Biology subjects

Schnell, S.

Publications and source records attributed to Schnell, S..

16 recordsLinked to original sources

bioRxiv2025

Ehrlich occupancy time: Beyond koff to a complete residence time framework

Drug-target occupancy time--the cumulative duration a target remains bound--critically influences therapeutic efficacy. While Copelands widely-used residence time (1/koff) emphasizes dissociation kinetics, it neglects association rates, rebinding events, and drug elimination that affect in vivo outcomes. Returning to Paul Ehrlichs 1913 principle that drugs act only when bound ("Corpora non agunt nisi fixata"), we develop a mathematically rigorous framework defining Ehrlich occupancy time, EOT, as the integral of fractional target occupancy over time. Our approach explicitly incorporates association (kon) and dissociation (koff) kinetics, accounts for rebinding, and extends to systems with drug removal. For drug-receptor closed systems at equilibrium, we prove that relative EOT equals the equilibrium occupancy fraction; under ligand-excess conditions this reduces to b0/(Kd +b0), where Kd is the dissociation constant and b0 the drug concentration. For induced-fit mechanisms, conformational changes reduce the effective dissociation constant to [Formula] (where k3 and k4 are forward and reverse isomerization rates), prolonging occupancy through kinetic trapping. Critically, for drug-receptor systems with firstorder drug elimination at rate k3, we derive rigorous bounds: b0/[(b0 + Kd)k3] [≤] EOT{infty} [≤] b0/(Kd {middle dot} k3), where EOT{infty}:= limT[->]{infty} EOT(T) is the total cumulative occupancy time as T[->] {infty}, revealing that both binding affinity and elimination rate jointly determine occupancy. This explains why high-affinity drugs can fail clinically if eliminated rapidly, and identifies pharmacokinetic optimization opportunities. We prove Copelands definition is a special case of Ehrlich occupancy time when rebinding is absent. Our framework provides quantitative tools for optimizing drug design beyond binding affinity and enables improved prediction of in vivo efficacy where pharmacokinetics dominate.

pharmacology and toxicology↗

bioRxiv2025

Structural hormesis in protein aggregation: A minimal mechanistic model

Protein aggregation underlies the pathogenesis of many neurodegenerative diseases, and inhibitors are often assumed to elicit monotonic dose-responses. We ask whether simple aggregation pathways can intrinsically generate hormesis--a biphasic profile with low-dose stimulation and high-dose inhibition. We formulate a minimal mechanistic model in which a single inhibitor interacts sequentially with pathway intermediates. Analysis and simulation show a robust non-monotonic response: low inhibitor doses increase aggregate formation, whereas high doses suppress it. We prove that this profile is structural--arising from chemical network topology rather than tuned kinetic parameters. The mechanism rationalizes pro-aggregating effects at low doses and underscores the need for full-range dose-response evaluation in inhibitor screening.

pharmacology and toxicology↗

bioRxiv2025

EpiPred: A gene-specific machine learning model for classifying missense variants in the epilepsy-related gene STXBP1

Missense variants in the STXBP1 gene are a frequent cause of early-onset developmental and epileptic encephalopathies and related neurodevelopmental disorders, but the clinical interpretation of these variants remains a major challenge. Most reported STXBP1 missense variants are classified as variants of uncertain significance (VUS), complicating diagnosis, counseling, and patient eligibility for precision therapies. Here, we developed EpiPred, a gene-specific machine learning classifier that predicts the pathogenicity of STXBP1 missense variants by integrating computational features with empirical evidence from cellular assays. Trained on a curated set of pathogenic and benign variants, EpiPred outperformed leading global prediction tools in accuracy, sensitivity, and specificity. We validated the models predictions using functional assays that measure protein abundance, solubility, stability, and interaction with the SNARE complex partner syntaxin 1. These biochemical readouts aligned closely with model outputs and enabled reclassification of several likely misdiagnosed variants. We deployed EpiPred in an interactive web application that allows clinicians, researchers, and patients to explore predictions for all possible missense variants in STXBP1. Our approach illustrates the power of gene-specific predictive modeling combined with experimental validation to improve variant interpretation and diagnostic resolution. By identifying likely pathogenic STXBP1 variants, including those that may respond to emerging therapies such as molecular chaperones, EpiPred supports more precise genetic diagnoses and offers a generalizable framework for other clinically relevant genes in neurological disease. ONE SENTENCE SUMMARYEpiPred improves STXBP1 variant interpretation, enabling precision genetic diagnoses and promoting access to targeted precision therapies

genetics↗

bioRxiv2023

The unreasonable effectiveness of the total quasi-steady state approximation, and its limitations

