Perspective: Differential dynamic microscopy extracts multi-scale activity in complex fluids and biological systems

Quantitative Visualization of Lipid Nanoparticle Fusion as a Function of Formulation and Process Parameters

Lipid nanoparticles (LNPs) have proven to be promising delivery vehicles for RNA-based vaccines and therapeutics, particularly in LNP formulations containing ionizable cationic lipids that undergo protonation/deprotonation in response to buffer pH changes. These nanoparticles are typically formulated using a rapid mixing technique at low pH, followed by a return to physiological pH that triggers LNP-LNP fusion. A detailed understanding of these dynamic processes is crucial to optimize the overall performance and efficiency of LNPs. However, knowledge gaps persist regarding how particle formation mechanisms impact drug loading and delivery functions. In this work, we employ single-molecule Convex Lens-induced Confinement (CLiC) microscopy in combination with Förster resonance energy transfer (FRET) measurements to study LNP fusion dynamics in relation to various formulation parameters, including lipid concentration, buffer conditions, drug loading ratio, PEG-lipid concentrations, and ionizable lipid selection. Our results reveal a strong correlation between the measured fusion dynamics and the formulation parameters used; these findings are consistent with DLS and Cryo-TEM-based assays. These measurements offer a cost-effective method for characterizing and screening potential drug candidates and can provide additional insights into their design, with opportunities for optimization.

Coherent light scattering from cellular dynamics in living tissues

This review examines the biological physics of intracellular transport probed by the coherent optics of dynamic light scattering from optically thick living tissues. Cells and their constituents are in constant motion, composed of a broad range of speeds spanning many orders of magnitude that reflect the wide array of functions and mechanisms that maintain cellular health. From the organelle scale of tens of nanometers and upward in size, the motion inside living tissue is actively driven rather than thermal, propelled by the hydrolysis of bioenergetic molecules and the forces of molecular motors. Active transport can mimic the random walks of thermal Brownian motion, but mean-squared displacements are far from thermal equilibrium and can display anomalous diffusion through Lévy or fractional Brownian walks. Despite the average isotropic three-dimensional environment of cells and tissues, active cellular or intracellular transport of single light-scattering objects is often pseudo-one-dimensional, for instance as organelle displacement persists along cytoskeletal tracks or as membranes displace along the normal to cell surfaces, albeit isotropically oriented in three dimensions. Coherent light scattering is a natural tool to characterize such tissue dynamics because persistent directed transport induces Doppler shifts in the scattered light. The many frequency-shifted partial waves from the complex and dynamic media interfere to produce dynamic speckle that reveals tissue-scale processes through speckle contrast imaging and fluctuation spectroscopy. Low-coherence interferometry, dynamic optical coherence tomography, diffusing-wave spectroscopy, diffuse-correlation spectroscopy, differential dynamic microscopy and digital holography offer coherent detection methods that shed light on intracellular processes. In health-care applications, altered states of cellular health and disease display altered cellular motions that imprint on the statistical fluctuations of the scattered light. For instance, the efficacy of medical therapeutics can be monitored by measuring the changes they induce in the Doppler spectra of livingex vivocancer biopsies.

Bile Is a Selective Elevator for Mucosal Mechanics and Transport

Mucus mechanically protects the intestinal epithelium and impacts the absorption of drugs, with a largely unknown role for bile. We explored the impacts of bile on mucosal biomechanics and drug transport within mucus. Bile diffused with square-root-of-time kinetics and interplayed with mucus, leading to transient stiffening captured in Brillouin images and a concentration-dependent change from subdiffusive to Brownian-like diffusion kinetics within the mucus demonstrated by differential dynamic microscopy. Bile-interacting drugs, Fluphenazine and Perphenazine, diffused faster through mucus in the presence of bile, while Metoprolol, a drug with no bile interaction, displayed consistent diffusion. Our findings were corroborated by rat studies, where co-dosing of a bile acid sequestrant substantially reduced the bioavailability of Perphenazine but not Metoprolol. We clustered over 50 drugs based on their interactions with bile and mucin. Drugs that interacted with bile also interacted with mucin but not vice versa. This study detailed the dynamics of mucus biomechanics under bile exposure and linked the ability of a drug to interact with bile to its abbility to interact with mucus.

Sizing multimodal suspensions with differential dynamic microscopy

Differential dynamic microscopy (DDM) can be used to extract the mean particle size from videos of suspensions. However, many suspensions have multimodal particle size distributions, for which a single 'mean' is not a sufficient description. After clarifying how different particle sizes contribute to the signal in DDM, we show that standard DDM analysis can extract the mean sizes of two populations in a bimodal suspension given prior knowledge of the sample's bimodality. Further, the use of the CONTIN algorithm obviates the need for such prior knowledge. Finally, we show that by selectively analysing portions of the DDM images, we can size a trimodal suspension where the large particles would otherwise dominate the signal, again without prior knowledge of the trimodality.

