Assessment of cell viability in three-dimensional scaffolds using cellular auto-fluorescence.

After assessing cell viability (CV), tissue-engineered constructs are often discarded, as current CV assays commonly require specific (fluorescent) dyes to stain cells and may need scaffold/tissue digestion before quantifying the live and dead cells. Here, we demonstrate and evaluate how cellular auto-fluorescence can be exploited to facilitate a noninvasive CV estimation in three-dimensional scaffolds using two advanced microscopy methods. Mixtures of live and dead C2C12 myoblasts (0%, 25%, 50%, 75%, and 100% live cells) were prepared, and CV was determined before seeding cells into collagen carriers using the trypan blue (TB) assay. Cell-seeded collagen gels ([CSCGs], n=5/cell mixture) were produced by mixing collagen solution with the live/dead cell mixtures (7×10(6) cells/mL). After polymerization, two-photon microscopy (TPM) and confocal microscopy images of the CSCG were acquired (n=30 images/CSCG). It was found that live and dead cells systematically emit auto-fluorescent light with different spectral characteristics. Viable cells showed predominantly blue fluorescence with a peak emission around 470 nm, whereas dead cells appeared to mainly emit green fluorescent light with a peak intensity around 560 nm. For TPM, live and dead cells were distinguished spectrally. For confocal images, the intensity ratio of images taken with band-pass filters was used to distinguish live from dead cells. CV values obtained with both TPM and confocal imaging did not significantly differ from those acquired with the established TB method. In comparison to TPM, confocal microscopy was found to be less accurate in assessing the exact CV in constructs containing mostly live or dead cells. In summary, monitoring cellular auto-fluorescence using advanced microscopy techniques allows CV assessment requiring no additional dyes and/or scaffold digestion and, thus, may be especially suitable for tissue-engineering studies where CV is measured at multiple time points.