Flow cytometric cell cycle analysis of muscle precursor cells cultured within 3D scaffolds in a perfusion bioreactor

It has been widely demonstrated that perfusion bioreactors improve in vitro three‐dimensional (3D) cultures in terms of high cell density and uniformity of cell distribution; however, the studies reported in literature were primarily based on qualitative analysis (histology, immunofluorescent staining) or on quantitative data averaged on the whole population (DNA assay, PCR). Studies on the behavior, in terms of cell cycle, of a cell population growing in 3D scaffolds in static or dynamic conditions are still absent. In this work, a perfusion bioreactor suitable to culture C2C12 muscle precursor cells within 3D porous collagen scaffolds was designed and developed and a method based on flowcytometric analyses for analyzing the cell cycle in the cell population was established. Cells were extracted by enzymatic digestion of the collagen scaffolds after 4, 7, and 10 days of culture, and flow cytometric live/dead and cell cycle analyses were performed with Propidium Iodide. A live/dead assay was used for validating the method for cell extraction and staining. Moreover, to investigate spatial heterogeneity of the cell population under perfusion conditions, two stacked scaffolds in the 3D domain, of which only the upstream layer was seeded, were analyzed separately. All results were compared with those obtained from static 3D cultures. The live/dead assay revealed the presence of less than 20% of dead cells, which did not affect the cell cycle analysis. Cell cycle analyses highlighted the increment of cell fractions in proliferating phases (S/G2/M) owing to medium perfusion in long‐term cultures. After 7–10 days, the percentage of proliferating cells was 8–12% for dynamic cultures and 3–5% for the static controls. A higher fraction of proliferating cells was detected in the downstream scaffold. From a general perspective, this method provided data with a small standard deviation and detected the differences between static and dynamic cultures and between upper and lower scaffolds. Our methodology can be extended to other cell types to investigate the influence of 3D culture conditions on the expression of other relevant cell markers