Characterizing microglia activation: a spatial statistics approach to maximize information extraction.
Characterizing microglia activation: a spatial statistics approach to maximize information extraction.
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DOI：
10.1038/s41598-017-01747-8
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发表时间：
2017-05-08
影响因子：
4.6
通讯作者：
De Groef L
中科院分区：
文献类型：
--
作者：
Davis BM;Salinas-Navarro M;Cordeiro MF;Moons L;De Groef L
小胶质细胞在中枢神经系统疾病的病理学中起着重要作用，然而，由于缺乏技术来充分评估其对损伤的复杂行为，这些细胞的神经保护/变性作用仍然存在显著的不确定性。先进的显微镜技术，转基因品系和良好的分子标记，使小胶质细胞群体的组织学评估更容易。然而，明显缺乏从这些图像中充分提取信息以充分识别小胶质细胞行为的工具。这一点，再加上不断增长的经济压力和最大限度地减少实验室动物使用的道德需求，促使我们开发工具，以最大限度地获得信息量。这项研究描述了一种新的方法，结合图像分析与空间统计技术。除了监测形态学参数和小胶质细胞密度，最近邻距离和规律性指数的全球变化外，我们还使用基于索马大小和圆度变化的聚类分析，以获得对小鼠视神经损伤模型中不同小胶质细胞表型行为的新见解。这些方法应该被认为是一种通用的工具，以定量评估小胶质细胞活化，小胶质细胞亚群的表型变化，并映射几乎每个CNS区域和疾病状态的空间分布。
Microglia play an important role in the pathology of CNS disorders, however, there remains significant uncertainty about the neuroprotective/degenerative role of these cells due to a lack of techniques to adequately assess their complex behaviour in response to injury. Advancing microscopy techniques, transgenic lines and well-characterized molecular markers, have made histological assessment of microglia populations more accessible. However, there is a distinct lack of tools to adequately extract information from these images to fully characterise microglia behaviour. This, combined with growing economic pressures and the ethical need to minimise the use of laboratory animals, led us to develop tools to maximise the amount of information obtained. This study describes a novel approach, combining image analysis with spatial statistical techniques. In addition to monitoring morphological parameters and global changes in microglia density, nearest neighbour distance, and regularity index, we used cluster analyses based on changes in soma size and roundness to yield novel insights into the behaviour of different microglia phenotypes in a murine optic nerve injury model. These methods should be considered a generic tool to quantitatively assess microglia activation, to profile phenotypic changes into microglia subpopulations, and to map spatial distributions in virtually every CNS region and disease state.