Quantitative Analysis of Cellular Composition in Advanced Atherosclerotic Lesions of Smooth Muscle Cell Lineage-Tracing Mice.

Quantitative Analysis of Cellular Composition in Advanced Atherosclerotic Lesions of Smooth Muscle Cell Lineage-Tracing Mice.
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DOI:
10.3791/59139
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发表时间:
2019-02
期刊:
Journal of visualized experiments : JoVE
影响因子:
--
通讯作者:
Sidney Mahan;Mingjun Liu;Richard A. Baylis;Delphine Gomez
Sidney Mahan;Mingjun Liu;Richard A. Baylis;Delphine Gomez
中科院分区:
其他
文献类型:
--
作者:
Sidney Mahan;Mingjun Liu;Richard A. Baylis;Delphine Gomez

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Atherosclerosis remains the leading cause of death worldwide and, despite countless preclinical studies describing promising therapeutic targets, novel interventions have remained elusive. This is likely due, in part, to a reliance on preclinical prevention models investigating the effects of genetic manipulations or pharmacological treatments on atherosclerosis development rather than the established disease. Also, results of these studies are often confounding because of the use of superficial lesion analyses and a lack of characterization of lesion cell populations. To help overcome these translational hurdles, we propose an increased reliance on intervention models that employ investigation of changes in cellular composition at a single cell level by immunofluorescent staining and confocal microscopy. To this end, we describe a protocol for testing a putative therapeutic agent in a murine intervention model including a systematic approach for animal dissection, embedding, sectioning, staining, and quantification of brachiocephalic artery lesions. In addition, due to the phenotypic diversity of cells within late-stage atherosclerotic lesions, we describe the importance of using cell-specific, inducible lineage tracing mouse systems and how this can be leveraged for unbiased characterization of atherosclerotic lesion cell populations. Together, these strategies may assist vascular biologists to more accurately model therapeutic interventions and analyze atherosclerotic disease and will hopefully translate into a higher rate of success in clinical trials.