Forces exerted on a cylinder in near-axial flow

International audienceThis study investigates the flow around a cylinder in a near-axial flow at a Reynolds number of 27,000. Both computational fluid dynamics (CFD) calculations and experiments are performed. Time-mean values of lift force coefficient are investigated against the inclination of the cylinder in the domain of low inclinations (<15 deg). A pressure distribution and flow profiles are also measured and extracted from the CFD calculation results for a characteristic inclination α = 5 deg. Numerical results for force and pressure show fair agreement with experiments for inclination below 5 deg and reveal that at low angles, the lift force is proportional to the angle. In the framework of a quasi-static approach, the instantaneous damping force exerted on a cylinder oscillating in axial flow is equivalent to the normal force exerted on a cylinder placed in an oblique flow

Molecular diversity, metabolic transformation, and evolution of carotenoid feather pigments in cotingas (Aves: Cotingidae)

Abstract Carotenoid pigments were extracted from 29 feather patches from 25 species of cotingas (Cotingidae) representing all lineages of the family with carotenoid plumage coloration. Using high-performance liquid chromatography (HPLC), mass spectrometry, chemical analysis, and 1 H-NMR, 16 different carotenoid molecules were documented in the plumages of the cotinga family. These included common dietary xanthophylls (lutein and zeaxanthin), canary xanthophylls A and B, four well known and broadly distributed avian ketocarotenoids (canthaxanthin, astaxanthin, a-doradexanthin, and adonixanthin), rhodoxanthin, and seven 4-methoxy-ketocarotenoids. Methoxy-ketocarotenoids were found in 12 species within seven cotinga genera, including a new, previously undescribed molecule isolated from the Andean Cock-of-the-Rock Rupicola peruviana, 3 0 -hydroxy-3-methoxy-b,b-carotene-4-one, which we name rupicolin. The diversity of cotinga plumage carotenoid pigments is hypothesized to be derived via four metabolic pathways from lutein, zeaxanthin, b-cryptoxanthin, and b-carotene. All metabolic transformations within the four pathways can be described by six or seven different enzymatic reactions. Three of these reactions are shared among three precursor pathways and are responsible for eight different metabolically derived carotenoid molecules. The function of cotinga plumage carotenoid diversity was analyzed with reflectance spectrophotometry of plumage patches and a tetrahedral model of avian color visual perception. The evolutionary history of the origin of this diversity is analyzed phylogenetically. The color space analyses document that the evolutionarily derived metabolic modifications of dietary xanthophylls have resulted in the creation of distinctive orange-red and purple visual colors

Du monomère à la cellule: Modèles de la dynamique de l'actine

Actin filaments are biological polymers that are very abundant in eucaryot cytoskeleton. Their auto-assembly and auto-organization are highly dynamic and are essential in cell motility and membrane deformations. In this thesis we propose three approaches, on different scales, in order to enlighten mechanisms for the regulation of assembly of, organization of and production of force by biological filaments such as actin filaments. First, we have developed a stochastic multi-agent simulation tool for studying biological filaments taking into consideration interactions on the nanometer scale. This new tool allowed us to bring out the acceleration of actin monomer turnover due to fragmentation of filaments by ADF/Cofilin and the symmetry breaking induced by this protein, which agree well with experimental data from L. Blanchoin team (CEA Grenoble). Secondly, we studied a continuous model for filament buckling, providing, on the one hand, an estimation of forces exerted in vitro or in vivo with respect to extremity attachment conditions and, on the other hand, limit conditions for buckling. Thirdly, we developed a framework for organizing kinetic biochemical data from reaction networks, which was used for the regulation of actin polymerization. These three modeling approaches improved the knowledge on actin dynamics and are useful complements for experimental approaches in biology.Les filaments d'actine sont des polymères biologiques très abondants dans le cytosquelette des eucaryotes. Leur auto-assemblage et leur auto-organisation sont très dynamiques et ils jouent un rôle majeur dans la motilité cellulaire et dans les déformations de la membrane. Nous présentons dans cette thèse trois approches de modélisation, à différentes échelles, afin de mieux comprendre les mécanismes de régulation de l'assemblage, de l'organisation et de la production de forces par des filaments biologiques tels que les filaments d'actine. Nous avons tout d'abord développé un outil de simulation multi-agent stochastique pour l'étude de la dynamique de filaments biologiques prenant en compte les interactions à l'échelle du nanomètre. Ce nouvel outil nous a permis de mettre en évidence l'accélération du turnover des monomères d'actine par fragmentation des filaments par l'ADF/Cofiline ainsi que les ruptures de symétries induites par cette protéine, résultats concordant avec les expériences de l'équipe de L. Blanchoin (CEA Grenoble). Nous avons également mené l'étude d'un modèle continu pour le flambage de filaments qui a permis d'estimer les forces exercées in vivo et in vitro en fonction des conditions d'attachement des extrémités et de donner des conditions limites de certains paramètres permettant le flambage. Troisièmement, nous avons développé un cadre pour l'organisation des données de cinétique biochimique de réseaux de régulation que nous avons utilisé pour la régulation de la polymérisation de l'actine. Ces trois approches de modélisation ont permis d'améliorer la connaissance sur la dynamique de l'actine et sont complémentaires aux approches expérimentales de la biologie

