Research Article

The Influence of Supplemental Zinc and Ractopamine Hydrochloride on the Performance and Longissimus Thoracis Proteome of Finishing Beef Steers

Authors
  • Katherine G. Hochmuth (Iowa State University)
  • Matthew D. Schulte orcid logo (Iowa State University)
  • Elizabeth M. Messersmith (Iowa State University)
  • Elisabeth J. Huff-Lonergan orcid logo (Iowa State University)
  • Stephanie L. Hansen (Iowa State Universtiy)

Abstract

To determine how Zn and ractopamine hydrochloride (RAC) supplementation affect the longissimus thoracis muscle proteome in beef cattle, 48 high percentage Angus steers (494±18.2 kg) were utilized in a 2×2 factorial study design. Steers were blocked by body weight (BW) and genetic gain potential (GeneMax; Zoetis, Parsippany, NJ) into control (CON; analyzed 36 mg Zn/kg dry matter [DM]) or supranutritional Zn (SUPZN; CON+60 mg Zn/kg DM from ZnSO4+60 mg Zn/kg DM from Zn-amino acid complex; Availa Zn, Zinpro, Eden Prairie, MN) dietary treatments (ZNTRT). Starting 28 d prior to harvest, steers were blocked by BW within ZNTRT to RAC treatments (RACTRT) of 0 (NO) or 300 mg·steer−1·d−1 (RAC; Actogain 45, Zoetis). After 15 d on RACTRT, longissimus thoracis biopsies were collected from all steers for proteomic analysis. Twenty-eight steers (n=7 per treatment) were harvested at a commercial abattoir on Day 90. A ZNTRT×RACTRT effect showed SUPZN-RAC steers had a greater dressing percentage than other treatments (P≤0.02). Steers fed SUPZN had a greater hot carcass weight, carcass-adjusted final BW, overall average daily gain, and overall gain to feed (P≤0.05). Differentially abundant proteins involved in energy metabolism, muscle structure, and protein synthesis potentially indicate muscle fiber characteristic differences because of Zn and RAC supplementation.Both myosin light chain kinase 2 and eukaryotic translation initiation factor 5A-1 were more abundant in SUPZN-RAC steers than SUPZN-NO (P≤0.05) or CON-NO (P≤0.04) steers when analyzed for phosphorylation modifications. L-lactate dehydrogenase B was more abundant in SUPZN-NO steers than CON-NO (P=0.03) or CON-RAC (P=0.01) steers. In conclusion, increased Zn supplementation may be needed to optimize the hypertrophic effects of RAC through its effects on the longissimus thoracis proteome.

Keywords: beef cattle, beta adrenergic agonists, muscle, proteomics, zinc

How to Cite:

Hochmuth, K. G. & Schulte, M. D. & Messersmith, E. M. & Huff-Lonergan, E. J. & Hansen, S. L., (2022) “The Influence of Supplemental Zinc and Ractopamine Hydrochloride on the Performance and Longissimus Thoracis Proteome of Finishing Beef Steers”, Meat and Muscle Biology 6(1): 14456, 1–17. doi: https://doi.org/10.22175/mmb.14456

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Published on
08 Nov 2022
Peer Reviewed

Introduction

Beef production in the United States has become increasingly efficient (USDA NASS, 2019) in part because of improvements in nutritional management strategies. These strategies include the use of β-adrenergic agonists, such as ractopamine hydrochloride (RAC). Approximately 85% of US feedlots utilize RAC as a growth-promoting technology (Samuelson et al., 2016). This β-adrenergic agonist has been shown to consistently improve average daily gain (ADG) and feed efficiency of cattle when supplemented 28 to 42 d before harvest (Bohrer et al., 2014). These effects are exerted through RAC activating β-adrenergic receptors on both skeletal muscle and adipose tissue, resulting in increased intracellular concentrations of cyclic AMP that bind to protein kinase A (Spurlock et al., 1994). This activation has downstream effects of decreasing protein degradation and increasing lipolysis (Wang and Beermann, 1988; Liu et al., 1989), causing lean muscle accretion associated with RAC supplementation.

Zn has also been shown to have intracellular effects required for bodily growth processes. Zn is needed intracellularly in the catalytic sites of RNA polymerases as well as in the Zn-finger protein domains for gene transcription (Dalton et al., 1997; Cousins, 1998). Additionally, Zn is able to increase protein synthesis in the muscle by phosphorylating and activating protein kinase B and mammalian target of rapamycin pathways (Kim et al., 2000; McClung et al., 2007). The supplementation of RAC with dietary Zn above the current recommendations (National Academies of Sciences, Engineering, and Medicine, 2016) has been shown to increase growth in cattle (Genther-Schroeder et al., 2016a, 2016b). Therefore, Zn may support RAC-enhanced growth processes, but the interaction of Zn and RAC occurring in the muscle is poorly understood and little is known about how RAC and supranutritional dietary Zn concentrations affect the muscle proteome of cattle, either independently or collectively. Therefore, the objective of this study was to determine how Zn and RAC supplementation affect the longissimus thoracis muscle proteome of beef steers. It was hypothesized that the abundance and phosphorylation state of proteins would be affected by supranutritional Zn and RAC supplementation to better support protein accretion, leading to increased muscle growth.

Materials and Methods

All procedures and protocols were approved by the Iowa State University Institutional Animal Care and Use Committee (11-17-8645-B).

Animals and experimental design

Seventy high percentage Angus steers (approximately 12 mo old) from one source were purchased, transported to the Iowa State University Beef Nutrition Farm (Ames, IA), and tested for their genetic merit for growth, carcass weight, and quality grade (marbling) using GeneMax Gain scores (GeneMax Focus, Zoetis). After performing GeneMax test, 48 steers (494 ± 18.2 kg) were identified as being in the top 60% of Angus cattle for growth potential and were selected for enrollment in this study. Steers were housed (6 or 8 steers per pen) in pens equipped with GrowSafe bunks (GrowSafe Systems Ltd., Airdrie, Alberta, Canada) and fed ad libitum to allow for the assessment of daily individual steer feed disappearance.

Steers were divided into 5 groups of 4 (1 steer/treatment) and a sixth group of 28 (7 steers/treatment) to accommodate harvest schedules. On Day 0, steers were implanted with Component TE-S with Tylan (120 mg trenbolone acetate, 24 mg estradiol, United States Pharmacopeia, Rockville, MD, and 29 mg tylosin tartrate; Elanco Animal Health, Greenfield, IN). This study used a 2 × 2 factorial as its treatment design. Zn supplementation (ZNTRT) began on Day 0 and consisted of the recommended daily minimum requirement of Zn to prevent deficiency (analyzed 36 mg Zn/kg DM; CON) or supranutritional Zn [CON {36 mg Zn/kg DM} + 60 mg Zn/kg DM as ZnSO4 + 60 mg Zn/kg DM as Zn-amino acid complex (Availa Zn, Zinpro), analyzed 140 mg Zn/kg DM; SUPZN]. Steers were blocked by similar GeneMax Gain scores and body weight (BW) on Day 0 before being randomly assigned to ZNTRT. Twenty-eight days prior to harvest (Day 62 of the trial), β-adrenergic agonists treatments (RACTRT) began, consisting of either 0 (NO) or 300 mg−1·steer−1·d−1 ractopamine HCl (Actogain 45, Zoetis; RAC). Twenty-eight days prior to harvest (Day 62 on trial), steers within a ZNTRT assignment were randomly assigned to an RACTRT to be continued through the end of the trial. Diet composition and nutrient analysis is shown in Table 1. Diets were stagger-started over a 30-d period such that days on ZNTRT and RACTRT were identical across groups. Groups 1 through 5 (1 steer/treatment) were harvested at the Iowa State University Meats Laboratory (Ames, IA) on 5 separate days (approximately 17 mo old) and data from these groups, including postmortem data, are described in Schulte et al. (2021). The remaining 28 steers (7 steers/treatment), composing Group 6 (approximately17 mo old), were harvested on a single day at National Beef (Tama, IA).

Table 1.

Diet ingredient composition and nutrient content

Ingredient (% DM) CON1 SUPZN1
Dry rolled corn 57 57
Sweet bran2 20 20
Hay 8 8
Dried distillers grains with solubles 10 5
Zinc treatment premix3 0 5
Micronutrients4 5 5
Analyzed components
Crude protein 13.1 13.4
Ether extract 3.8 3.8
Neutral detergent fiber 23.0 23.2
Zinc, mg/kg DM 36 140
  • CON diet contained no supplemental Zn; SUPZN diet contained 60 mg supplemental Zn/kg DM as ZnSO4 and 60 mg supplemental Zn/kg DM as Availa-Zn (Zinpro Corporation, Eden Prairie, MN).

  • Branded wet corn gluten feed (Cargill Corn Milling, Blair, NE).

  • Dried distillers grains plus solubles was used as carrier to deliver supplemental Zn treatment.

  • To provide as a percent of diet DM: 3% dried distillers grains, 1.5% limestone, 0.31% salt, 0.0135% Rumensin 90. To provide per kg diet DM: 10 mg Cu/kg DM (copper sulfate), 20 mg Mn/kg DM (manganese sulfate), 0.1 mg Se/kg DM (sodium selenite), 0.15 mg Co/kg DM (cobalt carbonate), 0.5 mg I/kg DM (calcium iodate), 2,200 IU vitamin A and 25 IU vitamin E.

Sample collection and analysis

Samples of the total mixed ration (TMR) for each diet were collected weekly, and dry matter (DM) content was determined by drying samples for 48 h at 70°C in a forced air oven. Resulting DM values were used to correct daily as fed feed disappearance for each steer to determine individual DM intake (DMI). Dried TMR samples were composited and sent to a commercial laboratory (Dairyland Laboratories, Inc., Arcadia, WI) for nitrogen (CP; AOAC, 2005a; method 990.03), neutral detergent fiber (AOAC, 2005b; method 2002.04), and ether extract (AOAC, 2000; method 920.39) analysis.

