A vascularized crypt-patterned colon model for high-throughput drug screening and disease modelling

Leveraging Organ-on-Chip Models to Investigate Host-Microbiota Dynamics and Targeted Therapies for Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is an idiopathic gastrointestinal disease with drastically increasing incidence rates. Due to its multifactorial etiology, a precise investigation of the pathogenesis is extremely difficult. Although reductionist cell culture models and more complex disease models in animals have clarified the understanding of individual disease mechanisms and contributing factors of IBD in the past, it remains challenging to bridge research and clinical practice. Conventional 2D cell culture models cannot replicate complex host-microbiota interactions and stable long-term microbial culture. Further, extrapolating data from animal models to patients remains challenging due to genetic and environmental diversity leading to differences in immune responses. Human intestine organ-on-chip (OoC) models have emerged as an alternative in vitro model approach to investigate IBD. OoC models not only recapitulate the human intestinal microenvironment more accurately than 2D cultures yet may also be advantageous for the identification of important disease-driving factors and pharmacological interventions targets due to the possibility of emulating different complexities. The predispositions and biological hallmarks of IBD focusing on host-microbiota interactions at the intestinal mucosal barrier are elucidated here. Additionally, the potential of OoCs to explore microbiota-related therapies and personalized medicine for IBD treatment is discussed.

Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3D in vitro tissue models of disease

Rapid advances in tissue engineering have resulted in more complex and physiologically relevant 3D in vitro tissue models with applications in fundamental biology and therapeutic development. However, the complexity provided by these models is often not leveraged fully due to the reductionist methods used to analyze them. Computational and mathematical models developed in the field of systems biology can address this issue. Yet, traditional systems biology has been mostly applied to simpler in vitro models with little physiological relevance and limited cellular complexity. Therefore, integrating these two inherently interdisciplinary fields can result in new insights and move both disciplines forward. In this review, we provide a systematic overview of how systems biology has been integrated with 3D in vitro tissue models and discuss key application areas where the synergies between both fields have led to important advances with potential translational impact. We then outline key directions for future research and discuss a framework for further integration between fields.

Vascularized organoid-on-a-chip: design, imaging, and analysis

Vascularized organoid-on-a-chip (VOoC) models achieve substance exchange in deep layers of organoids and provide a more physiologically relevant system in vitro. Common designs for VOoC primarily involve two categories: self-assembly of endothelial cells (ECs) to form microvessels and pre-patterned vessel lumens, both of which include the hydrogel region for EC growth and allow for controlled fluid perfusion on the chip. Characterizing the vasculature of VOoC often relies on high-resolution microscopic imaging. However, the high scattering of turbid tissues can limit optical imaging depth. To overcome this limitation, tissue optical clearing (TOC) techniques have emerged, allowing for 3D visualization of VOoC in conjunction with optical imaging techniques. The acquisition of large-scale imaging data, coupled with high-resolution imaging in whole-mount preparations, necessitates the development of highly efficient analysis methods. In this review, we provide an overview of the chip designs and culturing strategies employed for VOoC, as well as the applicable optical imaging and TOC methods. Furthermore, we summarize the vascular analysis techniques employed in VOoC, including deep learning. Finally, we discuss the existing challenges in VOoC and vascular analysis methods and provide an outlook for future development.