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