Prior to feeding, steers were weighed on Day −1 and 0 (initial BW), Day 61 and 62 (prior to RACTRT), and Day 88 and 89 (final BW). Because of the difference in harvest conditions and chill time, only carcass data from Group 6 (n = 28; 7 steers/group) harvested at National Beef were included in this manuscript. Carcass data including hot carcass weight (HCW), back fat thickness (BF), area of the longissimus thoracis muscle (REA), marbling score (MS), and kidney, pelvic, and heart fat (KPH) were collected by trained university personnel after a 48-h chilling period. These data were used to calculate yield grade (YG) using the USDA YG equation [2.50 + (2.5 × adjusted fat thickness [in]) + (0.2 × kidney, heart and pelvic fat [%]) + (0.0038 × HCW [lb]) −(0.32 × ribeye area [in2])]. Individual HCW was divided by the average dressing percentage (DP; 62.1%) to determine carcass-adjusted performance variables. A 4% calculated shrink was applied to all live BW measurements to account for gut fill, including those used to calculate ADG and gain-to-feed ratio (G:F).

Blood serum analysis

Blood samples were collected from each steer via jugular venipuncture prior to feeding on Day 62 (prior to RACTRT) and Day 89. Blood was collected in vacutainer tubes with sodium heparin, trace mineral grade K2 ethylenediamine tetraacetic acid (EDTA), or no additives for serum (Becton Dickinson, Franklin Lakes, NJ). Serum tubes were allowed to coagulate at room temperature for 1 h prior to centrifugation, whereas heparin and trace mineral grade K2 EDTA tubes were stored on ice to be transported to the laboratory. Heparin and trace mineral grade K2 EDTA tubes were centrifuged at 1,000 × g for 20 min at 4°C, and serum tubes were centrifuged at 1,500 × g for 20 min at 4°C. The resulting plasma and serum were then aliquoted and stored at −20°C until further analysis.

Trace mineral analysis

Trace mineral analyses of TMR, plasma, and liver (collected at harvest) were conducted using inductively coupled plasma optical emission spectrometry (Optima 7000 DV, PerkinElmer, Waltham, MA). Prior to mineral analysis, TMR samples were acid digested according to (Pogge et al., 2014), whereas plasma and liver samples were digested and prepped for analysis according to Pogge and Hansen (2013). Instrument accuracy was verified by a bovine liver standard from the National Institute of Standards and Technology (Gaithersburg, MA) for TMR and liver analysis and a trace elements serum toxicology control (UTAK Laboratories, Valencia, CA) for plasma trace mineral analysis. Variation in sample introduction within runs was accounted for through the use of yttrium (PerkinElmer) as an internal standard.

Nonesterified fatty acid and plasma urea nitrogen analysis

Commercial colorimetric kits were used to determine serum nonesterified fatty acid content (NEFA; Wako Pure Chemical Industries Ltd., Chuo-ku, Osaka, Japan) and plasma urea nitrogen (PUN; urea nitrogen reagent, Teco Diagnostics, Anaheim, CA). Blood analysis inter-assay and intra-assay coefficient of variation values were 11.08% and 5.85% for NEFA data and 3.42% and 1.13% for PUN data, respectively.

Muscle biopsies

Longissimus thoracis muscle biopsies were collected between the 11th and 12th rib on Day 77 (Day 15 on RACTRT) from each steer using a method modified from Pampusch et al. (2008). Briefly, steers were restrained in a hydraulic squeeze chute, hair was removed at the incision cite and cleaned using 70% isopropanol. A betadine solution was used as a local anesthetic. A sterile scalpel was used to make an incision and a modified bone marrow biopsy probe was used to collect the sample (approximately 1 g). Samples were flash frozen in liquid nitrogen and stored at −80°C until further analysis. At the completion of tissue collection, animals were returned to their original pen.

Sarcoplasmic protein extraction and protein identification

Frozen longissimus thoracis muscle from Day 77 biopsies were homogenized and powdered in liquid nitrogen, and sarcoplasmic proteins were extracted as described by Carlson et al. (2017) using sarcoplasmic extraction buffer (4°C: 50 mM Tris-HCl and 1 mM EDTA [pH 8.0]).

Sarcoplasmic extracts (200 μL; 10 mg/mL protein concentration) were submitted to the Iowa State University Protein Facility. A pooled control sample was prepared containing equal amounts of all samples. All samples were reduced with dithiothreitol, modified (Cys) with iodoacetamide, and digested with trypsin/Lys-C (Promega, Madison, WI) at 37°C overnight. The addition of formic acid stopped digestion before samples were dried in a Savant SpeedVac SC110A with a Thermo Refrigerated Vapor Trap RVT4104 (Thermo Scientific, Waltham, MA). Samples were desalted using C18 MicroSpin Columns (Nest Group, Southborough, MA) before drying again in a SpeedVac. Concentration of the samples was determined by the Pierce Colorimetric kit (Fisher Scientific, Hampton, NH) once they were reconstituted in 1 M triethylammonium bicarbonate. Each sample was labeled with TMT10plex reagents (Thermo Scientific), with the pooled control labeled with TMT11 (131C). Equal amounts of each sample from the individual TMT label and the control were pooled into a single tube and dried in a SpeedVac. Reconstitution of the samples was achieved by 5% acetonitrile/water/0.1% formic acid.

Peptides were separated by liquid chromatography (Thermo Scientific EASY nLC-1200 coupled to a Thermo Scientific Nanospray FlexIon source) through a pulled glass emitter 75 μm by 20 cm (Agilent, Santa Clara, CA). The tip of the emitter was packed with 5 μm SB-C18 packing material (Agilent), whereas the remainder of the column was packed with UChrom C18 3 μm material (nanoLCMS Solutions, Oroville, CA). A NanoSpray FlexIon source (Thermo Scientific) coupled to a Thermo Scientific Q Exactive Hybrid Quadrupole-Orbitrap Mass Spectrometer with a higher-energy C-trap dissociation fragmentation cell was used to perform MS/MS. The resulting intact mass and MS/MS fragmentation pattern was compared with MASCOT (Perkins et al., 1999) and Sequest HT (Tabb et al., 2001) theoretical fragmentation patterns in order to detect peptides that can identify proteins using Thermo Scientific’s Proteome Discoverer 2.4 software. The MASCOT and Sequest HT search was run against Uniprot Bos taurus. These searches were performed with static modification of carbamidomethyl (Cys) and TMT label (Lys and N-termini), along with dynamic modifications of oxidation (Met) and deamidation (Asn, Gln). Another search was performed with the dynamic modification of phosphorylation (Ser, Thr). Data were sent to the Iowa State University Bioinformatics Facility for analysis as described as follows.

Statistical analysis of feedlot performance, carcass data, liver and blood parameters

Normality was confirmed using the Shapiro-Wilk test. For the pre-RAC period, performance data were analyzed as a randomized complete block design using the Mixed procedure of SAS (SAS Institute Inc., Cary, NC), with the experimental unit of steer (n = 24/ZNTRT) and fixed effects of group (1 through 6) and ZNTRT; Day 62 blood parameters were analyzed similarly using SAS. A 2 × 2 factorial arrangement was used to analyze RAC period live-animal performance as well as Day 89 blood parameters and liver trace mineral concentrations with the fixed effects of group (1 through 6), ZNTRT, RACTRT, and the interaction of ZNTRT and RACTRT (n = 12/treatment combination). Carcass data and carcass-adjusted performance were analyzed similarly (n = 7/treatment combination) but without the effect of group. Initial BW served as a covariate for HCW analysis. Cook’s D was used to determine outliers at Cook’s D ≥ 0.2. Accordingly, 1 SUPZN-RAC, 3 SUPZN-RAC and 1 SUPZN-NO, and 1 SUPZN-RAC and SUPZN-NO were removed because they were identified as outliers from Day 62 plasma Zn, Cu, and Fe, respectively. Additionally, one SUPZN-RAC and CON-RAC were removed from Day 89 plasma Cu and Fe, respectively. Furthermore, one steer from CON-RAC was removed from all analyses because of health reasons unrelated to treatment. Significance was determined at P ≤ 0.05 and tendencies declared at 0.06 ≤ P ≤ 0.10. Tabular values are least square means, and pairwise differences were determined using the PDIFF statement in SAS.

Bioinformatics statistical analysis

For each peptide, the signal intensity was divided by the 131C intensity as the normalization factor before further analysis. Peptides with more than 50% missing value within each treatment group were not used. The remaining data were normalized using the interquantile range estimation method. If there were 2 data points for that peptide from Sets 1 and 2, one data point was randomly selected. If there was only one data point for that peptide, that data point was accepted. This process was repeated for each peptide in each treatment group. MetaboAnalyst 4.0 (Chong et al., 2018) was used for data analysis.

Upon finding data integrity to be satisfactory (positive values for the area), missing value estimation was attributed using Singular Value Decomposition method (Pang et al., 2020). Noninformative values that were near-constant throughout the experiment conditions were detected using the interquantile range estimation method and deleted. Data were transformed based on generalized logarithm transformations to make individual features more comparable. Individual treatment comparisons were made by t test with the P value cutoff of 0.1. Log2 fold change was performed to compare treatments. The Uniprot protein IDs that were up/down regulated with the adjusted P values less than 0.1 were used to retrieve the corresponding KEGG IDs using the “Retrieve/ID mapping” tool of Uniprot. KEGG IDs were then used to retrieve biological pathway association of the proteins. Enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) 6.8 Tools (Huang et al., 2009).

Results

Day 0 to 62 feedlot performance, liver, and blood metabolites

Growth performance, liver, and blood metabolite results for the initial 62 d of the trial, prior to RACTRT, are reported in Table 2. There was no effect of ZNTRT on BW, ADG, DMI, or G:F (P ≥ 0.32) during this time. As expected, Zn intake was greater in the SUPZN compared with the CON during this period (P = 0.0001), resulting in greater plasma Zn concentrations for SUPZN than CON (P = 0.007) on Day 62. However, plasma Cu and Fe concentrations were not affected by ZNTRT (P ≥ 0.32). Furthermore, CON tended to have greater NEFA concentrations (P = 0.06) than SUPZN on Day 62, though ZNTRT did not affect Day 62 PUN concentrations (P = 0.20).

Table 2.