Du monomère à la cellule (modèle de la dynamique de l'actine)

Les filaments d'actine sont des polymères biologiques très abondants dans le cytosquelette des eucaryotes. Leur auto-assemblage et leur autoorganisation sont très dynamiques et ils jouent un rôle majeur dans la motilité cellulaire et dans les déformations de la membrane. Nous présentons dan cette thèse trois approches de modélisation, à différentes échelles, afin de mieux comprendre les mécanismes de régulation de l'assemblage, de l'organisation et de la production de forces par des filaments biologiques tels que les filaments d'actine. Nous avons tout d'abord développé un outil de simulation multi-agent stochastique pour l'étude de la dynamique de filaments biologiques prenant en compte les interactions à l'échelle du nanomètre. Ce nouvel outil nous a permis de mettre en évidence l'accélération du turnover des monomères d'actine par fragmentation des filaments par l'ADF/Cofiline ainsi que les ruptures de symétries induites par cette protéine, résultats concordant avec les expériences de l'équipe de L. Blanchoin (CEA Grenoble). Nous avons également mené l'étude d'un modèle continu pour le flambage de filaments qui a permis d'estimer les forces exercées in vivo et in vitro en fonction des conditions d'attachement des extrémités et de donner des conditions limites de certains paramètres permettant le flambage. Troisièmement, nous avons développé un cadre pour l'organisation des données de cinétique biochimique de réseaux de régulation que nous avons utilisé pour la régulation de la polymérisation de l'actine. Ces trois approches de modélisation ont permis d'améliorer la connaissance sur la dynamique de l'actine et sont complémentaires aux approches expérimentales de la biologieActin filaments are biological polymers that are very abundant in eucaryot cytoskeleton. Their auto-assembly and auto-organization are highly dynami. and are essential in cell motility and membrane deformations. ln this thesis we propose three approaches, on different scales, in order to enlighten mechanisms for the regulation ofassembly of, organization of and production of force by biological filaments such as actin filaments. First, we have developed a stochastic multi-agent simulation tool for studying biological filaments taking into consideration interactions on the nanometer scale. This new tool allowed us to bring out the acceleration of actin monomer turnover due to fragmentation of filaments by ADF/Cofilin and the symmetry breaking induced by thisprotein, which agree weil with experimental data from L. Blanchoin team (CEA Grenoble). Secondly, we studied a continuou model for filament buckling, providing, on the one hand, an estimation of forces exerted in vitro or in vivo with respect to extremity attachment conditions and, on the other hand, limit conditions for buckling. Thirdly, we developed a framework for organizing kinetic biochemical data from reaction networks, which was used for the regulation of actin polymerization. These three modeling approaches improved the knowledge on actin dynamics and are useful complements for experimental approaches in biologyGRENOBLE1-BU Sciences (384212103) / SudocSudocFranceF

Rapid adaptation of endocytosis, exocytosis, and eisosomes after an acute increase in membrane tension in yeast cells.

During clathrin-mediated endocytosis (CME) in eukaryotes, actin assembly is required to overcome large membrane tension and turgor pressure. However, the molecular mechanisms by which the actin machinery adapts to varying membrane tension remain unknown. In addition, how cells reduce their membrane tension when they are challenged by hypotonic shocks remains unclear. We used quantitative microscopy to demonstrate that cells rapidly reduce their membrane tension using three parallel mechanisms. In addition to using their cell wall for mechanical protection, yeast cells disassemble eisosomes to buffer moderate changes in membrane tension on a minute time scale. Meanwhile, a temporary reduction in the rate of endocytosis for 2-6 min and an increase in the rate of exocytosis for at least 5 min allow cells to add large pools of membrane to the plasma membrane. We built on these results to submit the cells to abrupt increases in membrane tension and determine that the endocytic actin machinery of fission yeast cells rapidly adapts to perform CME. Our study sheds light on the tight connection between membrane tension regulation, endocytosis, and exocytosis

