Differential Dynamic Microscopy Research Articles

Topological DNA blends exhibit resonant deformation fields and strain propagation dynamics tuned by steric constraints

Understanding how polymers deform in response to local stresses and strains, and how strains propagate from a local disturbance, are grand challenges in wide-ranging fields from materials manufacturing to cell mechanics. These dynamics are particularly complex for blends of polymers of distinct topologies, for which several different species-dependent mechanisms may contribute. Here, we use OpTiDDM (Optical-Tweezers-integrating-Differential-Dynamic-Microscopy) to elucidate deformation fields and propagation dynamics of binary blends of linear, ring and supercoiled DNA of varying sizes. We reveal robust non-monotonic dependence of strain alignment and superdiffusive transport with strain rate. However, peak alignment and superdiffusivity are surprisingly decoupled, occurring at different strain rates resonant with the distinct relaxation rates of the different topologies. Despite this universal resonance, we find that strain propagation of ring-linear blends is dictated by entanglements while supercoiled-ring blends are governed by Rouse dynamics. Our results capture critical subtleties in propagation and deformation dynamics of topological blends, shedding new light on the governing physics and offering a route towards decoupled tuning of response features. We anticipate our approach to be broadly generalizable to mapping the deformation dynamics of polymer blends, with an eye towards bottom-up bespoke materials design. Statement of SignificanceIn biology and in manufacturing, biomaterials are often subject to localized and spatially nonuniform strains and stresses. Yet, understanding the extent to which strains are absorbed, distributed, or propagated across different spatiotemporal scales remains a grand challenge. Here, we combine optical tweezers with differential dynamic microscopy to elucidate deformation fields and propagation dynamics of blends of linear, ring and supercoiled DNA, revealing robust non-monotonic trends and decoupling of strain alignment and superdiffusivity, and capturing critical subtleties in propagation and deformation dynamics. Our results, shedding important new physical insight to guide decoupled tuning of response features, may be leveraged to map the deformation dynamics of wide-ranging systems of biopolymers and other macromolecules, with an eye towards bottom-up bespoke biomaterials design.

Anomalous relaxation of coarsening foams with viscoelastic continuous phases.

We investigate the ultraslow structural relaxation of ageing foams with rheologically tunable continuous phases. We probe the bubble dynamics associated with pressure-driven foam coarsening using differential dynamic microscopy, which allows characterising the sample dynamics in reciprocal space with imaging experiments. Similar to other out-of-equilibrium jammed soft systems, these foams exhibit compressed exponential relaxations, with a ballistic-like linear dependency of the relaxation rate on the scattering wavevector. By tuning the rheology of the continuous phase, we observe changes in the relaxation shape, where stiffer matrices yield larger compression exponents. Our results corroborate recent real-space observations obtained using bubble tracking, providing a comprehensive overview of structural relaxation in these complex systems, both in direct and reciprocal space.

Ab initio uncertainty quantification in scattering analysis of microscopy.

Estimating parameters from data is a fundamental problem in physics, customarily done by minimizing a loss function between a model and observed statistics. In scattering-based analysis, it is common to work in the reciprocal space. Researchers often employ their domain expertise to select a specific range of wave vectors for analysis, a choice that can vary depending on the specific case. We introduce another paradigm that defines a probabilistic generative model from the beginning of data processing and propagates the uncertainty for parameter estimation, termed the ab initio uncertainty quantification (AIUQ). As an illustrative example, we demonstrate this approach with differential dynamic microscopy (DDM) that extracts dynamical information through minimizing a loss function for the squared differences of the Fourier-transformed intensities, at a selected range of wave vectors. We first show that the conventional way of estimation in DDM is equivalent to fitting a temporal variogram in the reciprocal space using a latent factor model as the generative model. Then we derive the maximum marginal likelihood estimator, which optimally weighs the information at all wave vectors, therefore eliminating the need to select the range of wave vectors. Furthermore, we substantially reduce the computational cost of computing the likelihood function without approximation, by utilizing the generalized Schur algorithm for Toeplitz covariances. Simulated studies of a wide range of dynamical systems validate that the AIUQ method improves estimation accuracy and enables model selection with automated analysis. The utility of AIUQ is also demonstrated by three distinct sets of experiments: first in an isotropic Newtonian fluid, pushing limits of optically dense systems compared to multiple particle tracking; next in a system undergoing a sol-gel transition, automating the determination of gelling points and critical exponent; and lastly, in discerning anisotropic diffusive behavior of colloids in a liquid crystal. These studies demonstrate that the new approach does not require manually selecting the wave vector range and enables automated analysis.

