Biology subjects

Odde, D. J.

Publications and source records attributed to Odde, D. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Genetically inducible coordinators of cytokine signaling pathways for interrogating T cell motility

Chimeric antigen receptor (CAR) T cell therapy is promising for treating hematologic malignancies, but extending this success to treat solid tumors is challenging. Improving T cell phenotype to address this need is desirable, and one such property is increasing T cell infiltration into tumors. A promising potential approach comprises rewiring cytokine signaling using engineered receptors to change how the T cell responds to environmental cues. However, we currently lack the tools and mechanistic understanding to iterate and improve upon such strategies. Notably, receptors that rewire signaling make it challenging to decouple paracrine effects from those conferred by the signaling inducer. To address this gap, we developed a genetically inducible toolkit of proteins termed Constitutive Activators of Motility-associated Pathways (CAMPs). Building on prior knowledge, CAMPs incorporate domains from IL5R (interleukin-5 receptor) and TNFR (tumor necrosis factor receptor) to place cytokine-associated signaling under direct genetic control, such that expression of a CAMP using a small molecule cue or a condition-responsive promoter induces CAMP signaling. We first identified receptor configurations driving constitutive signaling through targeted pathways. TNFR-based signaling modules drove NF-{kappa}B activation across diverse receptor designs, while IL5R-based signaling modules exhibited stringent requirements for membrane-proximity and organization of subunits. We engineered primary human T cells with inducible CAMP circuits, enabling us to probe pathway-specific effects on motility and transcriptomic responses. Pharmacological induction of motility-associated programs downstream of PKC (protein kinase C) was shown to be feasible and dependent on T cell activation state. CAMP induction drove an inflammatory program, particularly when signaling through both NF-{kappa}B and STAT5, but none of the conditions tested enhanced 3D motility in our assay. Altogether, our findings are consistent with a model in which migratory behavior may be coupled and regulated by multiple stimuli. These findings and new CAMP tools provide a foundation for interrogating and ultimately harnessing motility for improved T cell therapy performance.

synthetic biology↗

bioRxiv2026

Ex vivo glioblastoma migration phenotypes define clinical recurrence and tumor heterogeneity

Glioblastoma's pronounced migratory capacity underlies its diffuse invasion, presenting a formidable barrier to successful treatment. Ex vivo characterization of glioblastoma cells isolated from freshly resected clinical samples under physiologically relevant conditions revealed two distinct migratory phenotypes, Fast Migrating (FM) and Slow Migrating (SM). These phenotypes reflect distinct mechanosensitivity profiles and are associated with pharmacological responses that support the motor clutch model of cell migration. Analysis of genes associated with these phenotypes revealed a transcriptomic signature that closely associated with in vitro cell migration, histological invasion in patient specimens, and clinical survival. Single-nucleus RNA sequencing revealed that FM and SM cells coexist within a single glioblastoma, with FM cells enriched at the periphery and SM cells localized to the tumor core. Collectively, our study demonstrates the utility of ex vivo glioblastoma characterization, allowing decoding of tumor heterogeneity and clinical prognostication as well as providing a framework for deconvoluting the complex cancer phenotype.

cancer biology↗

bioRxiv2026

Physiomimetic culture bias durotaxis toward soft environments

Directed cell migration underlies many biological phenomena, from embryonic development to tumor metastasis and organ fibrosis. Most cells typically migrate toward stiffer regions of their extracellular matrix -a behavior known as positive durotaxis. Here we show that culture on rigid plastic reinforces this response, whereas preconditioning in soft 3D physiomimetic environments reprograms migration towards softer environments, a phenomenon known as negative durotaxis. Fetal rat lung fibroblasts preconditioned in 3D physiomimetic hydrogels exhibited negative durotaxis and accumulated near [~]5 kPa, corresponding to the physiological stiffness of the lung. In contrast, genetically identical cells maintained on conventional 2D plastic substrates migrated up stiffness gradients, toward stiffer regions. Although both populations displayed a biphasic force-stiffness relationship, they differed in force magnitude and cytoskeletal organization. Molecular-clutch modeling revealed that durotaxis reversal emerges from two distinct mechanical regimes: a mechanosensitive, high-motor-clutch state that stabilizes adhesions on stiff substrates and drives positive durotaxis, and a low-motor, weak-adhesion state in which clutch slippage on the stiff side causes negative durotaxis. Our results show that durotaxis direction is not an intrinsic cellular property. Rather, it emerges from the interplay between motor activity and adhesion dynamics and can be tuned by culture conditions.

