Established cell surface markers efficiently isolate highly overlapping populations of skeletal muscle satellite cells by fluorescence-activated cell sorting
© The Author(s). 2016
Received: 8 July 2016
Accepted: 24 September 2016
Published: 8 November 2016
Fluorescent-activated cell sorting (FACS) has enabled the direct isolation of highly enriched skeletal muscle stem cell, or satellite cell, populations from postnatal tissue. Several distinct surface marker panels containing different positively selecting surface antigens have been used to distinguish muscle satellite cells from other non-myogenic cell types. Because functional and transcriptional heterogeneity is known to exist within the satellite cell population, a direct comparison of results obtained in different laboratories has been complicated by a lack of clarity as to whether commonly utilized surface marker combinations select for distinct or overlapping subsets of the satellite cell pool. This study therefore sought to evaluate phenotypic and functional overlap among popular satellite cell sorting paradigms.
Utilizing a transgenic Pax7-zsGreen reporter mouse, we compared the overlap between the fluorescent signal of canonical paired homeobox protein 7 (Pax7) expressing satellite cells to cells identified by combinations of surface markers previously published for satellite cells isolation. We designed two panels for mouse skeletal muscle analysis, each composed of markers that exclude hematopoietic and stromal cells (CD45, CD11b, Ter119, CD31, and Sca1), combined with previously published antibody clones recognizing surface markers present on satellite cells (β1-integrin/CXCR4, α7-integrin/CD34, and Vcam1). Cell populations were comparatively analyzed by flow cytometry and FACS sorted for functional assessment of myogenic activity.
Consistent with prior reports, each of the commonly used surface marker schemes evaluated here identified a highly enriched satellite cell population, with 89–90 % positivity for Pax7 expression based on zsGreen fluorescence. Distinct surface marker panels were also equivalent in their ability to identify the majority of the satellite cell pool, with 90–93 % of all Pax7-zsGreen positive cells marked by each of the surface marker schemes. The direct comparison among surface marker schemes validated their selection for highly overlapping subsets of cells. Functional analysis in vitro showed no differences in the abilities of cells sorted by these different methods to grow in culture and differentiate.
This study demonstrates the equivalency of several previously published and widely utilized surface marker schemes for isolating a highly purified and myogenically active population of satellite cells from the mouse skeletal muscle, which should facilitate cross-comparison of data across laboratories.
KeywordsSatellite cells Surface marker Fluorescence-activated cell sorting
The skeletal muscle is a highly dynamic tissue with a remarkable capacity for rapid regeneration following injury. The essential precursors driving this regenerative process are the satellite cells—a group of mononuclear, self-renewing, and tissue-resident adult stem cells comprising 2–5 % of all muscle nuclei [3, 8, 31]. Satellite cells are classically defined by their stereotypical location between the sarcolemma and basal lamina of multinucleated myofibers and by their expression of the canonical satellite cell regulatory gene, paired homeobox protein 7 (Pax7) [25, 30, 34]. Upon muscle damage and myofiber membrane disruption, satellite cells are exposed to extracellular cues that activate them for re-entry into cell cycle via induced expression of key myogenic regulatory transcription factors [2, 12, 13, 16]. Satellite cells then proliferate and divide [1, 17] to generate differentiated myoblasts that facilitate repair, as well as self-renewed satellite cells that replenish the muscle stem cell pool [8, 12, 23].
Recent studies have emphasized molecular and functional heterogeneity within the satellite cell pool [6, 11, 26]. For example, satellite cells expressing higher levels of Pax7 have been shown to display lower metabolic activity, proliferate less, and possess an increased propensity to self-renew . These transcriptional and functional differences have prompted researchers to classify muscle progenitors in the satellite cell pool hierarchically, with the hope of identifying the best candidate population for clinical and pre-clinical research. Yet, such studies remain dependent on robust methods for collecting these primary cells for study.
