arXiv subjects

Pablo Sartori

Publications and source records attributed to Pablo Sartori.

At least 19 recordsLinked to original sources

arXiv2026

Resolving Speed and Encoding Bottlenecks in Fast Heteromeric Self-Assembly

The cytoplasm is a heterogeneous mixture containing many types of proteins that self-assemble into a wide variety of complexes. The accuracy and speed of cytoplasmic self-assembly is astonishing because it involves the correct identification of components shared among different structures, despite pervasive thermal fluctuations. Typical toy models of self-assembly are based on the specificity of binding energies among components. However, kinetics plays a key role in biological self-assembly, often catalyzed by a plethora of assembly factors. Building on this observation, we extend a previous heteropolymer growth model to describe the retrieval of two-dimensional structures via quasi-2D growth. We find that the self-assembly of structures in this model is subject to strong speed and encoding bottlenecks. Moreover, we show that these bottlenecks can be suppressed by increasing the connectivity of a small fraction of components. This mechanism of kinetically controlling a small number of critical binding events provides a simple explanation for the timely assembly of large protein, and suggests a unifying principle for the role of assembly factors.

cond-mat.stat-mech↗

arXiv2026

Metastable phase separation and information retrieval in multicomponent mixtures

Liquid mixtures can separate into phases with distinct composition. This phenomenon has recently come back to prominence due to its role in complex biological liquids, such as the cytoplasm, which contain thousands of components. For simple two-component mixtures phase-separated states are global free energy minima. However, local free energy minima, i.e. metastable states, are known to play a dominant role in complex systems with many components. For example, Hopfield neural networks can retrieve information from partial cues via relaxation to metastable states. Under what conditions can phase separated states be metastable, and what are the implications for information processing in multicomponent liquids? In this work we develop the general thermodynamic formalism of metastable phase separation. We then apply this formalism to an illustrative toy example inspired by recent experiments, binary mixtures with high-order interactions. Finally, as core application of the formalism, we study metastability in Hopfield liquids, a class of multicomponent mixtures capable of storing information on the composition of phases. We show that these phases can be retrieved from partial cues via metastable phase separation. Spatial simulations of liquids with a large number of components match our analytical solution. Our work suggests that complex biological mixtures can perform information retrieval through metastable phase separation.

cond-mat.stat-mech↗

arXiv2025

Content-Addressable Memory with a Content-Free Energy Function

Content-addressable memory, i.e. stored information that can be retrieved from content-based cues, is key to computation. Besides natural and artificial neural networks, physical learning systems have recently been shown to have remarkable ability in this domain. While classical neural network models encode memories as energy minima, biochemical systems have been shown to be able to process information based on purely kinetic principles. This opens the question of whether neural networks can also encode information kinetically. Here, we propose a minimal model for content-addressable memory in which the kinetics, and not the energy function, are used to encode patterns. We find that the performance of this kinetic encoding approach is comparable to that of classical energy-based encoding schemes. This highlights the fundamental significance of the kinetic stability of kinetic traps as an alternative to the thermodynamic stability of energy minima, offering new insights into the principles of computation in physical and synthetic systems.

cond-mat.stat-mech↗

arXiv2025

Charting dissipation across the microbial world

The energy dissipated by a living organism is commonly identified with heat generation. However, as cells exchange metabolites with their environment they also dissipate energy in the form of chemical entropy. How dissipation is distributed between exchanges of heat and chemical entropy is largely unexplored. Here, we analyze an extensive experimental database recently created [1] to investigate how microbes partition dissipation between thermal and chemical entropy during growth. We find that aerobic respiration exchanges little chemical entropy and dissipation is primarily due to heat production, as commonly assumed. However, we also find several types of anaerobic metabolism that produce as much chemical entropy as heat. Counterintuitively, instances of anaerobic metabolisms such as acetotrophic methanogenesis and sulfur respiration are endothermic. We conclude that, because of their metabolic versatility, microbes are able to exploit all combinations of heat and chemical entropy exchanges that result in a net production of entropy.

