利用成像质谱流式技术建立肾脏空间免疫微环境的分析体系OA
Development of an analytical system for renal spatial immune microenvironment using imaging mass cytometry
目的 慢性肾病的进展与肾脏空间免疫微环境的紊乱密切相关,本研究旨在利用成像质谱流式技术(imaging mass cytometry,IMC),开发出一套解析慢性肾病免疫微环境的实验和分析体系,以用于全景式解析慢性肾病肾脏组织的单细胞空间免疫微环境.方法 ①筛选针对肾脏结构单元、基质细胞和免疫细胞的抗原标志物,构建质谱流式成像抗体组合,金属标记的抗体均通过免疫组织化学实验完成抗体特异性验证;②选取2例输尿管癌旁的正常肾脏活检组织、2例糖尿病肾病(diabetic nephropathy,DN)和2例免疫球蛋白A肾病(IgA nephropathy,IgAN)患者的肾穿刺活检组织,利用上述抗体进行染色孵育,通过Hyperion成像系统完成图形数据采集;③整合Ilastik与CellProfiler技术建立针对肾组织的单细胞分割流程,结合手动圈门与Phenograph无监督聚类算法完成细胞身份注释;④建立细胞间的空间邻近关系,利用置换检验对随机分布模型进行模拟,解析组织细胞与免疫细胞之间的空间关系;⑤采用 k 近邻(k-nearest neighbors,kNN)算法进行空间聚类,通过细胞邻域(cellular neighborhoods,CNs)划分出肾脏组织的空间功能单元,进而分析这些功能单元的免疫学特征和比例.结果 ①构建并优化出了1个37色的抗体组合,抗体均显示出高特异性和低背景噪声,该抗体组合可精准识别肾脏的结构细胞,基质细胞和浸润的免疫细胞;②通过Hyperion成像系统获得正常与2种慢性肾病的肾组织高维成像图片;③通过单细胞拆分流程系统绘制了21种肾脏组织细胞和17种免疫细胞的人类肾脏高分辨率单细胞图谱,鉴定出了CD15+巨噬细胞、GzmK+CD4+效应T细胞等免疫细胞以及3种新型的双阳性肾小管细胞,展现了DN与IgAN肾病组织中浸润免疫细胞的差异性;④建立了单细胞的空间互作分析方法,展现了慢性肾病组织中免疫细胞空间互作网络,发现肌成纤维细胞作为连接组织损伤与免疫细胞浸润的关键空间枢纽;⑤通过空间邻域分析可以将肾脏结构划分为肾小球区、近端小管区、髓袢升支区、血管和纤维化区与免疫细胞富集区等9个功能单元.病变组织中正常功能结构区域占比下降,而纤维化与免疫富集区比例显著上升.其中免疫细胞富集区普遍与各功能区域保持紧密共定位,而血管和纤维化区主要与收集管区和髓袢升支区相邻.结论 本研究成功开发了一套适用于肾脏组织成像的IMC方法学体系.该体系能高分辨率全景展现免疫细胞在慢性肾脏组织中的空间分布,解析了免疫细胞与组织细胞空间互作和局部免疫微环境特征.本技术将推动基于空间特征的肾脏病精准诊断和靶向治疗策略开发.
