化学
分辨率(逻辑)
高分辨率
色谱法
生物物理学
分子生物学
人工智能
遥感
计算机科学
生物
地质学
作者
Noah B. Bissonnette,Marie E. Zamanis,Steve D. Knutson,Zane Boyer,Angelo Harris,Daniel Martin,Jacob B. Geri,Suzana S. Couto,Tahamtan Ahmadi,Anantharaman Muthuswamy,Mark Fereshteh,David W. C. MacMillan
摘要
Many disease states can be understood by elucidating small-scale biomolecular protein interaction networks, or microenvironments. Photoproximity labeling methods, like μMap, have recently emerged as high-resolution techniques for mapping spatial relationships within subcellular architectures. However, in vitro models typically utilized lack the cell-type heterogeneity and three-dimensional structure essential for translating findings to clinical settings. To this end, formalin-fixed paraffin-embedded (FFPE) tissues are invaluable model systems for biomedical research, as they preserve complex multicellular interaction networks in their natural environment. While identifying microscale interactions in these samples could provide critical clinical insights, chemical modifications introduced during formalin-fixation and de-cross-linking are incompatible with standard photoproximity labeling techniques. Herein, we introduce μMap-FFPE, a new labeling system that enables comparison of the CD20 interactome across healthy cells, cancerous cells, and preserved patient tissues.
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