Fluorescent-activated cell sorting (FACS) using specific cell surface marker combinations is widely employed as a robust and reliable method for isolating mouse satellite cells from freshly harvested muscle-associated mononuclear cells. The use of cell surface markers has the advantage that it is broadly applicable across a range of mouse strains, ages, and genotypes. Congruently, populations lacking myogenic capabilities have been excluded using other surface markers, such as Sca1 and CD45, which mark muscle-resident and muscle-infiltrating hematopoietic and fibroadipogenic cell types [3, 22]. Yet, within the non-hematopoietic, non-fibroadipogenic subset of muscle mononuclear cells, many surface marker schemes have been reported to positively enrich satellite cells. Some of the cell surface antigens employed are used independently of other positive markers, including VCam1, α7-integrin, NCam1, cMet, m-Cadherin, and Synd3/4 [5, 15, 18, 21, 24, 34], and some are used in combination, including β1-integrin and CXCR4 or α7-integrin and CD34 [11, 14, 19, 29, 32, 33, 35]. However, it remains unknown if all of these surface proteins are expressed on the same satellite cells. Given the known heterogeneity in the satellite cell pool, this creates difficulty for drawing conclusions about satellite cell biology across studies employing different sorting paradigms.
In this study, we used a transgenic Pax7-zsGreen reporter mouse  and a panel of several commonly used surface markers to compare methods for identifying adult mouse satellite cells within a myofiber-associated cell pool by FACS. The markers examined—β1-integrin and CXCR4 , α7-integrin and CD34 , and VCam1 [18, 24]—were chosen based on the prevalence of their use in the field and the availability of well-characterized monoclonal antibodies with compatible fluorochromes. This approach allowed us to explore the overlap in expression of each surface marker-defined population, the efficiency with which each enables selection of muscle satellite cells, and whether multiple surface markers are indeed expressed on the same satellite cells.
Mice and antibodies
Pax7-zsGreen reporter mice  were bred and maintained on a C57BL/6J background at the Harvard University Biological Research Institute. Adult animals (6–12 weeks) of both sexes were used along with age-matched C57BL/6J controls.
The following antibodies were used at a 1:200 titer to exclude cells within hematopoietic and stromal cell types from further analysis: allophycocyanin (APC)-conjugated anti-mouse Ly6A/E (Sca1: Biolegend—clone E3-161.7), APC anti-CD31 (Biolegend—clone 390), APC anti-CD45 (Biolegend—clone 30-F11), APC anti-CD11b (Mac1: Biolegend—clone M1/70), APC anti-Ter119 (Biolegend—clone Ter119). All satellite cell-enriching antibodies were rigorously titered under standard staining conditions of 1E6 cells per 100 μL volume to optimize the separation between positive and negative staining cell populations (Additional file 1: Figure S1). The optimal dilutions for each antibody under these conditions were APC-Cy7 anti-CD29 (β1-integrin, titer 1:100: Biolegend—clone HMβ1-1), biotin anti-CD184 (CXCR4, titer 1:100: BD Biosciences—clone 2B11), phycoerythrin (PE) anti-CD106 (VCam1, titer 1:100: Lifetech—clone M/K-2), PE anti-α7-integrin (titer 1:200: AbLab—clone R2F2), Alexa-Fluor700 anti-CD34 (titer 1:25, e-Biosciences—clone Ram34). A PE-Cy7-streptavidin conjugate (titer 1:200) was used for biotin detection of CXCR4 staining. Both propidium iodide (PI; titer 1:1000: Sigma) and calcein blue (titer 1:1000: Lifetech) were added 5–10 min preceding flow cytometry to evaluate cell viability.