Objective The progression of chronic kidney disease(CKD)is closely associated with the disruption of renal spatial immune microenvironment.This study aimed to develop an integrated experimental and analytical system for dissecting the immune microenvironment of CKD using imaging mass cytometry(IMC),thereby enabling panoramic analysis of single-cell spatial immune microenvironment in CKD renal tissues.Methods ① Antigenic markers targeting renal structural units,stromal cells,and immune cells were screened to construct a mass cytometry imaging antibody panel;all metal-conjugated antibodies were validated for specificity by immunohistochemistry.②Two normal kidney biopsy specimens adjacent to ureteral carcinoma,2 diabetic nephropathy(DN),and 2 IgA nephropathy(IgAN)renal biopsy specimens were collected,stained with the aforementioned antibodies,and subjected to image data acquisition using the Hyperion imaging system to obtain multiplexed spatial data.③ An integrated Ilastik and CellProfiler workflow was established for single-cell segmentation pipeline tailored for renal tissues,and cell identity annotation was achieved using a combination of manual gating and Phenograph unsupervised clustering.④Spatial proximity relationships between cells were defined,and permutation testing was employed to simulate random distribution models to examine spatial relationships between tissue cells and immune cells.⑤ k-nearest neighbors(kNN)algorithm was applied for spatial clustering,and cellular neighborhoods(CNs)were used to delineate the spatial functional units within renal tissue,followed by analysis of the immunological characteristics and relative abundance of these units.Results ①A 37-color antibody panel was constructed and optimized,with all antibodies demonstrating high specificity and low background noise;this panel enabled accurate identification of renal structural cells,stromal cells,and infiltrating immune cells.② High-dimensional IMC imaging data were successfully obtained from normal and CKD renal tissues using the Hyperion imaging system.③ With the aid of the single-cell segmentation pipeline,a high-resolution single-cell atlas of human kidney was systematically mapped,comprising 21 structural cell types and 17 immune cell subtypes.Immune cell populations such as CD15⁺ macrophages,GzmK⁺ CD4⁺ effector T cells,and 3 distinct double-positive renal tubular cells were identified,revealing differential infiltration of immune cells in DN and IgAN tissues.④ A single-cell spatial interaction analysis framework was established,demonstrating a disease-specific spatial interaction network of immune cells in CKD tissues,and identifying myofibroblasts as a critical spatial hub connecting tissue injury and immune cell infiltration.⑤ Spatial neighborhood analysis delineated 9 functional units of renal tissue,including glomerular,proximal tubular,ascending limb of the loop of Henle,vascular and fibrotic,and immune cell-enriched regions.In diseased tissues,the proportion of normal functional regions was decreased,whereas the proportions of fibrotic and immune-enriched regions were increased significantly.Moreover,immune cell-enriched zones maintained close colocalization with various functional regions,while vascular and fibrotic regions were predominantly adjacent to collecting duct and ascending limb of the loop of Henle.Conclusion An IMC methodology tailored for the spatial analysis of renal tissue is successfully developed.This platform enables high-resolution,panoramic visualization of spatial distribution of immune cells in chronic renal tissues,dissecting spatial interactions between immune and structural cells and characteristics of local immune microenvironment.This technology holds promise to advance the development of spatially informed precision diagnostics and targeted therapeutic strategies for renal diseases.
刘佳雯;向群;沈一超;张江南;尹俐;田易;张静波;冯泽清;吴玉章
南方医科大学基础医学院免疫学教研室,广东广州重庆国际免疫研究院,重庆||重庆理工大学药学与生物工程学院,重庆重庆国际免疫研究院,重庆陆军军医大学(第三军医大学)第二附属医院肾内科,重庆重庆理工大学药学与生物工程学院,重庆陆军军医大学(第三军医大学)基础医学院免疫学教研室,重庆陆军军医大学(第三军医大学)第二附属医院肾内科,重庆重庆国际免疫研究院,重庆||重庆理工大学药学与生物工程学院,重庆南方医科大学基础医学院免疫学教研室,广东广州||陆军军医大学(第三军医大学)基础医学院免疫学教研室,重庆
医药卫生
成像质谱流式技术慢性肾脏病肾脏免疫空间微环境单细胞分析
imaging mass cytometrychronic kidney diseaserenal spatial immune microenvironmentsingle-cell analysis
《陆军军医大学学报》 2026 (7)
831-846,16
国家自然科学基金专项(32141005)国家自然科学基金面上项目(82271846) Supported by the Special Fund of National Natural Science Foundation of China(32141005)and the General Program of National Natural Science Foundation of China(82271846).
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