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International audience; We propose a chemical-mechanical model of myosin heads in sarcomeres, within the classical description of rigid sliding filaments. In our case, myosin heads have two mechanical degrees-of-freedom (dofs) - one of which associated with the so-called power stroke - and two possible chemical states, i.e. bound to an actin site or not. Our major motivations are twofold: (1) to derive a multiscale coupled chemical-mechanical model, and (2) to thus account - at the macroscopic scale - for mechanical phenomena that are out of reach for classical muscle models. This model is first written in the form of Langevin stochastic equations, and we are then able to obtain the corresponding Fokker-Planck partial differential equations governing the probability density functions associated with the mechanical dofs and chemical states. This second form is important, as it allows to monitor muscle energetics, and also to compare our model with classical ones, such as the Huxley'57 model to which our equations are shown to reduce under two different types of simplifying assumptions. This provides insight, and gives a Langevin form for Huxley'57. We then show how we can calibrate our model based on experimental data - taken here for skeletal muscles - and numerical simulations demonstrate the adequacy of the model to represent complex physiological phenomena, in particular the fast isometric transients in which the power stroke is known to have a crucial role, thus circumventing a limitation of many classical models.

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Significance We propose a mechanistic description of fusion of a synaptic vesicle with a target membrane executed by a team of zippering SNARE complexes (SNAREpins). In the context of neurotransmitters release, this process naturally decomposes in two steps with rates that depend on the number of SNAREpins N. The first step is synchronized escape from the metastable half-zippered state, which gets exponentially more sluggish as N increases. The second step is fusion of two closely tethered membranes, which is accelerated exponentially by an increase of N. The tradeoff between these two antagonist trends results in a sharply optimal number of SNAREpins N=3−6, which ensures fusion at the physiological submillisecond timescale., SNARE proteins zipper to form complexes (SNAREpins) that power vesicle fusion with target membranes in a variety of biological processes. A single SNAREpin takes about 1 s to fuse two bilayers, yet a handful can ensure release of neurotransmitters from synaptic vesicles much faster: in a 10th of a millisecond. We propose that, similar to the case of muscle myosins, the ultrafast fusion results from cooperative action of many SNAREpins. The coupling originates from mechanical interactions induced by confining scaffolds. Each SNAREpin is known to have enough energy to overcome the fusion barrier of 25–35 kBT; however, the fusion barrier only becomes relevant when the SNAREpins are nearly completely zippered, and from this state, each SNAREpin can deliver only a small fraction of this energy as mechanical work. Therefore, they have to act cooperatively, and we show that at least three of them are needed to ensure fusion in less than a millisecond. However, to reach the prefusion state collectively, starting from the experimentally observed half-zippered metastable state, the SNAREpins have to mechanically synchronize, which takes more time as the number of SNAREpins increases. Incorporating this somewhat counterintuitive idea in a simple coarse-grained model results in the prediction that there should be an optimum number of SNAREpins for submillisecond fusion: three to six over a wide range of parameters. Interestingly, in situ cryoelectron microscope tomography has very recently shown that exactly six SNAREpins participate in the fusion of each synaptic vesicle. This number is in the range predicted by our theory.

The chemomechanical model of Huxley and Simmons (HS) [A. F. Huxley and R. M. Simmons, Nature 233, 533 (1971)] provides a paradigmatic description of mechanically induced collective conformational changes relevant in a variety of biological contexts, from muscles power-stroke and hair cell gating to integrin binding and hairpin unzipping. We develop a statistical mechanical perspective on the HS model by exploiting a formal analogy with a paramagnetic Ising model. We first study the equilibrium HS model with a finite number of elements and compute explicitly its mechanical and thermal properties. To model kinetics, we derive a master equation and solve it for several loading protocols. The developed formalism is applicable to a broad range of allosteric systems with mean-field interactions., Comment: Physical Review E , American Physical Society (APS), 2016. arXiv admin note: text overlap with arXiv:1510.03011

International audience; Mechanically induced unfolding of passive crosslinkers is a fundamental biological phenomenon encountered across the scales from individual macro-molecules to cytoskeletal actin networks. In this paper we study a conceptual model of athermal load-induced unfolding and use a minimalistic setting allowing one to emphasize the role of long-range interactions while maintaining full analytical transparency. Our model can be viewed as a description of a parallel bundle of N bistable units confined between two shared rigid backbones that are loaded through a series spring. We show that the ground states in this model correspond to synchronized, single phase configurations where all individual units are either folded or unfolded. We then study the fine structure of the wiggly energy landscape along the reaction coordinate linking the two coherent states and describing the optimal mechanism of cooperative unfolding. Quite remarkably, our study shows the fundamental difference in the size and structure of the folding-unfolding energy barriers in the hard (fixed displacements) and soft (fixed forces) loading devices which persists in the continuum limit. We argue that both, the synchronization and the non-equivalence of the mechanical responses in hard and soft devices, have their origin in the dominance of long-range interactions. We then apply our minimal model to skeletal muscles where the power-stroke in acto-myosin crossbridges can be interpreted as passive folding. A quantitative analysis of the muscle model shows that the relative rigidity of myosin backbone provides the long-range interaction mechanism allowing the system to effectively synchronize the power-stroke in individual crossbridges even in the presence of thermal fluctuations. In view of the prototypical nature of the proposed model, our general conclusions pertain to a variety of other biological systems where elastic interactions are mediated by effective backbones.