A Synthetic Signaling Network Imitating the Action of Immune Cells in Response to Bacterial Metabolism

State-of-the-art bottom-up synthetic biology allows to replicate many basic biological functions in artificial-cell-like devices. To mimic more complex behaviors, however, artificial cells would need to perform many of these functions in a synergistic and coordinated fashion, which remains elusive. Here, a sophisticated biological response is considered, namely the capture and deactivation of pathogens by neutrophil immune cells, through the process of netosis. A consortium consisting of two synthetic agents is designed-responsive DNA-based particles and antibiotic-loaded lipid vesicles-whose coordinated action mimics the sought immune-like response when triggered by bacterial metabolism. The artificial netosis-like response emerges from a series of interlinked sensing and communication pathways between the live and synthetic agents, and translates into both physical and chemical antimicrobial actions, namely bacteria immobilization and exposure to antibiotics. The results demonstrate how advanced life-like responses can be prescribed with a relatively small number of synthetic molecular components, and outlines a new strategy for artificial-cell-based antimicrobial solutions.

Diffusion of gold nanoparticles in porous silica monoliths determined by dynamic light scattering

HYPOTHESIS

The applicability of the dynamic light scattering method for the determination of particle diffusivity under confinement without applying refractive index matching was not adequately explored so far. The confinement effect on particle diffusion in a porous material which is relevant for particle chromatography has also not yet been fully characterized.

EXPERIMENTS

Dynamic light scattering experiments were performed for unimodal dispersions of 11-mercaptoundecanoic acid-capped gold nanoparticles. Diffusion coefficients of gold nanoparticles in porous silica monoliths were determined without limiting refractive index matching fluids. Comparative experiments were also performed with the same nanoparticles and porous silica monolith but applying refractive index matching.

FINDINGS

Two distinct diffusivities could be determined inside the porous silica monolith, both smaller than that in free media, showing a slowing-down of the diffusion processes of nanoparticles under confinement. While the larger diffusivity can be related to the slightly slowed-down diffusion of particles in the bulk of the pores and in the necks connecting individual pores, the smaller diffusivity might be related to the diffusion of particles near the pore walls. It shows that the dynamic light scattering method with a heterodyne detection scheme can be used as a reliable and competitive tool for determining particle diffusion under confinement.

Extracting, quantifying, and comparing dynamical and biomechanical properties of living matter through single particle tracking

A panoply of new tools for tracking single particles and molecules has led to an explosion of experimental data, leading to novel insights into physical properties of living matter governing cellular development and function, health and disease. In this Perspective, we present tools to investigate the dynamics and mechanics of living systems from the molecular to cellular scale via single-particle techniques. In particular, we focus on methods to measure, interpret, and analyse complex data sets that are associated with forces, materials properties, transport, and emergent organisation phenomena within biological and soft-matter systems. Current approaches, challenges, and existing solutions in the associated fields are outlined in order to support the growing community of researchers at the interface of physics and the life sciences. Each section focuses not only on the general physical principles and the potential for understanding living matter, but also on details of practical data extraction and analysis, discussing limitations, interpretation, and comparison across different experimental realisations and theoretical frameworks. Particularly relevant results are introduced as examples. While this Perspective describes living matter from a physical perspective, highlighting experimental and theoretical physics techniques relevant for such systems, it is also meant to serve as a solid starting point for researchers in the life sciences interested in the implementation of biophysical methods.

Motor-driven advection competes with crowding to drive spatiotemporally heterogeneous transport in cytoskeleton composites

The cytoskeleton-a composite network of biopolymers, molecular motors, and associated binding proteins-is a paradigmatic example of active matter. Particle transport through the cytoskeleton can range from anomalous and heterogeneous subdiffusion to superdiffusion and advection. Yet, recapitulating and understanding these properties-ubiquitous to the cytoskeleton and other out-of-equilibrium soft matter systems-remains challenging. Here, we combine light sheet microscopy with differential dynamic microscopy and single-particle tracking to elucidate anomalous and advective transport in actomyosin-microtubule composites. We show that particles exhibit multi-mode transport that transitions from pronounced subdiffusion to superdiffusion at tunable crossover timescales. Surprisingly, while higher actomyosin content increases the range of timescales over which transport is superdiffusive, it also markedly increases the degree of subdiffusion at short timescales and generally slows transport. Corresponding displacement distributions display unique combinations of non-Gaussianity, asymmetry, and non-zero modes, indicative of directed advection coupled with caged diffusion and hopping. At larger spatiotemporal scales, particles in active composites exhibit superdiffusive dynamics with scaling exponents that are robust to changing actomyosin fractions, in contrast to normal, yet faster, diffusion in networks without actomyosin. Our specific results shed important new light on the interplay between non-equilibrium processes, crowding and heterogeneity in active cytoskeletal systems. More generally, our approach is broadly applicable to active matter systems to elucidate transport and dynamics across scales.

