Effects of sustained hyperprolactinemia in late gestation on the mammary parenchymal tissue transcriptome of gilts

Abstract

Background: Gilts experiencing sustained hyperprolactinemia from d 90 to 109 of gestation showed an early onset of lactogenesis coupled with premature mammary involution. To better understand the molecular mechanisms underlying the premature mammary involution observed in these gilts, a transcriptomic analysis was undertaken. Therefore, this study aimed to explore the effect of hyperprolactinemia on the global transcriptome in the mammary tissue of late gestating gilts and identify the molecular pathways involved in triggering premature mammary involution.

Methods: On d 90 of gestation, gilts received daily injections of (1) canola oil until d 109 ± 1 of gestation (CTL, n = 18); (2) domperidone (to induce hyperprolactinemia) until d 96 ± 1 of gestation (T7, n = 17) or; (3) domperidone (until d 109 ± 1 of gestation (T20, n = 17). Mammary tissue was collected on d 110 of gestation and total RNA was isolated from six CTL and six T20 gilts for microarray analysis. The GeneChip® Porcine Gene 1.0 ST Array was used for hybridization. Functional enrichment analyses were performed to explore the biological significance of differentially expressed genes, using the DAVID bioinformatics resource.

Results: The expression of 335 genes was up-regulated and that of 505 genes down-regulated in the mammary tissue of T20 vs CTL gilts. Biological process GO terms and KEGG pathways enriched in T20 vs CTL gilts reflected the concurrent premature lactogenesis and mammary involution. When looking at individual genes, it appears that mammary cells from T20 gilts can simultaneously upregulate the transcription of milk proteins such as WAP, CSN1S2 and LALBA, and genes triggering mammary involution such as STAT3, OSMR and IL6R. The down-regulation of PRLR expression and up-regulation of genes known to inactivate the JAK-STAT5 pathway (CISH, PTPN6) suggest the presence of a negative feedback loop trying to counteract the effects of hyperprolactinemia.

Conclusions: Genes and pathways identified in this study suggest that sustained hyperprolactinemia during late-pregnancy, in the absence of suckling piglets, sends conflicting pro-survival and cell death signals to mammary epithelial cells. Reception of these signals results in a mammary gland that can simultaneously synthesize milk proteins and initiate mammary involution.

Keywords: Domperidone; Gestation; Gilt; Mammary gland; Prolactin; Transcriptomic.

Fig. 1

Heatmap with hierarchical clustering of differentially expressed genes between T20 and CTL gilts. Heat map with hierarchical clustering of the top 50 genes with the most significant differences based on their adjusted P-values. Each row represents one of the 50 genes and each column one of the 12 samples (6 T20 and 6 CTL gilts) used in microarray analysis. The dendrogram at the top demonstrates similarity among samples, whereas the one on the left shows clusters of genes based on their similar gene expression pattern. Red = positive log fold-change (log FC); Blue = negative log FC

Fig. 2

STRING-generated interaction network among selected enriched KEGG pathways. The network image shows interactions between proteins encoded by DEGs identified in the following KEGG molecular pathways: PI3K-Akt signaling pathway (ssc04151), prolactin signaling pathway (ssc04917), JAK-STAT signaling pathway (ssc04630), protein processing in endoplasmic reticulum (ssc04141) and phagosome (ssc04145). Clusters of genes/proteins within specific KEGG pathways are indicated in boxes and by corresponding colored nodes in the network image. Bold = up-regulated genes; Plain text = down-regulated genes in T20 vs CTL gilts. The thickness of the lines represents the confidence prediction of the interaction between 2 genes (thinnest: confidence 0.400; medium: confidence 0.700; thickest: confidence 0.900). Nodes with no interaction with other nodes were deleted. The interaction score was set at > 0.400 and KEGG pathway enrichment significance at P > 0.05 (FDR Benjamini-Hochberg)