Satellite cell analysis and isolation
Myofiber-associated (MFA) cells were prepared for analysis and FACS from intact skeletal muscles using a two-step enzymatic digestion protocol previously described [14, 32]. Muscles included in this preparation were the triceps brachii, latissimus dorsi, pectoralis, extensor digitorum longus, gastrocnemius, quadriceps, soleus, tibialis anterior, and abdominis. Briefly, pooled muscles harvested from Pax7-zsGreen mice were digested with 0.2 % collagenase type II (285 U/mg, Lifetech) in Dulbecco’s modified Eagle medium (DMEM; Lifetech) for 90 min at 37 °C. The enzyme was inactivated with 20 % fetal bovine serum (FBS) in F10, and muscles were washed in phosphate buffered saline (PBS) and triturated to mechanically dissociate individual fibers from the tissue. The collected fibers were gravitationally sedimented through a series of settling steps at 37 °C for 25, 15, and 10 min, respectively. The fibers were next digested with 0.0125 % collagenase type II and 0.05 % dispase (1.81 U/mg, Lifetech) in F10 for 30 min at 37 °C to release mononuclear cells from fibers. Cells were further separated by pipette, spun at 400 rpm for 15 s to pellet debris, and the supernatant was filtered through a 70 μm cell strainer. Subsequently, cells were counted using a hemocytometer, brought to a total staining volume of 1E6 cells per 100 μL of staining media (2 % FBS in Hank’s Balanced Salt Solution) and split for staining. Based on commercial availability of particular fluorophore conjugates for each of the specific antibody clones needed for this study, we combined satellite cell markers in the following two combinations: β1-integrin, CXCR4, and VCam1 or β1-integrin, CXCR4, α7-integrin, and CD34. All cells were stained with antibodies recognizing Sca1, CD31, CD45, Mac1, and Ter119. Primary antibody incubations were performed on ice for 35 min and streptavidin incubations for 20 min. All cells were sorted twice to maximize cell purity; the three groups of cells sorted from the myogenic fractions were [PI−, calcein+, Sca1−, CD31−, CD45−, Mac1−, Ter119−, β1-integrin+, CXCR4+], [PI−, calcein+, Sca1−, CD31−, CD45−, Mac1−, Ter119−, VCam1+], or [PI−, calcein+, Sca1−, CD31−, CD45−, Mac1−, Ter119−, α7-integrin+, CD34+]. For both sorting and analysis, all gates were established using fluorescence minus one (FMO) controls , which contained cells stained with all fluorophores except the one conjugated to the surface marker of interest. Cell sorting was performed at the Harvard Stem Cell Institute Flow Cytometry core, and flow cytometry data were analyzed using FlowJo (BD Biosciences, 2015) analysis software.
Myogenic colony formation, myogenic commitment, and differentiation assays
For clonal analyses, cells were sorted at one cell per well into 96-well plates containing myogenic growth medium (F10, 20 % Donor Horse Serum, 1 % penicilin-streptomyocin, 1 % glutamax). Sorted cells were cultured for 5 days, with daily addition of 5 ng/mL basic fibroblast growth factor, at which point wells were assessed for visible cell growth. Wells were scored as “positive” in this assay (i.e., containing a cell colony) if two or more cells were detected. Unscored wells contained either no visible cells or only one cell.
For analysis of myogenic commitment, freshly isolated satellite cells were expanded in 24-well plates containing growth media with daily addition of basic fibroblastic growth factor for 5 days. After 5 days, cells were harvested from plates using a final concentration of 2.5 μM EDTA pH 8.0 for 15 min, counted, and seeded at a density of 3000 cells per well in growth medium in 96-well plates. Twenty-four hours later, immunofluorescence was performed using either anti-Pax7 (DSHB, 1/15), anti-MyoD (1/20, sc-760, clone M-318), or anti-Myogenin (1/50, BD Biosciences-556358) primary antibodies.
For analysis of differentiation, cells were expanded for 5 days in 24-well plates containing myogenic growth medium with daily addition of basic fibroblastic growth factor. After 5 days, cells were harvested, re-plated at a density of 3000 or 8000 cells per well and switched to myogenic differentiation media (F10, 2 % Donor Horse Serum, 1 % penicilin-streptomyocin, 1 % glutamax). Cells were allowed to differentiate for 72 h and then fixed with 4 % paraformaldehyde and stained for the differentiation marker myosin heavy chain (MyHC; Sigma fast-M4276 and slow-M8421). Hoechst 33342 was added to mark nuclei.