q-bio.OT↗

arXiv2024

High-Speed Combinatorial Polymerization through Kinetic-Trap Encoding

Like the letters in the alphabet forming words, reusing components of a heterogeneous mixture is an efficient strategy for assembling a large number of target structures. Examples range from synthetic DNA origami to proteins self-assembling into complexes. The standard self-assembly paradigm views target structures as free-energy minima of a mixture. While this is an appealing picture, at high speed structures may be kinetically trapped in local minima, reducing self-assembly accuracy. How then can high speed, high accuracy, and combinatorial usage of components coexist? We propose to reconcile these three concepts not by avoiding kinetic traps, but by exploiting them to encode target structures. This can be achieved by sculpting the kinetic pathways of the mixture, instead of its free-energy landscape. We formalize these ideas in a minimal toy model, for which we analytically estimate the encoding capacity and kinetic characteristics, in agreement with simulations. Our results may be generalized to other soft-matter systems capable of computation, such as liquid mixtures or elastic networks, and pave the way for high-dimensional information processing far from equilibrium.

cond-mat.stat-mech↗

arXiv2024

Liquid Hopfield model: retrieval and localization in multicomponent liquid mixtures

Biological mixtures, such as the cellular cytoplasm, are composed of a large number of different components. From this heterogeneity, ordered mesoscopic structures emerge, such as liquid phases with controlled composition. These structures compete with each other for the same components. This raises several questions, such as what types of interactions allow the retrieval of multiple ordered mesoscopic structures, and what are the physical limitations for the retrieval of said structures. In this work, we develop an analytically tractable model for liquids capable of retrieving states with target compositions. We name this model the liquid Hopfield model in reference to corresponding work in the theory of associative neural networks. By solving this model, we show that non-linear repulsive interactions are necessary for retrieval of target structures. We demonstrate that this is because liquid mixtures at low temperatures tend to transition to phases with few components, a phenomenon that we term localization. Taken together, our results demonstrate a trade-off between retrieval and localization phenomena in liquid mixtures.

physics.bio-ph↗

arXiv2022

Robust retrieval of dynamic sequences through interaction modulation

Many biological systems dynamically rearrange their components through a sequence of configurations in order to perform their functions. Such dynamic processes have been studied using network models that sequentially retrieve a set of stored patterns. Previous models of sequential retrieval belong to a general class in which the components of the system are controlled by a feedback ("input modulation"). In contrast, we introduce a new class of models in which the feedback modifies the interactions among the components ("interaction modulation"). We show that interaction modulation models are not only capable of retrieving dynamic sequences, but they do so more robustly than input modulation models. In particular, we find that modulation of symmetric interactions allows retrieval of patterns with different activity levels and has a much larger dynamic capacity. Our results suggest that interaction modulation may be a common principle underlying biological systems that show complex collective dynamics.

cond-mat.stat-mech↗

arXiv2021

Ciliary beating patterns map onto a low-dimensional behavioral space that accords with a simple mechanochemical model

Biological systems are robust to perturbations at both the genetic and environmental levels. Yet, these same perturbations can elicit variation in behavior. The interplay between functional robustness and behavioral variability is exemplified at the organellar level by the beating of cilia and flagella. The complex bending patterns of cilia emerge from the coordinated activities of hundreds of different proteins. Cilia are motile despite wide genetic diversity between and within species, large differences in intracellular concentrations of ATP and calcium, and considerable environment fluctuations in temperature and viscosity. At the same time, these perturbations result in a variety of spatio-temporal patterns that span a rich, and as of yet uncharted, behavioral space. To investigate this behavioral space we analyzed the dynamics of isolated cilia from the unicellular algae Chlamydomonas reinhardtii in thirty four different environmental and genetic conditions. We found that, despite large changes in beat frequency and amplitude, the space of waveform shapes is low-dimensional. Two features, parabolicity and asymmetry of the tangent angle, account for eighty per cent of the observed variation. Remarkably, the geometry of this behavioral space accords with the predictions of a simple mechanochemical model in the low viscosity regime. This allowed us to associate waveform shape variability with changes in only the curvature response coefficients of the dynein motors. Our work demonstrates that, despite the molecular complexity of the cilium, the space of beat variations is low dimensional and can be attributed to variation in mechanochemical regulation of the dynein motors.

