A single cell spatial temporal atlas of skeletal muscle reveals cellular neighborhoods that orchestrate regeneration and become disrupted in aging

Background

The regenerative capacity of skeletal muscle depends on muscle stem cells (MuSCs) that remain dormant until an injury is detected. With age, there is a decline in the regenerative capacity of skeletal muscle. The activation of MuSCs and, thus, the generation of myogenic progenitors that will fuse to form myofibers depends on various cellular interactions orchestrated by the surrounding niche. During aging, these coordinated events are deregulated which in turn disrupts the signals necessary for MuSCs activation and subsequent muscle repair.

Multiple studies suggest that the skeletal muscle stem cell niche is composed of a dynamic and highly regulated interplay of various cell types responsible for maintaining MuSC quiescence and the regenerative response. However, current technologies (i.e., single cell RNA-sequencing, flow cytometry, etc.) limit our understanding of the stem cell niche because we are unable to accurately assess cell-cell interactions within their spatial context. In this study, Yu Xin Wang et al. used multiplex imaging to profile the spatial distribution of 34 cell types at single-cell resolution during muscle regeneration. In doing so, they uncovered intercellular crosstalk events characterizing various cellular neighborhoods and gained insight into how these interactions change throughout the regenerative response and when confronted with macrophage depletion.

Key findings

Cellular heterogeneity during muscle repair

The authors created a single-cell spatial atlas of cell subsets involved in skeletal muscle regeneration using Co-Detection by Indexing (CODEX) technology which allows for a highly multiplexed analysis of over 40 protein markers to be visualized simultaneously in one tissue section. Yu Xin Wang et al. started off by constructing a CODEX antibody panel using previously characterized cell-type specific markers representative of myogenic, immune (i.e. monocytes, dendritic cells (DCs), B cells, T cells and macrophages), vascular, fibrogenic and motor neuron cell subsets and cell states. Intramuscular injections of notexin (NTX) in the tibialis anterior (TA) of young mice was used to induce various muscle injuries similar to those encountered in sports or trauma. Afterwards, CODEX was performed on tissue sections over a 10-day period to generate single-cell multiplexed imaging data at day 1, 3, 6 and 10 after injury.

Images generated by CODEX were analyzed to create a single-cell spatial atlas during skeletal muscle regeneration. Yu Xin Wang et al. developed an imaging processing pipeline termed CRISP that registered, stitched and cleared each image. After using CRISP, the authors utilized the deep learning module CellSeg which relies on a convolutional neural network (CNN) to segment nuclei present in an image. In doing so, they were able to quantify the intensity of each antibody in the nuclear and perinuclear compartments. The inherent multinucleated nature of myofibers and extracellular matrix (ECM) structures made these features difficult to characterize using CellSeg. To overcome these limitations, Xin Wang et al. developed FiberNet which relies on a CNN to characterize muscle fiber states and ECM features. Cell-type clustering and annotation was done using the HFcluster pipeline. HFcluster was developed by the authors and relies on learning antibody staining patterns of different cell types to identify cells sharing similar patterns within a dataset.

The CODEX protocol and subsequent data processing resolved specific signals of 34 distinct cell subsets, allowing Yu Xin Wang et al. to monitor dynamic changes in cell-cell numbers and organization at sites of injury following NTX. The analysis revealed a constant influx of myogenic, immune, vascular and fibrogenic cell subsets during muscle regeneration. Day 1 was marked by an influx of immune cells, followed by an increase in endothelial and vascular cell subsets on day 3 which further increased on day 6. Muscle regeneration is nearly complete at day 10. Moreover, it was found that the relative abundance of various cell subsets within each tissue can be used to characterize and distinguish the various time points. Cell types in uninjured, day 1, 3 and 6 samples were largely distinct. The largest cell subset diversity was found at day 3 and it was also revealed that numerous day 3 cell types were also found in day 1 and 6 tissues. Tissues from day 10 contained cells found in day 6 tissues but had the most cell subsets in common with uninjured samples.

Insights into cellular neighborhood dynamics

The correlated dynamics of various cell types led the authors to hypothesize that these cells organize into context-dependent cellular neighborhoods during skeletal muscle regeneration. Using a pairwise interaction analysis Xin Wang et al. identified various cellular neighborhoods of regenerating muscle. Injured myofiber neighborhood characterization revealed that neutrophiles, M1 macrophages, endothelial cells (ECs) and fibroadipogenic progenitors (FAPs) were enriched at the site of injury. Interestingly, CD38+ ECs, suggestive of capillary perfusion, were also enriched close to MuSCs. Myeloid subsets, including macrophages and neutrophiles, were enriched in the innate immune neighborhood and are responsible for recruiting monocytes as well as interacting with dendritic cells. The authors also uncovered that injured myofibers are subjected to not only an innate immune response, but potentially also an antibody mediated adaptive immune response later in the regenerative process. In fact, injured myofibers were enriched in cellular neighborhoods comprised of CD9+ DCs and IgM+ plasma cells.

