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Live cell imaging reveals marked variability in myoblast proliferation and fate

Live cell imaging reveals marked variability in myoblast proliferation and fate Background: During the process of muscle regeneration, activated stem cells termed satellite cells proliferate, and then differentiate to form new myofibers that restore the injured area. Yet not all satellite cells contribute to muscle repair. Some continue to proliferate, others die, and others become quiescent and are available for regeneration following subsequent injury. The mechanisms that regulate the adoption of different cell fates in a muscle cell precursor population remain unclear. Methods: We have used live cell imaging and lineage tracing to study cell fate in the C2 myoblast line. Results: Analyzing the behavior of individual myoblasts revealed marked variability in both cell cycle duration and viability, but similarities between cells derived from the same parental lineage. As a consequence, lineage sizes and outcomes differed dramatically, and individual lineages made uneven contributions toward the terminally differentiated population. Thus, the cohort of myoblasts undergoing differentiation at the end of an experiment differed dramatically from the lineages present at the beginning. Treatment with IGF-I increased myoblast number by maintaining viability and by stimulating a fraction of cells to complete one additional cell cycle in differentiation medium, and as a consequence reduced the variability of the terminal population compared with controls. Conclusion: Our results reveal that heterogeneity of responses to external cues is an intrinsic property of cultured myoblasts that may be explained in part by parental lineage, and demonstrate the power of live cell imaging for understanding how muscle differentiation is regulated. Keywords: Live cell imaging, Single cell analysis, Cell death, Insulin-like growth factors Background Muscle differentiation in culture has been studied pri- Muscle regeneration following injury occurs through marily using endpoint assays that average cellular re- stimulation of muscle stem cells, termed satellite cells sponses across the entire population. These assays [1]. Once activated, satellite cells proliferate to repopu- require analyzing different cohorts of cells at different late the injured area, and then exit the cell cycle to dif- times and have inherently low temporal resolution. Fur- ferentiate and eventually fuse to form new myofibers thermore, most endpoint assays assume homogeneity [1,2]. A similar series of steps occurs during muscle dif- across the entire population. This assumption has been ferentiation in culture. Yet, in both situations not all increasingly questioned by single cell measurements in cells exposed to the same milieu have the same outcome. other systems that find extensive variability within a Some myoblasts continue to proliferate, others die, and population with regard to several critical parameters, in- another fraction becomes quiescent [3-6]. Because pro- cluding levels of gene or protein expression, responses liferation and death can occur simultaneously within a to growth factor-activated signaling pathways, cell-cycle population, and can skew the fraction of cells that ultim- progression, and viability [7-11]. ately differentiate, it has been challenging to determine Live cell imaging resolves several limitations inherent why some cells adopt one fate rather than another. in endpoint assays by allowing the same cells to be tracked with high temporal and spatial fidelity. This sig- * Correspondence: rotweinp@ohsu.edu nificantly improves the amount and quality of acquired Department of Biochemistry and Molecular Biology, Oregon Health & data [12,13]. Furthermore, when combined with lineage Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239-3098, USA © 2013 Gross and Rotwein; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 2 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 tracing, live cell imaging can lead to insights regarding [19,20]. For generation of EGFP-expressing C2 cells, how cell fate decisions occur [8]. These approaches are myoblasts were transduced with the EGFP lentivirus as especially important when identifying mechanisms con- indicated [21]. Over 90% of cells expressed the recom- trolling differentiation, in which a decision regarding the binant protein, and EGFP expression persisted at com- outcome of individual cells could be based on a niche parable levels for more than five additional passages. signal, but could also be heritable or stochastic [14,15]. EGFP-positive and control C2 myoblasts were grown Here we have used live cell imaging and lineage tra- separately and mixed at a 1:4 ratio prior to plating for cing to assess both proliferation and the early phases of live cell imaging. Using a mixed population of myoblasts differentiation in the C2 muscle cell line. Our results re- at this ratio makes it possible to track labeled cells in veal marked variability in both lineage size and fractional dense populations, and is also amenable to automated survival, but remarkable homogeneity within individual tracking, which was not possible from bright field im- lineages in terms of cell fate and behavior. We also ages. For live cell imaging experiments, cells were plated assessed the impact of IGF-I treatment, and found that on 6-well plates and then immediately placed in the although myoblast proliferation and survival increased, IncuCyte FLR (Essen Biosciences, Ann Arbor, MI, USA), cell fate remained similar within lineages. These experi- a microscopy system located inside a standard tissue cul- ments suggest that myoblast fate is not stochastic, and ture incubator. The incubator was maintained at 37°C in provide an approach for discerning how various treat- humidified air with 5% CO . Bright field and EGFP im- ments might alter satellite cell behavior and function. ages were acquired at 10× magnification from four loca- tions per well at 15-min intervals in order to accurately Methods and completely track all labeled cells. The four locations, Materials which were predefined by the imaging system and con- Fetal and newborn calf serum was purchased from sistent across all experiments, were arranged as a square, Hyclone (Logan, UT, USA). Horse serum, goat serum, with each point equidistant from the midpoint of the Dulbecco’s modified Eagle’s medium (DMEM), and PBS well. After 24 h in growth medium cells were washed were from Life Technologies (Carlsbad, CA, USA). Por- with PBS, and differentiation medium (DM, DMEM with cine gelatin was from Sigma (St. Louis, MO, USA), 2% horse serum) was added. For selected wells, R3-IGF-I Hoechst 33258 nuclear dye, from Polysciences (Warring- [2 nM] was added with DM. ton, PA, USA), and R3-IGF-I from GroPep (Adelaide, Australia). The primary antibody to troponin-T (CT3 Image analysis from J. J-C. Lin) was purchased from the Developmental To quantify cell number a module was created using the Studies Hybridoma Bank (Iowa City, IA, USA), and the Cell Profiler software program [22] that loaded EGFP secondary antibody, AlexaFluor 594-conjugated-goat images as a batch, converted images to grayscale, and anti-mouse IgG, was from Life Technologies. C2 myo- performed an illumination correction. EGFP-positive blasts were obtained from Yaffe and Saxel [16], and cells in each field were identified by applying a back- HEK293FT cells were from Life Technologies. Other ground adaptive threshold, which separates primary ob- chemicals were reagent grade and were purchased from jects from the background by setting a threshold at commercial suppliers. twice the value of the mode of the histogram for pixel intensity. Objects identified by the algorithm that were Development of a recombinant lentivirus expressing below 15 microns in diameter were discarded from the EGFP automated count. Cell confluence was calculated for A recombinant lentivirus was generated to express en- each field using an IncuCyte algorithm, which quantifies hanced green fluorescent protein (EGFP) under control the relative cell area in each bright field image. of the EF-1α promoter using as a base Addgene plasmid For our studies we have defined a founder as a cell #12258 (Cambridge, MA, USA). Lentivirus was prepared present at the time of plating, and a lineage as all of the in HEK293FT cells and purified as described [17,18]. progeny of a founder cell. To follow lineages, founder cells Prior to use the virus was diluted in DMEM plus 2% and all progeny were manually tracked using registered fetal calf serum, and filtered through a 0.45 μM Gelman EGFP images starting from the first image obtained. Cells syringe filter (Pall Life Science, Ann Arbor, MI, USA). around the border of each field were excluded from ana- lysis as most tended to exit the viewing area over the Cell culture course of an experiment. Both cell division and death were C2 myoblasts were grown and expanded on tissue cul- readily identified and quantified (see Figure 1). Cell death ture plates coated with 0.2% gelatin in growth medium was easily detected, as it ultimately culminated in cell lysis, (DMEM, 10% heat-inactivated fetal calf serum, and 10% and was preceded by condensation, blebbing, and loss of heat-inactivated newborn calf serum), as described EGFP fluorescence. Additionally, an advantage of live cell Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 3 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 A Myoblast Division Elapsed time: 0 15 30 45 60 75 min B Myoblast Death Elapsed time: 0 15 30 45 60 75 min Figure 1 Visualizing myoblast division and death. (A) Time lapse images (EGFP and bright field) at 15 min increments of an EGFP-labeled myoblast undergoing mitosis. (B) Time lapse images (EGFP and bright field) at 15 min increments of myoblast death. The arrows point to EGFP- labeled myoblasts. The white arrows indicate cells that began to die prior to the first frame, and illustrate loss of EGFP fluorescence and detachment over time of observation. The yellow arrows mark cells that condensed and underwent death during the period of observation. Loss of EGFP fluorescence and detachment occurred during the subsequent 60 min (not shown). imaging is that subsequent tracking of same area of the a correlation between random cells, we randomized the field could confirm that death occurred. pairings and performed the same test. Results were con- sidered statistically significant when P ≤0.01. Immunocytochemistry To analyze muscle differentiation, plates that had been Results imaged for 90 h (24 h in growth medium plus 66 h in Defining myoblast dynamics by live cell imaging DM) were washed with PBS, fixed with paraformalde- We employed live cell imaging to track myoblast prolifer- hyde for 10 min, and washed again with PBS