Fluids
fluids
PhenoSign - Molecular Dynamic Insights
Do You Know Your Blood Glucose Level? You Probably Should! A single measurement is not enough to truly understand your metabolic health. Blood glucose levels fluctuate dynamically, and meaningful insights require continuous monitoring over time. But glucose is just one example. Many other molecular concentrations in the body are not static. Their variations are influenced by individual physiology and overall health. PhenoSign, a Swiss MedTech startup, is on a mission to become the leader in real-time molecular analysis of complex fluids, supporting clinical decision-making and life sciences applications. By providing real-time, in-situ molecular insights, we aim to advance medicine and transform life sciences research. This talk will provide an overview of PhenoSign’s journey since its inception in 2022—our achievements, challenges, and the strategic roadmap we are executing to shape the future of real-time molecular diagnostics.
Personalized medicine and predictive health and wellness: Adding the chemical component
Wearable sensors that detect and quantify biomarkers in retrievable biofluids (e.g., interstitial fluid, sweat, tears) provide information on human dynamic physiological and psychological states. This information can transform health and wellness by providing actionable feedback. Due to outdated and insufficiently sensitive technologies, current on-body sensing systems have capabilities limited to pH, and a few high-concentration electrolytes, metabolites, and nutrients. As such, wearable sensing systems cannot detect key low-concentration biomarkers indicative of stress, inflammation, metabolic, and reproductive status. We are revolutionizing sensing. Our electronic biosensors detect virtually any signaling molecule or metabolite at ultra-low levels. We have monitored serotonin, dopamine, cortisol, phenylalanine, estradiol, progesterone, and glucose in blood, sweat, interstitial fluid, and tears. The sensors are based on modern nanoscale semiconductor transistors that are straightforwardly scalable for manufacturing. We are developing sensors for >40 biomarkers for personalized continuous monitoring (e.g., smartwatch, wearable patch) that will provide feedback for treating chronic health conditions (e.g., perimenopause, stress disorders, phenylketonuria). Moreover, our sensors will enable female fertility monitoring and the adoption of more healthy lifestyles to prevent disease and improve physical and cognitive performance.
Mathematical and computational modelling of ocular hemodynamics: from theory to applications
Changes in ocular hemodynamics may be indicative of pathological conditions in the eye (e.g. glaucoma, age-related macular degeneration), but also elsewhere in the body (e.g. systemic hypertension, diabetes, neurodegenerative disorders). Thanks to its transparent fluids and structures that allow the light to go through, the eye offers a unique window on the circulation from large to small vessels, and from arteries to veins. Deciphering the causes that lead to changes in ocular hemodynamics in a specific individual could help prevent vision loss as well as aid in the diagnosis and management of diseases beyond the eye. In this talk, we will discuss how mathematical and computational modelling can help in this regard. We will focus on two main factors, namely blood pressure (BP), which drives the blood flow through the vessels, and intraocular pressure (IOP), which compresses the vessels and may impede the flow. Mechanism-driven models translates fundamental principles of physics and physiology into computable equations that allow for identification of cause-to-effect relationships among interplaying factors (e.g. BP, IOP, blood flow). While invaluable for causality, mechanism-driven models are often based on simplifying assumptions to make them tractable for analysis and simulation; however, this often brings into question their relevance beyond theoretical explorations. Data-driven models offer a natural remedy to address these short-comings. Data-driven methods may be supervised (based on labelled training data) or unsupervised (clustering and other data analytics) and they include models based on statistics, machine learning, deep learning and neural networks. Data-driven models naturally thrive on large datasets, making them scalable to a plethora of applications. While invaluable for scalability, data-driven models are often perceived as black- boxes, as their outcomes are difficult to explain in terms of fundamental principles of physics and physiology and this limits the delivery of actionable insights. The combination of mechanism-driven and data-driven models allows us to harness the advantages of both, as mechanism-driven models excel at interpretability but suffer from a lack of scalability, while data-driven models are excellent at scale but suffer in terms of generalizability and insights for hypothesis generation. This combined, integrative approach represents the pillar of the interdisciplinary approach to data science that will be discussed in this talk, with application to ocular hemodynamics and specific examples in glaucoma research.
