Performance of single nanopore and multi-pore membranes for blue energy.

The salinity gradient power extracted from the mixing of electrolyte solutions at dierent concentrations through selective nanoporous membranes is a promising route to renewable energy. However, several challenges need to be addressed to make this technology protable, one of the most relevant being the increase of the extractable power per membrane area. Here, the performance of asymmetric conical and bullet-shaped nanopores in a 50 nm thick membrane are studied via electrohydrodynamic simulations, varying the pore radius, curvature, and surface charge. The output power reaches ∼ 60 pW per pore for positively charged membranes (surface charge σw =160 mC/m2 ) and ∼ 30 pW for negatively charges ones, σw =-160 mC/m2 and it is robust to minor variations of nanopore shape and radius. A theoretical argument that takes into account the interaction among neighbour pores allows to extrapolate the single-pore performance to multi-pore membranes showing that power densities from tens to hundreds of W/m2 can be reached by proper tuning of the nanopore number density and the boundary layer thickness. Our model for scaling single-pore performance to multi-pore membrane can be applied also to experimental data providing a simple tool to effectively compare different nanopore membranes in blue energy applications.

Correlation, response and entropy approaches to allosteric behaviors: a critical comparison on the ubiquitin case.

Correlation analysis and its close variant principal component analysis are tools widely applied to predict the biological functions of macromolecules in terms of the relationship between fluctuation dynamics and structural properties. However, since this kind of analysis does not necessarily imply causation links among the elements of the system, its results run the risk of being biologically misinterpreted. By using as a benchmark the structure of ubiquitin, we report a critical comparison of correlation-based analysis with the analysis performed using two other indicators, response function and transfer entropy, that quantify the causal dependence. The use of ubiquitin stems from its simple structure and from recent experimental evidence of an allosteric control of its binding to target substrates. We discuss the ability of correlation, response and transfer-entropy analysis in detecting the role of the residues involved in the allosteric mechanism of ubiquitin as deduced by experiments. To maintain the comparison as much as free from the complexity of the modeling approach and the quality of time series, we describe the fluctuations of ubiquitin native state by the Gaussian network model which, being fully solvable, allows one to derive analytical expressions of the observables of interest. Our comparison suggests that a good strategy consists in combining correlation, response and transfer entropy, such that the preliminary information extracted from correlation analysis is validated by the two other indicators in order to discard those spurious correlations not associated with true causal dependencies.

Universal and Non-Universal Features in the Random Shear Model.

The stochastic transport of particles in a disordered two-dimensional layered medium, driven by correlated y-dependent random velocity fields is usually referred to as random shear model. This model exhibits a superdiffusive behavior in the x direction ascribable to the statistical properties of the disorder advection field. By introducing layered random amplitude with a power-law discrete spectrum, the analytical expressions for the space and time velocity correlation functions, together with those of the position moments, are derived by means of two distinct averaging procedures. In the case of quenched disorder, the average is performed over an ensemble of uniformly spaced initial conditions: albeit the strong sample-to-sample fluctuations, and universality appears in the time scaling of the even moments. Such universality is exhibited in the scaling of the moments averaged over the disorder configurations. The non-universal scaling form of the no-disorder symmetric or asymmetric advection fields is also derived.

Correlated escape of active particles across a potential barrier.

We study the dynamics of one-dimensional active particles confined in a double-well potential, focusing on the escape properties of the system, such as the mean escape time from a well. We first consider a single-particle both in near and far-from-equilibrium regimes by varying the persistence time of the active force and the swim velocity. A non-monotonic behavior of the mean escape time is observed with the persistence time of the activity, revealing the existence of an optimal choice of the parameters favoring the escape process. For small persistence times, a Kramers-like formula with an effective potential obtained within the unified colored noise approximation is shown to hold. Instead, for large persistence times, we developed a simple theoretical argument based on the first passage theory, which explains the linear dependence of the escape time with the persistence of the active force. In the second part of the work, we consider the escape on two active particles mutually repelling. Interestingly, the subtle interplay of active and repulsive forces may lead to a correlation between particles, favoring the simultaneous jump across the barrier. This mechanism cannot be observed in the escape process of two passive particles. Finally, we find that in the small persistence regime, the repulsion favors the escape, such as in passive systems, in agreement with our theoretical predictions, while for large persistence times, the repulsive and active forces produce an effective attraction, which hinders the barrier crossing.

How a local active force modifies the structural properties of polymers.

