ALTEN: A High-Fidelity Primary Tissue-Engineering Platform to Assess Cellular Responses Ex Vivo.

Law, AMK; Chen, J; Colino-Sanguino, Y; Fuente, LRDL; Fang, G; Grimes, SM; Lu, H; Huang, RJ; Boyle, ST; Venhuizen, J; Castillo, L; Tavakoli, J; Skhinas, JN; Millar, EKA; Beretov, J; Rossello, FJ; Tipper, JL; Ormandy, CJ; Samuel, MS; Cox, TR; Martelotto, L; Jin, D; Valdes-Mora, F; Ji, HP; Gallego-Ortega, D

ALTEN: A High-Fidelity Primary Tissue-Engineering Platform to Assess Cellular Responses Ex Vivo.

Law, AMK Chen, J Colino-Sanguino, Y Fuente, LRDL Fang, G Grimes, SM Lu, H

Huang, RJ Boyle, ST Venhuizen, J Castillo, L Tavakoli, J

Skhinas, JN Millar, EKA Beretov, J Rossello, FJ Tipper, JL Ormandy, CJ Samuel, MS Cox, TR Martelotto, L Jin, D

Valdes-Mora, F Ji, HP Gallego-Ortega, D

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Publisher:: WILEY
Publication Type:: Journal Article
Citation:: Adv Sci (Weinh), 2022, 9, (21), pp. e2103332
Issue Date:: 2022-07

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Field	Value	Language
dc.contributor.author	Law, AMK
dc.contributor.author	Chen, J
dc.contributor.author	Colino-Sanguino, Y
dc.contributor.author	Fuente, LRDL
dc.contributor.author	Fang, G
dc.contributor.author	Grimes, SM
dc.contributor.author	Lu, H https://orcid.org/0000-0001-6932-1900
dc.contributor.author	Huang, RJ
dc.contributor.author	Boyle, ST
dc.contributor.author	Venhuizen, J
dc.contributor.author	Castillo, L
dc.contributor.author	Tavakoli, J https://orcid.org/0000-0002-0696-6530
dc.contributor.author	Skhinas, JN
dc.contributor.author	Millar, EKA
dc.contributor.author	Beretov, J
dc.contributor.author	Rossello, FJ
dc.contributor.author	Tipper, JL
dc.contributor.author	Ormandy, CJ
dc.contributor.author	Samuel, MS
dc.contributor.author	Cox, TR
dc.contributor.author	Martelotto, L
dc.contributor.author	Jin, D https://orcid.org/0000-0003-1046-2666
dc.contributor.author	Valdes-Mora, F
dc.contributor.author	Ji, HP
dc.contributor.author	Gallego-Ortega, D
dc.date.accessioned	2023-01-25T03:16:15Z
dc.date.available	2023-01-25T03:16:15Z
dc.date.issued	2022-07
dc.identifier.citation	Adv Sci (Weinh), 2022, 9, (21), pp. e2103332
dc.identifier.issn	2198-3844
dc.identifier.issn	2198-3844
dc.identifier.uri	http://hdl.handle.net/10453/165428
dc.description.abstract	To fully investigate cellular responses to stimuli and perturbations within tissues, it is essential to replicate the complex molecular interactions within the local microenvironment of cellular niches. Here, the authors introduce Alginate-based tissue engineering (ALTEN), a biomimetic tissue platform that allows ex vivo analysis of explanted tissue biopsies. This method preserves the original characteristics of the source tissue's cellular milieu, allowing multiple and diverse cell types to be maintained over an extended period of time. As a result, ALTEN enables rapid and faithful characterization of perturbations across specific cell types within a tissue. Importantly, using single-cell genomics, this approach provides integrated cellular responses at the resolution of individual cells. ALTEN is a powerful tool for the analysis of cellular responses upon exposure to cytotoxic agents and immunomodulators. Additionally, ALTEN's scalability using automated microfluidic devices for tissue encapsulation and subsequent transport, to enable centralized high-throughput analysis of samples gathered by large-scale multicenter studies, is shown.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	WILEY
dc.relation.ispartof	Adv Sci (Weinh)
dc.relation.isbasedon	10.1002/advs.202103332
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.mesh	Alginates
dc.subject.mesh	Biomimetics
dc.subject.mesh	Cell Communication
dc.subject.mesh	Lab-On-A-Chip Devices
dc.subject.mesh	Tissue Engineering
dc.subject.mesh	Alginates
dc.subject.mesh	Tissue Engineering
dc.subject.mesh	Biomimetics
dc.subject.mesh	Cell Communication
dc.subject.mesh	Lab-On-A-Chip Devices
dc.title	ALTEN: A High-Fidelity Primary Tissue-Engineering Platform to Assess Cellular Responses Ex Vivo.
dc.type	Journal Article
utslib.citation.volume	9
utslib.location.activity	Germany
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - IBMD - Initiative for Biomedical Devices
pubs.organisational-group	/University of Technology Sydney/Centre for Health Technologies (CHT)
utslib.copyright.status	open_access	*
dc.date.updated	2023-01-25T03:15:57Z
pubs.issue	21
pubs.publication-status	Published
pubs.volume	9
utslib.citation.issue	21

Abstract:

To fully investigate cellular responses to stimuli and perturbations within tissues, it is essential to replicate the complex molecular interactions within the local microenvironment of cellular niches. Here, the authors introduce Alginate-based tissue engineering (ALTEN), a biomimetic tissue platform that allows ex vivo analysis of explanted tissue biopsies. This method preserves the original characteristics of the source tissue's cellular milieu, allowing multiple and diverse cell types to be maintained over an extended period of time. As a result, ALTEN enables rapid and faithful characterization of perturbations across specific cell types within a tissue. Importantly, using single-cell genomics, this approach provides integrated cellular responses at the resolution of individual cells. ALTEN is a powerful tool for the analysis of cellular responses upon exposure to cytotoxic agents and immunomodulators. Additionally, ALTEN's scalability using automated microfluidic devices for tissue encapsulation and subsequent transport, to enable centralized high-throughput analysis of samples gathered by large-scale multicenter studies, is shown.

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http://hdl.handle.net/10453/165428