Muscle regeneration is a dynamic process during which cell state and identity change over time. A major roadblock has been a lack of tools to resolve a myogenic progression in vivo. Here we capitalize on a transformative technology, single-cell mass cytometry (CyTOF), to identify in vivo skeletal muscle stem cell and previously unrecognized progenitor populations that precede differentiation. We discovered two cell surface markers, CD9 and CD104, whose combined expression enabled in vivo identification and prospective isolation of stem and progenitor cells. Data analysis using the X-shift algorithm paired with single-cell force-directed layout visualization defined a molecular signature of the activated stem cell state (CD44+/CD98+/MyoD+) and delineated a myogenic trajectory during recovery from acute muscle injury. Our studies uncover the dynamics of skeletal muscle regeneration in vivo and pave the way for the elucidation of the regulatory networks that underlie cell-state transitions in muscle diseases and ageing.
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Chang, N. C. & Rudnicki, M. A. Satellite cells: the architects of skeletal muscle. Curr. Top. Dev. Biol. 107, 161–181 (2014).
Blau, H. M., Cosgrove, B. D. & Ho, A. T. V. The central role of muscle stem cells in regenerative failure with aging. Nat. Med. 21, 854–862 (2015).
Weissman, I. L. Translating stem and progenitor cell biology to the clinic: barriers and opportunities. Science 287, 1442–1446 (2000).
Bendall, S. C. et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332, 687–696 (2011).
Bendall, S. C. et al. Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell 157, 714–725 (2014).
Levine, J. H. et al. Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell 162, 184–197 (2015).
Druker, B. J. Translation of the Philadelphia chromosome into therapy for CML. Blood 112, 4808–4817 (2008).
Spitzer, M. H. & Nolan, G. P. Mass cytometry: single cells, many features. Cell 165, 780–791 (2016).
Bosnakovski, D. et al. Prospective isolation of skeletal muscle stem cells with a Pax7 reporter. Stem Cells 26, 3194–3204 (2008).
Sacco, A., Doyonnas, R., Kraft, P., Vitorovic, S. & Blau, H. M. Self-renewal and expansion of single transplanted muscle stem cells. Nature 456, 502–506 (2008).
Cerletti, M. et al. Highly efficient, functional engraftment of skeletal muscle stem cells in dystrophic muscles. Cell 134, 37–47 (2008).
Liu, L., Cheung, T. H., Charville, G. W. & Rando, T. A. Isolation of skeletal muscle stem cells by fluorescence-activated cell sorting. Nat. Protoc. 10, 1612–1624 (2015).
Samusik, N., Good, Z., Spitzer, M. H., Davis, K. L. & Nolan, G. P. Automated mapping of phenotype space with single-cell data. Nat. Methods 13, 493–496 (2016).
Jacomy, M., Venturini, T., Heymann, S. & Bastian, M. ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLoS ONE 9, e98679 (2014).
Zunder, E. R., Lujan, E., Goltsev, Y., Wernig, M. & Nolan, G. P. A continuous molecular roadmap to iPSC reprogramming through progression analysis of single-cell mass cytometry. Cell Stem Cell 16, 323–337 (2015).
Karlsson, G. et al. The tetraspanin CD9 affords high-purity capture of all murine hematopoietic stem cells. Cell Rep. 4, 642–648 (2013).
Tachibana, I. & Hemler, M. E. Role of transmembrane 4 superfamily (TM4SF) proteins CD9 and CD81 in muscle cell fusion and myotube maintenance. J. Cell Biol. 146, 893–904 (1999).
Clarke, A. S., Lotz, M. M. & Mercurio, A. M. A novel structural variant of the human β4 integrin cDNA. Cell Adhes. Commun. 2, 1–6 (1994).
Su, L., Lv, X. & Miao, J. Integrin β4 in neural cells. Neuromol. Med. 10, 316–321 (2008).
Masugi, Y. et al. Upregulation of integrin β4 promotes epithelial-mesenchymal transition and is a novel prognostic marker in pancreatic ductal adenocarcinoma. Lab. Invest. 95, 308–319 (2015).
Guo, W. et al. β4 integrin amplifies ErbB2 signaling to promote mammary tumorigenesis. Cell 126, 489–502 (2006).
Liadaki, K. et al. β4 integrin marks interstitial myogenic progenitor cells in adult murine skeletal muscle. J. Histochem. Cytochem. 60, 31–44 (2012).
Jones, N. C. et al. The p38α/β MAPK functions as a molecular switch to activate the quiescent satellite cell. J. Cell Biol. 169, 105–116 (2005).
Troy, A. et al. Coordination of satellite cell activation and self-renewal by par-complex-dependent asymmetric activation of p38 α/β MAPK. Stem Cell 11, 541–553 (2012).
Cosgrove, B. D. et al. Rejuvenation of the muscle stem cell population restores strength to injured aged muscles. Nat. Med. 20, 255–264 (2014).
Segalés, J., Perdiguero, E. & Muñoz-Cánoves, P. Regulation of muscle stem cell functions: a focus on the p38 MAPK signaling pathway. Front. Cell Dev. Biol. 4, 91 (2016).
