Biology subjects

Krebs, C. F.

Publications and source records attributed to Krebs, C. F..

11 recordsLinked to original sources

bioRxiv2025

Spatial Analysis of T Cell Clonality in Autoimmune Kidney Disease Using TRV Probes

Hypothesizing that the localization of T cell clones correlates with immune function, our goal was to develop an unbiased method to study the spatial distribution of T cells in tissues. We created an in situ hybridization panel with 248 probes that identify immune and tissue cell types, and 132 probes for all variable TRAV, TRBV, TRGV, and TRDV gene segments. Applying this approach to analyze renal biopsies from patients with autoimmune kidney disease, combinations of TRV segments provided spatial information about T cell clonality. Confined clusters of clonally related {beta} T cells were found in proximity to increased numbers of antigen-presenting cells, B cells, and other T cells, reflecting local immune cell interactions. {gamma}{delta} T cells were more frequently located outside or at their periphery of T cell infiltration areas. In conclusion, integrating spatial information with TCR clonotype analysis provided new insights into the organization of immune responses at the tissue level.

immunology↗

bioRxiv2025

SCALE: Unsupervised Multi-Scale Domain Identification in Spatial Omics Data

Single-cell spatial transcriptomics enables precise mapping of cellular states and functional domains within their native tissue environment. These functional domains often exist at multiple spatial scales, with larger domains encompassing smaller ones, reflecting the hierarchical organization of biological systems. However, the identification of these functional domain hierarchies has been hardly explored due to the lack of appropriate computational methods. In this work, we present SCALE, an unsupervised algorithm for multi-scale domain identification in spatial transcriptomics data. SCALE combines neural graph representation learning with an entropy-based search algorithm to detect functional domains at different scales. It reaches state-of-the-art performance in single- and multi-scale domain detection on simulated and murine brain Xenium and MERFISH data, as well as patient-derived kidney tissue, highlighting its robustness and scalability across diverse tissue types and platforms. SCALEs ease of use makes it a powerful aid for advancing our understanding of tissue organization and function in health and disease.

bioinformatics↗

bioRxiv2024

Spatio-temporal interaction of immune and renal cells determines glomerular crescent formation in autoimmune kidney disease

Rapidly progressive glomerulonephritis (RPGN) is the most aggressive group of autoimmune kidney disease with the worst prognosis. Anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis, anti-glomerular basement membrane (anti-GBM) and lupus nephritis are the most common causes of RPGN and are characterized by the formation of glomerular crescents and infiltration of leukocytes that eventually lead to glomerulosclerosis and kidney failure. In this work, we used high-resolution spatial transcriptomics of 32 ANCA, 19 lupus nephritis, 6 anti-GBM, and 6 control patients to understand how intercellular signaling between immune and renal tissue cells leads to renal inflammation and glomerular injury. Using 3,218,210 immune and kidney cells, we observed that the biological pathways involved in the sequence of glomerular crescent formation are similar across the diseases. While innate immune cells infiltrated the glomerular compartment relatively early, later increases in adaptive immune cells were largely restricted to the periglomerular regions. These changes in immune cells temporally correlated with increases in glomerular parietal epithelial (PEC) and fibrotic mesangial cells, suggesting disease-relevant functional signaling between these immune and renal cells. Cell communication analysis revealed early disease PDGF signaling from epithelial and mesangial cells to PECs, causing their activation and proliferation. At later stages, TGF-{beta} signaling from macrophages, T cells, epithelial cells, and mesangial cells to PECs triggered the expression of extracellular matrix components resulting in glomerulosclerosis. Our results highlight a spatio-temporally conserved progression into glomerular crescents and sclerosis for ANCA, lupus nephritis, and anti-GBM disease, which is driven by consecutive PDGF and TGF-{beta} signaling to PECs.

immunology↗

bioRxiv2024

PCA-based spatial domain identification with state-of-the-art performance

The identification of biologically meaningful domains is a central step in the analysis of spatial transcriptomic data. Following Occams razor, we show that a simple PCA-based algorithm for spatial domain identification rivals the performance of ten competing state-of-the-art methods across six single-cell spatial transcriptomic datasets. Our reductionist approach, NichePCA, provides researchers with intuitive domain interpretation and excels in execution speed, robustness, and scalability.

