Skip to main content
Journal of Animal Science logoLink to Journal of Animal Science
. 2020 Jul 20;98(8):skaa232. doi: 10.1093/jas/skaa232

Fetal expression of genes related to metabolic function is impacted by supplementation of ground beef and sucrose during gestation in a swine model

Ashley S Hoyle 1, Ana Clara B Menezes 1, Megan A Nelson 1, Kendall C Swanson 1, Kimberly A Vonnahme 2, Eric P Berg 1, Alison K Ward 1,
PMCID: PMC7431213  PMID: 32687162

Abstract

To determine the effects of maternal supplementation on the mRNA abundance of genes associated with metabolic function in fetal muscle and liver, pregnant sows (Landrace × Yorkshire; initial body weight (BW) 221.58 ± 33.26 kg; n = 21) fed a complete gestation diet (corn–soybean meal based diet, CSM) were randomly assigned to 1 of 4 isocaloric supplementation treatments: control (CON, 378 g/d CSM, n = 5), sucrose (SUGAR, 255 g/d crystalized sugar, n = 5), cooked ground beef (BEEF, 330 g/d n = 6), or BEEF + SUGAR (B+S, 165 g/d cooked ground beef and 129 g/d crystalized sugar, n = 5), from days 40 to 110 of gestation. Sows were euthanized on day 111 of gestation. Two male and 2 female fetuses of median BW were selected from each litter, and samples of the longissimus dorsi muscle and liver were collected. Relative transcript level was quantified via qPCR with HPRT1 as the reference gene for both muscle and liver samples. The following genes were selected and analyzed in the muscle: IGF1R, IGF2, IGF2R, GYS-1, IRS-1, INSR, SREBP-1C, and LEPR; while the following were analyzed in the liver: IGF2, IGF2R, FBFase, G6PC, PC, PCK1, FGF21, and LIPC. No effect of fetal sex by maternal treatment interaction was observed in mRNA abundance of any of the genes evaluated (P > 0.11). In muscle, the maternal nutritional treatment influenced (P = 0.02) IGF2 mRNA abundance, with B+S and SUGAR fetuses having lower abundance than CON, which was not different from BEEF. Additionally, SREBP-1 mRNA abundance was greater (P < 0.01) for B+S compared with CON, BEEF, or SUGAR fetuses; and females tended (P = 0.06) to have an increased abundance of SREBP-1 than males. In fetal liver, IGF2R mRNA abundance was greater (P = 0.01) for CON and BEEF than SUGAR and B+S; while FBPase mRNA abundance was greater (P = 0.03) for B+S compared with the other groups. In addition, maternal nutritional tended (P = 0.06) to influence LIPC mRNA abundance, with increased abundance in CON compared with SUGAR and B+S. These data indicate limited changes in transcript abundance due to substitution of supplemental sugar by ground beef during mid to late gestation. However, the differential expression of FBPase and SREBP-1c in response to the simultaneous supplementation of sucrose and ground beef warrants further investigations, since these genes may play important roles in determining the offspring susceptibility to metabolic diseases.

Keywords: fetal programming, gene expression, liver, maternal supplementation, muscle, sows

Introduction

Prenatal and early postnatal nutrition can produce epigenetic changes that can impact postnatal development of metabolic pathways and physiology that ultimately result in increased susceptibility to chronic diseases such as obesity, insulin resistance, hypertension, and elevated serum cholesterol levels (Waterland and Jirtle, 2003; Heijmans et al., 2008; Tobi et al., 2009). A well-documented meta-analysis utilizing sheep or rodent models reported associations between nutritional challenges in early embryo development and health outcomes later in life (Lillycrop and Burdge, 2011). Human epidemiological studies, specifically studies of the Dutch Hunger Winter, suggest that individuals whose mothers were exposed to famine periconceptually and in the first trimester of pregnancy exhibit an increased risk of metabolic or mental diseases in adulthood (Tobi et al., 2009; Lillycrop and Burdge, 2015) that may be driven or influenced by the sex of the exposed individual (Tobi et al., 2009). In more recent times, much of the developed world’s populace is faced with over nutrition, characterized by excess levels of macronutrients, specially refined sugars (Kereliuk et al., 2017). According to recent USDA reports (Dietary Guidelines for Americans, 2015 to 2020), added sugars account for 270 additional calories (or 13% of calories consumed) per day in the United States. Furthermore, maternal diets containing high levels of saturated fats or refined sugars appear to be a factor in the pathogenesis of obesity and metabolic syndrome in subsequent offspring (Kereliuk et al., 2017).

In this study, a swine model was adopted because pigs share anatomical and physiological features with humans and is considered a unique model for translational research in nutrition-related pregnancy pathologies (Gonzalez-Bulnes et al., 2015). Additionally, in swine production, the gestational period is a critical phase (Wu et al., 2014; Ji et al., 2017) because in utero nutrition plays a significant role for litter performance (Oksbjerg et al., 2013), metabolic profile (Arentson-Lantz et al., 2014), and expression of genes involved in appetite and metabolism regulation (Óvilo et al., 2014). According to a recent literature review (Zhang et al., 2019), the effects of maternal undernutrition on neonatal development have been widely studied in sows; with intrauterine growth retardation being the focus of many studies (Foxcroft et al., 2006). Additionally, impaired glucose metabolism in piglets has been observed as a result of maternal energy restriction and obesity during pregnancy (Arentson-Lantz et al., 2014) and offspring muscle development, embryonic and neonatal growth are affected by dietary protein intake during pregnancy (Zhang et al., 2019). However, little is known about the epigenetic impacts of specific nutrient supplies, such as carbohydrates or protein on offspring metabolism.

The objective of this study was to determine if beef, sucrose, or the combination of beef and sucrose (snacks) supplemented during mid to late gestation impact expression of genes associated with glucose and lipid metabolism in offspring. We focused on mid to late gestation because little is known about the effects of maternal diet on fetal metabolism during this period, since researchers have focused more on the peri-implantation and early embryo development period (Kaczmarek et al., 2020). Fetuses were harvested at day 111 because most fetal growth occurs in the last 3 wk of pregnancy (Wu et al., 2006), suggesting that the effects of maternal diet on fetal metabolism would have a greater impact during this period.

Materials and Methods

All animal procedures were approved by the North Dakota State University Animal Care and Use Committee.