Optical-Tweezers-integrating-Differential-Dynamic-Microscopy maps the spatiotemporal propagation of nonlinear strains in polymer blends and composites

How local stresses propagate through polymeric fluids, and, more generally, how macromolecular dynamics give rise to viscoelasticity are open questions vital to wide-ranging scientific and industrial fields. Here, to unambiguously connect polymer dynamics to force response, and map the deformation fields that arise in macromolecular materials, we present Optical-Tweezers-integrating-Differential -Dynamic-Microscopy (OpTiDMM) that simultaneously imposes local strains, measures resistive forces, and analyzes the motion of the surrounding polymers. Our measurements with blends of ring and linear polymers (DNA) and their composites with stiff polymers (microtubules) uncover an unexpected resonant response, in which strain alignment, superdiffusivity, and elasticity are maximized when the strain rate is comparable to the entanglement rate. Microtubules suppress this resonance, while substantially increasing elastic storage, due to varying degrees to which the polymers buildup, stretch and flow along the strain path, and configurationally relax induced stress. More broadly, the rich multi-scale coupling of mechanics and dynamics afforded by OpTiDDM, empowers its interdisciplinary use to elucidate non-trivial phenomena that sculpt stress propagation dynamics-critical to commercial applications and cell mechanics alike.

Particle-Based Microrheology As a Tool for Characterizing Protein-Based Materials

Microrheology based on video microscopy of embedded tracer particles has the potential to be used for high-throughput protein-based materials characterization. This potential is due to a number of characteristics of the techniques, including the suitability for measurement of low sample volumes, noninvasive and noncontact measurements, and the ability to set up a large number of samples for facile, sequential measurement. In addition to characterization of the bulk rheological properties of proteins in solution, for example, viscosity, microrheology can provide insight into the dynamics and self-assembly of protein-based materials as well as heterogeneities in the microenvironment being probed. Specifically, passive microrheology in the form of multiple particle tracking and differential dynamic microscopy holds promise for applications in high-throughput characterization because of the lack of user interaction required while making measurements. Herein, recent developments in the use of multiple particle tracking and differential dynamic microscopy are reviewed for protein characterization and their potential to be applied in a high-throughput, automatable setting.

Reshaping sub-millimetre bubbles from spheres to tori

Shape-changing objects are prized for applications ranging from acoustics to robotics. We report sub-millimetre bubbles that reversibly and rapidly change not only their shape but also their topological class, from sphere to torus, when subjected to a simple pressure treatment. Stabilized by a solid-like film of nanoscopic protein "particles", the bubbles may persist in toroidal form for several days, most of them with the relative dimensions expected of Clifford tori. The ability to cross topological classes reversibly and quickly is enabled by the expulsion of protein from the strained surfaces in the form of submicron assemblies. Compared to structural modifications of liquid-filled vesicles, for example by slow changes in solution osmolality, the rapid inducement of shape changes in bubbles by application of pressure may hasten experimental investigations of surface mechanics, even as it suggests new routes to lightweight materials with high surface areas.

Multiscale heterogeneous dynamics in two-dimensional glassy colloids

On approaching the glass transition, a dense colloid exhibits a dramatic slowdown with minute structural changes. Most microscopy experiments directly follow the motion of individual particles in real space, whereas scattering experiments typically probe the collective dynamics in reciprocal space, at variable wavevector q. Multiscale studies of glassy dynamics are experimentally demanding and thus seldom performed. By using two-dimensional hard-sphere colloids at various area fractions φ, we show here that Differential Dynamic Microscopy (DDM) can be effectively used to measure the collective dynamics of a glassy colloid in a range of q within a single experiment. As φ is increased, the single decay of the intermediate scattering functions is progressively replaced by a more complex relaxation that we fit to a sum of two stretched-exponential decays. The slowest process, corresponding to the long-time particle escapes from caging, has a characteristic time τs = 1/(DLq2 ) with diffusion coefficient DL ∼ (φc −φ)2.8 , and φc ≈ 0.81. The fast process exhibits, instead, a non-Brownian scaling of the characteristic time τf(q) and a relative amplitude a(q) that monotonically increases with q. Despite the non-Brownian nature of τf(q), we succeed in estimating the short-time diffusion coefficient Dcage, whose φ-dependence is practically negligible compared to the one of DL. Finally, we extend DDM to measure the q-dependent dynamical susceptibility χ4(q,t), a powerful yet hard-to-access multiscale indicator of dynamical heterogeneities. Our results show that DDM is a convenient tool to study the dynamics of colloidal glasses over a broad range of time and length-scales.