physics.bio-ph↗

arXiv2019

Towards a theory of assembly of protein complexes: lessons from equilibrium statistical physics

Cellular functions are established through biological evolution, but are constrained by the laws of physics. For instance, the physics of protein folding limits the lengths of cellular polypeptide chains. Consequently, many cellular functions are carried out not by long, isolated proteins, but rather by multi-protein complexes. Protein complexes themselves do not escape physical constraints, one of the most important being the difficulty to assemble reliably in the presence of cellular noise. In order to lay the foundation for a theory of reliable protein complex assembly, we study here an equilibrium thermodynamic model of self-assembly that exhibits four distinct assembly behaviors: diluted protein solution, liquid mixture, "chimeric assembly" and "multifarious assembly". In the latter regime, different protein complexes can coexist without forming erroneous chimeric structures. We show that two conditions have to be fulfilled to attain this regime: (i) the composition of the complexes needs to be sufficiently heterogeneous, and (ii) the use of the set of components by the complexes has to be sparse. Our analysis of publicly available databases of protein complexes indicates that cellular protein systems might have indeed evolved so to satisfy both of these conditions.

physics.bio-ph↗

arXiv2019

Scaling behaviour of non-equilibrium planar $N$-atic spin systems under weak fluctuations

Starting from symmetry considerations, we derive the generic hydrodynamic equation of non-equilibrium $XY$ spin systems with $N$-atic symmetry under weak fluctuations. Through a systematic treatment we demonstrate that, in two dimensions, these systems exhibit two types of scaling behaviours. For $N=1$, they have long-range order and are described by the flocking phase of dry polar active fluids. For all other values of $N$, the systems exhibit quasi long-range order, as in the equilibrium $XY$ model at low temperature.

cond-mat.stat-mech↗

arXiv2019

Effect of curvature and normal forces on motor regulation of cilia

Cilia are ubiquitous organelles involves in eukaryotic motility. They are long, slender, and motile protrusions from the cell body. They undergo active regular oscillatory beating patterns that can propel cells, such as the algae Chlamydomonas, through fluids. When many cilia beat in synchrony they can also propel fluid along the surfaces of cells, as is the case of nodal cilia. The main structural elements inside the cilium are microtubules. There are also molecular motors of the dynein family that actively power the motion of the cilium. These motors transform chemical energy in the form of ATP into mechanical forces that produce sliding displacement between the microtubules. This sliding is converted to bending by constraints at the base and/or along the length of the cilium. Forces and displacements within the cilium can regulate dyneins and provide a feedback mechanism: the dyneins generate forces, deforming the cilium; the deformations, in turn, regulate the dyneins. This feedback is believed to be the origin of the coordination of dyneins in space and time which underlies the regularity of the beat pattern. Goals and approach. While the mechanism by which dyneins bend the cilium is understood, the feedback mechanism is much less clear. The two key questions are: which forces and displacements are the most relevant in regulating the beat? and how exactly does this regulation occur? In this thesis we develop a framework to describe the spatio-temporal patterns of a cilium with different mechanisms of motor regulation. Characterizing and comparing the predicted shapes and beat patterns of these different mechanisms to those observed in experiments provides us with further understanding on how dyneins are regulated. This comparison is done both, with a linear model that can be analytically solved, as with a non-linear model that we solve numerically.

