Biology subjects

Tsygankov, D.

Publications and source records attributed to Tsygankov, D..

8 recordsLinked to original sources

bioRxiv2026

Dynein-microtubule forces drive nucleokinesis and transmigration in T cells

Beyond the mechanical capacity of canonical actomyosin-driven amoeboid motility in permissive extracellular environments, the nucleus becomes the principal barrier to T cell migration in confining tissues. We establish the dynein-microtubule (MT) force-transmission axis as an essential mechanism for nuclear translocation during confined T cell migration and transmigration. We argue that dynein acts both as a motor and as an F-actin-anchored force-transmission element (fulcrum), sliding MTs and the MT-coupled nucleus along the cell cortex to drive nucleokinesis and productive cell displacement. Dynein is the primary driver of nucleokinesis: its inhibition arrests nucleus movement independently of myosin II activity, while F-actin dynamics remain spatiotemporally decoupled from nuclear oscillations. During transmigration, dynein and actomyosin act cooperatively and non-redundantly, and only combined inhibition abolishes nuclear passage. Computational modeling demonstrates that dynein-mediated pulling, together with volume exclusion imposed by the nucleus, is sufficient to generate self-organized nuclear oscillations. Dynein inhibition in zebrafish Langerhans cells impairs protrusion dynamics in situ, identifying the dynein-MT axis as an evolutionarily conserved mechanobiological program. Collectively, these findings identify the dynein-MT mechanical unit as a potential target for engineering T cells with enhanced solid-tumor infiltration.

cell biology↗

bioRxiv2026

A membrane-permeable small molecule biosensor accesses intractable cells and animals without genetic manipulation

Fluorescent biosensors have proven valuable for revealing the spatio-temporal dynamics of protein conformation in live cells and animals. The great majority of biosensors are genetically encoded, but genetic encoding is difficult or impossible to apply in many cases, including cells or animals with poorly understood genomes, no DNA, or sensitive to manipulation. Using biosensors without genetic manipulation could greatly simplify studies in animals, expand the range of accessible organisms, and ultimately enable application in humans. Here we explore using a membrane-permeable small molecule as a fluorescent biosensor. The drug trifluoperazine, which binds only to the active conformation of calmodulin, was covalently linked to an environment-sensing merocyanine dye to create CaMero, a biosensor of calmodulin activation. Simple incubation of CaMero in the extracellular medium, or injection in the tail vein of mice, led to sensitive real time reporting of calmodulin activity. The dye underwent a 12-fold change in fluorescence intensity upon binding to activated calmodulin, revealing waves of activation in peristaltic intestine, localization and kinetics of calmodulin activation during serum stimulation in fibroblasts, and localized activation in the single-celled marine protist foraminifera.

cell biology↗

bioRxiv2025

Immune Cell Migration Models Synergize Nuclear Piston, Uropod, and Microenvironment into Hydraulic Cell Engine

The nucleus and uropod are the largest and most mechanically distinct structures in migrating amoeboid lymphocytes, including NK, B, and T cells. The biophysical properties of these structures may shape the ability of immune cells to navigate dense tissue microenvironments during immune surveillance. Using bead-spring and agent-based cell models, we explore the biomechanical contributions of the nucleus, uropod, septin-templated cortical rings, actomyosin cytoskeleton, and extracellular matrix obstacles to lymphocyte migration. Our results support a migration model in which, following cell-matrix collisions, septins mediate the formation of cortical rings that hydraulically seal cytoplasmic compartments on each side of the passing nucleus, generating a pressure difference that propels the nucleus forward. This hydraulically driven nuclear piston actively enhances migration through confined spaces. Concurrently, the uropod emerging from the peristaltic collapse of rear compartments stabilizes directional persistence and prevents T cell repolarization. We show that such polarity stabilization boosts immune surveillance efficiency. Together, these models redefine the nucleus as an active component of the migratory engine and the uropod as a locomotion stabilizer. Furthermore, the models offer a predictive framework towards engineering of immune cell motility in complex tissue microenvironments with broad implications for cancer immunotherapy, aging, and regenerative medicine.

biophysics↗

bioRxiv2023

Septins Enable T Cell Contact Guidance via Amoeboid-Mesenchymal Switch

Lymphocytes exit circulation and enter in-tissue guided migration toward sites of tissue pathologies, damage, infection, or inflammation. By continuously sensing and adapting to the guiding chemo-mechano-structural properties of the tissues, lymphocytes dynamically alternate and combine their amoeboid (non-adhesive) and mesenchymal (adhesive) migration modes. However, which mechanisms guide and balance different migration modes are largely unclear. Here we report that suppression of septins GTPase activity induces an abrupt amoeboid-to-mesenchymal transition of T cell migration mode, characterized by a distinct, highly deformable integrin-dependent immune cell contact guidance. Surprisingly, the T cell actomyosin cortex contractility becomes diminished, dispensable and antagonistic to mesenchymal-like migration mode. Instead, mesenchymal-like T cells rely on microtubule stabilization and their non-canonical dynein motor activity for high fidelity contact guidance. Our results establish septins GTPase activity as an important on/off switch for integrin-dependent migration of T lymphocytes, enabling their dynein-driven fluid-like mesenchymal propulsion along the complex adhesion cues. SIGNIFICANCE STATEMENTDeciphering mechanisms of guided lymphocyte migration paves the way towards effective immunotherapies for the extracellular matrix-rich tissues, such as solid tumors. Here we demonstrate that T cell septins GTPase activity regulates both actomyosin and microtubules, alternately enhancing either of these two major motor systems. Surprisingly, the suppression of septin GTPase activity also induces a highly guided integrin-dependent mesenchymal-like migration directed by the extracellular matrix proteins. The phenomenon of guided mesenchymal-like migration of T cells relies on the microtubules and microtubule-based dynein motors that are responsible for the force generation, powering guided T cell motility. This finding opens a new perspective for future studies of septin GTPases in a context of the optimisation of T cell-based immunotherapies for the solid tissues.

