PDF(Pubmed)
Abstract：
Three-dimensional (3D) geometrical models are potent tools for quantifying complex tissue features and exploring structure-function relationships. However, these models are generally incomplete due to experimental limitations in acquiring multiple (> 4) fluorescent channels in thick tissue sections simultaneously. Indeed, predictive geometrical and functional models of the liver have been restricted to few tissue and cellular components, excluding important cellular populations such as hepatic stellate cells (HSCs) and Kupffer cells (KCs). Here, we combined deep-tissue immunostaining, multiphoton microscopy, deep-learning techniques, and 3D image processing to computationally expand the number of simultaneously reconstructed tissue structures. We then generated a spatial single-cell atlas of hepatic architecture (Hep3D), including all main tissue and cellular components at different stages of post-natal development in mice. We used Hep3D to quantitatively study 1) hepatic morphodynamics from early post-natal development to adulthood, and 2) the effect on the liver\'s overall structure when changing the hepatic environment after removing KCs. In addition to a complete description of bile canaliculi and sinusoidal network remodeling, our analysis uncovered unexpected spatiotemporal patterns of non-parenchymal cells and hepatocytes differing in size, number of nuclei, and DNA content. Surprisingly, we found that the specific depletion of KCs results in morphological changes in hepatocytes and HSCs. These findings reveal novel characteristics of liver heterogeneity and have important implications for both the structural organization of liver tissue and its function. Our next-gen 3D single-cell atlas is a powerful tool to understand liver tissue architecture, opening up avenues for in-depth investigations into tissue structure across both normal and pathological conditions.
摘要：
三维（3D）几何模型是量化复杂组织特征和探索结构-功能关系的有力工具。然而,由于同时在厚组织切片中获取多个(>4个)荧光通道的实验限制,这些模型通常是不完整的。的确,肝脏的预测几何和功能模型仅限于少数组织和细胞成分，排除重要的细胞群体，如肝星状细胞（HSC）和枯否细胞（KCs）。这里,我们结合了深层组织免疫染色，多光子显微镜，深度学习技术，和3D图像处理以计算地扩展同时重建的组织结构的数量。然后，我们生成了肝脏结构的空间单细胞图谱（Hep3D），包括小鼠出生后发育不同阶段的所有主要组织和细胞成分。我们使用Hep3D定量研究1）从出生后早期发育到成年的肝脏形态动力学，和2）去除KCs后改变肝脏环境对肝脏整体结构的影响。除了完整描述胆管和正弦网络重塑外，我们的分析揭示了大小不同的非实质细胞和肝细胞的意外时空模式，原子核的数量，和DNA含量。令人惊讶的是,我们发现KCs的特异性消耗导致肝细胞和HSC的形态学改变.这些发现揭示了肝脏异质性的新特征，对肝脏组织的结构组织及其功能具有重要意义。我们的下一代3D单细胞图谱是了解肝脏组织结构的强大工具，为在正常和病理条件下深入研究组织结构开辟了途径。
