Paternal long-term exercise programs offspring for low energy expenditure and increased risk for obesity in mice

Abstract

Obesity has more than doubled in children and tripled in adolescents in the past 30 yr. The association between metabolic disorders in offspring of obese mothers with diabetes has long been known; however, a growing body of research indicates that fathers play a significant role through presently unknown mechanisms. Recent observations have shown that changes in paternal diet may result in transgenerational inheritance of the insulin-resistant phenotype. Although diet-induced epigenetic reprogramming via paternal lineage has recently received much attention in the literature, the effect of paternal physical activity on offspring metabolism has not been adequately addressed. In the current study, we investigated the effects of long-term voluntary wheel-running in C57BL/6J male mice on their offspring’s predisposition to insulin resistance. Our observations revealed that fathers subjected to wheel-running for 12 wk produced offspring that were more susceptible to the adverse effects of a high-fat diet, manifested in increased body weight and adiposity, impaired glucose tolerance, and elevated insulin levels. Long-term paternal exercise also altered expression of several metabolic genes, including Ogt, Oga, Pdk4, H19, Glut4, and Ptpn1, in offspring skeletal muscle. Finally, prolonged exercise affected gene methylation patterns and micro-RNA content in the sperm of fathers, providing a potential mechanism for the transgenerational inheritance. These findings suggest that paternal exercise produces offspring with a thrifty phenotype, potentially via miRNA-induced modification of sperm.—Murashov, A. K., Pak, E. S., Koury, M., Ajmera, A., Jeyakumar, M., Parker, M., Williams, O., Ding, J., Walters, D., Neufer, P. D. Paternal long-term exercise programs offspring for low energy expenditure and increased risk for obesity in mice.

According to the U.S. Preventative Services Task Force (USPSTF), childhood and adolescent obesity has increased 3- to 6-fold in the past 3 decades, with the rate of increase dependent on age, gender, and ethnicity (1). Childhood obesity is associated with development of metabolic disorders later in life, including early-onset type II diabetes and cardiovascular disease (2, 3). Heritability estimates for obesity and type II diabetes are high, >0.70 (4) and 0.21–0.72, respectively (5). Although both genetic and environmental components contribute to the etiology of obesity and type II diabetes, changes in the gene pool of the population over this timeframe are not sufficient to explain the recent increase of type II diabetes in adolescents. Rather, such rapid changes in heritable traits are more likely because of epigenetic modification of the genome by environmental factors (6). Of particular interest is whether detrimental epigenetic modifications may be passed to offspring. Recent studies demonstrating the perpetuation of insulin resistance to offspring in response to paternal and maternal diets support the heritability of these long-term programming effects (7, 8). In particular, a growing body of research indicates a significant influence of father’s diet on offspring (8, 9). For example, a high-fat diet in male rats programs β-cell dysfunction in female offspring (8), and a low-protein diet in male mice results in elevated hepatic expression of genes involved in lipid and cholesterol biosynthesis in offspring (9). Complementary epidemiologic observations in human populations have reported that famine experienced by paternal grandfathers is strongly linked to obesity and cardiovascular risks in the 2 subsequent generations, suggesting a nongenetic type of inheritance (10). In addition to metabolic impacts, diet-induced obesity has been found to affect reproduction. Subjecting male mice to a high-fat diet diminished reproductive and gamete functions in the 2 subsequent generations. Although the exact mechanisms of transgenerational inheritance remain to be elucidated, recent observations suggest involvement of epimutations in the germ line with imprinted-like methylation patterns that permanently reprogram DNA expression (11). Furthermore, genomic profiling has documented changes in the methylation patterns of several genes allegedly involved in the phenomenon of transgenerational pathology. Diet-induced transgenerational hypomethylation of Il13ra2 (8), as well as increased methylation at a putative enhancer for the key lipid transcription factor Ppara (9), were among those changes observed in the offspring. However, in a few studies, somatic DNA methylation in offspring failed to correlate with DNA methylation in the sperm of fathers (9, 12). This finding indicates that transmission of the epigenetic message is likely a more complex process that involves several other molecular mechanisms (12).

Although most studies of transgenerational inheritance were focused on dietary influences on predisposition to diabetes, several new lines of evidence indicate that exercise may be another critical factor (13). Although seemingly counterintuitive, some observations suggest that genes involved in metabolic efficiency program a thrifty phenotype, accounting for both higher athletic prowess and an increased risk for obesity (14). It is therefore of great interest to determine whether paternal exercise programs metabolic efficiency in offspring and affect transgenerational susceptibility to insulin resistance.

