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Cao UMN, Zhang Y, Chen J, Sayson D, Pillai S, Tran SD. Microfluidic Organ-on-A-chip: A Guide to Biomaterial Choice and Fabrication. Int J Mol Sci 2023; 24:3232. [PMID: 36834645 PMCID: PMC9966054 DOI: 10.3390/ijms24043232] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 01/29/2023] [Accepted: 02/01/2023] [Indexed: 02/09/2023] Open
Abstract
Organ-on-A-chip (OoAC) devices are miniaturized, functional, in vitro constructs that aim to recapitulate the in vivo physiology of an organ using different cell types and extracellular matrix, while maintaining the chemical and mechanical properties of the surrounding microenvironments. From an end-point perspective, the success of a microfluidic OoAC relies mainly on the type of biomaterial and the fabrication strategy employed. Certain biomaterials, such as PDMS (polydimethylsiloxane), are preferred over others due to their ease of fabrication and proven success in modelling complex organ systems. However, the inherent nature of human microtissues to respond differently to surrounding stimulations has led to the combination of biomaterials ranging from simple PDMS chips to 3D-printed polymers coated with natural and synthetic materials, including hydrogels. In addition, recent advances in 3D printing and bioprinting techniques have led to the powerful combination of utilizing these materials to develop microfluidic OoAC devices. In this narrative review, we evaluate the different materials used to fabricate microfluidic OoAC devices while outlining their pros and cons in different organ systems. A note on combining the advances made in additive manufacturing (AM) techniques for the microfabrication of these complex systems is also discussed.
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Affiliation(s)
| | | | | | | | | | - Simon D. Tran
- McGill Craniofacial Tissue Engineering and Stem Cells Laboratory, Faculty of Dental Medicine and Oral Health Sciences, McGill University, 3640 University Street, Montreal, QC H3A 0C7, Canada
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Scheideler OJ, Yang C, Kozminsky M, Mosher KI, Falcón-Banchs R, Ciminelli EC, Bremer AW, Chern SA, Schaffer DV, Sohn LL. Recapitulating complex biological signaling environments using a multiplexed, DNA-patterning approach. SCIENCE ADVANCES 2020; 6:eaay5696. [PMID: 32206713 PMCID: PMC7080440 DOI: 10.1126/sciadv.aay5696] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Accepted: 12/17/2019] [Indexed: 05/22/2023]
Abstract
Elucidating how the spatial organization of extrinsic signals modulates cell behavior and drives biological processes remains largely unexplored because of challenges in controlling spatial patterning of multiple microenvironmental cues in vitro. Here, we describe a high-throughput method that directs simultaneous assembly of multiple cell types and solid-phase ligands across length scales within minutes. Our method involves lithographically defining hierarchical patterns of unique DNA oligonucleotides to which complementary strands, attached to cells and ligands-of-interest, hybridize. Highlighting our method's power, we investigated how the spatial presentation of self-renewal ligand fibroblast growth factor-2 (FGF-2) and differentiation signal ephrin-B2 instruct single adult neural stem cell (NSC) fate. We found that NSCs have a strong spatial bias toward FGF-2 and identified an unexpected subpopulation exhibiting high neuronal differentiation despite spatially occupying patterned FGF-2 regions. Overall, our broadly applicable, DNA-directed approach enables mechanistic insight into how tissues encode regulatory information through the spatial presentation of heterogeneous signals.
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Affiliation(s)
- Olivia J. Scheideler
- UC Berkeley–UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley, 306 Stanley Hall, Berkeley, CA 94720, USA
| | - Chun Yang
- Department of Bioengineering, University of California, Berkeley, 306 Stanley Hall, Berkeley, CA 94720, USA
| | - Molly Kozminsky
- California Institute for Quantitative Biosciences, University of California, Berkeley, 174 Stanley Hall, Berkeley, CA 94720, USA
| | - Kira I. Mosher
- California Institute for Quantitative Biosciences, University of California, Berkeley, 174 Stanley Hall, Berkeley, CA 94720, USA
| | - Roberto Falcón-Banchs
- UC Berkeley–UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley, 306 Stanley Hall, Berkeley, CA 94720, USA
| | - Emma C. Ciminelli
- Department of Bioengineering, University of California, Berkeley, 306 Stanley Hall, Berkeley, CA 94720, USA
| | - Andrew W. Bremer
- UC Berkeley–UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley, 306 Stanley Hall, Berkeley, CA 94720, USA
| | - Sabrina A. Chern
- Department of Physics, Harvard University, 17 Oxford Street, Cambridge, MA 02138, USA
| | - David V. Schaffer
- UC Berkeley–UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley, 306 Stanley Hall, Berkeley, CA 94720, USA
- Department of Chemical & Biomolecular Engineering, University of California, Berkeley, 201 Gilman Hall, Berkeley, CA 94720, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, 132 Barker Hall #3190, Berkeley, CA 94720, USA
- Corresponding author. (D.V.S.); (L.L.S.)
| | - Lydia L. Sohn
- UC Berkeley–UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley, 306 Stanley Hall, Berkeley, CA 94720, USA
- Department of Mechanical Engineering, University of California, Berkeley, 5118 Etcheverry Hall, Berkeley, CA 94720, USA
- Corresponding author. (D.V.S.); (L.L.S.)
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