followed by ation and monitor survival during a differentiation time a 90-s treatment with 50% acetone - 50% methanol, as course. To study myoblast dynamics, we plated a mixture described [19,20]. After three additional PBS washes of unmarked myoblasts with myoblasts expressing EGFP wells were incubated with 0.25% goat serum in PBS under control of the constitutively active EF-1α promoter, for ≥2 h to block non-specific antibody binding, followed and tracked EGFP-positive cells every 15 min using an au- by incubation overnight at 4°C with troponin-T primary tomated cell counting algorithm (Figure 2A). We found antibody (1:100 dilution), washing with PBS, and incubation that a mixed population was necessary for accurate track- for 90 min at 20°C with AlexaFluor 594-conjugated-goat ing once the cells reached confluence. We observed a pro- anti-mouse IgG (1:3,000 dilution) and Hoescht nuclear dye. gressive increase in cell number with an average doubling Cells were visualized with a Nikon Eclipse Ti-U inverted time of 17.6 h during the initial 24 h of incubation microscope and a Nikon DS-Qi1Mc camera using the NIS (Figure 2B). After 24 h, high serum growth medium elements 3.1 software. was replaced with low serum differentiation medium (DM). Following addition of DM, cell number contin- ued to increase, leading to a peak in myoblast number Statistical analysis between 8 and 14 h after medium was changed. Cell To assess observed cell viability data, we first calculated number then progressively declined, but began to the number of living and dead cells among sibling pairs. stabilize by the end of the recording period after 36 h Cells that failed to divide, or that had a sibling that in DM (Figure 2B). When myoblasts were plated at similar underwent a second division, were not entered into this densities these patterns were consistent across multiple lo- analysis since they had no comparable sibling. This ex- cations in a single well and across independent experi- cluded 16 cells, which had a percent survival of 25%. As- ments (Figure 2B and Additional file 1: Figure S1A, B), suming random death between pairs of cells, we but varied in degree and timing when cells were plated at calculated the expected number of pairs composed of higher or lower densities (Additional file 1: Figure S1C). two living myoblasts, a living and a dead cell, or two Tracking cells beyond 60 h revealed that EGFP- dead cells. Expected frequencies were then compared to positive myoblasts fused with both EGFP-expressing and observed data using a χ-squared test with two degrees of non-labeled cells to form multinucleated myotubes freedom. To test for a relationship between a variable in (Additional file 2: Figure S2). These results were con- sibling pairs (cell cycle duration or time to death), we firmed by identifying troponin-expressing cells by calculated the Pearson correlation coefficient. To test for 350 30 40 50 60 0 10 20 10 20 30 40 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 4 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 measures of cell number. Immediately upon plating, confluence was approximately 20% and cell number was Phase Contrast/EGFP Cell Counting approximately 25% of its maximum value (Figure 2C). Cells soon spread out and began to divide so that by 10 h in culture when the EGFP-positive myoblast number per field was approximately 30% to 40% of maximal, con- fluence had reached approximately 85% to 95% (Figure 2C). By 24 h in growth medium when the cell number was ap- proximately 70% to 80% of maximal, confluence was ap- proximately 99%, and it remained constant despite a GM DM further rise in myoblast number (Figure 2C). Thus, conflu- ence and cell number are poorly correlated. Defining myoblast population kinetics Our automated counting algorithm measured changes in cell number, but was unable to quantify individual in- Experiment: stances of cell death or division. In order to quantify #1 death and division, we manually tracked myoblasts and #2 #3 their progeny over a 60-h incubation period. Both cell division and death could be readily detected and moni- Time (hr) tored (Figure 1 and Additional files 3 and 4: Movie). During cell division, cells condensed into a circular GM DM shape, which was followed by mitosis and emergence of two progeny (Figure 1A). Cell death was detected by shrinkage, blebbing, lysis, and the ultimate loss of EGFP fluorescence (Figure 1B). Comparing manual and auto- mated measures of the total cell number revealed similar kinetics, thus validating the automated cell counting al- gorithm (Additional file 1: Figure S1A, B). Experiment: #1 Cell tracking revealed that myoblast proliferation con- #2 Cell confluence #3 tinued well after DM was added (Figure 3A, B, Additional #1 #2 Cell number file 5: Figure S3). Cell death was largely absent during the #3 24 h in GM, but was extensive after addition of DM so that cell division and death were occurring simultaneously Time (hr) (Figure 3C, Additional file 5: Figure S3). Addition of IGF-I Figure 2 Defining myoblast dynamics by live cell imaging. C2 ([2 nM] R3-IGF-I) with DM led to a rise in the maximal myoblasts were mixed at a 1:4 ratio with C2 cells stably infected myoblast number over controls (Figure 3A). This was a with an EGFP gene under control of the EF-1α promoter, and the consequence of an increase in cell division and a reduc- EGFP-expressing myoblasts were tracked at 15-min intervals using an automated cell counting algorithm. See ‘Methods’ for additional tion in myoblast death (Figure 3B, C). details. (A) Phase contrast image of EGFP-positive myoblasts (left) and the corresponding image of the same microscopic field with EGFP-expressing cells identified by an automated cell counting Myoblast lineage analysis algorithm. (B) Cell number as a function of time in culture for three To assess myoblast fate, we tracked 79 founder cells and independent experiments (blue, green, and red). Each dot represents their progeny starting from the time of plating, and mea- a single measurement. (C) Percentage of maximum cell number sured multiple kinetic parameters (Figure 4A). For the (closed dots) and percent confluence (open dots) as a function of purpose of our studies, we define lineage as all the pro- time in culture for three independent experiments (blue, green, and red). geny of a single cell, and fate as a specific outcome (for example, survival, death, differentiation). For each lineage, we recorded the duration from the start of im- immunocytochemistry (Additional file 2: Figure S2). Thus, aging until a founder cell divided, labeled as the time to neither EGFP expression nor live cell imaging compromised the first cell division (Figure 4A). This initial division muscle differentiation. produced two cells, sibling A and sibling B. The time Since confluence is frequently used to establish when from the first cell division to the division of each sibling DM is added, we tracked confluence and compared it to was recorded as the first full cell cycle (Figure 4A). Data EGFP+ cells/field Maximum value (%) 350 30 40 50 60 0 10 20 30 40 50 60 0 10 20 10 20 30 40 50 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 5 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 A A Sibling B GM DM ± IGF-I Founder Cell Myoblast Time to first cell division Living Sibling A Number Dead First full cell cycle No IGF-I + IGF-I GM DM Time (hr) Lineage A Lineage B Time (hr) GM DM ± IGF-I Myoblast Division Lineage C No IGF-I + IGF-I GM DM 024 60 Time (hr) Figure 4 Studying the fate of individual myoblasts. (A) Schematic of a hypothetical myoblast lineage tree, with different features indicated on the timeline. (B) Examples of three actual cell lineages with progeny and fates of individual cells indicated. Time (hr) GM DM ± IGF-I Myoblast from three lineages that varied in outcomes are depicted Death in Figure 4B. No IGF-I By tracking the time from plating until the first cell + IGF-I division, we found a relatively broad distribution that ranged from 2 to 30 h (Figure 5A). This illustrated that the start of cell division was asynchronous in the popu- lation. We next tracked cell cycle duration using the first full cell cycle following the division of each founder cell. This varied across the population from 8 to 26 h with a mean of 14.2 h (Figure 5B). The mean cell cycle duration was shorter than the population doubling time, due in Time (hr) part to eight of 79 founder myoblasts that failed to div- Figure 3 Defining myoblast population kinetics by live cell ide over the entire 60-h time course. imaging. Individual EGFP-expressing myoblasts were studied as in Despite the range of cell cycle durations in the popula- Figure 2 using manual counting. Differentiation medium (DM) was added ± IGF-I (R3-IGF-I [2 nM]), as indicated. (A) Effect of IGF-I on total tion, there was a remarkably close correlation between cell number. (B) Effect of IGF-I on the frequency of cell division (DM siblings (Figure 5C). This relationship was not detected 234 divisions; IGF-I 344 divisions). (C) Effect of IGF-I on myoblast death between cells paired randomly (Figure 5D). Between sib- (DM 208 deaths; IGF-I 154 deaths). For A to C, blue depicts control cells lings the Pearson correlation coefficient for cell cycle and red, myoblasts incubated with IGF-I. For B and C, the number of -13 duration was 0.85 (P = 1.834e ), but between random cells exhibiting a specific trait at a given time is plotted on the y-axis. pairs of cells it was −0.07 (P = 0.631). Number of EGFP+ cells Number of EGFP+ cells EGFP+ cells 20 22 26 28 8 12 16 4 8 12 16 20 24 14 18 22 18 22 6 10 6 10 14 14 14 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 6 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 A B 10 16 0 0 Time to first cell division (hr) Duration of first cell cycle (hr) C D Cell Cycle Duration (hr) Cell Cycle Duration (hr) Sibling B Random Cell B Figure 5 The cell-cycle duration of individual C2 myoblasts is heterogeneous. Individual EGFP-expressing myoblasts were monitored at 15-min intervalsasinFigures 1and 2. (A) Asynchronous entry of myoblasts into the cell cycle, as measured by the time from plating until the first cell division. The number of myoblasts undergoing mitosis at a given time is plotted on the y-axis. (B) Frequency distribution of the duration of the first full cell cycle. The number of myoblasts exhibiting a given cell cycle duration is plotted on the y-axis. (C) Close correlation (0.85, Pearson correlation coefficient) of cell -13 cycle duration between siblings (progeny of the same cell division; P =1.834e , t = 11.14, degrees of freedom (DF) = 49). (D) No correlation was observed for randomly paired cells (−0.07; P = 0.631, t = −0.4834, DF = 49)). We next assessed cell viability, since it has been shown both dying being reversed (P <0.0001). These results in- that a significant