37 research outputs found

    Modeling the emergence of polarity patterns for the intercellular transport of auxin in plants

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    The hormone auxin is actively transported throughout plants via protein machineries including the dedicated transporter known as PIN. The associated transport is ordered with nearby cells driving auxin flux in similar directions. Here we provide a model of both the auxin transport and of the dynamics of cellular polarisation based on flux sensing. Our main findings are: (i) spontaneous intracellular PIN polarisation arises if PIN recycling dynamics are sufficiently non-linear, (ii) there is no need for an auxin concentration gradient, and (iii) ordered multi-cellular patterns of PIN polarisation are favored by molecular noise.Comment: 17 pages and 9 figures (Main Text), 9 pages and 4 figures (Supplementary Material), revised version with some rearrangement

    Noise processing by microRNA-mediated circuits: The Incoherent Feed-Forward Loop, revisited

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    The intrinsic stochasticity of gene expression is usually mitigated in higher eukaryotes by post-transcriptional regulation channels that stabilise the output layer, most notably protein levels. The discovery of small non-coding RNAs (miRNAs) in specific motifs of the genetic regulatory network has led to identifying noise buffering as the possible key function they exert in regulation. Recent in vitro and in silico studies have corroborated this hypothesis. It is however also known that miRNA-mediated noise reduction is hampered by transcriptional bursting in simple topologies. Here, using stochastic simulations validated by analytical calculations based on van Kampen's expansion, we revisit the noise-buffering capacity of the miRNA-mediated Incoherent Feed Forward Loop (IFFL), a small module that is widespread in the gene regulatory networks of higher eukaryotes, in order to account for the effects of intermittency in the transcriptional activity of the modulator gene. We show that bursting considerably alters the circuit's ability to control static protein noise. By comparing with other regulatory architectures, we find that direct transcriptional regulation significantly outperforms the IFFL in a broad range of kinetic parameters. This suggests that, under pulsatile inputs, static noise reduction may be less important than dynamical aspects of noise and information processing in characterising the performance of regulatory elements

    Morfogenesi: una sfida interdisciplinare

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    Quali sono i processi e princìpi primi che permettono ad un organismo di assumere la sua forma funzionale per poter espletare tutte le funzioni vitali a partire da una cellula fecondata? Come questi processi interagiscono fra di loro attraverso le diverse scale biologiche, ovvero dalle cellule ai tessuti e viceversa? È possibile utilizzare le scoperte a questo riguardo per poter sviluppare terapie finalizzate a curare malformazioni e malattie dello sviluppo? In questo articolo, si illustreranno, dapprima, con una rassegna storica, la nascita dello studio dello sviluppo degli organismi da un punto di vista matematico quantitativo ed i diversi problemi da risolvere per rispondere alle domande sovracitate; verrà poi fornita una panoramica degli approcci tecnici fisico-matematici utilizzati nella biofisica della Morfogenesi e di come questi possano integrare e siano integrati con la scienza sperimentale; si concluderà infine con una discussione delle sfide a lungo termine, non solo tecniche ma anche di sviluppo di una comunità interdisciplinare conscia delle potenzialità, limiti e soprattutto complementarietà delle singole discipline e della sua fondamentale importanza per poter rispondere a domande fondamentali quali "Come si sviluppa la vita?"

    Noise Processing by MicroRNA-Mediated Circuits: the Incoherent Feed-Forward Loop, Revisited

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    The intrinsic stochasticity of gene expression is usually mitigated in higher eukaryotes by post-transcriptional regulation channels that stabilise the output layer, most notably protein levels. The discovery of small non-coding RNAs (miRNAs) in specific motifs of the genetic regulatory network has led to identifying noise buffering as the possible key function they exert in regulation. Recent in vitro} and in silico studies have corroborated this hypothesis. It is however also known that miRNA-mediated noise reduction is hampered by transcriptional bursting in simple topologies. Here, using stochastic simulations validated by analytical calculations based on van Kampen's expansion, we revisit the noise-buffering capacity of the miRNA-mediated Incoherent Feed Forward Loop (IFFL), a small module that is widespread in the gene regulatory networks of higher eukaryotes, in order to account for the effects of intermittency in the transcriptional activity of the modulator gene. We show that bursting considerably alters the circuit's ability to control static protein noise. By comparing with other regulatory architectures, we find that direct transcriptional regulation significantly outperforms the IFFL in a broad range of kinetic parameters. This suggests that, under pulsatile inputs, static noise reduction may be less important than dynamical aspects of noise and information processing in characterising the performance of regulatory elements.Comment: 25 pages (Main Text and Supplementary Information), 5 figure

    On the role of extrinsic noise in microRNA-mediated bimodal gene expression

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    Several studies highlighted the relevance of extrinsic noise in shaping cell decision making and differentiation in molecular networks. Bimodal distributions of gene expression levels provide experimental evidence of phenotypic differentiation, where the modes of the distribution often correspond to different physiological states of the system. We theoretically address the presence of bimodal phenotypes in the context of microRNA (miRNA)-mediated regulation. MiRNAs are small noncoding RNA molecules that downregulate the expression of their target mRNAs. The nature of this interaction is titrative and induces a threshold effect: below a given target transcription rate almost no mRNAs are free and available for translation. We investigate the effect of extrinsic noise on the system by introducing a fluctuating miRNA-transcription rate. We find that the presence of extrinsic noise favours the presence of bimodal target distributions which can be observed for a wider range of parameters compared to the case with intrinsic noise only and for lower miRNA-target interaction strength. Our results suggest that combining threshold-inducing interactions with extrinsic noise provides a simple and robust mechanism for obtaining bimodal populations without requiring fine tuning. Furthermore, we characterise the protein distribution’s dependence on protein half-life