To test this hypothesis, C57BL/6J male mice were housed for 12 wk in cages, with or without access to a running wheel, and then were mated with sedentary control females. After weaning, offspring from sedentary or exercising fathers were assigned to either a high-fat or control low-fat diet for 12 wk. The offspring metabolic responses were monitored over a 12 wk period with whole-body magnetic resonance imaging (MRI), metabolic cages, glucose tolerance tests (GTT), and insulin assays, followed by quantitative (q)RT-PCR for gene expression and DNA methylation. In this study, we produced the first evidence that long-term exercise in fathers reprograms energy expenditure (EE) and insulin resistance in mouse offspring.

MATERIALS AND METHODS

Animals

All experiments were performed in C57B/6J mice (The Jackson Laboratory, Bar Harbor, ME, USA) that were bred before testing for 2 generations at East Carolina University to minimize any transgenerational effects associated with the transition in facilities. All experiments were approved by the East Carolina University Animal Care and Use Committee and were performed in accordance with the Guide for the Care and Use of Laboratory Animals ( U.S. National Institutes of Health, Bethesda, MD, USA). Testing was performed on animals of both sexes at 4–16 wk of age, housed individually on a 12 h light/dark schedule, with unlimited access to food and water. The animals were fed either a control diet containing 10% energy by fat (Diet D12450B) or a high-fat diet containing 60% energy by fat (Diet D12492) (Research Diets; New Brunswick, NJ, USA). Four-week-old F0 generation male mice were randomly assigned to either physically active [exercise father (EF); n = 64] or sedentary [control father (CF); n = 64] conditions. EF mice were kept in individual cages with 24 h access to an in-cage running wheel. The activity of the EF mice was digitally recorded with Vital View software (Mini Mitter, Bend, OR, USA), and distance was calculated by multiplying wheel circumference (39.2 cm) by the number of revolutions. The average activity level was 7.1 ± 0.3 km/d over a 12 wk period. A duration of 12 wk was chosen based on our preliminary studies and observations suggesting that this duration of voluntary wheel-running is optimal for achieving a sustained level of running activity (15). Changes in animals’ metabolism, total motor activity, food and water intake, and EE at 0, 6, and 12 wk time points were analyzed by using metabolic cages (TSE Systems, Homburg, Germany). Body weight and composition were assessed with whole-body EchoMRI-700 (EchoMRI, Houston, TX, USA). At the end of the 12 wk regimen, 10 animals from each group were humanely euthanized at the same time of day (11 am) 4 h after food removal for collection of gastrocnemius muscle and epididymal sperm. The tissue samples were snap-frozen in liquid nitrogen and stored at −80°C for subsequent assays. Epididymal sperm was collected from F0 exercised and sedentary control groups of male mice. In brief, cauda epididymides were dissected from the connective tissue and incubated in Ham’s F12 culture medium containing 0.1% bovine serum albumin (BSA) for 10 min at 37°C, according to published methods (16). Released sperm was fractionated on a Percoll gradient (Sigma-Aldrich, St. Louis, MO, USA) to remove somatic cell contamination. After centrifugation, the sperm was washed 3 times with hypotonic solution and then subjected to total RNA and genomic DNA extraction. The remaining CF and EF animals were bred with age-matched females.

Breeding

The F1 generation offspring were obtained by mating nonlittermate control females to differently exposed males. During mating, 1 male and 1 female were housed together for 2 consecutive days, during which they were allowed free access to a control diet. Females were also kept on a control diet throughout gestation and lactation. Only offspring from litters of 5–6 pups were used for experiments. Upon weaning, F1 offspring were divided into 4 groups (n = 32 each): control father offspring (CFO) males, CFO females, exercise father offspring (EFO) males, and EFO females. At 4 wk of age, and for a duration of 12 wk, each group of offspring was randomly divided and assigned to either a high-fat or a control diet. The diet challenge was designed to reveal hidden differences in the offspring phenotypes that may contribute to a predisposition for metabolic impairment.

