Biology subjects

Kern, R.

Publications and source records attributed to Kern, R..

6 recordsLinked to original sources

bioRxiv2026

Functional genetics reveals a role for the proteasome in regulating centromere assembly

Centromeres link chromosomes to spindle microtubules to direct their segregation during mitosis. The vertebrate centromere is built on two critical DNA-binding proteins, the histone H3-variant CENP-A and histone fold protein CENP-T. CENP-T is a potent scaffold for kinetochore assembly, such that concentrating it at ectopic sites is sufficient to build kinetochore-like structures. How cells prevent excess CENP-T from acting at non-centromere sites remains unclear. Here, using optical pooled screening to systematically define the requirements for CENP-A and CENP-T localization, we recover the established CENP-A deposition machinery and reveal a specific role for the proteasome in controlling CENP-T levels. We find that non-centromere CENP-T is degraded in a ubiquitin- and proteasome-dependent manner. Whereas centromere-incorporated CENP-T is stable, CENP-T that is not bound to centromeres is rapidly turned over, with the CENP-T histone fold region sufficient to confer proteasome sensitivity. Quiescent cells, which disassemble their centromeres, continue to express CENP-T but eliminate it through continuous degradation. Thus, whereas CENP-A is controlled primarily through regulated deposition, cells additionally control CENP-T by selectively degrading the unincorporated protein.

cell biology↗

bioRxiv2026

Dual-acting Estrogen Receptor Modulator-Histone Lysine Demethylase Inhibitors

Epigenetic dysfunction and the malfunction of endocrine proteins such as estrogen receptor alpha (ER) are two key mechanisms for the sustenance of breast carcinoma. Agents that target ER signaling malfunctions are standard therapies for ER-dependent breast cancer (BCa) subtypes. Small molecule inhibitors of epigenetic modifiers, histone lysine demethylases (KDMs), have shown promise as therapeutic agents for several BCa subtypes. We demonstrated herein that the integration of ER antagonist (Tamoxifen) and agonist (17-ethinylestradiol) ligands with deferiprone (DFP)-derived KDM inhibitor moiety furnished dual-acting agents Tam-KDMi and EED-KDMi, respectively. These agents showed robust on-target effects and potent BCa cells-selective anti-proliferative activities. The Tam-KDMi are cytotoxic to both ER(+) and ER(-) BCa cells, while the lack of ER-signaling inhibition conferred an enhanced ER(-) cells cytotoxic to the EED-KDMi. Representative lead compounds Tam-KDMi DW-116 and EED-KDMi DW-088 and DW-95 significantly reduce tumor growth in murine xenograft models of ER(-) and ER(+) BCas with TGI as high as 70%. Collectively, our data showed that DW-116, DW-088 and DW-95 have a high potential as leads for the development of new agents for the treatment of BCa subtypes regardless of the tumor ER expression status.

cancer biology↗

bioRxiv2025

Transcriptomic Signature and PROTAC Strategy Revealed Histone Lysine Demethylase as a Target of Anticancer Activity of Deferiprone.

Deferiprone (DFP) is an iron chelator approved for treating iron overload in thalassemia patients. Recent observations have suggested that DFP has promising anticancer activities ascribed to several mechanisms including reduction of the intracellular free labile iron and zinc ion pools and inhibition of the activities of other intracellular targets, including ribonucleotide reductase (RNR). We previously reported that DFP inhibits the demethylase activities of several Fe(II)/- ketoglutarate dependent histone lysine demethylases (KDMs) at much lower concentrations at which it inhibits RNR activities and/or reduces the labile intracellular iron and zinc ion pools. In this study, we used RNA sequencing (RNA seq) and PROTACs strategies to validate and quantify the contribution of intracellular KDM inhibition to the antiproliferative activities of DFP. We report herein that DFP elicited gene expression signature that is largely similar to that of JIB-04, an established KDM inhibitor (KDMi), in two breast cancer (BCa) cells (MCF-7 and MDA-MD-231). Importantly, RNA seq revealed that DFP and JIB-04 downregulated the expression of hypoxia-inducible factor 1 (HIF-1), an oncogene whose expression is commonly modulated through histone demethylation mediated by KDMs and degraded by several KDMi. Moreover, DFP-derived PROTACs elicited enhanced cancer cell selective antiproliferative activities and intracellular on-target effects, downregulating several KDMs implicated in the etiology of BCa cells, including a strong degradation of KDMs 2A, 3A and 5B, and a moderate degradation of KDMs 4A-C, 5C, 6B. Collectively, our data supports KDM inhibition as a key mechanism of anticancer activity of DFP and identifies PROTAC is a viable strategy to obtain novel DFP analogs with improved potency and therapeutic index.