In this note, we discuss the range of parameters for which the total quasi-steady-state approximation of the Michaelis-Menten reaction mechanism holds validity. We challenge the prevalent notion that total quasi-steady-state approximation is "roughly valid" across all parameters, showing that its validity cannot be assumed, even roughly, across the entire parameter space -- when the initial substrate concentration is high. On the positive side, we show that the linearized one-dimensional equation for total substrate is a valid approximation when the initial reduced substrate concentration s0/KM is small. Moreover, we obtain a precise picture of the long-term time course of both substrate and complex.

systems biology↗

bioRxiv2022

Branched germline cysts and female-specific cyst fragmentation facilitate oocyte determination in mice

During mouse gametogenesis, germ cells derived from the same progenitor are connected via intercellular bridges forming germline cysts, within which asymmetrical or symmetrical cell fate occurs in female and male germ cells respectively. Here, we have identified branched cyst structures in mice, and investigated their formation and function in oocyte determination. In fetal female cysts, 16.8% of the germ cells are connected by three or four bridges, namely branching germ cells. These germ cells are preferentially protected from cell death and cyst fragmentation, and to accumulate organelles and cytoplasm from sister germ cells to become primary oocytes. Changes in cyst structure and single-cell mRNA profiles suggested that cytoplasmic transport in germline cysts is conducted in a directional manner, in which cellular content is first transported locally between peripheral germ cells and further enriched in branching germ cells, a process causing selective germ cell loss in cysts. Cyst fragmentation occurs extensively in female cysts, but not in male cysts. Male cysts in fetal and adult testes have branched cyst structures, without differential cell fates between germ cells. During cyst formation, E-cadherin junctions between germ cells position intercellular bridges to form branched cysts. Disrupted junction formation in E-cadherin-depleted cysts led to an altered ratio in branched cysts. Germ cell-specific E-cadherin knockout resulted in reductions in primary oocyte number and oocyte size. These findings shed light on the mechanism of how the size of the ovarian reserve, the number of primary oocytes available to sustain adult ovarian function, is determined during ovary formation.

developmental biology↗

bioRxiv2022

Predicting the unpredictable: heatwaves and history of variability shape phytoplankton community thermal responses within one generation

Predicting the effect of increased thermal unpredictability, for example in the shape of heatwaves on phytoplankton metabolic responses is ripe with challenges. While single genotypes in laboratory environments will respond to environmental fluctuations in predictable and repeatable ways, it is difficult to relate rapid evolutionary responses of whole communities to their ecological history. Previously experienced environments, including fluctuations therein, can shape an organisms specific niche as well as their responses to further environmental changes. This is a testable hypothesis as long as samples can be obtained where the environmental history is known, sufficiently diverse, and not obscured by confounding parameters such as day length and precipitation patterns. Here, we tested immediate (i.e. within one generation) metabolic temperature responses of natural phytoplankton assemblages from two thermally distinct regions in the Baltic Sea: the warmer and less predictable Kiel Area, and the overall colder and more predictable Bornholm Basin. Our approach allows us to investigate effects on immediate physiological time scales (responses curves), ecological and evolutionary processes on longer time scales (seasonal differences between basins) as well as mid-term responses during a natural occurring heatwave. We found evidence for a higher degree of phenotypic plasticity in samples from unpredictable environments (Kiel Area).

ecology↗

bioRxiv2021

The human disease gene CLEC16A encodes an intrinsically disordered protein region required for mitochondrial quality control