bioinformatics↗

bioRxiv2024

The integrated stress response/eIF2α pathway controls cytokine production in tissue-resident memory CD4+ T cells

Tissue-resident memory T (Trm) cells are a specialized T cell population that resides in tissues and can play both a protective and pathogenic role. The mechanism that enables Trm cells to provide a rapid protective response while restricting their function in homeostasis remains unclear. Here, we show that human and mouse CD4+ Trm cells exist in a poised state, characterized by storage of proinflammatory type-1 and type-3 cytokine mRNAs without protein production. In steady-state conditions, cytokine mRNA translation in Trm cells is suppressed by the integrated stress response (ISR)/eIF2 pathway, whereas Trm-cell activation under inflammatory conditions results in eIF2 dephosphorylation, leading to derepression and rapid translation of the cytokine mRNAs stored in stress granules. Pharmacological inhibition of eIF2 dephosphorylation resulted in reduced cytokine production from Trm cells, and ameliorated autoimmune kidney disease in mice. Consistent with these results, the ISR pathway in Trm cells was downregulated in patients with immune-mediated diseases of the kidney and the intestine. Our results identify ISR/eIF2-mediated control of cytokine mRNA translation as an underlying mechanism that restricts Trm cell activity in homeostasis but also promotes rapid response upon local infection or autoimmune reaction.

immunology↗

bioRxiv2023

Emergence and suppressive function of Tr1 cells in glomerulonephritis

T regulatory type 1 (Tr1) cells, which are defined by their regulatory function, lack of Foxp3, high expression of IL-10, CD49b, and LAG3, are known to be able to suppress Th1 and Th17 in the intestine. Th1 and Th17 cells are also the main drivers of crescentic glomerulonephritis, the most severe form of renal autoimmune disease. However, whether Tr1 cells emerge in renal inflammation and moreover, whether they exhibit regulatory function during glomerulonephritis has not been thoroughly investigated yet. To address these questions, we used a mouse model of experimental crescentic glomerulonephritis and double Foxp3mRFP IL-10eGFP reporter mice. We found that Foxp3neg IL-10-producing CD4+ T cells infiltrate the kidneys during glomerulonephritis progression. Using single-cell RNA- sequencing, we could show that these cells express the core transcriptional factors characteristic of Tr1 cells. In line with this, Tr1 cells showed a strong suppressive activity ex vivo and were protective in experimental crescentic glomerulonephritis in vivo. Finally, we could also identify Tr1 cells in the kidneys of patients with anti-neutrophil cytoplasmic autoantibody (ANCA)-associated glomerulonephritis and define their transcriptional profile. Tr1 cells are currently used in several immune-mediated inflammatory diseases, e.g. as T- cell therapy. Thus, our study provides proof of concept for Tr1 cell-based therapies in experimental glomerulonephritis.

immunology↗

bioRxiv2022

Single-cell transcriptomics reveals a mechanosensitive injury signaling pathway in early diabetic nephropathy

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease and histopathologic glomerular lesions are among the earliest structural alterations of DN. However, the signaling pathways that initiate these glomerular alterations are incompletely understood. To delineate the cellular and molecular basis for DN initiation, we performed single-cell and bulk RNA sequencing of renal cells from type 2 diabetes mice (BTBR ob/ob) at the early stage of DN. Analysis of differentially expressed genes revealed glucose-independent responses in glomerular cell types. The gene regulatory network upstream of glomerular cell programs suggested the activation of mechanosensitive transcriptional pathway MRTF-SRF predominantly taking place in mesangial cells. Importantly, activation of MRTF-SRF transcriptional pathway was also identified in DN glomeruli in independent patient cohort datasets. Furthermore, ex vivo kidney perfusion suggested that the regulation of MRTF-SRF is a common mechanism in response to glomerular hyperfiltration. Overall, our study presents a comprehensive single-cell transcriptomic landscape of early DN, highlighting mechanosensitive signaling pathways as novel targets of diabetic glomerulopathy.

molecular biology↗

bioRxiv2022

Transcriptional and clonal characterization of cytotoxic CD8+ T cells in crescentic glomerulonephritis

