Extended Data Fig. 7: Extended Data Fig. 7.

a, Flow cytometry gating strategy for selection of viable (SYTOX Blue^-) cells that had taken up SWNTs (Cy5.5⁺). b, Sequencing data quality metrics for cells isolated from aortae of mice following treatment with SWNT-Cy5.5 or SWNT-SHP1i. c, Violin plots showing number of genes (nGene), unique molecular identifier (nUMI), and percentage of mitochondrial gene reads (percent.mito) for cells in the full dataset (n = 8 biologically independent animals). Each point represents the given value from a single cell. d, Scatterplot of nGene and nUMI across the combined dataset used to identify and exclude outliers (for example cell doublets). e, Representative violin plots showing the distribution of gene expression of immune cell markers in the 7 identified leukocyte clusters (n = 8 biologically independent animals). The identity of clusters was defined according to canonical hematopoietic-lineage and immune cell markers: macrophages (Adgre1 encoding F4/80, Cd68, Csf1r), memory T cells (Cd3g, Il2r, Ptprc and Il7r encoding memory markers CD45RO and CD127), dendritic cells (Cd209a, Flt3, Itgax encoding CD11c), monocytes (Ccr2, Ly6c2, Itgam encoding CD11b), granulocytes (Csf3r, S100a9), and CD4⁺/CD8⁺ T cell subsets (Cd3e, Cd4, Cd8a). Each point represents log-normalized single cell expression levels. f, Analysis of SWNT-positive (Cy5.5⁺) cells in each cluster confirms that SWNTs specifically target macrophages in the atherosclerotic aorta. Detection of SWNT uptake was greater in macrophages when characterizing cells by their whole-transcriptome, rather than the traditional limited markers used in flow cytometry above (Fig. 2e, Supplementary Fig. 4). ~90% of lesional macrophages took up SWNTs in both SWNT-Cy5.5 and SWNT-SHP1i treated animals as compared to <30% of dendritic cells and <10% of T cells and granulocytes with SWNT detection. Similarly high SWNT uptake (>75%) was detected in “macrophage-like” cells.