Metabolic profiling

F0 and F1 animals were assessed for differences in body weights and body composition (lean mass, fat mass, free water, and total water; EchoMRI-700) and total activity, food and water intake, and EE at 0, 6, and 12 wk (metabolic cages; TSE Systems). The measures of O₂ consumption and CO₂ production in individual metabolic chambers were used to calculate EE and the respiratory exchange ratio, which is an index of the relative reliance on carbohydrate vs. fat oxidation. The metabolic cages were also used for the quantitative measurement of horizontal and vertical movement (XYZ-axis) as an index of physical activity over a given period. PhenoMaster software (TSE Systems) was used for recording and analyzing data.

Glucose tolerance test

GTTs were performed in the mice at 4, 10, and 16 wk of age. The mice were not fed for 4 h (7–11 am) before testing, to normalize glucose and insulin levels. The tails were nicked with a sterile razor blade and ∼50 μl of blood was collected into a capillary tube, which was immediately placed on ice. Baseline blood glucose (time 0) was measured during the initial tail nick with an AlphaTRAK glucometer (Abbott Laboratories, Alameda, CA, USA). After the baseline measurements, the animals were injected with a 50% glucose solution (2.5 g dextrose per kg of lean mass in 250 mg/ml solution, i.p.). Glucose was measured again at 30, 60, and 120 min after injection. Plasma insulin was analyzed by ELISA of blood samples collected at the 0 and 30 min time points (Millipore Corp., Billerica, MA, USA).

qRT-PCR

Total RNA was isolated from frozen tissues by standard methods (28) and then was used for cDNA synthesis and subsequent qRT-PCR. PCR reactions were performed on 10 samples each from the CFO and EFO groups for a panel of metabolic genes, including pyruvate dehydrogenase kinase 4 (Pdk4), glucose transporter 4 (Glut4) [solute carrier family 2-a4 (Slc2a4)], H19 [imprinted maternally expressed transcript (non-protein coding)], protein tyrosine phosphatase 1 (Ptpn1), O-GlcNAc transferase (Ogt), and O-GlcNAcase (Oga) (Table 1). Total RNA from sperm samples was extracted with an RNAqueous MicroScale RNA Isolation Kit according to the manufacturer’s instructions (Thermo Fisher–Life Technologies, Grand Island, NY, USA). Equal concentrations of total RNA from 3 individual sperm samples were used to produce 3 RNA pools per group. The samples were checked by RT-PCR for contamination by testicular cells (c-kit), leukocytes (CD45) or epithelial cells (E-cadherin) (17). Real-time PCR reactions on micro-RNA (miR) were performed in triplicate on a 7500 Real-Time PCR System (Thermo Fisher-Applied Biosystems, Foster City, CA, USA). As internal controls, primers for S12 (mitochondrial ribosome small subunit), U6 (the noncoding small nuclear RNA), and miR-191 were added for RNA template normalization, and the relative quantifications of gene and miRNA expression were calculated against miR-191 by the ∆∆C_t² method. Constitutively expressed miR-191 was used as a normalization control for miRNA qPCRs (18). All experiments were performed 3 times independently.

TABLE 1.