We study the dynamics of a polymer, described as a variant of a Rouse chain, driven by an active terminal monomer (head). The local active force induces a transition from a globule-like to an elongated state, as revealed by the study of the end-to-end distance, the variance of which is analytically predicted under suitable approximations. The change in the relaxation times of the Rouse-modes produced by the local self-propulsion is consistent with the transition from globule to elongated conformations. Moreover, also the bond-bond spatial correlation for the chain head are affected by the self-propulsion and a gradient of over-stretched bonds along the chain is observed. We compare our numerical results both with the phenomenological stiff-polymer theory and several analytical predictions in the Rouse-chain approximation.

Diffusion properties of self-propelled particles in cellular flows.

We study the dynamics of a self-propelled particle advected by a steady laminar flow. The persistent motion of the self-propelled particle is described by an active Ornstein-Uhlenbeck process. We focus on the diffusivity properties of the particle as a function of persistence time and free-diffusion coefficient, revealing non-monotonic behaviors, with the occurrence of a minimum and a steep growth in the regime of large persistence time. In the latter limit, we obtain an analytical prediction for the scaling of the diffusion coefficient with the parameters of the active force. Our study sheds light on the effect of a flow-field on the diffusion of active particles, such as living microorganisms and motile phytoplankton in fluids.

DCA for genome-wide epistasis analysis: the statistical genetics perspective.

Direct coupling analysis (DCA) is a now widely used method to leverage statistical information from many similar biological systems to draw meaningful conclusions on each system separately. DCA has been applied with great success to sequences of homologous proteins, and also more recently to whole-genome population-wide sequencing data. We here argue that the use of DCA on the genome scale is contingent on fundamental issues of population genetics. DCA can be expected to yield meaningful results when a population is in the quasi-linkage equilibrium (QLE) phase studied by Kimura and others, but not, for instance, in a phase of clonal competition. We discuss how the exponential (Potts model) distributions emerge in QLE, and compare couplings to correlations obtained in a study of about 3000 genomes of the human pathogen Streptococcus pneumoniae.

Transport of active particles in an open-wedge channel.

The transport of independent active Brownian particles within a two-dimensional narrow channel, modeled as an open-wedge, is studied both numerically and theoretically. We show that the active force tends to localize the particles near the walls, thus reducing the effect of the entropic force which, instead, is prevailing in the case of passive particles. As a consequence, the exit of active particles from the smaller side of the channel is facilitated with respect to their passive counterpart. By continuously re-injecting particles in the middle of the wedge, we obtain a steady regime whose properties are investigated in the presence and absence of an external constant driving field. We characterize the statistics and properties of the exit process from the two opposite sides of the channel, also by making a comparison between the active case and passive case. Our study reveals the existence of an optimal value of the persistence time of the active force which is able to guarantee the maximal efficiency in the transport process.

The Role of Data in Model Building and Prediction: A Survey Through Examples.

The goal of Science is to understand phenomena and systems in order to predict their development and gain control over them. In the scientific process of knowledge elaboration, a crucial role is played by models which, in the language of quantitative sciences, mean abstract mathematical or algorithmical representations. This short review discusses a few key examples from Physics, taken from dynamical systems theory, biophysics, and statistical mechanics, representing three paradigmatic procedures to build models and predictions from available data. In the case of dynamical systems we show how predictions can be obtained in a virtually model-free framework using the methods of analogues, and we briefly discuss other approaches based on machine learning methods. In cases where the complexity of systems is challenging, like in biophysics, we stress the necessity to include part of the empirical knowledge in the models to gain the minimal amount of realism. Finally, we consider many body systems where many (temporal or spatial) scales are at play-and show how to derive from data a dimensional reduction in terms of a Langevin dynamics for their slow components.

Frequency-control of protein translocation across an oscillating nanopore.

The translocation of a lipid binding protein (LBP) is studied using a phenomenological coarse-grained computational model that simplifies both chain and pore geometry. We investigated via molecular dynamics the interplay between transport and unfolding in the presence of a nanopore whose section oscillates periodically in time with a frequency ω, a motion often referred to as the radial breathing mode (RBM). We found that the LPB when mechanically pulled into the vibrating nanopore exhibits a translocation dynamics that in some frequency range is accelerated and shows a frequency locking to the pore dynamics. The main effect of pore vibrations is the suppression of stalling events of the translocation dynamics, hence, proper frequency tuning allows both regularization and control of the overall transport process. Finally, the interpretation of the simulation results is easily achieved by resorting to a first passage theory of elementary driven-diffusion processes.

Driven diffusion against electrostatic or effective energy barrier across α-hemolysin.