Animals, treatments, and fetal tissue collection

Twenty-one multiparous pregnant sows (Landrace × Yorkshire; initial body weight (BW) of 222 ± 35 kg) were used in this study. Sows were maintained on a common diet prior to artificial insemination from a common sire. Pregnancy was confirmed via ultrasonography on day 30 of gestation, and sows were individually housed in farrowing crates (2.1 × 0.6 m), exposed to 12 hr of light (0700 to 1900 hours) daily, and barn temperature maintained at 19.4 °C and fed a standard gestation diet (corn–soybean meal-based diet, CSM; Table 1), formulated to meet nutrient and net energy requirements for a gestating sow (NRC, 2012), daily at 0700 hours at an intake of 1% of BW on day 30. At day 40 of gestation, intake was adjusted to 1% BW on day 39, and sows were randomly assigned to 1 of 4 isocaloric supplementation treatments (Table 2): control (CON, 378 g/d CSM, n = 5), sucrose (SUGAR, 255 g/d crystalized sugar, n = 5), cooked ground beef (BEEF, 330 g/d n = 6), or BEEF + SUGAR (B+S, 165 g/d cooked ground beef and 129 g/d crystalized sugar, n = 5). The supplements were provided daily at 1100, 1500, and 1800 hours from days 40 to 110 of gestation. All sows were provided ad libitum access to water. On day 111 of gestation, sows were euthanized. One sow was euthanized through electrical stunning (ESS Best and Donovan Hog Stunner; Cincinnati, OH) and exsanguination, while all other sows were euthanized through chemical sedation using Telazol (Zoetis; Parsippany, NJ) and AnaSed (xylazine, AKORN Animal Health, Akorn, Inc.; Lake Forest, IL) administered at 0.1 mL/kg intramuscular injection followed by exsanguination. Longissimus dorsi muscle and liver samples were collected from 2 male and 2 female fetuses of median weight from each litter (n = 84), preserved in RNAlater (Thermo Fisher Scientific Inc., Waltham, MA), and stored at −20 °C.

Table 1.

Ingredients and chemical composition of the gestation diet

Items
Ingredients %, as fed basis
 Corn 70.77
 Soybean meal 9.85
 Soy hulls 14.99
 MonoCal 1.47
 Limestone 1.06
 Fat, Choice White Grease 0.75
 Salt 0.45
 Choline 60 (dry) 0.11
 EnMax Sow Premix 101 0.50
Chemical composition
 Dry matter, % 89.21
 Total carbohydrate2 51.04
 Ash 5.25
 Crude protein 11.18
 Total dietary fiber 18.62
 Ether extract 3.11
 Calcium 0.75
 Phosphorus 0.58
 Net energy3, Mcal/kg 2.06

1Provided the following (per kilogram of product): 181.8 g of crude protein, 151.0 g of lysine, 16.0 g of crude fiber, minimum 35 g of Ca, maximum 45 g of Ca, 59.99 ppm of Se, 18,814 ppm of Zn, and 141,666 FTU/kg phytase.

2Carbohydrates were estimated by difference.

3Calculated using ingredient values according to NRC (2012).

Table 2.

Chemical composition of the supplementation treatments fed to the sows from days 40 to 110 of gestation1

Item CON supplement BEEF supplement SUGAR supplement B+S supplement
Chemical composition, % as fed basis
 Dry matter, % 89.33 48.21 99.60 99.38
 Carbohydrates 52.46 0.05 100.00 49.79
 Ash 5.09 1.62 0.00 1.66
 Crude protein 12.02 23.46 0.00 24.18
 Total dietary fiber 16.45 0.00 0.00 0.00
 Ether extract 3.29 23.08 0.00 23.78
 Calcium 0.63 0.00 0.00 0.01
 Phosphorus 0.66 0.20 0.00 0.20
Dietary energy values2
Calories, daily 1015.9 1019.3 1026.6 1025.3
Calories, % total diet 13.13 13.17 13.25 13.23

1CON, control supplement (378 g/d corn–soybean meal); BEEF, cooked ground beef supplement (330 g/d); SUGAR, granulated sugar supplement (255 g/d); B+S, cooked ground beef (165 g/d) and granulated sugar (129 g/d).

2Calculated based on physiological fuel values of 4, 4, and 9 kcal/g for carbohydrate, protein, and lipid, respectively (FAO, 2003).

Genes of interest

In this study, genes of interest were selected based upon their association with glucose and lipid metabolism and subsequent association to metabolic diseases such as diabetes and obesity. The genes selected are involved in the following rate-limiting pathway steps: insulin-like growth factor pathway [insulin-like growth factor 1 receptor (IGF1R), insulin-like growth factor 2 (IGF2), and insulin-like growth factor 2 receptor (IGF2R)], gluconeogenesis [glycogen synthase 1 (GYS-1), fructose 1, 6-bisphosphatase (FBFase), glucose-6-phosphatase (G6PC), pyruvate carboxylase (PC), and phosphoenolpyruvate carboxykinase 1 (PCK1)], insulin signaling [insulin receptor substrate 1 (IRS-1), insulin receptor (INSR), and sterol regulatory element-binding protein 1-c (SREBP-1c)], and adipocyte metabolism [Leptin receptor (LEPR), fibroblast growth factor 21 (FGF21), and hepatic lipase (LIPC)].

RNA extraction, cDNA synthesis, and real-time PCR

Prior to RNA extraction, samples (~50 mg of muscle and 30 mg of liver) were lysed in 1 mL QIAzol Lysis reagent (Qiagen, Hilden, Germany), extracted with 200 µL chloroform (VWR, West Chester, PA), and the aqueous phase was combined with 500 µL isopropanol (Merk, Darmstadt, Germany). The RNA was extracted and purified via an RNeasy Mini Kit (Qiagen, Valencia, CA). The concentration of RNA extracted was determined using the Qubit 3.0 Fluorometer (Thermo Fisher Scientific Inc.). A total of 1 μg of RNA was used for cDNA synthesis via an Applied Biosystems High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific Inc.).

Real-time, quantitative PCR was performed for muscle and liver samples to determine relative mRNA abundance of IGF1R, IGF2, IGF2R, GYS-1, IRS-1, INSR, SREBP-1C, and LEPR in the muscle; and IGF2, IGF2R, FBFase, G6PC, PC, PCK1, FGF21, and LIPC in the liver. All primer sequences (Table 3) were designed using Primer-Blast (National Center for Biotechnology Information, Bethesda, MD). The relative mRNA abundance was quantified using a 7500 Fast Real-Time PCR System (Applied Biosystems, Grand Island, NY) with SYBR Green Master Mix (Bio-Rad Laboratories), with 20 μL total reaction volume for all genes. Amplification efficiency was determined by a 5-point 10-fold dilution standard curve and was within 90% to 110% for each primer set. A melt curve analysis was performed with each reaction to ensure that there was no off-target amplification. Relative abundance of the genes evaluated was calculated using the 2−ΔΔCt method (LiVak and Schmittgen, 2001). Four reference genes (GAPDH, HPRT1, PPIA, and ACTB) were evaluated separately for fetal liver and muscle tissue for their stability of expression across treatments. Hypoxanthine phosphoribosyltransferase 1 (HPRT1) was chosen as the reference gene because it had the lowest M-value in both the liver and muscle (Biogazelle qbase+ software, BioGazelle, Zwijnaarde, Belgium), indicating consistent expression across treatment groups.

Table 3.

