Tissue engineering is an elegant tool to create organs in vitro, that can help obviate the lack of organ donors in transplantation medicine and provide the opportunity of studying complex biological systems in vitro, thereby reducing the need for animal experiments. Artificial intestine models are at the core of Fish-AI, an EU FET-Open research project dedicated to the development of a 3D in vitro platform that is intended to enable the aquaculture feed industry to predict the nutritional and health value of alternative feed sources accurately and efficiently.At present, it is impossible to infer the health and nutrition value through the chemical characterization of any given feed. Therefore, each new feed must be tested through in vivo growth trials. The procedure is lengthy, expensive and requires the use of many animals. Furthermore, although this process allows for a precise evaluation of the final effect of each feed, it does not improve our basic knowledge of the cellular and molecular mechanisms determining such end-results. In turn, this lack of mechanistic knowledge severely limits the capacity to understand and predict the biological value of a single raw material and of their different combinations.The protocol described herein allows to develop the two main components essential to produce a functional platform for the efficient and reliable screening of feeds that the feed industry is currently developing for improving their health and nutritional value. It is here applied to the Rainbow Trout, but it can be fruitfully used to many other fish species.

Preparation of Biological Scaffolds and Primary Intestinal Epithelial Cells to Efficiently 3D Model the Fish Intestinal Mucosa / N. Verdile, A. Szabó, R. Pasquariello, T.A. Brevini, S. Van Vlierberghe, F. Gandolfi (METHODS IN MOLECULAR BIOLOGY). - In: Next Generation Culture Platforms for Reliable In Vitro Models / [a cura di] T.A.L. Brevini, A. Fazeli, K. Turksen. - [s.l] : Humana, 2021. - ISBN 9781071612453. - pp. 263-278

Preparation of Biological Scaffolds and Primary Intestinal Epithelial Cells to Efficiently 3D Model the Fish Intestinal Mucosa

N. Verdile
Primo
;
R. Pasquariello;T.A. Brevini;F. Gandolfi
2021

Abstract

Tissue engineering is an elegant tool to create organs in vitro, that can help obviate the lack of organ donors in transplantation medicine and provide the opportunity of studying complex biological systems in vitro, thereby reducing the need for animal experiments. Artificial intestine models are at the core of Fish-AI, an EU FET-Open research project dedicated to the development of a 3D in vitro platform that is intended to enable the aquaculture feed industry to predict the nutritional and health value of alternative feed sources accurately and efficiently.At present, it is impossible to infer the health and nutrition value through the chemical characterization of any given feed. Therefore, each new feed must be tested through in vivo growth trials. The procedure is lengthy, expensive and requires the use of many animals. Furthermore, although this process allows for a precise evaluation of the final effect of each feed, it does not improve our basic knowledge of the cellular and molecular mechanisms determining such end-results. In turn, this lack of mechanistic knowledge severely limits the capacity to understand and predict the biological value of a single raw material and of their different combinations.The protocol described herein allows to develop the two main components essential to produce a functional platform for the efficient and reliable screening of feeds that the feed industry is currently developing for improving their health and nutritional value. It is here applied to the Rainbow Trout, but it can be fruitfully used to many other fish species.
Artificial intestine; Fish intestine; Gelatin derivatives; In vitro model; Polymer scaffold; Polymer synthesis; Primary cell line; Rainbow trout
Settore VET/01 - Anatomia degli Animali Domestici
2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/819702
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