q-bio.SC↗

arXiv2019

Geometry of environment-to-phenotype mapping: Unifying adaptation strategies in varying environments

Biological organisms exhibit diverse strategies for adapting to varying environments. For example, a population of organisms may express the same phenotype in all environments (`unvarying strategy'), or follow environmental cues and express alternative phenotypes to match the environment (`tracking strategy'), or diversify into coexisting phenotypes to cope with environmental uncertainty (`bet-hedging strategy'). We introduce a general framework for studying how organisms respond to environmental variations, which models an adaptation strategy by an abstract mapping from environmental cues to phenotypic traits. Depending on the accuracy of environmental cues and the strength of natural selection, we find different adaptation strategies represented by mappings that maximize the longterm growth rate of a population. The previously studied strategies emerge as special cases of our model: the tracking strategy is favorable when environmental cues are accurate, whereas when cues are noisy, organisms can either use an unvarying strategy or, remarkably, use the uninformative cue as a source of randomness to bet-hedge. Our model of the environment-to-phenotype mapping is based on a network with hidden units; the performance of the strategies is shown to rely on having a high-dimensional internal representation, which can even be random.

q-bio.PE↗

arXiv2018

On the nonequilibrium entropy of large and small systems

Thermodynamics makes definite predictions about the thermal behavior of macroscopic systems in and out of equilibrium. Statistical mechanics aims to derive this behavior from the dynamics and statistics of the atoms and molecules making up these systems. A key element in this derivation is the large number of microscopic degrees of freedom of macroscopic systems. Therefore, the extension of thermodynamic concepts, such as entropy, to small (nano) systems raises many questions. Here we shall reexamine various definitions of entropy for nonequilibrium systems, large and small. These include thermodynamic (hydrodynamic), Boltzmann, and Gibbs-Shannon entropies. We shall argue that, despite its common use, the last is not an appropriate physical entropy for such systems, either isolated or in contact with thermal reservoirs: physical entropies should depend on the microstate of the system, not on a subjective probability distribution. To square this point of view with experimental results of Bechhoefer we shall argue that the Gibbs-Shannon entropy of a nano particle in a thermal fluid should be interpreted as the Boltzmann entropy of a dilute gas of Brownian particles in the fluid.

cond-mat.stat-mech↗

arXiv2016

Protocols for copying and proofreading in template-assisted polymerization

We discuss how information encoded in a template polymer can be stochastically copied into a copy polymer. We consider four different stochastic copy protocols of increasing complexity, inspired by building blocks of the mRNA translation pathway. In the first protocol, monomer incorporation occurs in a single stochastic transition. We then move to a more elaborate protocol in which an intermediate step can be used for error correction. Finally, we discuss the operating regimes of two kinetic proofreading protocols: one in which proofreading acts from the final copying step, and one in which it acts from an intermediate step. We review known results for these models and, in some cases, extend them to analyze all possible combinations of energetic and kinetic discrimination. We show that, in each of these protocols, only a limited number of these combinations leads to an improvement of the overall copying accuracy.

q-bio.SC↗

arXiv2015

Thermodynamics of Error Correction

Information processing at the molecular scale is limited by thermal fluctuations. This can cause undesired consequences in copying information since thermal noise can lead to errors that can compromise the functionality of the copy. For example, a high error rate during DNA duplication can lead to cell death. Given the importance of accurate copying at the molecular scale, it is fundamental to understand its thermodynamic features. In this paper, we derive a universal expression for the copy error as a function of entropy production and {\cred work dissipated by the system during wrong incorporations}. Its derivation is based on the second law of thermodynamics, hence its validity is independent of the details of the molecular machinery, be it any polymerase or artificial copying device. Using this expression, we find that information can be copied in three different regimes. In two of them, work is dissipated to either increase or decrease the error. In the third regime, the protocol extracts work while correcting errors, reminiscent of a Maxwell demon. As a case study, we apply our framework to study a copy protocol assisted by kinetic proofreading, and show that it can operate in any of these three regimes. We finally show that, for any effective proofreading scheme, error reduction is limited by the chemical driving of the proofreading reaction.