For all assays, 24- and 96-well plates were coated with a final concentration of 1 μg/ml of collagen type I (Sigma, #C7661) and 10 μg/mL of laminin (Invitrogen, #23017-015) 24 h prior to seeding cells.
Cell imaging and quantification
Imaging and quantification were performed using a Celigo imaging cytometer and software (Nexcelom, 2012). A “differentiation index” was defined using developer software and in-house scripts to determine the fraction of total nuclei contained within myosin heavy chain+ myotubes. Multi-nucleated myotubes at times contain highly dense nuclei that can be difficult to correctly segment into individual nuclei using imaging software. This circumstance can lead to the classification as a single object of a cluster that contains more than one nucleus. Thus, the use of count-based quantification in such instances can lead to inaccurate quantification. To overcome this limitation, we used integrative intensity of nuclear stain (DAPI or Hoechst) for each object rather than raw counts. To ensure capture of fused MyHC+ myotubes and not mononuclear cells expressing MyHC, we first defined the mean area (112.27 μm2) and standard deviation (104.35 μm2) of all single nuclei (objects) from myogenic cultures (representing six individual wells from each cell population: β1-integrin+CXCR4+, Vcam1+, or α7-integrin+CD34+) grown in growth media. Using the equation below, we defined myotubes as any object having an area greater than the mean mononuclear cell area +1 standard deviation (216.62 μm2) and positive for MyHC. Positivity for MyHC was determined based on secondary only control staining. The differentiation index was then defined as the sum of the integrated intensity of Hoechst within all MyHC+ objects meeting the aforementioned size criteria (nuclei within myotubes) divided by the sum of the integrated intensity of ALL objects (total nuclei in mononucleated and multinucleated cells) per well. We find this index to largely recapitulate results obtained from calculation of fusion index using manual cell/nuclear counting (data not shown).
Immunofluorescent staining and microscopy
Cells were fixed with 4 % paraformaldehyde for 20 min and then permeabilized with 0.3 % Triton-X for 20 min at room temperature. Cells were washed for 5 min with PBST three times after fixing and permeabilization. Cells were incubated in blocking media (PBS-T, 3 % bovine serum albumin, 5 % normal goat serum, 8 % protein concentrate (vector labs), and 0.2 % Tween-20) for 2 h at room temperature. Cells were incubated with primary antibody solution in blocking media with antibodies overnight at 4 °C at the following dilutions: 1:200 anti-fast MyHC (Sigma M4276) and 1:100 anti-slow MyHC (Sigma M8421), anti-Pax7 (DSHB, 1/15), anti-MyoD (1/20, sc-760, clone M-318), and anti-Myogenin (1/50, BD Biosciences-556358). After thorough washing (three times, 15 min each in PBST), the secondary antibody solution containing 1:250 goat anti-mouse 488 (Lifetech) or 1:250 goat anti-rabbit 488 (Lifetech) and Hoechst 33342 (Thermofisher) in blocking buffer was incubated for 1 h at room temperature (dilutions used for all immunofluorescent antibodies had previously been titrated in C2C12 differentiated myotubes). Images of sorted cells were obtained using an Axio-Observer inverted light microscope and AxioVision software (Zeiss, 2015). A merged multidimensional acquisition was set up using a 365-nm reflector for Hoechst and a 470-nm reflector for MyHC, Pax7, MyoD, and MyoG.
All statistical analyses were performed using Prism 6 software (GraphPad Software Inc., 2015). Group analyses were done using ordinary one-way ANOVA and comparison between two groups using Student’s t test.