The glymphatic system in motor neurone disease
Neurodegenerative diseases are chronic and inexorable conditions characterised by the presence of insoluble aggregates of abnormally ubiquinated and phosphorylated proteins. Recent evidence also suggests that protein misfolding can propagate throughout the body in a prion-like fashion via the interstitial or cerebrospinal fluids (CSF). As protein aggregation occurs well before the onset of brain damage and symptoms, new biomarkers sensitive to early pathology, together with therapeutic strategies that include eliminating seed proteins and blocking cell-to-cell spread, are of vital importance. The glymphatic system, which facilitates the continuous exchange of CSF and interstitial fluid to clear the brain of waste, presents as a potential biomarker of disease severity, therapeutic target, and drug delivery system. In this webinar, Associate Professor David Wright from the Department of Neuroscience, Monash University, will outline recent advances in using MRI to investigate the glymphatic system. He will also present some of his lab’s recent work investigating glymphatic clearance in preclinical models of motor neurone disease. Associate Professor David Wright is an NHMRC Emerging Leadership Fellow and the Director of Preclinical Imaging in the Department of Neuroscience, Monash University and the Alfred Research Alliance, Alfred Health. His research encompasses the development, application and analysis of advanced magnetic resonance imaging techniques for the study of disease, with a particular emphasis on neurodegenerative disorders. Although less than three years post PhD, he has published over 60 peer-reviewed journal articles in leading neuroscience journals such as Nature Medicine, Brain, and Cerebral Cortex.
The Equation of State of a Tissue
An equation of state is something you hear about in introductory thermodynamics, for example, the Ideal gas equation. The ideal gas equation relates the pressure, volume, and the number of particles of the gas, to its temperature, uniquely defining its state. This description is possible in physics when the system under investigation is in equilibrium or near equilibrium. In biology, a tissue is modeled as a fluid composed of cells. These cells are constantly interacting with each other through mechanical and chemical signaling, driving them far from equilibrium. Can an equation of state exist for such a messy interacting system? In this talk, I show that the presence of strong cell-cell interaction in tissues gives rise to a novel non-equilibrium, size-dependent surface tension, something unheard of for classical fluids. This surface tension, in turn, modifies the packing of cells inside the tissue generating a size-dependent density and pressure. Finally, we show that a combination of these non-equilibrium pressure and densities can yield an equation of state for biological tissues arbitrarily far from equilibrium. In the end, I discuss how this new paradigm of size-dependent biological properties gives rise to novel modes of cellular motion in tissues
Exact coherent structures and transition to turbulence in a confined active nematic
Active matter describes a class of systems that are maintained far from equilibrium by driving forces acting on the constituent particles. Here I will focus on confined active nematics, which exhibit especially rich flow behavior, ranging from structured patterns in space and time to disordered turbulent flows. To understand this behavior, I will take a deterministic dynamical systems approach, beginning with the hydrodynamic equations for the active nematic. This approach reveals that the infinite-dimensional phase space of all possible flow configurations is populated by Exact Coherent Structures (ECS), which are exact solutions of the hydrodynamic equations with distinct and regular spatiotemporal structure; examples include unstable equilibria, periodic orbits, and traveling waves. The ECS are connected by dynamical pathways called invariant manifolds. The main hypothesis in this approach is that turbulence corresponds to a trajectory meandering in the phase space, transitioning between ECS by traveling on the invariant manifolds. Similar approaches have been successful in characterizing high Reynolds number turbulence of passive fluids. Here, I will present the first systematic study of active nematic ECS and their invariant manifolds and discuss their role in characterizing the phenomenon of active turbulence.
Flow singularities in soft materials: from thermal motion to active molecular stresses
The motion of passive or active agents in soft materials generates long ranged deformation fields with signatures informed by hydrodynamics and the properties of the soft matter host. These signatures are even more complex when the soft matter host itself is an active material. Measurement of these fields reveals mechanics of the soft materials and hydrodynamics central to understanding self-organization. In this talk, I first introduce a new method based on correlated displacement velocimetry, and use the method to measure flow fields around particles trapped at the interface between immiscible fluids. These flow fields, decomposed into interfacial hydrodynamic multipoles, including force monopole and dipole flows, provide key insights essential to understanding the interface’s mechanical response. I then extend this method to various actomyosin systems to measure local strain fields around myosin molecular motors. I show how active stresses propagate in 2d liquid crystalline structures and in disordered networks that are formed by the actin filaments. In particular, the response functions of contractile and stable gels are characterized. Through similar analysis, I also measure the retrograde flow fields of stress fibers in single cells to understand subcellular mechanochemical systems.
