Transcriptional variation in human milk

PROJECT SUMMARY The Centers for Disease Control recommends breastfeeding for the first six months of an infant’s life due to significant long term health benefits for the infant and breastfeeding parent. Beyond meeting the nutritional needs of the infant, human milk is a dynamic fluid with composition that changes to meet the needs of the infant as it develops and bioactive components which provide protective immunity to the infant. However, much is still unknown about the cells in the mammary gland which produce these prized components of human milk. Currently, there are no FDA approved interventions known to boost milk production, so the 60-70% of parents who struggle to lactate are left with little support to improve lactation outcomes and set infants up for the long- term health benefits of breastfeeding. Recent studies using single cell RNA-sequencing (scRNA-seq) of the mammary gland cells exfoliated into human milk have begun to characterize the cells that produce this dynamic substance with the ultimate goal of improving understanding of the factors impacting milk production at a cellular level. Still, the transcriptional pathways involved in milk production as well as the way these pathways change as a result of maternal and infant factors remains poorly understood. This proposal will utilize existing data generated from human milk to improve the understanding of transcriptional basis of milk production by (1) using integrative analysis of existing scRNA-seq data to identify shared transcriptional pathways of lactation, (2) developing statistical models to expose genes and pathways that change in milk in concordance with maternal and infant characteristics, COVID-19 infection and vaccination, antibody concentrations, and human milk oligosaccharide concentration, and (3) apply these and other models to understand the changes in the mammary gland and milk composition as a result of COVID-19 infection and vaccination. This improved characterization of milk production will lead to future studies on interventions to improve lactation outcomes and immune protection from human milk. Research will take place at the Gladstone Institute of Data Science and Biotechnology, a highly collaborative research institution with a commitment to postdoctoral training. The trainee with receive training in statistical analysis and method development, lactation biology, immunology, and responsible conduct of research from an interdisciplinary and multi-institutional team of mentors and collaborators. The training plan will prepare the trainee for an independent career as a computational biologist studying lactation and maternal and infant health.