CLEC16A regulates mitochondrial health through mitophagy and is associated with over 20 human diseases. While CLEC16A has ubiquitin ligase activity, the key structural and functional regions of CLEC16A, and their relevance for human disease, remain unknown. Here, we report that a disease-associated CLEC16A variant lacks a C-terminal intrinsically disordered protein region (IDPR) that is critical for mitochondrial quality control. Using carbon detect NMR, we find that the CLEC16A C terminus lacks secondary structure, validating the presence of an IDPR. Loss of the CLEC16A C-terminal IDPR in vivo impairs pancreatic {beta}-cell mitophagy, mitochondrial function, and glucose-stimulated insulin secretion, ultimately causing glucose intolerance. Deletion of the CLEC16A C-terminal IDPR increases its self-ubiquitination and destabilizes CLEC16A, thus impairing formation of a critical CLEC16A-dependent mitophagy complex. Importantly, CLEC16A stability is dependent on proline bias within the C-terminal IDPR, but not amino acid sequence order or charge. Together, we clarify how an IDPR in CLEC16A prevents diabetes, thus implicating the disruption of IDPRs as novel pathological contributors to diabetes and other CLEC16A-associated diseases.

molecular biology↗

bioRxiv2021

Cerebrovascular super-resolution 4D Flow MRI - using deep learning to non-invasively quantify velocity, flow, and relative pressure

The development of cerebrovascular disease is tightly coupled to changes in cerebrovascular hemodynamics, with altered flow and relative pressure indicative of the onset, development, and acute manifestation of pathology. Image-based monitoring of cerebrovascular hemodynamics is, however, complicated by the narrow and tortuous vasculature, where accurate output directly depends on sufficient spatial resolution. To address this, we present a method combining dedicated deep learning and state-of-the-art 4D Flow MRI to generate super-resolution full-field images with coupled quantification of relative pressure using a physics-driven image processing approach. The method is trained and validated in a patient-specific in-silico cohort, showing good accuracy in estimating velocity (relative error: 12.0 {+/-} 0.1%, mean absolute error (MAE): 0.07 {+/-} 0.06 m/s at peak velocity), flow (relative error: 6.6 {+/-} 4.7%, root mean square error (RMSE): 0.5 {+/-} 0.1 mL/s at peak flow), and with maintained recovery of relative pressure through the circle of Willis (relative error: 11.0 {+/-} 7.3%, RMSE: 0.3 {+/-} 0.2 mmHg). Furthermore, the method is applied to an in-vivo volunteer cohort, effectively generating data at <0.5mm resolution and showing potential in reducing low-resolution bias in relative pressure estimation. Our approach presents a promising method to non-invasively quantify cerebrovascular hemodynamics, applicable to dedicated clinical cohorts in the future.

bioengineering↗

bioRxiv2021

Cultivation-based quantification and identification of bacteria at two hygienic key sides of domestic washing machines

Detergent drawer and door seal represent important sites for microbial life in domestic washing machines. Interestingly, quantitative data on microbial contamination of these sites is scarce. Here, 10 domestic washing machines were swap-sampled for subsequent bacterial cultivation at four different sampling sites, each: detergent drawer, detergent drawer chamber as well as top and bottom part of the rubber door seal. The average bacterial load over all washing machines and sites was 2.1 {+/-} 1.0 x 104 CFU cm-2 (average {+/-} standard error of the mean (SEM)). The top part of the door seal showed the lowest contamination (11.1 {+/-} 9.2 x 101 CFU cm-2), probably due to less humidity. Out of 212 isolates, 178 (84%) were identified on genus level and 118 (56%) on species level using MALDI biotyping, resulting in 29 genera and 40 identified species across all machines. The predominant bacterial genera were Staphylococcus and Micrococcus, which were found at all sites. 21 out of 40 species were classified as opportunistic pathogens, emphasizing the need for regular cleaning of the investigated sites.