biophysics↗

bioRxiv2026

Engineering physically optimized T cells for increased sampling of complex tumor microenvironments

Pancreatic ductal adenocarcinoma (PDA) remains highly lethal, in part, because its dense fibroinflammatory stroma restricts therapy distribution, including adoptive T cell immunotherapies where direct interactions between T and carcinoma cells are essential for effective therapy. While T cell function must be maintained once effector-target engagement occurs, without inducing co-localization subsequent cytotoxic function steps cannot be undertaken. We therefore developed a strategy to "physically optimize" T cells to more effectively sample complex tumor volumes. Informed by pharmacologic perturbations and mathematical modeling we shifted T cell phenotype through expression of constitutively activated RhoA to increase cortical contractility, activation, migration, and sampling in PDA, while showing decreases in exhaustion markers. In CAR T cells this results in more efficient targeting through decreased sampling time and increased engagement with carcinoma cells, consistent with modeling predictions. This significantly increases T cell infiltration and distribution in PDA, resulting in improved tumor control in vivo, suggesting that this is an effective strategy to overcome stromal constraints, improve tumor engagement, and enhance the therapeutic performance of engineered T cell therapies in solid tumors.

bioengineering↗

bioRxiv2025

Mathematical model of CISH knockout predicts increased efficacy in tumor-infiltrating lymphocyte activation with synergistic gene editing

Tumor-infiltrating lymphocyte (TIL) therapy is a type of adoptive cell therapy, where the lymphocytes of a cancer patients tumor are harvested, expanded in vitro using IL-2 stimulation, and then infused back into the patient[1], [2]. However, even with the use of TIL therapy, cancer cells can survive for various reasons, such as poor lymphocyte infiltration into tumors, chronic activation of the T cell receptor and the immunosuppressive tumor microenvironment[3]. Cytokine-inducible SH2-containing (CISH) protein is a negative regulator of T cell activation, and in a recent clinical trial was knocked out in TILs to improve TIL therapy efficacy[4]. A mechanistic signaling pathway model was developed to theoretically evaluate the efficacy of CISH knockout (CISH KO) in T cell activation and examine potential alternative target genes that can theoretically be targeted using multiplex gene-editing or drugs to further improve T cell activation and function[5]. Based on the results, CISH knockout increases the transcription of activation biomarkers IL-2 and TNF-, but also inhibitory biomarkers such as PD1 and FasL. Using global sensitivity analysis, we also found that GSK3B, which is responsible for the deactivation of NFAT, is also predicted to further increase T cell activation when knocked out. In addition, it was predicted that PDCD1, FAS and CTLA4 can be knocked out in combination with CISH to further enhance T cell activation and prevent exhaustion and apoptosis.

immunology↗

bioRxiv2025

UNC-45A Drives ATP-Independent Microtubule Destabilization via Defect Recognition and Repair Inhibition Contributing to Neurite Dystrophy

