Abstract
Tissues contain a variety of interconnected cells with different functional states and shapes and this complex organization and tissue architecture is impossible to capture in a single plane. In this thesis, the general objective was to develop novel high dimensional 3D imaging strategies to explore large volumes of intact tissues
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and organoids on a single cell level. Furthermore, we aimed to set up a spatio-phenotypic profiling pipeline that extracts fluorescent marker intensities, morphological features, and positional information of every single cell in the dataset and can link back to that specific cell in the original 3D image. We then applied this technology to study kidney development and Wilms Tumor (WT) biology. In Chapter 2 we developed an eight-color, single acquisition, multispectral Large-scale Single-cell Resolution 3D (mLSR-3D) imaging method by implementing ‘on the fly’ linear unmixing. We combined it with a deep learning enabled analysis pipeline; STAPL-3D, dedicated to (sub-) cellular segmentation and feature extraction from millions of cells present in intact tissue. The impact of the resulting high-dimensional dataset, encompassing molecular, morphological, and spatial features and enabling omics-like analysis, was demonstrated by the heterogeneity mapping of millions of cells within intact WT tissue and the identification of previously undescribed WT cell subsets. This technique was further used throughout this thesis to acquire volumetric imaging data. In Chapter 3 we combine 3D imaging and single-cell RNA sequencing to identify LGR6 as a marker for nephron progenitor cells (NPCs) and trace the progeny of LGR6+ cells throughout embryonic kidney development. Our findings demonstrate the multipotent capacity of LGR6+ cells to form all segments of the nephron, indicating the potential of LGR6 for NPC isolation, growing organoids and therapeutic targeting. We optimized and validated mLSR-3D for a large range of tissue types, including brain tissue and developed a protocol to reproducibly generate multispectral 3D imaging of intact healthy and tumor tissues using mLSR-3D, which is presented in detail in Chapter 4. For successful spectral imaging and linear unmixing, overlapping emission signals are required to be in the same order of magnitude. Designing intensity-balanced immunolabeling experiments becomes increasingly challenging the more antibody combinations are used together. To avoid testing combinations one-by-one, we designed an intensity equalization assay that provides, in a single overview, all intensities and possible combinations. Organoids harbor enormous potential for life sciences. However, most organoids are miniature, fragile cellular assemblies that can be challenging to harvest, immunolabel, optically clear and mount for imaging without damaging them. Therefore, we provide an optimized protocol for single-cell resolution 3D imaging of intact organoids in Chapter 5. Finally, in Chapter 6 we review the new insights into cancer biology uniquely brought to light by 3D imaging. We discuss the anticipated future directions of technological development and consider the challenges that must be overcome. In Chapter 7, we place our findings in a broader perspective and discuss the implications of 3D imaging-based profiling of healthy and tumor tissues, with a focus on WT.
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