PROJECT SUMMARY Our goal in this proposal is to identify biological networks involved in synchronizing placental growth and maturity. To accomplish this goal, we have established a collaborative effort between the Center for Prevention of Preterm Birth at Cincinnati Children’s Hospital Medical Center (CCHMC) and the Institute for Systems Biology (ISB) in Seattle to conduct a systems level analysis of “omics” data. Perturbed growth and maturity can lead to placental insufficiency, which underlies a significant proportion of adverse pregnancy outcomes, such as preterm birth. A paucity of knowledge regarding normal placental development and maturity greatly hinders any study of placental insufficiency. Placental growth and development occurs throughout gestation and reaches maturity at term. Therefore, it is critical to identify the networks involved and to assess them over the length of gestation. Our central hypothesis is that key biological networks vital to placental growth and maturity can be identified through the intersection of transcriptomic, proteomic, and metabolomics data from term and preterm placentae. Furthermore, utilizing longitudinal proteomics and metabolomics data, we can determine how those pathways change over gestation and differ between normal and preterm placentae. We will test this hypothesis through the following aims: Aim 1: Identification of key gene and metabolite signatures involved in placental development by analyzing longitudinal “omics” data. Using publically available transcriptomic data, we will generate a molecular profile of expressed genes in placental development throughout gestation. We will also determine the placental secretome and identify biomarker signatures that appear in maternal urine that reflect placental maturation. Aim 2: Identification of molecular pathways associated with placental maturity. We will utilize network topology algorithms to identify changes in molecular pathways in preterm and term placentae. These data will be combined with publically available data to identify molecular pathways and genes within those pathways that differ between term and preterm placentae to provide insight into placental maturity. Aim 3: Generation of a placenta-specific transcriptional network for identifying regulatory mechanisms involved in placental maturity. We will construct genome-scale, tissue specific models of placental transcriptional regulatory networks using our newly-developed Transcriptional Regulatory Network Analysis (TRENA) approach, which leverages a wealth of information from the NIH’s ENCODE project. We will characterize which transcriptional regulators are most likely responsible for perturbed gene expression, their signaling pathways and downstream tar...