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High-Throughput 3D Neural Cell Culture Analysis Facilitated by Aqueous Two-Phase Systems

Published online by Cambridge University Press:  08 May 2017

Kristin Robin Ko*
Affiliation:
School of Biomedical Engineering, 5981 University Ave, Halifax, NS B3H 4R2, Canada
Rishima Agarwal
Affiliation:
School of Biomedical Engineering, 5981 University Ave, Halifax, NS B3H 4R2, Canada
John Frampton
Affiliation:
School of Biomedical Engineering, 5981 University Ave, Halifax, NS B3H 4R2, Canada
*
*(Email: krk@dal.ca)
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Abstract

The three-dimensional (3D) culture of neural cells in extracellular matrix (ECM) gels holds promise for modeling neurodegenerative diseases and pre-clinical evaluation of novel therapeutics. However, most current strategies for fabricating 3D neural cell cultures are not well suited to automated production and analysis. Here, we present a facile, replicable, 3D cell culture system that is compatible with standard laboratory equipment and high-throughput workflows. This system uses aqueous two-phase systems (ATPSs) to confine small volumes (5 and 10 μl) of a commonly used ECM hydrogel (Matrigel) into thin, discrete layers, enabling highly-uniform production of 3D neural cell cultures in a 96-well plate format. These 3D neural cell cultures can be readily analyzed by epifluorescence microscopy and microplate reader. Our preliminary results show that many common polymers used in ATPSs interfere with Matrigel gelation and instead form fibrous precipitates. However, 0.5% hydroxypropyl methylcellulose (HPMC) and 2.5% dextran 10 kDa (D10) were observed to retain Matrigel integrity and had minimal impact on cell viability. This novel system offers a promising yet accessible platform for high-throughput fabrication of 3D neural tissues using readily available and cost-effective materials.

Type
Articles
Copyright
Copyright © Materials Research Society 2017 

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References

REFERENCES

Puschmann, T.B., Zandén, C., De Pablo, Y., Kirchhoff, F., Pekna, M., Liu, J., and Pekny, M., Glia 61, 432 (2013).CrossRefGoogle Scholar
Bozza, A., Coates, E.E., Incitti, T., Ferlin, K.M., Messina, A., Menna, E., Bozzi, Y., Fisher, J.P., and Casarosa, S., Biomaterials 35, 4636 (2014).CrossRefGoogle Scholar
Thomas, D.W., Burns, J., Audette, J., Carroll, A., Dow-Hygelund, C., and Hay, M., BIO Ind. Anal. 1 (2016).Google Scholar
Ko, K.R. and Frampton, J.P., Expert Rev. Neurother. 7175, 1 (2016).Google Scholar
Kim, Y.H., Choi, S.H., D’Avanzo, C., Hebisch, M., Sliwinski, C., Bylykbashi, E., Washicosky, K.J., Klee, J.B., Brustle, O., Tanzi, R.E., and Kim, D.Y., Nat. Protoc. 10, 985 (2015).CrossRefGoogle Scholar
Albertsson, P.A., Partition of Cell Particles and Macromolecules, 3rd ed. (Wiley, New York, 1986).Google Scholar
Encinas, M., Iglesias, M., Liu, Y., Wang, H., Muhaisen, A., Ceña, V., Gallego, C., and Comella, J.X., J. Neurochem. 75, 991 (2000).CrossRefGoogle Scholar
Leung, B.M., Moraes, C., Cavnar, S.P., Luker, K.E., Luker, G.D., and Takayama, S., J. Lab. Autom. 2211068214563793 (2014).Google Scholar