101 research outputs found

    Cytotoxicity in the Age of Nano: The Role of Fourth Period Transition Metal Oxide Nanoparticle Physicochemical Properties

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    A clear understanding of physicochemical factors governing nanoparticle toxicity is still in its infancy. We used a systematic approach to delineate physicochemical properties of nanoparticles that govern cytotoxicity. The cytotoxicity of fourth period metal oxide nanoparticles (NPs): TiO2, Cr2O3, Mn2O3, Fe2O3, NiO, CuO, and ZnO increases with the atomic number of the transition metal oxide. This trend was not cell-type specific, as observed in non-transformed human lung cells (BEAS-2B) and human bronchoalveolar carcinoma-derived cells (A549). Addition of NPs to the cell culture medium did not significantly alter pH. Physiochemical properties were assessed to discover the determinants of cytotoxicity: (1) point-of-zero charge (PZC) (i.e., isoelectric point) described the surface charge of NPs in cytosolic and lysosomal compartments; (2) relative number of available binding sites on the NP surface quantified by X-ray photoelectron spectroscopy was used to estimate the probability of biomolecular interactions on the particle surface; (3) band-gap energy measurements to predict electron abstraction from NPs which might lead to oxidative stress and subsequent cell death; and (4) ion dissolution. Our results indicate that cytotoxicity is a function of particle surface charge, the relative number of available surface binding sites, and metal ion dissolution from NPs. These findings provide a physicochemical basis for both risk assessment and the design of safer nanomaterials

    Intrinsic dynamic behavior of fascin in filopodia

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    Author Posting. © American Society for Cell Biology, 2007. This article is posted here by permission of American Society for Cell Biology for personal use, not for redistribution. The definitive version was published in Molecular Biology of the Cell 18 (2007): 3928-3940, doi:10.1091/mbc.E07-04-0346.Recent studies showed that the actin cross-linking protein, fascin, undergoes rapid cycling between filopodial filaments. Here, we used an experimental and computational approach to dissect features of fascin exchange and incorporation in filopodia. Using expression of phosphomimetic fascin mutants, we determined that fascin in the phosphorylated state is primarily freely diffusing, whereas actin bundling in filopodia is accomplished by fascin dephosphorylated at serine 39. Fluorescence recovery after photobleaching analysis revealed that fascin rapidly dissociates from filopodial filaments with a kinetic off-rate of 0.12 s–1 and that it undergoes diffusion at moderate rates with a coefficient of 6 µm2s–1. This kinetic off-rate was recapitulated in vitro, indicating that dynamic behavior is intrinsic to the fascin cross-linker. A computational reaction–diffusion model showed that reversible cross-linking is required for the delivery of fascin to growing filopodial tips at sufficient rates. Analysis of fascin bundling indicated that filopodia are semiordered bundles with one bound fascin per 25–60 actin monomers.This work was supported by a National Institutes of Health F31National Research Service Award NS055565-01 (to Y.S.A.), Northwestern University Pulmonary and Critical Care Division T32 (to T.E.S.), and National Institutes of Health grant GM-70898 (to G.G.B.)

    Coordination of Membrane and Actin Cytoskeleton Dynamics during Filopodia Protrusion

