Science and Research

Machine Learning Analysis of the Bleomycin Mouse Model Reveals the Compartmental and Temporal Inflammatory Pulmonary Fingerprint

The bleomycin mouse model is the extensively used model to study pulmonary fibrosis; however, the inflammatory cell kinetics and their compartmentalization is still incompletely understood. Here we assembled historical flow cytometry data, totaling 303 samples and 16 inflammatory-cell populations, and applied advanced data modeling 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. Multicolour imaging revealed the spatial-temporal cell distribution and the close association of T cells with deposited collagen. Unbiased immunophenotyping and data modeling exposed the dynamic shifts in immune-cell composition over the course of bleomycin-triggered lung injury. These results and workflow provide a reference point for future investigations and can easily be applied in the analysis of other datasets.

  • Bordag, N.
  • Biasin, V.
  • Schnoegl, D.
  • Valzano, F.
  • Jandl, K.
  • Nagy, B. M.
  • Sharma, N.
  • Wygrecka, M.
  • Kwapiszewska, G.
  • Marsh, L. M.

Keywords

  • Artificial Intelligence
  • Immune Response
  • Immunology
Publication details
DOI: 10.1016/j.isci.2020.101819
Journal: iScience
Pages: 101819 
Number: 12
Work Type: Original
Location: UGMLC
Disease Area: General Lung and Other
Partner / Member: UMR
Access-Number: 33319168

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