Effect of dietary Zn concentration on growth performance and blood analyses of steers for the 62 days prior to supplementation with ractopamine hydrochloride

Treatment P-value
Item CON1 SUPZN1 SEM ZNTRT
Steers (n) 23 24
BW2, kg
d 03 493 494 4.4 0.83
d 623 647 651 4.2 0.45
ADG2, kg 2.49 2.56 0.067 0.45
Dry matter intake, kg/d 13.8 13.7 0.42 0.94
Gain to feed 0.180 0.190 0.0080 0.32
Zn intake, mg/day 529 1880 57.1 0.0001
d 62 plasma trace mineral4, mg/L
Zn 1.19 1.32 0.038 0.007
Cu 0.88 0.88 0.028 0.99
Fe 2.11 2.21 0.086 0.32
NEFA5, mEq/L 131.8 114.7 7.64 0.06
PUN6, mg/dL 10.3 9.3 0.64 0.20
  • CON = no supplemental Zn (analyzed 36 mg Zn/kg DM); SUPZN = CON + 60 mg Zn/kg DM from ZnSO4 + 60 mg Zn/kg DM from Zn-AA complex (Availa-Zn; Zinpro Corporation, Eden Prairie, MN).

  • 4% shrink applied to all body weight calculations.

  • Average of two consecutive day body weights.

  • Plasma trace mineral on d 62; one steer removed from Zn ([1] SUPZN-RAC), four removed from Cu ([3] SUPZN-RAC and [1] SUPZN-No) and two removed from Fe ([1] SUPZN-RAC and [1] SUPZN-NO) analysis.

  • Serum non-esterified fatty acids on day 62; one steer removed from CON due to lack of sample.

  • Plasma urea nitrogen on day 62.

Day 62 to 89 feedlot performance, liver, and blood metabolites

Growth performance results for the final 28 d of the trial, during the RAC feeding period, are reported in Table 3. No ZNTRT, RACTRT, or ZNTRT × RACTRT effects were observed for BW or DMI (P ≥ 0.18). A ZNTRT × RACTRT effect was observed for ADG and G:F (P ≤ 0.05), in which CON-NO had lesser ADG and G:F than CON-RAC and CON-RAC ADG was greater than SUPZN-RAC. A tendency for a ZNTRT × RACTRT effect (P = 0.08) was observed in daily Zn intake during this period. Both CON-NO and CON-RAC had lesser Zn intake than SUPZN-NO and SUPZN-RAC, but SUPZN-NO had greater Zn intake than SUPZN-RAC.

Table 3.

Effect of dietary Zn and ractopamine hydrochloride on growth performance and Zn intake of steers during the ractopamine period

CON1 SUPZN1 P-value
Item NO2 RAC2 NO2 RAC2 SEM ZNTRT RACTRT ZNTRT x RACTRT
Steers (n) 12 11 12 12
BW3, kg
d 624 649 645 654 648 5.7 0.45 0.40 0.84
d 894 707 720 721 713 8.1 0.68 0.72 0.18
ADG3, kg 2.17b 2.77a 2.48ab 2.40ab 0.166 0.83 0.09 0.03
Dry matter intake, kg/d 14.9 15.6 15.4 15.5 0.59 0.68 0.47 0.54
Gain to feed 0.145b 0.178a 0.164ab 0.154ab 0.0118 0.80 0.30 0.05
Zn intake, mg/d 574z 617z 2203x 1999y 77.0 0.0001 0.24 0.08
  • CON = no supplemental Zn (analyzed 36 mg Zn/kg DM); SUPZN = CON + 60 mg Zn/kg DM from ZnSO4 + 60 mg Zn/kg DM from Zn-AA complex (Availa-Zn; Zinpro Corporation, Eden Prairie, MN).

  • NO = no supplemental ractopamine hydrochloride; RAC = 300 mg·steer-1·d-1 ractopamine hydrochloride (Actogain45; Zoetis, Parsippany, NJ) from day 62 to end of trial.

  • 4% shrink applied to all body weight calculations.

  • Average of two consecutive day body weights.

  • Within a row, means with differing superscripts are different (P ≤ 0.05).

  • Within a row, means with differing superscripts tend to be different (P ≤ 0.10).

Final liver trace mineral concentrations and blood metabolites during the RAC feeding period are reported in Table 4. No ZNTRT × RACTRT effects were observed in harvest liver or Day 89 plasma trace mineral concentrations (P ≥ 0.11). Both harvest liver and Day 89 plasma Zn were greatest for SUPZN (P ≤ 0.005), whereas RAC increased harvest liver Zn (P = 0.04) but not Day 89 plasma Zn concentrations (P = 0.21). Harvest liver Fe was not influenced by ZNTRT (P = 0.12) but Day 89 plasma Fe tended to be greater for SUPZN (P = 0.07). Furthermore, liver Fe was greater (P = 0.003) and plasma Fe lesser (P = 0.05) for RAC versus NO. Additionally, liver Mn concentrations increased (P = 0.05), whereas liver Cu concentrations tended to decrease (P = 0.07), in SUPZN compared with CON. No ZNTRT × RACTRT effects were observed for NEFA or PUN (P ≥ 0.15). However, RAC had lesser NEFA concentrations (P = 0.03) and tended to have lesser PUN concentrations (P = 0.06) compared with NO. No further effects of ZNTRT or RACTRT were observed for harvest liver, Day 89 plasma trace mineral concentrations, or blood metabolites (P ≥ 0.30).

Table 4.

Effect of dietary Zn and ractopamine hydrochloride on liver and blood analyses of steers

CON1 SUPZN1 P-value
Item NO2 RAC2 NO2 RAC2 SEM ZNTRT RACTRT ZNTRT x RACTRT
Steers (n) 12 11 12 12
Harvest liver, mg/kg DM
Zn 127 134 140 161 7.3 0.005 0.04 0.28
Cu 285 312 254 257 25.3 0.07 0.53 0.59
Fe 140 166 152 184 10.4 0.12 0.003 0.74
Mn 9.9 10.5 10.7 10.6 0.27 0.05 0.30 0.23
d 89 plasma3, mg/L
Zn 1.26 1.28 1.37 1.45 0.047 0.002 0.21 0.42
Cu 0.89 0.92 0.95 0.89 0.036 0.80 0.62 0.11
Fe 2.01 1.86 2.26 1.99 0.115 0.07 0.05 0.56
NEFA3, mEq/L 130.3 104.9 130.4 105.7 13.58 0.97 0.03 0.98
PUN4, mg/dL 12.5 9.5 10.8 10.4 0.99 0.61 0.06 0.15
  • CON = no supplemental Zn (analyzed 36 mg Zn/kg DM); SUPZN = CON + 60 mg Zn/kg DM from ZnSO4 + 60 mg Zn/kg DM from Zn-AA complex (Availa-Zn; Zinpro Corporation, Eden Prairie, MN).

  • NO = no supplemental ractopamine hydrochloride; RAC = 300 mg·steer-1·d-1 ractopamine hydrochloride (Actogain45; Zoetis, Parsippany, NJ) from day 62 to end of trial.

  • Plasma trace mineral on d 89; one steer removed from Cu (SUPZN-RAC) and Fe (CON-RAC) analysis.

  • Serum non-esterified fatty acids on day 89; one steer removed from CON-NO and two steers removed from SUPZN-NO due to lack of sample.

  • Plasma urea nitrogen on day 89; one steer removed from CON-NO due to lack of sample.

Carcass data

Carcass characteristics and carcass-adjusted performance data are reported in Table 5. A ZNTRT × RACTRT effect was observed in DP, BF, and YG (P ≤ 0.02). DP was greater in SUPZN-RAC DP than all other treatments. Related to BF, CON-NO presented greater BF than CON-RAC, whereas neither was different from SUPZN-NO or SUPZN-RAC. YG was greater in CON-RAC and SUPZN-NO than CON-NO, where SUPZN-RAC YG was not different from all other treatments. No ZNTRT × RACTRT effects were observed in HCW, KPH, REA, or MS (P ≥ 0.26). However, steers fed SUPZN had greater REA (P = 0.0008) and greater HCW (P = 0.05) than CON. A tendency for decreased KPH was observed in RAC steers compared with NO (P = 0.09). No further effects of ZNTRT or RACTRT were observed within carcass characteristics (P ≥ 0.14).

Table 5.

Effect of dietary Zn and ractopamine hydrochloride on carcass performance measures

CON1 SUPZN1 P-value
Item NO2 RAC2 NO2 RAC2 SEM ZNTRT RACTRT ZNTRT x RACTRT
Steers (n) 7 6 7 7
Carcass characteristics
HCW, kg3 429 438 444 451 7.1 0.05 0.25 0.88
Dress, % 62.0b 61.2b 61.7b 63.4a 0.45 0.03 0.28 0.009
KPH, % 2.4 2.3 2.6 2.3 0.12 0.27 0.09 0.43
Back fat, cm 1.60a 1.14b 1.20ab 1.56ab 0.161 0.95 0.77 0.01
REA, cm2 85.9 91.3 96.6 97.1 2.24 0.0008 0.18 0.26
Marbling score4 593 550 544 509 31.3 0.14 0.20 0.91
Yield grade 3.9a 3.2b 3.1b 3.5ab 0.21 0.22 0.44 0.02
Carcass-adjusted5
Final BW, kg 691 706 715 726 11.5 0.05 0.26 0.88
Overall ADG, kg/d 2.22 2.38 2.49 2.61 0.128 0.05 0.26 0.88
Overall dry matter intake, kg/d 13.6 13.5 12.9 13.8 0.83 0.84 0.66 0.56
Overall gain to feed 0.165 0.177 0.197 0.194 0.0120 0.04 0.68 0.50
  • CON = no supplemental Zn (analyzed 36 mg Zn/kg DM); SUPZN = CON + 60 mg Zn/kg DM from ZnSO4 + 60 mg Zn/kg DM from Zn-AA complex (Availa-Zn; Zinpro Corporation, Eden Prairie, MN).

  • NO = no supplemental ractopamine hydrochloride; RAC = 300 mg·steer-1·d-1 ractopamine hydrochloride (Actogain45; Zoetis, Parsippany, NJ) from day 62 to end of trial.

  • Initial BW used as covariate in analysis.

  • Modest = 500-599.

  • Carcass-adjusted performance was calculated by dividing HCW by the average dressing percentage (62.1%).

  • Within a row, means with differing superscripts are different (P ≤ 0.05).

Furthermore, no RACTRT or ZNTRT × RACTRT effects were observed in carcass-adjusted final BW, overall ADG, overall DMI, or overall G:F (P ≥ 0.26). Steers fed SUPZN had greater carcass-adjusted final BW, overall ADG, and overall G:F (P ≤ 0.04) compared with CON. However, overall DMI was not influenced by ZNTRT (P = 0.84).

