Stapenhorst França Fernanda, Gensel John C
Spinal Cord and Brain Injury Research Center and Department of Physiology, College of Medicine, University of Kentucky, Lexington, KY, United States.
Exp Neurol. 2025 Jun;388:115222. doi: 10.1016/j.expneurol.2025.115222. Epub 2025 Mar 18.
Spinal cord injury (SCI) triggers intraspinal inflammation through an influx of blood-derived inflammatory cells such as neutrophils and monocyte-derived macrophages. Macrophages play a complex role in SCI pathophysiology ranging from potentiating secondary injury to facilitating recovery and wound healing. In vitro, macrophages have been classified as having a pro-inflammatory, M1 phenotype, or a regenerative, M2 phenotype. In vivo, however, studies suggest that macrophages exist in a spectrum of phenotypes and can shift from one phenotype to another. Single-cell RNA sequencing (scRNA-seq) allows us to assess immune cell heterogeneity in the spinal cord after injury, and several groups have created publicly available datasets containing valuable data for further exploration. In this study, we compared three different scRNA-seq datasets and analyzed macrophage heterogeneity after SCI based on cell clustering according to gene expression profiles. We analyzed data from 7 days post injury (dpi) in young female mice that received a mid-thoracic SCI contusion. Using the Seurat pipeline, we clustered cells, subsetted macrophages from microglia and other myeloid cells, and identified different macrophage populations. Using SingleR as a cross-dataset cluster comparison tool, we identified similarities in macrophage populations across datasets. To confirm and refine this analysis, we analyzed the top 10 differentially expressed genes for each population in each dataset. Most clusters identified in the SingleR analysis were confirmed to have a unique genetic signature and were consistently present in all datasets analyzed. Taken together, four distinct macrophage populations were consistently identified after SCI at 7 dpi in three datasets from independent research teams. Our identification of biologically conserved macrophage populations after SCI using an unbiased approach highlights the power of data sharing and open data in redefining macrophage heterogeneity.
脊髓损伤（SCI）通过血液来源的炎性细胞（如中性粒细胞和单核细胞衍生的巨噬细胞）的流入引发脊髓内炎症。巨噬细胞在SCI病理生理学中发挥着复杂的作用，从增强继发性损伤到促进恢复和伤口愈合。在体外，巨噬细胞已被分类为具有促炎的M1表型或再生的M2表型。然而，在体内，研究表明巨噬细胞以一系列表型存在，并且可以从一种表型转变为另一种表型。单细胞RNA测序（scRNA-seq）使我们能够评估损伤后脊髓中的免疫细胞异质性，并且有几个研究小组创建了公开可用的数据集，其中包含有价值的数据以供进一步探索。在本研究中，我们比较了三个不同的scRNA-seq数据集，并根据基因表达谱通过细胞聚类分析了SCI后的巨噬细胞异质性。我们分析了接受胸中段SCI挫伤的年轻雌性小鼠在损伤后7天（dpi）的数据。使用Seurat管道，我们对细胞进行聚类，从小胶质细胞和其他髓样细胞中分离出巨噬细胞，并鉴定出不同的巨噬细胞群体。使用SingleR作为跨数据集聚类比较工具，我们确定了不同数据集中巨噬细胞群体的相似性。为了确认和完善这一分析，我们分析了每个数据集中每个群体的前10个差异表达基因。在SingleR分析中鉴定出的大多数聚类被证实具有独特的基因特征，并且在所有分析的数据集中都一致存在。综上所述，在来自独立研究团队的三个数据集中，在SCI后7 dpi时一致鉴定出四个不同的巨噬细胞群体。我们使用无偏方法鉴定SCI后生物学上保守的巨噬细胞群体，突出了数据共享和开放数据在重新定义巨噬细胞异质性方面的作用。
