Biophysics seminars

A key challenge in modern soft matter is to identify the principles that govern the organisation and functionality in non-equilibrium systems. Current research efforts largely focus on non-equilibrium processes that occur either at the single-molecule scale (e.g. protein and DNA conformations under driving forces), or at the scale of whole tissues, organisms, and active colloidal and microscopic objects. However, the range of the scales in-between — from molecules to large-scaled molecular assemblies that consume energy and perform work — remains under-explored. This is, nevertheless, the scale that is crucial for the function of a living cell, where molecular self-assembly driven far from equilibrium produces mechanical work needed for cell reshaping, transport, motility, division, and healing. Today I will discuss physical modelling of active elastic filaments, called ESCRT-III filaments, that dynamically assemble and disassemble on cell membranes. This dynamic assembly changes the filaments’ shape and mechanical properties and leads to the remodelling and cutting of cells. I will present a range of experimental comparisons of our simulation results: from ESCRT-III-driven trafficking in eukaryotes to division of evolutionary simple archaeal cells.

In 1676, using candle light and a small glass sphere as the lens, van Leeuwenhoek discovered the microscopic world of living microorganisms. Today, using lasers, spatial light modulators, digital cameras and computers, we study the statistical and fluid mechanics of microswimmers in ways that were unimaginable only 50 years ago. With light we can image swimming bacteria in 3D, apply controllable force fields or sculpt their 3D environment. In addition to shaping the physical world outside cells we can use light to control the internal state of genetically modified bacteria. I will review our recent work with light-bacteria interactions, going from some fundamental problems in the fluid and statistical mechanics of microswimmers to the use of bacteria as propellers for micro-machines or as a "living" paint controlled by light.

Biomolecular condensation is a mechanism for controlling cell organization. Many condensates are rich in nuclei acids such as RNA. The role of specific RNA sequences and structures in promoting the molecular identity of condensates formed for cell polarity and division and by the SARS CoV-2 virus will be discussed.

A wealth of experimental studies show that the trial-to-trial variability of neuronal activity is quenched during stimulus evoked responses. This fact has helped ground a popular view that the variability of spiking activity can be decomposed into two components. The first is due to irregular spike timing conditioned on the firing rate of a neuron (i.e. a Poisson process), and the second is the trial-to-trial variability of the firing rate itself. Quenching of the variability of the overall response is assumed to be a reflection of a suppression of firing rate variability. Network models have explained this phenomenon through a variety of circuit mechanisms. However, in all cases, from the vantage of a neuron embedded within the network, quenching of its response variability is inherited from its synaptic input. We analyze in vivo whole cell recordings from principal cells in layer (L) 2/3 of mouse visual cortex. While the variability of the membrane potential is quenched upon stimulation, the variability of excitatory and inhibitory currents afferent to the neuron are amplified. This discord complicates the simple inheritance assumption that underpins network models of neuronal variability. We propose and validate an alternative (yet not mutually exclusive) mechanism for the quenching of neuronal variability. We show how an increase in synaptic conductance in the evoked state shunts the transfer of current to the membrane potential, formally decoupling changes in their trial-to-trial variability. The ubiquity of conductance based neuronal transfer combined with the simplicity of our model, provides an appealing framework. In particular, it shows how the dependence of cellular properties upon neuronal state is a critical, yet often ignored, factor. Further, our mechanism does not require a decomposition of variability into spiking and firing rate components, thereby challenging a long held view of neuronal activity.

Our group is interested in discovering design principles that govern the structure and function of neurons and neural circuits. We record from well-defined neurons, mainly in flies’ visual systems, to measure the molecular and cellular factors that determine relevant measures of performance, such as representational capacity, dynamic range and accuracy. We combine this empirical approach with modelling to see how the basic elements of neural systems (ion channels, second messengers systems, membranes, synapses, neurons, circuits and codes) combine to determine performance. We are investigating four general problems. How are circuits designed to integrate information efficiently? How do sensory adaptation and synaptic plasticity contribute to efficiency? How do the sizes of neurons and networks relate to energy consumption and representational capacity? To what extent have energy costs shaped neurons, sense organs and brain regions during evolution?