UNC-45A is the only known ATP-independent microtubule severing protein. Using in vitro reconstitution and TIRF microscopy, we show that, unlike canonical severing enzymes such as katanin, spastin, and fidgetin, which hydrolyze ATP to remove tubulin dimers and promote lattice repair, UNC-45A selectively binds to pre-existing microtubule defects and inhibits GTP-tubulin incorporation. This mechanism prevents the formation of stabilized hot spots that typically protect microtubules from disassembly, resulting in persistent lattice damage and net microtubule loss, even in the presence of physiological levels of free GTP-tubulin. We further demonstrate that UNC-45A localizes near amyloid deposits in both mouse models and human cases of Alzheimers disease (AD). In cultured neurons, UNC-45A accumulates in axonal swellings--regions of pronounced microtubule disruption and experimental surrogates for dystrophic neurites in AD--and exacerbates their size and number, particularly under conditions mimicking microtubule damage. Notably, this is the first report of a microtubule severing protein that both localizes near amyloid plaques in tissue and accumulates in neurite swellings in cultured neurons, where it modulates their pathology. Together, our findings establish the mechanism of ATP-independent, damage-responsive severing pathway that couple defects recognition to repair inhibition, defining a new paradigm in microtubule quality control with broad implications for cytoskeletal integrity and remodeling in health and disease.

cell biology↗

bioRxiv2025

A systematic approach to analyze T cell migration: application to mouse melanoma tumors

T cells must assess and choose between surveilling large areas, but also engage efficiently with the target cells. This process is translated into variations in speed and turning angle of T cells. In this study, we propose a generalized algorithm to analyze cell migration data with focus on CD8+ T cells, using clustering technique to identify the number of different migration states and Hidden Markov Model to capture the dynamical switching between them. The algorithm only requires a set of position observations in a series of times, independent of other factors. While this study focuses on CD8+ T cell migration, this approach can potentially be used broadly to study the migration of other cell types as well. For the current analysis, low and high avidity T cells in melanoma tumors were tracked ex vivo using two-photon microscopy. Our findings suggest that CD8+ T cells follow a two-state migration dynamic, with one state being faster, while the other slower and more localized. Moreover, we established a statistical methodology to analyze T cell migration to assess whether there is true variability in cell speeds as distinguished from stochastic fluctuations about a single speed, and it can be applied across different experimental platforms.

immunology↗

bioRxiv2025

Allocation of resources among multiple daughter cells

Cell division commonly produces two daughter cells, but there are many exceptions where large cells produce multiple daughters. Multiple fission of some green algae and bacteria, cellularization during embryogenesis of plants and insects, and growth of Ichthyosporeans, Chytrids, and Apicomplexans all provide variations on this theme. In some yeast species, a large multi-nucleate mother cell grows multiple buds (daughters) simultaneously. Here we address how mothers partition growth equally among their buds in the multi-budding yeast Aureobasidium pullulans. Bud growth is directed by actin cable networks that appear to be optimized for even partitioning despite complex cell geometries. Even partitioning does not rely on compensatory mechanisms to adjust bud volumes, but rather stems directly from effective equalization of polarity sites. These results reveal how conserved cell polarity and cytoskeletal networks are adapted to build complex morphologies in fungi.

cell biology↗

bioRxiv2023

Biophysical modeling identifies an optimal hybrid amoeboid-mesenchymal phenotype for maximal T cell migration speeds

Despite recent advances in understanding cell migration mechanics, the principles governing rapid T cell movement remain unclear. Efficient migration is critical for antitumoral T cells to locate and eliminate cancer cells. To investigate the upper limits of cell speed, we developed a hybrid stochastic-mean field model of bleb-based cell motility. Our model suggests that cell-matrix adhesion-free bleb-based migration is highly inefficient, challenging the feasibility of cell swimming/adhesion-independent migration as a primary fast motility mode. Instead, we show that T cells can achieve rapid migration by combining bleb formation with adhesion-based forces. Supporting our predictions, our three-dimensional gel experiments confirm that T cells migrate significantly faster under adherent conditions than in adhesion-free environments. These findings highlight the mechanical constraints of T cell motility and suggest that modifying tissue adhesion properties in a controlled manner could enhance immune cell infiltration into tumors. Our computational and experimental work provides insights for optimizing T cell-based immunotherapies. While antifibrotic treatments could alter the tumor microenvironment, indiscriminate reduction of adhesion may not be ideal for T cell infiltration and motility, highlighting the need for targeted antifibrotic strategies.