cancer biology↗

bioRxiv2025

Brieflow: An Integrated Computational Pipeline for High-Throughput Analysis of Optical Pooled Screening Data

Optical pooled screening (OPS) has emerged as a powerful technique for functional genomics, enabling researchers to link genetic perturbations with complex cellular morphological phenotypes at unprecedented scale. However, OPS data analysis presents challenges due to massive datasets, complex multi-modal integration requirements, and the absence of standardized frameworks. Here, we present Brieflow, a computational pipeline for end-to-end analysis of fixed-cell optical pooled screening data. We demonstrate Brieflows capabilities through reanalysis of a CRISPR-Cas9 screen encompassing 5,072 fitness-conferring genes, processing more than 70 million cells with multiple phenotypic markers. To accelerate biological interpretation, we additionally present MozzareLLM, a framework leveraging large language models to identify biological processes within phenotypic clusters and prioritize gene candidates for experimental validation. Our combined analysis recovered coherent biological modules missed by existing analytical approaches, including five core mitochondrial sub-programs that were absent from the original study. The modular design and open-source implementation of Brieflow facilitates the integration of novel analytical components while ensuring computational reproducibility and improved performance for the use of high-content phenotypic screening in biological discovery.

cell biology↗

bioRxiv2024

Toward generalizable phenotype prediction from single-cell morphology representations

Functional cell processes (e.g., molecular signaling, response to environmental stimuli, mitosis, etc.) impact cell phenotypes, which scientists can easily and robustly measure with cell morphology. However, linking these morphology measurements with phenotypes remains challenging because biologically interpretable phenotypes require manually annotated labels. Automatic phenotype annotation from cell morphology would link biological processes with their phenotypic outcomes and deepen understanding of cell function. We propose that nuclear morphology can be a predictive marker for cell phenotypes that is generalizable across cell types. Nucleus morphology is commonly and easily accessible with microscopy, but annotating specific phenotypic information requires labels. Therefore, we reanalyzed a pre-labeled, publicly-available nucleus microscopy dataset from the MitoCheck consortium to predict single-cell phenotypes. We extracted single-cell morphology features using CellProfiler and DeepProfiler, which provide fast, robust, and generalizable data processing pipelines. We trained multinomial, multi-class elastic net logistic regression models to classify nuclei into one of 15 phenotypes such as Anaphase, Apoptosis, and Binuclear. In a held-out test set, we observed an overall F1 score of 0.84, where individual phenotype scores ranged from 0.64 (indicating moderate performance) to 0.99 (indicating high performance). Notably, phenotypes such as Elongated, Metaphase, and Apoptosis showed high performance. While CellProfiler and DeepProfiler morphology features were generally equally effective, combining feature spaces yielded the best results for 9 of the 15 phenotypes. However, leave-one-image-out (LOIO) cross-validation analysis showed a significant performance decline, indicating our model could not reliably predict phenotype in new single images. Poor performance, which we show was unrelated to factors like illumination correction or model selection, limits generalizability to new datasets and highlights the challenges of morphology to phenotype annotation. Nevertheless, we modified and applied our approach to the JUMP Cell Painting pilot data. Our modified approach improved dataset alignment and highlighted many perturbations that are known to be associated with specific phenotypes. We propose several strategies that could pave the way for more generalizable methods in single-cell phenotype prediction, which is a step toward morphology representation ontologies that would aid in cross-dataset interpretability.

cell biology↗

bioRxiv2017

Taking a semi-local dynamic snapshot as a possibility for local homing in initially naive bumblebees

For central place foragers, such as bumblebees, it is essential to return reliably to their nest. Instead of just flying away to forage, bumblebees, leaving their inconspicuous nest hole for the first time, need to gather and learn sufficient information about the surroundings to allow them to return to the nest at the end of their trip. Therefore, we assume an intrinsic learning program that manifests itself in the flight structure immediately after leaving the nest for the first time.\n\nIn this study, we recorded and analysed the first outbound flight of individually marked naive bumblebees in an indoor environment. We found characteristic loop-like features in the flight pattern that appear to be necessary for the bees to acquire environmental information and might be relevant for finding the nest hole after a foraging trip.\n\nDespite common features in their spatio-temporal organisation, the first departure flights from the nest are characterised by a high level of variability in their loop-like flight structure across animals. Changes in turn direction of body orientation, for example, are distributed evenly across the entire area used for the flights without any systematic relation to the nest location. By considering the common flight motifs as well as this variability, we came to the hypothesis, that a kind of dynamic snapshot is taken during the early phase of departure flights in the close vicinity of the nest location. The quality of this snapshot is hypothesised to be tested during the later phases of the departure flights concerning its usefulness for local homing.

animal behavior and cognition↗