Biology subjects

Hofherr, A.

Publications and source records attributed to Hofherr, A..

4 recordsLinked to original sources

bioRxiv2025

Extra-ciliary role for polycystins in regulation of Ezrin and renal tubular morphology

Full understanding of the functions of the polycystin proteins, PC1 and PC2, in renal epithelial cells is obscured by signaling complexity and renal injury that occurs in Autosomal Dominant Polycystic Kidney Disease (ADPKD). The polycystins likely function as a complex in the primary cilium, yet previous work hinted at a critical role for PC1 function outside of the primary cilium (extra-ciliary) during tubule development. Here, we investigate an extra-ciliary role for the polycystins in regulating renal cell and tubular morphology. First, we found acute loss of polycystins significantly increased the circularity of renal epithelial cells and tubuloids grown in 3D culture. Next, we demonstrated that both PC1 and PC2 can immunoprecipitate Ezrin, an ERM protein important for apical compartment shape. In human ADPKD renal cystic tissue, and after acute inducible knockout of Pkd1 or Pkd2, we found that Ezrin protein abundance is significantly reduced, with the remaining Ezrin protein mis-localized. Immunofluorescence in 2D cells and 3D tubuloids suggested acute polycystin loss specifically reduced the active form of Ezrin at the apical surface, leaving inactive Ezrin colocalized with ZO1 in the cell junctions. A specific ERM phosphorylation inhibitor, NSC668394, phenocopied the increased circularity observed in the Pkd1 knockout spheroids, as did inhibition of PKC activity, implicating the polycystin complex in regulating Ezrin phosphorylation. Our data strongly support a role for the polycystin complex in regulating renal cell and tubular shape via interactions with the ERM protein Ezrin, interactions that do not require trafficking to the primary cilium.

cell biology↗

bioRxiv2025

Deep learning-based image quantification of epithelial cell shapes and its application to polycystic kidney disease

Cell shape is a fundamental determinant of tissue architecture and organ function. In epithelial tissues, cytoskeletal organization and tight junctions regulate cell geometry, shaping functional tissue units. Disruption of these mechanisms may cause diseases such as autosomal dominant polycystic kidney disease (ADPKD), in which cyst formation is characterized by abnormal regulation of epithelial cell shape. The mechanisms of cystogenesis remain incompletely understood, highlighting the need for robust, high-throughput methods to quantify the morphology of epithelial cells. Here, we present a fully automated, deep learning-based image analysis pipeline to quantify epithelial cell shape and tight junction morphology from immunofluorescence images. Our approach employs a U-Net convolutional neural network for accurate segmentation of fluorescence labeled tight junctions. We introduce novel algorithms to quantify overall cell shape and tight junction morphology, as well as to estimate cytoskeletal traction at shared cell borders. Our analysis pipeline objectively identifies subtle morphogenetic changes associated with disease-related mutations, applied to a genetically modified Madin-Darby Canine Kidney cell model of ADPKD. The method enables high-throughput, standardized analysis, reduces observer bias, and facilitates comparison across experiments. We further demonstrate the pipelines generalizability by applying it to Drosophila egg chamber epithelia. Our results establish a robust and scalable framework for analyzing cell shape and mechanical interactions in epithelial tissues, with broad applications in phenotypic screening, disease modeling, and morphogenesis research. Author SummaryThe shape of epithelial cells is critical for organ function. In the kidney, properly shaped epithelial cells assemble to tubules ensuring efficient waste excretion as well as body electrolyte and water balance. Disruption of cell shape regulation can lead to diseases such as autosomal dominant polycystic kidney disease (ADPKD), characterized by cyst formation and displacement of normal kidney tissue. Traditionally, analysis of epithelial cell morphology has relied on manual, low-throughput methods, which are time-consuming and prone to error. To overcome these limitations, we developed a fully automated, artificial intelligence-based pipeline that rapidly and reliably quantifies cell shape and junctional organization from microscopic images. We validated our approach using a cellular model of ADPKD, demonstrating clear differences in cell shape and junctional structure between normal and mutant cells harboring mutations in PKD-related genes. Our method enables efficient, objective analysis of large datasets and provides a powerful tool for understanding the mechanisms underlying cell shape regulation in health and disease.

bioinformatics↗

bioRxiv2024

The Role of the Co-Chaperone DNAJB11 in Polycystic Kidney Disease: Molecular Mechanisms and Cellular Origin of Cyst Formation

Autosomal dominant polycystic kidney disease (ADPKD) is caused by mutations in PKD1 and PKD2, encoding polycystin-1 (PC1) and polycystin-2 (PC2), which are required for the regulation of the renal tubular diameter. Loss of polycystin function results in cyst formation. Atypical forms of ADPKD are caused by mutations in genes encoding endoplasmic reticulum (ER)-resident proteins through mechanisms that are not well understood. Here, we investigate the function of DNAJB11, an ER co-chaperone associated with atypical ADPKD. We generated mouse models with constitutive and conditional Dnajb11 inactivation and Dnajb11-deficient renal epithelial cells to investigate the mechanism underlying autosomal dominant inheritance, the specific cell types driving cyst formation, and molecular mechanisms underlying DNAJB11-dependent polycystic kidney disease. We show that biallelic loss of Dnajb11 causes cystic kidney disease and fibrosis, mirroring human disease characteristics. In contrast to classical ADPKD, cysts predominantly originate from proximal tubules. Cyst formation begins in utero and the timing of Dnajb11 inactivation strongly influences disease severity. Furthermore, we identify impaired PC1 cleavage as a potential mechanism underlying DNAJB11-dependent cyst formation. Proteomic analysis of Dnajb11- and Pkd1-deficient cells reveals common and distinct pathways and dysregulated proteins, providing a foundation to better understand phenotypic differences between different forms of ADPKD.

molecular biology↗

bioRxiv2019

Eomes and Brachyury control pluripotency exit and germ layer segregation by changes of chromatin state

The first lineage specification of pluripotent mouse epiblast segregates neuroectoderm (NE) from mesoderm and endoderm (ME) by currently poorly understood mechanisms. Here we demonstrate that the induction of any ME-gene programs critically relies on the T-box (Tbx) transcription factors Eomes and Brachyury that concomitantly repress pluripotency and NE gene programs. Tbx-deficient cells retain pluripotency and differentiate to NE lineages despite the presence of ME-inducing signals TGF{beta}/Nodal and WNT. Pluripotency and NE gene networks are additionally repressed by Tbx-induced ME factors, demonstrating a remarkable redundancy in program regulation to safeguard mutually exclusive lineage specification. Chromatin analyses revealed that accessibility of ME-gene enhancers depends on Tbx-binding, while NE-gene enhancers are accessible and activation-primed already at pluripotency state. This asymmetry of chromatin landscape thus explains the default differentiation of pluripotent cells to NE in the absence of ME-induction mediated through the activating and repressive functions of early Tbx factors Eomes and Brachyury.

developmental biology↗