metabolites were significantly affected by the aging

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(P < 0.05); 150 of which showed strong signals (FDR < 0.05, P < 0.05) after Benjamin–

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Hochberg multiple testing correction, an adjustment of P–values to control the level of Type I

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error. From the 222 compounds, the major groups included free amino acids, fatty acetyl

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carnitines, vitamins and coenzymes, and nucleotide–related metabolites as listed in Table 5.

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For the effect of muscle type, 35 of the metabolites were identified as significant. Primary

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metabolites being identified from this group were presented in Table 5. Overall, the LL and SM

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muscles were characterized with more abundant in β–alanine–histidyl dipeptides, fatty acetyl

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carnitines, phenylalanine and niacinamide. L–carnitine, xanthine and hypoxanthine were tested

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using non–parametric method (KWT). The fold changes of these compounds indicate a decrease

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of these metabolites with aging (data not shown).

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Principal Component Analysis (PCA). The principal component analysis (PCA) was

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used to visualize the extent of distinct differences of the identified metabolomes of the muscles

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with aging. Two PCA models have been built based on the different subsets of the original

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dataset, namely the 243 metabolites that showed statistical significance indicated by ANOVA or

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KWT (Figure 1A and 1B) and the 150 metabolites that satisfied both P < 0.05 and FDR < 0.05

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criteria of ANOVA (Figure 1C and 1D). The PCA plots based on the further selected data

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(Figure 1C and 1D) clearly showed improved efficacy compared to those on the initially selected

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data (Figure 1A and 1B), as the total variance explained by first principal component (PC1)

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increased from 33% in the first model to 41% in the second model. As showed in the both

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figures, the first two principal components have already specified more than 50% of the observed

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variance. In particular, PC1 mostly accounted for the difference in aging treatments and clearly

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separated muscle samples that aged for 9 days, 16 days, and 23 days respectively. Because PC1

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is the axis where the data set has the largest variation

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differences of the metabolomes among muscle samples were caused by postmortem aging. In

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addition, PC2 could explain 21% of the total variance of the data set, which separated the PM

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samples from the cluster formed by overlapped LL and SM samples. Moreover, the loading

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analysis indicated some possible associations between metabolites and each PC (Table S1,

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Figure 1E). The top 10 metabolites with positive or negative scores in each PC were listed in

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Table S1, which included NAD/NADH, carnitines, and peptides. As reflected in their scores,

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these metabolites may be more closely affected by the aging process. More biological

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interpretations will be discussed in later sections.

26

, in the current study, the major

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Correlation. The heatmaps demonstrated the correlations between key metabolites that

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were significantly affected by either muscle type or aging time and major color characteristics

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and pro–oxidation related indexes (Figure. S1). Metabolites that were significantly correlated to

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the color or oxidation related chemical attributes were mainly NAD, acyl–carnitines, free amino

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acids, assorted nucleotides, and glucuronides (Table S2). In particular, NAD showed significant

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positive correlations to CIE a* (r = 0.672) and negative correlation to discoloration (r = -0.535),

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TBARS (r = -0.554), and non–heme iron (r = -0.667). Acyl carnitines, nucleotides xanthine and

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hypoxanthine, free amino acids phenylalanine and tryptophan, and glucuronides were, in general,

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positively associated with discoloration characteristics and non–heme iron accumulation.

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DISCUSSION

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Effect of Aging on Oxidation Stabilities of Different Muscles. Meat color stability is a

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muscle–specific trait. The observed muscle differences in color stability were in agreement with

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several other studies

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impacts on beef color stability is also a muscle–specific trait, where PM, color labile muscle, is

289

more susceptible to aging–induced discoloration compared to other color stable muscles (e.g.

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LL).

7, 27

. Particularly, the current observation indicates that the adverse aging

291

The current study found moderate correlations between CD and myoglobin content, non-

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heme iron, and all the color characteristics except CIE L* value (Table 4), suggesting that

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primary oxidation could affect meat color deterioration mainly due to its impact on pigment

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redox stability. Previous studies showed that lipid oxidation–induced myoglobin oxidation was

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more likely due to primary rather than secondary products

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lipid hydroperoxide was reported to trigger myoglobin into a transient ferryl status. This leads to

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formation of a covalent bond between the heme group and protein moiety

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myoglobin contains heme iron, which is highly reactive to oxidation processes. During aging,

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exposure of heme group caused by myoglobin deformation would result in non–heme iron

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accumulation 30, which may further facilitate meat discoloration.

28

, with the supporting evidence that

29

. Furthermore,

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Effect of Aging on Muscle Metabolome and Oxidative Stabilities. During postmortem

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aging, muscle cells and cell apparatuses lose structural integrity and enzyme activities, resulting

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in a decreased ability to maintain reducing conditions. Such changes may lead postmortem

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muscles to be more oxidation susceptible 31. The multivariate analysis results in the current study

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clearly indicated the substantial aging impact on the metabolome profiling. In particular, the

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current study identified that oxidative stability of bovine muscles could be related to key

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metabolites including NAD, assorted free amino acids, nucleotides and its degradation products,

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and phenolic compounds as illustrated in Figure S1 and Table S2. However, it should be noted

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that the current study used reversed-phase HPLC-MS, which provides better retention on semi-

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polar metabolites rather than polar metabolites including sugars and organic acids 32. This could

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likely explain why little to no detection of metabolites related to glycolytic or TCA was present

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in the current study.

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Nicotinamide adenine dinucleotide (NADH) and its oxidized form NAD+ was identified by

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the m/z values 665.1249 and 663.1092 respectively. The ANOVA results indicated that both

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NADH and NAD+ were significantly decreased with prolonged aging period (P < 0.05, FDR