biophysics↗

bioRxiv2023

Glioblastoma cells use an integrin- and CD44-mediated motor-clutch mode of migration in brain tissue

Glioblastoma (GBM) is an aggressive malignant brain tumor with 2-year survival rates of 6.7% [1], [2]. One key characteristic of the disease is the ability of glioblastoma cells to migrate rapidly and spread throughout healthy brain tissue[3], [4]. To develop treatments that effectively target cell migration, it is important to understand the fundamental mechanism driving cell migration in brain tissue. Here we utilized confocal imaging to measure traction dynamics and migration speeds of glioblastoma cells in mouse organotypic brain slices to identify the mode of cell migration. Through imaging cell-vasculature interactions and utilizing drugs, antibodies, and genetic modifications to target motors and clutches, we find that glioblastoma cell migration is most consistent with a motor-clutch mechanism to migrate through brain tissue ex vivo, and that both integrins and CD44, as well as myosin motors, play an important role in constituting the adhesive clutch.

cancer biology↗

bioRxiv2023

Cell migration simulator-based biomarkers for glioblastoma

Glioblastoma is the most aggressive malignant brain tumor with poor survival due to its invasive nature driven by cell migration, with unclear linkage to transcriptomic information. Here, we applied a physics-based motor-clutch model, a cell migration simulator (CMS), to parameterize the migration of glioblastoma cells and define physical biomarkers on a patient-by-patient basis. We reduced the 11-dimensional parameter space of the CMS into 3D to identify three principal physical parameters that govern cell migration: motor number - describing myosin II activity, clutch number - describing adhesion level, and F-actin polymerization rate. Experimentally, we found that glioblastoma patient-derived (xenograft) (PD(X)) cell lines across mesenchymal (MES), proneural (PN), classical (CL) subtypes and two institutions (N=13 patients) had optimal motility and traction force on stiffnesses around 9.3kPa, with otherwise heterogeneous and uncorrelated motility, traction, and F-actin flow. By contrast, with the CMS parameterization, we found glioblastoma cells consistently had balanced motor/clutch ratios to enable effective migration, and that MES cells had higher actin polymerization rates resulting in higher motility. The CMS also predicted differential sensitivity to cytoskeletal drugs between patients. Finally, we identified 11 genes that correlated with the physical parameters, suggesting that transcriptomic data alone could potentially predict the mechanics and speed of glioblastoma cell migration. Overall, we describe a general physics-based framework for parameterizing individual glioblastoma patients and connecting to clinical transcriptomic data, that can potentially be used to develop patient-specific anti-migratory therapeutic strategies generally. Significance StatementSuccessful precision medicine requires biomarkers to define patient states and identify personalized treatments. While biomarkers are generally based on expression levels of protein and/or RNA, we ultimately seek to alter fundamental cell behaviors such as cell migration, which drives tumor invasion and metastasis. Our study defines a new approach for using biophysics-based models to define mechanical biomarkers that can be used to identify patient-specific anti-migratory therapeutic strategies.

bioengineering↗

bioRxiv2023

Optimality of motor and clutch mechanical properties in a generalized model for cell traction forces

