Quantifying the fidelity of in vitro human cell culture systems using a biomedical foundation model
收藏NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/SRP677179
下载链接
链接失效反馈官方服务:
资源简介:
Primary cell culture is fast becoming a dominant method for discovery work regarding human disease. Currently there are no methods to quantitatively benchmark these systems. Here we apply a uniform in vitro culture system of human intestinal epithelial cells to achieve this goal. We previously established methods for long-term 2-dimensional (2D) cultivation of mouse intestinal epithelial cells using an air-liquid interface (ALI) technique. Here, we further refined these methods for long-term 2D cultivation of human IECs, with histological and molecular features of differentiated intestinal epithelia. Leveraging the power and scalability of a biomedical foundation model (BMFM) trained on single cell RNA sequencing data (BMFM-RNA), we performed classification tasks to identify cell types across sample sources and to quantitatively benchmark our in vitro differentiated cells against cells collected from patient biopsies. We observed a striking concordance between our in vitro differentiated cells and the corresponding cell types in vivo for multiple differentiated secretory cell types. This novel approach using BMFM-RNA holds promise to expand our understanding of the regulatory mechanisms, including gene-gene regulation underlying homeostasis and regeneration, as well as the functions of rare and poorly understood lineages within the human intestinal epithelia. Moreover, these methods may be applicable to other organs, model systems, and experimental modalities. We propose that the framework used here can be deployed as a standard benchmarking methodology, ultimately improving the fidelity of primary human culture systems. Overall design: Human rectal intestinal epithelial stem cells were expanded in matrigel then seeded on transwell filters and allowed to differentiate for either 2 or 7 days, after which cells were collected for single cell RNA sequencing
创建时间:
2026-02-28



