Biology subjects

Csikasz-Nagy, A.

Publications and source records attributed to Csikasz-Nagy, A..

9 recordsLinked to original sources

bioRxiv2026

Circadian clock regulates intestinal epithelial cell differentiation via NOTCH/Hes1 oscillations

The circadian clock regulates diverse cellular processes, including intestinal epithelial cell (IEC) proliferation. However, mechanisms regulating clock-dependent IEC differentiation remain unknown. We performed a time course RNA-Seq using the mouse small intestine and identified NOTCH signaling, a key mechanism regulating IEC differentiation, as one of the pathways under the control of circadian rhythms. Using mouse enteroids, we discovered that a NOTCH reporter, Hes1-luciferase, exhibits both ultradian or circadian oscillations depending on the stemness of mouse enteroids. Furthermore, single-cell analysis of Hes1-mCherry revealed that the period of Hes1 oscillations varies widely, but circadian rhythms modulate the number of Hes1-mCherry+ cells in the population. Finally, we show that Paneth cell numbers fluctuate over the circadian cycle, suggesting that circadian clock-regulated Hes1 drives the circadian dynamics of IEC composition. Our study provides a deeper insight into circadian regulation of IEC differentiation, which will be critical for applications of chronotherapies for digestive diseases.

molecular biology↗

bioRxiv2025

Digital Twin Approaches for Interpretable Side Effect Prediction in Drug Discovery

Artificial intelligence plays an ever-greater role in preclinical drug development, ranging from target identification and molecule design to ADME-Tox prediction; however, predicting side effects before performing clinical trials is still lagging behind. The best performing side effect predictors in the literature use either ATC codes, which are expert-derived features not even available at early stages, or graph neural networks based on chemical similarity, which - although use readily available features - are "black boxes" that do not deliver actionable insights. We argue that a paradigm shift is needed. Instead of using the latest neural network architectures that have proved worthy in other domains with a plethora of available data, one could use the off-targets of the compounds and build simple and interpretable predictors of side effects. To add another layer of biological realism, intricate biophysical mechanisms within the cells could also be simulated and used as features for training. Although not outperforming the current methods by a great margin, this digital twin-based model has the benefit of being interpretable, i.e., it puts biology behind the predictions. We showcase, with real-world examples, how the side effects predicted by this model can be interpreted and traced back to off-target proteins, and the complexes and signaling pathways in which they partake. In this way, the proposed model not only provides actionable insights, but in the future, may contribute to the amendment of secondary pharmacology assays. HighlightsO_LINo standard tool is available to predict side effects in early-phase drug discovery. C_LIO_LIAs publicly available side effect data is scarce, only simple models should be trained. C_LIO_LISimple models trained on biorealistic features, such as off-target proteins, are interpretable. C_LIO_LIInterpreting predictions can highlight critical off-targets and are therefore actionable. C_LI

pharmacology and toxicology↗

bioRxiv2023

Simulated complexes formed from a set of postsynaptic proteins suggest a localised effect of a hypomorphic Shank mutation

The postsynaptic density is an elaborate protein network beneath the postsynaptic membrane built up from the same major proteins but differing between synapses in exact composition and organization. Mutations perturbing generally occurring protein:protein interactions in this network can lead to specific effects, and the translation of biochemical effects to the system level can be especially challenging. In this work we use systems biology-based modeling of protein complex distributions in a set of major postsynaptic proteins including either a wild-type or a hypomorphic PDZ mutant Shank protein. Our results suggest that the effect of such mutations is heavily dependent on the overall availability of the protein components of the whole network. We simulated protein complex formation based on experimental data of various cell types with diverse protein abundances. The simulations revealed that mutations interfering with a single protein interaction can lead to protein complex changes only in specific cell types and in specific complexes. Although our system is currently far from a comprehensive description of the PSD, the results suggest a way to interpret specific mutations within a complex framework. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/562557v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@fdf273org.highwire.dtl.DTLVardef@3891deorg.highwire.dtl.DTLVardef@1f0c37borg.highwire.dtl.DTLVardef@1b1e629_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIEffect of mutations affecting protein:protein interactions can be modeled in context C_LIO_LIChanges in emerging protein complexes upon mutations are dependent on the availability of the individual proteins C_LIO_LIOur model provides conceptual explanation of confided phenotypic effects of a mutation C_LI

systems biology↗

bioRxiv2020

Unifying the mechanism of mitotic exit control in a spatio-temporal logical model

1The transition from mitosis into the first gap phase of the cell cycle in budding yeast is controlled by the Mitotic Exit Network (MEN). The network interprets spatio-temporal cues about the progression of mitosis and ensures that release of Cdc14 phosphatase occurs only after completion of key mitotic events. The MEN has been studied intensively however a unified understanding of how localization and protein activity function together as a system is lacking. In this paper we present a compartmental, logical model of the MEN that is capable of representing spatial aspects of regulation in parallel to control of enzymatic activity. Through optimization of the model, we reveal insights into role of Cdc5 in Cdc15 localization and the importance of Lte1 regulation in control of Bfa1. We show that our model is capable of correctly predicting the phenotype of[~] 80% of mutants we tested, including mutants representing mislocalizing proteins. We use a continuous time implementation of the model to demonstrate the role of Cdc14 Early Anaphase Release (FEAR) to ensure robust timing of anaphase and verify our findings in living cells. We show that our model can represent measured cell-cell variation in Spindle Position Checkpoint (SPoC) mutants. Finally, we use the model to predict the impact of forced localization of MEN proteins and validate these predictions experimentally. This model represents a unified view of the mechanism of mitotic exit control.

