Encoding folding paths of RNA switches

RNA co-transcriptional folding has long been suspected to play an active role in helping proper native folding of ribozymes and structured regulatory motifs in mRNA untranslated regions. Yet, the underlying mechanisms and coding requirements for efficient co-transcriptional folding remain unclear. Traditional approaches have intrinsic limitations to dissect RNA folding paths, as they rely on sequence mutations or circular permutations that typically perturb both RNA folding paths and equilibrium structures. Here, we show that exploiting sequence symmetries instead of mutations can circumvent this problem by essentially decoupling folding paths from equilibrium structures of designed RNA sequences. Using bistable RNA switches with symmetrical helices conserved under sequence reversal, we demonstrate experimentally that native and transiently formed helices can guide efficient co-transcriptional folding into either long-lived structure of these RNA switches. Their folding path is controlled by the order of helix nucleations and subsequent exchanges during transcription, and may also be redirected by transient antisense interactions. Hence, transient intra- and intermolecular base pair interactions can effectively regulate the folding of nascent RNA molecules into different native structures, provided limited coding requirements, as discussed from an information theory perspective. This constitutive coupling between RNA synthesis and RNA folding regulation may have enabled the early emergence of autonomous RNA-based regulation networks.Comment: 9 pages, 6 figure

Biomimetic emulsions reveal the effect of homeostatic pressure on cell-cell adhesion

Cell-cell contacts in tissues are continuously subject to mechanical forces due to homeostatic pressure and active cytoskeleton dynamics. While much is known about the molecular pathways of adhesion, the role of mechanics is less well understood. To isolate the role of pressure we present a dense packing of functionalized emulsion droplets in which surface interactions are tuned to mimic those of real cells. By visualizing the microstructure in 3D we find that a threshold compression force is necessary to overcome electrostatic repulsion and surface elasticity and establish protein-mediated adhesion. Varying the droplet interaction potential maps out a phase diagram for adhesion as a function of force and salt concentration. Remarkably, fitting the data with our theoretical model predicts binder concentrations in the adhesion areas that are similar to those found in real cells. Moreover, we quantify the adhesion size dependence on the applied force and thus reveal adhesion strengthening with increasing homeostatic pressure even in the absence of active cellular processes. This biomimetic approach reveals the physical origin of pressure-sensitive adhesion and its strength across cell-cell junctions.Comment: 20 pages, 5 figure

A lattice Boltzmann model with random dynamical constraints

In this paper we introduce a modified lattice Boltzmann model (LBM) with the capability of mimicking a fluid system with dynamic heterogeneities. The physical system is modeled as a one-dimensional fluid, interacting with finite-lifetime moving obstacles. Fluid motion is described by a lattice Boltzmann equation and obstacles are randomly distributed semi-permeable barriers which constrain the motion of the fluid particles. After a lifetime delay, obstacles move to new random positions. It is found that the non-linearly coupled dynamics of the fluid and obstacles produces heterogeneous patterns in fluid density and non-exponential relaxation of two-time autocorrelation function.Comment: 10 pages, 9 figures, to be published in Eur. Phys. J.

Tensorial Constitutive Models for Disordered Foams, Dense Emulsions, and other Soft Nonergodic Materials

In recent years, the paradigm of `soft glassy matter' has been used to describe diverse nonergodic materials exhibiting strong local disorder and slow mesoscopic rearrangement. As so far formulated, however, the resulting `soft glassy rheology' (SGR) model treats the shear stress in isolation, effectively `scalarizing' the stress and strain rate tensors. Here we offer generalizations of the SGR model that combine its nontrivial aging and yield properties with a tensorial structure that can be specifically adapted, for example, to the description of fluid film assemblies or disordered foams.Comment: 18 pages, 4 figure

Localized Joule heating produced by ion current focusing through micron-size holes

We provide an experimental demonstration that the focusing of ionic currents in a micron size hole connecting two chambers can produce local temperature increases of up to $100^\circ$ C with gradients as large as $1^\circ$ K$\mu m^{-1}$. We find a good agreement between the measured temperature profiles and a finite elements-based numerical calculation. We show how the thermal gradients can be used to measure the full melting profile of DNA duplexes within a region of 40 $\mu$m. The possibility to produce even larger gradients using sub-micron pores is discussed.Comment: 3 pages, accepted to Appl. Phys. Lett

Rejuvenation and overaging in a colloidal glass under shear

We report the modifications of the microscopic dynamics of a colloidal glass submitted to shear. We use multispeckle diffusing wave spectroscopy to monitor the evolution of the spontaneous slow relaxation processes after the sample have been submitted to various straining. We show that high shear rejuvenates the system and accelerates its dynamics whereas moderate shear overage the system. We analyze this phenomena within the frame of the Bouchaud's trap model.Comment: 4 pages, 4 figures, to be published in PR

Generalizable Denoising of Microscopy Images using Generative Adversarial Networks and Contrastive Learning

Microscopy images often suffer from high levels of noise, which can hinder further analysis and interpretation. Content-aware image restoration (CARE) methods have been proposed to address this issue, but they often require large amounts of training data and suffer from over-fitting. To overcome these challenges, we propose a novel framework for few-shot microscopy image denoising. Our approach combines a generative adversarial network (GAN) trained via contrastive learning (CL) with two structure preserving loss terms (Structural Similarity Index and Total Variation loss) to further improve the quality of the denoised images using little data. We demonstrate the effectiveness of our method on three well-known microscopy imaging datasets, and show that we can drastically reduce the amount of training data while retaining the quality of the denoising, thus alleviating the burden of acquiring paired data and enabling few-shot learning. The proposed framework can be easily extended to other image restoration tasks and has the potential to significantly advance the field of microscopy image analysis

Multispeckle diffusing-wave spectroscopy: a tool to study slow relaxation and time-dependent dynamics

A multispeckle technique for efficiently measuring correctly ensemble-averaged intensity autocorrelation functions of scattered light from non-ergodic and/or non-stationary systems is described. The method employs a CCD camera as a multispeckle light detector and a computer-based correlator, and permits the simultaneous calculation of up to 500 correlation functions, where each correlation function is started at a different time. The correlation functions are calculated in real time and are referenced to a unique starting time. The multispeckle nature of the CCD camera detector means that a true ensemble average is calculated; no time averaging is necessary. The technique thus provides a "snapshot" of the dynamics, making it particularly useful for non-stationary systems where the dynamics are changing with time. Delay times spanning the range from 1 ms to 1000 s are readily achieved with this method. The technique is demonstrated in the multiple scattering limit where diffusing-wave spectroscopy theory applies. The technique can also be combined with a recently-developed two-cell technique that can measure faster decay times. The combined technique can measure delay times from 10 ns to 1000 s. The method is peculiarly well suited for studying aging processes in soft glassy materials, which exhibit both short and long relaxation times, non-ergodic dynamics, and slowly-evolving transient behavior.Comment: 11 pages 13 figures Accepted in Review of Scientific Instrument (june 02