The modern structurator: increased performance for calculating the structure function

The autocorrelation function is a statistical tool that is often combined with dynamic light scattering (DLS) techniques to investigate the dynamical behavior of the scattered light fluctuations in order to measure, for example, the diffusive behavior of transparent particles dispersed in a fluid. An alternative approach to the autocorrelation function for the analysis of DLS data has been proposed decades ago and consists of calculating the autocorrelation function starting from difference of the signal at different times by using the so-called structure function. The structure function approach has been proven to be more robust than the autocorrelation function method in terms of noise and drift rejection. Therefore, the structure function analysis has gained visibility, in particular in combination with imaging techniques such as dynamic shadowgraphy and differential dynamic microscopy. Here, we show how the calculation of the structure function over thousands of images, typical of such techniques, can be accelerated, with the aim of achieving real-time analysis. The acceleration is realized by taking advantage of the Wiener-Khinchin theorem, i.e., by calculating the difference of images through Fourier transform in time. The new algorithm was tested both on CPU and GPU hardware, showing that the acceleration is particularly large in the case of CPU.

Uncertainty quantification and estimation in differential dynamic microscopy

Differential dynamic microscopy (DDM) is a form of video image analysis that combines the sensitivity of scattering and the direct visualization benefits of microscopy. DDM is broadly useful in determining dynamical properties including the intermediate scattering function for many spatiotemporally correlated systems. Despite its straightforward analysis, DDM has not been fully adopted as a routine characterization tool, largely due to computational cost and lack of algorithmic robustness. We present statistical analysis that quantifies the noise, reduces the computational order, and enhances the robustness of DDM analysis. We propagate the image noise through the Fourier analysis, which allows us to comprehensively study the bias in different estimators of model parameters, and we derive a different way to detect whether the bias is negligible. Furthermore, through use of Gaussian process regression (GPR), we find that predictive samples of the image structure function require only around 0.5%-5% of the Fourier transforms of the observed quantities. This vastly reduces computational cost, while preserving information of the quantities of interest, such as quantiles of the image scattering function, for subsequent analysis. The approach, which we call DDM with uncertainty quantification (DDM-UQ), is validated using both simulations and experiments with respect to accuracy and computational efficiency, as compared with conventional DDM and multiple particle tracking. Overall, we propose that DDM-UQ lays the foundation for important new applications of DDM, as well as to high-throughput characterization.

Characterising shear-induced dynamics in flowing complex fluids using differential dynamic microscopy

Microscopic dynamics reveal the origin of the bulk rheological response in complex fluids. In model systems particle motion can be tracked, but for industrially relevant samples this is often impossible. Here we adapt differential dynamic microscopy (DDM) to study flowing highly-concentrated samples without particle resolution. By combining an investigation of oscillatory flow, using a novel "echo-DDM" analysis, and steady shear, through flow-DDM, we characterise the yielding of a silicone oil emulsion on both the microscopic and bulk level. Through measuring the rate of shear-induced droplet rearrangements and the flow velocity, the transition from a solid-like to liquid-like state is shown to occur in two steps: with droplet mobilisation marking the limit of linear visco-elasticity, followed by the development of shear localisation and macroscopic yielding. Using this suite of techniques, such insight could be developed for a wide variety of challenging complex fluids.

Deformation profiles and microscopic dynamics of complex fluids during oscillatory shear experiments

Oscillatory shear tests are widely used in rheology to characterize the linear and non-linear mechanical response of complex fluids, including the yielding transition. There is an increasing urge to acquire detailed knowledge of the deformation field that is effectively present across the sample during these tests; at the same time, there is mounting evidence that the macroscopic rheological response depends on the elusive microscopic behavior of the material constituents. Here we employ a strain-controlled shear-cell with transparent walls to visualize and quantify the dynamics of tracers embedded in various cyclically sheared complex fluids, ranging from almost-ideal elastic to yield stress fluids. For each sample, we use image correlation processing to measure the macroscopic deformation field, and echo-differential dynamic microscopy to probe the microscopic irreversible sample dynamics in reciprocal space; finally, we devise a simple scheme to spatially map the rearrangements in the sheared sample, once again without tracking the tracers. For the yield stress sample, we obtain a wave-vector dependent characterization of shear-induced diffusion across the yielding transition, which is accompanied by a three-order-of-magnitude speed-up of the dynamics and by a transition from localized, intermittent rearrangements to a more spatially homogeneous and temporally uniform activity. Our tracking free approach is intrinsically multi-scale, can successfully discriminate between different types of dynamics, and can be automated to minimize user intervention. Applications are many, as it can be translated to other imaging modes, including fluorescence, and can be used with sub-resolution tracers and even without tracers, for samples that provide intrinsic optical contrast.