M1 macrophages facilitate and coordinate muscle repair

ECM structures (i.e. basal lamina) may act as selective barriers allowing only certain cell types to pass through. The authors quantified the cell subsets found in ECM structures as well as their co-occurrence to reveal cellular heterogeneity within ECM structures at different time points during muscle regeneration. Xin Wang et al. demonstrated that M1 macrophages are enriched near ECM structures and that they are the major cell type found within ECM structures. Additionally, M1 macrophages were accompanied by lower levels of monocytes, DCs, fibroblast, regenerating myofibers and other macrophage subsets. The presence of Ly6G neutrophils, CD31 ECs and myogenic progenitors within ECM structures varied across different time points. More precisely, the authors observed ECM structures dominated by neutrophiles and M1 macrophages at day 1 post-injury. Day 3 was marked by macrophage-dominant ECM structures that became macrophage-derived DC-dominant by day 6. The results further highlight the importance of M1 macrophages as facilitators and coordinators of muscle repair.

The presence of M1 macrophages near and within ECM structures led the authors to hypothesize that M1 macrophages are a key cell type that paves the way for myogenic cell intervention during muscle regeneration.  To assess the importance of M1 macrophages during the regenerative response, intramuscular injections of clodronate liposomes were administered day 2 post-injury to deplete macrophages locally. A significant reduction of M1 macrophages was observed as well as the reduction of M1 macrophage-dominant ECM structures. Moreover, samples treated with clodronate contained IgM+ myofiber debris at day 10 which suggests that movement of M1 macrophages across ECM structures plays a critical role in removing injured myofibers. Clodronate treated samples, in comparison to non-clodronate treated samples, had fewer regenerating myofibers (day 6 and day 10), fewer ECM structures containing mature regenerating myofibers (day 6 and day 10) and an increased number of ECM structures containing MuSCs and myocytes (day 6). Additionally, an abnormal organization of regenerating myofibers was observed in clodronate treated samples at day 10 due to the presence of myofiber debris.

Xin Wang et al. utilized a spatialtemporal cell neighborhood analysis to assess the impact of localized disruptions, such as the depletion of M1 macrophages, on the spatial arrangement of cells and the time at which certain events take place during the regenerative response. In non-clodronate treated samples, the authors identified 26 spatial neighborhoods, 10 of which are temporal clusters that change across the time course. Interestingly, a cell neighborhood unique to clodronate treated samples was identified in the study. The neighborhood contained disorganized injured myofibers, myogenic cell subsets at various stages, innate and adaptative immune cells as well as fibroblasts. Unlike non-clodronate samples, these cell types appeared in a disorganized manner and co-exist in clodronate treated samples. Moreover, the authors found an aberrant accumulation of myeloid subsets, MyoD+ MyoG+ myoblasts and CD38+ ECs, at day 3 in clodronate treated samples. Overall, it was evidenced by Xin Wang et al. that M1 macrophages play a critical role in coordinating regeneration events. Their depletion results in a disruption of cell subset progression and cell neighborhood organization during muscle repair marked by a delay in myotube maturation at day 10.

Why this work is important

Employing tissue dissociation techniques prevents researchers from building a comprehensive atlas of skeletal muscle regeneration at the spatial scale. The use of CODEX by Xin Wang et al. allowed the researchers to generate the first single-cell spatialtemporal atlas of muscle repair. The atlas can now be shared within the scientific community to advance our understanding of the cell-cell interactions as well as cell-neighborhood formation and organization occurring during muscle repair. Additionally, the work performed in this study revealed that macrophage depletion does not halt muscle regeneration, but rather impacts it’s coordinated processes at both the spatial and temporal scale due to impaired phagocytosis and an accumulation of cellular debris. Overall, this study highlights the necessity for spatialtemporal analyses in understanding how cells are dynamically organized and interact across various processes in pathophysiological conditions.

Questions for the authors

1. You mentioned that the depletion of M1 macrophages does not lead to a stall across cell types during muscle regeneration. Do you expect this to be the case for both acute and chronic muscle damage?
2. Do you envision depleting macrophages in aged mice and performing a spatialtemporal cell neighborhood analysis to assess whether the appearance of the cell neighborhood unique to clodronate treated young mice appears in older mice as well?

Tags: multiplex imaging, spatial proteomics

doi: https://doi.org/10.1242/prelights.32523

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