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Increasing the information depth of single kidney biopsies can improve diagnostic precision, personalized medicine and accelerate basic kidney research. Until now, information on mRNA abundance and morphologic analysis has been obtained from different samples, missing out on the spatial context and single-cell correlation of findings. Herein, we present scoMorphoFISH, a modular toolbox to obtain spatial single-cell single-mRNA expression data from routinely generated kidney biopsies. Deep learning was used to virtually dissect tissue sections in tissue compartments and cell types to which single-cell expression data were assigned. Furthermore, we show correlative and spatial single-cell expression quantification with super-resolved podocyte foot process morphometry. In contrast to bulk analysis methods, this approach will help to identify local transcription changes even in less frequent kidney cell types on a spatial single-cell level with single-mRNA resolution. Using this method, we demonstrate that ACE2 can be locally upregulated in podocytes upon injury. In a patient suffering from COVID-19-associated collapsing FSGS, ACE2 expression levels were correlated with intracellular SARS-CoV-2 abundance. As this method performs well with standard formalin-fixed paraffin-embedded samples and we provide pretrained deep learning networks embedded in a comprehensive image analysis workflow, this method can be applied immediately in a variety of settings.
Chronic kidney disease (CKD) is a major public health burden affecting more than 500 million people worldwide. Podocytopathies are the main cause for the majority of CKD cases due to pathogenic morphological as well as molecular biological alterations of postmitotic podocytes. Podocyte de-differentiation is associated with foot process effacement subsequently leading to proteinuria. Since currently no curative drugs are available, high throughput screening methods using a small number of animals are a promising and essential tool to identify potential drugs against CKD in the near future. Our study presents the implementation of the already established mouse GlomAssay as a semi-automated high-throughput screening method—shGlomAssay—allowing the analysis of several hundreds of FDA-verified compounds in combination with downstream pathway analysis like transcriptomic and proteomic analyses from the same samples, using a small number of animals. In an initial prescreening we have identified vitamin D3 and its analog calcipotriol to be protective on podocytes. Furthermore, by using RT-qPCR, Western blot, and RNA sequencing, we found that mRNA and protein expression of nephrin, the vitamin D receptor and specific podocyte markers were significantly up-regulated due to vitamin D3- and calcipotriol-treatment. In contrast, kidney injury markers were significantly down-regulated. Additionally, we found that vitamin D3 and calcipotriol have had neither influence on the expression of the miR-21 and miR-30a nor on miR-125a/b, a miRNA described to regulate the vitamin D receptor. In summary, we advanced the established mouse GlomAssay to a semi-automated high-throughput assay and combined it with downstream analysis techniques by using only a minimum number of animals. Hereby, we identified the vitamin D signaling pathway as podocyte protective and to be counteracting their de-differentiation.