Primer sets used for real-time quantitative reverse-transcription PCR

Gene1 Accession no. Length, bp2 Forward Reverse
GYS-1 NM_001195508.1 150 CAGGACTGGAAGATTGGGAGG AGTAGTTGTCGCCCCATTCA
INSR XM_005654749.2 123 GCCTTTCAAACGAGCAGGTG GCATCTTGGGGTTGAACTGC
IRS-1 NM_001244489.1 130 AGAGGACCGTCAGTAGCTCA GAAGGTGTGAGGTCCTGGTT
IGF1R NM_214172.1 139 GATTCAGGCCACCTCTCTCTCC CCCTCCTACTATCAACAGAACGGC
IGF2 NM_213883.2 212 ACACCCTCCAGTTTGTCTGC GGGGTATCTGGGGAAGTTGT
IGF2R NM_001244473.1 194 CAGGAACTGCTTTCTGAGCA TGGAATCTGCCTTTTTCACC
LEPR NM_001024587.1 82 TCTGCTCCCCCAGAAAGGTA CACAGGCACATGGCATTCAC
SREBP-1C NM_214157.1 75 AATAAATCCGCCGTCTTGCG CTGCTTGAGCTTCTGGTTGC
LIPC NM_001143714.1 119 GCCTGGGATTAGAGCTACTGG CTGACAGCCCTGATCGGTTT
PCK1 NM_001123158.1 78 CAAGGAGAGAAAACGTAGGCGA TTTGAGAGCTGAGGAGGCAT
G6PC NM_001113445.1 79 TTGCTGGAGTCTTGTCAGGC TTCTTGAGGCTGGCGTTGTA
PC NM_214349.1 78 TACGTCGCCCACAACTTCAG GAAGCGCATCGCAACATCAA
FGF21 NM_001163410.1 89 CACGTCCCATTCCTGACTCC AGTTTCCTGGGCATCATCCG
FBPase NM_213979.1 130 GAGTTCGACCCTGCCATCAC TCCCTCCATAGACCAGCGTG
HPRT1 XM_021079504.1 167 GGGAGGCCATCACATCGTAG CGCCCGTTGACTGGTCATTA
ACTB XM_021086047 170 AGATCAAGATCATCGCGCCT ATGCAACTAACAGTCCGCCT
GAPDH NM_001206359.1 84 CATTGCCCTCAACGACCACT ATGAGGTCCACCACCCTGTT
PPIA NM_214353 174 GCGTCTCCTTCGAGCTGTTT ACTTGCCACCAGTGCCATTA

1 GYS-1, glycogen synthase 1; INSR, insulin receptor; IRS-1, insulin receptor substrate 1; IGF1R, insulin like growth factor 1 receptor; IGF2, insulin like growth factor 2; IGF2R, insulin like growth factor 2 receptor; LEPR, leptin receptor; SREBP-1C, sterol regulatory element binding protein 1c; LIPC, hepatic lipase; PCK1, phosphoenolpyruvate carboxykinase 1; G6PC, glucose 6 phosphatase; PC, pyruvate carboxylase; FGF21, fibroblast growth factor 21; FBPase, fructose 1,6 bisphosphatase; HPRT1, hypoxanthine phosphoribosyltransferase 1.

2Amplicon length in base pairs.

Feed analysis and calculations

Diet samples and sucrose and corn–soybean meal samples (used to manufacture SUGAR, CON, and B+S snacks) were dried in a 55 °C oven for at least 48 hr and ground to pass a 1-mm screen; while samples of ground beef (used to manufacture the BEEF and B+S snacks) were freeze dried and ground. All samples were analyzed for dry matter, ash, N (Kjehldahl method), ether extract, Ca, and P by standard procedures (AOAC, 1990). Percentage CP was calculated by multiplying N concentration × 6.25. Additionally, carbohydrates were estimated by difference (available carbohydrates), and dietary fiber was determined by an enzymatic-gravimetric method (Lee et al., 1992; AOAC method 991.43). Dietary available energy values were estimated using physiological fuel values of 4, 4, and 9 kcal/g for carbohydrate, protein, and lipid, respectively (FAO, 2003). The basal diet provided on average 6,723.12 kcal/d, and the snacks were formulated to provide on average 1,021.8 kcal/d (Table 2), and therefore a total daily caloric intake of 7,744.9 kcal. Thus, the amount of calories provided by the snacks represented ~13% of the daily calorie consumption. In this study, the extra calories provided by the supplements (snacks) mimic the average caloric intake of added sugar per day by women in reproductive age in the United States (Dietary Guidelines for Americans, 2015 to 2020).

Statistical analysis

The experimental design was completely randomized with a 2 × 4 factorial arrangement of treatments, comparing fetal sex (male vs. female) with maternal dietary supplementation (CON vs. BEEF vs. B+S vs. SUGAR). Gene expression data were analyzed using the GLM procedure of SAS version 9.4 (SAS Inst. Inc., Cary, NY). Fetal sex, maternal supplementation treatment, and their interaction were included as fixed effects in the model. Litter size was included as a covariate for fetal BW. Means were separated with a PDIFF STDERR option of LSMEANS statement, with differences determined at a P-value of ≤0.05, while P-values between 0.05 and 0.10 were considered a trend.

Results

Morphological measurements

Dietary did not affect sow BW on day 39 or 111 of gestation (Table 4). Additionally, there was no effect of treatment on litter size, number of males per litter, or number of females per litter. There was a trend (P = 0.10) for treatment × sex interaction for fetal BW (Figure 1). This appears to be driven by the BEEF treatment in which females had a numerically greater BW than males, in contrast to all other treatments where the reverse was true. This treatment × sex interact for fetal BW was significant (P = 0.01) for the subset of 2 male and 2 female median weight fetuses per litter (Figure 2). BEEF male fetuses had significantly greater BW than BEEF females and SUGAR males were significantly greater than CON females.

Table 4.

Sow BW, litter size, and fetal BW of fetuses harvested at 111 d of gestation from sows submitted to 4 different supplementation treatments (adapted from Nelson, 2019)

Measurement Treatments1 SEM P-value
CON BEEF B+S SUGAR Trt
Sow day 39 BW, kg 201.9 240.2 205.1 208.8 18.5 0.99
Sow day 111 BW, kg 235.3 235.5 231.7 238.4 17.8 0.94
Males per litter 8.2 8.2 8.0 5.4 2.0 0.31
Females per litter 7.4 6.6 7.0 6.8 1.1 0.96
Total litter size 15.8 14.8 15.0 12.6 2.0 0.55

1CON, control supplement (378 g/d corn–soybean meal); BEEF, cooked ground beef supplement (330 g/d); B+S, cooked ground beef (165 g/d) and granulated sugar (129 g/d); SUGAR, granulated sugar supplement (255 g/d).

Figure 1.

Figure 1.

The effect of maternal dietary treatment during gestation on fetal piglet BW at day 111 of gestation. CON, control supplement (378 g/d corn–soybean meal); BEEF, cooked ground beef supplement (330 g/d); SUGAR, granulated sugar supplement (255 g/d); B+S, cooked ground beef (165 g/d) and granulated sugar (129 g/d). Error bars depict the standard error.

Figure 2.

Figure 2.

The effect of maternal dietary treatment during gestation on fetal piglet BW of the median 2 male and 2 female piglets per litter at day 111 of gestation. CON, control supplement (378 g/d corn–soybean meal); BEEF, cooked ground beef supplement (330 g/d); SUGAR, granulated sugar supplement (255 g/d); B+S, cooked ground beef (165 g/d) and granulated sugar (129 g/d). Values not sharing a common superscript are significantly different (P ≤ 0.05). Error bars depict the standard error.