fraction of myoblasts undergo apop- dicate that survival was not purely stochastic, but in- totic death during incubation in DM [23-27]. For this stead was biased by parental lineage. analysis, we compared the survival of 149 sibling pairs When the time from last division to death was tracked (298 total cells). As depicted in Figure 6A, over 60% of between concordant siblings (Figure 6B), we found a close cells died in DM. When survival and death were correlation similar to that seen with cell cycle duration, assessed on the basis of parentage, we found that 73% of further reinforcing the importance of parental lineage. siblings had concordant fates, with 49% both dying and The Pearson correlation coefficient for time to death be- -12 24% both living, and 27% were discordant, with one tween siblings was 0.72 (P =2.247e ), while by contrast myoblast living and the other dying (Figure 6A). The between random cells the value was 0.12 (P = 0.3271) number of shared fates between siblings was significantly (Figure 6C). larger than expected if survival occurred solely by chance (values expected if cell death is random: 40.3% Heterogeneity among myoblast lineages both die, 13.3% both live, 46.4% discordant (P <0.0001)). We next sought to analyze how concordance between Similarly, even though incubation with IGF-I reduced siblings altered lineage outcomes during muscle differ- the percentage of cells that died (Figure 3), concordance entiation. We found that lineage sizes were unequal as among siblings was 75% (50% both living and 25% both a consequence of variable rates of cell division and sur- dying, Additional file 6: Figure S4). This bias toward vival. A fraction of lineages failed to divide, another concordant sibling fates was nearly identical to that ob- fraction underwent fewer than two cell divisions, and served in cells incubated with DM alone (Figure 6A), another had multiple divisions (Figure 7). Myoblast despite the percentages of both myoblasts living and survival also was heterogeneous, as some lineages of Cell Cycle Duation (hr) Random Cell A Cell Cycle Duration (hr) Number of EGFP+ cells Sibling A Number of EGFP+ cells 300 10 20 30 40 50 0 10 20 30 0 10 20 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 7 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 GM DM Sibling Outcomes Both live (24%) One lives (27%) One dies Both die (49%) Time (hr) B C Time to Death (hr) Time to Death (hr) Sibling B Random Cell B Figure 6 Concordance of myoblast fate. Individual EGFP-expressing myoblasts were analyzed at 15-min intervals as in Figures 1 and 2. (A) The line plot shows the fate of each myoblast (n = 298). Each horizontal line indicates a survival timeline for a single myoblast with the left end representing the time after the last cell division (= starting point), and the right end indicating either the time of death or survival to 36 h in DM. Concordance or discordance of outcomes between siblings is indicated (black and blue lines reflect concordance, red discordance). The number of identical fates between siblings was significantly larger than expected by chance (χ = 21.064, DF = 2, two-tailed P <0.0001). (B, C) Correlation -12 of time of cell death for siblings (Pearson correlation coefficient between sibling cells was 0.7196 (P <2.247e , t = 8.733, DF = 71) and between randomly paired cells was 0.1163 (P <0.3271, t = 0.9868, DF = 71)). Time to Death (hr) Individual EGFP+ Cells Sibling A Time to Death (hr) Random Cell A 60 0 10 20 30 40 50 0 10 20 30 40 50 60 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 8 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 A B 15 15 DM DM + IGF-I Alive Alive 0 0 -5 -5 Dead Dead -10 -10 GM DM GM DM + IGF-I C D ≥3 Survivors ≥3 Survivors 1-2 Survivors 60 1-2 Survivors 0 Survivors 20 20 0 Survivors Time (hr) Time (hr) Figure 7 Myoblast lineages are heterogeneous. EGFP-expressing myoblasts were studied as in Figure 1. Differentiation medium (DM) was added ± IGF-I (R3-IGF-I (2 nM)), as indicated. (A, B) Line plots showing the number of cells derived from each lineage and the outcome (alive or dead) tracked on the y-axis. (C, D). Variation in outcomes of progeny for individual founder myoblasts leads to a shift in the population. The population number was normalized across time. Red, founder cells and their progeny with zero surviving myoblasts; green, founders with 1 to 2 survivors; blue, lineages with ≥3 survivors. similar size maintained 100% viability, others under- 20% of the initial population to approximately 60% of went 100% death, and others had mixed outcomes the final cohort (Figure 7C, red). Thus, the overall popu- (Figure 7A). Incubation of myoblasts in DM with IGF-I lation at the end of the experiment differed substantially led to a higher fraction of lineages with 100% survival, from the population at the start. but IGF-I was not able to rescue all lineages since 16 In myoblasts incubated in DM plus IGF-I the relative (approximately 20%) still underwent complete death number of lineages in each group was different. IGF-I (Figure 7B). Thus, myoblast lineage size and viability treatment resulted in only 20% of founders not being were variable. represented in the final population, and 57% of founders To assess how heterogeneity in lineage size or survival comprised 85% of the final group (Figure 7D). Thus, might be reflected in the total population after a differ- addition of IGF-I in DM maintained the myoblast entiation time course, we plotted the number of living lineage distribution so that it more closely resembled the myoblasts in each lineage over time, grouping lineages population at the start. according to outcome. We found that the population was evenly represented by each of the founder cell line- Discussion ages during incubation in growth medium, but not after Here we have used live cell imaging and lineage tracing addition of DM. One group of myoblasts, comprising to address the dynamics of muscle cell proliferation and approximately 40% of the initial population (Figure 7C, survival in the C2 myoblast cell line. We find a wide green tracing), maintained a similar representation for variation in the rate and extent of both proliferation and the entire culture period, while another equivalently viability of myoblasts derived from different parental sized group of founders failed to have one cell survive cells, but concordant behavior in cells arising from the after incubation in DM (Figure 7C, red). In contrast, a same parents. As a consequence, the population of myo- third group significantly expanded from approximately blasts undergoing differentiation varied substantially Population (%) Number of EGFP+ Myoblasts Population (%) Number of EGFP+ Myoblasts Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 9 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 from the cells present at the start of an experiment. response to muscle injury in vivo, satellite cell prolifera- Addition of IGF-I to DM reduced population heterogen- tion is followed by a period of satellite cell death [6]. We eity primarily by sustaining myoblast viability, and thus found that the net decline in cell number following 36 h increased the number and sizes of surviving lineages. As in DM was approximately 35%. This is in line with the a result, the terminal population more closely resembled 20% to 30% value previously reported with endpoint the cohort of myoblasts at the start than it did in un- methods, including TUNEL assays, cell counting, and treated cells. Our observations reveal that under stand- ‘live-dead’ staining [25,35]. Yet, by tracking both the div- ard treatment protocols extensive heterogeneity is an ision and death of individual cells, we found that over intrinsic property of cultured myoblasts, and that an ef- 60% of the population died during 36 h in DM, with the fect of IGF-I is to decrease this variability. majority of death occurring during the initial 15 h (Figure 3C). This value differed substantially from cell Myoblast population features number calculations because of concurrent proliferation of We found that cell cycle durations were heterogeneous other EGFP-labeled myoblasts during incubation in DM. across the population and that cell division continued after Thus, we suggest that traditional apoptosis assays under- DM was added. The average cell cycle duration of the estimate the extent of myoblast death by failing to account population in growth medium was 14.2 h. This value for ongoing proliferation of other cells in the culture. matches doubling times of C2 myoblasts obtained by other By identifying and tracking individual myoblasts and approaches, including labeling of DNA synthesis and direct their offspring, we found that cell death was not ran- cell counting [23], but was easier to acquire and potentially dom. Rather, siblings were biased toward adopting con- more accurate, since individual myoblasts were tracked ra- cordant fates after incubation in DM. The tendency ther than averaging multiple time points from different toward common outcomes was maintained even in groups of cells. Despite agreement of our data with previ- cells exposed to IGF-I, despite enhanced myoblast sur- ous observations, we found that the cell cycle duration of vival from IGF-I treatment (Figure 3C, Additional file 4: individual myoblasts varied extensively (range, 8–26 h), and Figure S4). The mechanisms responsible for these biases that approximately 10% of the founder cells failed to divide are unclear, but could arise from genetic or epigenetic dif- once over the entire 60-h tracking period. Remarkably, ferences, or from environmental influences. We suspect these observations are similar to results obtained with satel- that a fraction of the bias may be explained by similar lite cells derived from dissociated single muscle fibers [28], levels or activity of the IGF-I - PI3-kinase - Akt signaling where both the onset of proliferation and individual cell pathway between related cells, since exposure to IGF-I re- cycle durations varied in the population (range, 5.1-17.8 h), duced myoblast death, but maintained concordant fates and approximately 16% of cells failed to divide once [28]. between siblings. It is therefore possible that cells of By assessing myoblast lineage, we observed that there shared parentage inherit similar amounts of signaling was a close correlation between the cell cycle durations components, and/or share epigenetic or genetic alter- of siblings (Figure 5C), in remarkable agreement with an ations that affect regulation of this pathway. This is observation noted more than 25 years ago in primary consistent with observations that cell siblings adopt quail myoblasts [29]. These similarities between cells of concordant fates in response to apoptosis-inducing shared parentage in both primary myoblasts and a muscle agents because of a common