International Journal of Molecular Sciences (Dec 2022)

Cost-Effective Mechanical Aggregation of Cardiac Progenitors and Encapsulation in Matrigel Support Self-Organization in a Dynamic Culture Environment

  • Tiago P. Dias,
  • Sandra N. Pinto,
  • Sandra Carvalho,
  • Tiago G. Fernandes,
  • Fábio Fernandes,
  • Maria Margarida Diogo,
  • Maria C. Peleteiro,
  • Manuel Prieto,
  • Joaquim M. S. Cabral

DOI
https://doi.org/10.3390/ijms232415785
Journal volume & issue
Vol. 23, no. 24
p. 15785

Abstract

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Human iPSC-derived self-organized cardiac tissues can be valuable for the development of platforms for disease modeling and drug screening, enhancing test accuracy and reducing pharmaceutical industry financial burden. However, current differentiation systems still rely on static culture conditions and specialized commercial microwells for aggregation, which hinders the full potential of hiPSC-derived cardiac tissues. Herein, we integrate cost-effective and reproducible manual aggregation of hiPSC-derived cardiac progenitors with Matrigel encapsulation and a dynamic culture to support hiPSC cardiac differentiation and self-organization. Manual aggregation at day 7 of cardiac differentiation resulted in 97% of beating aggregates with 78% of cTnT-positive cells. Matrigel encapsulation conjugated with a dynamic culture promoted cell migration and the creation of organized structures, with observed cell polarization and the creation of lumens. In addition, encapsulation increased buoyancy and decreased coalescence of the hiPSC-derived cardiac aggregates. Moreover, VEGF supplementation increased over two-fold the percentage of CD31-positive cells resulting in the emergence of microvessel-like structures. Thus, this study shows that the explored culture parameters support the self-organization of hiPSC-derived cardiac microtissues containing multiple cardiac cell types. Additional stimuli (e.g., BMP) in long-term scalable and fully automatized cultures can further potentiate highly structured and mature hiPSC-derived cardiac models, contributing to the development of reliable platforms for high-throughput drug screening and disease modeling.

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