Microalgal motility through day/night cycles
We have characterised the motility of the swimming microalga Chlamydomonas reinhardtii as a function of day/night cycles, to which the microalgal growth is entrained. Intriguingly, we find that the microalgae swim almost twice as fast during the night than during the day. I will connect this result with the bioenergetics of flagellar propulsion, discussing consequences for the distributions of cells in lab-based and environmental water columns.
Coordinated motion of active filaments on spherical surfaces
Filaments (slender, microscopic elastic bodies) are prevalent in biological and industrial settings. In the biological case, the filaments are often active, in that they are driven internally by motor proteins, with the prime examples being cilia and flagella. For cilia in particular, which can appear in dense arrays, their resulting motions are coupled through the surrounding fluid, as well as through surfaces to which they are attached. In this talk, I present numerical simulations exploring the coordinated motion of active filaments and how it depends on the driving force, density of filaments, as well as the attached surface. In particular, we find that when the surface is spherical, its topology introduces local defects in coordinated motion which can then feedback and alter the global state. This is particularly true when the surface is not held fixed and is free to move in the surrounding fluid. These simulations take advantage of a computational framework we developed for fully 3D filament motion that combines unit quaternions, implicit geometric time integration, quasi-Newton methods, and fast, matrix-free methods for hydrodynamic interactions and it will also be presented.
Swimming and crawling of Euglena gracilis: a tale with many twists
Euglena gracilis is an interesting unicellular protist, also because it can adopt different motility strategies: swimming by flagellar propulsion, or crawling thanks to large amplitude shape changes of the whole body (a behavior known as “metaboly”, or “amoeboid motion”). Swimming trajectories are helical. The are powered by the beating of a single emerging flagellum, which spans non-planar waveforms in the shape of a twisted lasso. Finally the harmoniously coordinated shape changes that make metaboly possible, reminiscent of peristaltic waves, arise form the relative sliding of its pellicle strips, resulting in twisted helical bundles. We will report on the most recent findings on these interconnected topics, for which helical shapes provide a striking fil rouge.
Trapping active particles up to the limiting case: bacteria enclosed in a biofilm
Active matter systems are composed of constituents, each one in nonequilibrium, that consume energy in order to move [1]. A characteristic feature of active matter is collective motion leading to nonequilibrium phase transitions or large scale directed motion [2]. A number of recent works have featured active particles interacting with obstacles, either moving or fixed [3,4,5]. When an active particle encounters an asymmetric obstacle, different behaviours are detected depending on the nature of its active motion. On the one side, rectification effects arise in a suspension of run-and-tumble particles interacting with a wall of funnelled-shaped openings, caused by particles persistence length [6]. The same trapping mechanism could be responsible for the intake of microorganisms in the underground leaves [7] of Carnivorous plants [8]. On the other side, for aligning particles [9] interacting with a wall of funnelled-shaped openings, trapping happens on the (opposite) wider opening side of the funnels [10,11]. Interestingly, when funnels are located on a circular array, trapping is more localised and depends on the nature of the Vicsek model. Active particles can be synthetic (such as synthetic active colloids) or alive (such as living bacteria). A prototypical model to study living microswimmers is P. fluorescens, a rod shaped and biofilm forming bacterium. Biofilms are microbial communities self-assembled onto external interfaces. Biofilms can be described within the Soft Matter physics framework [12] as a viscoelastic material consisting of colloids (bacterial cells) embedded in a cross-linked polymer gel (polysaccharides cross-linked via proteins/multivalent cations), whose water content vary depending on the environmental conditions. Bacteria embedded in the polymeric matrix control biofilm structure and mechanical properties by regulating its matrix composition. We have recently monitored structural features of Pseudomonas fluorescens biofilms grown with and without hydrodynamic stress [13,14]. We have demonstrated that bacteria are capable of self-adapting to hostile hydrodynamic stress by tailoring the biofilm chemical composition, thus affecting both the mesoscale structure of the matrix and its viscoelastic properties that ultimately regulate the bacteria-polymer interactions. REFERENCES [1] C. Bechinger et al. Rev. Mod. Phys. 88, 045006 (2016); [2] T. Vicsek, A. Zafeiris Phys. Rep. 517, 71 (2012); [3] C. Bechinger, R. Di Leonardo, H. Lowen, C. Reichhardt, G. Volpe, and