跨发育和疾病严重程度的急性新生儿肺损伤的空间转录组图谱。

IF 3.5 2区 医学 Q1 PHYSIOLOGY
Saahithi Mallapragada, Ruqian Lyu, Arianna L Williams-Katek, Brandon K Fischer, Annika Vannan, Niran Hadad, Evan D Mee, Shawyon P Shirazi, Christopher S Jetter, Nicholas M Negretti, Anne Hilgendorff, Laurie C Eldredge, Gail H Deutsch, Davis J McCarthy, Jonathan A Kropski, Jennifer M S Sucre, Nicholas E Banovich
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引用次数: 0

摘要

对肺器官发生的分子理解需要描述细胞转变的时间和调节,最终形成并支持能够气体交换的表面。虽然单细胞转录组学的出现已经允许发现和鉴定在肺发育过程中存在的转录不同的细胞群,但这些转录变化的时空动态仍然不明确。利用基于成像的空间转录组学,我们分析了17个处于不同发育和损伤阶段的人类婴儿肺部的基因表达模式,创建了约120万个细胞的空间转录组图谱。我们应用计算聚类方法来确定该队列中共享的分子模式,了解组织结构和分子空间关系如何在发育过程中协调并在疾病中中断。认识到所有早产都是对发育中的肺部的伤害,我们建立了一个简化的分类方案,该方案依赖于常规收集的胎龄和寿命的客观测量。在这个框架内,我们已经确定了在使用传统的“疾病与对照”二元比较时可能被忽视的胎龄和寿命变量的细胞类型模式。总之,这些数据代表了肺部研究界的一个开放资源,支持基于发现的调查和确定正常和停滞人类肺部发育的靶向分子机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
CiteScore
9.20
自引率
4.10%
发文量
146
审稿时长
2 months
期刊介绍: The American Journal of Physiology-Lung Cellular and Molecular Physiology publishes original research covering the broad scope of molecular, cellular, and integrative aspects of normal and abnormal function of cells and components of the respiratory system. Areas of interest include conducting airways, pulmonary circulation, lung endothelial and epithelial cells, the pleura, neuroendocrine and immunologic cells in the lung, neural cells involved in control of breathing, and cells of the diaphragm and thoracic muscles. The processes to be covered in the Journal include gas-exchange, metabolic control at the cellular level, intracellular signaling, gene expression, genomics, macromolecules and their turnover, cell-cell and cell-matrix interactions, cell motility, secretory mechanisms, membrane function, surfactant, matrix components, mucus and lining materials, lung defenses, macrophage function, transport of salt, water and protein, development and differentiation of the respiratory system, and response to the environment.
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