We analyze the translocation of a charged particle across an α-Hemolysin (αHL) pore in the framework of a driven diffusion over an extended energy barrier generated by the electrical charges of the αHL. A one-dimensional electrostatic potential is extracted from the full 3D solution of the Poisson's equation. We characterize the particle transport under the action of a constant forcing by studying the statistics of the translocation time. We derive an analytical expression of translocation time average that compares well with the results from Brownian dynamic simulations of driven particles over the electrostatic potential. Moreover, we show that the translocation time distributions can be perfectly described by a simple theory which replaces the true barrier by an equivalent structureless square barrier. Remarkably, our approach maintains its accuracy also for low-applied voltage regimes where the usual inverse-Gaussian approximation fails. Finally, we discuss how the comparison between the simulated time distributions and their theoretical prediction results to be greatly simplified when using the notion of the empirical Laplace transform technique.

Coarse-grained modeling of protein unspecifically bound to DNA.

There is now a certain consensus that transcription factors (TFs) reach their target sites, where they regulate gene transcription, via a mechanism dubbed facilitated diffusion (FD). In FD, the TF cycles between events of 3D diffusion in solution (jumps), 1D diffusion along DNA (sliding), and small jumps (hopping), achieving association rates higher than for 3D diffusion alone. We investigate the FD phenomenology through molecular dynamics simulations in the framework of coarse-grained modeling. We show that, despite the crude approximations, the model generates, upon varying the equilibrium distance of the DNA-TF interaction, a phenomenology matching a number of experimental and numerical results obtained with more refined models. In particular, focusing on the kinematics of the process, we characterize the geometrical properties of TF trajectories during sliding. We find that sliding occurs via helical paths around the DNA helix, leading to a coupling of translation along the DNA axis with rotation around it. The 1D diffusion constant measured in simulations is found to be interwoven with the geometrical properties of sliding and we develop a simple argument that can be used to quantitatively reproduce the measured values.

Surface-particle interactions control the escape time of a particle from a nanopore-gated nanocavity system: a coarse grained simulation.

Nanopores and nanocavities are promising single molecule tools for investigating the behavior of individual molecules within confined spaces. For single molecule analysis, the total duration of time the analyte remains within the pore/cavity is highly important. However, this dwell time is ruled by a complex interplay among particle-surface interactions, external forces on the particle and Brownian diffusion, making the prediction of the dwell time challenging. Here, we show how the dwell time of an analyte in a nanocavity that is connected to the external environment by two nanopore gates depends on the sizes of the nanocavity/nanopore, as well as particle-wall interactions. For this purpose, we used a coarse-grained model that allowed us to simulate hundreds of individual analyte trajectories within a nanocavity volume. We found that by increasing the attraction between the particle and the wall, the diffusion process transforms from a usual 3D scenario (repulsive wall) to a 2D motion along the cavity surface (highly attractive wall). This results in a significant reduction of the average dwell time. Additionally, the comparison of our results with existing theories on narrow escape problem allowed us to quantify the reliability of theory derived for ideal conditions to geometries more similar to actual devices.

Extracting causation from millennial-scale climate fluctuations in the last 800 kyr.

The detection of cause-effect relationships from the analysis of paleoclimatic records is a crucial step to disentangle the main mechanisms at work in the climate system. Here, we show that the approach based on the generalized Fluctuation-Dissipation Relation, complemented by the analysis of the Transfer Entropy, allows the causal links to be identified between temperature, CO[Formula: see text] concentration and astronomical forcing during the glacial cycles of the last 800 kyr based on Antarctic ice core records. When considering the whole spectrum of time scales, the results of the analysis suggest that temperature drives CO[Formula: see text] concentration, or that are both driven by the common astronomical forcing. However, considering only millennial-scale fluctuations, the results reveal the presence of more complex causal links, indicating that CO[Formula: see text] variations contribute to driving the changes of temperature on such time scales. The results also evidence a slow temporal variability in the strength of the millennial-scale causal links between temperature and CO[Formula: see text] concentration.

DNA compaction and dynamic observation in a nanopore gated sub-attoliter silicon nanocavity.

Confinement of biopolymers inside volumes with micro- or nanoscale lateral dimensions is ubiquitous in nature. Investigating the behavior of biopolymers in a confined environment is essential to improve our basic understanding in life sciences. In this work, we present a nanopore gated sub-attoliter silicon nanocavity device, which allows DNA compaction similar to that in virus capsids. Single DNA molecules can be electrically driven into the nanocavity, and then get compacted inside the nanocavity under certain conditions. The dynamic fluctuations of the compacted DNA can be monitored via ionic current measurements. The mechanism for the DNA compaction is elucidated by varying the DNA length or concentration, voltage polarity, nanocavity dimensions and ionic strength. Furthermore, Brownian dynamics simulations reveal the dynamic fluctuations of the compacted DNA, which are reflected in the measured ionic current. Our nanocavity device is anticipated to provide a controlled environment in extremely small volumes for investigating the physics of confined biopolymers.