Fig. 3

Schematic representation of transcriptomic adaptations and molecular pathways involved in triggering premature mammary involution in gilts that experienced sustained hyperprolactinemia from d 90 to 109 of gestation. Injections of the dopamine receptor antagonist domperidone from d 90 to 109 of gestation provoked sustained hyperprolactinemia. Upon binding to its receptor (PRLR), PRL activates the JAK2-STAT5 signaling pathway, which then induces the transcription of milk proteins such as WAP, CSN1S2 and LALBA. STAT5 can also induce the transcription of AKT and P85, two proteins that are part of the PI3k-AKT signaling pathway. In the absence of milk removal, the JAK1-STAT3 signaling pathway is activated leading to programmed cell death. In the first phase of mammary involution, the lysosomal cell death is mediated through the LIFR-JAK1-STAT3 signaling pathway. In the second phase, oncostatin M and its receptor (OSMR) mediate the apoptotic cell death. The up-regulation of FOXO1 is known to induce cellular apoptosis. The downregulation of PRLR transcript and the increased expression of PTPN6 and CISH suggest a negative feedback loop to reduce the activation of the PRLR-JAK2-STAT5 signaling pathway. The upregulation of PPP2R3A and downregulation of HSP90AB1 may inactivate the PI3K-Akt signaling pathway. The up-regulation of S100A12, LTF, TLR2, TLR4, MYD88, CXCL2, CXCL8 and CCL23 transcripts suggests an activation of the TLR-NF-κB signaling pathway. The up-regulation of CXCL2, CXCL8 and CCL23 chemokines, as well as the IL2, IL6 and TNF receptors may induce the infiltration of neutrophils and professional phagocytes (macrophages) in the involuting mammary glands. Differentially expressed genes are indicated in yellow boxes with up-regulated genes in bold character and down-regulated genes in plain text. AKT: AKT serine/threonine kinase; BIM/BCL2L11: BCL2 like 11; CCL2: C-C motif chemokine ligand 2; CCND1: cyclin D1; CIDEA: cell death inducing DFFA like effector A; CISH: cytokine inducible SH2 containing protein; CSN1S2: alpha(s2)-casein; gp130: glycoprotein 130; CTSC: cathepsin C; CTSH: cathepsin H; CXCL2: C-X-C motif chemokine ligand 2; CXCL8: C-X-C motif chemokine ligand 8; FASL: fas ligand; FOS: Fos proto-oncogene, AP1 transcription factor subunit; FOXO1: forkhead box O1; HSP90AB1: heat shock protein 90 alpha family class B member 1; IKBα: NFKB inhibitor alpha; IKKβ: inhibitor of nuclear factor kappa B kinase subunit beta; IL2: interleukin 2; IL2RG: interleukin 2 receptor subunit gamma; IL6: interleukin 6; IL6R: interleukin 6 receptor; IRAK: interleukin 1 receptor associated kinase; JAK1: janus kinase 1; JAK2, janus kinase 2; LALBA: lactalbumin alpha; LIFR: LIF receptor subunit alpha; LITAF: LPS induced TNF factor; LTF: lactotransferrin; MCL1: MCL1 apoptosis regulator, BCL2 family member; MYC: MYC proto-oncogene, BHLH transcription factor; MYD88: MYD88 innate immune signal transduction adaptor; NEMO/IKBKG: inhibitor of nuclear factor kappa B kinase regulatory subunit gamma; NF-κB: nuclear factor kappa B; OSMR: oncostatin M receptor; P85: phosphoinositide-3-kinase regulatory subunit 1; PI3K: phosphoinositide-3-kinase; PPP2R3A: protein phosphatase 2 regulatory subunit B alpha; PRL: prolactin; PRLR: prolactin receptor; PTPN6: protein tyrosine phosphatase non-receptor type 6; S100A12: S100 calcium binding protein A12; STAT3: signal transducer and activator of transcription 3; STAT5: signal transducer and activator of transcription 5; STING1: stimulator of interferon response CGAMP interactor 1; TAK1/MAP 3 K7: mitogen-activated kinase kinase kinase 7; TIRAP: TIR domain containing adaptor protein; TLR2: toll like receptor 2; TLR4: toll like receptor 4; TNF: tumor necrosis factor; TNFRSF17: TNF receptor superfamily member 17; TRAF6: TNF receptor associated factor 6; WAP: whey acid protein