Hematopoietic stem cells (HSCs) develop from the hemogenic endothelium in cluster structures that protrude into the embryonic aortic lumen. Although much is known about the molecular characteristics of the developing hematopoietic cells, we lack a complete understanding of their origin and the three-dimensional organization of the niche. Here, we use advanced live imaging techniques of organotypic slice cultures, clonal analysis, and mathematical modeling to show the two-step process of intra-aortic hematopoietic cluster (IACH) formation. First, a hemogenic progenitor buds up from the endothelium and undergoes division forming the monoclonal core of the IAHC. Next, surrounding hemogenic cells are recruited into the IAHC, increasing their size and heterogeneity. We identified the Notch ligand Dll4 as a negative regulator of the recruitment phase of IAHC. Blocking of Dll4 promotes the entrance of new hemogenic Gfi1 + cells into the IAHC and increases the number of cells that acquire HSC activity. Mathematical modeling based on our data provides estimation of the cluster lifetime and the average recruitment time of hemogenic cells to the cluster under physiologic and Dll4-inhibited conditions.
Many efforts targeting amyloid-β (Aβ) plaques for the treatment of Alzheimer's Disease thus far have resulted in failures during clinical trials. Regional and temporal heterogeneity of efficacy and dependence on plaque maturity may have contributed to these disappointing outcomes. In this study, we mapped the regional and temporal specificity of various anti-Aβ treatments through high-resolution light-sheet imaging of electrophoretically cleared brains. We assessed the effect on amyloid plaque formation and growth in Thy1-APP/PS1 mice subjected to β-secretase inhibitors, polythiophenes, or anti-Aβ antibodies. Each treatment showed unique spatiotemporal Aβ clearance, with polythiophenes emerging as a potent anti-Aβ compound. Furthermore, aligning with a spatial-transcriptomic atlas revealed transcripts that correlate with the efficacy of each Aβ therapy. As observed in this study, there is a striking dependence of specific treatments on the location and maturity of Aβ plaques. This may also contribute to the clinical trial failures of Aβ-therapies, suggesting that combinatorial regimens may be significantly more effective in clearing amyloid deposition.
Genetic and biochemical evidence suggests a role for amyloid-β (Aβ) in Alzheimer’s disease, yet many anti-Aβ treatments are clinically ineffective. Regional heterogeneity of efficacy may contribute to these disappointing results. Here we compared the regiospecificity of various anti-Aβ treatments by combining focused electrophoretic whole-brain clearing, amyloid labelling and light-sheet imaging with whole-brain analyses of plaque topology in Aβ-overexpressing mice. Aβ plaque numbers progressed from around 1’200’000 to 2’500’000 over a 9-month period. We then assessed the regiospecific plaque clearance in mice subjected to β-secretase inhibition, amyloid intercalation by polythiophenes, and anti-Aβ antibodies. Each treatment showed unique spatiotemporal Aβ clearance signatures, with polythiophenes emerging as potent anti-Aβ compounds with promising pharmacokinetic properties and the anti-Aβ antibody showing only minor effects. By aligning (25 µm)3 voxels that showed drug effectiveness to spatial transcriptomics atlases, we identified genes matching regiospecific Aβ clearance. As expected, Bace1 expression was highly correlated with the regiospecific efficacy of BACE inhibition. In addition, we found that voxels cleared by polythiophenes correlated with transcripts encoding synaptic proteins, whereas voxels cleared by BACE inhibition correlated with oligodendrocyte-specific genes. The differential regional susceptibility of distinct plaque populations to specific treatments may explain the clinical failure of anti-Aβ therapies, and suggests that combinatorial regimens may improve functional outcomes.
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