Hausburg, M. A. et al. Post-transcriptional regulation of satellite cell quiescence by TTP-mediated mRNA decay. eLife 4, e03390 (2015).
Seale, P. et al. Pax7 is required for the specification of myogenic satellite cells. Cell 102, 777–786 (2000).
von Maltzahn, J., Jones, A. E., Parks, R. J. & Rudnicki, M. A. Pax7 is critical for the normal function of satellite cells in adult skeletal muscle. Proc. Natl Acad. Sci. USA 110, 16474–16479 (2013).
Gilbert, P. M. et al. Substrate elasticity regulates skeletal muscle stem cell self-renewal in culture. Science 329, 1078–1081 (2010).
Relaix, F. & Zammit, P. S. Satellite cells are essential for skeletal muscle regeneration: the cell on the edge returns centre stage. Development 139, 2845–2856 (2012).
Behbehani, G. K., Bendall, S. C., Clutter, M. R., Fantl, W. J. & Nolan, G. P. Single-cell mass cytometry adapted to measurements of the cell cycle. Cytometry 81A, 552–566 (2012).
Mylona, E., Jones, K. A., Mills, S. T. & Pavlath, G. K. CD44 regulates myoblast migration and differentiation. J. Cell. Physiol. 209, 314–321 (2006).
Drummond, M. J. et al. An increase in essential amino acid availability upregulates amino acid transporter expression in human skeletal muscle. Am. J. Physiol. Endocrinol. Metab. 298, E1011–8 (2010).
Conboy, M. J., Karasov, A. O. & Rando, T. A. High incidence of non-random template strand segregation and asymmetric fate determination in dividing stem cells and their progeny. PLoS Biol. 5, e102 (2007).
Rocheteau, P., Gayraud-Morel, B., Siegl-Cachedenier, I., Blasco, M. A. & Tajbakhsh, S. A subpopulation of adult skeletal muscle stem cells retains all template DNA strands after cell division. Cell 148, 112–125 (2012).
Leung, K. T. et al. The tetraspanin CD9 regulates migration, adhesion, and homing of human cord blood CD34+ hematopoietic stem and progenitor cells. Blood 117, 1840–1850 (2011).
Gutiérrez-López, M. D. et al. The sheddase activity of ADAM17/TACE is regulated by the tetraspanin CD9. Cell. Mol. Life Sci. 68, 3275–3292 (2011).
Arduise, C. et al. Tetraspanins regulate ADAM10-mediated cleavage of TNF-α and epidermal growth factor. J. Immunol. 181, 7002–7013 (2008).
Mizuno, S. et al. A disintegrin and metalloprotease 10 is indispensable for maintenance of the muscle satellite cell pool. J. Biol. Chem. 290, 28456–28464 (2015).
Koch, U., Lehal, R. & Radtke, F. Stem cells living with a Notch. Development 140, 689–704 (2013).
Uezumi, A. et al. Cell-surface protein profiling identifies distinctive markers of progenitor cells in human skeletal muscle. Stem Cell Rep. 7, 263–278 (2016).
Alexander, M. S. et al. CD82 is a marker for prospective isolation of human muscle satellite cells and is linked to muscular dystrophies. Cell Stem Cell 19, 800–807 (2016).
van der Neut, R., Krimpenfort, P., Calafat, J., Niessen, C. M. & Sonnenberg, A. Epithelial detachment due to absence of hemidesmosomes in integrin β4 null mice. Nat. Genet. 13, 366–369 (1996).
Saab, R., Spunt, S. L. & Skapek, S. X. Myogenesis and rhabdomyosarcoma the Jekyll and Hyde of skeletal muscle. Curr. Top. Dev. Biol. 94, 197–234 (2011).
Hsu, Y.-C., Pasolli, H. A. & Fuchs, E. Dynamics between stem cells, niche, and progeny in the hair follicle. Cell 144, 92–105 (2011).
Hsu, Y.-C., Li, L. & Fuchs, E. Transit-amplifying cells orchestrate stem cell activity and tissue regeneration. Cell 157, 935–949 (2014).
Rando, T. A. & Blau, H. M. Primary mouse myoblast purification, characterization, and transplantation for cell-mediated gene therapy. J. Cell Biol. 125, 1275–1287 (1994).
Fienberg, H. G., Simonds, E. F., Fantl, W. J., Nolan, G. P. & Bodenmiller, B. A platinum-based covalent viability reagent for single-cell mass cytometry. Cytometry 81A, 467–475 (2012).
Ornatsky, O. I. et al. Study of cell antigens and intracellular DNA by identification of element-containing labels and metallointercalators using inductively coupled plasma mass spectrometry. Anal. Chem. 80, 2539–2547 (2008).
Behbehani, G. K. et al. Transient partial permeabilization with saponin enables cellular barcoding prior to surface marker staining. Cytometry A 85, 1011–1019 (2014).
Zunder, E. R. et al. Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm. Nat. Protoc. 10, 316–333 (2015).
Finck, R. et al. Normalization of mass cytometry data with bead standards. Cytometry A 83, 483–494 (2013).