Crescentic glomerulonephritis (cGN), most often caused by anti-neutrophil cytoplasmic autoantibody (ANCA)-associated vasculitis, is an aggressive form of immune-mediated kidney disease and represents an important cause of end-stage renal failure. Although it is known that T cells infiltrate the kidney in cGN, their precise role in autoimmune kidney disease remains to be fully elucidated. By performing single-cell analysis, we identified activated, clonally expanded CD8+ T cells with a cytotoxic gene expression profile in the kidneys of patients with ANCA-associated cGN. Using an experimental model of cGN, we demonstrated that clonally expanded murine CD8+ T cells highly expressed the cytotoxic molecule granzyme B. Moreover, lack of CD8+ T cells or granzyme B resulted in an ameliorated course of cGN. This was associated with reduced cleaved caspase-3 induction in renal tissue cells. Our data indicate that clonally expanded cytotoxic CD8+ T cells have a previously unrecognized pathogenic function in aggravating immune-mediated kidney disease.

immunology↗

bioRxiv2022

GM-CSF drives immune-mediated glomerular disease by licensing monocyte-derived cells to produce MMP12

Glomerulonephritis is a group of immune-mediated diseases that cause inflammation within the glomerulus and adjacent compartments of the kidney and is a major cause of end-stage renal disease. T cells are among the main drivers of glomerulonephritis. However, the T cell subsets, cytokine networks, and downstream effector mechanisms that lead to renal tissue injury are largely unknown, which has hindered the development of targeted therapies. Here we identify a population of GM-CSF-producing T cells that accumulates in the kidneys of patients with ANCA-associated glomerulonephritis, infiltrates the renal tissue in a mouse model of glomerulonephritis, and promotes tissue destruction and loss of renal function. Mechanistically, we show that GM-CSF producing T cells licence monocyte-derived cells to produce matrix metalloproteinase 12 (MMP12), which cleaves components of the glomerular basement membrane and exacerbates renal pathology. These findings provide a mechanistic rationale for the immunopathology of T cell-mediated diseases and identify the "GM-CSF - monocyte-derived cells - MMP12" pathway as a promising therapeutic target in treatment of glomerulonephritis.

immunology↗

bioRxiv2020

Deep learning-based molecular morphometrics for kidney biopsies

Morphologic examination of tissue biopsies is essential for histopathological diagnosis. However, accurate and scalable cellular quantification in human samples remains challenging. Here, we present a deep learning-based approach for antigen-specific cellular morphometrics in human kidney biopsies, which combines indirect immunofluorescence imaging with U-Net-based architectures for image-to-image translation and dual segmentation tasks, achieving human-level accuracy. In the kidney, podocyte loss represents a hallmark of glomerular injury and can be estimated in diagnostic biopsies. Thus, we profiled over 27,000 podocytes from 110 human samples, including patients with anti-neutrophil cytoplasmic antibody-associated glomerulonephritis (ANCA-GN), an immune-mediated disease with aggressive glomerular damage and irreversible loss of kidney function. Previously unknown morphometric signatures of podocyte depletion were identified in patients with ANCA-GN, which allowed patient classification and showed potential for risk stratification in combination with routine clinical tools. Together, our approach enables robust and scalable molecular morphometric analysis of human tissues, yielding deeper biological insights into the human kidney pathophysiology. SummaryDeep learning enables robust and scalable molecular morphometric analysis of human tissues, yielding deeper biological insights into the human kidney pathophysiology.

pathology↗

bioRxiv2018

Realistic in silico generation and augmentation of single cell RNA-seq data using Generative Adversarial Neural Networks

A fundamental problem in biomedical research is the low number of observations available, mostly due to a lack of available biosamples, prohibitive costs, or ethical reasons. Augmenting few real observations with generated in silico samples could lead to more robust analysis results and a higher reproducibility rate. Here we propose the use of conditional single cell Generative Adversarial Neural Networks (cscGANs) for the realistic generation of single cell RNA-seq data. cscGANs learn non-linear gene-gene dependencies from complex, multi cell type samples and use this information to generate realistic cells of defined types. Augmenting sparse cell populations with cscGAN generated cells improves downstream analyses such as the detection of marker genes, the robustness and reliability of classifiers, the assessment of novel analysis algorithms, and might reduce the number of animal experiments and costs in consequence. cscGANs outperform existing methods for single cell RNA-seq data generation in quality and hold great promise for the realistic generation and augmentation of other biomedical data types.

bioinformatics↗