systems biology↗

bioRxiv2019

Proteostasis collapse halts G1 progression and delimits replicative lifespan

Loss of proteostasis and cellular senescence are key hallmarks of cell aging, but whether they are subject to direct cause-effect relationships is not known. We show that most yeast cells arrest in G1 before death with low nuclear levels of cyclin Cln3, a key activator of Start extremely sensitive to chaperone status. Chaperone availability is seriously compromised in aged cells, and the G1 arrest coincides with massive aggregation of a metastable chaperone-activity reporter. A mathematical model integrating autocatalytic protein aggregation and a minimal Start network recapitulates empirical observations. As key predictions, G1-cyclin overexpression increases lifespan in a chaperone-dependent manner, and lifespan reduction by enforced protein aggregation is greatly alleviated by increased expression of specific chaperones or cyclin Cln3. Overall, our data indicate the crucial role of chaperone malfunction in setting lifespan in yeast cells, and configure a molecular pathway whereby proteostasis breakdown acts as a direct effector of cell senescence.

cell biology↗

bioRxiv2019

Comparative analysis of Synthetic Physical Interactions with the yeast centrosome

1The yeast centrosome or Spindle Pole Body (SPB) is situated in the nuclear membrane, where it nucleates spindle microtubules and acts as a signalling hub. Previously, we used Synthetic Physical Interactions to map the regions of the cell that are sensitive to forced relocalization of proteins across the proteome [Berry et al., 2016]. Here, we expand on this work to show that the SPB, in particular, is sensitive to the relocalization of many proteins. This work inspired a new data analysis approach that indicates that relocalization screens may produce more growth defects than previously reported. A set of associations with the SPB result in elevated SPB number and since hyper-proliferation of centrosomes is a hallmark of cancer cells, these associations point the way for the use of yeast models in the study of spindle formation and chromosome segregation in cancer.

cell biology↗

bioRxiv2018

The chaperone-client network subordinates cell-cycle entry to growth and stress

The precise coordination of growth and proliferation has a universal prevalence in cell homeostasis. As a prominent property, cell size is modulated by the coordination between these processes in bacterial, yeast and mammalian cells, but the underlying molecular mechanisms are largely unknown. Here we show that multifunctional chaperone systems play a concerted and limiting role in cell-cycle entry, specifically driving nuclear accumulation of the G1 Cdk-cyclin complex. Based on these findings, we establish and test a molecular competition model that recapitulates cell-cycle-entry dependence on growth rate. As key predictions at a single-cell level, we show that availability of the Ydj1 chaperone and nuclear accumulation of the G1 cyclin Cln3 are inversely dependent on growth rate and readily respond to changes in protein synthesis and stress conditions that alter protein folding requirements. Thus, chaperone workload would subordinate Start to the biosynthetic machinery and dynamically adjust proliferation to the growth potential of the cell.

molecular biology↗

bioRxiv2018

Activation of polarized cell growth by inhibition of cell polarity

A key feature of cells is the capacity to activate new functional polarized domains contemporaneously to pre-existing ones. How cells accomplish this is not clear. Here, we show that in fission yeast inhibition of cell polarity at pre-existing domains of polarized cell growth is required to activate new growth. This inhibition is mediated by the ERM-related polarity factor Tea3, which antagonizes the activation of the Rho-GTPase Cdc42 by its co-factor Scd2. We demonstrate that Tea3 acts in a phosphorylation-dependent manner controlled by the PAK kinase Shk1 and that, like Scd2, Tea3 is direct substrate of Shk1. Importantly, we show that Tea3 and Scd2 compete for their binding to Shk1, indicating that their biochemical competition for Shk1 underpins their antagonistic roles in controlling polarity. Thus, by preventing pre-existing growth domains from becoming overpowering, Tea3 allows cells to redistribute their polarity-activating machinery to prospective sites and control their timing of activation.

cell biology↗

bioRxiv2017

Reconstructing regulatory pathways by systematically mapping protein localization interdependency networks

A key goal of functional genomics is to elucidate how genes and proteins act together in space and time, wired as pathways, to control specific aspects of cell biological function. Here, we develop a method to quantitatively determine proteins localization interdependencies at high throughput. We show that this method can be used to systematically obtain weighted, signed and directional pathway relationships, and hence to reconstruct a detailed pathway wiring. As proof-of-principle, we focus on 42 factors that control cell polarity in fission yeast (Schizosaccharomyces pombe) and use high-throughput confocal microscopy and quantitative image analysis to reconstruct their Localization Interdependency Network (LIN). Through this approach we identify 554 pairwise interactions across the factors, including 98% putative new directed links. Validation of an unexpected interaction between two polarity factor subgroups - the polarity landmark proteins and the cell integrity pathway components - by orthogonal phenotyping demonstrates the power of the LIN approach in detecting subtle, systems-level causal connections.

cell biology↗