Label-Free Techniques for Probing Biomolecular Condensates.

Biomolecular condensates play important roles in a wide array of fundamental biological processes, such as cellular compartmentalization, cellular regulation, and other biochemical reactions. Since their discovery and first observations, an extensive and expansive library of tools has been developed to investigate various aspects and properties, encompassing structural and compositional information, material properties, and their evolution throughout the life cycle from formation to eventual dissolution. This Review presents an overview of the expanded set of tools and methods that researchers use to probe the properties of biomolecular condensates across diverse scales of length, concentration, stiffness, and time. In particular, we review recent years' exciting development of label-free techniques and methodologies. We broadly organize the set of tools into 3 categories: (1) imaging-based techniques, such as transmitted-light microscopy (TLM) and Brillouin microscopy (BM), (2) force spectroscopy techniques, such as atomic force microscopy (AFM) and the optical tweezer (OT), and (3) microfluidic platforms and emerging technologies. We point out the tools' key opportunities, challenges, and future perspectives and analyze their correlative potential as well as compatibility with other techniques. Additionally, we review emerging techniques, namely, differential dynamic microscopy (DDM) and interferometric scattering microscopy (iSCAT), that have huge potential for future applications in studying biomolecular condensates. Finally, we highlight how some of these techniques can be translated for diagnostics and therapy purposes. We hope this Review serves as a useful guide for new researchers in this field and aids in advancing the development of new biophysical tools to study biomolecular condensates.

Protein biomarker detection via differential dynamic microscopy

We demonstrate a pioneering application of differential dynamic microscopy (DDM) for disease diagnosis by monitoring the dynamic signal of probe beads. When the target antibody binds to our sensitized probe beads, it allows these originally non-fluorescent beads to be indirectly decorated with fluorescently labeled secondary antibodies. Using standard epi-fluorescence microscopy without the need for purification, DDM reliably detects the resulting increase in fluorescence signal from the probe beads. It effectively discerns this signal from the background, which includes residual free fluorescent secondary antibodies. As a proof-of-concept, polystyrene beads (500 nm in diameter) were conjugated with the receptor binding domain of SARS-CoV-2’s spike protein to quantify immunoglobulin G1-specific antibodies against it in three different media of increasing complexity (phosphate buffer, model saliva and fetal bovine serum). Our results show that as the medium becomes more complex, more dilution and/or longer incubation time may be needed to overcome the competition effect between the target and interfering proteins. By optimizing imaging parameters and sample preparation we could surpass clinically relevant limits of detection in both saliva and serum samples. In contrast to conventional diagnostic techniques including ELISA and PCR, DDM brings many advantages including simplicity of the preparation protocol, high speed, and versatility without requiring very expensive or complicated equipment. As such, DDM-based disease diagnostics has the potential to be utilized in many laboratories, especially in remote regions with limited resources and point-of-use applications may also be feasible by miniaturizing the imaging setup.

Specialized proresolving mediator resolvin E1 corrects the altered cystic fibrosis nasal epithelium cilia beating dynamics

In cystic fibrosis (CF), impaired mucociliary clearance leads to chronic infection and inflammation. However, cilia beating features in a CF altered environment, consisting of dehydrated airway surface liquid layer and abnormal mucus, have not been fully characterized. Furthermore, acute inflammation is normally followed by an active resolution phase requiring specialized proresolving lipid mediators (SPMs) and allowing return to homeostasis. However, altered SPMs biosynthesis has been reported in CF. Here, we explored cilia beating dynamics in CF airways primary cultures and its response to the SPMs, resolvin E1 (RvE1) and lipoxin B4 (LXB4). Human nasal epithelial cells (hNECs) from CF and non-CF donors were grown at air-liquid interface. The ciliary beat frequency, synchronization, orientation, and density were analyzed from high-speed video microscopy using a multiscale Differential Dynamic Microscopy algorithm and an in-house developed method. Mucins and ASL layer height were studied by qRT-PCR and confocal microscopy. Principal component analysis showed that CF and non-CF hNEC had distinct cilia beating phenotypes, which was mostly explained by differences in cilia beat organization rather than frequency. Exposure to RvE1 (10 nM) and to LXB4 (10 nM) restored a non-CF-like cilia beating phenotype. Furthermore, RvE1 increased the airway surface liquid (ASL) layer height and reduced the mucin MUC5AC thickness. The calcium-activated chloride channel, TMEM16A, was involved in the RvE1 effect on cilia beating, hydration, and mucus. Altogether, our results provide evidence for defective cilia beating in CF airway epithelium and a role of RvE1 and LXB4 to restore the main epithelial functions involved in the mucociliary clearance.