microbiology↗

bioRxiv2020

Concentration Sensing in Crowded Environments

Signal transduction within crowded cellular compartments is essential for the physiological function of cells and organisms. While the accuracy with which receptors can probe the concentration of ligands has been thoroughly investigated in dilute systems, the effect of macromolecular crowding on the inference of concentration remains unknown. In this work we develop a novel algorithm to simulate reversible reactions between reacting Brownian particles. This facilitates the calculation of reaction rates and correlation times for ligand-receptor systems in the presence of macromolecular crowding. Using this method, we show that it is possible for crowding to increase the accuracy of estimated ligand concentration based on receptor occupancy. In particular, we find that crowding can enhance the effective association rates between small ligands and receptors to a large enough degree to overcome the increased chance of rebinding due to caging by crowding molecules. For larger ligands, crowding decreases the accuracy of the receptors estimate primarily by decreasing the microscopic association and dissociation rates. SIGNIFICANCEDeveloping an understanding of how cells effectively transmit signals within or between compartments under physical constraints is an important challenge for biophysics. This work investigates the effect that macromolecular crowding can have on the accuracy of a simple ligand-receptor signaling system. We show that the accuracy of an inferred ligand concentration based on the occupancy of the receptor can be enhanced by crowding under certain circumstances. Additionally, we develop a simulation algorithm that speeds the calculation of reaction rates in crowded environments and can be readily applied to other, more complex systems.

biophysics↗

bioRxiv2020

β-arrestin mediates communication between plasma membrane and intracellular GPCRs to regulate signaling

It has become increasingly apparent that G protein-coupled receptor (GPCR) localization is a master regulator of cell signaling. However, the molecular mechanisms involved in this process are not well understood. To date, observations of intracellular GPCR activation can be organized into two categories: a dependence on OCT3 cationic channel-permeable ligands or the necessity of endocytic trafficking. Using CXC chemokine receptor 4 (CXCR4) as a model, we identified a third mechanism of intracellular GPCR signaling. We show that independent of membrane permeable ligands and endocytosis, upon stimulation, plasma membrane and internal pools of CXCR4 are post-translationally modified and collectively regulate EGR1 transcription. We found that {beta}-arrestin-1 (arrestin 2) is necessary to mediate communication between plasma membrane and internal pools of CXCR4. Notably, these observations may explain that while CXCR4 overexpression is highly correlated with cancer metastasis and mortality, plasma membrane localization is not. Together these data support a model were a small initial pool of plasma membrane-localized GPCRs are capable of activating internal receptor-dependent signaling events.

cell biology↗

bioRxiv2020

Tyrosine phosphorylation of ACLY regulates lipid metabolism and oncogenesis in ALK positive Anaplastic Large Cell Lymphoma

A fundamental requirement for growth of rapidly proliferating cells is metabolic adaptation to promote synthesis of biomass1. ATP citrate lyase (ACLY) is a critical enzyme responsible for synthesis of cytosolic acetyl-CoA, the key building component for de novo fatty acid synthesis and links vital pathways such as carbohydrate and lipid metabolism2. The mechanisms of ACLY regulation are not completely understood and the regulation of ACLY function by tyrosine phosphorylation is unknown. Here we show using mass-spectrometry-driven phosphoproteomics and metabolomics that ACLY is phosphorylated and functionally regulated at an evolutionary conserved residue, Y682. Physiologic signals promoting rapid cell growth such as epidermal growth factor stimulation in epithelial cells and T-cell receptor activation in primary human T-cells result in rapid phosphorylation of ACLY at Y682. In vitro kinase assays demonstrate that Y682 is directly phosphorylated by multiple tyrosine kinases, including ALK, ROS1, SRC, JAK2 and LTK. Oncogenically activating structural alterations such as gene-fusions, amplification or point mutations of ALK tyrosine kinase result in constitutive phosphorylation of ACLY in diverse forms of primary human cancer such as lung cancer, anaplastic large cell lymphoma (ALCL) and neuroblastoma. Expression of a phosphorylation-defective ACLY-Y682F mutant in NPM-ALK+ ALCL decreases ACLY activity and attenuates lipid synthesis. Metabolomic analyses reveal that ACLY-Y682F expression results in increased {beta}-oxidation of 13C-oleic acid-labeled fatty acid with increased labeling of +2-citrate (p<0.01) and +18-oleyol carnitine (p<0.001). Similarly, oxygen consumption rate (OCR) is significantly increased in cells expressing ACLY-Y682F (p<0.001). Moreover, expression of ACLY-Y682F dramatically decreases cell proliferation, impairs clonogenicity and abrogates tumor growth in vivo. Our results reveal a novel mechanism for direct ACLY regulation that is subverted by multiple oncogenically-activated tyrosine kinases in diverse human cancers. These findings have significant implications for novel therapies targeting ACLY in cancer and metabolism.

