Formula feeding alters hepatic gene expression signature, iron and cholesterol homeostasis in the neonatal pig

Abstract

In the U.S. formula feeding remains more popular than breast-feeding. In the current study, neonatal piglets were breast fed and compared with those fed commercially available milk-based formula (milk) or soy-based formula (soy) from postnatal day 2 (PND2) until death at PND21 (the usual age of weaning). Liver weights were greater in formula-fed piglets (P<0.05) than in breast-fed piglets (P<0.05). Affymetrix array analysis revealed significant differences in hepatic gene expression signatures between piglets fed breast milk or formula, as well as between piglets fed milk or soy. In males, expression of 346 hepatic genes differed between formula-fed and breast-fed piglets, and soy-fed differed from milk-fed piglets in 277 genes. Furthermore, gene expression profiles of males differed from females, even when the same diet was consumed. Serum cholesterol was lower in piglets fed formula relative to breast-fed piglets (P<0.05), and this was associated with elevations in mRNA encoding cholesterol 7α-hydroxylase (CYP7A1). Consistent with the human literature, breast-fed piglets had lower hepatic iron accumulation than formula-fed piglets. Hepcidin, a major regulator of hepatic iron trafficking, was elevated in piglets fed formula relative to breast-fed piglets (P<0.05). Female piglets fed soy formula had increased expression of CYP3A enzymes (P<0.05), and soy formula feeding decreased expression of several hepatic genes considered estrogen inducible. These data suggest that: 1) gene expression profiles in neonates differ significantly depending on the diet consumed, 2) hepatic iron storage and cholesterol metabolism clearly differ between breast and formula feeding in piglets, 3) there is no evidence that soy is estrogenic in neonatal pig liver.

Female mice lacking p47phoxhave altered adipose tissue gene expression and are protected against high fat-induced obesity

“…The intensity values of different probe sets (genes) generated by Affymetrix GeneChip Software were imported into GeneSpring version 11.5 software (Agilent Technologies, Santa Clara, CA) for data analysis. The data files (CEL files) containing the probe level intensities were processed using the robust multiarray average algorithm, for background correction, log2-transformation, and quantile normalization of the perfect match probe level values (30,31). For comparison analysis, genes were filtered based on minimum 1.5-fold ratio change and P value Յ 0.05 using Student's t-test followed by Benjamini and Hochberg false discovery rate.…”

“…Visualization of data was accomplished using GeneSpring GX v11.0.2. Known biological functions of genes were queried and acquired from Affymetrix online data analysis resource NetAffx and gene ontology (GO) analyses performed using Affymetrix GO Browser (31). Analysis of genes mapped to biological pathways was conducted using Affymetrix NetAffx and GO analysis for biological/ molecular function performed using GeneSpring using false discovery rate of P Ͻ 0.1 (default for Gene Spring) (31).…”

“…Known biological functions of genes were queried and acquired from Affymetrix online data analysis resource NetAffx and gene ontology (GO) analyses performed using Affymetrix GO Browser (31). Analysis of genes mapped to biological pathways was conducted using Affymetrix NetAffx and GO analysis for biological/ molecular function performed using GeneSpring using false discovery rate of P Ͻ 0.1 (default for Gene Spring) (31). Furthermore, the lists of genes with significantly different expression in fat pads from WT AIN-93G vs. P47KO AIN-93G mice, WT AIN-93G vs. WT HFD, P47KO AIN-93G vs. P47KO HFD, and WT HFD vs. P47KO HFD were analyzed using DAVID to perform functional annotation.…”

“…Furthermore, the lists of genes with significantly different expression in fat pads from WT AIN-93G vs. P47KO AIN-93G mice, WT AIN-93G vs. WT HFD, P47KO AIN-93G vs. P47KO HFD, and WT HFD vs. P47KO HFD were analyzed using DAVID to perform functional annotation. This analysis included identifying top interacting networks based on gene databases from the known literature as described previously for other mRNA data sets (31). Confirmation of microarray gene expression data was done by real-time RT-PCR.…”

“…Western blots of whole tissue homogenates were utilized to confirm effects of P47 phox genotype and HFD feeding on mRNAs at the level of protein expression. PPAR␥ and CD36 protein expression was determined in female mouse adipose tissue using gonadal fat pads and methods previously described (31,38). Expression of lipoprotein lipase (LPL) protein was analyzed in gonadal fat pads using a monoclonal antibody from Abcam (ab21356).…”