Dynamic and mechanical evolution of an oil-water interface during bacterial biofilm formation

We present an experimental study combining particle tracking, active microrheology, and differential dynamic microscopy (DDM) to investigate the dynamics and rheology of an oil-water interface during biofilm formation by the bacteria Pseudomonas Aeruginosa PA14. The interface transitions from an active fluid dominated by the swimming motion of adsorbed bacteria at early age to an active viscoelastic system at late ages when the biofilm is established. The microrheology measurements using microscale magnetic rods indicate that the biofilm behaves as a viscoelastic solid at late age. The bacteria motility at the interface during the biofilm formation, which is characterized in the DDM measurements, evolves from diffusive motion at early age to constrained, quasi-localized motion at later age. Similarly, the mobility of passively moving colloidal spheres at the interface decreases significantly with increasing interface age and shows a dependence on sphere size after biofilm formation that is orders-of-magnitude larger than that expected in a homogeneous system in equilibrium. We attribute this anomalous size dependence to either length-scale-dependent rheology of the biofilm or widely differing effects of the bacteria activity on the motion of spheres of different sizes.

Responsive core-shell DNA particles trigger lipid-membrane disruption and bacteria entrapment

Biology has evolved a variety of agents capable of permeabilizing and disrupting lipid membranes, from amyloid aggregates, to antimicrobial peptides, to venom compounds. While often associated with disease or toxicity, these agents are also central to many biosensing and therapeutic technologies. Here, we introduce a class of synthetic, DNA-based particles capable of disrupting lipid membranes. The particles have finely programmable size, and self-assemble from all-DNA and cholesterol-DNA nanostructures, the latter forming a membrane-adhesive core and the former a protective hydrophilic corona. We show that the corona can be selectively displaced with a molecular cue, exposing the 'sticky' core. Unprotected particles adhere to synthetic lipid vesicles, which in turn enhances membrane permeability and leads to vesicle collapse. Furthermore, particle-particle coalescence leads to the formation of gel-like DNA aggregates that envelop surviving vesicles. This response is reminiscent of pathogen immobilisation through immune cells secretion of DNA networks, as we demonstrate by trapping E. coli bacteria.

Probing roto-translational diffusion of small anisotropic colloidal particles with a bright-field microscope

Soft and biological materials are often composed of elementary constituents exhibiting an incessant roto-translational motion at the microscopic scale. Tracking this motion with a bright-field microscope becomes increasingly challenging when the particle size becomes smaller than the microscope resolution, a case which is frequently encountered. Here we demonstrate squared-gradient differential dynamic microscopy (SG-DDM) as a tool to successfully use bright-field microscopy to extract the roto-translational dynamics of small anisotropic colloidal particles, whose rotational motion cannot be tracked accurately in direct space. We provide analytical justification and experimental demonstration of the method by successful application to an aqueous suspension of peanut-shaped particles.

Disentangling collective motion and local rearrangements in 2D and 3D cell assemblies

The accurate quantification of cellular motility and of the structural changes occurring in multicellular aggregates is critical in describing and understanding key biological processes, such as wound repair, embryogenesis and cancer invasion. Current methods based on cell tracking or velocimetry either suffer from limited spatial resolution or are challenging and time-consuming, especially for three-dimensional (3D) cell assemblies. Here we propose a conceptually simple, robust and tracking-free approach for the quantification of the dynamical activity of cells via a two-step procedure. We first characterise the global features of the collective cell migration by registering the temporal stack of the acquired images. As a second step, a map of the local cell motility is obtained by performing a mean squared amplitude analysis of the intensity fluctuations occurring when two registered image frames acquired at different times are subtracted. We successfully apply our approach to cell monolayers undergoing a jamming transition, as well as to monolayers and 3D aggregates that exhibit a cooperative unjamming-via-flocking transition. Our approach is capable of disentangling very efficiently and of assessing accurately the global and local contributions to cell motility.

Myosin-driven actin-microtubule networks exhibit self-organized contractile dynamics

The cytoskeleton is a dynamic network of proteins, including actin, microtubules, and their associated motor proteins, that enables essential cellular processes such as motility, division, and growth. While actomyosin networks are extensively studied, how interactions between actin and microtubules, ubiquitous in the cytoskeleton, influence actomyosin activity remains an open question. Here, we create a network of co-entangled actin and microtubules driven by myosin II. We combine dynamic differential microscopy, particle image velocimetry, and particle tracking to show that both actin and microtubules undergo ballistic contraction with unexpectedly indistinguishable characteristics. This contractility is distinct from faster disordered motion and rupturing that active actin networks exhibit. Our results suggest that microtubules enable self-organized myosin-driven contraction by providing flexural rigidity and enhanced connectivity to actin networks. Beyond the immediate relevance to cytoskeletal dynamics, our results shed light on the design of active materials that can be precisely tuned by the network composition.

