BACKGROUND: The emergence of three-dimensional (3D) cell culture in neural tissue engineering has significantly elevated the complexity and relevance of in vitro systems. This is due in large part to the incorporation of biomaterials to impart structural dimensionality on the neuronal cultures. However, a comprehensive understanding of how key seeding parameters affect changes in cell distribution and viability remain unreported. NEW METHOD: In this study, we systematically evaluated permutations in seeding conditions (i.e., cell concentration and atmospheric CO2 levels) to understand how these affect key parameters in 3D culture characterization (i.e., cell health and distribution). Primary rat cortical neurons (i.e., 2 × 106, 4 × 106, and 1 × 107 cells/mL) were entrapped in collagen blended with ECM proteins (ECM-Collagen) and exposed to atmospheric CO2 (i.e., 0 vs 5% CO2) during fibrillogenesis. RESULTS: At 14 days in vitro (DIV), cell distribution within the hydrogel was dependent on cell concentration and atmospheric CO2 during fibrillogenesis. A uniform distribution of cells was observed in cultures with 2 × 106 and 4 × 106 cells/mL in the presence of 5% CO2, while a heterogeneous distribution was observed in cultures with 1 × 107 cells/mL or in the absence of CO2. Furthermore, increased cell concentration was proportional to the rise in cell death at 14 DIV, although cells remain viable >30 DIV. COMPARISON WITH EXISTING METHODS: ECM-Collagen gels have been shown to increase cell viability of neurons long-term. CONCLUSION: In using ECM-collagen gels, we highlight the importance of optimizing seeding parameters and thorough 3D culture characterization to understand the neurophysiological responses of these 3D systems.
BACKGROUND: The emergence of three-dimensional (3D) cell culture in neural tissue engineering has significantly elevated the complexity and relevance of in vitro systems. This is due in large part to the incorporation of biomaterials to impart structural dimensionality on the neuronal cultures. However, a comprehensive understanding of how key seeding parameters affect changes in cell distribution and viability remain unreported. NEW METHOD: In this study, we systematically evaluated permutations in seeding conditions (i.e., cell concentration and atmospheric CO2 levels) to understand how these affect key parameters in 3D culture characterization (i.e., cell health and distribution). Primary rat cortical neurons (i.e., 2 × 106, 4 × 106, and 1 × 107 cells/mL) were entrapped in collagen blended with ECM proteins (ECM-Collagen) and exposed to atmospheric CO2 (i.e., 0 vs 5% CO2) during fibrillogenesis. RESULTS: At 14 days in vitro (DIV), cell distribution within the hydrogel was dependent on cell concentration and atmospheric CO2 during fibrillogenesis. A uniform distribution of cells was observed in cultures with 2 × 106 and 4 × 106 cells/mL in the presence of 5% CO2, while a heterogeneous distribution was observed in cultures with 1 × 107 cells/mL or in the absence of CO2. Furthermore, increased cell concentration was proportional to the rise in cell death at 14 DIV, although cells remain viable >30 DIV. COMPARISON WITH EXISTING METHODS: ECM-Collagen gels have been shown to increase cell viability of neurons long-term. CONCLUSION: In using ECM-collagen gels, we highlight the importance of optimizing seeding parameters and thorough 3D culture characterization to understand the neurophysiological responses of these 3D systems.
Authors: Jingjie Hu; Izzet Altun; Zefu Zhang; Hassan Albadawi; Marcela A Salomao; Joseph L Mayer; L P Madhubhani P Hemachandra; Suliman Rehman; Rahmi Oklu Journal: Adv Mater Date: 2020-06-23 Impact factor: 30.849
Authors: Fang Chen; David C Mundy; Peter Le; Youngyoon Amy Seo; Caitlin M Logan; Gabriella Maria Fernandes-Cunha; Chris A Basco; David Myung Journal: Transl Vis Sci Technol Date: 2022-10-03 Impact factor: 3.048
Authors: Paola Sanjuan-Alberte; Charlie Whitehead; Joshua N Jones; João C Silva; Nathan Carter; Simon Kellaway; Richard J M Hague; Joaquim M S Cabral; Frederico C Ferreira; Lisa J White; Frankie J Rawson Journal: iScience Date: 2022-06-07