There was no significant treatment × sex interaction for median fetal liver weight (P = 0.48), liver weight as a % of BW (P = 0.40), semimembranosus with adductor weight (P = 0.48), semimembranosus with adductor weight as a % of BW (P = 0.53), semitendinosus weight (P = 0.37), or semitendinosus weight as a % of BW (P = 0.39), therefore only the main effects of treatment will be presented. Fetal liver weight was significantly greater for SUGAR than CON or BEEF; however, this difference was no longer present when corrected to % BW (Table 5). There was also no effect of treatment on semimembranosus with adductor weight, semimembranosus with adductor weight as a % of BW, semitendinosus weight, or semitendinosus weight as a % of BW (Table 5).

Table 5.

Fetal body, liver, and muscle weights of 2 median weigh male and female fetuses per litter harvested at 111 d of gestation from sows submitted to 4 different supplementation treatments (adapted from Nelson, 2019)

Measurement Treatments1 SEM P-value
CON BEEF B+S SUGAR Trt
Liver, g 33.4a 31.4a 34.2ab 40.1b 2.16 0.04
Liver, % BW 4.07 2.70 2.75 2.49 0.78 0.32
Semimembranosus with adductor, g 7.13 7.93 7.74 7.12 0.86 0.84
Semimembranosus with adductor, % BW 0.89 0.66 0.62 0.41 0.21 0.30
Semitendinosus, g 3.41 3.28 3.76 3.48 0.48 0.53
Semitendinosus, % BW 0.29 0.23 0.21 0.13 0.07 0.34

1CON, control supplement (378 g/d corn–soybean meal); BEEF, cooked ground beef supplement (330 g/d); B+S, cooked ground beef (165 g/d) and granulated sugar (129 g/d); SUGAR, granulated sugar supplement (255 g/d).

abMeans without a common superscript differ (P ≤ 0.05).

Muscle

There were no interactions between treatment and fetal sex (P > 0.12) on the relative mRNA abundance of any of the genes evaluated (Table 6). A main effect of maternal nutritional treatment and fetal sex was only seen in a few instances; therefore, we will describe only significant main effects and tendencies observed. The maternal nutritional treatment influenced (P = 0.02) IGF2 mRNA abundance, with B+S and SUGAR treatments lower than CON, which was not different from BEEF Additionally, SREBP-1 mRNA abundance was greater (P < 0.01) for B+S fetuses compared with CON, BEEF, or SUGAR fetuses; and female fetuses tended (P = 0.06) to have a greater mRNA abundance of SREBP-1 than males.

Table 6.

Messenger RNA abundance of IGF1R, IGF2, IGF2R, GYS-1, IRS-1, INSR, SREBP-1c, and LEPR in muscle samples of female and male fetuses harvested at 111 d of gestation from sows submitted to 4 different supplementation treatments

Gene1 Sex Treatments2 SEM P-value
CON BEEF B+S SUGAR Average Sex Trt Sex Trt × Sex
IGF1R Female 4.97 6.54 2.64 6.74 5.22 2.40 0.52 0.29 0.97
Male 3.41 4.34 2.36 4.28 3.59
Average Trt 4.19 5.44 2.49 5.51
IGF2 Female 1.53 2.19 1.19 0.92 1.46 0.68 0.02 0.25 0.18
Male 3.81 2.17 1.07 0.87 1.98
Average Trt 2.67a 2.19ab 1.13b 0.89b
IGF2R Female 1.56 5.75 5.48 4.86 0.99 2.32 0.29 0.89 0.92
Male 2.65 4.65 5.93 3.68 1.00
Average Trt 2.10 5.20 5.71 4.27
GYS-1 Female 2.41 1.98 1.44 2.19 2.01 0.91 0.96 0.45 0.69
Male 2.38 1.99 3.24 2.29 2.48
Average Trt 2.39 1.99 2.34 2.24
IRS1 Female 0.26 0.92 0.29 0.28 0.44 0.29 0.46 0.48 0.44
Male 0.22 0.29 0.46 0.24 0.30
Average Trt 0.24 0.60 0.38 0.26
INSR Female 0.61 0.65 0.63 0.62 0.63 0.06 0.58 0.84 0.76
Male 0.59 0.64 0.71 0.59 0.64
Average Trt 0.60 0.65 0.67 0.61
SREBP-1c Female 1.32 1.52 3.81 2.54 2.29a 0.48 <0.01 0.06 0.12
Male 1.46 1.64 2.11 1.54 1.69b
Average Trt 1.39a 1.58a 2.96b 2.04a
LEPR Female 0.31 0.45 0.19 0.48 0.36 0.17 0.67 0.71 0.59
Male 0.46 0.32 0.24 0.24 0.32
Average Trt 0.38 0.39 0.22 0.36

1 IGF1R, insulin-like growth factor 1 receptor; IGF2, insulin-like growth factor 2; IGF2R, insulin-like growth factor 2 receptor; GYS-1, glycogen synthase 1; IRS-1, insulin receptor substrate 1; INSR, insulin receptor; SREBP-1C, sterol regulatory element binding protein 1c; LEPR, leptin receptor.

2CON, control supplement (378 g/d corn–soybean meal); BEEF, cooked ground beef supplement (330 g/d); B+S, cooked ground beef (165 g/d) and granulated sugar (129 g/d); SUGAR, granulated sugar supplement (255 g/d).

abMeans without a common superscript differ (P ≤ 0.05).

Liver

None of the genes evaluated were affected by a treatment × sex interaction (P > 0.11) or by the main effect of fetal sex (P > 0.13); therefore, we will only discuss the significant main effect of maternal treatment (Table 7). The mRNA abundance of IGF2R was greater (P = 0.01) for CON and BEEF than SUGAR and B+S, while the FBPase mRNA abundance was greater (P = 0.03) for B+S compared with the other groups. In addition, diet composition tended (P = 0.06) to influence LIPC abundance, with lower expression in SUGAR and B+S compared with CON.

Table 7.

Messenger RNA abundance of IGF2, IGF2R, FBPase, G6PC, PC, PCK1, FGF21, and LIPC in liver samples of female and male fetuses harvested at 111 d of gestation from sows submitted to 4 different supplementation treatments

Gene1 Sex Treatments2 SEM P-value
CON BEEF B+S SUGAR Average Sex Trt Sex Trt × Sex
IGF2 Female 0.36 0.28 0.09 0.27 0.26 0.26 0.26 0.13 0.84
Male 0.78 0.57 0.08 0.61 0.51
Average Trt 0.57 0.42 0.09 0.44
IGF2R Female 0.99 0.92 0.19 0.28 0.59 0.31 0.01 0.49 0.99
Male 0.95 0.68 0.05 0.12 0.45
Average Trt 0.97a 0.79a 0.12b 0.20b
FBPase Female 1.49 1.84 2.93 1.92 2.05 0.42 0.03 0.76 0.76
Male 1.36 2.19 2.42 1.85 1.96
Average Trt 1.43a 2.02a 2.68b 1.89a
G6PC Female 1.11 0.77 0.91 1.01 0.95 0.79 0.40 0.72 0.47
Male 2.34 1.49 0.09 0.62 1.13
Average Trt 1.72 1.13 0.49 0.81
PC Female 1.37 0.75 2.79 0.91 1.45 0.63 0.27 0.29 0.11
Male 1.05 1.79 0.88 0.31 1.00
Average Trt 1.21 1.27 1.84 0.61
PCK1 Female 0.42 0.42 1.14 0.43 0.60 0.38 0.59 0.58 0.22
Male 0.67 0.91 0.23 0.04 0.46
Average Trt 0.54 0.66 0.69 0.24
FGF21 Female 1.02 1.11 0.64 1.56 1.08 1.00 0.43 0.66 0.41
Male 2.24 2.68 0.26 0.34 1.38
Average Trt 1.63 1.89 0.45 0.95
LIPC Female 3.15 1.14 1.76 1.09 1.78 0.97 0.06 0.79 0.66
Male 3.03 2.26 0.75 0.40 1.61
Average Trt 3.09a 1.69ab 1.26b 0.75b