Structural organization and energy storage in crosslinked actin assemblies

<div><p>During clathrin-mediated endocytosis in yeast cells, short actin filaments (< 200nm) and crosslinking protein fimbrin assemble to drive the internalization of the plasma membrane. However, the organization of the actin meshwork during endocytosis remains largely unknown. In addition, only a small fraction of the force necessary to elongate and pinch off vesicles can be accounted for by actin polymerization alone. In this paper, we used mathematical modeling to study the self-organization of rigid actin filaments in the presence of elastic crosslinkers in conditions relevant to endocytosis. We found that actin filaments condense into either a disordered meshwork or an ordered bundle depending on filament length and the mechanical and kinetic properties of the crosslinkers. Our simulations also demonstrated that these nanometer-scale actin structures can store a large amount of elastic energy within the crosslinkers (up to 10<i>k</i>_B<i>T</i> per crosslinker). This conversion of binding energy into elastic energy is the consequence of geometric constraints created by the helical pitch of the actin filaments, which results in frustrated configurations of crosslinkers attached to filaments. We propose that this stored elastic energy can be used at a later time in the endocytic process. As a proof of principle, we presented a simple mechanism for sustained torque production by ordered detachment of crosslinkers from a pair of parallel filaments.</p></div

Model description.

<p>(A) Actin filaments are modeled as rigid rods made of subunits carrying an orientational vector <b>O</b>_<i>i</i> that represents the normal vector to the binding surface of the actin crosslinker. For visualization, each subunit is depicted as a sphere but is actually a disk-shape with a diameter of <i>b</i> = 6nm and a height of <i>δ</i> = 2.7nm. The orientation of a filament is described by the unit vector <b>N</b>, pointing from the pointed end (-) to the barbed end (+), and the first subunit’s orientational vector <b>M</b> = <b>O</b>₁. Two consecutive subunits have an angle of <i>π</i>14/13 in their orientations. (B) Crosslinker turnover is described by stochastic formation and breakage of bonds between two actin subunits in different filaments, with rate constants <i>k</i>_f and <i>k</i>_b, respectively. (C) Each crosslinker is modeled as a combination of three springs, one extensional spring with stiffness <i>κ</i>_ext, which characterizes the stretchiness <i>l</i>_<i>c</i> between the two actin binding domains, and two torsional springs with stiffness <i>κ</i>_tor, which characterizes the flexibility of the angles <i>θ</i>_<i>i</i> and <i>θ</i>_<i>j</i> between the axis of the crosslinker (which links the centers of each subunits it is attached to) and the vector normal to the binding surface of each actin subunit in each filament (<b>O</b>_<i>i</i> and <b>O</b>_<i>j</i>).</p

Phase diagram of actin network organization as a function of the crosslinking rate <i>k</i>_f and filament length <i>L</i>.

<p>(A, D) Local nematic order parameter <i>S</i>_local as a function of <i>k</i>_f and <i>L</i>. (B, E) Number of attached crosslinkers <i>N</i>_attach as a function of <i>k</i>_f and <i>L</i>. (C, F) Classification of actin network organizations as a function of <i>k</i>_f and <i>L</i>. The extensional stiffness <i>κ</i>_ext is 0.1pN/nm in panels (A-C), and 1pN/nm in panels (D-F). In panels (A, B, D, E), plots are constructed by interpolation of results obtained for increment Δ<i>L</i> = 27nm of <i>L</i> between 81nm and 218nm, and increment Δ<i>k</i>_f = 0.1<i>s</i>⁻¹ of <i>k</i>_f between 0.1<i>s</i>⁻¹ and 1<i>s</i>⁻¹. The value for each parameter set is an average over 10 simulations. In (C) and (F), the border separating bundle (light gray) from meshwork (gray) is defined by <i>S</i>_local = 0.75. The border separating meshwork (gray) from uncrosslinked (dark gray) is defined by <i>N</i>_attach = 300.</p

List of parameters.

<p>List of parameters.</p

Influence of the crosslinker’s mechanical and kinetic properties on the organization of the actin network.

<p>(A-D) Organization of 135nm-long actin filaments at the end of the simulation (<i>t</i> = 50<i>s</i>) for different values of extensional stiffness <i>κ</i>_ext, torsional stiffness <i>κ</i>_tor, and breakage rate , as indicated above the figure. (E) Local nematic order parameter <i>S</i>_local as a function of the extensional stiffness <i>κ</i>_ext, with <i>κ</i>_tor = 10pN ⋅ nm ⋅ rad⁻¹ and . (F) Local nematic order parameter <i>S</i>_local as a function of the torsional stiffness <i>κ</i>_tor, with <i>κ</i>_ext = 0.1pN/nm and . (G) Local nematic order parameter <i>S</i>_local as a function of the strain-free breakage rate , with <i>κ</i>_tor = 10pN ⋅ nm and <i>κ</i>_ext = 1pN/nm. In (E-G), simulations were performed for filaments of various lengths: 81nm (blue), 135nm (red), 189nm (orange). For each simulation, the means of <i>S</i>_local were calculated from the data between <i>t</i> = 40<i>s</i> to 50<i>s</i> and the error bars indicate standard deviation over 10 simulations. <i>S</i>_local corresponding to the networks in panels (A-D) are identified by the red symbols with corresponding shapes.</p