Adipose tissue is an attractive source of stem cells due to its wide availability. They contribute to the stromal vascular fraction (SVF), which is composed of pre-adipocytes, tissue-progenitors, and pericytes, among others. Because its direct use in medical applications is increasing worldwide, new quality control systems are required. We investigated the ability of the Non-Equilibrium Earth Gravity Assisted Dynamic Fractionation (NEEGA-DF) method to analyze and separate cells based solely on their physical characteristics, resulting in a fingerprint of the biological sample. Adipose tissue was enzymatically digested, and the SVF was analyzed by NEEGA-DF. Based on the fractogram (the UV signal of eluting cells versus time of analysis) the collection time was set to sort alive cells. The collected cells (F-SVF) were analyzed for their phenotype, immunomodulation ability, and differentiation potential. The SVF profile showed reproducibility, and the alive cells were collected. The F-SVF showed intact adhesion phenotype, proliferation, and differentiation potential. The methodology allowed enrichment of the mesenchymal component with a higher expression of mesenchymal markers and depletion of debris, RBCs, and an extracellular matrix still present in the digestive product. Moreover, cells eluting in the last minutes showed higher circularity and lower area, proving the principles of enrichment of a more homogenous cell population with better characteristics. We proved the NEEGA-DF method is a "gentle" cell sorter that purifies primary cells obtained by enzymatic digestion and does not alter any stem cell function.

Quality Control Platform for the Standardization of a Regenerative Medicine Product / Zia, Silvia; Roda, Barbara; Zannini, Chiara; Alviano, Francesco; Bonsi, Laura; Govoni, Marco; Vivarelli, Leonardo; Fazio, Nicola; Dallari, Dante; Reschiglian, Pierluigi; Zattoni, Andrea. - In: BIOENGINEERING. - ISSN 2306-5354. - ELETTRONICO. - 9:4(2022), pp. 142-153. [10.3390/bioengineering9040142]

Quality Control Platform for the Standardization of a Regenerative Medicine Product

Roda, Barbara;Zannini, Chiara;Alviano, Francesco;Bonsi, Laura;Govoni, Marco;Fazio, Nicola;Dallari, Dante;Reschiglian, Pierluigi;Zattoni, Andrea
2022

Abstract

Adipose tissue is an attractive source of stem cells due to its wide availability. They contribute to the stromal vascular fraction (SVF), which is composed of pre-adipocytes, tissue-progenitors, and pericytes, among others. Because its direct use in medical applications is increasing worldwide, new quality control systems are required. We investigated the ability of the Non-Equilibrium Earth Gravity Assisted Dynamic Fractionation (NEEGA-DF) method to analyze and separate cells based solely on their physical characteristics, resulting in a fingerprint of the biological sample. Adipose tissue was enzymatically digested, and the SVF was analyzed by NEEGA-DF. Based on the fractogram (the UV signal of eluting cells versus time of analysis) the collection time was set to sort alive cells. The collected cells (F-SVF) were analyzed for their phenotype, immunomodulation ability, and differentiation potential. The SVF profile showed reproducibility, and the alive cells were collected. The F-SVF showed intact adhesion phenotype, proliferation, and differentiation potential. The methodology allowed enrichment of the mesenchymal component with a higher expression of mesenchymal markers and depletion of debris, RBCs, and an extracellular matrix still present in the digestive product. Moreover, cells eluting in the last minutes showed higher circularity and lower area, proving the principles of enrichment of a more homogenous cell population with better characteristics. We proved the NEEGA-DF method is a "gentle" cell sorter that purifies primary cells obtained by enzymatic digestion and does not alter any stem cell function.
2022
Quality Control Platform for the Standardization of a Regenerative Medicine Product / Zia, Silvia; Roda, Barbara; Zannini, Chiara; Alviano, Francesco; Bonsi, Laura; Govoni, Marco; Vivarelli, Leonardo; Fazio, Nicola; Dallari, Dante; Reschiglian, Pierluigi; Zattoni, Andrea. - In: BIOENGINEERING. - ISSN 2306-5354. - ELETTRONICO. - 9:4(2022), pp. 142-153. [10.3390/bioengineering9040142]
Zia, Silvia; Roda, Barbara; Zannini, Chiara; Alviano, Francesco; Bonsi, Laura; Govoni, Marco; Vivarelli, Leonardo; Fazio, Nicola; Dallari, Dante; Reschiglian, Pierluigi; Zattoni, Andrea
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/898007
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