1 IGF2, insulin-like growth factor 2; IGF2R, insulin-like growth factor 2 receptor; FBPase, fructose 1,6 bisphosphatase; G6PC, glucose 6 phosphatase; PC, pyruvate carboxylase; PCK1, phosphoenolpyruvate carboxykinase 1; FGF21, fibroblast growth factor 21; LIPC, hepatic lipase.

2CON, control supplement (378 g/d corn–soybean meal); BEEF, cooked ground beef supplement (330 g/d); B+S, cooked ground beef (165 g/d) and granulated sugar (129 g/d); SUGAR, granulated sugar supplement (255 g/d).

abMeans without a common superscript differ (P ≤ 0.05).

Discussion

In this study, a swine model was used to determine whether beef, sucrose, or the combination of beef and sucrose (snacks) supplemented during mid to late gestation impact expression of genes associated with glucose and lipid metabolism in offspring. The level of supplemental sucrose offered in the present study was based on the average intake of added sugar per day by women of reproductive age in the United States (Dietary Guidelines for Americans, 2015 to 2020). Therefore, the SUGAR supplement parallels the elevated consumption of high-glycemic carbohydrates present in the standard American diet, or Western pattern diet, where junk food, sugar-sweetened beverages, and confectionary products are major dietary components (Dietary Guidelines for Americans, 2015 to 2020; Zambrano and Nathanielsz, 2017). Furthermore, in the context of increasingly energy-dense, nutrient-poor food environment in the United States, there is increased interest in the promotion of nutrient-rich diets during pregnancy (Colón-Ramos et al., 2015), especially because the Western-style high sugar diet can adversely impact mothers and fetuses during pregnancy and predispose offspring to later life metabolic dysfunction (Zambrano and Nathanielsz, 2017).

Thus, as red meat is an important dietary source of protein, saturated fat, and essential nutrients including iron, zinc, and vitamin B12 (McAfee et al., 2010), our supplemental BEEF treatment was hypothesized to provide a healthy alternative to sugar, while providing the same daily caloric intake during gestation and lactation. A recent study (O’Connor et al., 2018) reported that overweight or obese adults can consume typical U.S. quantities of lean, unprocessed beef, and pork (red meat; ∼70 g/d) when following a balanced diet to improve cardiometabolic disease risk factors. In addition, Derbyshire (2017) revealed that UK women consuming diets lower in red meat (<40 g/d) had reduced micronutrient intake of zinc, iron, and vitamin D, suggesting that nutritional demands of pregnancy would not be attained. Nevertheless, health recommendations worldwide encourage a reduction in red meat intake (Dietary Guidelines for Americans, 2015 to 2020).

Muscle and liver are key tissues regulating whole animal energy balance. Therefore, among all the target tissues affected by maternal nutrition, muscle and liver have received considerable scientific interest. Skeletal muscle plays a key role in the regulation of glucose homeostasis (Lowell and Shulman 2005), while liver is a central organ in lipogenesis, gluconeogenesis, and cholesterol metabolism (Bechmann et al., 2012). Glucose plays an important role in fetal development since it is the main energy source for fetal growth (Père, 1995). The pregnant sow undergoes significant metabolic adaptations during the last third of pregnancy, such as a decline in glucose tolerance, in order to improve placental transfer of glucose to meet the fetal requirements (Pere et al., 2000). However, fetal-maternal glucose homeostasis is a complex trait, and according to a recent review (Franzago et al., 2019), the identification of polymorphisms in genes related to carbohydrate metabolism, lipid/lipoprotein metabolism, appetite control/food intake, and energy expenditure, suggest a strong relationship among maternal diet, fetal gene expression, and glucose homeostasis.

In the current study, we observed that the supplementation treatments during mid to late gestation resulted in a differential mRNA abundance of IGF2 in muscle and IGF2R in liver of offspring. The IGF pathway, which comprises insulin, IGF1, IGF2, and their respective receptors and binding proteins, is known to have a central role in fetal growth. In this study, the relative mRNA abundance of IGF2 in fetal muscle was greater for CON and BEEF, which would suggest a greater fetal BW. Though there was a treatment × sex interaction for fetal BW (Figure 2), it did not follow the pattern that we would expect from the IGF2 mRNA abundance. An important consideration is that there is a substantial posttranscriptional, translational, and protein degradation event that controls steady-state protein abundances (Vogel and Marcotte, 2012). In this study, we did not measure the fetal IGF2 protein abundance. It is possible that IGF2 levels did not differ among fetuses from different treatments. It is also possible that the IGF2 mRNA downregulation observed in SUGAR and B+S fetuses may be a compensatory mechanism to prevent excessive fetal growth from increased maternal sucrose supply.

Regarding the IGF2R mRNA abundance in fetal liver, it was observed a decreased IGF2R mRNA abundance in fetuses from SUGAR and B+S sows, which were treatments that provided the fetuses with more available glucose for growth. Given that IGF2R is involved in the degradation of IGF2, a growth-promoting factor, our results suggest that IGF2R expression in the fetus responds to maternal nutrients by adapting expression levels that maintain its function as a growth suppressor. Similar results were observed by Wang et al. (2015), who reported that expression levels of IGF2R were greater in calves from dams receiving high starch vs. dams fed low starch ratios, suggesting subsequent phenotypic changes in offspring BW. In fact, previous studies in sheep (Radunz et al., 2011a; Radunz et al., 2011b; Lan et al 2013) reported that birth weight of progeny from dams fed high starch diets was greater than progeny from dams fed low starch rations. These data, along with our IGF2R mRNA abundance results, would suggest that IGF2 levels would be higher in SUGAR and B+S fetuses, and consequently those fetuses would have a heavier BW. As previously highlighted, we did not measure the fetal IGF2 protein abundance; however, SUGAR fetuses presented a heavier liver than CON and BEEF (Table 5)