Genomic and cDNA primer sequences used in PCR reactions

Target	Gene name	Forward sequence	Reverse sequence
cDNA	Ogt	GACGCAACCAAACTTTGCAGT	TCAAGGGTGACAGCCTTTTCA
	Oga (Mgea5)	GGGTTATGGAGCAGAGAAAAGAG	CCTGGCGAAATAGCATAGATGAA
	Pdk4	AGGGAGGTCGAGCTGTTCTC	GGAGTGTTCACTAAGCGGTCA
	Ptpn1	GGAACTGGGCGGCTATTTACC	CAAAAGGGCTGACATCTCGGT
	Glut4 (Slc2a4)	GTGACTGGAACACTGGTCCTA	CCAGCCACGTTGCATTGTAG
	Ppargc1α	AACCAGTACAACAATGAGCCTG	AATGAGGGCAATCCGTCTTCA
	Igf2	GTGCTGCATCGCTGCTTAC	ACGTCCCTCTCGGACTTGG
	H19	CCTTGTCGTAGAAGCCGTCTG	GGGTAGCACCATTTCTTTCATCT
	FoxO1	AACCAGCTCAAATGCTAGTACCATC	CAGAAGGTTCTCCATGTTTTTCTGGA
	Gfpt1α	GCCGAGCTGTGCAAACTCT	GGCTGCTCAAAAATTTCCTTC
	Ins2	GACCCACAAGTGGCACAAC	TCTACAATGCCACGCTTCTG
Genomic DNA	Ogt	CCCATAGGGAGCCCTTAACC	GCGTAACAAGACTACCGACC
	Oga (Mgea5)	GGCGCCCTTTGTCCTTTT	CGCTTCCTGTTTATCCGCAC
	Pdk4	CTCCTCCCTCTCACCCTTTG	AACTTTGGGCTCCTCCCTTT
	Ptpn1	TGGAGAAGGAGTTCGAGGAG	TCTAGGGCGACGAGGATG
	Glut4 (Slc2a4)	TCGGGGCATACACACATACA	TGAAAGGTCGAAGAGGAGGG
	Ppargc1α	GAGTGACAGCCCAGCCTAC	TCCACTCTGACACACAGCAC
	H19	ATAAGGGTCATGGGGTGGT	GGCATCGTCTGTCCATTTAG
	FoxO1	AAAATACCCCACCGCCCC	GCCGAAGCAGCCAATGAAC
	Gfpt1α	AACATTCCCTTCCTCCTCCT	CCAGCATCCGCTTTAGGTTC
	Ins2	TGGCCATCTGCTGACCTAC	GACCAAAGCACCTCCTCTCT
	β-Actin	ATGCTGACCCTCATCCACTT	AATAGCCTCCGCCCTTGT

DNA methylation

Genomic DNA was isolated with DNeasy Blood and Tissue Kit (Qiagen, Germantown, MD, USA). Isolated DNA was then sonicated (S4000; Misonix, Farmingdale, NY, USA) at maximum amplitude for 9 min (30 s on/30 s off, to cool the sample) to produce 250–500 bp fragments. Size, integrity, and purity of DNA were subsequently verified by gel electrophoresis. Fragmented DNA was then incubated with MBD2 protein-coupled magnetic beads (MethylMiner Methylated DNA Enrichment Kit; Thermo Fisher–Life Technologies). The captured fragments were eluted according to the manufacturer’s protocol and precipitated in ethanol. Equal concentrations of DNA from 3 individual sperm samples were used to produce 3 DNA pools per group. The qPCR reactions were performed in triplicate with Express SyberGreenER qPCR SuperMix Universal (Thermo Fisher–Life Technologies). Primers specific for promoter regions of metabolic genes [Ogt, Oga, Pdk4, Glut4, insulin 2 (Ins2), forkhead box protein O1 (FoxO1), Ptpn1, and H19 (an imprinted gene that controls growth and body composition; ref. 20)]were obtained from Thermo Fisher–Invitrogen (Table 1). As an internal control, primers for genomic β-actin were added for template normalization. Values for each gene were then normalized vs. input fraction, which was set at 100% (captured DNA/input ×100). All methylation assays were also performed independently 3 times.

Statistical analysis

Data are expressed as means ± sem and were analyzed with Prism version 5 for Windows (Graph Pad Software; La Jolla, CA, USA). All PCR data were log transformed before statistical analyses. One-way ANOVA with post hoc Tukey multiple-comparison test or Student’s t test was used to identify the difference between means. The level of significance was set at P < 0.05.