Proteomics

Proteomic analysis identified 2,425 proteins. Seventy-five of these proteins differed significantly in abundances (adjusted P ≤ 0.10) in at least 1 treatment comparison. Thirteen of the 75 identified proteins were also different in at least one treatment comparison when analyzed for phosphorylation modifications. The descriptions of the proteomic analysis of all proteins with significantly different abundances between treatments are reported in Table 6. Fold changes and P values of proteins with significantly different abundances between treatments are reported in Tables 7 to 10 and Supplementary Table 1; these include proteins involved in energy metabolism (Table 7), structural proteins (Table 8), protein synthesis/degradation (Table 9), cell health (Table 10), and miscellaneous proteins (Supplementary Table 1).

Table 6.

Descriptions of differentially abundant proteins

Uniprot ID Protein Name Sequence Coverage Unique Peptides Mascot Score MW (kDa) pI
A0A3S5ZPM3 6-phosphogluconate dehydrogenase 10% 3 347 60.7 8.19
P20004 Aconitate hydratase 42% 23 7,141 85.3 7.83
Q3SZR3 Alpha-1-acid glycoprotein 30% 5 98 23.2 5.87
K4JDR8 Alpha-2-macroglobulin 16% 1 80 45.0 7.46
P05631 ATP synthase subunit gamma 14% 2 254 33.1 9.33
A0A3Q1LSB6 ATP-citrate synthase 2% 1 73 120.8 7.24
Q3B7N0 Cadherin-13 5% 3 96 78.1 5.03
A5D7J6 Calreticulin 20% 6 115 48.1 4.48
E1BNE7 Caveolae associated protein 1 17% 6 659 50.2 6.15
Q29RK1 Citrate synthase 35% 12 4,682 51.7 8.12
Q3T0B6 Complement component 1 Q subcomponent binding protein 23% 3 784 30.6 4.86
F6QE33 COP9 signalosome subunit 7A 6% 1 113 30.3 8.24
A0A3Q1LX93 CXXC motif-containing zinc-binding protein 16% 2 26 18.1 5.12
P62894 Cytochrome c 47% 4 1,741 11.7 9.50
O62654 Desmin 26% 9 1,017 53.5 5.27
Q32PH8 Elongation factor 1-alpha 2 59% 19 7,320 50.4 9.03
A6QR19 Enolase 2 25% 2 374,739 47.2 5.07
A5PK37 EPM2A glucan phosphatase 28% 4 173 36.8 6.52
Q6EWQ7 Eukaryotic translation initiation factor 5A-1 52% 7 3,480 16.8 5.24
F1N647 Fatty acid synthase 17% 1 2,748 274.2 6.29
F6QND5 Fibrinogen alpha chain 17% 14 2,709 94.7 6.00
A0A3Q1MG04 Fibrinogen beta chain 26% 10 425 57.4 8.12
A0A3Q1LSN6 Glutathione S-transferase 42% 8 2,212 28.4 6.79
F1MVX2 Glutathione S-transferase LANCL1 33% 8 838 45.3 7.33
A1A4L7 Glutathione S-transferase Mu 1 43% 2 3,316 25.7 7.49
P10096 Glyceraldehyde-3-phosphate dehydrogenase 78% 17 740,918 35.8 8.35
A7MB78 Glycogen synthase 25% 12 2,599 83.8 6.04
F1MCZ0 GMP reductase 6% 1 64 38.0 7.24
Q3ZCH9 Haloacid dehalogenase-like hydrolase domain-containing protein 31% 5 351 28.6 6.65
Q3SZV7 Hemopexin 24% 8 3,171 52.2 7.80
A0A3Q1ND53 Hydroxyacylglutathione hydrolase 14% 6 332 60.5 8.10
O77784 Isocitrate dehydrogenase subunit beta 5% 2 343 42.5 8.68
A0A3Q1M1H0 LIM domain binding 3 23% 10 2,219 66.4 7.99
A0A3Q1M5R4 L-lactate dehydrogenase B 60% 18 22,862 37.4 6.25
Q32LG3 Malate dehydrogenase 66% 18 34,702 35.6 8.54
Q32PA8 Mth938 domain-containing protein 33% 3 1,219 13.4 7.28
A0A1K0FUF3 Myoglobin 95% 31 278,464 17.1 7.46
A4IFM7 Myosin light chain kinase 2 49% 18 8,328 67.2 4.94
Q0P571 Myosin regulatory light chain 2 74% 12 14,743 19.0 5.01
Q29RP6 NAPEPLD protein 21% 6 2,246 43.8 5.67
A4IFQ8 NOL3 protein 17% 2 1,082 22.6 4.17
F1N7X3 Nucleosome assembly protein 1-like 4 5% 2 61 46.4 4.74
Q2HJ33 Obg-like ATPase 1 29% 10 1,391 44.7 7.81
Q5E947 Peroxiredoxin-1 64% 10 5,511 22.2 8.40
P12234 Phosphate carrier protein 10% 4 138 40.1 9.31
A0A3Q1LYW4 Phosphorylase b kinase regulatory subunit 29% 25 6,727 123.1 7.42
A0A3Q1M0J3 Phosphorylase kinase catalytic subunit gamma 1 34% 12 3,365 56.2 7.97
P02584 Profilin-1 65% 7 8,176 15.0 8.28
F1MU19 Proteasome activator complex subunit 2 13% 2 96 28.6 5.27
Q3T0X5 Proteasome subunit alpha type-1 26% 5 151 29.6 6.61
F1N3V8 Protein phosphatase 1 regulatory inhibitor subunit 1A 30% 3 147 17.4 5.58
P02638 Protein S100-B 40% 3 216 10.7 4.59
Q3ZC87 Pyruvate kinase 70% 28 244,749 61.4 8.34
P48644 Retinal dehydrogenase 1 27% 11 562 54.8 6.65
G3X6N3 Serotransferrin 64% 40 9,102 77.7 7.17
A0A0A0MP92 Serpin A3-7 6% 3 314 47.0 6.24
A0A3Q1MAU7 S-formylglutathione hydrolase 44% 9 985 32.7 7.65
A0A3Q1LP42 SHSP domain-containing protein 36% 5 150 18.4 5.96
F8SWQ9 Slow skeletal troponin 1 23% 5 933 21.6 9.64
E1BIS6 Synemin 5% 5 93 170.7 4.93
E1BNE2 TIP120 domain-containing protein 24% 17 1,637 134.6 5.63
A5PJM2 TNNI2 protein 30% 6 3,250 23.5 8.98
Q148L6 Trans-1,2-dihydrobenzene-1,2-diol dehydrogenase 27% 7 1,265 36.6 7.30
A0A452DID1 Translationally-controlled tumor protein 10% 2 33 24.6 6.24
O46375 Transthyretin 51% 6 3,451 15.7 6.30
A0A452DIX3 Triosephosphate isomerase 80% 25 114,034 30.6 6.24
P63315 Troponin C, slow skeletal 44% 5 2,166 18.4 4.18
F1N3P2 Ubiquitin carboxyl-terminal hydrolase 6% 3 118 95.8 5.01
A0A3Q1MK32 Ubiquitin-conjugating enzyme E2 L3 52% 6 365 17.9 8.51
A0A3Q1LKR8 Ubiquitin-like modifier-activating enzyme 1 20% 14 839 129.4 5.80
A0A3Q1MT05 UTP—glucose-1-phosphate uridylyltransferase 37% 17 4,486 57.5 7.58
P48616 Vimentin 38% 13 9,189 53.7 5.12
F1N789 Vinculin 33% 29 5,957 123.8 5.76
O97764 Zeta-crystallin 48% 10 978 35.4 8.22
Table 7.

Differentially abundant proteins related to energy metabolism

Proteomic Data Phosphorylation Modification
Uniprot ID Protein Name Fold Change Adj. P-value Fold Change Adj. P-value
CON-RAC/CON-NO1
A0A1K0FUF3 Myoglobin 0.735 < 0.001 -- --
P10096 Glyceraldehyde 3-phosphate dehydrogenase 1.255 0.013 -- --
A0A452DIX3 Triosephosphate isomerase 0.866 0.066 -- --
P20004 Aconitate hydratase -- -- 0.836 0.087
Q148L6 Trans-1,2-dihydrobenzene-1,2-diol dehydrogenase 1.127 0.090 -- --
A0A3S5ZPM3 6-phosphogluconate dehydrogenase 0.886 0.097 -- --
SUPZN-NO/CON-NO1
A0A3Q1M5R4 L-lactate dehydrogenase B 1.175 0.029 -- --
O77784 Isocitrate dehydrogenase subunit beta 0.816 0.056 -- --
F1N647 Fatty acid synthase -- -- 1.331 0.066
Q29RK1 Citrate synthase 0.896 0.082 -- --
A0A1K0FUF3 Myoglobin 0.870 0.085 -- --
SUPZN-RAC/CON-NO1
O77784 Isocitrate dehydrogenase subunit beta 1.249 0.048 -- --
A0A1K0FUF3 Myoglobin -- -- 0.736 0.076
SUPZN-RAC/CON-NO1
A0A3Q1MT05 UTP—glucose-1-phosphate uridylyltransferase 1.107 0.086 -- --
SUPZN-NO/CON-RAC1
F1N647 Fatty acid synthase 1.326 0.004 1.553 0.004
A0A3Q1M5R4 L-lactate dehydrogenase B 1.260 0.010 -- --
P10096 Glyceraldehyde 3-phosphate dehydrogenase 0.807 0.019 -- --
O77784 Isocitrate dehydrogenase subunit beta 0.723 0.028 -- --
A7MB78 Glycogen synthase -- -- 0.763 0.036
Q3ZC87 Pyruvate kinase 0.911 0.088 -- --
P20004 Aconitate hydratase -- -- 1.217 0.089
SUPZN-RAC/CON-RAC1
P20004 Aconitate hydratase 1.141 0.023 -- --
P05631 ATP synthase subunit gamma 1.140 0.044 -- --
SUPZN-RAC/SUPZN-NO1
A7MB78 Glycogen synthase 1.162 0.009 -- --
F1N647 Fatty acid synthase -- -- 0.711 0.035
Q32LG3 Malate dehydrogenase 1.129 0.052 -- --
SUPZN-RAC/SUPZN-NO1
A6QR19 Enolase 2 1.157 0.057 1.595 0.064
P62894 Cytochrome c 1.195 0.059 1.323 0.093
A0A3Q1LSB6 ATP-citrate synthase 0.836 0.082 -- --
P20004 Aconitate hydratase 1.093 0.097 -- --
  • CON = no supplemental Zn (analyzed 36 mg Zn/kg DM); SUPZN = CON + 60 mg Zn/kg DM from ZnSO4 + 60 mg Zn/kg DM from Zn-AA complex (Availa-Zn; Zinpro Corporation, Eden Prairie, MN); NO = no supplemental ractopamine hydrochloride; RAC = 300 mg·steer-1·d-1 ractopamine hydrochloride (Actogain45; Zoetis, Parsippany, NJ) from day 62 to end of trial.

