The bleomycin mouse-model is the extensively used model to study pulmonary fibrosis, however, the inflammatory cell kinetics and their compartmentalisation is still incompletely understood. Here we assembled historical flow cytometry data, totalling 303 samples and 16 inflammatory-cell populations, and applied advanced data modelling and machine learning methods to conclusively detail these kinetics. Three days post-bleomycin, the inflammatory profile was typified by acute innate inflammation, pronounced neutrophilia, especially of SiglecF+ neutrophils, and alveolar macrophage loss. Between 14 and 21 days, rapid-responders were increasingly replaced by T and B cells, and monocyte-derived alveolar macrophages. Multi-colour imaging revealed the spatial-temporal cell distribution and the close association of T cells with deposited collagen. Unbiased immunophenotyping and data modelling exposed the dynamic shifts in immune-cell composition over the course of bleomycin-triggered lung injury. These results and workflow provides a reference point for future investigations, and can easily be applied in the analysis of other datasets.

中文翻译：

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博来霉素-小鼠模型的机器学习分析揭示了房室和颞部炎性肺部指纹

博来霉素小鼠模型是研究肺纤维化的广泛使用的模型，但是，对炎症细胞动力学及其区室化的理解仍不完全。在这里，我们汇总了历史流式细胞仪数据，总共303个样本和16个炎症细胞群体，并应用了先进的数据建模和机器学习方法来详尽地详细说明这些动力学。博来霉素三天后，炎症特征为急性先天性炎症，明显的中性粒细胞增多，特别是SiglecF +中性粒细胞，以及肺泡巨噬细胞丢失。在14到21天之间，快速反应者越来越多地被T细胞和B细胞以及单核细胞衍生的肺泡巨噬细胞所取代。多色成像显示时空细胞分布以及T细胞与沉积胶原蛋白的紧密联系。无偏倚的免疫表型和数据建模揭示了博来霉素触发的肺损伤过程中免疫细胞组成的动态变化。这些结果和工作流为将来的调查提供了参考点，并且可以轻松地应用于其他数据集的分析。