RESULTS

Paternal exercise affects EE in male offspring

Exercise-induced influences on metabolic profiles in fathers and offspring were studied in male mice beginning at 4 wk of age. Animals were randomly assigned to either physically active or sedentary conditions. These 2 groups included CF mice with standard single-cage housing, and EF mice housed in individual cages with in-cage running wheels that allowed 24 h access to voluntary training. The activity of mice on running wheels was monitored by an automated computer system, and only the animals that ran ∼7.1 ± 0.3 km per 24 h cycle over the 12 wk period were selected for further analyses and breeding. At the end of the 12 wk period, we observed a marked increase in spontaneous motor activity of EF mice as measured in metabolic cages, which suggests an acquired shift in the physical activity level (Fig. 1). No significant differences were observed between the CF and EF groups in EE, GTT, and insulin plasma levels. The weight and especially the fat mass were significantly lower in the EF group after 12 wk of exercise (fat mass control, 5.24 ± 0.6; exercise, 2.74 ± 0.17 g; P < 0.001). Both CF and EF males then mated with age-matched control females. The F1 offspring were tracked with respect to the F0 sire to prevent any given F0 male from dominating the pool of F1 animals. On average, each father was represented by 2 offspring in each offspring group, with n based on the number of contributing fathers. The offspring metabolic responses were monitored over the 12-wk period with whole-body MRIs, GTTs, insulin ELISA, and housing for 5 consecutive days (including 2 d adaptation) in metabolic cages. At 4 wk of age, metabolic profiles of offspring from CFO and EFO mice, maintained on a control diet, were examined in metabolic cages. EE was significantly lower in EFO males than in CFO males (CFO, 24.53 ± 0.8707, n = 10; EFO, 22.36 ± 0.5652, n = 12; P < 0.05), whereas motor activity, food and water consumption, and caloric intakes were the same (Fig. 2). No significant differences were observed between female groups of offspring because of high variability of the data (data not shown). At this age, each group of offspring was randomly divided and assigned to either a high-fat diet or control diet for a duration of 12 wk. After 12 wk on a control diet, no differences were observed between CFO and EFO mice in metabolic cages (data not shown). However, after 12 wk on a high-fat regimen, EFO mice developed significantly higher weight and adiposity than CFO mice (CFO, 13.18 ± 0.9412 g, n = 11; EFO, 16.42 ± 0.7391 g, n = 12; P < 0.05), despite having consumed the same calories as the CFO mice (Fig. 3). In addition, at 12 wk the EFO group showed a significantly higher area under the curve (AUC) for glucose level in the GTT (CFO, 42002 ± 3555 n = 10; EFO, 54166 ± 3366 n = 11; P < 0.05), as well as a higher plasma insulin level revealed by ELISA (CFO, 1.37 ± 0.302 n = 8; EFO, 2.67 ± 0.326 n = 9; P < 0.05). These data demonstrate that EFO mice were more susceptible than CFO mice to weight gain and development of insulin resistance when challenged with a high-fat diet, despite no difference in activity level, food and water consumption, or total amount of calories consumed. EE was lower, however, in the EFO group, suggesting that the increased obesity of that group was attributable to a slower basal metabolic rate. These findings demonstrate that the EFO and CFO metabolic phenotypes are differentially affected by the respective fathers’ physical activity.

Figure 1.

Metabolic profiling of F0 male mice. A) Total mean weight of CF and EF mice was not significantly different before 12 wk of exercise. After 12 wk, the weight of the EF group was significantly lower. B) Low adiposity was observed in EF mice after 12 wk of exercise. C) EE was not significantly different in EF vs. CF mice, at both the 0 and 12 wk time points. D) Total motor activity was measured over 3 d at the 0 and 12 wk time points in metabolic cages. Male mice housed in cages with free wheels had significantly higher spontaneous motor activity. E) GTTs showed no differences in AUC in EFO vs. CFO mice. F) Insulin plasma levels in CFO vs. EFO mice were not different at 0 and at 12 wk time points. CFO, unfilled boxes (n = 11); EFO, filled boxes (n = 10). Data are means ± se; ANOVA.

Figure 2.

Epigenetic programming of EE in F1 mice on control diet. Offspring EE was measured at 4 wk of age in metabolic cages over a 3 d period (after a 2 d acclimation). CFO, unfilled bar (n = 8); EFO, filled bar (n = 8); y-axis, EE (in kilocalories per hour per kilogram lean mass). Data are means ± se. Student’s t test.

Figure 3.

Increased susceptibility to obesity in EFO F1 mice on a high-fat diet. A) Total weight was significantly increased. B) Increased adiposity in EFO mice challenged with a high-fat diet. C) EE was significantly lower in EFO vs. CFO mice, at both the 0 and 12 wk time points. D) Total activity at 0 and 12 wk time points, as measured in metabolic cages. E) GTT showed an increased AUC in EFO vs. CFO. F) Elevated insulin plasma levels in EFO at 12 wk time point. CFO, unfilled bars (n = 8); EFO, filled bars (n = 8). Data are means ± se; ANOVA.