Hepatic gluconeogenic enzymes develop in the porcine fetus during the last weeks of pregnancy to maintain glucose availability to the fetus during this period of rapid growth (Fowden et al., 1995). The rate of gluconeogenesis is determined by the key enzymes G6PC, PCK1, and FBPase. It has been reported that in intrauterine growth retardation fetuses, inadequate nutrient supply stimulates gluconeogenesis earlier in pregnancy by upregulating the gluconeogenic enzymes G6PC and PCK1 (Fowden et al., 1995; Jia et al., 2012,Metges et al., 2014), which possibly contribute to adult-onset hyperglycemia. A differential mRNA abundance of G6PC, PCK1, PC, and GYS-1 mRNA was not observed in this study, likely because the treatments were able to provide an adequate glucose supply to the fetuses. This study did however reveal an increased hepatic FBPase mRNA abundance in B+S fetuses. It is unclear why FBPase was differentially expressed in B+S fetuses, but it is possible that there was a synergistic interaction between the supplemental macronutrients (especially carbohydrates and protein) provided by the simultaneous supplementation of sucrose and ground beef. In fact, human studies show that a combination of protein and carbohydrate after exercise increase lean body mass, by decreasing muscle protein breakdown, and replenish glycogen stores in trained individuals (Outlaw et al., 2014; Kerksick et al., 2008; Campbell et al., 2007; Tarnopolsky et al., 1997, and Tremblay et al., 1994). Even though FBPase is known as a regulatory enzyme in gluconeogenesis, data from our lab (Hoyle, 2019) has found that the overexpression of hepatic FBPase in B+S fetuses did not result in changes in blood glucose concentration at birth or 2 d postpartum, nor changes in response to a glucose tolerance test performed at d 144 of age.

Results of this study suggest that the mRNA abundance of SREBP-1c in fetal muscle may be influenced by fetal sex, since we observed a tendency of greater SREBP-1c mRNA abundance in females than males. Female pigs present a higher potential for intramuscular fat deposition in the longissimus dorsi muscle than males (Wang et al., 2013), and it is known than SREBP-1c plays an important role in lipogenesis and triglyceride storage in skeletal muscle (Nadeau et al., 2006; Kamei et al., 2008). Additionally, elevated skeletal muscle triglyceride storage has been associated with insulin resistance and the development of type 2 diabetes (Stannard and Johnson., 2004; Savage et al., 2007). Therefore, further investigations regarding gender-related differences in SREBP-1c mRNA abundance and its association with intramuscular fat content and metabolic diseases may be of interest. In addition, this study suggests that SREBP-1c may be upregulated by a synergistic macronutrient interaction, since the simultaneous supplementation of sucrose and ground beef resulted in a greater expression of this gene.

Insulin resistance increases considerably in the last half of pregnancy. As a consequence, lipid metabolism is affected leading to double or triple concentrations of triglyceride and cholesterol late in gestation (Kampmann et al., 2019). Maternal high circulating levels of triglycerides reach the placenta, where they are hydrolyzed and taken up as fatty acids, then re-esterified within the placenta, and transported in lipoproteins to the fetal circulation (Mazzucco et al., 2013). Since hepatic lipase has a major role in lipoprotein metabolism, we expected that LIPC would be differentially expressed in BEEF or SUGAR offspring, due to the fat and sucrose (respectively) provided by the maternal supplements. However, LIPC mRNA abundance tended to lower in B+S and SUGAR fetuses. Previous research in rats found no change for fetal hepatic expression of INSR, LEPR, and LPL (genes related to insulin signaling and lipid metabolism) in response to a maternal diet rich in saturated fats; however, these genes were upregulated in the placenta (Mazzucco et al., 2013). Therefore, it is unclear why LIPC tended to have a greater expression in CON fetuses in the present study. Further research evaluating the hepatic fetal triglyceride content or triglyceride placenta transporters would help clarify our findings.

In conclusion, data of this study indicate limited changes in transcript abundance due to beef, sugar, or the combination of beef and sugar supplementation during mid to late gestation. We investigated key genes from 5 metabolic pathways. The differential mRNA abundance of FBPase and SREBP-1c in response to the simultaneous supplementation of sucrose and ground beef warrants further investigations. These genes are associated with gluconeogenesis and insulin signaling, respectively, suggesting that alterations in epigenetic processes may play an important role in determining the offspring susceptibility to metabolic disease. The impact of supplementing various foods and or food combinations to an otherwise healthy gestation and lactation diet on offspring growth, development, and gene expression is necessary.

Acknowledgments

Authors would like to thank the North Dakota Beef Commission and the North Dakota State Board of Agriculture Research and Education for funding support and Jennifer Young, Courtney Crane, and Mara Hirchert (North Dakota State University) for technical support.

Glossary

Abbreviations

BW

body weight

FBFase

fructose 1, 6-bisphosphatase

FGF21

fibroblast growth factor 21

GYS-1

glycogen synthase 1

G6PC

glucose-6-phosphatase

IGF1R

insulin like growth factor 1 receptor

IGF2

insulin like growth factor 2

IGF2R

insulin like growth factor 2 receptor

INSR

insulin receptor

IRS-1

insulin receptor substrate 1

LEPR

leptin receptor

LIPC

hepatic lipase

PC

pyruvate carboxylase

PCK1

phosphoenolpyruvate carboxykinase 1

SREBP-1c

sterol regulatory element-binding protein 1-c

SUGAR

sucrose treatment

Conflict of interest statement

The authors declare no real or perceived conflicts of interest.

