Department of Neurology, Heinrich-Heine University Düsseldorf, Medical Faculty, Düsseldorf, Germany.
Brain and Mind Center, University of Sydney, Sydney, NSW, Australia.
Front Immunol. 2021 Oct 21;12:761776. doi: 10.3389/fimmu.2021.761776. eCollection 2021.
Confocal scanning laser ophthalmoscopy (cSLO) is a non-invasive technique for real-time imaging of the retina. We developed a step-by-step protocol for the semi-automatic evaluation of myeloid cells in cSLO images from CX3CR1 mice, expressing green fluorescent protein (GFP) under control of the endogenous CX3C chemokine receptor 1 locus. We identified cSLO parameters allowing us to distinguish animals with experimental autoimmune encephalomyelitis (EAE) from sham-treated/naïve animals. Especially cell count (CC) and the total microglial area (SuA) turned out to be reliable parameters. Comparing the cSLO results with clinical parameters, we found significant correlations between the clinical EAE score and the SuA and of the inner retinal layer thickness, measured by optical coherence tomography, with the CC as well as the SuA. As a final step, we performed immunohistochemistry to confirm that the GFP-expressing cells visualized by the cSLO are Iba1 positive and validated the step-by-step protocol against manual counting. We present a semi-automatic step-by-step protocol with a balance between fast data evaluation and adequate accuracy, which is optimized by the option to manually adapt the contrast threshold. This protocol may be useful for numerous research questions on the role of microglial polarization in models of inflammatory and degenerating CNS diseases involving the retina.
共聚焦扫描激光检眼镜（cSLO）是一种用于实时成像视网膜的非侵入性技术。我们开发了一种逐步协议，用于半自动评估 CX3CR1 小鼠 cSLO 图像中的髓样细胞，这些细胞在内源性 CX3C 趋化因子受体 1 基因座的控制下表达绿色荧光蛋白（GFP）。我们确定了 cSLO 参数，使我们能够将患有实验性自身免疫性脑脊髓炎（EAE）的动物与假处理/未处理的动物区分开来。特别是细胞计数（CC）和总小胶质细胞面积（SuA）被证明是可靠的参数。将 cSLO 结果与临床参数进行比较，我们发现临床 EAE 评分与 SuA 以及光学相干断层扫描测量的内视网膜层厚度之间存在显著相关性，与 CC 和 SuA 均存在相关性。作为最后一步，我们进行了免疫组织化学染色以确认 cSLO 可视化的 GFP 表达细胞为 Iba1 阳性，并针对手动计数验证了逐步协议。我们提出了一种半自动逐步协议，在快速数据评估和足够的准确性之间取得平衡，并通过手动适应对比度阈值的选项进行了优化。该协议可能对涉及视网膜的炎症和退行性中枢神经系统疾病模型中微胶质细胞极化作用的众多研究问题有用。