inheritance of proteins cell line point to the potential importance of heritability from their mother [7,8]. Alternatively, as siblings share and the immediate environment in regulating cell fate. a similar microenvironment, we cannot exclude the Myoblast differentiation requires exit from the cell cycle possibility that paracrine factors also contribute to the in G1 [30-32]. Since our data showed that cell division con- regulation of cell survival. tinued well after addition of DM in a fraction of cells, this The main impact of cell death not being random was a dramatic change in the composition of the myoblast indicates that the onset of muscle differentiation is hetero- geneous. Furthermore, since IGF-I treatment prolonged population by the end of the culture period. This was the time of cell division, it is likely to increase the duration not apparent during the initial 24 h of incubation in growth medium because myoblast viability was complete over which cells exit the cell cycle (Figure 3B). This prob- lem of variability is further compounded by methods that and most of the cells underwent at least one cell division rely on confluence to mark the time when DM should be (Figure 5). Variability arose, however, during the subse- quent 36 h in DM, as distinct subpopulations developed added [33,34], since confluence is relatively difficult to visu- ally quantify, and as seen here, small changes in confluence rapidly from heterogeneous cell division coupled with can equate to large differences in cell numbers (Figure 2B). variable survival. This led to substantial differences in the contributions of different lineages to the final myoblast It is well known that a fraction of cultured myoblasts succumb to apoptotic cell death during incubation in population (Figure 6A, 7, Additional file 6: Figure S4). DM [23-25,35]. Similarly, it has been reported that in Our results suggest that measurements that average Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 10 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 cellular characteristics during a differentiation time remarkable homogeneity within individual lineages in course, such as immunoblots or gene expression assays, terms of cell fate. Treatment with IGF-I increased myo- can obscure the properties of subpopulations. blast number by maintaining viability and by stimulating a fraction of cells to complete one additional cell cycle Impact of IGF-I on myoblast proliferation, survival, and in DM, and as a consequence reduced the variability of differentiation the terminal population compared with controls. Our re- IGF-I exerts potentially contradictory effects on muscle cells, sults reveal that heterogeneity is an intrinsic property of including promoting both proliferation and differentiation cultured myoblasts, and demonstrate the power of live [33]. Our observations suggest one resolution to this prob- cell imaging to provide insights into the regulation of lem. Analysis of the onset of the last division revealed that muscle differentiation. IGF-I led to an average delay of approximately 5 h com- pared with untreated controls (Figure 3B, Additional file 6: Additional files Figure S4). As this delay did not lead to more than one add- Additional file 1: Figure S1. Characterizing myoblasts by live cell itional cell division, our interpretation is that the main action imaging. C2 cells were mixed at a 1:4 ratio with C2 myoblasts stably of IGF-I is to maintain myoblast survival so that otherwise infected with an EGFP gene under control of the EF-1α promoter. The vulnerable cells are able to complete a single final round of EGFP-expressing myoblasts were tracked at 15-min intervals. (A) Concordance between results of manual and automated cell counting. replication. These effects of IGF-I complicate comparisons Cells were incubated for 60 h, with DM ± IGF-I (R3-IGF-I [2 nM]) being with untreated cells, as both fractional myoblast survival added for the last 36 h (red traces). Solid lines represent manual tracking and the starting points for differentiation are different. Fu- of lineages and dots represent automated counting. (B) Reproducibility of automated cell counting. Four wells were plated with an identical ture applications of reporters for different aspects of differ- number of cells, and were incubated for 60 h, with DM ± IGF-I being entiation are needed to improve our understanding of the added for the last 36 h. (C) Effects of plating density on myoblast kinetics and regulation of muscle differentiation by separat- dynamics. Cells were plated at varying concentrations, and EGFP-positive cells were identified by automated counting at 15-min intervals for 60 h. ing out these confounding factors. Additional file 2: Figure S2. EGFP-expressing myoblasts undergo differentiation. Confluent myoblasts were incubated in DM for 66 h. (A) Satellite cell fate and muscle regeneration Live cell images of EGFP fluorescence were captured (10× magnification). An important question in skeletal muscle biology is how (B) Differentiating myoblasts were fixed and stained with antibodies to troponin-T (red), and nuclei were stained with Hoescht dye (blue, 100× satellite cell fate is regulated during muscle regeneration. magnification). Following injury, satellite cells must divide sufficiently to Additional file 3: Movie 1. Live cell imaging of C2 myoblasts. Live cell insure adequate numbers of differentiating myoblasts for imaging of C2 myoblasts for 60 h (24 h in growth medium, 36 h in DM). immediate muscle repair, but also must maintain a re- Fluorescent images were captured every 15 min. serve population for regeneration after subsequent injury Additional file 4: Movie 1. Live cell imaging of C2 myoblasts with manual tracking overlay. Live cell imaging of C2 myoblasts for 60 h (24 h [4,6,36]. Thus, multiple cell fate decisions are necessary in growth medium, 36 h in DM). Fluorescent images were captured every to ensure adequate current and future muscle repair. 15 min. Live cell imaging has begun to be applied to this ques- Additional file 5: Figure S3. Reproducibility of myoblast dynamics by tion, and has revealed the importance of asymmetric live cell imaging. Individual EGFP-expressing myoblasts were manually tracked at 15-min intervals in three independent experiments, as in and symmetric satellite cell divisions [14,37,38]. Other Figure 3. Left panels: cell number measured as a function of time in studies have shown that the satellite cell population is culture. Center panels: frequency of cell division analyzed as a function of very heterogeneous, not only in terms of its behavior in time in culture. Right panels: frequency of myoblast death recorded as a function of time in culture. response to proliferative or migratory cues [28,39], but Additional file 6: Figure S4. IGF-I promotes myoblast proliferation and also with respect to cell of origin [36], and surface pro- enhances viability. Individual EGFP-expressing myoblasts were analyzed at tein expression [6,40]. Thus both environmental and 15-min intervals as in Figures 3 and 6. The line plot shows the fate of genetic factors potentially play influential regulatory each myoblast (n = 372). Each horizontal line indicates a survival timeline for a single myoblast with the left end representing the time after the roles in muscle regeneration through effects on satellite last cell division (= starting point), and the right end indicating either the cells. Elucidating how this heterogeneity impacts the de- time of death or survival to 36 h in DM. Concordance or discordance of cisions that lead to satellite cell differentiation will be outcomes is indicated (black and blue lines reflect concordance, red discordance). The number of identical fates between siblings was critical to understanding the dynamics of muscle regen- significantly larger than expected by chance (χ =45.581, DF =2, two-tailed eration and how under certain circumstances such as P <0.0001). aging this process can go awry. Abbreviations Conclusions DM: Differentiation medium; DMEM: Dulbecco’s modified Eagle’s medium; EGFP: Enhanced green fluorescent protein; GM: Growth medium; IGF- We have used live cell imaging and lineage tracing to as- I: Insulin like growth factor-I; PBS: Phosphate buffered saline.. sess both proliferation and the early events of differenti- ation in C2 myoblasts. Our results reveal marked Competing interests variability in lineage size and fractional survival, but The authors declare that they have no competing interests. Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 11 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 Authors’ contributions 23. 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Guasconi V, Puri PL: Chromatin: the interface between extrinsic cues and variability in myoblast proliferation and fate. Skeletal Muscle 2013 3:10. the epigenetic regulation of muscle regeneration. Trends Cell Biol 2009, 19:286–294. 16. Yaffe D, Saxel O: Serial passaging and differentiation of myogenic cells isolated from dystrophic mouse muscle. Nature 1977, 270:725–727. 17. Mukherjee A, Wilson EM, Rotwein P: Selective signaling by Akt2 promotes bone morphogenetic protein 2-mediated osteoblast differentiation. Mol Cell Biol 2010, 30:1018–1027. 18. Mukherjee A, Rotwein P: Selective signaling by Akt1 controls osteoblast Submit your next manuscript to BioMed Central differentiation and osteoblast-mediated osteoclast development. Mol Cell Biol 2012, 32:490–500. and take full advantage of: 19. Lawlor MA, Feng X, Everding DR, Sieger K, Stewart CE, Rotwein P: Dual control of muscle cell survival by distinct growth factor-regulated • Convenient online submission signaling pathways. Mol Cell Biol 2000, 20:3256–3265. • Thorough peer review 20. Wilson EM, Tureckova J, Rotwein P: Permissive roles of phosphatidyl inositol 3-kinase and Akt in skeletal myocyte maturation. Mol Biol Cell • No space constraints or color figure charges 2004, 15:497–505. • Immediate publication on acceptance 21. Gardner S, Anguiano M, Rotwein P: Defining Akt actions in muscle • Inclusion in PubMed, CAS, Scopus and Google Scholar differentiation. Am J Physiol Cell Physiol 2012, 303:C1292–C1300. 22. Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, Guertin • Research which is freely available for redistribution DA, Chang JH, Lindquist RA, Moffat J, Golland P, Sabatini DM: Cell Profiler: image analysis software for identifying and quantifying cell phenotypes. Submit your manuscript at Genome Biol 2006, 7:R100. www.biomedcentral.com/submit http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Skeletal Muscle Springer Journals

Live cell imaging reveals marked variability in myoblast proliferation and fate

Skeletal Muscle , Volume 3 (1) – May 2, 2013

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Copyright © 2013 by Gross and Rotwein; licensee BioMed Central Ltd.
