Preterm birth is a leading cause of neonatal morbidity and mortality, with intra-amniotic infection and inflammation being major contributors to early preterm labor (PTL). Despite ongoing research aimed at reducing inflammation in neonates, most studies have focused on post-delivery while few have been done prior to delivery. IL-1 is a central upstream mediator of inflammation in the amniotic cavity and the neonate. IL-1 is a key cytokine that is responsible for induction or propagation of the cytokine cascade responsible for PTL. Rytvela, an interleukin-1 receptor antagonist made up of seven D-amino acids, acts as a selective antagonist of IL-1 signaling, which could be used to act as a therapeutic approach to reduce inflammation and prevent PTL. The purpose of this experiment is to determine if interleukin-1 (IL-1) is a key molecular target for the development of antenatal therapeutics to prevent PTL and fetal injury. We hypothesize that Rytvela administered intravenously to the mother will cross the placenta and be detectable in the amniotic fluid and fetal plasma, suggesting that Rytvela could effectively block IL-1 signaling in the fetus and therefore reduce fetal inflammation. Maternal blood plasma samples were drawn at Day 1, 2, 6 and 10 post infusion. To confirm the transfer of Rytvela to the fetus, we used liquid chromatography-mass spectrometry (LC-MS) to detect the drug, looking at integration, peak identification, and backlog pressures to see if Rytvela is detectable in maternal plasma. Rytvela was detected and luminex plates were run to measure cytokine levels. After GBS infection, Il-1 beta and Il-23 concentrations increased. After Rytvela administration, the concentration of the pro-inflammatory cytokines decreased. Future directions will involve measuring cytokine levels at these time points and correlating them with Rytvela infusion to evaluate the drug’s impact on maternal-fetal inflammation

Pregnant women infected with influenza A virus (IAV) are at higher risk of morbidity, mortality, and poor fetal outcomes. However, the difference in the pathogenesis of IAV between pregnant women and non-pregnant women remains inadequately understood, primarily due to the lack of animal studies that use a translational model of infection. I hypothesized that higher IAV viral load and Type I interferon concentrations would be observed in the lungs and bronchoalveolar lavage of pregnant pig-tail macaques compared to non-pregnant macaques, and that correlating these metrics would yield different results across groups. We inoculated pregnant (n=11) and non-pregnant female (n=18) pig-tail macaques (Macaca nemestrina) with IAV H1N1 (A/California/07/2009) and euthanized them at 5 days post-inoculation, when we expected to observe peak lung pathology. We tested pulmonary function at baseline and study endpoint and conducted clinical assessments daily. I extracted RNA and performed quantitative polymerase chain reactions on the samples to calculate viral load. I also performed enzyme-linked immunosorbent assays to quantify concentrations of Type I interferons (IFN-α, IFN-β). Lastly, I analyzed pulmonary physiology data and clinical assessment scores as a reliable measure of disease severity. A bi-modal distribution of viral load was observed in the lungs of pregnant animals (high>9e5 copies/mg; low<2e4 copies/mg), which was not observed in non-pregnant animals.  When correlating viral load at 5 days post-inoculation with Type I IFN in the lung of the pregnant animals, I found a significant positive correlation between IFN-β and viral load in both the lungs (ρ=0.8, p=0.03) and BAL (ρ=0.9, p=0.02). These results suggest that despite a strong IFN-β response in the lung, a high viral load persisted in the pregnant animals. Next steps could explore whether the kinetics of the pulmonary innate immune response is delayed in pregnancy, which impairs viral clearance. 