Surface markers used within flow cytometry panels
Using surface markers to distinguish satellite cells has been integral for primary cell isolation by FACS from mouse skeletal muscle. This approach has greatly advanced our understanding of satellite cell biology, with studies examining all facets of satellite cell fate and function, including assessments of gene expression profile and muscle regenerative capacity. However, a lack of clarity regarding the relationship among the different surface marker paradigms used to identify satellite cells has hindered cross-study comparison in the field. Our rigorous comparison of satellite cell surface marker expression, Pax7 positivity, and myogenic activity clearly demonstrates that three highly utilized surface marker combinations efficiently isolate a highly enriched and largely overlapping population of cells from the adult mouse skeletal muscle.
Of note, in our analysis of satellite cells from Pax7-zsGreen transgenic mice, we did not observe enriched expression of any of the surface markers evaluated within the Pax7hi or Pax7lo satellite cell subsets (see Additional file 4: Figure S4). Our observations contrast with a prior analysis of Pax7-nGFP transgenic mice , which indicated that the top 10 % of nGFP+ cells expressed significantly higher levels of CD34 (by FACS and RT-PCR) and of CXCR4 (by RT-PCR). The discrepancy in these two studies regarding the correlation between Pax7 and cell surface marker expression can likely be attributed to one or more key differences in the animal models used to track Pax7 expression. In particular, different spectral properties, sub-cellular localization, and protein stability of monomeric, nuclear GFP protein versus cytoplasmically localized, tetrameric ZsGreen could affect the ability to resolve highly similar sub-populations by FACS. In addition, differences in transgene integration site could impact the overall expression levels of the reporter genes in the two strains in a potentially cell type specific or cell subset specific manner. In any event, regardless of the underlying reasons, these data suggest that the Pax7-zsGreen mouse line may not be optimal for separating Pax7hi cells with unique functional characteristics as described by .
Also of importance, while our data strongly suggest that the three different sorting strategies examined here are essentially interchangeable, both phenotypically and functionally, for isolating satellite cells from the uninjured muscles of adult mice, and thus directly comparable across studies, they do not address the equivalency of these sorting schemes in older animals or from the previously injured muscle. Thus, it will be important in future studies to rigorously examine how expression of these surface markers in satellite cells may be influenced by various muscle injury protocols  or in aged or diseased environments . Nonetheless, these results provide a first step towards harmonizing the field with respect to satellite cell identification and analysis, and we hope these data provide a useful benchmark to facilitate the exchange of information across diverse laboratory groups studying muscle satellite cell biology.
Satellite cell populations freshly isolated from mouse skeletal muscle by surface marker panels using Sca1, CD31, CD45, Mac1, and Ter119 exclusion with positive enrichment for either β1-integrin and CXCR4, VCam1, or α7-integrin and CD34 are highly overlapping.
Equivalent, highly enriched populations of satellite cells can be isolated by each of these three distinct selection schemes.
These three surface marker schemes are phenotypically and functionally interchangeable
Fluorescence-activated cell sorting
Fetal bovine serum
Fluorescence minus one
Myosin heavy chain
Phosphate-buffered saline (-Tween)
Skeletal muscle precursor
We thank the HSCRB flow cytometry core, supported by the Harvard Stem Cell Institute and Stanley Center, for help with flow cytometry, M. Kyba for provision of Pax7-zsGreen mice, and A. Castiglioni for technical assistance.
This study was funded by grants from Atlas Ventures, GlaxoSmithKline, the Paul F. Glenn Foundation, and a Burroughs Wellcome Fund Postdoctoral fellowship Award, and a T32 NIH training grant (5T32DK007260-38) to AEA.
Availability of data and materials
The datasets generated and analyzed during the current study will be made available from the corresponding authors upon reasonable request.
CM isolated satellite cells, performed antibody titrations, FACS, single cell colony formation assays, myogenic differentiation assays, analyzed data, and wrote the paper. AEA designed the research and performed myogenic differentiation assays and Pax7, MyoD, and MyoG IF staining, analyzed data, and wrote the paper. AJW designed research, analyzed data, and wrote the paper. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
All animal experimentation was carried out in accord with animal use protocols reviewed and approved by our Institutional Animal Care and Use Committee (IACUC).
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