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高参数蛋白质图谱揭示了早期人类肺部的空间组织。

High-parametric protein maps reveal the spatial organization in early-developing human lung.

机构信息

Science for Life Laboratory, Solna, Sweden.

Department of Protein Science, KTH-Royal Institute of Technology, Stockholm, Sweden.

出版信息

Nat Commun. 2024 Oct 30;15(1):9381. doi: 10.1038/s41467-024-53752-x.

Abstract

The respiratory system, including the lungs, is essential for terrestrial life. While recent research has advanced our understanding of lung development, much still relies on animal models and transcriptome analyses. In this study conducted within the Human Developmental Cell Atlas (HDCA) initiative, we describe the protein-level spatiotemporal organization of the lung during the first trimester of human gestation. Using high-parametric tissue imaging with a 30-plex antibody panel, we analyzed human lung samples from 6 to 13 post-conception weeks, generating data from over 2 million cells across five developmental timepoints. We present a resource detailing spatially resolved cell type composition of the developing human lung, including proliferative states, immune cell patterns, spatial arrangement traits, and their temporal evolution. This represents an extensive single-cell resolved protein-level examination of the developing human lung and provides a valuable resource for further research into the developmental roots of human respiratory health and disease.

摘要

呼吸系统包括肺,对陆地生命至关重要。尽管最近的研究提高了我们对肺发育的理解,但仍有许多依赖于动物模型和转录组分析。在人类发育细胞图谱(HDCA)计划内进行的这项研究中,我们描述了人类妊娠头三个月肺的蛋白质水平时空组织。使用具有 30 种抗体组合的高参数组织成像,我们分析了来自受孕后 6 至 13 周的人类肺样本,在五个发育时间点生成了来自超过 200 万个细胞的数据。我们提供了一个资源,详细描述了发育中人类肺的细胞类型组成,包括增殖状态、免疫细胞模式、空间排列特征及其时空演变。这代表了对发育中人类肺的单细胞水平的广泛蛋白质水平检查,并为进一步研究人类呼吸健康和疾病的发育根源提供了有价值的资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e925/11525936/79c3a2759e00/41467_2024_53752_Fig1_HTML.jpg

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