The remarkable properties of information-processing of biological and of artificial neuronal networks alike arise from the interaction of large numbers of neurons. A central quest is thus to characterize their collective states. The directed coupling between pairs of neurons and their continuous dissipation of energy, moreover, cause dynamics of neuronal networks outside thermodynamic equilibrium. Tools from non-equilibrium statistical mechanics and field theory are thus instrumental to obtain a quantitative understanding. We here present progress with this recent approach [1]. On the experimental side, we show how correlations between pairs of neurons are informative on the dynamics of cortical networks: they are poised near a transition to chaos [2]. Close to this transition, we find prolongued sequential memory for past signals [3]. In the chaotic regime, networks offer representations of information whose dimensionality expands with time. We show how this mechanism aids classification performance [4]. Together these works illustrate the fruitful interplay between theoretical physics, neuronal networks, and neural information processing.

Much of the science underpinning the global response to the COVID-19 pandemic lies in the soft matter domain. Coronaviruses are composite particles with a core of nucleic acids complexed to proteins surrounded by a protein-studded lipid bilayer shell. A dominant route for transmission is via air-borne aerosols and droplets. Viral interaction with polymeric body fluids, particularly mucus, and cell membranes controls their infectivity, while their interaction with skin and artificial surfaces underpins cleaning and disinfection and the efficacy of masks and other personal protective equipment. The global response to COVID-19 has highlighted gaps in the soft matter knowledge base. I will survey these gaps, especially as pertaining to the transmission of the disease, and suggest questions that can (and need to) be tackled, both in response to COVID-19 and to better prepare for future viral pandemics.

Neural networks can learn and recognize subtle correlations in high dimensional inputs. However, neural networks are simply many-body systems with strong non-linearities and disordered interactions. Hence, many-body physical systems with similar interactions should be able to show neural network-like behavior. Here we show neural network-like behavior in the nucleation dynamics of promiscuously interacting molecules with multiple stable crystalline phases. Using a combination of theory and experiments, we show how the physics of the system dictates relationships between the difficulty of the pattern recognition task solved, time taken and accuracy. This work shows that high dimensional pattern recognition and learning are not special to software algorithms but can be achieved by the collective dynamics of sufficiently disordered molecular systems.

Electric Gymnotiform fish live in muddy, shallow waters near the shore – hiding in the dense filamentous roots of floating plants such as Eichornia crassipes (“camalote”). They explore their surroundings by using a series of electric pulses that serve as self emitted carrier of electrosensory signals. This propagates at the speed of light through this spongiform habitat and is barely sensed by the lateral line of predators and prey. The emitted field polarizes the surroundings according to the difference in impedance with water which in turn modifies the profile of transcutaneous currents considered as an electrosensory image. Using this system, pulse Gymnotiformes create an electrosensory bubble where an object’s location, impedance, size and other characteristics are discriminated and probably recognized. Although consciousness is still not well-proven, cognitive functions as volition, attention, and path integration have been shown. Here I will summarize different aspects of the electromotor electrosensory loop of pulse Gymnotiforms. First, I will address how objects are polarized with a stereotyped but temporospatially complex electric field, consisting of brief pulses emitted at regular intervals. This relies on complex electric organs quasi periodically activated through an electromotor coordination system by a pacemaker in the medulla. Second, I will deal with the imaging mechanisms of pulse gymnotiform fish and the presence of two regions in the electrosensory field, a rostral region where the field time course is coherent and field vector direction is constant all along the electric organ discharge and a lateral region where the field time course is site specific and field vector direction describes a stereotyped 3D trajectory. Third, I will describe the electrosensory mosaic and their characteristics. Receptor and primary afferents correspond one to one showing subtypes optimally responding to the time course of the self generated pulse with a characteristic train of spikes. While polarized objects at the rostral region project their electric images on the perioral region where electrosensory receptor density, subtypes and central projection are maximal, the image of objects on the side recruit a single type of scattered receptors. Therefore, the rostral mosaic has been likened to an electrosensory fovea and its receptive field referred to as foveal field. The rest of the mosaic and field are referred to as peripheral. Finally, I will describe ongoing work on early processing structures. I will try to generate an integrated view, including anatomical and functional data obtained in vitro, acute experiments, and unitary recordings in freely moving fish. We have recently shown have shown that these fish tract allo-generated fields and the virtual fields generated by nearby objects in the presence of self-generated fields to explore the nearby environment. These data together with the presence of a multimodal receptor mosaic at the cutaneous surface particularly surrounding the mouth and an important role of proprioception in early sensory processing suggests the hypothesis that the active electrosensory system is part of a multimodal haptic sense.