Paternal exercise affects gene expression in male offspring

We also performed qRT-PCR on a group of metabolic genes in isolated gastrocnemius muscles (including both lateral and medial portions) of F0 fathers and F1 male offspring (Fig. 4). The tissues were collected after 12 wk of exercise in F0 and 12 wk of control diet in F1. In F0, we saw a significant increase only in the expression of mRNA levels of Pdk4, a mitochondrial enzyme that is a key negative regulator of glucose oxidation (19). In F1, the mRNA levels for Pdk4, H19, and Ptpn1, a negative regulator of both insulin and leptin signaling involved in the control of glucose homeostasis and EE (21), were all reduced, whereas the mRNA for Slc2a4, a glucose transporter protein, was increased in EFO compared with that in CFO muscle (Fig. 5). These differential changes in expression of metabolic genes are consistent with an increased reliance on glucose metabolism. There was a 1.27-fold increase in Ogt and a 1.26-fold increase in Oga, the sole enzymes responsible for the cycling of O-linked β-d-N-acetylglucosamine (O-GlcNAc) a key transcriptional and epigenetic regulator in metabolic conditions (22). Taken together, these findings suggest that offspring metabolic phenotypes at the transcriptome level were affected by their respective fathers’ individual experiences.

Figure 4.

Differential expression of metabolic genes in gastrocnemius muscle of F0 fathers. Samples were collected from F0 mice after 12 wk of exercise. CF, unfilled boxes (n = 10); EF, filled boxes (n = 10); y-axis, relative change in gene expression. Data are means ± se. Student’s t test.

Figure 5.

Differential expression of metabolic genes in gastrocnemius muscle of F1 offspring. Samples were collected from 120-d-old F1 offspring maintained on a control diet. CFO, unfilled bars (n = 10); EFO, filled bars (n = 10); y-axis, relative change in gene expression. Data are means ± se. Student’s t test.

Long-term exercise affects sperm DNA methylation in F0 and F1

Growing evidence suggests an altered epigenome in the germline is transmitted through subsequent generations because of changes in DNA methylation (23). These germline-mediated epimutations predominantly affect methylation of cytosines in the context of a cytosine-phosphate-guanine (CpG) dinucleotide. Methylation of CpG islands and non-CpG islands, genes in the promoter regions, can subsequently affect transcription of these genes in the developing cells and tissues (24). In this study, we evaluated DNA methylation changes in mouse sperm in response to long-term exercise. Genomic DNA was isolated from purified epididymal sperm collected from exercise and sedentary control groups of 8-wk-old C57BL/6J male mice. Methylated DNA fragments captured with MBD2 protein-coupled magnetic beads were used for the real-time qPCR reactions. Values for each gene were then normalized vs. the input fraction, which was set at 100% (captured DNA/input × 100). We found differential methylation at promoter regions in response to long-term exercise (Fig. 6). Genes with significant methylation changes included Ogt and Oga (enzymes involved in cycling of O-GlcNAc), 2 genes that are known to negatively influence insulin sensitivity in muscle cells and adipocytes by inhibiting phosphorylation of Akt1 (22); H19, an imprinted gene that is involved in the negative regulation of body weight (20); and Ptpn1 (Ptp1B), a negative regulator of the insulin signaling pathway (21). We further examined the methylation pattern of the same promoter regions in offspring sperm after 12 wk on the control diet. We found a significant decrease in the methylation of the OGA promoter and increase in methylation for PDK4 promoter in EFO DNA (Fig. 6). However, although H19 methylation was elevated, it did not reach statistical significance. These data indicate that the paternal methylation pattern, although it influences the F1 phenotype, may be not completely inherited by F2 generation.

Figure 6.

Promoter-specific analysis of methylation levels in spermatozoal DNA of F0 and F1. Top: methylation of promoter regions for metabolic genes in F0 spermatozoa. Data indicate a significant increase in methylation of OGT, Ptpn1, and H19 in F0 mice, whereas the methylation level of OGA decreased after the fathers’ long-term exercise, in comparison to methylation level in sedentary control fathers. Bottom: methylation of promoter regions for metabolic genes in F1 spermatozoa. Data are means ± se. Student’s t test (n = 3). *P < 0.05, **P < 0.01 vs. CFO.

