Single-cell RNA sequencing reveals important role of monocytes and macrophages during mucopolysaccharidosis treatment

Abstract

Mucopolysaccharidosis (MPS) encompasses a heterogeneous group of lysosomal storage diseases resulting from mutations in genes encoding lysosomal enzymes responsible for the degradation of mucopolysaccharides, also known as glycosaminoglycans (GAGs). Current therapeutic strategies for MPS include hematopoietic stem cell transplantation (HSCT), enzyme replacement therapy (ERT), and symptomatic therapy. This study investigated dynamic changes in MPS type II (MPS-II) through genomic and single-cell sequencing in a patient undergoing ERT. Analysis of peripheral blood mononuclear cells (PBMCs) from one MPS-II patient of 10 year old at different disease stages through scRNA-seq identified various immune cell types, including natural killer (NK) cells, NKT cells, CD4 + and CD8 + T cells, CD14 + and CD16 + monocytes, and B cells. Monocytes and macrophages were significantly reduced during the severe stage of MPS-II but increased during the recovery stage following ERT. Notably, monocyte subtype mono3 was exclusively expressed in the severe stage, while mono1_2, a subtype of mono1, was absent during the severe stage and exhibited distinct biological functions. These findings suggest that monocytes and macrophages play critical roles in the pathogenesis of MPS-II and in the response to ERT. Pseudotime, Gene Ontology, and cell-communication analyses revealed unique functions for the different cellular subtypes. Notably, key molecules mediating cellular interactions during ERT in MPS-II included CXCR3, PF4, APP, and C5AR1 in macrophages, RPS19 in T cells, HLA-DPB1 in B cells, ADRB2 in NK cells, and IL1B, C5AR1, RPS19, and TNFSF13B in monocytes. Overall, integrative analysis delineated the expression dynamics of various cell types and identified mutations in MPS-II, providing a comprehensive atlas of transcriptional programs, cellular characterizations, and genomic variation profiles in MPS-II. This dataset, along with advanced integrative analysis, represents a valuable resource for the discovery of drug targets and the improvement of therapeutic strategies for MPS-II.

Keywords: Enzyme replacement therapy; Single-cell RNA sequencing; T-cell receptor sequencing; Type II mucopolysaccharidosis; Whole-genome sequencing.

Fig. 1

Clinical manifestations and single-cell transcriptional profile of mucopolysaccharidosis II (MPS-II) patient. (A) Clinical pictures of the patient. (a) claw hands of the patient; (b) X-ray image shows the j-shape sella; (c) MRI image shows enlarged supratentorial ventricle, deepened cerebral sulci, and scattered small cystic with long T1 and long T2 signals. (B) Uniform manifold approximation and projection (UMAP) plot of integrated data splited by group (Health: normal sample; MPS II (a): sample from first stage treatment; MPS II (b): sample from second stage treatment), colored by cell type. (C) Cell types identified by known marker genes. (D) Heatmap showing top 10 differential expressed genes in each group. (E) Location of germline mutation of IDS, HPSE, HPSE2. (F) Feature plot showing IDS gene expression level in three groups. (G) Heatmap illustrating the expression level of genes involved in pathways related with IDS in three groups.

Fig. 2

Single-cell transcriptional profile of monocytes. (A) Umap plot of monocyte subtypes split by group. (B) Dotplot showing marker genes of monocyte subtypes (mono1: classical monocyte; mono2: nonclassical monocyte; mono3: Mono3; mono4: Mono4). (C) KEGG enriched terms of genes upregulated mono3. (D) KEGG enriched terms of genes upregulated mono1_2. (E–F) Visualization of single-cell clusters of monocyte using TooManyCells, which was split by samples and cell subtypes. Cells begin at the central node and are recursively divided based on transcriptional differences. Branch width corresponds to cell number. (G) Ridge plot of the distribution of monocyte subtype along pesudotime(top), heatmap of differential expressed genes along pesudotime trajectory(bottom). Umap plot at right showing the trajectory of monocyte subtypes analyzed by monocle.

Fig. 3

Single-cell transcriptional profile of macrophages. (A) Umap plot of cell subtypes of macrophages split by group. (B) KEGG terms of macrophage in each group. Gene ratio was indicated by the circle size and color indicated the adjusted pvalue. (C) Ridgeplot of the distribution of macrophage subtypes along pesudotime(top), heatmap of differential expressed genes along pesudotime trajectory(bottom). (D) RNA velocity analysis delineated dynamic changes in cell fate, projected onto a UMAP plot. The right illustrates re-clustered result of monocyte and macrophages, the left is RNA velocity plot of monocyte. Arrowheads indicated the predicted direction of cell development, with arrow size denoting the strength of predicted directionality. (E) Visualization of monocyte and macrophage subtypes trajectory using TooManyCells. (F) Dot plot of the predicted interactions between macrophage subtypes.

Fig. 4

Single-cell transcriptional profile of T cells and NK cells. (A) UMAP plot of cell subtypes of T cell. (B) Barplot of the percentageof T cell subtypes in each sample. (C) Bubble plot showing gene ontology (GO) terms of each group. Gene ratio was indicated by the circle size and color indicated the adjusted pvalue. (D–E) Ridgeplot shows the distribution of subtypes of CD4 + T and CD8 + T cell along pesudotime(top), heatmap of differential expressed genes along pesudotime trajectory(bottom). (F) RNA velocity plot of T cell. (G) Umap plot of the distribution of TCR clonotype split by group. (H) Alluvial plot illustrating amino acid sequence VDJC genes clonotype changes of TCR between samples.

Fig. 5

Single-cell transcriptional profile of B cells. (A) Umap plot of cell subtypes of B cell split by groups. (B) Bubble plot showing KEGG terms of each group. Gene ratio was indicated by the circle size and color indicated the adjusted pvalue. (C) Ridgeplot of the distribution of B cell subtype (top) and heatmap of differential expressed genes (bottom) along pesudotime trajectory. (D) RNA velocity plot of B cell. (E) Dot plot of the predicted interactions between B cell subtypes in different group. Interactions are indicated by the color. (F) Umap plot illustrating the distribution of BCR clonotype. (G) Umap plot of the distribution of BCR clonotype split by group. (H) Alluvial plot illustrating amino acid sequence VDJC genes clonotype changes of BCR between samples.

Fig. 6

Cellular interactions between PBMC cell types. (A) Number of cell-cell interactions between each cell types in each group. (B) KEGG pathway dotplot of health control, MPS1, and MPS2. (C–E). Dot plot of the predicted interactions between each cell types in different group. Interactions are indicated by the color. (C) ligan-receptor pairs between cells except monocyte and macrophage; (D) ligan-receptor pairs between monocyte and other cell types; (E) ligan-receptor pairs between macrophage and other cell types. (F) Predicated cell transformation and cellular interactions through potential ligand-receptor pairs.