The mechanical properties of the extracellular environment influence cell behavior, such as cell morphogenesis, cell migration and cell fate. During the cell migration cycle, cells extend plasma membrane protrusions via actin polymerization, actin filaments move retrogradely via myosin motors and actin polymerization, and the formation of adhesion complexes commonly called clutches mediate the production of traction forces on the extracellular microenvironment allowing the cell to move forward. In this study, we revisited the motor-clutch model for cell migration and derived its mean-field counterpart to study force production of cellular protrusions on compliant substrates. We derived an analytical expression for the optimum substrate stiffness that maximizes force transmission, without unknown adjustable parameters that is valid for all motor-clutch ratio regimes; and determined the required conditions for the protrusion to operate in the clutch-dominated "stalled" regime, the motor-clutch "balanced" regime and motor-dominated "free flowing" regime. We explored these regimes theoretically and obtained an analytical expression for the traction force produced in the limits of low and high myosin activity. We discovered the existence of an optimum clutch stiffness for maximal cellular traction force and identified a biphasic dependence of traction force produced by protrusions on rigid substrates on motor activity and unloaded myosin motor velocity, results that could be tested via novel molecular tension sensor experiments. We additionally showed that clutch reinforcement shifts the optimum substrate and clutch stiffnesses to larger values whereas the optimum substrate stiffness is found to be insensitive to changes in clutch catch bond properties. Overall, our work reveals that altering cell adhesion levels, actomyosin activity and rigidity of clutches and extracellular matrix can cause nontrivial traction force changes and modulated cell migration capabilities that provide insights to effectively design novel cell and stromal-based therapies to treat development and human diseases, such as cancer invasion and metastasis. STATEMENT OF SIGNIFICANCEAdherent cells produce mechanical forces on their environment that critically regulate cell adhesion, signaling and function, essential during developmental events and human disease. Despite recent progress, cell-generated force measurements across a wide range of extracellular stiffnesses and cell states have faced numerous technical challenges. Our mean-field study provides a new generalized analysis of regulation of force transmission by modulation of cellular components and extracellular rigidity. We identify the existence of an intermediate stiffness of cell adhesion complexes for maximum force transmission and find that effective force transmission on rigid environments reduces to a competition between cell adhesion reinforcement and load-dependent dissociation kinetics. The developed model provides important insights to aid design of novel therapeutic strategies for cancers and other diseases.

biophysics↗

bioRxiv2022

RAD-TGTs: Measurement of cellular tensions via flow cytometry and DNA sequencing enabled by force-dependent rupture and delivery of DNA tension probes

Mechanical force is a key driver of cellular processes and is dysregulated in many diseases. Measuring cellular tensions to elucidate mechanotransduction pathways typically involves high-resolution but low throughput imaging of surfaces and arduous experimental preparation of materials. We present here Rupture and Deliver DNA-duplex based molecular tension sensors-RAD-TGTs. RAD-TGTs consist of immobilized DNA duplexes conjugated to a ligand and indicator (fluorophore, barcode etc) which rupture in a force-dependent manner when cells are bound. Readout of rupture is performed in cells of interest using high throughput methods such as flow cytometry and leveraging covalent DNA-protein linking HUH-tags simplifies the preparation of the tension sensor to allow use of "off-the-shelf" oligos. We demonstrate that rupture and delivery is decreased by inhibitors of cytoskeletal dynamics and knockout of mechanosensing proteins. We also show that rupture and delivery correlates with ligand affinity. Excitingly, we demonstrate that rupture and delivery of barcoded DNA-duplexes can be quantified using DNA sequencing, propelling cellular force measurements into the -omics era.

biophysics↗

bioRxiv2022

Differential migration mechanics and immune responses of glioblastoma subtypes

Glioblastoma remains a deadly cancer driven in part by invasion of tumor cells into the brain. Transcriptomic analyses have identified distinct molecular subtypes, but mechanistic differences that account for clinical differences are not clear. Here, we show that, as predicted by the motor-clutch model of cell migration, mesenchymal glioma cells are more spread, generate larger traction forces, and migrate faster in brain tissue compared to proneural cells. Despite their rapid migration and comparable proliferation rates in vitro, mice with mesenchymal tumors survive longer than those with proneural tumors. This improved survival correlated with an immune response in the mesenchymal tumors, including T cell-mediated. Consistently, inducing mesenchymal tumors in immunodeficient mice resulted in shorter survival supporting a protective immune role in mesenchymal tumors. Thus, mesenchymal tumors have aggressive migration, but are immunologically hot which suppresses net proliferation. These two features counteract each other and may explain the lack of a strong survival difference between subtypes clinically, while also opening up new opportunities for subtype-specific therapies. Significant StatementThis study highlights new mechanical and immunological insights into glioblastoma molecular subtypes using an integrated modeling-genome engineering strategy, which can potentially facilitate glioblastoma subtype-specific therapeutic strategies.

