Modulating local S1P receptor signaling as a regenerative immunotherapy after volumetric muscle loss injury

Figure S1 Visualization of circulating immune cell subsets with single cell 2D projections and pseudotime trajectories reveals innate leukocyte heterogeneity. High dimensional flow cytometry data of peripheral blood taken from uninjured animals represented as 2D projections using UMAP and SPADE dimensionality reduction techniques. (A) SPADE trees and accompanying UMAPs generated with manually gated CD11b⁺ cells circulating homeostatic blood from WT mice (A-I, III) as well as S1PR3 KO (KO) mice (A-II, IV). Within the CD11b⁺ SPADE trees, neutrophils (A-I, II) and monocytes (A-III, IV) were manually gated and overlaid onto their respective SPADE trees, where the node color represents normalized cell frequency of its specified phenotype in heatmap form. A red overlay on the corresponding UMAPs represent cells identified as a neutrophil or monocyte, respectively. (B) SPADE trees and UMAPS generated with manually gated CD3⁺ T cells from the blood of uninjured WT mice (B-I, III) and S1PR3 KO mice (B-II, IV). CD4⁺ T cells (B-I, II) and CD8⁺ T cells (B-III, IV) were manually gated and overlaid onto the SPADE trees, as well as onto the single cell UMAP projections. UMAP and SPADE representations of high dimensional flow data reveal discrete heterogeneities as observed through the multiple islands depicted on the UMAPs and many nodes clustered via SPADE per phenotypic characterization. n = 3 samples (A) and 7 samples (B) per genotype.

Figure S2 Cell frequency quantifications between WT and S1PR3 KO mice within each SPADE node containing cells of specified phenotype. Bar graph representation and statistical analysis applied to the tornado plots presented in Figure 4. For each specified cellular phenotype, every node containing cells of this particular subset are analyzed for phenotype-specific cell frequency between experimental groups to evaluate which nodes are significantly dominated by subsets from a particular genotype. Nodes containing cells of the respective phenotype are denoted along the x-axis while the phenotype-specific cell frequency is quantified as a percentage of all live cells. Two-way ANOVAs with Tukey's multiple comparisons were performed for statistical analyses with n = 7 samples per genotype. Data is presented as mean ± SEM. *p < 0.05, **p < 0.01, ****p < 0.0001

Figure S3 Characterization of VPC01091-loaded nanofiber scaffold. Release of VPC01091 from PLGA-PCL nanofiber scaffolds and biomaterial characterization by atomic force microscopy (AFM). (A) Experimental setup for electrospinning VPC01091-loaded PLGA-PCL nanofibers. (B) VPC01091 in vitro release profile exhibits sustained delivery. (C) Average Young's modulus values obtained via AFM for blank control nanofiber scaffold (NF) and NF loaded with VPC01091 (VPC). (D, G) AFM generated topography (height) map of blank (D) and VPC01091-loaded (G) PLGA-PCL nanofiber scaffold. Height values throughout nanofiber range from low (black) to high (white) regions. (E, H) AFM generated stiffness map of blank (E) and VPC01091-loaded (H) PLGA-PCL nanofiber scaffold in which white regions represent areas of greater stiffness. (F, I) Histogram of Young's modulus values (MPa) obtained from AFM over multiple contact points on blank (F) and VPC01091-loaded (I) PLGA-PCL nanofiber scaffold. Unpaired two-sided t-test was performed for statistical analysis (C) and data is presented as mean ± SEM.

Figure S4 Cell frequency quantifications between mice treated with control and VPC01091-loaded nanofibers within each SPADE node containing cells of specified phenotype. Bar graph representation and statistical analysis applied to the tornado plots presented in Figure 5. For each specified cellular phenotype, every node containing cells of this particular subset are analyzed for phenotype-specific cell frequency between experimental groups to evaluate which nodes are significantly dominated by subsets from a particular treatment. Nodes containing cells of the respective phenotype are denoted along the x-axis while the phenotype-specific cell frequency is quantified as a percentage of all live cells. Two-way ANOVAs with Tukey's multiple comparisons were performed for statistical analysis with n = 8 samples per treatment. Data is presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.000.

Figure S5 Circulating lymphocytes after muscle injury unaffected by S1PR3 deficiency. SPADE trees generated with CD3⁺ T cells from the peripheral blood of WT and global S1PR3 KO mice (A-C) and mice treated with blank control nanofibers (NF) and those releasing VPC01091 (D-F) 3 days post VML injury. (A, D) CD4⁺ (I) and CD8⁺ (II) T cells were manually gated and overlaid onto their respective SPADE trees where colored node annotation represents normalized cell frequency in the form of a heatmap, illustrating the phenotypic differences in these T cell subpopulations as they are located on opposing sides of the tree. (B, E) CD4 (I) and CD8 (II) fluorescence marker intensities overlaid onto the SPADE trees with the manually gated annotation circled in black to further characterize their expression as displayed by SPADE clustering. (C, F) SPADE quantifications of total CD4⁺ and CD8⁺ T cells circulating the blood of WT versus S1PR3 KO mice (C) and mice treated with blank control or VPC01091-loaded (VPC) nanofibers (F). Data represented as mean ± SEM using a two-way ANOVA with Tukey's multiple comparisons test. n = 7 samples per experimental group.

Figure S6 Lack of S1PR3 leads to increased numbers of muscle resident stem cells. SPADE trees generated from Lin⁻ cell events taken from uninjured spinotrapezius and hindlimb muscles. (A) MuSCs from the spinotrapezius (A-I) and hindlimb (A-II) are manually gated and overlaid onto their respective trees, annotated with colored nodes representing normalized cell frequency and displayed as a heatmap on the tree. Each node containing MuSCs is given a node assignment number as given next to each colored node. (B) MuSC frequency within each node annotated on spinotrapezius and hindlimb derived SPADE trees. Nodes from the SPADE tree generated with Lin⁻ spinotrapezius derived cells are quantified for MuSC frequency (B-I) while those derived from the hindlimb are quantified by node in (B-II). (C) Tornado plot representation of the difference in average MuSC frequency percentage between S1PR3 deficient mice and their WT counterparts shows that nodes containing MuSCs largely contain those derived from mice lacking S1PR3 (KO) in both the spinotrapezius and hindlimb (C-I, II). Two-way ANOVAs with Tukey's multiple comparisons were conducted for statistical analyses and data is presented as mean ± SEM with n = 3 per genotype for hindlimb samples and an n = 4 per genotype for spinotrapezius samples. *p < 0.05

Figure S7 Treatment with blank nanofiber scaffold increases macrophage infiltration to defect area 3 days post injury. Flow cytometry analysis of CD11b⁺CD64⁺MerTK⁺ macrophages in injured spinotrapezius muscle 3 days post injury between WT mice receiving no treatment (injury control, black bar) and WT mice treated with blank nanofiber scaffolds (white bar). Statistical analysis performed with two-tailed t-test. Data presented as mean ± SEM. n = 7 for WT injury control and n = 8 for mice treated with blank nanofibers.