Convolutional neural networks applied to differential dynamic microscopy reduces noise when quantifying heterogeneous dynamics.

Differential dynamic microscopy (DDM) typically relies on movies containing hundreds or thousands of frames to accurately quantify motion in soft matter systems. Using movies much shorter in duration produces noisier and less accurate results. This limits the applicability of DDM to situations where the dynamics are stationary over extended times. Here, we investigate a method to denoise the DDM process, particularly suited to when a limited number of imaging frames are available or when dynamics are quickly evolving in time. We use a convolutional neural network encoder-decoder (CNN-ED) model to reduce the noise in the intermediate scattering function that is computed via DDM. We demonstrate this approach of combining machine learning and DDM on samples containing diffusing micron-sized colloidal particles. We quantify how the particles' diffusivities change over time as the fluid they are suspended in gels. We also quantify how the diffusivity of particles varies with position in a sample containing a viscosity gradient. These test cases demonstrate how studies of non-equilibrium dynamics and high-throughput screens could benefit from a method to denoise the outputs of DDM.

Enzymatic cleaving of entangled DNA rings drives scale-dependent rheological trajectories.

DNA, which naturally occurs in linear, ring, and supercoiled topologies, frequently undergoes enzyme-driven topological conversion and fragmentation in vivo, enabling it to perform a variety of functions within the cell. In vitro, highly concentrated DNA polymers form entanglements that yield viscoelastic properties dependent on the topologies and lengths of the DNA. Enzyme-driven alterations of DNA size and shape therefore offer a means of designing active materials with programmable viscoelastic properties. Here, we incorporate multi-site restriction endonucleases into dense DNA solutions to linearize and fragment circular DNA molecules. We pair optical tweezers microrheology with differential dynamic microscopy and single-molecule tracking to measure the linear and nonlinear viscoelastic response and transport properties of entangled DNA solutions over a wide range of spatiotemporal scales throughout the course of enzymatic digestion. We show that, at short timescales, relative to the relaxation timescales of the polymers, digestion of these 'topologically-active' fluids initially causes an increase in elasticity and relaxation times followed by a gradual decrease. Conversely, for long timescales, linear viscoelastic moduli exhibit signatures of increasing elasticity. DNA diffusion, likewise, becomes increasingly slowed, in direct opposition to the short-time behavior. We hypothesize that this scale-dependent rheology arises from the population of small DNA fragments, which increases as digestion proceeds, driving self-association of larger fragments via depletion interactions, giving rise to slow relaxation modes of clusters of entangled chains, interspersed among shorter unentangled fragments. While these slow modes likely dominate at long times, they are presumably frozen out in the short-time limit, which instead probes the faster relaxation modes of the unentangled population.

Mapping deformation dynamics to composition of topologically-active DNA blends.

Blends of circular and linear polymers have fascinated researchers for decades, and the role of topology on their stress response and dynamics remains fervently debated. While linear polymers adopt larger coil sizes and form stronger, more pervasive entanglements than their circular counterparts, threading of circular polymers by linear chains can introduce persistent constraints that dramatically decrease mobility, leading to emergent rheological properties in blends. However, the complex interplay between topology-dependent polymer overlap and threading propensity, along with the large amounts of material required to sample many compositions, has limited the ability to experimentally map stress response to composition with high resolution. Moreover, the role of supercoiling on the response of circular-linear blends remains poorly understood. Here, we leverage in situ enzymatic topological conversion to map the deformation dynamics of DNA blends with over 70 fractions of linear, ring and supercoiled molecules that span the phase space of possible topological compositions. We use OpTiDDM (optical tweezers integrating differential dynamic microscopy) to map strain-induced deformation dynamics to composition, revealing that strain-coupling, quantified by superdiffusive dynamics that are aligned with the strain, is maximized for blends with comparable fractions of ring and linear polymers. Increasing the supercoiled fraction dramatically reduces strain-coupling, while converting rings to linear chains offers more modest coupling reduction. We demonstrate that these results are a direct consequence of the interplay between increasing polymer overlap and decreasing threading probability as circular molecules are converted to linear chains, with a careful balance achieved for blends with ample ring fractions but devoid of supercoiled molecules.