Table 8.

Differentially abundant proteins related to muscle structure

Proteomic Data Phosphorylation Modification
Uniprot ID Protein Name Fold Change Adj. P-value Fold Change Adj. P-value
CON-RAC/CON-NO1
F8SWQ9 Slow skeletal troponin 1 0.876 0.045 -- --
P48616 Vimentin 0.860 0.059 -- --
A4IFM7 Myosin light chain kinase 2 -- -- 1.236 0.059
SUPZN-NO/CON-NO1
F8SWQ9 Slow skeletal troponin 1 0.891 0.094 -- --
SUPZN-RAC/CON-NO1
A4IFM7 Myosin light chain kinase 2 1.211 0.004 1.477 0.003
Q0P571 Myosin regulatory light chain 2 0.900 0.015 -- --
A5PJM2 TNNI2 protein 0.722 0.052 -- --
A0A3Q1LP42 SHSP domain-containing protein 0.839 0.063 -- --
P48616 Vimentin 0.870 0.086 -- --
E1BIS6 Synemin 1.108 0.087
SUPZN-NO/CON-RAC1
Q29RP6 NAPEPLD protein 1.140 0.035 -- --
A4IFM7 Myosin light chain kinase 2 0.897 0.046 0.795 0.050
P48616 Vimentin 1.147 0.049 -- --
SUPZN-NO/CON-RAC1
P63315 Troponin C 1.172 0.095 -- --
SUPZN-RAC/CON-RAC1
Q0P571 Myosin regulatory light chain 2 0.864 0.001 -- --
A0A3Q1LP42 SHSP domain-containing protein 0.776 0.004 -- --
Q3B7N0 Cadherin-13 0.864 0.043 -- --
F1N789 Vinculin 0.875 0.054 -- --
SUPZN-RAC/SUPZN-NO1
Q29RP6 NAPEPLD protein 0.843 0.011 -- --
A4IFM7 Myosin light chain kinase 2 1.132 0.022 1.443 0.005
O62654 Desmin 0.859 0.055 -- --
P48616 Vimentin 0.881 0.092 -- --
P02584 Profilin-1 1.091 0.097 -- --
  • CON = no supplemental Zn (analyzed 36 mg Zn/kg DM); SUPZN = CON + 60 mg Zn/kg DM from ZnSO4 + 60 mg Zn/kg DM from Zn-AA complex (Availa-Zn; Zinpro Corporation, Eden Prairie, MN); NO = no supplemental ractopamine hydrochloride; RAC = 300 mg·steer-1·d-1 ractopamine hydrochloride (Actogain45; Zoetis, Parsippany, NJ) from day 62 to end of trial.

Table 9.

Differentially abundant proteins related to protein synthesis/degradation pathways

Proteomic Data Phosphorylation Modification
Uniprot ID Protein Name Fold Change Adj. P-value Fold Change Adj. P-value
CON-RAC/CON-NO1
Q3T0X5 Proteasome subunit alpha type-1 1.177 0.022 -- --
A0A452DID1 Translationally-controlled tumor protein -- -- 1.749 0.033
SUPZN-NO/CON-NO1
F6QE33 COP9 signalosome subunit 7A 1.282 0.051 -- --
SUPZN-RAC/CON-NO1
A0A452DID1 Translationally-controlled tumor protein -- -- 1.860 0.010
Q32PH8 Elongation factor 1-alpha 2 1.103 0.018 -- --
F1N3P2 Ubiquitin carboxyl-terminal hydrolase 1.215 0.033 -- --
F6QE33 COP9 signalosome subunit 7A 1.344 0.034 -- --
Q6EWQ7 Eukaryotic translation initiation factor 5A-1 -- -- 1.355 0.036
SUPZN-NO/CON-RAC1
O97764 Zeta-crystallin 1.193 0.034 -- --
E1BNE2 TIP120 domain-containing protein 1.167 0.046 -- --
A0A3Q1MK32 Ubiquitin-conjugating enzyme E2 L3 0.875 0.068 -- --
SUPZN-RAC/CON-RAC1
F1MU19 Proteasome activator complex subunit 2 1.208 0.024 -- --
A0A3Q1LKR8 Ubiquitin-like modifier-activating enzyme 1 0.833 0.064 -- --
Q3T0X5 Proteasome subunit alpha type-1 0.897 0.097 -- --
SUPZN-RAC/SUPZN-NO1
A0A3Q1MK32 Ubiquitin-conjugating enzyme E2 L3 1.168 0.038 -- --
E1BNE7 Caveolae associated protein 1 0.906 0.079 -- --
Q6EWQ7 Eukaryotic translation initiation factor 5A-1 1.112 0.099 1.342 0.047
A0A452DID1 Translationally-controlled tumor protein 1.188 0.099 -- --
  • CON = no supplemental Zn (analyzed 36 mg Zn/kg DM); SUPZN = CON + 60 mg Zn/kg DM from ZnSO4 + 60 mg Zn/kg DM from Zn-AA complex (Availa-Zn; Zinpro Corporation, Eden Prairie, MN); NO = no supplemental ractopamine hydrochloride; RAC = 300 mg·steer-1·d-1 ractopamine hydrochloride (Actogain45; Zoetis, Parsippany, NJ) from day 62 to end of trial.

Table 10.

Differentially abundant proteins related to cellular health

Proteomic Data Phosphorylation Modification
Uniprot ID Protein Name Fold Change Adj. P-value Fold Change Adj. P-value
CON-RAC/CON-NO1
Q3SZR3 Alpha-1-acid glycoprotein 1.251 0.023 -- --
SUPZN-NO/CON-NO1
A0A3Q1MG04 Fibrinogen beta chain 1.252 0.049 -- --
A1A4L7 Glutathione S-transferase mu 1 0.726 0.075 -- --
F6QND5 Fibrinogen alpha chain 1.176 0.079 -- --
SUPZN-RAC/CON-NO1
A0A3Q1MG04 Fibrinogen beta chain -- -- 0.657 0.003
F1MVX2 Glutathione S-transferase LANCL1 0.862 0.047 -- --
Q5E947 Peroxiredoxin-1 1.141 0.047 -- --
SUPZN-NO/CON-RAC1
A0A3Q1LSN6 Glutathione S-transferase 1.347 0.047 -- --
A1A4L7 Glutathione S-transferase mu 1 0.518 0.058 -- --
A0A3Q1MG04 Fibrinogen beta chain 1.236 0.066 -- --
SUPZN-RAC/CON-RAC1
Q3SZR3 Alpha-1-acid glycoprotein 0.717 0.001 -- --
A0A3Q1MAU7 S-formylglutathione hydrolase 1.143 0.086 -- --
SUPZN-RAC/SUPZN-NO1
A0A3Q1MG04 Fibrinogen beta chain 0.772 0.017 0.561 0.005
A0A3Q1ND53 Hydroxyacylglutathione hydrolase 1.182 0.090 -- --
F6QND5 Fibrinogen alpha chain 0.848 0.095 -- --
  • CON = no supplemental Zn (analyzed 36 mg Zn/kg DM); SUPZN = CON + 60 mg Zn/kg DM from ZnSO4 + 60 mg Zn/kg DM from Zn-AA complex (Availa-Zn; Zinpro Corporation, Eden Prairie, MN); NO = no supplemental ractopamine hydrochloride; RAC = 300 mg·steer-1·d-1 ractopamine hydrochloride (Actogain45; Zoetis, Parsippany, NJ) from day 62 to end of trial.

Supplementation of RAC demonstrates shifts in muscle structure and metabolism proteins, representing potential for greater glycolytic-like muscle fiber characteristics. Supplementation of Zn altered muscle structure proteins, representing potential for greater glycolytic-like muscle fibers. The combination of feeding RAC and Zn influenced proteins related to protein synthesis potentially indicating greater protein synthesis.

Discussion

In previous studies, supplementing Zn at concentrations well above National Academies of Sciences, Engineering, and Medicine (2016) recommendations (30 mg Zn/kg DM) has been shown to increase the performance benefits of RAC in beef cattle. Genther-Schroeder et al. (2016a) noted ADG and G:F were linearly increased in steers fed RAC at 300 mg·steer−1·d−1 and supplemented a Zn-amino acid complex at 0 to 90 mg Zn/kg DM (88 to 178 mg total dietary Zn/kg DM). Further examination of Zn supplementation (85 or 150 mg dietary Zn/kg DM) to RAC-fed steers indicated greater supplementation of Zn increased ADG and G:F of steers fed RAC at 300 mg·steer−1·d−1 for 28 d and increased carcass-adjusted final BW, ADG, and HCW when steers received RAC for 28 or 42 d (Genther-Schroeder et al., 2016b). Interestingly, supranutritional supplementation of Zn (140 mg Zn/kg DM) in the current study improved HCW by 14 kg and improved carcass-adjusted final BW and overall ADG compared with CON steers, regardless of RAC treatment. However, the interaction between ZNTRT and RACTRT for DP is supportive of the synergistic effects of these 2 supplements seen in previous studies (Genther-Schroeder et al., 2016a, 2016b).

Performance responses to Zn and RAC supplementation have been variable. Edenburn et al. (2016) observed no effects of increased Zn supplementation (33 mg Zn/kg DM vs. 97 mg Zn/kg DM) with RAC supplementation (400 mg·steer−1·d−1) on performance or carcass data of steers fed to 638 kg, but steers were only started on the Zn treatment 35 d prior to RAC supplementation. Additionally, Genther-Schroeder et al. (2018) did not see any performance or carcass data effects from steers fed RAC (300 mg·steer−1·d−1) after 47 d of dietary Zn supplementation (total dietary Zn analyzed at 30, 95, 152, 188, 209, or 230 mg Zn/kg DM). Unlike the current study, Genther-Schroeder et al. (2018) utilized steers weighing only 427 kg at the start of the trial and 585 kg at harvest. In comparison, steers in the current study were started on their Zn treatment 62 d prior to RAC supplementation and were approximately 715 kg when harvested. In studies where Zn and RAC had positive effects on performance and carcass data, steers were started on their Zn treatment 42 to 86 d prior to RAC supplementation and were at least 600 kg when harvested. Interestingly, more pronounced beta-adrenergic agonist responses have been observed in heavier cattle (Vestergaard et al., 1994; Winterholler et al., 2007), suggesting greater fat stores provide more substrate for RAC to mobilize and fuel protein accretion. Therefore, the number of days on increased Zn supplementation, as well as the finished BW of the steers being supplemented, may affect the response to RAC.