I shall present two recent piece of work investigating how shape effects the transport of active particles in shear. Firstly we will consider the sedimentation of particles in 2D laminar flow fields of increasing complexity; and how insights from this can help explain why turbulence can enhance the sedimentation of negatively buoyant diatoms [1]. Secondly, we will consider the 3D transport of elongated active particles under the action of an aligning force (e.g. gyrotactic swimmers) in some simple flow fields; and will see how shape can influence the vertical distribution, for example changing the structure of thin layers [2]. [1] Enhanced sedimentation of elongated plankton in simple flows (2018). IMA Journal of Applied Mathematics W Clifton, RN Bearon, & MA Bees. [2] Elongation enhances migration through hydrodynamic shear (in Prep), RN Bearon & WM Durham.

When was the last time you ran into a giant? Chances are never. Almost 100 years ago, JBS Haldane posed an outwardly simple yet complex question – what is the most optimal size (for a biological system)? The living world around us contains a huge diversity of organisms, each with its own characteristic size. Even the size of subcellular organelles is tightly controlled. In absence of physical rulers, how do cells and organisms truly “know” how large is large enough? What are the mechanisms in place to enforce size control? Many of these questions have motivated generations of scientists to look for physical principles underlying size control in biological systems. In the next edition of Emory's Theory and Modeling of Living Systems (TMLS) workshop series, our panel of speakers will take a close look at these questions, across the entire scale - from the molecular, all the way to the ecosystem.

Motility is a crucial virulence factor for many species of bacteria, but it is not fully understood how bacterial motility is practically involved in pathogenicity. This time I will give a talk on the association of motility with pathogenicity in the zoonotic spirochete bacterium Leptospira. Recently, we measured swimming force of individual leptospires using optical tweezers and found that they can generate ~30 times of the swimming force of E. coli. We also observed that leptospires increase the reversal frequency of swimming at the gel-liquid interface, resembling host dermis exposed to contaminated water (Abe et al., 2020, Sci Rep). These could be involved in percutaneous infection of the spirochete. We have shown that Leptospira not only swims in liquid but also moves over solid surfaces (Tahara et al., 2018, Sci Adv). We quantified the surface motility called “crawling” on cultured kidney tissues from various mammals, showing that pathogenic leptospires crawl over the tissue surfaces more persistently that non-pathogenic ones (Xu et al., 2020, Front Microbiol). I will discuss the spirochete motility related to pathogenicity from the biophysical viewpoint.

Proteins and membranes form remarkably complex structures that are key to intracellular compartmentalization, cargo transport, and cell morphology. Despite this wealth of examples in living systems, we still lack design principles for controlling membrane morphology in synthetic systems. With experiments and simulations, we show that even the simple case of spherical or rod-shaped nanoparticles binding to lipid-bilayer membrane vesicles results in a remarkably rich set of morphologies that can be reliably controlled via the particle binding energy. When the binding energy is weak relative to a characteristic membrane-bending energy, vesicles adhere to one another and form a soft solid gel, which is a useful platform for controlled release. With larger binding energy, a transition from partial to complete wrapping of the nanoparticles causes a remarkable vesicle destruction process culminating in rupture, nanoparticle-membrane tubules, and vesicle inversion. We have explored the behavior across a wide range of parameter space. These findings help unify the wide range of effects observed when vesicles or cells are exposed to nanoparticles. They also show how they open the door to a new class of vesicle-based, closed-cell gels that are more than 99% water and can encapsulate and release on demand. I will discuss how triggering membrane remodeling could lead to shape-responsive systems in the future.