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.

Protein Sizing with Differential Dynamic Microscopy

Protein Sizing with Differential Dynamic Microscopy

Kinesin and myosin motors compete to drive rich multiphase dynamics in programmable cytoskeletal composites.

The cellular cytoskeleton relies on diverse populations of motors, filaments, and binding proteins acting in concert to enable nonequilibrium processes ranging from mitosis to chemotaxis. The cytoskeleton's versatile reconfigurability, programmed by interactions between its constituents, makes it a foundational active matter platform. However, current active matter endeavors are limited largely to single force-generating components acting on a single substrate-far from the composite cytoskeleton in cells. Here, we engineer actin-microtubule (MT) composites, driven by kinesin and myosin motors and tuned by crosslinkers, to ballistically restructure and flow with speeds that span three orders of magnitude depending on the composite formulation and time relative to the onset of motor activity. Differential dynamic microscopy analyses reveal that kinesin and myosin compete to delay the onset of acceleration and suppress discrete restructuring events, while passive crosslinking of either actin or MTs has an opposite effect. Our minimal advection-diffusion model and spatial correlation analyses correlate these dynamics to structure, with motor antagonism suppressing reconfiguration and demixing, while crosslinking enhances clustering. Despite the rich formulation space and emergent formulation-dependent structures, the nonequilibrium dynamics across all composites and timescales can be organized into three classes-slow isotropic reorientation, fast directional flow, and multimode restructuring. Moreover, our mathematical model demonstrates that diverse structural motifs can arise simply from the interplay between motor-driven advection and frictional drag. These general features of our platform facilitate applicability to other active matter systems and shed light on diverse ways that cytoskeletal components can cooperate or compete to enable wide-ranging cellular processes.

Mesoscopic Characterization of the Early Stage of the Glucono-δ-Lactone-Induced Gelation of Milk via Image Analysis Techniques.

We provide a method for quantifying the kinetics of gelation in milk acidified with glucono-δ-lactone (GDL) using image analysis techniques, particle image velocimetry (PIV), differential variance analysis (DVA) and differential dynamic microscopy (DDM). The gelation of the milk acidified with GDL occurs through the aggregation and subsequent coagulation of the casein micelles as the pH approaches the isoelectric point of the caseins. The gelation of the acidified milk with GDL is an important step in the production of fermented dairy products. PIV qualitatively monitors the average mobility of fat globules during gelation. The gel point estimated by PIV is in good agreement with that obtained by rheological measurement. DVA and DDM methods reveal the relaxation behavior of fat globules during gelation. These two methods make it possible to calculate microscopic viscosity. We also extracted the mean square displacement (MSD) of the fat globules, without following their movement, using the DDM method. The MSD of fat globules shifts to sub-diffusive behavior as gelation progresses. The fat globules used as probes show the change in matrix viscoelasticity caused by the gelling of the casein micelles. Image analysis and rheology can be used complementarily to study the mesoscale dynamics of the milk gel.

Mechanics and stress propagation in non-equilibrium cytoskeleton composites

The cytoskeleton is able to access a wide range of material properties to facilitate cellular processes in a controlled and precise manner via active restructuring and reconfiguration of its constituents by ATP-consuming motor proteins. In vitro cytoskeleton composites have been shown to exhibit tunable mechanical properties, and the addition of force-generating motors to these composites induces non-equilibrium dynamics and restructuring. We characterize the effects of non-equilibrium activity on the mechanical properties of actin-microtubule composites driven by variable concentrations of kinesin motor clusters by performing optical tweezers microrheology experiments. We measure the nonlinear force response of the composites subject to cyclical strain at varied strain rates. Additionally, we measure stress propagation through the composites due to locally imposed strain using differential dynamic microscopy (DDM). We uncover a transition from dissipative to stiffening force response of the composites at mesoscopic lengthscales, with a non-monotonic dependence on kinesin concentration. Our work sheds light on how active restructuring by motor proteins tunes the material response of the cytoskeleton to local stresses, enabling diverse processes such as shape change, motility, and repair.

