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Engineers are from PDMS-land, Biologists are from Polystyrenia
Abstract
As the integration of microfluidics into cell biology research proceeds at an ever-increasing pace, a critical question for those working at the interface of both disciplines is which device material to use for a given application. While PDMS and soft lithography methods offer the engineer rapid prototyping capabilities, PDMS as a material has characteristics that have known adverse effects on cell-based experiments. In contrast, while polystyrene (PS), the most commonly used thermoplastic for laboratory cultureware, has provided decades of grounded and validated research conclusions in cell behavior and function, PS as a material has posed significant challenges in microfabrication. These competing issues have forced microfluidics engineers and biologists to make compromises in how they approach specific research questions, and furthermore, have attenuated the impact of microfluidics on biological research. In this review, we provide a comparison of the attributes of PDMS and PS, and discuss reasons for their popularity in their respective fields. We provide a critical evaluation of the strengths and limitations of PDMS and PS in relation to the advancement and future impact on microfluidic cell-based studies and applications. We believe that engineers have a responsibility to overcome any challenges associated with microfabrication, whether with PS or other materials, and that engineers should provide options and solutions that assist biologists in their experimental design. Our goal is not to advocate for any specific material, but provide guidelines for researchers who desire to choose the most suitable material for their application, and suggest important research directions for engineers working at the interface between microfabrication technology and biological application.
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Zhang, Y., Ishida, M., Kazoe, Y., Sato, Y., & Miki, N. (2009) · IEEJ Transactions on Electrical and Electronic Engineering · doi:10.1002/tee.20429 · Cited by 45
A plate reader-compatible microchannel array for cell biology assays
Yu, H., Alexander, C. M., & Beebe, D. J. (2007) · Lab on a Chip · doi:10.1039/b612358a · Cited by 44
Self-citationEvaporation from microreservoirs
Lynn, N. S., Jr., Henry, C. S., & Dandy, D. S. (2009) · Lab on a Chip · doi:10.1039/b900556k · Cited by 38
Hyperoxia augments ER-stress-induced cell death independent of BiP loss
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Njoroge, S. K., Witek, M. A., Hupert, M. L., & Soper, S. A. (2010) · Electrophoresis · doi:10.1002/elps.200900641 · Cited by 12
Shen, M., & Horbett, T. A. (2001) · Journal of Biomedical Materials Research · doi:10.1002/1097-4636(20011205)57:3<336::aid-jbm1176>3.0.co;2-e
Cited by
The present and future role of microfluidics in biomedical research
Sackmann, E. K., Fulton, A. L., & Beebe, D. J. (2014) · Nature · doi:10.1038/nature13118 · Cited by 2,995
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A guide to the organ-on-a-chip
Leung, C. M., de Haan, P., Ronaldson-Bouchard, K., Kim, G.-A., Ko, J., Rho, H. S., Chen, Z., Habibovic, P., Jeon, N. L., Takayama, S., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00118-6 · Cited by 1,116
Advantages and challenges of microfluidic cell culture in polydimethylsiloxane devices
Halldorsson, S., Lucumi, E., Gómez-Sjöberg, R., & Fleming, R. M. T. (2015) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2014.07.029 · Cited by 1,027
Advances in organ-on-a-chip engineering
Zhang, B., Korolj, A., Lai, B. F. L., & Radisic, M. (2018) · Nature Reviews Materials · doi:10.1038/s41578-018-0034-7 · Cited by 1,017
Metadata
- Authors
- Berthier, E., Young, E. W. K., & Beebe, D.
- Venue
- Lab on a Chip
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2012
- Volume
- 12
- Issue
- 7
- Pages
- 1224
- ISSN
- 1473-0189 (ISSN-L)
- 1473-0197
- OpenAlex
- W1995139987
- Cited by
- 799
- References
- 111
- FWCI
- 25.64
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