cancer biology↗

bioRxiv2019

Information processing by endoplasmic reticulum stress sensors

The unfolded protein response (UPR) is a collection of cellular feedback mechanisms that seek to maintain protein folding homeostasis in the endoplasmic reticulum (ER). When the ER is \"stressed\", either through high protein folding demand or undersupply of chaperones and foldases, stress sensing proteins in the ER membrane initiate the UPR. Recently, experiments have indicated that these signaling molecules detect stress by being both sequestered by free chaperones and activated by free unfolded proteins. However, it remains unclear what advantage this bidirectional sensor control offers stressed cells. Here, we show that combining positive regulation of sensor activity by unfolded proteins with negative regulation by chaperones allows the sensor to make a more informative measurement of ER stress. The increase in the information capacity of the combined sensing mechanism stems from stretching of the active range of the sensor, at the cost of increased uncertainty due to the integration of multiple signals. These results provide a possible rationale for the evolution of the observed stress sensing mechanism.

systems biology↗

bioRxiv2018

How to design an optimal sensor network for the unfolded protein response

Cellular protein homeostasis requires continuous monitoring of stress in the endoplasmic reticulum (ER). Stress detection networks control protein homeostasis by mitigating the deleterious effects of protein accumulation, such as aggregation and misfolding, with precise modulation of chaperone production. Here, we develop a coarse model of the unfolded protein response in yeast, and use multi-objective optimization to determine which sensing and activation strategies optimally balance the trade-off between unfolded protein accumulation and chaperone production. By comparing a stress-sensing mechanism that responds directly to the level of unfolded protein in the ER to a mechanism that is negatively regulated by unbound chaperones, we show that chaperone-mediated sensors are more efficient than sensors that detect unfolded proteins directly. This results from the chaperone-mediated sensor having separate thresholds for activation and deactivation. Lastly, we demonstrate that a sensor responsive to both unfolded protein and unbound chaperone does not further optimize homeostatic control. Our results suggest a strategy for designing stress sensors and may explain why BiP-mitigated ER stress sensing networks have evolved.

systems biology↗

bioRxiv2018

Dynamic recruitment of single RNAs to processing bodies depends on RNA functionality

Cellular RNAs often colocalize with cytoplasmic, membrane-less ribonucleoprotein (RNP) granules enriched for RNA processing enzymes, termed processing bodies (PBs). Here, we track the dynamic localization of individual miRNAs, mRNAs and long non-coding RNAs (lncRNAs) to PBs using intracellular single-molecule fluorescence microscopy. We find that unused miRNAs stably bind to PBs, whereas functional miRNAs, repressed mRNAs and lncRNAs both transiently and stably localize within either the core or periphery of PBs, albeit to different extents. Consequently, translation potential and positioning of cis-regulatory elements significantly impact PB-localization dynamics of mRNAs. Using computational modeling and supporting experimental approaches we show that phase separation into large PBs attenuates mRNA silencing, suggesting that physiological mRNA turnover predominantly occurs outside of PBs. Instead, our data support a role for PBs in sequestering unused miRNAs to regulate their surveillance and provides a framework for investigating the dynamic assembly of RNP granules by phase separation at single-molecule resolution.

molecular biology↗

bioRxiv2017

Inferring intracellular signal transduction circuitry from molecular perturbation experiments

The development of network inference methodologies that accurately predict connectivity in dysregulated pathways may enable the rational selection of patient therapies. Accurately inferring an intracellular network from data remains a very challenging problem in molecular systems biology. Living cells integrate extremely robust circuits that exhibit significant heterogeneity, but still respond to external stimuli in predictable ways. This phenomenon allows us to introduce a network inference methodology that integrates measurements of protein activation from perturbation experiments. The methodology relies on logic-based networks to provide a predictive approximation of the transfer of signals in a network. The approach presented was validated in silico with a set of test networks and applied to investigate the epidermal growth factor receptor signaling of a breast epithelial cell line, MFC10A. In our analysis, we predict the potential signaling circuitry most likely responsible for the experimental readouts of several proteins in the mitogen activated protein kinase and phosphatidylinositol-3 kinase pathways. The approach can also be used to identify additional necessary perturbation experiments to distinguish between a set of possible candidate networks.

systems biology↗