Relation between Cell Division and Gene Expression by
Using Single Cell Tracking System
Kazumi Hakamada1,2
Satoshi Fujita1,2
[email protected]
[email protected]
Jun Miyake1,2
[email protected]
1
2
School of Engineering , The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8656, JAPAN
Research Institute for Cell Engineering, National Institute of Advanced Industrial Science and Technology
2-41-6 Aomi, Koto-ku, Tokyo 135-0064, Japan
Keywords: single cell tracking system, gene expression, cell division
1
Introduction
In the analysis of cell biology, the main target is usually followed by analyzing populations of cells rather
than individual cells without knowing their identities. This is because, it is impossible (or extremely hard) to
monitor their precise behavior in the culture. Real time tracking of single cells in culture is extremely
powerful approach to fully understand their complexity. To tracking single cell on real time, we and Olympus
corp. jointly developed real time single cell tracking system. This system made it possible to tracking
thousands of cells on real time. Using this system, we tried to tracking dynamic behavior of onset timing of
GFP expression in large number of cells. In this study, in most of cells, gene expression starts around one and
half hour after cell division
2
Method and Results
HeLa cells were transfected with EGFP and were monitored 2 days in every 15 minutes. As the result our
monitoring system can track 18571 cells. In the next, we extracted 9163 single cells that were tracked more
than 7 cycles (105 min). To divide data based on their feature, the time course of these cells were applied to k
means clustering and each cluster was evaluated by silhouette method [3] to determine the number of
clusters. Since maximum silhouette value was given when data was divided into 4 clusters, we divided 9163
cells into 4 clusters (Figure 1,2). In this study, HeLa cells were transfected with EGFP, which was driven by
CMV promoter (pEGFP-n1 (TaKaRa) ). Because this promoter expressed EGFP constitutively, we chose one
cluster that had 2049 cells and expression of EGFP monotonously increased. In this cluster, Euclidean
distance was calculated between center of cluster and EGFP expression intensity of each cell. In the next,
200 cells were selected which was located around center of cluster (Figure 3). Finally, by checking phase
contrast data and EGFP data, mis-tracking cells were eliminated then we chose 159 cells. Using these cells
we investigated relation between timing of cell division and onset timing of EGFP expression. As the result,
74.2 % cells started to express EGFP (Figure 4) around 8 cycles (120 min) after cell division (Figure 5).
C2
C3
C4
C5
C6
C7
C8
C9
C10
Frequency (-)
2000
1500
1500
1000
500
500
00
0.88
0.88
0.90
0.90
0.92
0.92
0.94
0.94
Silhouette value (-)
Figure 1: Distribution of silhouette value in each
1.0
1.0
Normalized
intensity (-)
2500
2500
centroid1
centroid2
centroid3
centroid4
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0.0
0.0
0
0
12
2
34
4
56
6
8
Number of cycles (-)
Figure 2: Time course of GFP expression in each centroid
Frequency (-)
Normalized
intensity (-)
1.0
1.0
0.8
0.6
0.4
0.4
0.2
0.0
0.0
4040
30
2020
10
00
0
50
0
0
1
2
2
3
4
4
5
6
6
15 min
30 min
100
100
Number of cycles after cell division (-)
Figure 4: Distribution of GFP
7
Number of cycles (-)
Figure 3: Time course of EGFP expression in selected
0 min
50
expression
105 min
120 min
135 min
Figure 5: Phase-contrast and Fluorescence pictures on each
3
Discussion
In this study, expression of EGFP started around 8 cycles (120 min) after cell division. This result suggested
that, when cells did not divide, gene transfer was not occurred and nuclear import of plasmid was greatly
facilitated by cell division. Our suggestion was supported by Escriou et al. [1] that they showed gene
expression was greatly enhanced when cells underwent mitosis.
Since each cell has different cell cycle in the culture, gene expressions of cells are averaged and it is
impossible to observe onset timing of gene expression of single cell. On the contrary our system showed we
can track thousands of cells simultaneously in the culture as a single cell. Not only EGFP but also in case of
apoptosis pathway, onuki et al. [2] showed Aβ did not played a significant role in the cleavage of pro-caspase
8 in the apoptosis pathway by monitoring single cells, however; previous study had suggested Aβ played a
significant role in activate caspase 8. These results showed understanding precise behavior of cells, it is
necessary to monitor single cell. Since our real time single cell tracking system can track thousands of cells,
it is a powerful tool to understand precise dynamics of cell.
Acknowledgment
This study was entrusted by New Energy and Industrial Technology Development Organization (NEDO).
References
[1] Escriou, V., Carriere, M., Bussone, F., Wils, P., and Scherman, D., Critical assessment of the nuclear
import of plasmid during cationic lipid-mediated gene transfer, J. Gene. Med., 3:179–187, 2001.
[2] Onuki, R., Nagasaki, A., Kawasaki, H., Baba, T., Uyeda, T.Q.P., and Taira, K., Confirmation by FRET in
individual living cells of the absence of significant amyloid -mediated caspase 8 activation, Proc. Natl.
Acad. Sci. USA, 99:14716–14721, 2002.
[3] Rousseeuw, P., Silhouettes, J., A graphical aid to the interpretation and validataion of cluseter analysis, J.
Compt. Appl. Math., 20:53–65, 1987.