Full
Outline
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.
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. ④ Spatial 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.
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.
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.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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