4. Conclusions
In summary, we sequenced the single-cell transcriptomes of high cell
density suspension mammalian cell cultures. Our findings indicated that
cellular transcriptome heterogeneity increased with increasing culture
time, while genomic mutations did not increase during suspension
culture. We also established a method for the quantitative evaluation of
cellular heterogeneity, which was previously not possible. This method
entails examining the evidence of monoclonality by single-cell
sequencing of the mitochondria of cell strains. Further, we uncovered
several differences between adherent cells and suspension cells based on
single-cell genomics. Fundamental biological observation and assessment
are of incremental importance in successful bioengineering. Instead,
further single-cell resolution observations (Norichika Ogata, 2018) and
improved measurement technologies are needed. The intercellular
variations in the mitochondrial genome sequences discovered in this
study are also useful for generating clonal markers for future
applications.
Acknowledgments
This work was funded partly by the Ministry of Economy, Trade, and
Industry (METI) of Japan, and the Japan Agency for Medical Research and
Development (AMED) for “Developing key technology for discovering and
manufacturing pharmaceuticals used for next-generation treatments and
diagnoses” (JP17ae0101003 and JP18ae0101054). We thank Dr. Itoshi
Nikaido and Dr. Hiroki Danno for performing Quartz-Seq library
preparation. We thank Natasha Beeton-Kempen, Ph.D., from Edanz Group
(https://en-author-services.edanzgroup.com/) for editing a draft of this
manuscript.
Conflict of Interest
The authors declare no conflict of interest.
Data accessibility
The resulting short-read data have been deposited in the Short Read
Archive of the DNA Data Bank of Japan (DDBJ) under project ID DRA004159.
References
Altschuler, S. J., & Wu, L. F. (2010). Cellular heterogeneity: do
differences make a difference? Cell, 141 (4), 559-563.
doi:10.1016/j.cell.2010.04.033
Bachl, J., Carlson, C., Gray-Schopfer, V., Dessing, M., & Olsson, C.
(2001). Increased transcription levels induce higher mutation rates in a
hypermutating cell line. J Immunol, 166 (8), 5051-5057.
Ben-David, U., Siranosian, B., Ha, G., Tang, H., Oren, Y., Hinohara, K.,
. . . Golub, T. R. (2018). Genetic and transcriptional evolution alters
cancer cell line drug response. Nature, 560 (7718), 325-330.
doi:10.1038/s41586-018-0409-3
Buettner, F., Natarajan, K. N., Casale, F. P., Proserpio, V., Scialdone,
A., Theis, F. J., . . . Stegle, O. (2015). Computational analysis of
cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals
hidden subpopulations of cells. Nature biotechnology, 33 (2),
155-160. doi:10.1038/nbt.3102
Evans, K., Albanetti, T., Venkat, R., Schoner, R., Savery, J.,
Miro-Quesada, G., . . . Groves, C. (2015). Assurance of monoclonality in
one round of cloning through cell sorting for single cell deposition
coupled with high resolution cell imaging. Biotechnology progress,
31 (5), 1172-1178. doi:10.1002/btpr.2145
Furusawa, M. (2014). The disparity mutagenesis model predicts rescue of
living things from catastrophic errors. Frontiers in genetics, 5 ,
421. doi:10.3389/fgene.2014.00421
Greber, D., & Fussenegger, M. (2007). Mammalian synthetic biology:
engineering of sophisticated gene networks. Journal of
biotechnology, 130 (4), 329-345. doi:10.1016/j.jbiotec.2007.05.014
H. G. Weller, G. T., H. Jasak, C. Fureby. (1998). A tensorial approach
to computational continuum mechanics
using object-oriented techniques. COMPUTERS IN PHYSICS, 12 ,
620-631. Retrieved fromwww.OpenFOAM.org
Hacker, D. L., De Jesus, M., & Wurm, F. M. (2009). 25 years of
recombinant proteins from reactor-grown cells - where do we go from
here? Biotechnol Adv, 27 (6), 1023-1027.
doi:10.1016/j.biotechadv.2009.05.008
Harada, A., Maehara, K., Handa, T., Arimura, Y., Nogami, J.,
Hayashi-Takanaka, Y., . . . Ohkawa, Y. (2018). A chromatin integration
labelling method enables epigenomic profiling with lower input.Nat Cell Biol . doi:10.1038/s41556-018-0248-3
Hayashi, T., Shibata, N., Okumura, R., Kudome, T., Nishimura, O., Tarui,
H., & Agata, K. (2010). Single-cell gene profiling of planarian stem
cells using fluorescent activated cell sorting and its ”index sorting”
function for stem cell research. Development, growth &
differentiation, 52 (1), 131-144. doi:10.1111/j.1440-169X.2009.01157.x
Kao, F. T., & Puck, T. T. (1968). Genetics of somatic mammalian cells,
VII. Induction and isolation of nutritional mutants in Chinese hamster
cells. Proceedings of the National Academy of Sciences of the
United States of America, 60 (4), 1275-1281.