G. Volpe, Reviews of Modern Physics 88, 045006 (2016); [4] R Martinez, F Alarcon, DR Rodriguez, JL Aragones, C Valeriani The European Physical Journal E 41, 1 (2018); [5] DR Rodriguez, F Alarcon, R Martinez, J Ramírez, C Valeriani, Soft matter 16 (5), 1162 (2020); [6] C. O. Reichhardt and C. Reichhardt, Annual Review of Condensed Matter Physics 8, 51 (2017); [7] W Barthlott, S Porembski, E Fischer, B Gemmel Nature 392, 447 (1998); [8] C B. Giuliano, R Zhang, R.Martinez Fernandez, C.Valeriani and L.Wilson (in preparation, 2021); [9] R Martinez, F Alarcon, JL Aragones, C Valeriani Soft matter 16 (20), 4739 (2020); [10] P. Galajada, J. Keymer, P. Chaikin and R.Austin, Journal of bacteriology, 189, 8704 (2007); [11] M. Wan, C.O. Reichhardt, Z. Nussinov, and C. Reichhardt, Physical Review Letters 101, 018102 (2008); [12] J N. Wilking , T E. Angelini , A Seminara , M P. Brenner , and D A. Weitz MRS Bulletin 36, 385 (2011); [13]J Jara, F Alarcón, A K Monnappa, J Ignacio Santos, V Bianco, P Nie, M Pica Ciamarra, A Canales, L Dinis, I López-Montero, C Valeriani, B Orgaz, Frontiers in microbiology 11, 3460 (2021); [14] P Nie, F Alarcon, I López-Montero, B Orgaz, C Valeriani, M Pica Ciamarra
Microorganism locomotion in viscoelastic fluids
Many microorganisms and cells function in complex (non-Newtonian) fluids, which are mixtures of different materials and exhibit both viscous and elastic stresses. For example, mammalian sperm swim through cervical mucus on their journey through the female reproductive tract, and they must penetrate the viscoelastic gel outside the ovum to fertilize. In micro-scale swimming the dynamics emerge from the coupled interactions between the complex rheology of the surrounding media and the passive and active body dynamics of the swimmer. We use computational models of swimmers in viscoelastic fluids to investigate and provide mechanistic explanations for emergent swimming behaviors. I will discuss how flexible filaments (such as flagella) can store energy from a viscoelastic fluid to gain stroke boosts due to fluid elasticity. I will also describe 3D simulations of model organisms such as C. Reinhardtii and mammalian sperm, where we use experimentally measured stroke data to separate naturally coupled stroke and fluid effects. We explore why strokes that are adapted to Newtonian fluid environments might not do well in viscoelastic environments.
Flocks and crowds: a Gulliver travel
In the first part of my talk, combining experimental, numerical and theoretical results, I will explain how self-propelled colloidal particles self-organize in one of the most robust ordered state found in nature: flocks. I will explain how to describe macroscopic flocking motion as the spontaneous flows of an active fluid, and use this framework to elucidate the phase ordering dynamics of polar active matter. In the second part of my talk, I will show that the same tools and concepts can be effectively used to infer a hydrodynamic description of active fluids composed of particles 6 order of magnitude larger in size: pedestrian crowds.
Sperm have got the bends
The journey of development begins with sperm swimming through the female reproductive tract en-route to the egg. In order to successfully complete this journey sperm must beat a single flagellum, propelling themselves through a wide range of fluids, from liquified semen to viscous cervical mucus. It is well-known that the beating tail is driven by an array of 9 microtubule doublets surrounding a central pair, with interconnecting dynein motors generating shear forces and driving elastic wave propagation. Despite this knowledge, the exact mechanism by which coordination of these motors drives oscillating waves along the flagellum remains unknown; hypothesised mechanisms include curvature control, sliding control, and geometric clutch. In this talk we will discuss the mechanisms of flagellar bending, and present a simple model of active curvature that is able to produce many of the various sperm waveforms that are seen experimentally, including those in low and high viscosity fluids and after a cell has ‘hyperactivated’ (a chemical process thought to be key for fertilization). We will show comparisons between these simulated waveforms and sperm that have been experimentally tracked, and discuss methods for fitting simulated mechanistic parameters to these real cells.
Free-falling dynamically scaled models: Foraminifera as a test case
The settling speeds of small biological particles influence the distribution of organisms such as plants, corals, and phytoplankton, but these speeds are difficult to quantify without magnification. In this talk, I highlight my novel method, using dynamic scaling principles and 3D printed models to solve this problem. Dynamic scaling involves creating models with differ in size to the original system and match the physical forces acting upon the model to the original system. I discuss the methodology behind the technique and show how it differs to previous works using dynamically scaled models. I show the flexibility of the technique and suggest how it can be applied to other free-falling particles (e.g. seeds and spores).