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Life Sciences; Cell Biology; Developmental Biology; Biochemistry, general; Systems Biology; Biotechnology
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2044-5040
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10.1186/2044-5040-3-10
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23638706
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Abstract

Background: During the process of muscle regeneration, activated stem cells termed satellite cells proliferate, and then differentiate to form new myofibers that restore the injured area. Yet not all satellite cells contribute to muscle repair. Some continue to proliferate, others die, and others become quiescent and are available for regeneration following subsequent injury. The mechanisms that regulate the adoption of different cell fates in a muscle cell precursor population remain unclear. Methods: We have used live cell imaging and lineage tracing to study cell fate in the C2 myoblast line. Results: Analyzing the behavior of individual myoblasts revealed marked variability in both cell cycle duration and viability, but similarities between cells derived from the same parental lineage. As a consequence, lineage sizes and outcomes differed dramatically, and individual lineages made uneven contributions toward the terminally differentiated population. Thus, the cohort of myoblasts undergoing differentiation at the end of an experiment differed dramatically from the lineages present at the beginning. Treatment with IGF-I increased myoblast number by maintaining viability and by stimulating a fraction of cells to complete one additional cell cycle in differentiation medium, and as a consequence reduced the variability of the terminal population compared with controls. Conclusion: Our results reveal that heterogeneity of responses to external cues is an intrinsic property of cultured myoblasts that may be explained in part by parental lineage, and demonstrate the power of live cell imaging for understanding how muscle differentiation is regulated. Keywords: Live cell imaging, Single cell analysis, Cell death, Insulin-like growth factors Background Muscle differentiation in culture has been studied pri- Muscle regeneration following injury occurs through marily using endpoint assays that average cellular re- stimulation of muscle stem cells, termed satellite cells sponses across the entire population. These assays [1]. Once activated, satellite cells proliferate to repopu- require analyzing different cohorts of cells at different late the injured area, and then exit the cell cycle to dif- times and have inherently low temporal resolution. Fur- ferentiate and eventually fuse to form new myofibers thermore, most endpoint assays assume homogeneity [1,2]. A similar series of steps occurs during muscle dif- across the entire population. This assumption has been ferentiation in culture. Yet, in both situations not all increasingly questioned by single cell measurements in cells exposed to the same milieu have the same outcome. other systems that find extensive variability within a Some myoblasts continue to proliferate, others die, and population with regard to several critical parameters, in- another fraction becomes quiescent [3-6]. Because pro- cluding levels of gene or protein expression, responses liferation and death can occur simultaneously within a to growth factor-activated signaling pathways, cell-cycle population, and can skew the fraction of cells that ultim- progression, and viability [7-11]. ately differentiate, it has been challenging to determine Live cell imaging resolves several limitations inherent why some cells adopt one fate rather than another. in endpoint assays by allowing the same cells to be tracked with high temporal and spatial fidelity. This sig- * Correspondence: rotweinp@ohsu.edu nificantly improves the amount and quality of acquired Department of Biochemistry and Molecular Biology, Oregon Health & data [12,13]. Furthermore, when combined with lineage Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239-3098, USA © 2013 Gross and Rotwein; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 2 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 tracing, live cell imaging can lead to insights regarding [19,20]. For generation of EGFP-expressing C2 cells, how cell fate decisions occur [8]. These approaches are myoblasts were transduced with the EGFP lentivirus as especially important when identifying mechanisms con- indicated [21]. Over 90% of cells expressed the recom- trolling differentiation, in which a decision regarding the binant protein, and EGFP expression persisted at com- outcome of individual cells could be based on a niche parable levels for more than five additional passages. signal, but could also be heritable or stochastic [14,15]. EGFP-positive and control C2 myoblasts were grown Here we have used live cell imaging and lineage tra- separately and mixed at a 1:4 ratio prior to plating for cing to assess both proliferation and the early phases of live cell imaging. Using a mixed population of myoblasts differentiation in the C2 muscle cell line. Our results re- at this ratio makes it possible to track labeled cells in veal marked variability in both lineage size and fractional dense populations, and is also amenable to automated survival, but remarkable homogeneity within individual tracking, which was not possible from bright field im- lineages in terms of cell fate and behavior. We also ages. For live cell imaging experiments, cells were plated assessed the impact of IGF-I treatment, and found that on 6-well plates and then immediately placed in the although myoblast proliferation and survival increased, IncuCyte FLR (Essen Biosciences, Ann Arbor, MI, USA), cell fate remained similar within lineages. These experi- a microscopy system located inside a standard tissue cul- ments suggest that myoblast fate is not stochastic, and ture incubator. The incubator was maintained at 37°C in provide an approach for discerning how various treat- humidified air with 5% CO . Bright field and EGFP im- ments might alter satellite cell behavior and function. ages were acquired at 10× magnification from four loca- tions per well at 15-min intervals in order to accurately Methods and completely track all labeled cells. The four locations, Materials which were predefined by the imaging system and con- Fetal and newborn calf serum was purchased from sistent across all experiments, were arranged as a square, Hyclone (Logan, UT, USA). Horse serum, goat serum, with each point equidistant from the midpoint of the Dulbecco’s modified Eagle’s medium (DMEM), and PBS well. After 24 h in growth medium cells were washed were from Life Technologies (Carlsbad, CA, USA). Por- with PBS, and differentiation medium (DM, DMEM with cine gelatin was from Sigma (St. Louis, MO, USA), 2% horse serum) was added. For selected wells, R3-IGF-I Hoechst 33258 nuclear dye, from Polysciences (Warring- [2 nM] was added with DM. ton, PA, USA), and R3-IGF-I from GroPep (Adelaide, Australia). The primary antibody to troponin-T (CT3 Image analysis from J. J-C. Lin) was purchased from the Developmental To quantify cell number a module was created using the Studies Hybridoma Bank (Iowa City, IA, USA), and the Cell Profiler software program [22] that loaded EGFP secondary antibody, AlexaFluor 594-conjugated-goat images as a batch, converted images to grayscale, and anti-mouse IgG, was from Life Technologies. C2 myo- performed an illumination correction. EGFP-positive blasts were obtained from Yaffe and Saxel [16], and cells in each field were identified by applying a back- HEK293FT cells were from Life Technologies. Other ground adaptive threshold, which separates primary ob- chemicals were reagent grade and were purchased from jects from the background by setting a threshold at commercial suppliers. twice the value of the mode of the histogram for pixel intensity. Objects identified by the algorithm that were Development of a recombinant lentivirus expressing below 15 microns in diameter were discarded from the EGFP automated count. Cell confluence was calculated for A recombinant lentivirus was generated to express en- each field using an IncuCyte algorithm, which quantifies hanced green fluorescent protein (EGFP) under control the relative cell area in each bright field image. of the EF-1α promoter using as a base Addgene plasmid For our studies we have defined a founder as a cell #12258 (Cambridge, MA, USA). Lentivirus was prepared present at the time of plating, and a lineage as all of the in HEK293FT cells and purified as described [17,18]. progeny of a founder cell. To follow lineages, founder cells Prior to use the virus was diluted in DMEM plus 2% and all progeny were manually tracked using registered fetal calf serum, and filtered through a 0.45 μM Gelman EGFP images starting from the first image obtained. Cells syringe filter (Pall Life Science, Ann Arbor, MI, USA). around the border of each field were excluded from ana- lysis as most tended to exit the viewing area over the Cell culture course of an experiment. Both cell division and death were C2 myoblasts were grown and expanded on tissue cul- readily identified and quantified (see Figure 1). Cell death ture plates coated with 0.2% gelatin in growth medium was easily detected, as it ultimately culminated in cell lysis, (DMEM, 10% heat-inactivated fetal calf serum, and 10% and was preceded by condensation, blebbing, and loss of heat-inactivated newborn calf serum), as described EGFP fluorescence. Additionally, an advantage of live cell Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 3 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 A Myoblast Division Elapsed time: 0 15 30 45 60 75 min B Myoblast Death Elapsed time: 0 15 30 45 60 75 min Figure 1 Visualizing myoblast division and death. (A) Time lapse images (EGFP and bright field) at 15 min increments of an EGFP-labeled myoblast undergoing mitosis. (B) Time lapse images (EGFP and bright field) at 15 min increments of myoblast death. The arrows point to EGFP- labeled myoblasts. The white arrows indicate cells that began to die prior to the first frame, and illustrate loss of EGFP fluorescence and detachment over time of observation. The yellow arrows mark cells that condensed and underwent death during the period of observation. Loss of