Kim, D., Langmead, B., & Salzberg, S. L. (2015). HISAT: a fast spliced
aligner with low memory requirements. Nature methods, 12 (4),
357-360. doi:10.1038/nmeth.3317
Konstantinov, K. B., & Cooney, C. L. (2015). White Paper on Continuous
Bioprocessing May 20–21 2014 Continuous Manufacturing
Symposium. Journal of Pharmaceutical Sciences, 104 (3), 813-820.
doi:10.1002/jps.24268
Langmead, B., Wilks, C., Antonescu, V., & Charles, R. (2018). Scaling
read aligners to hundreds of threads on general-purpose processors.Bioinformatics . doi:10.1093/bioinformatics/bty648
Li, B., & Dewey, C. N. (2011). RSEM: accurate transcript quantification
from RNA-Seq data with or without a reference genome. BMC
bioinformatics, 12 , 323. doi:10.1186/1471-2105-12-323
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., .
. . Genome Project Data Processing, S. (2009). The Sequence
Alignment/Map format and SAMtools. Bioinformatics, 25 (16),
2078-2079. doi:10.1093/bioinformatics/btp352
Mahata, B., Zhang, X., Kolodziejczyk, A. A., Proserpio, V.,
Haim-Vilmovsky, L., Taylor, A. E., . . . Teichmann, S. A. (2014).
Single-cell RNA sequencing reveals T helper cells synthesizing steroids
de novo to contribute to immune homeostasis. Cell reports, 7 (4),
1130-1142. doi:10.1016/j.celrep.2014.04.011
Norichika Ogata, A. S., Takayuki Komiya, Yoji Iizuka, Ken Matsuse,
Fuminobu Imaizumi, Tomoyuki Suwa, Akinobu Teramoto. (2018). An
Electrical Impedance Biosensor Array for Tracking Moving Cells. Paper
presented at the IEEE Sensors, New Dehli.
O’Callaghan, P. M., Berthelot, M. E., Young, R. J., Graham, J. W.,
Racher, A. J., & Aldana, D. (2015). Diversity in host clone performance
within a Chinese hamster ovary cell line. Biotechnology progress .
doi:10.1002/btpr.2097
Omasa, T., Onitsuka, M., & Kim, W. D. (2010). Cell engineering and
cultivation of chinese hamster ovary (CHO) cells. Curr Pharm
Biotechnol, 11 (3), 233-240.
Pollock, J., Ho, S. V., & Farid, S. S. (2013). Fed-batch and perfusion
culture processes: economic, environmental, and operational feasibility
under uncertainty. Biotechnology and bioengineering, 110 (1),
206-219. doi:10.1002/bit.24608
RCoreTeam. (2013). R: A Language and Environment for Statistical
Computing. Retrieved fromhttp://www.R-project.org/
Santos, A., Wernersson, R., & Jensen, L. J. (2015). Cyclebase 3.0: a
multi-organism database on cell-cycle regulation and phenotypes.Nucleic acids research, 43 (Database issue), D1140-1144.
doi:10.1093/nar/gku1092
Sasagawa, Y., Nikaido, I., Hayashi, T., Danno, H., Uno, K. D., Imai, T.,
& Ueda, H. R. (2013). Quartz-Seq: a highly reproducible and sensitive
single-cell RNA sequencing method, reveals non-genetic gene-expression
heterogeneity. Genome biology, 14 (4), R31.
doi:10.1186/gb-2013-14-4-r31
Scialdone, A., Natarajan, K. N., Saraiva, L. R., Proserpio, V.,
Teichmann, S. A., Stegle, O., . . . Buettner, F. (2015). Computational
assignment of cell-cycle stage from single-cell transcriptome data.Methods, 85 , 54-61. doi:10.1016/j.ymeth.2015.06.021
Snijder, B., Sacher, R., Ramo, P., Damm, E. M., Liberali, P., &
Pelkmans, L. (2009). Population context determines cell-to-cell
variability in endocytosis and virus infection. Nature,
461 (7263), 520-523. doi:10.1038/nature08282
Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., . . .
Surani, M. A. (2009). mRNA-Seq whole-transcriptome analysis of a single
cell. Nature methods, 6 (5), 377-382. doi:10.1038/nmeth.1315
Tapia, F., Vazquez-Ramirez, D., Genzel, Y., & Reichl, U. (2016).
Bioreactors for high cell density and continuous multi-stage
cultivations: options for process intensification in cell culture-based
viral vaccine production. Appl Microbiol Biotechnol, 100 (5),
2121-2132. doi:10.1007/s00253-015-7267-9
Wurm, F. M. (2013). CHO Quasispecies—Implications for Manufacturing
Processes. Processes, 1 (3), 296-311. doi:10.3390/pr1030296
Ziegenhain, C., Vieth, B., Parekh, S., Reinius, B., Guillaumet-Adkins,
A., Smets, M., . . . Enard, W. (2017). Comparative Analysis of
Single-Cell RNA Sequencing Methods. Mol Cell, 65 (4), 631-643
e634. doi:10.1016/j.molcel.2017.01.023
Zydney, A. L. (2015). Perspectives on integrated continuous
bioprocessing—opportunities and challenges. Current Opinion in
Chemical Engineering, 10 , 8-13.
doi:https://doi.org/10.1016/j.coche.2015.07.005