How human-derived brain organoids are built differently from brain organoids derived of genetically-close relatives: A multi-scale hypothesis

17 Apr 2023  ·  Tao Zhang, Sarthak Gupta, Madeline A. Lancaster, J. M. Schwarz ·

How genes affect tissue scale organization remains a longstanding biological puzzle. As experimental efforts are underway to solve this puzzle via quantification of gene expression and sub-cellular, cellular and tissue structure, computational efforts remain far behind. To potentially help accelerate the computational efforts, we review two recent publications, the first on a cellular-based model for tissues and the second on a cell nucleus model consisting of chromatin and a lamina shell. We then give a perspective on how the two models can be combined to test multiscale hypotheses linking the chromatin scale and the tissue scale. To be concrete, we turn to an in vitro system for the brain known as a brain organoid. We provide a multiscale hypothesis to distinguish structural differences between brain organoids built from induced-pluripotent human stem cells and from induced-pluripotent gorilla and chimpanzee stem cells. Recent experiments discover that a cell fate transition from neuroepithelial cells to radial glial cells includes a new intermediate state that is delayed in human-derived brain organoids as compared to their genetically-close relatives, which significantly narrows and lengthens the cells on the apical side [1]. Additional experiments revealed that the protein ZEB2 plays a major role in the emergence of this new intermediate state with ZEB2 mRNA levels peaking at the onset of the emergence [1]. We postulate that the enhancement of ZEB2 expression driving this intermediate state is potentially due to chromatin reorganization. More precisely, there exists critical strain triggering the reorganization that is higher for human-derived stem cells, thereby resulting in a delay. Such a hypothesis can readily be tested experimentally within individual cells and within brain organoids as well as computationally to work towards solving the gene-to-tissue organization puzzle.

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