Multiple dynamic regimes in a coarsening foam

Intermittent dynamics driven by internal stress imbalances in disordered systems is a fascinating yet poorly understood phenomenon. Here, we study it for a coarsening foam. By exploiting differential dynamic microscopy and particle tracking we determine the dynamical characteristics of the foam at different ages in reciprocal and direct space, respectively. At all wavevectors q investigated, the intermediate scattering function exhibits a compressed exponential decay. However, the access to unprecedentedly small values of q highlights the existence of two distinct regimes for the q-dependence of the foam relaxation rate Γ(q). At high q, Γ(q) ∼ q consistent with directionally-persistent and intermittent bubble displacements. At low q, we find the surprising scaling Γ(q) ∼ q ^δ , with δ = 1.6 ± 0.2. The analysis of the bubble displacement distribution in real space reveals the existence of a displacement cut-off of the order of the bubble diameter. Introducing such cut-off length in an existing model, describing stress-driven dynamics in disordered systems, fully accounts for the observed behavior in direct and reciprocal space.

Dynamic Light Scattering Measurements for Soft Materials on Solid Substrates: Employing Evanescent-wave Illumination and Dark-field Collection with a High Numerical Aperture Microscope Objective

We developed an instrument that allows us to measure dynamic light scattering from soft materials on solid substrates by avoiding strong background due to the reflection light from substrates. In the instrument, samples on substrates are illuminated by evanescent-light field and the resultant scattered light from the samples is collected with a dark-field optical configuration by employing a high numerical aperture microscope objective. We applied the instrument to measure the dynamic properties of supported lipid bilayers (SLBs), which have been widely utilized in industries as functional materials such as biosensors. From the time course of the scattered light from the SLBs, the power spectrum with the broad peak ranging from 10 to 20 kHz is observed. The use of the microscope objectives enables us to apply the instrument to future light scattering imaging for dynamic properties of soft materials supported on various substrates by combining with conventional microscope systems.

Adaptable DNA interactions regulate surface triggered self assembly

DNA-mediated multivalent interactions between colloidal particles have been extensively applied for their ability to program bulk phase behaviour and dynamic processes. Exploiting the competition between different types of DNA-DNA bonds, here we experimentally demonstrate the selective triggering of colloidal self-assembly in the presence of a functionalised surface, which induces changes in particle-particle interactions. Besides its relevance to the manufacturing of layered materials with controlled thickness, the intrinsic signal-amplification features of the proposed interaction scheme make it valuable for biosensing applications.

Characterization of active matter in dense suspensions with heterodyne laser Doppler velocimetry

We present a novel approach for characterizing the properties and performance of active matter in dilute suspension as well as in crowded environments. We use Super-Heterodyne Laser-Doppler-Velocimetry (SH-LDV) to study large ensembles of catalytically active Janus particles moving under UV illumination. SH-LDV facilitates a model-free determination of the swimming speed and direction, with excellent ensemble averaging. In addition, we obtain information on the distribution of the catalytic activity. Moreover, SH-LDV operates away from walls and permits a facile correction for multiple scattering contributions. It thus allows for studies of concentrated suspensions of swimmers or of systems where swimmers propel actively in an environment crowded by passive particles. We demonstrate the versatility and the scope of the method with a few selected examples. We anticipate that SH-LDV complements established methods and paves the way for systematic measurements at previously inaccessible boundary conditions.

Emergence of Multiscale Dynamics in Colloidal Gels

To gain insight into the kinetics of colloidal gel evolution at low particle volume fractions ϕ, we utilize differential dynamic microscopy to investigate particle aggregation, geometric percolation, and the subsequent transition to nonergodic dynamics. We report the emergence of unexpectedly rich multiscale dynamics upon the onset of nonergodicity, which separates the wave vectors q into three different regimes. In the high-q domain, the gel exhibits ϕ-independent internal vibrations of fractal clusters. The intermediate-q domain is dominated by density fluctuations at the length scale of the clusters, as evidenced by the q independence of the relaxation time τ. In the low-q domain, the scaling of τ as q^{-3} suggests that the network appears homogeneous. The transitions between these three regimes introduce two characteristic length scales, distinct from the cluster size.