    Stochastic sequestration dynamics: A minimal model with extrinsic noise for bimodal distributions and competitors correlation

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    Many biological processes are known to be based on molecular sequestration. This kind of dynamics involves two types of molecular species, namely targets and sequestrants, that bind to form a complex. In the simple framework of mass-action law, key features of these systems appear to be threshold-like profiles of the amounts of free molecules as a function of the parameters determining their possible maximum abundance. However, biochemical processes are probabilistic and take place in stochastically fluctuating environments. How these different sources of noise affect the final outcome of the network is not completely characterised yet. In this paper we specifically investigate the effects induced by a source of extrinsic noise onto a minimal stochastic model of molecular sequestration. We analytically show how bimodal distributions of the targets can appear and characterise them as a result of noise filtering mediated by the threshold response. We then address the correlations between target species induced by the sequestrant and discuss how extrinsic noise can turn the negative correlation caused by competition into a positive one. Finally, we consider the more complex scenario of competitive inhibition for enzymatic kinetics and discuss the relevance of our findings with respect to applications

    Friction forces position the neural anlage

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    During embryonic development, mechanical forces are essential for cellular rearrangements driving tissue morphogenesis. Here, we show that in the early zebrafish embryo, friction forces are generated at the interface between anterior axial mesoderm (prechordal plate, ppl) progenitors migrating towards the animal pole and neurectoderm progenitors moving in the opposite direction towards the vegetal pole of the embryo. These friction forces lead to global rearrangement of cells within the neurectoderm and determine the position of the neural anlage. Using a combination of experiments and simulations, we show that this process depends on hydrodynamic coupling between neurectoderm and ppl as a result of E-cadherin-mediated adhesion between those tissues. Our data thus establish the emergence of friction forces at the interface between moving tissues as a critical force-generating process shaping the embryo

    Modélisation et inférence de systèmes biologiques : de la dynamique de l’auxine dans les plantes aux séquences des protéines

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    All biological systems are made of atoms and molecules interacting in a non- trivial manner. Such non-trivial interactions induce complex behaviours allow- ing organisms to fulfill all their vital functions. These features can be found in all biological systems at different levels, from molecules and genes up to cells and tissues. In the past few decades, physicists have been paying much attention to these intriguing aspects by framing them in network approaches for which a number of theoretical methods offer many powerful ways to tackle systemic problems. At least two different ways of approaching these challenges may be considered: direct modeling methods and approaches based on inverse methods. In the context of this thesis, we made use of both methods to study three different problems occurring on three different biological scales. In the first part of the thesis, we mainly deal with the very early stages of tissue development in plants. We propose a model aimed at understanding which features drive the spontaneous collective behaviour in space and time of PINs, the transporters which pump the phytohormone auxin out of cells. In the second part of the thesis, we focus instead on the structural properties of proteins. In particular we ask how conservation of protein function across different organ- isms constrains the evolution of protein sequences and their diversity. Hereby we propose a new method to extract the sequence positions most relevant for protein function. Finally, in the third part, we study intracellular molecular networks that implement auxin signaling in plants. In this context, and using extensions of a previously published model, we examine how network structure affects network function. The comparison of different network topologies provides insights into the role of different modules and of a negative feedback loop in particular. Our introduction of the dynamical response function allows us to characterize the systemic properties of the auxin signaling when external stimuli are applied.Tous les systèmes biologiques sont formés d’atomes et de molécules qui interagissent et dont émergent des propriétés subtiles et complexes. Par ces interactions, les organismes vivants peuvent subvenir à toutes leurs fonctions vitales. Ces propriétés apparaissent dans tous les systèmes biologiques à des niveaux différents, du niveau des molécules et gènes jusqu’aux niveau des cellules et tissus. Ces dernières années, les physiciens se sont impliqués dans la compréhension de ces aspects particulièrement intrigants, en particulier en étudiant les systèmes vivants dans le cadre de la théorie des réseaux, théorie qui offre des outils d’analyse très puissants. Il est possible aujourd’hui d’identifier deux classes d’approches qui sont utilisée pour étudier ces types de systèmes complexes : les méthodes directes de modélisation et les approches inverses d’inférence. Dans cette thèse, mon travail est basé sur les deux types d’approches appliquées à trois niveaux de systèmes biologiques. Dans la première partie de la thèse, je me concentre sur les premières étapes du développement des tissus biologiques des plantes. Je propose un nouveau modèle pour comprendre la dynamique collective des transporteurs de l’hormone auxine et qui permet la croissance non-homogène des tissu dans l’espace et le temps. Dans la deuxième partie de la thèse, j’analyse comment l’évolution contraint la diversité́ de séquence des protéines tout en conservant leur fonction dans différents organismes. En particulier, je propose une nouvelle méthode pour inférer les sites essentiels pour la fonction ou la structure de protéines à partir d’un ensemble de séquences biologiques. Finalement, dans la troisième partie de la thèse, je travaille au niveau cellulaire et étudie les réseaux de signalisation associés à l’auxine. Dans ce contexte, je reformule un modèle préexistant et propose une nouvelle technique qui permet de définir et d’étudier la réponse du système aux signaux externes pour des topologies de réseaux différentes. J’exploite ce cadre théorique pour identifier le rôle fonctionnel de différentes topologies dans ces systèmes
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