cell biology↗

bioRxiv2023

Dynein-Powered Cell Locomotion Guides Metastasis of Breast Cancer

Metastasis is a principal cause of death in cancer patients, which remains an unresolved fundamental and clinical problem. Conventionally, metastatic dissemination is linked to the actomyosin-driven cell locomotion. However, locomotion of cancer cells often does not strictly line up with the measured actomyosin forces. Here, we identify a complementary mechanism of metastatic locomotion powered by the dynein-generated forces. These forces that arise within a non-stretchable microtubule network drive persistent contact guidance of migrating cancer cells along the biomimetic collagen fibers. We also show that dynein-powered locomotion becomes indispensable during invasive 3D migration within a tissue-like luminal network between spatially confining hydrogel microspheres. Our results indicate that the complementary contractile system of dynein motors and microtubules is always necessary and in certain instances completely sufficient for dissemination of metastatic breast cancer cells. These findings advance fundamental understanding of cell locomotion mechanisms and expand the spectrum of clinical targets against metastasis.

cell biology↗

bioRxiv2022

Coordinated Regulation of Cdc42ep1, Actin, and Septin Filaments during Neural Crest Cell Migration

The septin cytoskeleton has been demonstrated to interact with other cytoskeletal components to regulate various cellular processes, including cell migration. However, the mechanisms of how septin regulates cell migration are not fully understood. In this study, we use the highly migratory neural crest cells of frog embryos to examine the role of septin filaments in cell migration. We found that septin filaments are required for proper migration of neural crest cells by controlling both the speed and the direction of cell migration. We further determined that septin filaments regulate these features of cell migration by interacting with actin stress fibers. In neural crest cells, septin filaments co-align with actin stress fibers, and the loss of septin filaments leads to impaired stability and contractility of actin stress fibers. In addition, we showed that a partial loss of septin filaments leads to drastic changes in the orientations of newly formed actin stress fibers, suggesting that septin filaments help maintain the persistent orientation of actin stress fibers during directed cell migration. Lastly, our study revealed that these activities of septin filaments depend on Cdc42ep1, which co-localizes with septin filaments in the center of neural crest cells. Cdc42ep1 interacts with septin filaments in a reciprocal manner, with septin filaments recruiting Cdc42ep1 to the cell center and Cdc42ep1 supporting the formation of septin filaments.

cell biology↗

bioRxiv2021

Correcting artifacts in ratiometric biosensor imaging; an improved approach for dividing noisy signals

The accuracy of biosensor ratio imaging is limited by signal/noise. Signals can be weak when biosensor concentrations must be limited to avoid cell perturbation. This can be especially problematic in imaging of low volume regions, e.g., along the cell edge. The cell edge is an important imaging target in studies of cell motility. We show how the division of fluorescence intensities with low signal-to-noise at the cell edge creates specific artifacts due to background subtraction and division by small numbers, and that simply improving the accuracy of background subtraction cannot address these issues. We propose a new approach where, rather than simply subtracting background from the numerator and denominator, we subtract a noise correction factor (NCF) from the numerator only. This NCF can be derived from the analysis of noise distribution in the background near the cell edge or from ratio measurements in the cell regions where signal-to-noise is high. We test the performance of the method first by examining two noninteracting fluorophores distributed evenly in cells. This generated a uniform ratio that could provide a ground truth. We then analyzed actual protein activities reported by a single chain biosensor for the guanine exchange factor Asef, and a dual chain biosensor for the GTPase Cdc42. The reduction of edge artifacts revealed persistent Asef activity in a narrow band ([~]640 nm wide) immediately adjacent to the cell edge. For Cdc42, the NCF method revealed an artefact that would have been obscured by traditional background subtraction approaches.

cell biology↗

bioRxiv2020

Shape-to-graph Mapping Method for Efficient Characterization and Classification of Complex Geometries in Biological Images

With the ever-increasing quality and quantity of imaging data in biomedical research comes the demand for computational methodologies that enable efficient and reliable automated extraction of the quantitative information contained within these images. One of the challenges in providing such methodology is the need for tailoring algorithms to the specifics of the data, limiting their areas of application. Here we present a broadly applicable approach to quantification and classification of complex shapes and patterns in biological or other multi-component formations. This approach integrates the mapping of all shape boundaries within an image onto a global information-rich graph and machine learning on the multidimensional measures of the graph. We demonstrated the power of this method by (1) extracting subtle structural differences from visually indistinguishable images in our phenotype rescue experiments using the endothelial tube formations assay, (2) training the algorithm to identify biophysical parameters underlying the formation of different multicellular networks in our simulation model of collective cell behavior, and (3) analyzing the response of U2OS cell cultures to a broad array of small molecule perturbations. Author SummaryIn this paper, we present a methodology that is based on mapping an arbitrary set of outlines onto a complete, strictly defined structure, in which every point representing the shape becomes a terminal point of a global graph. Because this mapping preserves the whole complexity of the shape, it allows for extracting the full scope of geometric features of any scale. Importantly, an extensive set of graph-based metrics in each image makes integration with machine learning routines highly efficient even for a small data sets and provide an opportunity to backtrack the subtle morphological features responsible for the automated distinction into image classes. The resulting tool provides efficient, versatile, and robust quantification of complex shapes and patterns in experimental images.

bioinformatics↗