International audience; Complex 3D beating heart models are now available, but their complexity makes calibration and validation very difficult tasks. We thus propose a systematic approach of deriving simplified reduced-dimen\-sional models, in ''0D'' --~typically, to represent a cardiac cavity, or several coupled cavities --~and in ''1D'' --~to model elongated structures such as muscle samples or myocytes. We apply this approach with an earlier-proposed 3D cardiac model designed to capture length-dependence effects in contraction, which we here complement by an additional modeling component devised to represent length-dependent relaxation. We then pre\-sent experimental data produced with rat papillary muscles samples when varying preload and afterload conditions, and we achieve some detailed validations of the 1D model with these data, including for the length-dependence effects that are accurately captured. Finally, when running simulations of the 0D model pre-calibrated with the 1D model parameters, we obtain pressure-volume indicators of the left ventricle in good agreement with some important features of cardiac physiology, including the so-called Frank-Starling mechanism, the End-Systolic Pres\-sure-Volume Relationship (ESPVR), as well as varying elastance properties. This integrated multi-dimensional modeling approach thus sheds new light on the relations between the phenomena observed at different scales and at the local vs. organ levels.

To be published as proceedings in: Functional Imaging and Modeling of the Heart 7th International Conference, FIMH 2013, London, UK, Lecture Notes in Computer Science 7945; International audience; Complex 3D beating heart models are now available, but their complexity makes calibration and validation very difficult tasks. We thus propose a systematic approach of deriving simplified reduced- dimensional models, in "0D" - typically, to represent a cardiac cavity, or several coupled cavities - and in "1D" - to model elongated structures such as fibers or myocytes. As illustrations of our approach, we demon- strate model validation based on experiments performed with papillary muscles, and calibration using patient-specific pressure-volume loops.

Passive mechanical response of skeletal muscles at fast time scales is dominated by long range interactions inducing cooperative behavior without breaking the detailed balance. This leads to such unusual "material properties" as negative equilibrium stiffness and different behavior in force and displacement controlled loading conditions. Our fitting of experimental data suggests that "muscle material" is finely tuned to perform close to a critical point which explains large fluctuations observed in muscles close to the stall force., Comment: Accepted for publication in Physical Review Letters

This PhD thesis deals with the mathematical description of the micro-scale muscle contraction mechanisms with the aim of proposing and integrating our models into a multiscale heart simulation framework.This research effort is made in the context of digital medicine, which proposes to improve the treatment of patients with the use of numerical tools.The first contribution of this thesis is a literature review of the experimental works characterizing the actin-myosin interaction and its regulations to compile information in a useable form for the development of models.This stage is an essential prerequisite to modeling.We then propose a hierarchy of muscle contraction models starting from a previously proposed refined stochastic model, which was only validated for skeletal muscles, and applying successive simplification assumptions.The simplification stages transform the initial stochastic differential equation into a partial differential equation with a model that is part of the Huxley'57 model family.A further simplification then leads to a description governed by a set of ordinary differential equations.The relevance of these models, targeting different time scales, is demonstrated by comparing them with experimental data obtained with cardiac muscles and their range of validity is investigated.To integrate these microscopic descriptions into a heart simulation framework, we extend the models to take into account the force regulation mechanisms that take place in vivo, leading to the derivation of new partial differential equations.Then, we link the microscopic contraction models to the macroscopic organ model.We follow for that an approach based on the thermodynamical principles to deal with the multi-scale nature in time and space of the muscle tissue at the continuous and at the discrete levels.The validity of this simulation framework is demonstrated by showing its ability to reproduce the heart behavior and in particular to capture the essential features of the Frank-Starling effect.; L'objectif de cette thèse est la modélisation mathématique des mécanismes de contraction musculaire à l'échelle microscopique dans le but de proposer et d'intégrer ces modèles dans un environnement de simulation cardiaque multi-échelle.Ce travail est réalisé dans le contexte de la médecine numérique, qui propose d'améliorer le traitement des patients par l'utilisation d'outils numériques.La première contribution de cette thèse est une analyse bibliographique des travaux expérimentaux caractérisant l’interaction actine-myosine et ses régulations afin de compiler les informations sous une forme utilisable pour le développement de modèles.Cette étape est une condition préalable essentielle à la modélisation.Nous proposons ensuite une hiérarchie de modèles de contraction musculaire à partir d'un modèle stochastique raffiné existant, mais validé uniquement pour les muscles squelettiques, en appliquant des hypothèses de simplification successives.Les étapes de simplification transforment l'équation différentielle stochastique initiale en une équation aux dérivées partielles avec une description qui fait partie de la famille de modèles dérivée du modèle Huxley'57.Une simplification supplémentaire conduit ensuite à un modèle décrit par un ensemble d'équations différentielles ordinaires.La pertinence des modèles proposés, qui ciblent différentes échelles de temps, est démontrée en les comparant aux données expérimentales obtenues avec des muscles cardiaques, et leur domaine de validité est étudié.Pour intégrer ces descriptions dans un environnement de simulation cardiaque, nous avons étendu ces modèles afin de prendre en compte les mécanismes de régulation de la force qui se produisent in vivo.Cela conduit à de nouvelles équations aux dérivées partielles.Ensuite, nous lions les modèles de contraction microscopiques à un modèle d’organe macroscopique.Nous suivons pour cela une approche fondée sur les principes thermodynamiques pour traiter la nature multi-échelle en temps et en espace du tissu musculaire aux niveaux continu et discret.La validité de cet environnement de simulation est démontrée en présentant sa capacité à reproduire le comportement du coeur et en particulier les caractéristiques essentielles de l'effet Frank-Starling.