Structural proteins

In the current study, myosin regulatory light chain 2 abundance was greater in SUPZN-RAC than CON-RAC and CON-NO. As myosin regulatory light chain 2 is increasingly phosphorylated, it is believed to increase muscle fiber contractile force by upregulating the pyrophosphate release of actomyosin crossbridges, even at decreased calcium concentrations (Davis et al., 2002; Bozzo et al., 2003). Myosin light chain kinase 2, the enzyme responsible for phosphorylating myosin regulatory light chain 2, had a greater abundance in RAC-fed steers. This RAC-driven increase in abundance of myosin light chain kinase is also shown in the proteomics data analyzed for phosphorylation modifications. Previous studies have observed an increase in phosphorylated myosin regulatory light chain 2 when the muscle fibers have experienced a slow-to-fast-twitch fiber type shift (Bozzo et al., 2003). It has been hypothesized that fast-twitch muscle fibers are more responsive to extracellular signals than slow-twitch (Nwoye et al., 1982). This has been especially apparent through beta-adrenergic agonist consistently increasing the cross-sectional area of fast-twitch fibers, resulting in greater muscle mass but having inconsistent effects on slow-twitch fibers (Miller et al., 1988). Additionally, the observed lesser abundance of slow skeletal troponin 1 in both CON-RAC and SUPZN-NO compared with CON-NO supports the myosin light chain data because this protein is more abundant in slow-twitch muscle. Thus, revealing a potential role of both supranutritional Zn and RAC independently influencing muscle fiber characteristics in the biopsies collected in this study. Because histochemical analysis was not conducted in this experiment, it is unknown if these nutritional strategies influenced muscle fiber types.

Energy metabolism

As the proportion of fast-twitch fibers increases, the abundance of glycolytic enzymes would be expected to increase as well. Aconitase is an enzyme in oxidative metabolism responsible for the reversible conversion of citrate to isocitrate. The phosphorylation of mitochondrial aconitase results in an increase in the reverse reaction (Lin et al., 2009). This decreases the amount of substrate entering the electron transport chain and results in decreased mitochondrial function and impaired oxidative metabolism. In the present study, aconitase was more abundant in SUPZN-RAC compared with CON-RAC or SUPZN-NO, and abundance was greater in SUPZN-NO and CON-NO compared with CON-RAC when analyzed for phosphorylation modifications. Therefore, Zn and RAC may independently be facilitating the phosphorylation of aconitase to reduce the oxidative potential of muscle fiber characteristics. L-lactate dehydrogenase B is a Zn-dependent enzyme (Price, 1962) responsible for the anaerobic conversion of pyruvate to lactate and is more abundant in glycolytic fibers (Huber et al., 2007). In the current study, L-lactate dehydrogenase B had an increased abundance in SUPZN-NO compared with CON-NO and CON-RAC. This may suggest that steers fed SUPZN had greater ability to utilize lactate as an energy substrate, an effect that carried over into postmortem muscle and hastened pH decline as well as postmortem tenderization as reported by Schulte et al. (2021). Interestingly, this effect was diminished by RAC supplementation, resulting in a slower fall in postmortem pH and greater time needed for postmortem tenderization (Schulte et al., 2021). In addition, the abundance of the aerobic enzyme citrate synthase was lesser in SUPZN-NO compared with CON-NO, showing the decreased oxidative metabolic potential in SUPZN-NO. Myoglobin is more abundant in oxidative fibers because of the need to transport oxygen to facilitate greater aerobic metabolism. Myoglobin was greater in abundance in CON-NO compared with CON-RAC and SUPZN-NO and was also greater in abundance in CON-NO compared with SUPZN-RAC when analyzed for phosphorylation modifications. These differences were also confirmed in muscle at 1 h postmortem, wherein CON-NO–fed steers had a greater abundance of myoglobin compared with CON-RAC–fed animals (Schulte, unpublished data, 2023). This difference could relate to muscle fiber characteristics; however, muscle fiber types were not analyzed in the current study.

Protein synthesis/degradation

Along with metabolic shifts, in the current study, both supranutritional Zn and RAC affected the abundance of enzymes involved in protein synthesis in the longissimus thoracis. Supplementation of RAC resulted in increased abundance of eukaryotic initiation factor 5A in SUPZN-RAC compared with SUPZN-NO as well as an increased abundance in SUPZN-RAC compared with SUPZN-NO and CON-NO when analyzed for phosphorylation modifications. This specific initiation factor is present in differentiating satellite cells (Luchessi et al., 2009), and muscle fibers are able to synthesize protein at only 70% of the typical rate when the fibers are depleted of this initiation factor (Kang and Hershey, 1994). Although the role of phosphorylation on this factor has yet to be defined, its positive regulation of translation has been observed when it is phosphorylated (Chung et al., 2013). Additionally, elongation factor 1-alpha 2 was more abundant in SUPZN-RAC compared with CON-NO. This factor is needed for the elongation of proteins in the ribosome during protein synthesis (Sanges et al., 2012). The greater abundance of both of these factors in SUPZN-RAC demonstrates the increased potential for protein synthesis because of combined effect of Zn and RAC fed together.

These Zn effects on enzymes involved in protein synthesis paired with greater HCW in SUPZN steers suggest that increased Zn supplementation is critical to improve cattle growth. In the current study, Zn supplementation resulted in a 10.92% increase in plasma Zn concentrations by Day 62 that continued throughout the RAC feeding period. Similarly, Genther-Schroeder et al. (2016a) observed a linear increase in plasma Zn concentrations following 78 d of Zn supplementation (60, 90, 120, or 150 mg Zn/kg DM) prior to feeding RAC. This plasma Zn response corresponded to linear improvements in growth performance during RAC supplementation (Genther-Schroeder et al., 2016a), suggesting an increased pool of circulating Zn may be critical to support RAC-induced growth processes. Furthermore, both SUPZN and RAC increased liver Zn concentrations, even though liver Zn is readily difficult to change (Suttle, 2010). However, a linear decrease in liver Zn concentrations with increasing Zn supplementation within RAC-fed steers observed by Genther-Schroeder et al. (2016a) contradicts the findings of the current study. Perhaps supplemental Zn was great enough to support increased circulating Zn concentrations and Zn storage in the liver. However, more research is warranted to understand how supplemental Zn influences liver and plasma Zn concentrations and how body Zn stores affect the growth performance of RAC-fed steers.

Cell health proteins

Both Zn and Fe have been shown to be sequestered during infection to prevent their use by infectious microbes in a process known as nutritional immunity (Corbin et al., 2008; Kehl-Fie and Skaar, 2010). Genther-Schroeder et al. (2016b) hypothesized supplementation of RAC may be causing an inflammatory response, leading to an increase in Zn and Fe in the liver. Although not statistically significant in the study by Genther-Schroeder et al. (2016b) or the current study, this RAC effect of increased liver Zn and Fe appears to be numerically driven by increased supplementation of Zn. Genther-Schroeder et al. (2016b) did not measure liver Fe, but RAC was shown to decrease plasma Fe similarly to the decrease in plasma Fe observed in the current study. These data further support the hypothesis that Fe is being sequestered.

In addition to supranutritional Zn supplementation influencing liver and plasma Fe concentrations, the current study observed ZNTRT effects on liver Mn and Cu concentrations. Increased liver Mn concentrations at harvest caused by SUPZN appear to be driven by the numerically decreased liver Mn in CON-NO steers. However, a similar effect was observed by Carmichael et al. (2018) when Mn absorption and retention were increased with increasing Zn supplementation. Perhaps this effect is in response to Mn and Zn competing for Zrt/Irt-like proteins (ZIP) transporters to enter the liver (Lin et al., 2017). Consistent with our understanding of Zn’s antagonistic pressure on Cu (Reeves et al., 1993; Kincaid, 2000), SUPZN steers tended to have 14.41% lower liver Cu concentrations at harvest than CON steers. Similarly, Messersmith et al. (2021b) observed a 6.52% decrease in liver Cu concentrations in heifers supplemented 100 vs. 30 mg Zn/kg DM for 168 d. Stable plasma Cu concentrations throughout the study suggest the antagonism between Zn and Cu more strongly influences liver Cu stores than circulating Cu concentrations. Furthermore, liver Cu concentrations of Zn supplemented steers remained adequate (Kincaid, 2000), indicating the antagonism was not severe.

Miscellaneous proteins

RAC has been shown to decrease lipogenesis and increase lipolysis (Mills and Liu, 1990; Peterla and Scanes, 1990; Ross et al. 2011). Lesser abundance of fatty acid synthase in the longissimus thoracis of CON-RAC steers versus SUPZN-NO steers in the present study may reflect the depressive effect of RAC on lipogenic enzymes. The current study also noted decreased serum NEFA concentrations caused by RAC, consistent with observations by Messersmith et al. (2021a). This effect is likely a result of rapidly growing tissues picking up NEFA from the bloodstream as an energy source at a faster rate than they are being released. It has been established that RAC supplementation increases N retention as protein is accreted in the animal (Ricke et al., 1999; Ross et al., 2011; Carmichael et al., 2018). As a result, less muscle protein is likely to be catabolized, supporting the lesser PUN noted in RAC steers in the present study.

Conclusions

In conclusion, supranutritional Zn and RAC supplementation positively affect carcass-adjusted performance. Because of the lack of positive effects of Zn supplementation when it is initiated close to the start of RAC supplementation (Edenburn et al., 2016), it is interesting to speculate that there may be a minimum number of days of Zn supplementation needed prior to RAC supplementation. Although muscle fiber type was not measured in the current study, supranutritional Zn and RAC supplementation, both independently and collectively, demonstrates evidence of an altered muscle fiber characteristics through shifting structural and metabolic enzyme abundances and phosphorylation states. More research is needed to determine if Zn supplementation is shifting muscle fiber type and, if so, how this occurs in order to design a Zn and RAC supplementation strategy to maximize these hypertrophic effects.