Native-state fingerprint on the ubiquitin translocation across a nanopore.

We study the translocation of the ubiquitin molecule (Ubq) across a channel with a double section which constitutes a general feature of several transmembrane nanopores such as the α-hemolysin (αHL). Our purpose is to establish the structure-dependent character of the Ubq translocation pathway. This implies to find the correspondence, if any, between the translocational unfolding steps and the Ubq native state. For this reason, it is convenient to apply a coarse-grained computational approach, where the protein is described only by the backbone and the force field only exploits the information contained in the native state (in the spirit of Go-like models, or native-centric models). The αHL-like pore is portrayed as two coaxial confining cylinders: a larger one for the vestibule and a narrower one for the barrel (or stem). Such simplified approach allows a large number of translocation events to be collected by limited computational resources. The co-translocational unfolding of Ubq is described via a few collective variables that characterize the translocation progress. We find two translocation intermediates (stalled conformations) that can be associated with specific unfolding stages. In particular, in the earliest step, the strand S5 unfolds and enters the pore. This step splits the native conformation into two structural clusters packing against each other in the Ubq fold. A second stall occurs when the hairpin of the N terminal engages the stem region.

Analytical Model for Particle Capture in Nanopores Elucidates Competition among Electrophoresis, Electroosmosis, and Dielectrophoresis.

The interaction between nanoparticles dispersed in a fluid and nanopores is governed by the interplay of hydrodynamical, electrical, and chemical effects. We developed a theory for particle capture in nanopores and derived analytical expressions for the capture rate under the concurrent action of electrical forces, fluid advection, and Brownian motion. Our approach naturally splits the average capture time in two terms, an approaching time due to the migration of particles from the bulk to the pore mouth and an entrance time associated with a free-energy barrier at the pore entrance. Within this theoretical framework, we described the standard experimental condition where a particle concentration is driven into the pore by an applied voltage, with specific focus on different capture mechanisms: under pure electrophoretic force, in the presence of a competition between electrophoresis and electroosmosis, and finally under dielectrophoretic reorientation of dipolar particles. Our theory predicts that dielectrophoresis is able to induce capture for both positive and negative voltages. We performed a dedicated experiment involving a biological nanopore (α-hemolysin) and a rigid dipolar dumbbell (realized with a ß-hairpin peptide) that confirms the theoretically proposed capture mechanism.

A statistical model for translocation of structured polypeptide chains through nanopores.

The translocation process of a globular protein (ubiquitin) across a cylindrical nanopore is studied via molecular dynamics simulations. The ubiquitin is described by a native-centric model on a Calpha carbon backbone to investigate the influence of protein-like structural properties on the translocation mechanism. A thermodynamical and kinetic characterization of the process is obtained by studying the statistics of blockage times, the mobility, and the translocation probability as a function of the pulling force F acting in the pore. The transport dynamics occurs when the force exceeds a threshold Fc depending on a free-energy barrier that ubiquitin has to overcome in order to slide along the channel. Such a barrier results from competition of the unfolding energy and the entropy associated with the confinement effects of the pore. We implement appropriate umbrella sampling simulations to compute the free-energy profile as a function of the position of the ubiquitin center of mass inside of the channel (reaction coordinate). This free energy is then used to construct a phenomenological drift-diffusion model in the reaction coordinate which explains and reproduces the behavior of the observables during the translocation.

Translocation intermediates of ubiquitin through an α-hemolysin nanopore: implications for detection of post-translational modifications.

Nanopore based sensors constitute a promising approach to single molecule protein characterization being able, in principle, to detect sequences, structural elements and folding states of proteins and polypeptide chains. In narrow nanopores, one of the open issues concerns the coupling between unfolding and translocation. Here, we studied the ubiquitin translocation in an α-hemolysin nanopore, the most widely used pore for nanopore sensing, via all-atom molecular dynamics simulations. We completely characterize the co-translocational unfolding pathway finding that robust translocation intermediates are associated with the rearrangement of secondary structural elements, as also confirmed by coarse grained simulations. An interesting recurrent pattern is the clogging of the α-hemolysin constriction by an N-terminal ß-hairpin. This region of ubiquitin is the target of several post-translational modifications. We propose a strategy to detect post-translational modifications at the N-terminal using the α-hemolysin nanopore based on the comparison of the co-translocational unfolding signals associated with modified and unmodified proteins.