Department of Genetics, Stanford University School of Medicine, Stanford, United States; Neuroscience Program, Stanford University School of Medicine, Stanford, United States
Zhonglin Lyu
Department of Neurosurgery, Stanford University School of Medicine, Stanford, United States
Min K Tsai
Department of Genetics, Stanford University School of Medicine, Stanford, United States
Cancer Biology Program, Stanford University School of Medicine, Stanford, United States; Immunology Program, Stanford University School of Medicine, Stanford, United States; Department of Pathology, Stanford University School of Medicine, Stanford, United States
Wonjae Lee
Department of Neurosurgery, Stanford University School of Medicine, Stanford, United States
Department of Genetics, Stanford University School of Medicine, Stanford, United States; Cancer Biology Program, Stanford University School of Medicine, Stanford, United States; Department of Pathology, Stanford University School of Medicine, Stanford, United States
Cell-cell interactions influence all aspects of development, homeostasis, and disease. In cancer, interactions between cancer cells and stromal cells play a major role in nearly every step of carcinogenesis. Thus, the ability to record cell-cell interactions would facilitate mechanistic delineation of the role of the cancer microenvironment. Here, we describe GFP-based Touching Nexus (G-baToN) which relies upon nanobody-directed fluorescent protein transfer to enable sensitive and specific labeling of cells after cell-cell interactions. G-baToN is a generalizable system that enables physical contact-based labeling between various human and mouse cell types, including endothelial cell-pericyte, neuron-astrocyte, and diverse cancer-stromal cell pairs. A suite of orthogonal baToN tools enables reciprocal cell-cell labeling, interaction-dependent cargo transfer, and the identification of higher order cell-cell interactions across a wide range of cell types. The ability to track physically interacting cells with these simple and sensitive systems will greatly accelerate our understanding of the outputs of cell-cell interactions in cancer as well as across many biological processes.
