Combinatorial protein barcodes enable self-correcting neuron tracing with nanoscale molecular context

Area of Science:

• Neuroscience
• Molecular Biology
• Bioinformatics

Background:

• Mapping neuronal morphology is crucial for understanding brain circuits.
• Current methods face limitations due to segmentation errors and sample defects.
• Existing genetic labeling strategies have spectral or morphological signal limitations.

Purpose of the Study:

• To introduce PRISM (Protein-barcode Reconstruction via Iterative Staining with Molecular annotations), a novel platform for high-resolution neuronal mapping.
• To overcome limitations of existing methods for reconstructing neuronal morphology with molecular context.
• To enable accurate, self-correcting neuron reconstruction and synaptic mapping.

Main Methods:

• PRISM integrates combinatorial protein barcoding, tissue expansion, multi-cycle imaging, and barcode-augmented reconstruction.
• Utilizes anti-genically distinct, cell-filling proteins for enhanced label diversity (>750-fold over multicolor labeling).
• Applies barcode-augmented reconstruction for intrinsic error correction and gap reconnection.

Main Results:

• Achieved an 8x increase in automatic tracing accuracy of genetically labeled neurons by combining barcodes with shape information.
• Demonstrated PRISM's ability to proofread across micron-scale gaps and reconnect neurites across hundreds of microns.
• Mapped synapse distribution onto traced neural morphology, characterizing thorny excrescences and discovering TE size correlations.

Conclusions:

• PRISM provides a self-correcting neuron reconstruction platform with integrated molecular context.
• The platform significantly enhances the accuracy and completeness of nanoscale neuronal mapping.
• PRISM facilitates detailed characterization of neural circuits and synaptic structures.