Sung Yun Park, Arlo Sheridan, Bobae An, Erin Jarvis, Julia Lyudchik, William Patton, Jun Y Axup, Stephanie W Chan, Hugo G J Damstra, Daniel Leible, Kylie S Leung, Clarence A Magno, Aashir Meeran, Julia M Michalska, Franz Rieger, Claire Wang, Michelle Wu, George M Church, Jan Funke, Todd Huffman, Kathleen G C Leeper, Sven Truckenbrodt, Johan Winnubst, Joergen M R Kornfeld, Edward S Boyden, Samuel G Rodriques, Andrew C Payne
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However, multicolor approaches are spectrally limited in diversity, whereas nucleic acid barcoding lacks a cell-filling morphology signal for segmentation. Here, we introduce PRISM (Protein-barcode Reconstruction via Iterative Staining with Molecular annotations), a platform that integrates combinatorial delivery of anti-genically distinct, cell-filling proteins with tissue expansion, multi-cycle imaging, barcode-augmented reconstruction, and molecular annotation. Protein barcodes increase label diversity by >750-fold over multicolor labeling and enable morphology reconstruction with intrinsic error correction. We acquired a ~10 million μm<sup>3</sup> volume of mouse hippocampal area CA2/3, multiplexed across 23 barcode antigen and synaptic marker channels. By combining barcodes with shape information, we achieve an 8x increase in automatic tracing accuracy of genetically labelled neurons. 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引用次数: 0
摘要
用分子注释绘制纳米级神经元形态对于理解健康和功能失调的脑回路至关重要。目前的方法受到图像分割错误和样本缺陷(如信号间隙、截面损失)的限制。遗传策略有望通过使用易于区分的细胞身份标签来克服这些挑战。然而,多色方法在光谱多样性方面受到限制,而核酸条形码缺乏用于分割的细胞填充形态学信号。在这里,我们介绍了PRISM (Protein-barcode Reconstruction via Iterative stain with Molecular annotations),这是一个将抗原性不同的细胞填充蛋白与组织扩增、多周期成像、条形码增强重建和分子注释结合在一起的平台。蛋白质条形码使标签多样性比多色标记增加了50- 750倍,并使形态学重建具有内在的纠错能力。我们获得了约1000万μm 3体积的小鼠海马区CA2/3,通过23个条形码抗原和突触标记通道进行多路复用。通过将条形码与形状信息相结合,我们将遗传标记神经元的自动跟踪准确性提高了8倍。我们证明PRISM支持自动校对跨越微米尺度的空间间隙,并重新连接跨越数百微米的不连续的神经突。利用PRISM的分子注释功能,我们将突触的分布映射到追踪的神经形态学上,表征棘手的突触结构,如荆棘赘生物(te),并发现同一树突上空间近端te之间的大小相关性。PRISM因此支持分子背景下的自我校正神经元重建。
Combinatorial protein barcodes enable self-correcting neuron tracing with nanoscale molecular context.
Mapping nanoscale neuronal morphology with molecular annotations is critical for understanding healthy and dysfunctional brain circuits. Current methods are constrained by image segmentation errors and by sample defects (e.g., signal gaps, section loss). Genetic strategies promise to overcome these challenges by using easily distinguishable cell identity labels. However, multicolor approaches are spectrally limited in diversity, whereas nucleic acid barcoding lacks a cell-filling morphology signal for segmentation. Here, we introduce PRISM (Protein-barcode Reconstruction via Iterative Staining with Molecular annotations), a platform that integrates combinatorial delivery of anti-genically distinct, cell-filling proteins with tissue expansion, multi-cycle imaging, barcode-augmented reconstruction, and molecular annotation. Protein barcodes increase label diversity by >750-fold over multicolor labeling and enable morphology reconstruction with intrinsic error correction. We acquired a ~10 million μm3 volume of mouse hippocampal area CA2/3, multiplexed across 23 barcode antigen and synaptic marker channels. By combining barcodes with shape information, we achieve an 8x increase in automatic tracing accuracy of genetically labelled neurons. We demonstrate PRISM supports automatic proofreading across micron-scale spatial gaps and reconnects neurites across discontinuities spanning hundreds of microns. Using PRISM's molecular annotation capability, we map the distribution of synapses onto traced neural morphology, characterizing challenging synaptic structures such as thorny excrescences (TEs), and discovering a size correlation among spatially proximal TEs on the same dendrite. PRISM thus supports self-correcting neuron reconstruction with molecular context.