Biomedical Engineering Reference
In-Depth Information
over a Raman shift range of 675-950 cm
−1
, the authors determined that the CARS intensities
at 811 cm
−1
, which is assigned to the RNA backbone, is significantly lower for differentiated
stem cells, while intensities over the range of 730-770 cm
−1
were higher for this population.
As such, Turner and co-workers were able to conclude that the Raman spectra obtained
from undifferentiated and differentiated stem cells are distinct and characteristic of their
differentiation state and can be used as an efficient indicator for the label-free monitoring of
stem-cell differentiation based on Raman spectroscopy. In a similar research effort, the same
group utilized normal Raman spectroscopy instead of CARS for the analysis of ESCs [33].
In this study, the authors detected normal Raman signals from undifferentiated and differ-
entiated ESCs and generated a library of Raman intensities for each peak. Finally, the
Raman intensities of nucleic acids (DNA-RNA composites) at 784 cm
−1
were divided by
protein-related bands (e.g., tryptophan), which exist at 757cm
−1
, in order to discriminate
undifferentiated stem cells from differentiated stem cells. Remarkably, the distribution of the
Raman peaks for the two protein/nucleic-acid intensity ratios (757/784 cm
−1
and 853/784 cm
−1
)
were found to be separated clearly between the two cell populations. This indicates that
normal Raman spectroscopy is also effective for the identification of undifferentiated and
differentiated stem cells.
More recently, surface-enhanced Raman spectroscopy (SERS) has been applied exten-
sively in live cell research to overcome the weak intensities that are characteristic of
normal Raman techniques, often considered a critical disadvantage of Raman-based
monitoring tools. Surface-enhanced Raman spectroscopy is normally generated from 'hot
spots” that exist in the nanogap present between noble metal structures (gold, silver,
copper, etc.) and gives 10-15-fold higher signal intensities than normal Raman peaks [34].
Hence, SERS can be used as an efficient tool for the identification of stem-cell
differentiation. Recently, Tamiya and co-workers reported a novel SERS-based tool that
is capable of monitoring mouse ESCs, including undifferentiated single cells, embryoid
bodies (EBs), and terminally differentiated cardiomyocytes [35] (Figure 19.6). To this end,
cells were treated with gold nanoparticles of different diameters (40, 60, and 100 nm) and
subjected to SERS studies. Interestingly, the SERS spectra of undifferentiated stem cells
showed strong Raman signals at the characteristic DNA and RNA peaks (O-P-O stretch
DNA: 787 cm
−1
and O-P-O stretch RNA: 813 cm
−1
), while EBs and differentiated cardio-
myocytes showed high SERS intensity for protein peaks (amide I, amide II, and amide III)
and mitochondria (1604 cm
−1
). According to the authors' report, the increase in protein
components in differentiated cardiomyocytes is mainly caused by the increase in cellular
activity related to protein translation, post-translation, and cell signaling, which is mark-
edly different from undifferentiated single ESCs. Hence, it is obvious that SERS-based
techniques are also very powerful for the noninvasive and label-free monitoring of stem
cell differentiation, which can overcome the disadvantages of current stem-cell-related
characterization techniques.
Microscopy-Based Methods
In conventional immunocytochemical and flow cytometrical methods, cell-surface markers
are detected using fluorescently labeled antibodies. This method represents a noninvasive
method with which to determine stem cell self-renewal and differentiation. However,
these methods detect only the end-point of the antibody-antigen reaction as opposed to the
real-time binding reaction kinetics (e.g., equilibrium dissociation constant
K
d
), which can
be used to reveal both the presentation and population of the surface antigens from
one differentiation stage to another. Moreover, not only does the actual process of
