Decellularized Brain Extracellular Matrix Hydrogel Aids the Formation of Human Spinal-Cord Organoids Recapitulating the Complex Three-Dimensional Organization.
Weidong WuYoujun LiuRenfeng LiuYuhao WangYuqi ZhaoHui LiBotao LuCheng JuXinlin GaoHailiang XuYulin CaoShixiang ChengZhiyuan WangShuaijun JiaChunping HuLei ZhuDingjun HaoPublished in: ACS biomaterials science & engineering (2024)
The intricate electrophysiological functions and anatomical structures of spinal cord tissue render the establishment of in vitro models for spinal cord-related diseases highly challenging. Currently, both in vivo and in vitro models for spinal cord-related diseases are still underdeveloped, complicating the exploration and development of effective therapeutic drugs or strategies. Organoids cultured from human induced pluripotent stem cells (hiPSCs) hold promise as suitable in vitro models for spinal cord-related diseases. However, the cultivation of spinal cord organoids predominantly relies on Matrigel, a matrix derived from murine sarcoma tissue. Tissue-specific extracellular matrices are key drivers of complex organ development, thus underscoring the urgent need to research safer and more physiologically relevant organoid culture materials. Herein, we have prepared a rat decellularized brain extracellular matrix hydrogel (DBECMH), which supports the formation of hiPSC-derived spinal cord organoids. Compared with Matrigel, organoids cultured in DBECMH exhibited higher expression levels of markers from multiple compartments of the natural spinal cord, facilitating the development and maturation of spinal cord organoid tissues. Our study suggests that DBECMH holds potential to replace Matrigel as the standard culture medium for human spinal cord organoids, thereby advancing the development of spinal cord organoid culture protocols and their application in in vitro modeling of spinal cord-related diseases.
Keyphrases
- spinal cord
- induced pluripotent stem cells
- extracellular matrix
- neuropathic pain
- spinal cord injury
- endothelial cells
- machine learning
- gene expression
- drug delivery
- multiple sclerosis
- oxidative stress
- white matter
- poor prognosis
- pluripotent stem cells
- climate change
- deep learning
- binding protein
- subarachnoid hemorrhage
- cerebral ischemia
- african american