Protein nanobarcodes enable single-step multiplexed fluorescence imaging
Daniëlle de Jong-Bolm1, Mohsen Sadeghi2, Cristian A Bogaciu1
1Department of Neuro- and Sensory physiology, University of Göttingen Medical Center, Cluster of Excellence "Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells" (MBExC), Göttingen, Germany.
Plos Biology
|December 11, 2023
Summary
We developed protein nanobarcodes for efficient multiplexed cellular imaging. This novel method uses nanobodies and deep learning for precise protein identification in complex biological assays.
Area of Science:
- Biotechnology
- Molecular Biology
- Cellular Imaging
Background:
- Multiplexed cellular imaging often involves complex, sequential probe application.
- Existing methods using antibodies or DNA barcodes are time-consuming.
Purpose of the Study:
- To develop a streamlined method for multiplexed protein detection and identification.
- To enable precise analysis of large numbers of protein combinations in a single step.
Main Methods:
- Developed protein nanobarcodes using epitope combinations and specific nanobodies.
- Utilized nanobodies conjugated to distinct fluorophores for a single imaging step.
- Applied deep neural networks to fluorescence images for protein identification.
Main Results:
- Achieved precise protein identification using fluorescence images from nanobarcodes.
- Demonstrated an efficient and straightforward protein identification method.
- Successfully applied the method to a multicell competition assay with neurexin and neuroligin isoforms.
Conclusions:
- Protein nanobarcodes offer an efficient solution for complex multiplexed cellular imaging.
- The deep learning-based approach enables high-precision protein identification.
- This method is applicable to various biological assays, including isoform binding studies.