EGFP fluorescence and detachment occurred during the subsequent 60 min (not shown). imaging is that subsequent tracking of same area of the a correlation between random cells, we randomized the field could confirm that death occurred. pairings and performed the same test. Results were con- sidered statistically significant when P ≤0.01. Immunocytochemistry To analyze muscle differentiation, plates that had been Results imaged for 90 h (24 h in growth medium plus 66 h in Defining myoblast dynamics by live cell imaging DM) were washed with PBS, fixed with paraformalde- We employed live cell imaging to track myoblast prolifer- hyde for 10 min, and washed again with PBS followed by ation and monitor survival during a differentiation time a 90-s treatment with 50% acetone - 50% methanol, as course. To study myoblast dynamics, we plated a mixture described [19,20]. After three additional PBS washes of unmarked myoblasts with myoblasts expressing EGFP wells were incubated with 0.25% goat serum in PBS under control of the constitutively active EF-1α promoter, for ≥2 h to block non-specific antibody binding, followed and tracked EGFP-positive cells every 15 min using an au- by incubation overnight at 4°C with troponin-T primary tomated cell counting algorithm (Figure 2A). We found antibody (1:100 dilution), washing with PBS, and incubation that a mixed population was necessary for accurate track- for 90 min at 20°C with AlexaFluor 594-conjugated-goat ing once the cells reached confluence. We observed a pro- anti-mouse IgG (1:3,000 dilution) and Hoescht nuclear dye. gressive increase in cell number with an average doubling Cells were visualized with a Nikon Eclipse Ti-U inverted time of 17.6 h during the initial 24 h of incubation microscope and a Nikon DS-Qi1Mc camera using the NIS (Figure 2B). After 24 h, high serum growth medium elements 3.1 software. was replaced with low serum differentiation medium (DM). Following addition of DM, cell number contin- ued to increase, leading to a peak in myoblast number Statistical analysis between 8 and 14 h after medium was changed. Cell To assess observed cell viability data, we first calculated number then progressively declined, but began to the number of living and dead cells among sibling pairs. stabilize by the end of the recording period after 36 h Cells that failed to divide, or that had a sibling that in DM (Figure 2B). When myoblasts were plated at similar underwent a second division, were not entered into this densities these patterns were consistent across multiple lo- analysis since they had no comparable sibling. This ex- cations in a single well and across independent experi- cluded 16 cells, which had a percent survival of 25%. As- ments (Figure 2B and Additional file 1: Figure S1A, B), suming random death between pairs of cells, we but varied in degree and timing when cells were plated at calculated the expected number of pairs composed of higher or lower densities (Additional file 1: Figure S1C). two living myoblasts, a living and a dead cell, or two Tracking cells beyond 60 h revealed that EGFP- dead cells. Expected frequencies were then compared to positive myoblasts fused with both EGFP-expressing and observed data using a χ-squared test with two degrees of non-labeled cells to form multinucleated myotubes freedom. To test for a relationship between a variable in (Additional file 2: Figure S2). These results were con- sibling pairs (cell cycle duration or time to death), we firmed by identifying troponin-expressing cells by calculated the Pearson correlation coefficient. To test for 350 30 40 50 60 0 10 20 10 20 30 40 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 4 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 measures of cell number. Immediately upon plating, confluence was approximately 20% and cell number was Phase Contrast/EGFP Cell Counting approximately 25% of its maximum value (Figure 2C). Cells soon spread out and began to divide so that by 10 h in culture when the EGFP-positive myoblast number per field was approximately 30% to 40% of maximal, con- fluence had reached approximately 85% to 95% (Figure 2C). By 24 h in growth medium when the cell number was ap- proximately 70% to 80% of maximal, confluence was ap- proximately 99%, and it remained constant despite a GM DM further rise in myoblast number (Figure 2C). Thus, conflu- ence and cell number are poorly correlated. Defining myoblast population kinetics Our automated counting algorithm measured changes in cell number, but was unable to quantify individual in- Experiment: stances of cell death or division. In order to quantify #1 death and division, we manually tracked myoblasts and #2 #3 their progeny over a 60-h incubation period. Both cell division and death could be readily detected and moni- Time (hr) tored (Figure 1 and Additional files 3 and 4: Movie). During cell division, cells condensed into a circular GM DM shape, which was followed by mitosis and emergence of two progeny (Figure 1A). Cell death was detected by shrinkage, blebbing, lysis, and the ultimate loss of EGFP fluorescence (Figure 1B). Comparing manual and auto- mated measures of the total cell number revealed similar kinetics, thus validating the automated cell counting al- gorithm (Additional file 1: Figure S1A, B). Experiment: #1 Cell tracking revealed that myoblast proliferation con- #2 Cell confluence #3 tinued well after DM was added (Figure 3A, B, Additional #1 #2 Cell number file 5: Figure S3). Cell death was largely absent during the #3 24 h in GM, but was extensive after addition of DM so that cell division and death were occurring simultaneously Time (hr) (Figure 3C, Additional file 5: Figure S3). Addition of IGF-I Figure 2 Defining myoblast dynamics by live cell imaging. C2 ([2 nM] R3-IGF-I) with DM led to a rise in the maximal myoblasts were mixed at a 1:4 ratio with C2 cells stably infected myoblast number over controls (Figure 3A). This was a with an EGFP gene under control of the EF-1α promoter, and the consequence of an increase in cell division and a reduc- EGFP-expressing myoblasts were tracked at 15-min intervals using an automated cell counting algorithm. See ‘Methods’ for additional tion in myoblast death (Figure 3B, C). details. (A) Phase contrast image of EGFP-positive myoblasts (left) and the corresponding image of the same microscopic field with EGFP-expressing cells identified by an automated cell counting Myoblast lineage analysis algorithm. (B) Cell number as a function of time in culture for three To assess myoblast fate, we tracked 79 founder cells and independent experiments (blue, green, and red). Each dot represents their progeny starting from the time of plating, and mea- a single measurement. (C) Percentage of maximum cell number sured multiple kinetic parameters (Figure 4A). For the (closed dots) and percent confluence (open dots) as a function of purpose of our studies, we define lineage as all the pro- time in culture for three independent experiments (blue, green, and red). geny of a single cell, and fate as a specific outcome (for example, survival, death, differentiation). For each lineage, we recorded the duration from the start of im- immunocytochemistry (Additional file 2: Figure S2). Thus, aging until a founder cell divided, labeled as the time to neither EGFP expression nor live cell imaging compromised the first cell division (Figure 4A). This initial division muscle differentiation. produced two cells, sibling A and sibling B. The time Since confluence is frequently used to establish when from the first cell division to the division of each sibling DM is added, we tracked confluence and compared it to was recorded as the first full cell cycle (Figure 4A). Data EGFP+ cells/field Maximum value (%) 350 30 40 50 60 0 10 20 30 40 50 60 0 10 20 10 20 30 40 50 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 5 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 A A Sibling B GM DM ± IGF-I Founder Cell Myoblast Time to first cell division Living Sibling A Number Dead First full cell cycle No IGF-I + IGF-I GM DM Time (hr) Lineage A Lineage B Time (hr) GM DM ± IGF-I Myoblast Division Lineage C No IGF-I + IGF-I GM DM 024 60 Time (hr) Figure 4 Studying the fate of individual myoblasts. (A) Schematic of a hypothetical myoblast lineage tree, with different features indicated on the timeline. (B) Examples of three actual cell lineages with progeny and fates of individual cells indicated. Time (hr) GM DM ± IGF-I Myoblast from three lineages that varied in outcomes are depicted Death in Figure 4B. No IGF-I By tracking the time from plating until the first cell + IGF-I division, we found a relatively broad distribution that ranged from 2 to 30 h (Figure 5A). This illustrated that the start of cell division was asynchronous in the popu- lation. We next tracked cell cycle duration using the first full cell cycle following the division of each founder cell. This varied across the population from 8 to 26 h with a mean of 14.2 h (Figure 5B). The mean cell cycle duration was shorter than the population doubling time, due in Time (hr) part to eight of 79 founder myoblasts that failed to div- Figure 3 Defining myoblast population kinetics by live cell ide over the entire 60-h time course. imaging. Individual EGFP-expressing myoblasts were studied as in Despite the range of cell cycle durations in the popula- Figure 2 using manual counting. Differentiation medium (DM) was added ± IGF-I (R3-IGF-I [2 nM]), as indicated. (A) Effect of IGF-I on total tion, there was a remarkably close correlation between cell number. (B) Effect of IGF-I on the frequency of cell division (DM siblings (Figure 5C). This relationship was not detected 234 divisions; IGF-I 344 divisions). (C) Effect of IGF-I on myoblast death between cells paired randomly (Figure 5D). Between sib- (DM 208 deaths; IGF-I 154 deaths). For A to C, blue depicts control cells lings the Pearson correlation coefficient for cell cycle and red, myoblasts incubated with IGF-I. For B and C, the number of -13 duration was 0.85 (P = 1.834e ), but between random cells exhibiting a specific trait at a given time is plotted on the y-axis. pairs of cells it was −0.07 (P = 0.631). Number of EGFP+ cells Number of EGFP+ cells EGFP+ cells 20 22 26 28 8 12 16 4 8 12 16 20 24 14 18 22 18 22 6 10 6 10 14 14 14 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 6 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 