Kesapragada Manasa, Sun Yao-Hui, Zhu Kan, Recendez Cynthia, Fregoso Daniel, Yang Hsin-Ya, Rolandi Marco, Isseroff Rivkah, Zhao Min, Gomez Marcella
Department of Applied Mathematics, University of California, Santa Cruz, Santa Cruz, CA, United States of America.
Department of Ophthalmology & Vision Science, School of Medicine, University of California, Davis, Sacramento, CA, United States of America.
PLoS One. 2024 Dec 31;19(12):e0315023. doi: 10.1371/journal.pone.0315023. eCollection 2024.
The motility of macrophages in response to microenvironment stimuli is a hallmark of innate immunity, where macrophages play pro-inflammatory or pro-reparatory roles depending on their activation status during wound healing. Cell size and shape have been informative in defining macrophage subtypes. Studies show pro and anti-inflammatory macrophages exhibit distinct migratory behaviors, in vitro, in 3D and in vivo but this link has not been rigorously studied. We apply both morphology and motility-based image processing approaches to analyze live cell images consisting of macrophage phenotypes. Macrophage subtypes are differentiated from primary murine bone marrow derived macrophages using a potent lipopolysaccharide (LPS) or cytokine interleukin-4 (IL-4). We show that morphology is tightly linked to motility, which leads to our hypothesis that motility analysis could be used alone or in conjunction with morphological features for improved prediction of macrophage subtypes. We train a support vector machine (SVM) classifier to predict macrophage subtypes based on morphology alone, motility alone, and both morphology and motility combined. We show that motility has comparable predictive capabilities as morphology. However, using both measures can enhance predictive capabilities. While motility and morphological features can be individually ambiguous identifiers, together they provide significantly improved prediction accuracies (75%) from a training dataset of 1000 cells tracked over time using only phase contrast time-lapse microscopy. Thus, the approach combining cell motility and cell morphology information can lead to methods that accurately assess functionally diverse macrophage phenotypes quickly and efficiently. This can support the development of cost efficient and high through-put methods for screening biochemicals targeting macrophage polarization.
巨噬细胞响应微环境刺激的运动性是先天免疫的一个标志，在伤口愈合过程中，巨噬细胞根据其激活状态发挥促炎或促修复作用。细胞大小和形状在定义巨噬细胞亚型方面具有参考价值。研究表明，促炎和抗炎巨噬细胞在体外、三维环境和体内表现出不同的迁移行为，但这种联系尚未得到严格研究。我们应用基于形态学和运动性的图像处理方法来分析由巨噬细胞表型组成的活细胞图像。使用强效脂多糖（LPS）或细胞因子白细胞介素-4（IL-4）从原代小鼠骨髓衍生的巨噬细胞中区分出巨噬细胞亚型。我们表明形态学与运动性紧密相关，这使我们提出一个假设，即运动性分析可以单独使用或与形态学特征结合使用，以更好地预测巨噬细胞亚型。我们训练了一个支持向量机（SVM）分类器，分别基于单独的形态学、单独的运动性以及形态学和运动性的组合来预测巨噬细胞亚型。我们表明运动性具有与形态学相当的预测能力。然而，同时使用这两种测量方法可以提高预测能力。虽然运动性和形态学特征单独作为标识符可能具有模糊性，但它们共同使用时，从仅使用相差延时显微镜随时间跟踪的1000个细胞的训练数据集中能显著提高预测准确率（75%）。因此，结合细胞运动性和细胞形态学信息的方法可以产生能够快速、高效地准确评估功能多样的巨噬细胞表型的方法。这可以支持开发用于筛选靶向巨噬细胞极化的生化物质的经济高效且高通量的方法。