This PhD thesis deals with the mathematical description of the micro-scale muscle contraction mechanisms with the aim of proposing and integrating our models into a multiscale heart simulation framework.This research effort is made in the context of digital medicine, which proposes to improve the treatment of patients with the use of numerical tools.The first contribution of this thesis is a literature review of the experimental works characterizing the actin-myosin interaction and its regulations to compile information in a useable form for the development of models.This stage is an essential prerequisite to modeling.We then propose a hierarchy of muscle contraction models starting from a previously proposed refined stochastic model, which was only validated for skeletal muscles, and applying successive simplification assumptions.The simplification stages transform the initial stochastic differential equation into a partial differential equation with a model that is part of the Huxley'57 model family.A further simplification then leads to a description governed by a set of ordinary differential equations.The relevance of these models, targeting different time scales, is demonstrated by comparing them with experimental data obtained with cardiac muscles and their range of validity is investigated.To integrate these microscopic descriptions into a heart simulation framework, we extend the models to take into account the force regulation mechanisms that take place in vivo, leading to the derivation of new partial differential equations.Then, we link the microscopic contraction models to the macroscopic organ model.We follow for that an approach based on the thermodynamical principles to deal with the multi-scale nature in time and space of the muscle tissue at the continuous and at the discrete levels.The validity of this simulation framework is demonstrated by showing its ability to reproduce the heart behavior and in particular to capture the essential features of the Frank-Starling effect.; L'objectif de cette thèse est la modélisation mathématique des mécanismes de contraction musculaire à l'échelle microscopique dans le but de proposer et d'intégrer ces modèles dans un environnement de simulation cardiaque multi-échelle.Ce travail est réalisé dans le contexte de la médecine numérique, qui propose d'améliorer le traitement des patients par l'utilisation d'outils numériques.La première contribution de cette thèse est une analyse bibliographique des travaux expérimentaux caractérisant l’interaction actine-myosine et ses régulations afin de compiler les informations sous une forme utilisable pour le développement de modèles.Cette étape est une condition préalable essentielle à la modélisation.Nous proposons ensuite une hiérarchie de modèles de contraction musculaire à partir d'un modèle stochastique raffiné existant, mais validé uniquement pour les muscles squelettiques, en appliquant des hypothèses de simplification successives.Les étapes de simplification transforment l'équation différentielle stochastique initiale en une équation aux dérivées partielles avec une description qui fait partie de la famille de modèles dérivée du modèle Huxley'57.Une simplification supplémentaire conduit ensuite à un modèle décrit par un ensemble d'équations différentielles ordinaires.La pertinence des modèles proposés, qui ciblent différentes échelles de temps, est démontrée en les comparant aux données expérimentales obtenues avec des muscles cardiaques, et leur domaine de validité est étudié.Pour intégrer ces descriptions dans un environnement de simulation cardiaque, nous avons étendu ces modèles afin de prendre en compte les mécanismes de régulation de la force qui se produisent in vivo.Cela conduit à de nouvelles équations aux dérivées partielles.Ensuite, nous lions les modèles de contraction microscopiques à un modèle d’organe macroscopique.Nous suivons pour cela une approche fondée sur les principes thermodynamiques pour traiter la nature multi-échelle en temps et en espace du tissu musculaire aux niveaux continu et discret.La validité de cet environnement de simulation est démontrée en présentant sa capacité à reproduire le comportement du coeur et en particulier les caractéristiques essentielles de l'effet Frank-Starling.