Spatial reconstruction of immune niches by combining photoactivatable reporters and scRNA-seq

Abstract

Cellular functions are strongly dependent on surrounding cells and environmental factors. Current technologies are limited in their ability to characterize the spatial location and gene programs of cells in poorly structured and dynamic niches. We developed a method, NICHE-seq, that combines photoactivatable fluorescent reporters, two-photon microscopy, and single-cell RNA sequencing (scRNA-seq) to infer the cellular and molecular composition of niches. We applied NICHE-seq to examine the high-order assembly of immune cell networks. NICHE-seq is highly reproducible in spatial tissue reconstruction, enabling identification of rare niche-specific immune subpopulations and gene programs, including natural killer cells within infected B cell follicles and distinct myeloid states in the spleen and tumor. This study establishes NICHE-seq as a broadly applicable method for elucidating high-order spatial organization of cell types and their molecular pathways.

Fig. 1. NICHE-seq accurately and reproducibly depicts the cellular composition of defined niches.

(A) TPLSM images of naive inguinal lymph nodes (LNs) from PA-GFP host mice, before and after photoactivation of subregions (green). Adoptively transferred TdTomato⁺ cells (red) and CFP⁺ B cells (cyan) mark the T cell area and the B follicles, respectively. Second harmonic generation was used to detect collagen fibers (cyan). (B) Cell type distribution in the unlabeled LN and photoactivated B cell follicles and Tcell areas, measured by flow cytometry. Error bars represent standard error from three independent experiments. (C) Gene expression profiles of 3900 single cells from photoactivated B cell follicles or Tcell areas of naive inguinal LNs, grouped into five clusters (table S1). The color bar at the top indicates each cell’s origin. Expression is normalized by total cell count and highest gene value. (D) Relative enrichment of different cell types in each subregion (log₂ fold change compared with the total naive LN). Error bars represent 90% confidence intervals. *q < 0.001; Fisher test. (E) Same as (C), but for 8100 single cells from inguinal LNs, 72 hours after infection with LCMV, grouped into seven clusters (table S2). Mono, monocytes; act, activated; inf, inflammatory. (F) Same as (D), but for LCMV-infected cells.

Fig. 2. Characterization of the cellular composition of diverse splenic niches.

(A) TPLSM images of naive spleens of PA-GFP/CX₃CR1-GFP chimeric mice (17), showing CX₃CR1⁺ cells (cyan), T cell areas labeled with adoptively transferred DsRed⁺ T cells (red), and B cell follicles labeled with CFP⁺ B cells (blue), before and after photoactivation of the MZ (green). WP, white pulp; RP, red pulp. Results represent three independent experiments. (B) Gene expression profiles of 7852 single cells from photoactivated splenic B cell follicles, Tcell areas, or MZs, grouped into 16 clusters (table S3). The color bar at the top indicates each cell’s origin. iT_reg, induced T_regs; neut, neutrophils, pDC, plasmacytoid DCs; mac, macrophages. (C) Relative gene expression in different cell types (log₂ fold change compared with expression in other detected splenic cell types). The x and y axes represent relative expression in two biological replicates. (D) Relative abundances of different cell types in splenic niches and the total spleen. Data represent cell counts from both biological and technical replicates (fig. S1, B to F). Cell counts were divided by the total number of cells and multiplied by 1000.

Fig. 3. Viral infection induces distinct changes in the cellular and molecular composition of specific splenic niches.

(A) Changes in splenic B cell follicle, T cell area, and MZ cellular compositions upon LCMV infection compared with their naive equivalents. Error bars represent 90% confidence intervals. *q < 0.001; Fisher test. (B) Representative confocal images from NKp46iCre x Rosa26 TdTomato reporter mice showing tissue localization of NKp46⁺ NK cells (cyan) in naive and LCMV-infected spleens. B220⁺ cells (blue) and CD8⁺ cells (green) mark B cell follicles and T cell areas, respectively. These data are representative of two independent experiments. (C) Quantification of NKp46⁺ cells in B cell follicles and red pulp in two replicates. Error bars represent the range between two experiments. (D) Relative abundances of different cell types in the LCMV-replicating area and the total LCMV-infected spleen. Data represent cell counts from both biological and technical replicates (fig. S1, B to F). Cell counts were divided by the total number of cells and multiplied by 1000. (E) Mean expression levels of genes showing significant cell type–specific differences between the LCMV-replicating area and the total LCMV-infected spleen (q < 0.001; χ² test). Bars indicate the average unique molecular identifier count per 1000 transcripts, normalized to cell size.