Particle diffusion in extracellular hydrogels

Hyaluronic acid is an abundant polyelectrolyte in the human body that forms extracellular hydrogels in connective tissues. It is essential for regulating tissue biomechanics and cell-cell communication, yet hyaluronan overexpression is associated with pathological situations such as cancer and multiple sclerosis. Due to its enormous molecular weight (in the range of millions of Daltons), accumulation of hyaluronan hinders transport of macromolecules including nutrients and growth factors through tissues and also hampers drug delivery. However, the exact contribution of hyaluronan to tissue penetrability is poorly understood due to the complex structure and molecular composition of tissues. Here we reconstitute biomimetic hyaluronan gels and systematically investigate the effects of gel composition and crosslinking on the diffusion of microscopic tracer particles. We combine ensemble-averaged measurements via differential dynamic microscopy with single-particle tracking. We show that the particle diffusivity depends on the particle size relative to the network pore size and also on the stress relaxation dynamics of the network. We furthermore show that addition of collagen, the other major biopolymer in tissues, causes the emergence of caged particle dynamics. Our findings are useful for understanding macromolecular transport in tissues and for designing biomimetic extracellular matrix hydrogels for drug delivery and tissue regeneration.

Uncovering the dynamic precursors to motor-driven contraction of active gels

Cells and tissues have the remarkable ability to actively generate the forces required to change their shape. This active mechanical behavior is largely mediated by the actin cytoskeleton, a crosslinked network of actin filaments that is contracted by myosin motors. Experiments and active gel theories have established that the length scale over which gel contraction occurs is governed by a balance between molecular motor activity and crosslink density. By contrast, the dynamics that govern the contractile activity of the cytoskeleton remain poorly understood. Here we investigate the microscopic dynamics of reconstituted actin-myosin networks using simultaneous real-space video microscopy and Fourier-space dynamic light scattering. Light scattering reveals different regimes of microscopic dynamics as a function of sample age. We uncover two dynamical precursors that precede macroscopic gel contraction. One is characterized by a progressive acceleration of stress-induced rearrangements, while the other consists of sudden, heterogeneous rearrangements. Intriguingly, our findings suggest a qualitative analogy between self-driven rupture and collapse of active gels and the delayed rupture of passive gels observed in earlier studies of colloidal gels under external loads.

Measuring capillary wave dynamics using differential dynamic microscopy

The interface between two fluids is roughened by thermally excited capillary waves. By using colloid-polymer systems which exhibit liquid-gas phase separation, the time and length scales of capillary waves become accessible to optical microscopy methods. Here, we study such a system using bright-field optical microscopy combined with a novel extension of differential dynamic microscopy. With differential dynamic microscopy, we analyze images in order to determine the decay time of interfacial fluctuations spanning wavevectors from 0.1 to 1 μm-1. We find capillary velocities on the order of 0.1 μm s-1 that depend on the sample composition in expected ways and that match values from the literature. This work demonstrates the first application of differential dynamic microscopy to the study of interfacial dynamics.

Reduced Salivary Mucin Binding and Glycosylation in Older Adults Influences Taste in an In Vitro Cell Model

Background: Taste loss is a significant problem in older adults, affecting quality of life and nutrition. Altered salivary rheology and loss of mucin function may contribute to taste loss by reducing mucosal defences in the oral cavity, impairing sensitivity to oral stimulants. This study aimed to investigate the effects of salivary rheology on taste loss in ageing. Salivary mucin glycosylation and binding to the oral epithelium was investigated in older and younger adults. A cell-based model was utilised to consider the role of saliva in taste loss. Methods: Human subjects aged >60 years (n = 25) and 18–30 (n = 30) provided saliva samples which were analysed for viscosity, mucin composition and mucin binding to oral epithelial cells (TR146/MUC1). Oral epithelial cells (TR146/MUC1 and SCC090) provided models for taste receptor activation. Results: Reduced levels and sialylation of MUC7 were evident in saliva of older adults which may lead to reduced viscoelasticity, while viscosity is unaffected. Impaired muco-adhesion of saliva from older adults was also observed. Saliva from older adults facilitated the bitter taste receptor activation less well than saliva from younger adults. The causes of taste dysfunction in older adults are unknown, but this study supports a role of saliva in facilitating the activation of taste receptors.

Phenotyping ciliary dynamics and coordination in response to CFTR-modulators in Cystic Fibrosis respiratory epithelial cells

Personalized approaches for systematically assessing ciliary beat dynamics and for drug testing would improve the challenging task of diagnosing and treating respiratory disorders. In this pilot study, we show how multiscale differential dynamic microscopy (multi-DDM) can be used to characterize collective ciliary beating in a non-biased automated manner. We use multi-DDM to assess the efficacy of different CFTR-modulating drugs in human airway epithelial cells derived from subjects with cystic fibrosis (ΔF508/ΔF508 and ∆F508/-) based on ciliary beat frequency and coordination. Similar to clinical observations, drug efficacy is variable across donors, even within the same genotype. We show how our assay can quantitatively identify the most efficient drugs for restoring ciliary beating for each individual donor. Multi-DDM provides insight into ciliary beating responses following treatment with drugs, and has application in the broader context of respiratory disease and for drug screening.