Life in complex fluids
Inertial active soft matter
Active particles which are self-propelled by converting energy into mechanical motion represent an expanding research realm in physics and chemistry. For micron-sized particles moving in a liquid (``microswimmers''), most of the basic features have been described by using the model of overdamped active Brownian motion [1]. However, for macroscopic particles or microparticles moving in a gas, inertial effects become relevant such that the dynamics is underdamped. Therefore, recently, active particles with inertia have been described by extending the active Brownian motion model to active Langevin dynamics which include inertia [2]. In this talk, recent developments of active particles with inertia (``microflyers'', ``hoppers'' or ``runners'') are summarized including: inertial delay effects between particle velocity and self-propulsion direction [3], tuning of the long-time self-diffusion by the moment of inertia [3], the influence of inertia on motility-induced phase separation and the cluster growth exponent [4], and the formation of active micelles (“rotelles”) by using inertial active surfactants. References [1] C. Bechinger, R. di Leonardo, H. Löwen, C. Reichhardt, G. Volpe, G. Volpe, Reviews of Modern Physics 88, 045006 (2016). [2] H. Löwen, Journal of Chemical Physics 152, 040901 (2020). [3] C. Scholz, S. Jahanshahi, A. Ldov, H. Löwen, Nature Communications 9, 5156 (2018). [4] S. Mandal, B. Liebchen, H. Löwen, Physical Review Letters 123, 228001 (2019). [5] C. Scholz, A. Ldov, T. Pöschel, M. Engel, H. Löwen, Surfactants and rotelles in active chiral fluids, will be published
Hydrodynamic shape of microorganisms: Generalised Jeffery orbits
'Shape' of microorganisms are diverse. However, we sometimes approximate them as a sphere or a spheroid when we mathematically model the hydrodynamics of motile and non-motile cells. Such a geometrical simplification can be theoretically validated for motions in a linear background flow, since the dynamics, known as the Jeffery orbit, only contain a single geometric parameter, called the Bretherton constant. In this talk, we generalise the Jeffery equations for a chiral axisymmetric object using the low-Reynolds-number hydrokinetic symmetry and then demonstrate that the dynamics of a certain type of chiral object in a fluid flow are characterised by a new chiral parameter in addition to the Bretherton constant. We also discuss how the generalised Jeffery orbits are applied to biased locomotion of bacteria in a bulk shear flow and we will share the idea of hydrodynamic `shape' of microorganisms to simplify the description of their dynamics.
Sperm Navigation: from hydrodynamic interactions to parameter estimation
Microorganisms can swim in a variety of environments, interacting with chemicals and other proteins in the fluid. In this talk, we will highlight recent computational methods and results for swimming efficiency and hydrodynamic interactions of swimmers in different fluid environments. Sperm are modeled via a centerline representation where forces are solved for using elastic rod theory. The method of regularized Stokeslets is used to solve the fluid-structure interaction where emergent swimming speeds can be compared to asymptotic analysis. In the case of fluids with extra proteins or cells that may act as friction, swimming speeds may be enhanced, and attraction may not occur. We will also highlight how parameter estimation techniques can be utilized to infer fluid and/or swimmer properties.
Exploring the evolution of motile curved bacteria using a regularized Stokeslet Boundary Element Method and Pareto optimality theory
Bacteria exhibit a bewildering diversity of morphologies, but despite their impact on nearly all aspects of life, they are frequently classified into a few general categories, usually just “spheres” and “rods.” Curved-rod bacteria are one simple variation observed in many environments, particularly the ocean. However, why so many species have evolved this shape is unknown. We used a regularized Stokeslet Boundary Element Method to model the motility of flagellated, curved bacteria. We show that curvature can increase swimming efficiency, revealing a widely applicable selective advantage. Furthermore, we show that the distribution of cell lengths and curvatures observed across bacteria in nature is predicted by evolutionary trade-offs between three tasks influenced by shape: efficient swimming, the ability to detect chemical gradients, and reduced cost of cell construction. We therefore reveal shape as an important component of microbial fitness.