References

  1. AOAC. 1990. Official methods of analysis. 15th ed.Assoc. Offic. Anal. Chem., Washington, DC. [Google Scholar]
  2. Arentson-Lantz E J, Buhman K K, Ajuwon K, and Donkin S S. . 2014. Excess pregnancy weight gain leads to early indications of metabolic syndrome in a swine model of fetal programming. Nutr. Res. 34:241–249. doi: 10.1016/j.nutres.2014.01.001. [DOI] [PubMed] [Google Scholar]
  3. Bechmann L P, Hannivoort R A, Gerken G, Hotamisligil G S, Trauner M, and Canbay A. . 2012. The interaction of hepatic lipid and glucose metabolism in liver diseases. J. Hepatol. 56:952–964. doi: 10.1016/j.jhep.2011.08.025. [DOI] [PubMed] [Google Scholar]
  4. Campbell B, Kreider R B, Ziegenfuss T, La Bounty P, Roberts M, Burke D, Landis J, Lopez H, and Antonio J. . 2007. International Society of Sports Nutrition position stand: protein and exercise. J. Int. Soc. Sports Nutr. 4:8. doi: 10.1186/1550-2783-4-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Colón-Ramos U, Racette S B, Ganiban J, Nguyen T G, Kocak M, Carroll K N, Völgyi E, and Tylavsky F A. . 2015. Association between dietary patterns during pregnancy and birth size measures in a diverse population in Southern US. Nutrients 7:1318–1332. doi: 10.3390/nu7021318. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Derbyshire E. 2017. Associations between red meat intakes and the micronutrient intake and status of UK females: a secondary analysis of the UK National Diet and nutrition survey. Nutrients 9(7):768. doi: 10.3390/nu9070768. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Dietary Guidelines for Americans 2015 to 2020 2015. Government Printing Office. 8th ed.Committee DGA; U.S. Department of Health and Human Services and U.S. Department of Agriculture, Washington, D.C. 2015–2020 Dietary Guidelines for Americans; December 2015. Available from http://health.gov/dietaryguidelines/2015/guidelines/. [Google Scholar]
  8. FAO. 2003. Food energy - methods of analysis and conversion factors: report of a technical workshop. FAO Food and Nutrition Paper 77. FAO, Rome, Italy: Available from http://www.fao.org/uploads/media/FAO_2003_Food_Energy_02.pdf [Google Scholar]
  9. Fowden A L, Apatu R S, and Silver M. . 1995. The glucogenic capacity of the fetal pig: developmental regulation by cortisol. Exp. Physiol. 80:457–467. doi: 10.1113/expphysiol.1995.sp003860. [DOI] [PubMed] [Google Scholar]
  10. Foxcroft G R, Dixon W T, Novak S, Putman C T, Town S C, and Vinsky M D A. . 2006. The biological basis for prenatal programming of postnatal performance in pigs. J. Anim. Sci. 84:E105–E112. doi: 10.2527/2006.8413_supplE105x [DOI] [PubMed] [Google Scholar]
  11. Franzago M, Fraticelli F, Stuppia L, and Vitacolonna E. . 2019. Nutrigenetics, epigenetics and gestational diabetes: consequences in mother and child. Epigenetics. 14:215–235. doi: 10.1080/15592294.2019.1582277 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Gonzalez-Bulnes A, Torres-Rovira L, Astiz S, Ovilo C, Sanchez-Sanchez R, Gomez-Fidalgo E, Perez-Solana M, Martin-Lluch M, Garcia-Contreras C, and Vazquez-Gomez M. . 2015. Fetal sex modulates developmental response to maternal malnutrition. PLoS One 10:e0142158. doi: 10.1371/journal.pone.0142158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Heijmans B T, Tobi E W, Stein A D, Putter H, Blauw G J, Susser E S, Slagboom P E, and Lumey L. . 2008. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc. Natl Acad. Sci. USA. 105:17046–17049. doi: 10.1073/pnas.0806560105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Hoyle A S. 2019. The role of supplemental beef vs. sugar during pregnancy on fetal and offspring developmental programming in swine [MS theses]. North Dakota State University, Fargo, ND. [Google Scholar]
  15. Ji Y, Wu Z, Dai Z, Wang X, Li J, Wang B, and Wu G. . 2017. Fetal and neonatal programming of postnatal growth and feed efficiency in swine. J. Animal Sci. Biotechnol. 8:42. doi: 10.1186/s40104-017-0173-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Jia Y, Cong R, Li R, Yang X, Sun Q, Parvizi N, and Zhao R. . 2012. Maternal low-protein diet induces gender-dependent changes in epigenetic regulation of the glucose-6-phosphatase gene in newborn piglet liver. J. Nutr. 142:1659–1665. doi: 10.3945/jn.112.160341. [DOI] [PubMed] [Google Scholar]
  17. Kaczmarek M M, Najmula J, Guzewska M M, and Przygrodzka E. . 2020. MiRNAs in the Peri-Implantation Period: Contribution to Embryo–Maternal Communication in Pigs. Int. J. Mol. Sci. 21(6):2229. doi: 10.3390/ijms21062229. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kamei Y, Miura S, Suganami T, Akaike F, Kanai S, Sugita S, Katsumata A, Aburatani H, Unterman T G, Ezaki O, . et al. 2008. Regulation of SREBP1c gene expression in skeletal muscle: role of retinoid X receptor/liver X receptor and forkhead-O1 transcription factor. Endocrinology 149:2293–2305. doi: 10.1210/en.2007-1461. [DOI] [PubMed] [Google Scholar]
  19. Kampmann U, Knorr S, Fuglsang J, and Ovesen P. . 2019. Determinants of Maternal Insulin Resistance during Pregnancy: An Updated Overview. J. Diabetes Res. 2019:5320156. doi: 10.1155/2019/5320156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kereliuk S M, Brawerman G M, and Dolinsky V W. . 2017. Maternal macronutrient consumption and the developmental origins of metabolic disease in the offspring. Int. J. Mol. Sci. 18(7):1451. doi: 10.3390/ijms18071451. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Kerksick C, Harvey T, Stout J, Campbell B, Wilborn C, Kreider R, Kalman D, Ziegenfuss T, Lopez H, and Landis. J. 2008. International Society of Sports Nutrition position stand: nutrient timing. J. Int. Soc. Sports Nutr. 14:33. doi: 10.1186/s12970-017-0189-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Lan X, Cretney E C, Kropp J, Khateeb K, Berg M A, Peñagaricano F, Magness R, Radunz A E, and Khatib H. . 2013. Maternal diet during pregnancy induces gene expression and DNA methylation changes in fetal tissues in sheep. Front. Genet. 4:49. doi: 10.3389/fgene.2013.00049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lee S, Prosky L, and Dervies J W. . 1992. Determination of total, soluble, and insoluble dietary fiber in foods: Collaborative study. J. AOAC Int. 75:395–416. doi: 10.1093/jaoac/75.3.395 [DOI] [Google Scholar]
  24. Lillycrop K A, and Burdge G C. . 2011. Epigenetic changes in early life and future risk of obesity. Int. J. Obes. (Lond.). 35:72–83. doi: 10.1038/ijo.2010.122. [DOI] [PubMed] [Google Scholar]
  25. Lillycrop K A, and Burdge G C. . 2015. Maternal diet as a modifier of offspring epigenetics. J. Dev. Orig. Health Dis. 6:88–95. doi: 10.1017/S2040174415000124. [DOI] [PubMed] [Google Scholar]
  26. Livak K J and Schmittgen T D. . 2001. Analysis of relative gene expression data using real-time quantitative PCR and the 2− ΔΔCT method. Methods. 25:402–408. doi: 10.1006/meth.2001.1262. [DOI] [PubMed] [Google Scholar]
  27. Lowell B B, and Shulman G I. . 2005. Mitochondrial dysfunction and type 2 diabetes. Science 307:384–387. doi: 10.1126/science.1104343. [DOI] [PubMed] [Google Scholar]
  28. Mazzucco M B, Higa R, Capobianco E, Kurtz M, Jawerbaum A, and White V. . 2013. Saturated fat-rich diet increases fetal lipids and modulates LPL and leptin receptor expression in rat placentas. J. Endocrinol. 217:303–315. doi: 10.1530/joe-13-0021. [DOI] [PubMed] [Google Scholar]