Both computational and experimental results in single neurons and small networks demonstrate that very similar network function can result from quite disparate sets of neuronal and network parameters. Using the crustacean stomatogastric nervous system, we study the influence of these differences in underlying structure on differential resilience of individuals to a variety of environmental perturbations, including changes in temperature, pH, potassium concentration and neuromodulation. We show that neurons with many different kinds of ion channels can smoothly move through different mechanisms in generating their activity patterns, thus extending their dynamic range. The talk will be simultaneously translated to spanish by the interpreter Liliana Viera, MSc. Los resultados tanto computacionales como experimentales en neuronas individuales y redes pequeñas demuestran que funcionamientos de redes muy similares pueden pueden resultar de conjuntos bastante dispares de parámetros neuronales y de las redes. Utilizando el sistema nervioso estomatogástrico de los crustáceos, estudiamos la influencia de estas diferencias en la estructura subyacente en la resistencia diferencial de los individuos a una variedad de perturbaciones ambientales, incluidos los cambios de temperatura, pH, concentración de potasio y neuromodulación. Mostramos que neuronas con muchos tipos diferentes de canales iónicos pueden moverse suavemente a través de diferentes mecanismos para generar sus patrones de actividad, extendiendo así su rango dinámico. La conferencia será traducida simultáneamente al español por la intérprete Liliana Viera MSc.

Understanding individual and macroscopic transport properties of motile micro-organisms in complex environments is a timely question, relevant to many ecological, medical and technological situations. At the fundamental level, this question is also receiving a lot of attention as fluids loaded with swimming micro-organisms has become a rich domain of applications and a conceptual playground for the statistical physics of “active matter”. The existence of microscopic sources of energy borne by the motile character of these micro-swimmers is driving self-organization processes at the origin of original emergent phases and unconventional macroscopic properties leading to revisit many standard concepts in the physics of suspensions. In this presentation, I will report on a recent exploration on the question of spontaneous formation of large scale collective motion in relation with the rheological response of active suspensions. I will also present new experiments showing how the motility of bacteria can be controlled such as to extract work macroscopically.

My lab studies the design principles of cytoskeletal materials the drive cellular morphogenesis, with a focus on contractile machinery in adherent cells. In addition to force generation, a key feature of these materials are distributed force sensors which allow for rapid assembly, adaptation, repair and disintegration. Here I will describe how optogenetic control of RhoA GTPase is a powerful and versatile force spectroscopy approach of cytoskeletal assemblies and its recent use to probe repair response in actomyosin stress fibers. I will also describe our recent identification of 18 proteins from the zyxin, paxillin, Tes and Enigma families with mechanosensitive LIM (Lin11, Isl- 1 & Mec-3) domains that bind exclusively to mechanically stressed actin filaments. Our results suggest that the evolutionary emergence of contractile F-actin machinery coincided with, or required, proteins that could report on the stresses present there to maintain homeostasis of actively stressed networks.

Epithelial cell sheets form a fundamental role in the developing embryo, and also in adult tissues including the gut and the cornea of the eye. Soft and active matter provides a theoretical and computational framework to understand the mechanics and dynamics of these tissues.I will start by introducing the simplest useful class of models, active brownian particles (ABPs), which incorporate uncoordinated active crawling over a substrate and mechanical interactions. Using this model, I will show how the extended ’swirly’ velocity fluctuations seen in sheets on a substrate can be understood using a simple model that couples linear elasticity with disordered activity. We are able to quantitatively match experiments using in-vitro corneal epithelial cells.Adding a different source of activity, cell division and apoptosis, to such a model leads to a novel 'self-melting' dense fluid state. Finally, I will discuss a direct application of this simple particle-based model to the steady-state spiral flow pattern on the mouse cornea.