Probes for PPIB

The adult spinal cord stem cell potential resides within the ependymal cell population and declines with age. Ependymal cells are, however, heterogeneous, and the biological diversity this represents and how it changes with age remain unknown. Here, we present a single-cell transcriptomic census of spinal cord ependymal cells from adult and aged mice, identifying not only all known ependymal cell subtypes but also immature as well as mature cell states. By comparing transcriptomes of spinal cord and brain ependymal cells, which lack stem cell abilities, we identify immature cells as potential spinal cord stem cells. Following spinal cord injury, these cells re-enter the cell cycle, which is accompanied by a short-lived reversal of ependymal cell maturation. We further analyze ependymal cells in the human spinal cord and identify widespread cell maturation and altered cell identities. This in-depth characterization of spinal cord ependymal cells provides insight into their biology and informs strategies for spinal cord repair.

Background and Aims Although high-throughput single-cell transcriptomic analysis, super-resolution light microscopy and deep-learning methods are broadly used, the gold-standard to evaluate kidney biopsies is still the histologic assessment of formalin-fixed and paraffin embedded (FFPE) samples with parallel ultrastructural evaluation. Recently, we and others have shown that super-resolution fluorescence microscopy can be used to study glomerular ultrastructure in human biopsy samples. Additionally, in the last years mRNA in situ hybridization techniques have been improved to increase specificity and sensitivity to enable transcriptomic analysis with single-mRNA resolution (smFISH). Method For smFISH, we used the fluorescent multiplex RNAscope kit with probes targeting ACE2, WT1, PPIB, UBC and POLR2A. To find an on-slide reference gene, the normfinder algorithm was used. The smFISH protocol was combined with a single-step anti-podocin immunofluorescence enabled by VHH nanobodies. Podocytes were labeled by tyramide-signal amplified immunofluorescence using recombinant anti-WT1 antibodies. Slides were imaged using confocal laser scanning, as well as 3D structured illumination microscopy. Deep-learning networks to segment glomeruli and cell nuclei (UNet and StarDist) were trained using the ZeroCostDL4Mic approach. Scripts to automate analysis were developed in the ImageJ1 macro language. Results First, we show robust functionality of threeplex smFISH in archived routine FFPE kidney biopsy samples with single-mRNA resolution. As variations in sample preparation can negatively influence mRNA-abundance, we established PPIB as an ideal on-slide reference gene to account for different RNA-integrities present in biopsy samples. PPIB was chosen for its most stable expression in microarray dataset of various glomerular diseases determined by the Normfinder algorithm as well as its smFISH performance. To segment glomeruli and to label glomerular and tubulointerstitial cell subsets, we established a combination of smFISH and immunofluorescence. As smFISH requires intense tissue digestion to liberate cross-linked RNAs, immunofluorescence protocols had to be adapted: For podocin, a small-sized single-step label approach enabled by small nanobodies and for WT1, tyramide signal amplification was used. For enhanced segmentation performance, we used deep learning: First, a network was customized to recognize DAPI+ cell nuclei and WT1/DAPI+ podocyte nuclei. Second, a UNet was trained to segment glomeruli in podocin-stained tissue sections. Using these segmentation masks, we could annotate PPIB-normalized single mRNA transcripts to individual cells. We established an ImageJ script to automatize transcript quantification. As a proof-of-principle, we demonstrate inverse expression of WT1 and ACE2 in glomerular vs. tubulointerstitial single cells. Furthermore, in the podocyte subset, WT1 highly clustered whereas no significant ACE2 expression was found under baseline conditions. Additionally, when imaged with super-resolution microscopy, podocyte filtration slit morphology could be visualized The optical resolution was around 125 nm and therefore small enough to resolve individual foot processes. The filtration slit density as a podocyte-integrity marker did not differ significantly from undigested tissue sections proving the suitability for correlative podocyte foot process morphometry with single-podocyte transcript analysis. Conclusion Here we present a modular toolbox which combines algorithms for multiplexed, normalized single-cell gene expression with single mRNA resolution in cellular subsets (glomerular, tubulointerstitial and podocytes). Additionally, this approach enables correlation with podocyte filtration slit ultrastructure and gross glomerular morphometry.

CXCL8 is an inflammatory chemokine elevated in the colorectal cancer (CRC) tumour microenvironment. CXCR2, the major receptor for CXCL8, is predominantly expressed by neutrophils. In the cancer setting, CXCL8 plays important roles in neutrophil chemotaxis, facilitating angiogenesis, invasion, and metastasis. This study aimed to assess the spatial distribution of CXCL8 mRNA expression in CRC specimens, explore associations with clinical characteristics, and investigate the underlying biology of aberrant CXCL8 levels. CXCR2 expression was also assessed in a second cohort of unique CRC primary tumours and synchronously resected matched liver metastases. A previously constructed tissue microarray consisting of a cohort of stage I-IV CRC patients undergoing surgical resection with curative intent (n = 438) was probed for CXCL8 via RNAscope . Analysis was performed using HALO digital pathology software to quantify expression in the tumour and stromal compartments. Scores were assessed for association with clinical characteristics. Mutational analyses were performed on a subset of these patients to determine genomic differences in patients with high CXCL8 expression. A second cohort of stage IV CRC patients with primary and matched metastatic liver tumours was stained via immunohistochemistry for CXCR2, and scores were assessed for clinical significance. CXCL8 expression within the stromal compartment was associated with reduced cancer-specific survival in the first cohort (p = 0.035), and this relationship was potentiated in right-sided colon cancer cases (p = 0.009). High CXCL8 within the stroma was associated with driving a more stromal-rich phenotype and the presence of metastases. When stromal CXCL8 scores were combined with tumour-infiltrating macrophage counts or systemic neutrophil counts, patients classified as high for both markers had significantly poorer prognosis. CXCR2+ immune cell infiltration was associated with increased stromal invasion in liver metastases (p = 0.037). These data indicate a role for CXCL8 in driving unfavourable tumour histological features and promoting metastases. This study suggests that inhibiting CXCL8/CXCR2 should be investigated in patients with right-sided colonic disease and stroma-rich tumours.