  29. McAfee A J, McSorley E M, Cuskelly G J, Moss B W, Wallace J M, Bonham M P, and Fearon A M. . 2010. Red meat consumption: an overview of the risks and benefits. Meat Sci. 84:1–13. doi: 10.1016/j.meatsci.2009.08.029. [DOI] [PubMed] [Google Scholar]
  30. Metges C C, Görs S, Lang I S, Hammon H M, Brüssow K P, Weitzel J M, Nürnberg G, Rehfeldt C, and Otten W. . 2014. Low and high dietary protein:carbohydrate ratios during pregnancy affect materno-fetal glucose metabolism in pigs. J. Nutr. 144:155–163. doi: 10.3945/jn.113.182691. [DOI] [PubMed] [Google Scholar]
  31. Nadeau K J, Ehlers L B, Aguirre L E, Moore R L, Jew K N, Ortmeyer H K, Hansen B C, Reusch J E, and Draznin B. . 2006. Exercise training and calorie restriction increase SREBP-1 expression and intramuscular triglyceride in skeletal muscle. Am. J. Physiol. Endocrinol. Metab. 291:E90–E98. doi: 10.1152/ajpendo.00543.2005. [DOI] [PubMed] [Google Scholar]
  32. Nelson M A. 2019. Effects of replacing supplemental sucrose with beef during mid to late gestation on maternal health and fetal development using a sow biomedical model [PhD diss.]. North Dakota State University, Fargo, ND. [Google Scholar]
  33. NRC , 2012. Nutrient requirements of swine. 11th rev ed.Washington, DC:National Academics Press. [Google Scholar]
  34. O’Connor L E, Paddon-Jones D, Wright A J, and Campbell W W. . 2018. A Mediterranean-style eating pattern with lean, unprocessed red meat has cardiometabolic benefits for adults who are overweight or obese in a randomized, crossover, controlled feeding trial. Am. J. Clin. Nutr. 108:33–40. doi: 10.1093/ajcn/nqy075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Oksbjerg N, Nissen P M, Therkildsen M, Møller H S, Larsen L B, Andersen M, and Young J F. . 2013. Meat Science and Muscle Biology Symposium: in utero nutrition related to fetal development, postnatal performance, and meat quality of pork. J. Anim. Sci. 91:1443–1453. doi: 10.2527/jas.2012-5849. [DOI] [PubMed] [Google Scholar]
  36. Outlaw J J, Wilborn C D, Smith-Ryan A E, Hayward S E, Urbina S L, Taylor L W, and Foster C A. . 2014. Effects of a pre-and post-workout protein-carbohydrate supplement in trained crossfit individuals. Springerplus 3:369. doi: 10.1186/2193-1801-3-369. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Óvilo C, González-Bulnes A, Benítez R, Ayuso M, Barbero A, Pérez-Solana M L, Barragán C, Astiz S, Fernández A, and López-Bote C. . 2014. Prenatal programming in an obese swine model: sex-related effects of maternal energy restriction on morphology, metabolism and hypothalamic gene expression. Br. J. Nutr. 111:735–746. doi: 10.1017/S0007114513002948 [DOI] [PubMed] [Google Scholar]
  38. Père M C. 1995. Maternal and fetal blood levels of glucose, lactate, fructose, and insulin in the conscious pig. J. Anim. Sci. 73:2994–2999. doi: 10.2527/1995.73102994x. [DOI] [PubMed] [Google Scholar]
  39. Père M C, Etienne M, and Dourmad J Y. . 2000. Adaptations of glucose metabolism in multiparous sows: effects of pregnancy and feeding level. J. Anim. Sci. 78:2933–2941. doi: 10.2527/2000.78112933x. [DOI] [PubMed] [Google Scholar]
  40. Radunz A E, Fluharty F L, Susin I, Felix T L, Zerby H N, and Loerch S C. . 2011a. Winter-feeding systems for gestating sheep II. Effects on feedlot performance, glucose tolerance, and carcass composition of lamb progeny. J. Anim. Sci. 89:478–488. doi: 10.2527/jas.2010-3037. [DOI] [PubMed] [Google Scholar]
  41. Radunz A, Fluharty F, Zerby H, and Loerch. S C. 2011b. Winter-feeding systems for gestating sheep I. Effects on pre-and postpartum ewe performance and lamb progeny preweaning performance. J. Anim. Sci. 89:467–477. doi: 10.2527/jas.2010-3035. [DOI] [PubMed] [Google Scholar]
  42. Savage D B, Petersen K F, and Shulman G I. . 2007. Disordered lipid metabolism and the pathogenesis of insulin resistance. Physiol. Rev. 87:507–520. doi: 10.1152/physrev.00024.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Stannard S and Johnson N. . 2004. Insulin resistance and elevated triglyceride in muscle: more important for survival than ‘thrifty’ genes? J. Physiol. 554:595–607. doi: 10.1113/jphysiol.2003.053926. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Tarnopolsky M A, Bosman M, Macdonald J R, Vandeputte D, Martin J, and Roy B D. . 1997. Postexercise protein-carbohydrate and carbohydrate supplements increase muscle glycogen in men and women. J. Appl. Physiol. (1985). 83:1877–1883. doi: 10.1152/jappl.1997.83.6.1877. [DOI] [PubMed] [Google Scholar]
  45. Tobi E W, Lumey L H, Talens R P, Kremer D, Putter H, Stein A D, Slagboom P E, and Heijmans B T. . 2009. DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific. Hum. Mol. Genet. 18:4046–4053. doi: 10.1093/hmg/ddp353. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Tremblay A, Simoneau J A, and Bouchard C. . 1994. Impact of exercise intensity on body fatness and skeletal muscle metabolism. Metabolism. 43:814–818. doi: 10.1016/0026-0495(94)90259-3. [DOI] [PubMed] [Google Scholar]
  47. Vogel C, and Marcotte E M. . 2012. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat. Rev. Genet. 13:227–232. doi: 10.1038/nrg3185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Wang X, Lan X, Radunz A E, and Khatib H. . 2015. Maternal nutrition during pregnancy is associated with differential expression of imprinted genes and DNA methyltranfereases in muscle of beef cattle offspring. J. Anim. Sci. 93:35–40. doi: 10.2527/jas.2014-8148. [DOI] [PubMed] [Google Scholar]
  49. Wang W, Xue W, Jin B, Zhang X, Ma F, and Xu X. . 2013. Candidate gene expression affects intramuscular fat content and fatty acid composition in pigs. J. Appl. Genet. 54:113–118. doi: 10.1007/s13353-012-0131-z. [DOI] [PubMed] [Google Scholar]
  50. Waterland R A, and Jirtle R L. . 2003. Transposable elements: targets for early nutritional effects on epigenetic gene regulation. Mol. Cell. Biol. 23:5293–5300. doi: 10.1128/mcb.23.15.5293-5300.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Wu G, Bazer F W, Dai Z, Li D, Wang J, and Wu Z. . 2014. Amino acid nutrition in animals: protein synthesis and beyond. Annu. Rev. Anim. Biosci. 2:387–417. doi: 10.1146/annurev-animal-022513-114113. [DOI] [PubMed] [Google Scholar]
  52. Wu G, Bazer F W, Wallace J M, and Spencer T E. . 2006. Board-invited review: intrauterine growth retardation: implications for the animal sciences. J. Anim. Sci. 84:2316–2337. doi: 10.2527/jas.2006-156. [DOI] [PubMed] [Google Scholar]
  53. Zambrano E, and Nathanielsz P W. . 2017. Relative contributions of maternal Western‐type high fat, high sugar diets and maternal obesity to altered metabolic function in pregnancy. J. Physiol. 595(14):4573. doi: 10.1113/JP274392. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Zhang S, Heng J, Song H, Zhang Y, Lin X, Tian M, Chen F, and Guan W. . 2019. Role of maternal dietary protein and amino acids on fetal programming, early neonatal development, and lactation in swine. Animals. 9:19. doi: 10.3390/ani9010019 [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Journal of Animal Science are provided here courtesy of Oxford University Press

RESOURCES