生物分子
编码(内存)
显微镜
分辨率(逻辑)
超分辨显微术
纳米技术
生物
计算生物学
细胞生物学
计算机科学
材料科学
神经科学
物理
扫描共焦电子显微镜
光学
人工智能
作者
Siyue Fan,X Li,Huan Liu,Mengying Ye,Yanliang He,Wenhao Fu,Feng Chen,Yongxi Zhao
出处
期刊:Angewandte Chemie
[Wiley]
日期:2025-03-11
卷期号:64 (21): e202425136-e202425136
被引量:3
标识
DOI:10.1002/anie.202425136
摘要
Abstract Cellular biomolecules may exhibit dense distribution and organization at the nanoscale to govern vital biological processes. However, it remains a common challenge to digitize the spatially dense biomolecules under the spatial resolution of microscopies. Here, a proof‐of‐principle method, molecule differentiation encoding microscopy by orthogonal tandem repeat DNA identifiers is reported, to resolve the copy numbers of dense biomolecules in cellular nanoenvironments. The method encodes each copy of the same biomolecules into different types of DNA barcodes based on stochastic multiplexed reactions. It can transform the overlap of the same spectrum into the overlap of different spectra. Furthermore, an algorithm is developed to automatically quantitate overlapping spots and individual spots. Using this method, RNAs in the cytoplasm, DNA epigenetic modifications in the cell nucleus, and glycans and glycoRNAs on the cell surface are dissected, respectively. It is found that all these biomolecules present dense distribution with diverse degrees in crowded cellular nanoenvironments. Especially, an average 17% copies of U1 glycoRNA of single cells are gathered in various nano environments on the cell surface. The strategy provides a powerful tool for digitally quantitative visualization of dense biomolecules below the spatial resolution of microscopies and can provide insights into underlying functions and mechanisms of the dense distribution information.
科研通智能强力驱动
Strongly Powered by AbleSci AI