Long-term exercise affects sperm miRNA content

Several lines of evidence suggest that transgenerational programming involves altered miRNA content in germ cells (25, 26). In this study, sperm miRNA content was assessed on total RNA isolated from epididymal sperm collected from exercised and sedentary male mice. Equal concentrations of total RNA from 3 individual sperm samples were used to produce 3 RNA pools per group. The real-time RT-PCR reactions were performed in triplicate for each sample with miR-191 as the internal control. All experiments were performed 3 times independently. The experiments revealed differential expression of metabolic miRNAs in response to previous paternal experiences (Fig. 7). Significantly changed genes include miR-483-3p, located within the Igf2 locus of the imprinted Igf2/H19 genes, and up-regulated in adipose tissue from low-birth-weight adult humans and prediabetic adult rats (27); miR-431, neuronal miRNA that regulates Wnt signaling (28); miR-221, involved in adipocyte differentiation and obesity (29); and miR-21, involved in a plethora of biologic functions and diseases, including development, cancer, cardiovascular diseases, and inflammation (30). These findings suggest that identified metabolic miRNAs are involved in developmental processes that underlie epigenetic reprogramming of the metabolic phenotype.

Figure 7.

Long-term exercise-induced changes in F0 spermatozoal miRNA content. Data indicate a significant increase in miR-483-3p, -431, and -21, whereas the expression level of miR-221 decreased after a month of constant exercise in comparison to expression of these miRNAs in sedentary control samples, taken as 100% (n = 3). miRNA expression was normalized to reference miR-191. Data are means ± se. Student’s t test. *P < 0.05.

DISCUSSION

Although diet-induced epigenetic reprogramming via paternal lineage has recently received much attention in the literature, the effect of paternal physical activity on offspring metabolism has not been adequately addressed. National statistics demonstrate that level of physical activity is a critical factor that contributes to the spread of the obesity epidemic. Conversely, regular physical activity has been shown to reduce the risk for obesity and type 2 diabetes (31), cardiovascular diseases (32), cancers (33), and depression (34). Skeletal muscle has been identified as a major secretory organ, which exerts autocrine, paracrine, and endocrine signals, and communicates with other organs, such as adipose tissue, liver, pancreas, bone, and brain (35). Although acute physical activity has been shown to change DNA methylation in skeletal muscle (36), to date, there have been no systematic studies investigating exercise-induced long-term epigenetic reprogramming. In the current study we investigated the effects of long-term free wheel-running on the metabolic phenotype of offspring and on exercise-induced epigenetic alterations in male germ cells. Our data showed that offspring whose fathers were exposed to a long-term exercise regimen were more metabolically efficient. As a result, these offspring exhibited lower EE and an increased risk of obesity and insulin resistance on a high-fat diet. This manifested in increased body weight and adiposity, impaired glucose tolerance, and higher insulin levels. A recent study showed similar effects of parental long-term exercise on offspring metabolic phenotype (13). In particular, the investigators reported offspring from mice that were exercised constantly had higher serum insulin and impaired glucose tolerance compared with offspring from sedentary animals. In addition, analysis of skeletal muscle mRNA levels revealed several generational- and sex-specific differences in mRNA levels for multiple metabolic genes, including levels of Hk2, Ppard, Ppargc1a, Adipoq, and Scd1 (13). In our experiments, we observed altered expression of several metabolic genes in skeletal muscle of offspring, including Pdk4, Slc2a, H19, Ptpn1, Ogt, and Oga. In addition, analyses of paternal sperm revealed a differential methylation pattern for H19, Ptpn1, Ogt, and Oga. We observed 3.7-fold relative increase in H19 methylation in the H19 imprinting control region incorporating CCCTC-binding factor (CTCF)-4 binding site, because the binding site was hypomethylated in control animals and hypermethylated in exercise. The finding is not entirely surprising, as it has been shown that the mouse sperm promoter region of H19 may have hypomethylation in certain parts (37). In addition, we found that prolonged exercise altered spermatozoal miRNA content. Of particular interest was the increase in miR-483-3p. This miRNA is encoded by the locus of the imprinted Igf2/H19 cis-regulatory genes and is up-regulated in adipose tissue from low-birth-weight adult humans and prediabetic adult rats (27). The observed epigenetic modification of metabolic genes and miRNAs indicates that paternal long-term exercise alters offspring metabolic phenotype, in part by affecting the offspring epigenome.