q-bio.SC↗

arXiv2015

Beat regulation in twisted axonemes

Cilia and flagella are hairlike organelles that propel cells through fluid. The active motion of the axoneme, the motile structure inside cilia and flagella, is powered by molecular motors of the dynein family. These motors generate forces and torques that slide and bend the microtubule doublets within the axoneme. To create regular waveforms the activities of the dyneins must be coordinated. It is thought that coordination is mediated by stresses due to radial, transverse, or sliding deformations, that build up within the moving axoneme. However, which particular component of the stress regulates the motors to produce the observed flagellar waveforms remains an open question. To address this question, we describe the axoneme as a three-dimensional bundle of filaments and characterize its mechanics. We show that regulation of the motors by radial and transverse stresses can lead to a coordinated flagellar motion only in the presence of twist. By comparison, regulation by shear stress is possible without twist. We calculate emergent beating patterns in twisted axonemes resulting from regulation by transverse stresses. The waveforms are similar to those observed in flagella of Chlamydomonas and sperm. Due to the twist, the waveform has non-planar components, which result in swimming trajectories such as twisted ribbons and helices that agree with observations.

q-bio.SC↗

arXiv2015

Dynamic curvature regulation accounts for the symmetric and asymmetric beats of Chlamydomonas flagella

Axonemal dyneins are the molecular motors responsible for the beating of cilia and flagella. These motors generate sliding forces between adjacent microtubule doublets within the axoneme, the motile cytoskeletal structure inside the flagellum. To create regular, oscillatory beating patterns, the activities of the axonemal dyneins must be coordinated both spatially and temporally. It is thought that coordination is mediated by stresses or strains that build up within the moving axoneme, but it is not known which components of stress or strain are involved, nor how they feed back on the dyneins. To answer this question, we used isolated, reactivate axonemes of the unicellular alga Chlamydomonas as a model system. We derived a theory for beat regulation in a two-dimensional model of the axoneme. We then tested the theory by measuring the beat waveforms of wild type axonemes, which have asymmetric beats, and mutant axonemes, in which the beat is nearly symmetric, using high-precision spatial and temporal imaging. We found that regulation by sliding forces fails to account for the measured beat, due to the short lengths of Chlamydomonas cilia. We found that regulation by normal forces (which tend to separate adjacent doublets) cannot satisfactorily account for the symmetric waveforms of the mbo2 mutants. This is due to the model's failure to produce reciprocal inhibition across the axes of the symmetrically beating axonemes. Finally, we show that regulation by curvature accords with the measurements. Unexpectedly, we found that the phase of the curvature feedback indicates that the dyneins are regulated by the dynamic (i.e. time-varying) component of axonemal curvature, but not by the static one. We conclude that a high-pass filtered curvature signal is a good candidate for the signal that feeds back to coordinate motor activity in the axoneme.

physics.bio-ph↗

arXiv2015

The free energy cost of reducing noise while maintaining a high sensitivity

Living systems need to be highly responsive, and also to keep fluctuations low. These goals are incompatible in equilibrium systems due to the Fluctuation Dissipation Theorem (FDT). Here, we show that biological sensory systems, driven far from equilibrium by free energy consumption, can reduce their intrinsic fluctuations while maintaining high responsiveness. By developing a continuum theory of the E. coli chemotaxis pathway, we demonstrate that adaptation can be understood as a non-equilibrium phase transition controlled by free energy dissipation, and it is characterized by a breaking of the FDT. We show that the maximum response at short time is enhanced by free energy dissipation. At the same time, the low frequency fluctuations and the adaptation error decrease with the free energy dissipation algebraically and exponentially, respectively.

physics.bio-ph↗