We thank D. Burns and F. Gherardini for valuable discussion; G. Han for help with graphics; M. Kyba for Pax7-ZsGreen transgenic mice and M. A. Rudnicki for Pax7 knockout mice; K. Koleckar, P. Kraft and M. Blake for technical assistance; and the Stanford Shared FACS Facility for technical support. This study was supported by a BD Biosciences Stem Cell grant (E.P.); US National Institutes of Health (NIH) grant K99AG042491 (B.D.C.); Muscular Dystrophy Association (MDA) development grant 217821 (A.T.V.H.), NIH grants NS089533 and AG020961, California Institute for Regenerative Medicine grant RB5-07469 and the Baxter Foundation (H.M.B.).
The authors declare no competing financial interests.
Integrated supplementary information
(a) Intracellular staining of Pax7 by flow cytometry in sorted muscle stem cells (left panel) and myoblasts (right panel). (b) Muscle cells isolated from Pax-Zs green reporter mice were fixed and permeabilized for intracellular staining. Cells were simultaneously stained with antibodies against Zs-Green and Pax7. Cells that were positive for Pax7 were gated and the fraction of Zs-Green+ cells was quantified to be 90%. (c) CyTOF antibody titration. Isotope-chelated anti-mouse antibodies against the surface marker of muscle stem cells, α7 integrin, and intracellular myogenic transcription factors Pax7, MyoD, Myogenin have been titrated using positive (muscle) and negative (spleen) controls to optimize signal, achieve saturation and minimize background. (d) Gating strategy on CyTOF samples as described in Fig. 2a. Individual contour plots are shown. (e) Histogram plot of CD9 (left panels) and CD104 (right panels) expression in MuSCs (upper panels) and myoblasts (lower panels) compared to the respective isotype control. (f) Screening data were analyzed using the Bland-Altman method to measure significant differences in signal intensity (also known as Median Fluorescence Intensity (MFI)) of individual markers in myoblasts compared to MuSCs. The percentage difference from the average MFI (100 × (Myoblast MFI- MuSC MFI)/Average MFI) is plotted (y axis) as a function of the average MFI ((Myoblast MFI + MuSC MFI)/2) (x axis). (g) PCA plot of Live/Lineage−/α7 integrin+/CD9+ cells by population in uninjured (day 0) samples. Protein expression levels were clustered by their log2 median intensities (representative experiment, n = 3 mice).
Supplementary Figure 2 (related to Figure 2 and 3). Functional characterization of the newly identified progenitor population in skeletal muscle.
(a) Representative biaxial dot plots of CD9 (y axis) by CD104 (x axis) colored by channel, showing MAPKAPK2 phosphorylation in populations SC, P1, P2 and P3 in Pax7−/− muscle (right) and WT control (left), isolated from neonates (upper panels) (n = 3 mice, 2 independent experiments) and 3 weeks old mice (lower panels) (n = 1 Pax7−/−; mean ± SEM from n = 10 WT, 2 independent experiments). (b) Representative biaxial dot plots of CD9 by CD104 as in a colored by Myogenin expression. (c) Representative biaxial dot plots of CD9 by CD104 as in a colored by Pax7 expression. (d) Individual populations were sorted by FACS and cultured in differentiation media for one week. Images were acquired with an AxioPlan2 epifluorescent microscope (Carl Zeiss) with ORCA-ER digital camera (Hamamatsu Photonics). Each population was differentiated to yield fusion competent cells (n = 4, 2 independent experiments). Scale bar, 50 μm. (e) Representative images showing the gating strategy on samples analyzed by flow cytometry at day 0 (upper panels) and day 6 (lower panels) (Figure 3d-f). Live cells are identified based on lack of DAPI staining. Lineage+ cells (CD45+/CD11b+/CD31+/Sca1+) are excluded from the analysis and myogenic cells are enriched by gating on the α7integrin+/CD9+ fraction. A biaxial plot of CD9 (y axis) by CD104 (x axis) (far right) shows populations SC, P1 and P2 (representative images, n = 3 mice per condition).
Supplementary Figure 3 (related to Figure 5). Molecular characterization of stem and progenitor cells during acute muscle injury identifies cell state transitions.
(a) Supervised clustering analysis enforcing a 2-cluster solution in the stem (SC) and progenitor (P1, P2) cell populations during the time course of recovery from acute injury (Day 0 = D0; Day 3 = D3; Day 6 = D6), (representative experiment, n = 3 mice per condition). Dendrograms were fitted using hclust function in R. The distance matrix was calculated through the dist function using euclidean parameters. (b) Representative biaxial dot plot of CD9 by CD104 colored by channel, showing expression of CD9 (upper panel) and CD82 (lower panel), in adult mice (n = 6 mice, 2 independent experiments). CD82 is highly expressed only in a small subset of populations P1 and P2.
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Porpiglia, E., Samusik, N., Ho, A. et al. High-resolution myogenic lineage mapping by single-cell mass cytometry. Nat Cell Biol 19, 558–567 (2017). https://doi.org/10.1038/ncb3507
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