Biology subjects

Moos, K.

Publications and source records attributed to Moos, K..

5 recordsLinked to original sources

bioRxiv2026

Sexually dimorphic effects of mutations in ccRCC driver genes in renal proximal tubule cells

Clear cell renal cell carcinoma (ccRCC) arises more frequently in men than in women, but it remains unclear why this is the case. Mouse models that mimic the truncal mutation of the two most commonly affected tumor suppressor genes in human ccRCC revealed that the transcriptional effects of Vhl or Vhl/Pbrm1 mutation in male and female proximal tubule cells only partially overlap. Cellular responses to mutations in these genes were also sex-specific. Vhl and Vhl/Pbrm1 mutation in females, but only Vhl/Pbrm1 mutation in males, induced the accumulation of PLIN2-coated lipid droplets. The accumulation of optically-clear lipid droplets, reflecting the hallmark clear-cell histological feature of ccRCC, only arose in Vhl/Pbrm1 mutant male mice. Consistent with lipotoxic tubular damage, markers of tubular repair and ongoing epithelial cell proliferation correlated with the lipid accumulation phenotypes. Vhl/Pbrm1 mutation caused stronger clonal expansion than Vhl mutation in males, but not in females. These findings suggest that there are likely to be sexual dimorphisms at the very earliest stages of ccRCC evolution that result from the interplay of intrinsic and mutation-induced transcriptional differences between male and female proximal tubule cells.

cancer biology↗

bioRxiv2024

Halfpipe: a tool for analyzing metabolic labeling RNA-seq data to quantify RNA half-lives

We introduce Halfpipe, a tool for analyzing RNA-seq data from metabolic RNA labeling experiments. Its main features are the absolute quantification of 4sU-labeling-induced T>C conversions in the data as generated by SLAM-seq, calculating the proportion of newly synthesized transcripts, and estimating subcellular RNA half-lives. Halfpipe excels at correcting critical biases caused by typically low labeling efficiency. We measure and compare the RNA metabolism in the G1 phase and during the mitosis of synchronized human cells. We find that RNA half-lives of constantly expressed RNAs are similar in mitosis and G1 phase, suggesting that RNA stability of those genes is constant throughout the cell cycle. Our estimates correlate well with literature values and with known RNA sequence features. Halfpipe is freely available at https://github.com/IMSBCompBio/Halfpipe

bioinformatics↗

bioRxiv2024

The PIDDosome controls cardiomyocyte polyploidization during postnatal heart development

The adult mammalian heart is characterized by post-mitotic polyploid cardiomyocytes (CMs). Understanding how CMs regulate cell cycle exit and ploidy can help developing new heart regenerative therapies. Here, we uncover that the PIDDosome, a multi-protein complex activating the endopeptidase Caspase-2, helps to implement a CM-specific differentiation program that limits ploidy during postnatal heart development. DNA content analyses show that PIDDosome-loss causes a cell-autonomous increase in nuclear and cellular CM ploidy. Remarkably, increased ploidy does not affect cardiac structure nor function. PIDDosome-imposed ploidy restriction commences at postnatal day 7 (P7), reaching a plateau on P14. PIDDosome activation requires ANKRD26, targeting PIDD1 to mother centrioles. Opposite to prior observations in liver development, the PIDDosome limits CM polyploidization in a p53-independent manner but reliant on p21/Cdkn1a, a notion supported by nuclear RNA sequencing and genetic deletion experiments. Our results provide new insights how proliferation of polyploid CMs is restricted during postnatal heart development.

developmental biology↗

bioRxiv2023

Nuclear export is a limiting factor in eukaryotic mRNA metabolism

The eukaryotic mRNA life cycle includes transcription, nuclear mRNA export and degradation. To quantify all these processes simultaneously, we perform thiol-linked alkylation after metabolic labeling of RNA with 4-thiouridine (4sU), followed by sequencing of RNA (SLAM-seq) in the nuclear and cytosolic compartments. We develop a model that reliably quantifies mRNA synthesis, nuclear export, and nuclear and cytosolic degradation rates on a genome-wide scale. We find that nuclear degradation of polyadenylated mRNA is negligible and nuclear mRNA export is slow, while cytosolic mRNA degradation is comparatively fast. Consequently, an mRNA molecule generally spends most of its life in the nucleus. We also observe large differences in the nuclear export rates of different 3UTR transcript isoforms. Furthermore, we identify genes whose expression is abruptly induced upon metabolic labeling. These transcripts are exported substantially faster than average mRNAs, suggesting the existence of alternative export pathways. Our results highlight nuclear mRNA export as a limiting factor in mRNA metabolism and gene regulation.

systems biology↗

bioRxiv2021

A user-friendly tool for cloud-based whole slide image segmentation, with examples from renal histopathology

BackgroundImage-based machine learning tools hold great promise for clinical applications in nephropathology and kidney research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often face prohibitive challenges in using these tools to their full potential, including the lack of technical expertise, suboptimal user interface, and limited computation power. MethodsWe have developed Histo-Cloud, a tool for segmentation of whole slide images (WSIs) that has an easy-to-use graphical user interface. This tool runs a state-of-the-art convolutional neural network (CNN) for segmentation of WSIs in the cloud and allows the extraction of features from segmented regions for further analysis. ResultsBy segmenting glomeruli, interstitial fibrosis and tubular atrophy, and vascular structures from renal and non-renal WSIs, we demonstrate the scalability, best practices for transfer learning, and effects of dataset variability. Finally, we demonstrate an application for animal model research, analyzing glomerular features in murine models of aging, diabetic nephropathy, and HIV associated nephropathy. ConclusionThe ability to access this tool over the internet will facilitate widespread use by computational non-experts. Histo-Cloud is open source and adaptable for segmentation of any histological structure regardless of stain. Histo-Cloud will greatly accelerate and facilitate the generation of datasets for machine learning in the analysis of kidney histology, empowering computationally novice end-users to conduct deep feature analysis of tissue slides.

pathology↗