A B 10 16 0 0 Time to first cell division (hr) Duration of first cell cycle (hr) C D Cell Cycle Duration (hr) Cell Cycle Duration (hr) Sibling B Random Cell B Figure 5 The cell-cycle duration of individual C2 myoblasts is heterogeneous. Individual EGFP-expressing myoblasts were monitored at 15-min intervalsasinFigures 1and 2. (A) Asynchronous entry of myoblasts into the cell cycle, as measured by the time from plating until the first cell division. The number of myoblasts undergoing mitosis at a given time is plotted on the y-axis. (B) Frequency distribution of the duration of the first full cell cycle. The number of myoblasts exhibiting a given cell cycle duration is plotted on the y-axis. (C) Close correlation (0.85, Pearson correlation coefficient) of cell -13 cycle duration between siblings (progeny of the same cell division; P =1.834e , t = 11.14, degrees of freedom (DF) = 49). (D) No correlation was observed for randomly paired cells (−0.07; P = 0.631, t = −0.4834, DF = 49)). We next assessed cell viability, since it has been shown both dying being reversed (P <0.0001). These results in- that a significant fraction of myoblasts undergo apop- dicate that survival was not purely stochastic, but in- totic death during incubation in DM [23-27]. For this stead was biased by parental lineage. analysis, we compared the survival of 149 sibling pairs When the time from last division to death was tracked (298 total cells). As depicted in Figure 6A, over 60% of between concordant siblings (Figure 6B), we found a close cells died in DM. When survival and death were correlation similar to that seen with cell cycle duration, assessed on the basis of parentage, we found that 73% of further reinforcing the importance of parental lineage. siblings had concordant fates, with 49% both dying and The Pearson correlation coefficient for time to death be- -12 24% both living, and 27% were discordant, with one tween siblings was 0.72 (P =2.247e ), while by contrast myoblast living and the other dying (Figure 6A). The between random cells the value was 0.12 (P = 0.3271) number of shared fates between siblings was significantly (Figure 6C). larger than expected if survival occurred solely by chance (values expected if cell death is random: 40.3% Heterogeneity among myoblast lineages both die, 13.3% both live, 46.4% discordant (P <0.0001)). We next sought to analyze how concordance between Similarly, even though incubation with IGF-I reduced siblings altered lineage outcomes during muscle differ- the percentage of cells that died (Figure 3), concordance entiation. We found that lineage sizes were unequal as among siblings was 75% (50% both living and 25% both a consequence of variable rates of cell division and sur- dying, Additional file 6: Figure S4). This bias toward vival. A fraction of lineages failed to divide, another concordant sibling fates was nearly identical to that ob- fraction underwent fewer than two cell divisions, and served in cells incubated with DM alone (Figure 6A), another had multiple divisions (Figure 7). Myoblast despite the percentages of both myoblasts living and survival also was heterogeneous, as some lineages of Cell Cycle Duation (hr) Random Cell A Cell Cycle Duration (hr) Number of EGFP+ cells Sibling A Number of EGFP+ cells 300 10 20 30 40 50 0 10 20 30 0 10 20 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 7 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 GM DM Sibling Outcomes Both live (24%) One lives (27%) One dies Both die (49%) Time (hr) B C Time to Death (hr) Time to Death (hr) Sibling B Random Cell B Figure 6 Concordance of myoblast fate. Individual EGFP-expressing myoblasts were analyzed at 15-min intervals as in Figures 1 and 2. (A) The line plot shows the fate of each myoblast (n = 298). Each horizontal line indicates a survival timeline for a single myoblast with the left end representing the time after the last cell division (= starting point), and the right end indicating either the time of death or survival to 36 h in DM. Concordance or discordance of outcomes between siblings is indicated (black and blue lines reflect concordance, red discordance). The number of identical fates between siblings was significantly larger than expected by chance (χ = 21.064, DF = 2, two-tailed P <0.0001). (B, C) Correlation -12 of time of cell death for siblings (Pearson correlation coefficient between sibling cells was 0.7196 (P <2.247e , t = 8.733, DF = 71) and between randomly paired cells was 0.1163 (P <0.3271, t = 0.9868, DF = 71)). Time to Death (hr) Individual EGFP+ Cells Sibling A Time to Death (hr) Random Cell A 60 0 10 20 30 40 50 0 10 20 30 40 50 60 Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 8 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 A B 15 15 DM DM + IGF-I Alive Alive 0 0 -5 -5 Dead Dead -10 -10 GM DM GM DM + IGF-I C D ≥3 Survivors ≥3 Survivors 1-2 Survivors 60 1-2 Survivors 0 Survivors 20 20 0 Survivors Time (hr) Time (hr) Figure 7 Myoblast lineages are heterogeneous. EGFP-expressing myoblasts were studied as in Figure 1. Differentiation medium (DM) was added ± IGF-I (R3-IGF-I (2 nM)), as indicated. (A, B) Line plots showing the number of cells derived from each lineage and the outcome (alive or dead) tracked on the y-axis. (C, D). Variation in outcomes of progeny for individual founder myoblasts leads to a shift in the population. The population number was normalized across time. Red, founder cells and their progeny with zero surviving myoblasts; green, founders with 1 to 2 survivors; blue, lineages with ≥3 survivors. similar size maintained 100% viability, others under- 20% of the initial population to approximately 60% of went 100% death, and others had mixed outcomes the final cohort (Figure 7C, red). Thus, the overall popu- (Figure 7A). Incubation of myoblasts in DM with IGF-I lation at the end of the experiment differed substantially led to a higher fraction of lineages with 100% survival, from the population at the start. but IGF-I was not able to rescue all lineages since 16 In myoblasts incubated in DM plus IGF-I the relative (approximately 20%) still underwent complete death number of lineages in each group was different. IGF-I (Figure 7B). Thus, myoblast lineage size and viability treatment resulted in only 20% of founders not being were variable. represented in the final population, and 57% of founders To assess how heterogeneity in lineage size or survival comprised 85% of the final group (Figure 7D). Thus, might be reflected in the total population after a differ- addition of IGF-I in DM maintained the myoblast entiation time course, we plotted the number of living lineage distribution so that it more closely resembled the myoblasts in each lineage over time, grouping lineages population at the start. according to outcome. We found that the population was evenly represented by each of the founder cell line- Discussion ages during incubation in growth medium, but not after Here we have used live cell imaging and lineage tracing addition of DM. One group of myoblasts, comprising to address the dynamics of muscle cell proliferation and approximately 40% of the initial population (Figure 7C, survival in the C2 myoblast cell line. We find a wide green tracing), maintained a similar representation for variation in the rate and extent of both proliferation and the entire culture period, while another equivalently viability of myoblasts derived from different parental sized group of founders failed to have one cell survive cells, but concordant behavior in cells arising from the after incubation in DM (Figure 7C, red). In contrast, a same parents. As a consequence, the population of myo- third group significantly expanded from approximately blasts undergoing differentiation varied substantially Population (%) Number of EGFP+ Myoblasts Population (%) Number of EGFP+ Myoblasts Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 9 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 from the cells present at the start of an experiment. response to muscle injury in vivo, satellite cell prolifera- Addition of IGF-I to DM reduced population heterogen- tion is followed by a period of satellite cell death [6]. We eity primarily by sustaining myoblast viability, and thus found that the net decline in cell number following 36 h increased the number and sizes of surviving lineages. As in DM was approximately 35%. This is in line with the a result, the terminal population more closely resembled 20% to 30% value previously reported with endpoint the cohort of myoblasts at the start than it did in un- methods, including TUNEL assays, cell counting, and treated cells. Our observations reveal that under stand- ‘live-dead’ staining [25,35]. Yet, by tracking both the div- ard treatment protocols extensive heterogeneity is an ision and death of individual cells, we found that over intrinsic property of cultured myoblasts, and that an ef- 60% of the population died during 36 h in DM, with the fect of IGF-I is to decrease this variability. majority of death occurring during the initial 15 h (Figure 3C). This value differed substantially from cell Myoblast population features number calculations because of concurrent proliferation of We found that cell cycle durations were heterogeneous other EGFP-labeled myoblasts during incubation in DM. across the population and that cell division continued after Thus, we suggest that traditional apoptosis assays under- DM was added. The average cell cycle duration of the estimate the extent of myoblast death by failing to account population in growth medium was 14.2 h. This value for ongoing proliferation of other cells in the culture. matches doubling times of C2 myoblasts obtained by other By identifying and tracking individual myoblasts and approaches, including labeling of DNA synthesis and direct their offspring, we found that cell death was not ran- cell counting [23], but was easier to acquire and potentially dom. Rather, siblings were biased toward adopting con- more accurate, since individual myoblasts were tracked ra- cordant fates after incubation in DM. The tendency ther than averaging multiple time points from different toward common outcomes was maintained even in groups of cells. Despite agreement of our data with previ- cells exposed to IGF-I, despite enhanced myoblast sur- ous observations, we found that the cell cycle duration of vival from