Human gastrulation is the period of embryonic development during which a single-layered blastula develops the three germ layers, which give rise to all of the specialized cell types in our bodies. Differentiation of these layers is controlled by epigenetic factors, which chemically modify the DNA, therefore activating or repressing a gene’s activity. Very little is known about the role of epigenetic factors in human gastrulation, as it’s difficult to obtain samples at the proper time for study; samples from IVF are too early to study, and fetal samples are too developed. Despite these complications, it’s important to study gastrulation because it’s during this time that developmental disorders and loss of pregnancy can occur. My goal is to delete seven epigenetic factors and determine their role in human embryogenesis using a human pluripotent stem cell derived embryoid model (retinoic acid treated gastruloids). Using CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas9 technology, I plan to perform individual gene knockouts on our genes of interest in human embryonic stem cells. Next, we will generate mutant gastruloids from these knockout cell lines, and phenotype using single-cell RNA sequencing and fluorescent microscopy. From there, we can see how knocking out this gene affects gastruloid cell type composition and morphology. Using this strategy, our lab has successfully knocked out 60 genes. Given the strong phenotypes observed in null mutant mouse embryos for these genes, we expect to observe strong phenotypes from these seven epigenetic factors. With these findings, we can further understand the role of these epigenetic factors in development and disease. These findings can advance the progress of therapies and better understand our knowledge of human embryonic development as a whole.

Adenomyosis is a painful gynecological condition with a prevalence ranging from 20-35% in symptomatic patients. Current detection methods, ultrasonography and magnetic resonance imaging, are suboptimal and definitive diagnosis frequently relies on hysterectomy, prompting more research for less invasive diagnostic tests, which is the aim of this study. We enrolled 108 women undergoing hysterectomies, after post-operative histopathology diagnosed women with adenomyosis (n=46) and other benign conditions (n=62). Cervicovaginal lavage (CVL) and vaginal swab samples were collected. CVLs were used for global metabolomic data, as well as immunoproteomic profiling. We conducted 16s rRNA microbiome profiling on vaginal swabs. The integration of datasets was performed using MetaboAnalyst and MetOrigin. No significant differences were found in body mass index, menopausal status, co-occurring conditions, and parity between patient groups. Pathway enrichment analysis revealed co-metabolic pathways pyrimidine metabolism, D-amino acid metabolism, arginine and proline metabolism, and histidine metabolism as the most enriched in the adenomyosis group. Using least absolute shrinkage and selection operator (LASSO) for biomarker selection, multivariate receiver operating characteristic (ROC) analysis revealed that a model based on metabolomics dataset has an area under the curve (AUC) of 0.852, predictive accuracy (PA) of 77%, and Youden's Index (J) of 0.607. Compared to immunoproteomics and microbiome models, which had a PA of 68.8% and 66.5%, respectively, combining metabolomics with immunoproteomics resulted in an improved PA of 74.8%, while combining metabolomics with microbiome led to a PA of 74.3%, both outperforming their individual counterparts. Three-omics integration in a multivariate model resulted in an AUC of 0.859, PA of 77.4%, and J of 0.624, with metabolites being the top predictive features in the model. Our study identified that global metabolomics is the best single omics predictor of adenomyosis. Multi-omics integration increases performance metrics. Overall, this study identified key metabolic biomarkers for diagnostic development and assessment in future studies. 

Pregnancy represents a state of "immunological paradox," where the maternal immune system supports a genetically and immunologically distinct fetus. This process requires precise and distinct immune regulation that changes throughout the different trimesters of pregnancy. Placental immune cells such as T-cells, macrophages, and natural killer cells play a crucial role in supporting fetal development as well as promoting maternal tolerance. However, while the immune functions of immune cells are well studied, the metabolic pathways that drive their activity during pregnancy remain unknown. Given that function is tightly linked to metabolism, understanding how placental immune cells produce energy throughout pregnancy is essential for uncovering key mechanisms of maternal-fetal immunology. This project aims to investigate the immunometabolic profiles of placental immune cells across trimesters using SCENITH (Single-cell Metabolism by Profiling Translation Inhibition), a method to study metabolic profiles in single cells paired with flow cytometry. By analyzing placental immune cells from first, second, and third-trimester placental samples, we will assess their reliance on glycolysis, oxidative phosphorylation, and other metabolic pathways. We hypothesize that placental immune cells undergo trimester-specific metabolic adaptions. By mapping these metabolic profiles, our research seeks to provide insights into immune function in normal pregnancy, as well as pregnancy disorders such as pre-eclampsia, preterm birth, or fetal growth restriction. By deepening our understanding of immune cells and their metabolic requirements during pregnancy, we could identify potential new therapies that can prevent these complications and pave a way for novel treatments to improve pregnancy outcomes and maternal health.