The effect of paternal lifestyle and environmental exposures on spermatogenesis and germ cells is supported by observed declines in sperm concentration, motility, and morphology in men engaged in constant physical exercise (38). Possible mechanisms affecting male reproductive function include changes in the hypothalamus–pituitary–testis (HPT) axis (39), oxidative stress (40), increased formation of ROS (41), and DNA damage (reviewed in 42). These processes are likely to impact DNA methylation (43), histone modifications (44), and miRNA levels (45) in male germ cells, which can result in transmission of acquired traits to offspring (Fig. 8). Multiple classes of small noncoding RNAs have been recently detected in human and mouse spermatozoa which supports their suspected roles as modifiers of postfertilization processes (26, 46, 47). There is mounting evidence that sperm-borne miRNAs play a critical role in nonmendelian inheritance of epigenetic traits (48) and first cleavage divisions (26). Specific miRNAs identified in the spermatozoal of bulls were linked to different fertility phenotypes of offspring (49). Recently, environmental factors such as pollution and smoking have been shown to induce significant changes in human spermatozoal miRNAs (50, 51), whereas paternal obesity has been linked to altered mouse sperm miRNA content (52). In addition, recent observations have directly implicated spermatozoal miRNA as a material carrier of epigenetic information passed to offspring (53). The authors showed that, injection of sperm miRNAs from behaviorally traumatized fathers into wild-type oocytes produced negative behavioral and metabolic alterations in the resulting offspring (25). Based on the literature and our own observations, we hypothesize that paternal experiences change the level of the miRNAs in spermatozoa via HPT axis. The spermatozoal miRNAs are delivered to ovum during fertilization and affect embryonic developmental programs by targeting developmental genes. The top-predicted target of the miRNAs detected by Rodgers et al. (53) in paternal sperm was DNA methyltransferase 3a (DNMT3a), a crucial regulator of de novo DNA methylation of imprinted genes. Therefore, spermatozoal miRNAs can also alter early embryonic development by affecting the gene methylation pattern. Thus, environmental changes, while leaving the DNA sequence unchanged, can affect the next generation via miRNAs that regulate gene expression. Evolutionarily, this process may be a novel mechanism of changing offspring phenotypic features in response to environmental challenges experienced by fathers. In theory, this mechanism may increase phenotypic variability in a population during geological changes and accelerate speciogenesis. Two of the most intriguing questions that come from transgenerational studies are why the phenotypic changes in offspring are often directional or of the same modality as changes in parental phenome and what molecular and physiologic mechanisms guide those processes. Further studies into mechanisms of genome and epigenome interactions during gametogenesis should yield important insights into the molecular control of transgenerational epigenetic programming. The limitation of this study is that it was focused on F1 generation.

Figure 8.

The complex epigenetic factors that may contribute to the transgenerational effect of long-term exercise on offspring metabolic phenotype. Long-term exercise may affect metabolism and the HPT axis in F0 mice, leading to epimutations during spermatogenesis. The epimutations are likely to include DNA methylation, histone modifications, and noncoding RNAs in male germ cells, which can result in transmission of novel traits to offspring.

In conclusion, our data demonstrate that long-term free wheel-running of male mice programmed their offspring for thrifty phenotype. To our knowledge, this is the first direct demonstration that paternal exercise can induce generational transmission of metabolic traits to the offspring. These findings suggest that offspring have phenotype programmed to thrive under the same environmental conditions as their respective fathers. Evolutionarily, epigenetic programming may help offspring to adapt to changes in the environment experienced by their ancestors. Although it is not yet clear whether similar effects are observable in human populations, it has been reported that lower EE might contribute to both higher athletic capability and prevalence of obesity in an ethnic-specific manner (14, 54). The reason for this difference is not clear, but may relate to both genetic and epigenetic inheritance of metabolic traits, in particular, insulin responsiveness. Together, these results suggest that parental physical activity level is a critical epigenetic factor in epidemiological and transgenerational studies of obesity and metabolic and cardiovascular diseases in humans.

Glossary

AUC

area under the curve

CF

control father

CFO

control father offspring

CpG

cytosine-phosphate-guanine

CTCF

CCCTC-binding factor

EF

exercise father

EFO

exercise father offspring

FoxO1

forkhead box protein O1

Glut4

glucose transporter 4

GTT

glucose tolerance test

H19

imprinted maternally expressed transcript (non-protein coding)

HPT

hypothalamus-pituitary-testis

Ins2

insulin 2

miR/miRNA

micro-RNA

MRI

magnetic resonance image/imaging

Oga

O-GlcNAcase

O-GlcNAc

O-linked β-d-N-acetylglucosamine

Ogt

O-GlcNAc transferase

Pdk

pyruvate dehydrogenase kinase 4

Ptpn1

protein tyrosine phosphatase 1

qPCR

quantitative PCR

Slc2a4

solute carrier family 2 a4