106 The Effects of Fetal Programming on Offspring Pancreas DNA Methylation

It has been well documented that fetal programming, caused by changes to the maternal environment during pregnancy, can impact the overall health and growth of the offspring in livestock and non-livestock species alike. These effects are observed in the F1 offspring as well as across subsequent generations; however, the mechanisms by which this occurs are still poorly understood. Epigenetics is one of the many mechanisms that is hypothesized to have a role in fetal programming and may be mediating the observed effects across multiple generations. It has been demonstrated by others that DNA methylation patterns can be altered by an individuals’ diet and that the pancreas is vulnerable to the effects of fetal programming. Therefore, we evaluated the effects of poor maternal nutrition during gestation on the pancreas tissue of lambs. We have demonstrated that maternal under- or overnutrition during gestation alters the DNA methylation patterns of the offspring pancreas tissue with these effects being diet dependent and sex specific. We have also begun evaluating the effects of maternal diet in murine models using whole-genome bisulfite sequencing to compare species differences and determine if there are any changes conserved across species. This will allow us to focus on a smaller number of critical factors in individuals as they age and across multiple generations in livestock species such as sheep and cattle. From these data we will be able to elucidate the role DNA methylation has in mediating the effects of maternal programming in the pancreas tissue.

PSV-10 The effects of maternal programming on postnatal growth and inflammation in neonatal dairy bull calves

Neonatal dairy calves are highly susceptible to respiratory and digestive diseases. A mechanism that could be predisposing calves to disease is maternal programming. We hypothesized that high milk production and/or mastitis infection during gestation will 1) affect postnatal growth and development 2) cause increased inflammation in neonatal dairy bull calves. Calves (n = 45) were selected from dams classified has high producers (HI; Top 25% for herd M305; n = 7), high producers with high SCC (HIMAST; SCC test during pregnancy over 200,000 cells/mL; n = 15), moderate producers (MOD; lower 60% for herd M305; n = 17) or moderate producers with high SCC (MODMAST; n = 6). Calves were transported to the University of Rhode Island at 24 hrs of age. Body weights and body measurements (crown rump length (CRL), skull length (SL), skull width (SW), Girth, Height) were collected at 24 hrs (Initial) and at weaning (8 weeks). C-reactive protein (Abclonal, Woburn, MA) and Malondialdehyde (Abcam, Cambridge, MA) analyses were performed on plasma samples collected 72 hrs post travel. Data were analyzed in SAS using repeated measures (BW and growth measurements) and proc mixed (inflammatory biomarkers). As expected, an effect of time was observed on calf BW, CRL, SL, SW, Girth and Height (P ≤ 0.01). However, no difference in calf BW, CRL, SL, SW, Girth and Height were observed between groups (P>0.05). No effect of dam milk production and/or SCC during gestation was observed on CRP or MDA concentrations at 72 hrs post travel (P ≥ 0.17). In conclusion, high maternal milk production and/or mastitis infection during gestation does not affect calf BW and body measurements when analyzed overtime. Correlation analyses will be performed to better understand the relationship between maternal programming and calf growth. Additional inflammatory biomarkers are also going to be evaluated.

91 Maternal Programming of the Piglet Microbiome from Birth to Weaning

The objective of this study was to investigate seeding of the piglet microbiome, in the context of maternal programming in pre/perinatal environments. Maternal programming refers to maternal factors that predetermine offspring development and health. We hypothesized that increased sanitation level in maternal environments affects development of piglet fecal and nasal microbiomes, and physiological performance. Six sows were allocated randomly to two treatment groups: farrowing stalls cleaned with (D; n = 3) or without (ND; n = 3) disinfectant. Swabs were collected from stall floors, drinkers and feeders, and from sows’ vaginal, rectal, oral and udder surfaces at d109 of gestation and the day before farrowing. Fecal and nasal swabs were collected from piglets at days: 0 (within 24h of birth), 7, 14, and 21 postpartum. Nine piglets were selected randomly from each sow (n = 27/treatment) for microbiome analyses. DNA was extracted from swabs and the V4 variable region of the 16srRNA bacterial gene was sequenced on the MiSeq platform. Sequence data were analyzed using DADA2 and various packages within the R statistical software. Although environmental microbiomes were different between D and ND stalls (PERMANOVA, R2=0.474, P = 0.031) after cleaning, no compositional differences were detected among any D or ND sow samples. However, at d0, ND compared with D piglets exhibited higher gut (Shannon’s H, P = 9.131e-08) and nasal (P = 6.164e-08) alpha diversity. ND piglets also displayed greater nasal bacterial diversity at d21 (P = 0.036), and different gut (R2=0.06–0.129, P = 0.001) and nasal (R2=0.136–0.196, P = 0.001) microbiome compositions across all timepoints. However, D piglets exhibited higher average birth (P = 3.773e-05) and weaning weights (P = 5.803e-06) compared to ND piglets. These results indicate that sanitation level during farrowing persistently alters swine microbiomes and growth performance.

246 Maternal Programming of the Piglet Microbiome from Birth to Weaning

The objective of this study was to investigate seeding of the piglet microbiome, in the context of maternal programming in pre/perinatal environments. Maternal programming refers to maternal factors that predetermine offspring development and health. We hypothesized that increased sanitation level in maternal environments affects development of piglet fecal and nasal microbiomes, and physiological performance. Six sows were allocated randomly to two treatment groups: farrowing stalls cleaned with (D; n = 3) or without (ND; n = 3) disinfectant. Swabs were collected from stall floors, drinkers and feeders, and from sows’ vaginal, rectal, oral and udder surfaces at d109 of gestation and the day before farrowing. Fecal and nasal swabs were collected from piglets at days: 0 (within 24h of birth), 7, 14, and 21 postpartum. Nine piglets were selected randomly from each sow (n = 27/treatment) for microbiome analyses. DNA was extracted from swabs and the V4 variable region of the 16srRNA bacterial gene was sequenced on the MiSeq platform. Sequence data were analyzed using DADA2 and various packages within the R statistical software. Although environmental microbiomes were different between D and ND stalls (PERMANOVA, R2 = 0.474, P = 0.031) after cleaning, no compositional differences were detected among any D or ND sow samples. However, at d0, ND compared with D piglets exhibited higher gut (Shannon’s H, P = 9.131e-08) and nasal (P = 6.164e-08) alpha diversity. ND piglets also displayed greater nasal bacterial diversity at d21 (P = 0.036), and different gut (R2 = 0.06–0.129, P = 0.001) and nasal (R2 = 0.136–0.196, P = 0.001) microbiome compositions across all timepoints. However, D piglets exhibited higher average birth (P = 3.773e-05) and weaning weights (P = 5.803e-06) compared to ND piglets. These results indicate that sanitation level during farrowing persistently alters swine microbiomes and growth performance.