Personalized approaches to diagnosis and treatment monitoring could improve the management of cystic fibrosis patients. Here the authors show that multiscale differential dynamic microscopy can assess changes in cilia beating dynamics and coordination in patient-derived airway epithelial cells, in response to different CFTR-modulating drugs, in a patient-specific manner.

Probing shear-induced rearrangements in Fourier space. II. Differential dynamic microscopy

We discuss in two companion papers how Fourier-space measurements may be coupled to rheological tests in order to elucidate the relationship between mechanical properties and microscopic dynamics in soft matter. In this second companion paper, we focus on Differential Dynamic Microscopy (DDM) under shear. We highlight the analogies and the differences with dynamic light scattering coupled to rheology, providing a theoretical approach and practical guidelines to separate the contributions to DDM arising from the affine and the non-affine part of the microscopic displacement field. We show that in DDM under shear the coherence of the illuminating source plays a key role, determining the effective sample thickness that is probed. Our theoretical analysis is validated by experiments on 2D samples and 3D gels.

Microliter viscometry using a bright-field microscope: η-DDM

The rheological properties of a medium can be inferred from the Brownian motion of colloidal tracer particles using the microrheology procedure. The tracer motion can be characterized by the mean-squared displacement (MSD). It can be calculated from the intermediate scattering function determined by Differential Dynamic Microscopy (DDM). Here we show that DDM together with the empirical Cox-Merz rule is particularly suited to measure the steady-shear viscosity, i.e. the viscosity towards zero frequency, due to its ability to provide reliable information on long time and length scales and hence small frequencies. This method, η-DDM, is tested and illustrated using three different systems: Newtonian fluids (glycerol-water mixtures), colloidal suspensions (protein samples) and a viscoelastic polymer solution (aqueous poly(ethylene oxide) solution). These tests show that common lab equipment, namely a bright-field optical microscope, can be used as a convenient and reliable microliter viscometer. Because η-DDM requires much smaller sample volumes than classical rheometry, only a few microliters, it is particularly useful for biological and soft matter systems.

Dark field differential dynamic microscopy enables accurate characterization of the roto-translational dynamics of bacteria and colloidal clusters

Micro- and nanoscale objects with anisotropic shape are key components of a variety of biological systems and inert complex materials, and represent fundamental building blocks of novel self-assembly strategies. The time scale of their thermal motion is set by their translational and rotational diffusion coefficients, whose measurement may become difficult for relatively large particles with small optical contrast. Here we show that dark field differential dynamic microscopy is the ideal tool for probing the roto-translational Brownian motion of anisotropic shaped particles. We demonstrate our approach by successful application to aqueous dispersions of non-motile bacteria and of colloidal aggregates of spherical particles.

Different scenarios of dynamic coupling in glassy colloidal mixtures

The composition of mixtures determines the mechanism of glass formation and dynamic coupling of different species.

The hitchhiker's guide to quantitative diffusion measurements

Quantitative comparison of three widely used techniques for diffusion measurements, implemented on a light sheet microscope.

Formation of a transient amorphous solid in low density aqueous charged sphere suspensions

Colloidal glasses formed from hard spheres, nearly hard spheres, ellipsoids and platelets or their attractive variants, have been studied in great detail. Complementing and constraining theoretical approaches and simulations, the many different types of model systems have significantly advanced our understanding of the glass transition in general. Despite their early prediction, however, no experimental charged sphere glasses have been found at low density, where the competing process of crystallization prevails. We here report the formation of a transient amorphous solid formed from charged polymer spheres suspended in thoroughly deionized water at volume fractions of 0.0002-0.01. From optical experiments, we observe the presence of short-range order and an enhanced shear rigidity as compared to the stable polycrystalline solid of body centred cubic structure. On a density dependent time scale of hours to days, the amorphous solid transforms into this stable structure. We further present preliminary dynamic light scattering data showing the evolution of a second slow relaxation process possibly pointing to a dynamic heterogeneity known from other colloidal glasses and gels. We compare our findings to the predicted phase behaviour of charged sphere suspensions and discuss possible mechanisms for the formation of this peculiar type of colloidal glass.

Image windowing mitigates edge effects in Differential Dynamic Microscopy

Differential Dynamic Microscopy (DDM) analyzes traditional real-space microscope images to extract information on sample dynamics in a way akin to light scattering, by decomposing each image in a sequence into Fourier modes, and evaluating their time correlation properties. DDM has been applied in a number of soft-matter and colloidal systems. However, objects observed to move out of the microscope's captured field of view, intersecting the edges of the acquired images, can introduce spurious but significant errors in the subsequent analysis. Here we show that application of a spatial windowing filter to images in a sequence before they enter the standard DDM analysis can reduce these artifacts substantially. Moreover, windowing can increase significantly the accessible range of wave vectors probed by DDM, and may further yield unexpected information, such as the size polydispersity of a colloidal suspension.