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    Leading edge protrusion of migrating cells involves tightly coordinated changes in the plasma membrane and actin cytoskeleton. It remains unclear whether polymerizing actin filaments push and deform the membrane, or membrane deformation occurs independently and is subsequently stabilized by actin filaments. To address this question, we employed an ability of the membrane-binding I-BAR domain of IRSp53 to uncouple the membrane and actin dynamics and to induce filopodia in expressing cells. Using time-lapse imaging and electron microscopy of IRSp53-I-BAR-expressing B16F1 melanoma cells, we demonstrate that cells are not able to protrude or maintain durable long extensions without actin filaments in their interior, but I-BAR-dependent membrane deformation can create a small and transient space at filopodial tips that is subsequently filled with actin filaments. Moreover, the expressed I-BAR domain forms a submembranous coat that may structurally support these transient actin-free protrusions until they are further stabilized by the actin cytoskeleton. Actin filaments in the I-BAR-induced filopodia, in contrast to normal filopodia, do not have a uniform length, are less abundant, poorly bundled, and display erratic dynamics. Such unconventional structural organization and dynamics of actin in I-BAR-induced filopodia suggests that a typical bundle of parallel actin filaments is not necessary for generation and mechanical support of the highly asymmetric filopodial geometry. Together, our data suggest that actin filaments may not directly drive the protrusion, but only stabilize the space generated by the membrane deformation; yet, such stabilization is necessary for efficient protrusion

    Evolving cell models for systems and synthetic biology

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    This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm’s results as well as of the resulting evolved cell models

    Growth landscape formed by perception and import of glucose in yeast

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    An important challenge in systems biology is to quantitatively describe microbial growth using a few measurable parameters that capture the essence of this complex phenomenon. Two key events at the cell membrane—extracellular glucose sensing and uptake—initiate the budding yeast’s growth on glucose. However, conventional growth models focus almost exclusively on glucose uptake. Here we present results from growth-rate experiments that cannot be explained by focusing on glucose uptake alone. By imposing a glucose uptake rate independent of the sensed extracellular glucose level, we show that despite increasing both the sensed glucose concentration and uptake rate, the cell’s growth rate can decrease or even approach zero. We resolve this puzzle by showing that the interaction between glucose perception and import, not their individual actions, determines the central features of growth, and characterize this interaction using a quantitative model. Disrupting this interaction by knocking out two key glucose sensors significantly changes the cell’s growth rate, yet uptake rates are unchanged. This is due to a decrease in burden that glucose perception places on the cells. Our work shows that glucose perception and import are separate and pivotal modules of yeast growth, the interaction of which can be precisely tuned and measured.National Institutes of Health (U.S.). Pioneer AwardNatural Sciences and Engineering Research Council of Canada (NSERC). Graduate Fellowshi

    Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks

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    Background The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. Methodology/Principal Findings To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes () and latency of the optimized engineered gene networks. Conclusions/Significance Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.National Institutes of Health (U.S.) (Grant # 7R01GM74712-5)United States. Defense Advanced Research Projects Agency (contract HR0011-10-C-0168)National Science Foundation (U.S.) (NSF CAREER award 0968682)BBN Technologie

    The Role of Actin Turnover in Retrograde Actin Network Flow in Neuronal Growth Cones

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    The balance of actin filament polymerization and depolymerization maintains a steady state network treadmill in neuronal growth cones essential for motility and guidance. Here we have investigated the connection between depolymerization and treadmilling dynamics. We show that polymerization-competent barbed ends are concentrated at the leading edge and depolymerization is distributed throughout the peripheral domain. We found a high-to-low G-actin gradient between peripheral and central domains. Inhibiting turnover with jasplakinolide collapsed this gradient and lowered leading edge barbed end density. Ultrastructural analysis showed dramatic reduction of leading edge actin filament density and filament accumulation in central regions. Live cell imaging revealed that the leading edge retracted even as retrograde actin flow rate decreased exponentially. Inhibition of myosin II activity before jasplakinolide treatment lowered baseline retrograde flow rates and prevented leading edge retraction. Myosin II activity preferentially affected filopodial bundle disassembly distinct from the global effects of jasplakinolide on network turnover. We propose that growth cone retraction following turnover inhibition resulted from the persistence of myosin II contractility even as leading edge assembly rates decreased. The buildup of actin filaments in central regions combined with monomer depletion and reduced polymerization from barbed ends suggests a mechanism for the observed exponential decay in actin retrograde flow. Our results show that growth cone motility is critically dependent on continuous disassembly of the peripheral actin network
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