Biology subjects

Vorobyev, A.

Publications and source records attributed to Vorobyev, A..

5 recordsLinked to original sources

bioRxiv2025

CDK7, CDK9, or CDK11 Inhibition Reduces Neutrophil-Driven Inflammation and Tissue Damage in Experimental Autoimmune Models

BackgroundCyclin-dependent kinases (CDKs) are involved in basic cellular processes like regulation of cell-cycle progression and transcription. However, recent data also indicate a specific role in terminally differentiated neutrophils by promoting reactive oxygen species (ROS) release, degranulation, neutrophil extracellular trap formation, or apoptosis. Since these mechanisms are implicated in multiple autoimmune diseases, we aimed to delineate the role of CDKs in IC-mediated autoimmune diseases both in vitro and in vivo. MethodsWe analyzed CDK gene expression in unstimulated and immune complex (IC)-stimulated neutrophils. Subsequently, we investigated the effect of pharmacological CDK inhibition on IC-activated neutrophil functions. To analyze the inhibitors in a more translational approach, we proceeded with the systemic and topical application of the effective inhibitors in a murine antibody transfer-induced local epidermolysis bullosa acquisita (EBA) model. The most efficient inhibitor, MC180295, was validated in two other IC-mediated models of autoimmune disease: Serum-transfer arthritis (STA), which also, but not exclusively, depends on neutrophils and immune thrombocytopenia (ITP), which is considered less neutrophil-dependent. ResultsWe found 14 CDKs expressed in unstimulated cells, while the IC-stimulation showed an upregulation of CDK2 and CDK4 expression. Inhibitors selectively targeting CDK1, CDK2, CDK4/6, CDK7, CDK9, CDK11, and CDK12 showed effects on different neutrophil functions (surface activation marker expression, ROS release, adhesion, apoptosis) in vitro. In the predominantly neutrophil-driven EBA model, we observed a reduction of disease severity upon treatment with CDK7, CDK9, or CDK11 inhibitors. Inhibiting these CDKs with topical THZ2, MC180295, or OTS964, respectively, also improved the clinical phenotype. In line with our hypothesis, MC180295 impaired the development of STA, but not ITP. ConclusionsCDK7, CDK11, and especially CDK9 inhibition show therapeutic potential in IC-driven neutrophil-mediated diseases such as rheumatoid arthritis and EBA.

immunology↗

bioRxiv2025

Mapping the nervous system of the Idiosepius hallami pygmy squid: insights from whole-animal X-ray nanotomography imaging.

The study of a nervous system as big as the cephalopods requires multimodal imaging approaches capable of capturing neural architecture across scales. Here, we present a whole-animal volume of the pygmy squid hatchling Idiosepius hallami, acquired using X-ray holographic nanotomography at the beamline ID16A of the European Synchrotron. The reconstructed 3D volume comprises 40 tiled scans acquired at a voxel size of 125 nm. While individual neurons are not resolved at this resolution, we segmented major body regions and mapped the large-scale connectivity by tracing afferent and efferent nerve bundles, including projections from the olfactory organs, chromatophore lobes, and arm ganglia to the brain. The acquisition of this dataset represents a significant milestone for X-ray nanotomography, being the largest whole animal volume imaged at this spatial resolution. The volume serves as a resource for comparative neuroscience and cephalopod biology.

neuroscience↗

bioRxiv2025

Critical point drying of brain tissue for X-ray phase contrast imaging

X-ray phase contrast tomography is emerging as a powerful method for imaging large volumes of brain tissue at sub-cellular resolution. However, current sample preparation methods are largely inherited from visible light or electron microscopy workflows and hence are not optimised to exploit the full potential of X-ray contrast mechanisms. Here we propose to replace interstitial material by air to enhance X-ray phase contrast of the ultrastructural features. We used critical point drying (CPD) of heavy metal-stained mouse brain tissue to produce mechanically stable samples with preserved ultrastructure and enhanced refractive index boundaries, a nanofoam-like material that remains compatible with follow-up conventional resin embedding. Using two complementary synchrotron-based setups, a high-throughput microtomography beamline (P14, DESY) and a nanoscale holographic tomography beamline (ID16A, ESRF), we found that CPD samples consistently showed 2-4x stronger phase-shift signal than conventional resin-embedded tissue. The contrast gain remained consistent across samples, imaging conditions, and beamlines. Our results suggest that CPD offers a versatile route for preparing tissue for subcellular and ultrastructural-resolution X-ray imaging. It retains structural detail while improving signal, and is compatible with other processing procedures like femtosecond laser milling or electron microscopy, paving the path for biological tissue imaging beyond the mm3 scale.

neuroscience↗

bioRxiv2023

Functional networks of inhibitory neurons orchestrate synchrony in the hippocampus

Inhibitory interneurons are pivotal components of cortical circuits. Beyond providing inhibition, they have been proposed to coordinate the firing of excitatory neurons within cell assemblies. While the roles of specific interneuron subtypes have been extensively studied, their influence on pyramidal cell synchrony in vivo remains elusive. Employing an all-optical approach, we simultaneously recorded hippocampal interneurons and pyramidal cells and probed the network influence of individual interneurons using optogenetics. We demonstrate that CA1 interneurons form a functionally interconnected network that promotes synchrony through disinhibition during awake immobility, while preserving endogenous cell assemblies. Our network model underscores the importance of both cell assemblies and dense, unspecific interneuron connectivity in explaining our experimental findings, suggesting that interneurons may operate not only via division of labor but also through concerted activity.

neuroscience↗

bioRxiv2021

Transparent exploration of machine learning for biomarker discovery from proteomics and omics data

Biomarkers are of central importance for assessing the health state and to guide medical interventions and their efficacy, but they are lacking for most diseases. Mass spectrometry (MS)-based proteomics is a powerful technology for biomarker discovery, but requires sophisticated bioinformatics to identify robust patterns. Machine learning (ML) has become indispensable for this purpose, however, it is sometimes applied in an opaque manner, generally requires expert knowledge and complex and expensive software. To enable easy access to ML for biomarker discovery without any programming or bioinformatic skills, we developed OmicLearn (https://OmicLearn.com), an open-source web-based ML tool using the latest advances in the Python ML ecosystem. We host a web server for the exploration of the researchers results that can readily be cloned for internal use. Output tables from proteomics experiments are easily uploaded to the central or a local webserver. OmicLearn enables rapid exploration of the suitability of various ML algorithms for the experimental datasets. It fosters open science via transparent assessment of state-of-the-art algorithms in a standardized format for proteomics and other omics sciences. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/434053v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@7b95corg.highwire.dtl.DTLVardef@11a5357org.highwire.dtl.DTLVardef@15586c2org.highwire.dtl.DTLVardef@2357f_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIOmicLearn is an open-source platform allows researchers to apply machine learning (ML) for biomarker discovery C_LIO_LIThe ready-to-use structure of OmicLearn enables accessing state-of-the-art ML algorithms without requiring any prior bioinformatics knowledge C_LIO_LIOmicLearns web-based interface provides an easy-to-follow platform for classification and gaining insights into the dataset C_LIO_LISeveral algorithms and methods for preprocessing, feature selection, classification and cross-validation of omics datasets are integrated C_LIO_LIAll results, settings and method text can be exported in publication-ready formats C_LI

biochemistry↗