Impact of cell-sized confinement on particle transport within a motor-driven cytoskeletal network.

Intracellular transport of small particles and macromolecules is affected by the degree of crowding, confinement, and motor-driven activity within the cell. In vitro studies have examined how transport dynamics depend on each of these factors. But studies have primarily focused on these factors in isolation. Previously, we showed how crowding and confinement synergistically couple to slow the diffusion of DNA molecules. Here, we explore the combined effects of crowding by a composite network of actin and microtubule filaments, activity driven by molecular motors, and confinement by a lipid membrane to cell-sized volumes. We quantify transport of tracer particles within this tunable in vitro environment using differential dynamic microscopy (DDM) and single particle tracking. We simultaneously measure the dynamics and spatial organization of the composite network to link transport dynamics to network properties. To what degree tracers exhibit subdiffusive motion due to caging within the network mesh or superdiffusive motion due to motor activity depends on network composition, motor concentration, and confinement size.

Optical tweezers and DDM characterize time-varying strain fields in kinesin-driven cytoskeleton composites.

The cytoskeleton continuously self-generates forces and reconfigures itself - in part by motor proteins pushing and pulling on the comprising filaments - to enable diverse mechanical responses to local stresses and strains. We previously showed that kinesin-microtubule interactions lead to dynamics ranging from uncorrelated isotropic fluctuations, to mesoscale restructuring, to bulk flow of actin-microtubule composites. These non-equilibrium dynamics mediate varying degrees of de-mixing, clustering and bundling of originally interpenetrating networks of actin and microtubules. Here, we combine optical tweezers microrheology and fluorescence microscopy to visualize the dynamical response and strain field of composites subject to cyclic mesoscale straining. To characterize the time-varying filament deformations and stress propagation we use space- and time-resolved differential dynamic microscopy (DDM) for quantifying the strain alignment, speed, periodicity, and dissipation of the network dynamics. We show that intermediate concentrations of kinesin motors lead to the most pronounced strain alignment and stress propagation while both low and high motor concentrations lead to more rapidly decaying response. Composite dynamics also exhibit similar emergent non-monotonic dependences on strain speed owing to the different relaxation mechanisms available to structurally-evolving composites.

Dynamic concatenation leads to anomalous transport of ring DNA in concentrated solutions.

Circular DNA polymers have been widely studied due to their biological relevance as well as the unique anomalous transport properties they exhibit in concentrated solutions and blends with linear DNA. In cells, topoisomerase II relaxes torsional strain in circular DNA by cutting and then reconnecting one of the strands of the double-stranded polymer, enabling replication, transcription, and repair. When topoisomerase II acts on nicked circular DNA at high concentration, the relaxed rings can concatenate, forming Olympic ring structures reminiscent of kinetoplasts. The rate of topoisomerase activity as well as the concentration and size of the DNA can tune the nonequilibrium dynamics and conformations of the concatemers. Here, we visualize the fluorescent-labeled DNA rings comprising the concatemers and use particle tracking and differential dynamic microscopy to characterize the dynamics and time-varying size and shape of the actively linking and unlinking molecules. Beyond the insight our work provides to biological processes mediated by active restructuring of DNA, the complex fluids we engineer and study may have applications in the design of biocompatible active materials for cellular repair, toxin filtration and drug delivery.

Effects of Molecular Weight and Surface Interactions on Polymer Diffusion in Confinement

Understanding the transport and thermodynamics of polymers in confined spaces is helpful for many separation processes like water purification, drug delivery, and oil recovery. Specifically, for water purification, dextran has been used as a "model" foulant. Uncovering how these polymers interact in confinement can reduce the fouling of organic membranes and will lead to better separation processes overall. We have determined the diffusion coefficient, D, of dextran and sodium polyacrylate in convex lens-induced confinement using differential dynamic microscopy. In this setup, the gap height ranges continuously from 0.077-21.8 μm. It was found that polymer diffusion becomes slower in higher confinement, which is consistent with a change in the increase of the hydrodynamic resistance to macromolecule motion and depends on the surface properties. These findings indicate that dextran diffusion changes in confinement and can lead to a better understanding of separation processes.

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.

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.