IGF-I treatment (Figure 3C, Additional file 4: individual myoblasts varied extensively (range, 8–26 h), and Figure S4). The mechanisms responsible for these biases that approximately 10% of the founder cells failed to divide are unclear, but could arise from genetic or epigenetic dif- once over the entire 60-h tracking period. Remarkably, ferences, or from environmental influences. We suspect these observations are similar to results obtained with satel- that a fraction of the bias may be explained by similar lite cells derived from dissociated single muscle fibers [28], levels or activity of the IGF-I - PI3-kinase - Akt signaling where both the onset of proliferation and individual cell pathway between related cells, since exposure to IGF-I re- cycle durations varied in the population (range, 5.1-17.8 h), duced myoblast death, but maintained concordant fates and approximately 16% of cells failed to divide once [28]. between siblings. It is therefore possible that cells of By assessing myoblast lineage, we observed that there shared parentage inherit similar amounts of signaling was a close correlation between the cell cycle durations components, and/or share epigenetic or genetic alter- of siblings (Figure 5C), in remarkable agreement with an ations that affect regulation of this pathway. This is observation noted more than 25 years ago in primary consistent with observations that cell siblings adopt quail myoblasts [29]. These similarities between cells of concordant fates in response to apoptosis-inducing shared parentage in both primary myoblasts and a muscle agents because of a common inheritance of proteins cell line point to the potential importance of heritability from their mother [7,8]. Alternatively, as siblings share and the immediate environment in regulating cell fate. a similar microenvironment, we cannot exclude the Myoblast differentiation requires exit from the cell cycle possibility that paracrine factors also contribute to the in G1 [30-32]. Since our data showed that cell division con- regulation of cell survival. tinued well after addition of DM in a fraction of cells, this The main impact of cell death not being random was a dramatic change in the composition of the myoblast indicates that the onset of muscle differentiation is hetero- geneous. Furthermore, since IGF-I treatment prolonged population by the end of the culture period. This was the time of cell division, it is likely to increase the duration not apparent during the initial 24 h of incubation in growth medium because myoblast viability was complete over which cells exit the cell cycle (Figure 3B). This prob- lem of variability is further compounded by methods that and most of the cells underwent at least one cell division rely on confluence to mark the time when DM should be (Figure 5). Variability arose, however, during the subse- quent 36 h in DM, as distinct subpopulations developed added [33,34], since confluence is relatively difficult to visu- ally quantify, and as seen here, small changes in confluence rapidly from heterogeneous cell division coupled with can equate to large differences in cell numbers (Figure 2B). variable survival. This led to substantial differences in the contributions of different lineages to the final myoblast It is well known that a fraction of cultured myoblasts succumb to apoptotic cell death during incubation in population (Figure 6A, 7, Additional file 6: Figure S4). DM [23-25,35]. Similarly, it has been reported that in Our results suggest that measurements that average Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 10 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 cellular characteristics during a differentiation time remarkable homogeneity within individual lineages in course, such as immunoblots or gene expression assays, terms of cell fate. Treatment with IGF-I increased myo- can obscure the properties of subpopulations. blast number by maintaining viability and by stimulating a fraction of cells to complete one additional cell cycle Impact of IGF-I on myoblast proliferation, survival, and in DM, and as a consequence reduced the variability of differentiation the terminal population compared with controls. Our re- IGF-I exerts potentially contradictory effects on muscle cells, sults reveal that heterogeneity is an intrinsic property of including promoting both proliferation and differentiation cultured myoblasts, and demonstrate the power of live [33]. Our observations suggest one resolution to this prob- cell imaging to provide insights into the regulation of lem. Analysis of the onset of the last division revealed that muscle differentiation. IGF-I led to an average delay of approximately 5 h com- pared with untreated controls (Figure 3B, Additional file 6: Additional files Figure S4). As this delay did not lead to more than one add- Additional file 1: Figure S1. Characterizing myoblasts by live cell itional cell division, our interpretation is that the main action imaging. C2 cells were mixed at a 1:4 ratio with C2 myoblasts stably of IGF-I is to maintain myoblast survival so that otherwise infected with an EGFP gene under control of the EF-1α promoter. The vulnerable cells are able to complete a single final round of EGFP-expressing myoblasts were tracked at 15-min intervals. (A) Concordance between results of manual and automated cell counting. replication. These effects of IGF-I complicate comparisons Cells were incubated for 60 h, with DM ± IGF-I (R3-IGF-I [2 nM]) being with untreated cells, as both fractional myoblast survival added for the last 36 h (red traces). Solid lines represent manual tracking and the starting points for differentiation are different. Fu- of lineages and dots represent automated counting. (B) Reproducibility of automated cell counting. Four wells were plated with an identical ture applications of reporters for different aspects of differ- number of cells, and were incubated for 60 h, with DM ± IGF-I being entiation are needed to improve our understanding of the added for the last 36 h. (C) Effects of plating density on myoblast kinetics and regulation of muscle differentiation by separat- dynamics. Cells were plated at varying concentrations, and EGFP-positive cells were identified by automated counting at 15-min intervals for 60 h. ing out these confounding factors. Additional file 2: Figure S2. EGFP-expressing myoblasts undergo differentiation. Confluent myoblasts were incubated in DM for 66 h. (A) Satellite cell fate and muscle regeneration Live cell images of EGFP fluorescence were captured (10× magnification). An important question in skeletal muscle biology is how (B) Differentiating myoblasts were fixed and stained with antibodies to troponin-T (red), and nuclei were stained with Hoescht dye (blue, 100× satellite cell fate is regulated during muscle regeneration. magnification). Following injury, satellite cells must divide sufficiently to Additional file 3: Movie 1. Live cell imaging of C2 myoblasts. Live cell insure adequate numbers of differentiating myoblasts for imaging of C2 myoblasts for 60 h (24 h in growth medium, 36 h in DM). immediate muscle repair, but also must maintain a re- Fluorescent images were captured every 15 min. serve population for regeneration after subsequent injury Additional file 4: Movie 1. Live cell imaging of C2 myoblasts with manual tracking overlay. Live cell imaging of C2 myoblasts for 60 h (24 h [4,6,36]. Thus, multiple cell fate decisions are necessary in growth medium, 36 h in DM). Fluorescent images were captured every to ensure adequate current and future muscle repair. 15 min. Live cell imaging has begun to be applied to this ques- Additional file 5: Figure S3. Reproducibility of myoblast dynamics by tion, and has revealed the importance of asymmetric live cell imaging. Individual EGFP-expressing myoblasts were manually tracked at 15-min intervals in three independent experiments, as in and symmetric satellite cell divisions [14,37,38]. Other Figure 3. Left panels: cell number measured as a function of time in studies have shown that the satellite cell population is culture. Center panels: frequency of cell division analyzed as a function of very heterogeneous, not only in terms of its behavior in time in culture. Right panels: frequency of myoblast death recorded as a function of time in culture. response to proliferative or migratory cues [28,39], but Additional file 6: Figure S4. IGF-I promotes myoblast proliferation and also with respect to cell of origin [36], and surface pro- enhances viability. Individual EGFP-expressing myoblasts were analyzed at tein expression [6,40]. Thus both environmental and 15-min intervals as in Figures 3 and 6. The line plot shows the fate of genetic factors potentially play influential regulatory each myoblast (n = 372). Each horizontal line indicates a survival timeline for a single myoblast with the left end representing the time after the roles in muscle regeneration through effects on satellite last cell division (= starting point), and the right end indicating either the cells. Elucidating how this heterogeneity impacts the de- time of death or survival to 36 h in DM. Concordance or discordance of cisions that lead to satellite cell differentiation will be outcomes is indicated (black and blue lines reflect concordance, red discordance). The number of identical fates between siblings was critical to understanding the dynamics of muscle regen- significantly larger than expected by chance (χ =45.581, DF =2, two-tailed eration and how under certain circumstances such as P <0.0001). aging this process can go awry. Abbreviations Conclusions DM: Differentiation medium; DMEM: Dulbecco’s modified Eagle’s medium; EGFP: Enhanced green fluorescent protein; GM: Growth medium; IGF- We have used live cell imaging and lineage tracing to as- I: Insulin like growth factor-I; PBS: Phosphate buffered saline.. sess both proliferation and the early events of differenti- ation in C2 myoblasts. Our results reveal marked Competing interests variability in lineage size and fractional survival, but The authors declare that they have no competing interests. Gross and Rotwein Skeletal Muscle 2013, 3:10 Page 11 of 11 http://www.skeletalmusclejournal.com/content/3/1/10 Authors’ contributions 23. 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Skeletal MuscleSpringer Journals

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