Acknowledgements

This research was funded by the Agriculture and Food Research Initiative grant no. 2018-67015-27546/project accession no. 1015001 from the USDA National Institute of Food and Agriculture. The authors declare no conflicts of interest.

Literature Cited

AOAC. 2000. Fat (crude) or ether extract in animal feed. AOAC 920.39. AOAC International, Rockville, MD.

AOAC. 2005a. Protein (crude) in animal feed. AOAC 990.03. AOAC International, Rockville, MD.

AOAC. 2005b. Amylase-treated neutral detergent fiber in feeds using refluxing in beakers or crucibles. AOAC 2002.04. AOAC International, Rockville, MD.

Bohrer, B. M., B. M. Edenburn, D. D. Boler, A. C. Dilger, and T. L. Felix. 2014. Effect of feeding ractopamine hydrochloride (Optaflexx) with or without supplemental zinc and chromium propionate on growth performance, carcass characteristics, and meat quality of finishing steers. J. Anim. Sci. 92:3988–3996. doi: https://doi.org/10.2527/jas.2014-7824.

Bozzo, C., L. Stevens, L. Toniolo, Y. Mounier, and C. Reggiani. 2003. Increased phosphorylation of myosin light chain associated with slow-to-fast transition in rat soleus. Am. J. Physiol.-Cell Ph. 285:C575–C583. doi: https://doi.org/10.1152/ajpcell.00441.2002.

Carlson, K. B., K. J. Prusa, C. A. Fedler, E. M. Steadham, E. Huff-Lonergan, and S. M. Lonergan. 2017. Proteomic features linked to tenderness of aged pork loins. J. Anim. Sci. 95:2533–2546. doi: https://doi.org/10.2527/JAS.2016.1122.

Carmichael, R. N., O. N. Genther-Schroeder, C. P. Blank, E. L. Deters, S. J. Hartman, E. K. Niedermayer, and S. L. Hansen. 2018. The influence of supplemental zinc and ractopamine hydrochloride on trace mineral and nitrogen retention of beef steers. J. Anim. Sci. 96:2939–2948. doi: https://doi.org/10.1093/jas/sky177.

Chong, J., O. Soufan, C. Li, I. Caraus, S. Li, G. Bourque, D. Wishart, and J. Xia. 2018. MetaboAnalyst 4.0: towards more transparent and integrative metabolomics anlaysis. Nucleic Acids Res. 46:W486–W494. doi: https://doi.org/10.1093/nar/gky310.

Chung, J., A. A. Rocha, R. R. Tonelli, B. A. Castilho, and S. Schenkman. 2013. Eukaryotic initiation factor 5A dephosphorylation is required for translational arrest in stationary phase cells. Biochem. J. 451:257–267. doi: https://doi.org/10.1042/BJ20121553.

Corbin, B. D., E. H. Seeley, A. Raab, J. Feldmann, M. R. Miller, V. J. Torres, K. L. Anderson, B. M. Dattilo, P. M. Dunman, R. Gerads, R. M. Caprioli, W. Nacken, W. J. Chazin, and E. P. Skaar. 2008. Metal chelation and inhibition of bacterial growth in tissue abscesses. Science. 319:962–965. doi: https://doi.org/10.1126/science.1152449.

Cousins, R. J. 1998. A role of zinc in the regulation of gene expression. P. Nutr. Soc. 57:307–311. doi: https://doi.org/10.1079/pns19980045.

Dalton, T. P., D. Bittel, and G. K. Andrews. 1997. Reversible activation of mouse metal response element-binding transcription factor 1 DNA binding involves zinc interaction with the zinc finger domain. Mol. Cell. Biol. 17:2781–2789. doi: https://doi.org/10.1128/MCB.17.5.2781.

Davis, J. S., C. L. Satorius, and N. D. Epstein. 2002. Kinetic effects of myosin regulatory light chain phosphorylation on skeletal muscle contraction. Biophys. J. 83:359–370. doi: https://doi.org/10.1016/S0006-3495(02)75175-8.

Edenburn, B. M., S. G. Kneeskern, B. M. Bohrer, W. Rounds, D. D. Boler, A. C. Dilger, and T. L. Felix. 2016. Effects of supplementing zinc or chromium to finishing steers fed ractopamine hydrochloride on growth performance, carcass characteristics, and meat quality. J. Anim. Sci. 94:771–779. doi: https://doi.org/10.2527/jas.2015-9979.

Genther-Schroeder, O. N., M. E. Branine, and S. L. Hansen. 2016a. The effects of increasing supplementation of zinc-amino acid complex on growth performance, carcass characteristics, and inflammatory response of beef cattle fed ractopamine hydrochloride. J. Anim. Sci. 94:3389–3398. doi: https://doi.org/10.2527/jas.2015-0209.

Genther-Schroeder, O. N., M. E. Branine, and S. L. Hansen. 2016b. The influence of supplemental Zn-amino acid complex and ractopamine hydrochloride feeding duration on growth performance and carcass characteristics of finishing beef cattle. J. Anim. Sci. 94:4338–4345. doi: https://doi.org/10.2527/jas.2015-0159.

Genther-Schroeder, O. N., M. E. Branine, and S. L. Hansen. 2018. Effects of increasing supplemental dietary Zn concentration on growth performance and carcass characteristics in finishing steers fed ractopamine hydrochloride. J. Anim. Sci. 96:1903–1913. doi: https://doi.org/10.1093/jas/sky094.

Huang, D. W., B. T. Sherman, X. Zheng, J. Yang, T. Imamichi, R. Stephens, and R. A. Lempicki. 2009. Extracting biological meaning from large gene lists with DAVID. Current Protocols in Bioinformatics. 27:13.11.1–13.11.13. doi: https://doi.org/10.1002/0471250953.bi1311s27.

Huber, K., J. Petzold, C. Rehfeldt, K. Ender, and I. Fiedler. 2007. Muscle energy metabolism: structural and functional features in different types of porcine striated muscles. J. Muscle Res. Cell M. 28:249–258. doi: https://doi.org/10.1007/s10974-007-9123-8.

Kang, H. A., and J. W. B. Hershey. 1994. Effect of initiation factor eIF-5A depletion on protein synthesis and proliferation of Saccharomyces cerevisiae. J. Biol. Chem. 269:3934–3940. doi: https://doi.org/10.1016/S0021-9258(17)41723-6.

Kehl-Fie, T. E., and E. P. Skaar. 2010. Nutritional immunity beyond iron: a role for manganese and zinc. Curr. Opin. Chem. Biol. 14:218–224. doi: https://doi.org/10.1016/j.cbpa.2009.11.008.

Kim, S., Y. Jung, D. Kim, H. Koh, and J. Chung. 2000. Extracellular zinc activates p70 S6 kinase through the phosphatidylinositol 3-kinase signaling pathway. J. Biol. Chem. 275:25979–25984. doi: https://doi.org/10.1074/jbc.M001975200.

Kincaid, R. L. 2000. Assessment of trace mineral status of ruminants: a review. J. Anim. Sci. 77:1–10. doi: https://doi.org/10.2527/jas2000.77E-Suppl1x.

Lin, G., R. W. Brownsey, and K. M. MacLeod. 2009. Regulation of mitochondrial aconitase by phosphorylation in diabetic rat heart. Cell. Mol. Life Sci. 66:919–932. doi: https://doi.org/10.1007/s00018-009-8696-3.

Lin, W., D. R. Vann, P.-T. Doulias, T. Wang, G. Landesberg, X. Li, E. Ricciotti, R. Scalia, M. He, N. J. Hand, and D. J. Rader. 2017. Hepatic metal ion transporter ZIP8 regulates manganese homeostasis and manganese-dependent enzyme activity. J. Clin. Invest. 127:2407–2417. doi: https://doi.org/10.1172/JCI90896.

Liu, C. Y., J. L. Boyer, and S. E. Mills. 1989. Acute effects of beta-adrenergic agonists on porcine adipocyte metabolism in vitro. J. Anim. Sci. 67:2930–2936. doi: https://doi.org/10.2527/jas1989.67112930x.

Luchessi, A. D., T. D. Cambiaghi, S. M. Hirabara, R. H. Lambertucci, L. R. Silveira, I. L. Baptista, A. S. Moriscot, C. M. Costa-Neto, and R. Curi. 2009. Involvement of eukaryotic translation initiation factor 5A (eIF5A) in skeletal muscle stem cell differentiation. J. Cell. Physiol. 218:480–489. doi: https://doi.org/10.1002/jcp.21619.

McClung, J. P., T. N. Tarr, B. R. Barnes, A. G. Scrimgeour, and A. J. Young. 2007. Effect of supplemental dietary zinc on the mammalian target of rapamycin (mTOR) signaling pathway in skeletal muscle and liver from post-absorptive mice. Biol. Trace Elem. Res. 118:65–76. doi: https://doi.org/10.1007/s12011-007-0018-8.

Messersmith, E., M. Branine, O. Genther-Schroeder, J. McGill, and S. Hansen. 2021a. Initial liver copper status in finishing beef steers fed three dietary concentrations of copper affects beta agonist performance, carcass characteristics, lipolysis response, and muscle inflammation markers. Animals. 11:2753. doi: https://doi.org/10.3390/ANI11092753.

Messersmith, E. M., E. K. Niedermayer, K. J. Thornton, G. I. Crawford, and S. L. Hansen. 2021b. Zinc supplementation strategies in feedlot heifers receiving an extended-release implant or an aggressive re-implant program. J. Anim. Sci. 99:skab212. doi: https://doi.org/10.1093/JAS/SKAB212.

Miller, M. F., D. K. Garcia, M. E. Coleman, P. A. Ekeren, D. K. Lunt, K. A. Wagner, M. Procknor, T. H. Welsh, Jr., and S. B. Smith. 1988. Adipose tissue, longissimus muscle and anterior pituitary growth and function in clenbuterol-fed heifers. J. Anim. Sci. 66:12–20.

Mills, S. E., and C. Y. Liu. 1990. Sensitivity of lipolysis and lipogenesis to dibutyryl-cAMP and β-adrenergic agonists in swine adipocytes in vitro. J. Anim. Sci. 68:1017–1023. doi: https://doi.org/10.2527/1990.6841017x.