Imposed flow in active liquid crystals
Inspired by ongoing experiments on three dimensional active gels composed of sliding microtubule bundles, we study a few idealized problems in a minimal hydrodynamic model for active liquid crystals. Our aim is to use flow to determine the value of the coefficient of activity in a continuum theory. We consider the case of apolar active particles that form a disordered phase in the absence of flow, and study how activity affects the swimming speed of a prescribed swimmer, as well as the stability of a fluid interface. We also consider flows of active matter in channels or past immersed objects.
Soft matter physics and the COVID-19 pandemic
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.
Stochastic control of passive colloidal objects by micro-swimmers
The way single colloidal objects behave in presence of active forces arising from within the bulk of the system is crucial to many situations, notably biological and ecological (e.g. intra-cellular transport, predation), and potential medical or environmental applications (e.g. targeted delivery of cargoes, depollution of waters and soils). In this talk I will present experimental findings that my collaborators and I have obtained over the past years on the dynamics of single Brownian colloids in suspensions of biological micro-swimmers, especially the green alga Chlamydomonas reinhardtii. I'll show notably that spatial heterogeneities and anisotropies in the active particles statistics can control the preferential localisation of their passive counterparts. The results will be rationalized using theoretical approaches from hydrodynamics and stochastic processes.
The impact of elongation on transport in shear flow
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.
Transport and dispersion of active particles in complex porous media
Understanding the transport of microorganisms and self-propelled particles in porous media has important consequences in human health as well as for microbial ecology. In this work, we explore models for the dispersion of active particles in both periodic and random porous media. In a first problem, we analyze the long-time transport properties in a dilute system of active Brownian particles swimming in a periodic lattice in the presence of an external flow. Using generalized Taylor dispersion theory, we calculate the mean transport velocity and dispersion dyadic and explain their dependence on flow strength, swimming activity and geometry. In a second approach, we address the case of run-and-tumble particles swimming through unstructured porous media composed of randomly distributed circular pillars. There, we show that the long-time dispersion is described by a universal hindrance function that depends on the medium porosity and ratio of the swimmer run length to the pillar size. An asymptotic expression for the hindrance function is derived in dilute media, and its extension to semi-dilute and dense media is obtained using stochastic simulations. We conclude by discussing the role of hydrodynamic interactions and swimmer concentration effects.
Motility-dependent pathogenicity of a spirochetal bacterium
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.
Motility control in biological microswimmers
It is often assumed that biological swimmers conform faithfully to certain stereotypes assigned to them by physicists and mathematicians, when the reality is in fact much more complicated. In this talk we will use a combination of theory, experiments, and robotics, to understand the physical and evolutionary basis of motility control in a number of distinguished organisms. These organisms differ markedly in terms of their size, shape, and arrangement of locomotor appendages, but are united in their use of cilia - the ultimate shape-shifting organelle - to achieve self-propulsion and navigation.
Spontaneous and driven active matter flows
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.
Continuum modelling of active fluids beyond the generalised Taylor dispersion
The Smoluchowski equation has often been used as the starting point of many continuum models of active suspensions. However, its six-dimensional nature depending on time, space and orientation requires a huge computational cost, fundamentally limiting its use for large-scale problems, such as mixing and transport of active fluids in turbulent flows. Despite the singular nature in strain-dominant flows, the generalised Taylor dispersion (GTD) theory (Frankel & Brenner 1991, J. Fluid Mech. 230:147-181) has been understood to be one of the most promising ways to reduce the Smoluchowski equation into an advection-diffusion equation, the mean drift and diffusion tensor of which rely on ‘local’ flow information only. In this talk, we will introduce an exact transformation of the Smoluchowski equation into such an advection-diffusion equation requiring only local flow information. Based on this transformation, a new advection-diffusion equation will subsequently be proposed by taking an asymptotic analysis in the limit of small particle velocity. With several examples, it will be demonstrated that the new advection-diffusion model, non-singular in strain-dominant flows, outperforms the GTD theory.
Synthetic swimmers: microorganism swimming without microorganisms
The effect of non Newtonian liquid rheology on the swimming performance of microorganisms is still poorly understood, despite numerous recent studies. In our effort to clarify some aspects of this problem, we have developed a series of magnetic synthetic swimmers that self-propel immersed in a fluid by emulating the swimming strategy of flagellated microorganisms. With these devices, it is possible to control some aspects of the motion with the objective to isolate specific effects. In this talk, recent results on the effects of shear-thinning viscosity and viscoelasticity on the motion of helical swimmers will presented and discussed. Also, a number of other new uses of the synthetic swimmers will be presented including swimming across gradients, swimming in sand, interactions and rheometry.