A spatial transcriptomic atlas of acute neonatal lung injury across development and disease severity

A molecular understanding of lung organogenesis requires delineation of the timing and regulation of the cellular transitions that ultimately form and support a surface capable of gas exchange. Although the advent of single-cell transcriptomics has allowed for the discovery and identification of transcriptionally distinct cell populations present during lung development, the spatiotemporal dynamics of these transcriptional shifts remain undefined. With imaging-based spatial transcriptomics, we analyzed the gene expression patterns in 17 human infant lungs at varying stages of development and injury, creating a spatial transcriptomic atlas of approximately 1.2 million cells. We applied computational clustering approaches to identify shared molecular patterns among this cohort, informing how tissue architecture and molecular spatial relationships are coordinated during development and disrupted in disease. Recognizing that all preterm birth represents an injury to the developing lung, we created a simplified classification scheme that relies upon the routinely collected objective measures of gestational age and lifespan. Within this framework, we have identified cell type patterns across gestational age and life span variables that would likely be overlooked when using the conventional "disease versus control" binary comparison. Together, these data represent an open resource for the lung research community, supporting discovery-based inquiry and identification of targetable molecular mechanisms in both normal and arrested human lung development.NEW & NOTEWORTHY Mapping the spatial and temporal transcriptional relationships during lung development is fundamental to understanding regeneration and chronic lung disease; however, the classification of samples as control or disease is especially challenging in the setting of preterm birth (itself a lung injury). Here, we report the largest neonatal lung transcriptomic atlas to date and an analysis framework based only on gestational age and lifespan, providing a new resource for hypothesis generation to the lung community.