National Academies of Sciences, Engineering, and Medicine. 2016. Nutrient requirements of beef cattle. 8th ed. National Academies Press, Washington, DC.

Nwoye, L., W. F. Mommaerts, D. R. Simpson, K. Seraydarian, and M. Marusich. 1982. Evidence for a direct action of thyroid hormone in specifying muscle properties. Am. J. Physiol.-Reg. I. 242:R401–R408. doi: https://doi.org/10.1152/ajpregu.1982.242.3.R401.

Pampusch, M. S., M. E. White, M. R. Hathaway, T. J. Baxa, K. Y. Chung, S. L. Parr, B. J. Johnson, W. J. Weber, and W. R. Dayton. 2008. Effects of implants of trenbolone acetate, estradiol, or both, on muscle insulin-like growth factor-I, insulin-like growth factor-I receptor, estrogen receptor-α, and androgen receptor messenger ribonucleic acid levels in feedlot steers. J. Anim. Sci. 86:3418–3423. doi: https://doi.org/10.2527/jas.2008-1085.

Pang, Z., J. Chong, S. Li, and J. Xia. 2020. MetaboAnalystR 3.0: toward an optimized workflow for global metabolomics. Metabolites. 10:186. doi: https://doi.org/10.3390/metabo10050186.

Perkins, D. N., D. J. Pappin, D. M. Creasy, and J. S. Cottrell. 1999. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis. 20:3551–3567. doi: https://doi.org/10.1002/(sici)1522-2683(19991201)20:18%3C3551::aid-elps3551%3E3.0.co;2-2.

Peterla, T. A., and C. G. Scanes. 1990. Effect of β-adrenergic agonists on lipolysis and lipolgenesis by porcine adipose tissue in vitro. J. Anim. Sci. 68:1024–1029. doi: https://doi.org/10.2527/1990.6841024x.

Pogge, D. J., M. E. Drewnoski, and S. L. Hansen. 2014. High dietary sulfur decreases the retention of copper, manganese, and zinc in steers. J. Anim. Sci. 92:2182–2191. doi: https://doi.org/10.2527/jas.2013-7481.

Pogge, D. J., and S. L. Hansen. 2013. Supplemental vitamin C improves marbling in feedlot cattle consuming high sulfur diets. J. Anim. Sci. 91:4303–4314. doi: https://doi.org/10.2527/jas.2012-5638.

Price, C. A. 1962. A zinc-dependent lactate dehydrogenase in Euglena gracilis. Biochem. J. 82:61–66. doi: https://doi.org/10.1042/bj0820061.

Reeves, P. G., K. L. Rossow, and D. J. Bobilya. 1993. Zinc-induced metallothionein and copper metabolism in intestinal mucosa, liver, and kidney of rats. Nutr. Res. 13:1419–1431. doi: https://doi.org/10.1016/S0271-5317(05)80791-2.

Ricke, E. A., D. J. Smith, V. J. Feil, G. L. Larsen, and J. S. Caton. 1999. Effects of ractopamine HCl stereoisomers on growth, nitrogen retention, and carcass composition in rats. J. Anim. Sci. 77:701–707. doi: https://doi.org/10.2527/1999.773701x.

Ross, K. A., A. D. Beaulieu, J. Merrill, G. Vessie, and J. F. Patience. 2011. The impact of ractopamine hydrochloride on growth and metabolism, with special consideration of its role on nitrogen balance and water utilization in pork production. J. Anim. Sci. 89:2243–2256. doi: https://doi.org/10.2527/jas.2010-3117.

Samuelson, K. L., M. E. Hubbert, M. L. Galyean, and C. A. Löest. 2016. Nutritional recommendations of feedlot consulting nutritionists: the 2015 New Mexico State and Texas Tech University survey. J. Anim. Sci. 94:2648–2663. doi: https://doi.org/10.2527/jas.2016-0282.

Sanges, C., C. Scheuermann, R. P. Zahedi, A. Sickmann, A. Lamberti, N. Migliaccio, A. Baljuls, M. Marra, S. Zappavigna, J. Reinders, U. Rapp, A. Abbruzzese, M. Caraglia, and P. Arcari. 2012. Raf kinases mediate the phosphorylation of eukaryotic translation elongation factor 1A and regulate its stability in eukaryotic cells. Cell Death Dis. 3:e276. doi: https://doi.org/10.1038/cddis.2012.16.

Schulte, M. D., K. G. Hochmuth, E. M. Steadham, K. J. Prusa, S. M. Lonergan, S. L. Hansen, and E. Huff-Lonergan. 2021. The influence of supranutritional zinc and ractopamine hydrochloride supplementation on early postmortem pH decline and meat quality development of beef. Meat Muscle Biol. 5:37, 1–15.

Spurlock, M. E., J. C. Cusumano, S. Q. Ji, D. B. Anderson, C. K. Smith, II, D. L. Hancock, and S. E. Mills. 1994. The effect of ractopamine on β-adrenoceptor density and affinity in porcine adipose and skeletal muscle tissue. J. Anim. Sci. 72:75–80. doi: https://doi.org/10.2527/1994.72175x.

Suttle, N. F. 2010. Mineral nutrition of livestock. 4th ed. CABI Publishing, Wallingford, UK.

Tabb, D. L., J. K. Eng, and J. R. Yates, III. 2001. Protein identification by SEQUEST. In: P. James, editor, Proteom research: mass spectrometry. Springer Berlin, Heidelberg, Germany. p. 125–142. doi: https://doi.org/10.1007/978-3-642-56895-4_7.

USDA NASS. 2019. 2017 census of agriculture: United States summary and state data. Volume 1: Part 51. USDA, Washington, DC.

Vestergaard, M., P. Henckel, N. Oksbjerg, and K. Sejrsen. 1994. The effect of cimaterol on muscle fiber characteristics, capillary supply, and metabolic potentials of longissimus and semitendinosus muscles from young Friesian bulls. J. Anim. Sci. 72:2298–2306. doi: https://doi.org/10.2527/1994.7292298x.

Wang, S.-Y., and D. H. Beermann. 1988. Reduced calcium-dependent proteinase activity in cimaterol-induced muscle hypertrophy in lambs. J. Anim. Sci. 66:2545–2550. doi: https://doi.org/10.2527/jas1988.66102545x.

Winterholler, S. J., G. L. Parsons, C. D. Reinhardt, J. P. Hutcheson, W. T. Nichols, D. A. Yates, R. S. Swingle, and B. J. Johnson. 2007. Response to ractopamine-hydrogen chloride is similar in yearling steers across days on feed. J. Anim. Sci. 85:413–419. doi: https://doi.org/10.2527/jas.2006-555.

Supplementary Table 1.

Miscellaneous differentially abundant proteins

Proteomic Data Phosphorylation Modification
Uniprot ID Protein Name Fold Change Adj. P-value Fold Change Adj. P-value
CON-RAC/CON-NO1
A0A3Q1LX93 CXXC motif-containing zinc-binding protein 0.835 0.030 -- --
A5D7J6 Calreticulin 0.838 0.073 -- --
SUPZN-NO/CON-NO1
A4IFQ8 NOL3 protein 0.890 0.007 -- --
Q2HJ33 Obg-like ATPase 1 0.837 0.008 -- --
A0A3Q1LX93 CXXC motif-containing zinc-binding protein 0.809 0.010 -- --
A0A3Q1LYW4 Phosphorylase b kinase regulatory subunit 0.896 0.038 -- --
Q3T0B6 Complement component 1 Q subcomponent binding protein 0.811 0.040 -- --
P48644 Retinal dehydrogenase 1 1.227 0.053 -- --
Q3ZCH9 Haloacid dehalogenase-like hydrolase domain-containing protein 1.248 0.071 -- --
F1MCZ0 GMP reductase 0.829 0.078 -- --
A0A0A0MP92 Serpin A3-7 0.822 0.081 -- --
K4JDR8 Alpha-2-macroglobulin 1.161 0.088 -- --
O46375 Transthyretin -- -- 1.344 0.10
SUPZN-RAC/CON-NO1
A0A3Q1LX93 CXXC motif-containing zinc-binding protein 0.826 0.033 -- --
A5PK37 EPM2A glucan phosphatase 1.247 0.035 -- --
P12234 Phosphate carrier protein 1.245 0.053 -- --
A0A3Q1M0J3 Phosphorylase kinase catalytic subunit gamma 1 1.135 0.076 1.381 0.042
G3X6N3 Serotransferrin 0.898 0.082 -- --
Q3SZV7 Hemopexin -- -- 1.244 0.079
O46375 Transthyretin 0.805 0.085 -- --
SUPZN-NO/CON-RAC1
Q3SZV7 Hemopexin 1.140 0.008 -- --
Q32PA8 Mth938 domain-containing protein 0.894 0.047 -- --
O46375 Transthyretin 1.195 0.051 1.443 0.058
F1MCZ0 GMP reductase 0.760 0.055 -- --
A0A3Q1M1H0 LIM domain binding 3 1.149 0.063 -- --
Q3ZCH9 Haloacid dehalogenase-like hydrolase domain-containing protein 1.189 0.074 -- --
SUPZN-RAC/CON-RAC1
A0A3Q1M0J3 Phosphorylase kinase catalytic subunit gamma 1 1.140 0.074 1.319 0.080
Q3SZV7 Hemopexin 1.129 0.078 1.227 0.071
SUPZN-RAC/SUPZN-NO1
A0A3Q1M1H0 LIM domain binding 3 0.845 0.017 -- --
O46375 Transthyretin 0.733 0.017 0.700 0.061
Q32PA8 Mth938 domain-containing protein 1.106 0.037 -- --
F1N7X3 Nucleosome assembly protein 1-like 4 1.181 0.051 -- --
A5PK37 EPM2A glucan phosphatase 1.191 0.097 -- --
A0A3Q1M0J3 Phosphorylase kinase catalytic subunit gamma 1 -- -- 1.299 0.100
  • CON = no supplemental Zn (analyzed 36 mg Zn/kg DM); SUPZN = CON + 60 mg Zn/kg DM from ZnSO4 + 60 mg Zn/kg DM from Zn-AA complex (Availa-Zn; Zinpro Corporation, Eden Prairie, MN); NO = no supplemental ractopamine hydrochloride; RAC = 300 mg·steer-1·d-1 ractopamine hydrochloride (Actogain45; Zoetis, Parsippany, NJ) from day 62 to end of trial.