cancer biology↗

bioRxiv2021

Clinically Validated Model Predicts the Effect of Intratumoral Heterogeneity on Overall Survival for Non-Small Cell Lung Cancer (NSCLC) Patients

PurposeWe demonstrate the importance of considering intratumoral heterogeneity and the development of resistance during fractionated radiotherapy when the same dose of radiation is delivered for all fractions (Fractional Equivalent Dosing FED). Materials and MethodsA mathematical model was developed with the following parameters: a starting population of 1011 non-small cell lung cancer (NSCLC) tumor cells, 48-hour doubling time, and cell death per the linear-quadratic (LQ) model with and {beta} values derived from RSI/{beta}, in a previously described gene expression based model that estimates and {beta}. To incorporate both inter- and intratumor radiation sensitivity, RSI/{beta} output for each patient sample is assumed to represent an average value in a gamma distribution with the bounds set to -50% and +50% of RSI/b. Therefore, we assume that within a given tumor there are subpopulations that have varying radiation sensitivity parameters that are distinct from other tumor samples with a different mean RSI/{beta}. A simulation cohort (SC) comprised of 100 lung cancer patients with available RSI/{beta} (patient specific and {beta} values) was used to investigate 60Gy in 30 fractions with fractionally equivalent dosing (FED). A separate validation cohort (VC) of 57 lung cancer patients treated with radiation with available local control (LC), overall survival (OS), and tumor gene expression was used to clinically validate the model. Cox regression was used to test for significance to predict clinical outcomes as a continuous variable in multivariate analysis (MVA). Finally, the VC was used to compare FED schedules with various altered fractionation schema utilizing a Kruskal-Wallis test. This was examined using the end points of end of treatment log cell count (LCC) and by a parameter described as mean log kill efficiency (LKE) defined as: O_FD O_INLINEFIG[Formula 1]C_INLINEFIGM_FD(1)C_FD ResultsCox regression analysis on LCC for the VC demonstrates that, after incorporation of intratumoral heterogeneity, LCC has a linear correlation with local control (p = 0.002) and overall survival (p =< 0.001). Other suggested treatment schedules labeled as High Intensity Treatment (HIT) with a total 60Gy delivered over 6 weeks have a lower mean LCC and an increased LKE compared to standard of care 60Gy delivered in FED in the VC. ConclusionWe find that LCC is a clinically relevant metric that is correlated with local control and overall survival in NSCLC. We conclude that 60Gy delivered over 6 weeks with altered HIT fractionation leads to an enhancement in tumor control compared to FED when intratumoral heterogeneity is considered.

cancer biology↗

bioRxiv2020

Negative durotaxis: cell movement toward softer environments

Durotaxis - the ability of cells to sense and migrate along stiffness gradients - is important for embryonic development and has been implicated in pathologies including fibrosis and cancer. Although cellular processes can sometimes turn toward softer environments, durotaxis at the level of cells has thus far been observed exclusively as migration from soft to stiff regions. The molecular basis of durotaxis, especially the factors that contribute to different durotactic behaviors in various cell types, are still inadequately understood. With the recent discovery of optimal stiffness, where cells generate maximal traction forces on substrates in an intermediate stiffness range, we hypothesized that some migratory cells may be capable of moving away from stiff environments and toward matrix on which they can generate more traction. Combining hydrogel-based stiffness gradients, live-cell imaging, genetic manipulations, and computational modeling, we found that cells move preferentially toward their stiffness optimum for maximal force transmission. Importantly, we directly observed biased migration toward softer environments, i.e. negative durotaxis, in human glioblastoma cells. This directional migration did not coincide with changes in FAK, ERK or YAP signaling, or with altered actomyosin contractility. Instead, integrin-mediated adhesion and motor-clutch dynamics alone are sufficient to generate asymmetric traction to drive both positive and negative durotaxis. We verified this mechanistically by applying a motor-clutch-based model to explain negative durotaxis in the glioblastoma cells and in neurites, and experimentally by switching breast cancer cells from positive to negative durotaxis via talin downregulation. Our results identify the likely molecular mechanisms of durotaxis, with a cells contractile and adhesive machinery dictating its capacity to exert traction on mechanically distinct substrates, directing cell migration.

