Formisano, Lucia (2016) Guiding stem cell self-organization and differentiation through material nanopatterning. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Lingua: English
Title: Guiding stem cell self-organization and differentiation through material nanopatterning
Creators:
CreatorsEmail
Formisano, Lucialucia.formisano@unina.it
Date: 30 March 2016
Number of Pages: 72
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Chimica, dei Materiali e della Produzione Industriale
Scuola di dottorato: Ingegneria industriale
Dottorato: Ingegneria dei materiali e delle strutture
Ciclo di dottorato: 28
Coordinatore del Corso di dottorato:
nomeemail
Mensitieri, Giuseppegiuseppe.mensitieri@unina.it
Tutor:
nomeemail
Netti, Paolo AntonioUNSPECIFIED
Date: 30 March 2016
Number of Pages: 72
Uncontrolled Keywords: Stem cell, nanopattern, focal adhesions, tenogenic differentiation, self-organization, tissue development
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-IND/34 - Bioingegneria industriale
Date Deposited: 12 Apr 2016 23:33
Last Modified: 20 May 2017 01:00
URI: http://www.fedoa.unina.it/id/eprint/10836

Abstract

Biophysical stimuli in the local microenviroment proved to be effective in influencing various aspects of cell behavior such as adhesion, spreading, migration and differentiation [1]. In particular, many studies focused on biomaterials with nanometric scale surface topography able to dictate specific cell shapes, which in turn control cell fate and functions through mechanotransduction pathways [2]. While the role of biophysical signals and more specifically of topographic signals on single cell behavior is well established, there are comparatively less studies on their role on the collective cell behavior. In particular it is not clear how biophysical signals may affect cells self-organization into a three-dimensional tissue. Here, we used nanopatterned substrates able to control adhesion and contractility processes to generate ordered tissues in vitro. In particular we show that by changing the combination of the initial conditions for cell adhesion we obtained different cell behaviours in terms of self-organization and subsequent tissue development. Bone-marrow-derived hMSCs were cultured on polydimethylsiloxane (PDMS) substrates containing parallel and straight channels having ridge to groove width ratio of 1:1, previously treated with the oxygen plasma, that increases the hydrophilicity, improving cell adhesion. Pattern features used, were 350 nm width and depth of 100 nm. Focal adhesions, cytoskeleton and matrix production were visualized with confocal, scanning electron and transmission electron microscopy. Expression of relevant genes was assessed by RT-PCR analysis. In this culturing setup, hMSCs proliferated and organized into dense cells sheets displaying a multi-level order. Molecular analysis suggests that these conditions create a microenvironment that allows the maintenance of stemness and the enhance of the expression of the pluripotency genes into hMSC. By modifying the initial conditions, dramatically changes the cellular behavior were observed. In fact, by increasing the size of the topographic patterns (channels of 700 nm width and 250 nm depth), without surface chemical treatments, the hMSC were stimulated to arrange themselves into self-organized structures that shared similarities with the tendon tissue, in terms of macroscopic morphology, internal cellular organization and molecular profile. Thses data suggest that the pattern provides an initial guidance for FAs and subsequent cell alignment. Aligned cell exert a polarized contractility that leads to the formation of ordered structures. In conclusion, our results demonstrate that the chemical-physical characteristics of the substrate, were able to strongly affect cell behavior in terms of cell fate and in vitro generated tissue functions. In conclusion, nanoengineered material surfaces can be in principle employed to set off the hMSC program toward tissue genesis in a deterministic manner by using the correct combination of initial biophysical signals. References 1. Ventre et al. J R Soc Interface, 9, 2017-2032, 2012 2. McNamara et al. J Tissue Eng, 120623, 2012

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