Converging neural-centric and mechano-regulation in organoid modeling for system biology and medicine

<p>The understanding of complex biological systems and the development of effective precision medicine strategies necessitate controllable and tractable experimental models. The human body is composed of systemic and systematic interactions at multiple levels such as occurs between cells, tissues, and organs. Hence, how to recapitulate the system complexity of the human body has become an inevitable problem. This review emphasizes the need to understand complex interactions between organs by exploring the potential use of organoids and their derivatives. We focus on the nervous system and its pivotal roles in the regulation of peripheral organs, and meanwhile, highlight the importance of often overlooked mechanobiological factors. The nervous system controls many neuromodulation processes and is capable of transmitting biological information through electrophysiology. In addition, mechano-regulation operates at the cellular and microenvironment levels, functioning through system-level regulation. It can influence neural tissue or collaborate with nerves to direct skin and visceral tissue responses and their immunity. To achieve <i>in situ</i> probing and manipulation of such processes, we recommend the use of organoid assembloids that directly fusion individual organoids to create interactive structures of neural-centric complexes and mechano-regulation conditions, or organoids-on-a-chip that relies on microfluidic chips as tailorable bioreactors to form multi-organ associations and simulate and incorporate mechanobiological and neurological regulations. Based on mechano-regulatory influence at the cellular and microenvironment levels, we may develop more systematic, biomimetic, and robust in-vitro models. These models not only approach genuine physiology and pathology in humans without sacrificing real-time observation capabilities but present minimal ethical concerns and offer substantial potential for industrial scalability.</p>