biophysics↗

bioRxiv2020

Biophysical modeling of the SARS-CoV-2 viral cycle reveals ideal antiviral targets

Effective therapies for COVID-19 are urgently needed. Presently there are more than 800 COVID-19 clinical trials globally, many with drug combinations, resulting in an empirical process with an enormous number of possible combinations. To identify the most promising potential therapies, we developed a biophysical model for the SARS-CoV-2 viral cycle and performed a sensitivity analysis for individual model parameters and all possible pairwise parameter changes (162 = 256 possibilities). We found that model-predicted virion production is fairly insensitive to changes in most viral entry, assembly, and release parameters, but highly sensitive to some viral transcription and translation parameters. Furthermore, we found a cooperative benefit to pairwise targeting of transcription and translation, predicting that combined targeting of these processes will be especially effective in inhibiting viral production.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2020

Poisson poisoning as the mechanism of action of the microtubule-targeting agent colchicine

Microtubule-directed anti-cancer drugs, such as paclitaxel, vinblastine, and colchicine, disrupt cell mitosis through suppression of microtubule dynamics ("kinetic stabilization"). However, while the molecular mechanisms of paclitaxel and vinblastine act as pseudo- and true-kinetic stabilizers, respectively, the molecular mechanism of colchicine has remained enigmatic since it requires explanation of both the slow kinetics of the drug and suppression of microtubule dynamics. In this work, we applied an integrated multi-scale modeling-experimental approach to systematically characterize the microtubule targeting agent (MTA) colchicine. We found that colchicine stabilizes microtubule dynamics significantly both in vivo and in vitro in a time and concentration-dependent manner. Molecular modeling results suggest that tubulins binding pocket is accessible to the drug for only 15% of the simulation trajectory time in straight and 82% in curved conformation on average, confirming that colchicine mainly binds to free tubulin. Molecular dynamics simulations show that there are conformational changes at longitudinal and lateral residues of GTP-tubulin-colchicine compared to a lattice tubulin structure, explaining why further incorporation of tubulin dimers to a tubulin-colchicine complex at a protofilament tip is unfavorable. Thermokinetic modeling of microtubule assembly shows that colchicine bound at fractions as low as [~]0.008 to free tubulin can poison the ends of protofilaments with a Poisson distribution and thus, reduce the microtubule growth rate, while stabilizing the tubulin lateral bond and reducing the microtubule shortening rate, i.e. true kinetic stabilization. This study suggests new strategies for colchicine administration to improve the therapeutic window in the treatment of cancer and inflammatory diseases. Significance StatementColchicine is an ancient microtubule targeting agent (MTA) known to attenuate microtubule (MT) dynamics but its cancer treatment efficacy is often limited by lack of a detailed understanding of the drugs mechanism of action. The primary goal of this study was to perform a multi-scale systematic analysis of molecular mechanism of action of colchicine. The analysis indicates that unlike paclitaxel and vinblastine, colchicine poisons the ends of protofilaments of MTs at low fractions bound to tubulin, in a time-dependent manner. Our results suggest new insights into improvement of the clinical administration of colchicine and new colchicine-site inhibitors.

biophysics↗