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Modelling Human Post-Implantation Development via Extra-Embryonic Niche Engineering.
Hislop, Joshua; Alavi, Amir; Song, Qi; Schoenberger, Rayna; Kamyar, Keshavarz F; LeGraw, Ryan; Velazquez, Jeremy; Mokhtari, Tahere; Taheri, Mohammad Nasser; Rytel, Matthew; de Sousa Lopes, Susana M Chuva; Watkins, Simon; Stolz, Donna; Kiani, Samira; Sozen, Berna; Bar-Joseph, Ziv; Ebrahimkhani, Mo R.
Afiliação
  • Hislop J; Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA.
  • Alavi A; Department of Pathology, Division of Experimental Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Song Q; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA.
  • Schoenberger R; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Kamyar KF; Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • LeGraw R; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Velazquez J; Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Mokhtari T; Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA.
  • Taheri MN; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA.
  • Rytel M; Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA.
  • de Sousa Lopes SMC; Department of Pathology, Division of Experimental Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Watkins S; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA.
  • Stolz D; Department of Pathology, Division of Experimental Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Kiani S; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA.
  • Sozen B; Department of Pathology, Division of Experimental Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Bar-Joseph Z; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA.
  • Ebrahimkhani MR; Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA.
bioRxiv ; 2023 Jul 24.
Article em En | MEDLINE | ID: mdl-37398391
ABSTRACT
Implantation of the human embryo commences a critical developmental stage that comprises profound morphogenetic alteration of embryonic and extra-embryonic tissues, axis formation, and gastrulation events. Our mechanistic knowledge of this window of human life remains limited due to restricted access to in vivo samples for both technical and ethical reasons. Additionally, human stem cell models of early post-implantation development with both embryonic and extra-embryonic tissue morphogenesis are lacking. Here, we present iDiscoid, produced from human induced pluripotent stem cells via an engineered a synthetic gene circuit. iDiscoids exhibit reciprocal co-development of human embryonic tissue and engineered extra-embryonic niche in a model of human post-implantation. They exhibit unanticipated self-organization and tissue boundary formation that recapitulates yolk sac-like tissue specification with extra-embryonic mesoderm and hematopoietic characteristics, the formation of bilaminar disc-like embryonic morphology, the development of an amniotic-like cavity, and acquisition of an anterior-like hypoblast pole and posterior-like axis. iDiscoids offer an easy-to-use, high-throughput, reproducible, and scalable platform to probe multifaceted aspects of human early post-implantation development. Thus, they have the potential to provide a tractable human model for drug testing, developmental toxicology, and disease modeling.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article