Static and dynamic errors in particle tracking microrheology

Cell-Material Interactions in Covalent Adaptable Thioester Hydrogels

Covalent adaptable networks (CANs) are polymeric networks with cross-links that can break and reform in response to external stimuli, including pH, shear, and temperature, making them potential materials for use as injectable cell delivery vehicles. In the native niche, cells rearrange the extracellular matrix (ECM) to undergo basic functions including migration, spreading, and proliferation. Bond rearrangement enables these hydrogels to mimic viscoelastic properties of the native ECM which promote migration and delivery from the material to the native tissue. In this work, we characterize thioester CANs to inform their design as effective cell delivery vehicles. Using bulk rheology, we characterize the rearrangement of these networks when they are subjected to strain, which mimics the strain applied by a syringe, and using multiple particle tracking microrheology (MPT) we measure cell-mediated remodeling of the pericellular region. Thioester networks are formed by photopolymerizing 8-arm poly(ethylene glycol) (PEG)-thiol and PEG-thioester norbornene. Bulk rheology measures scaffold properties during low and high strain and demonstrates that thioester scaffolds can recover rheological properties after high strain is applied. We then 3D encapsulated human mesenchymal stem cells (hMSCs) in thioester scaffolds. Using MPT, we characterize degradation in the pericellular region. Encapsulated hMSCs degrade these scaffolds within ≈4 days post-encapsulation. We hypothesize that this degradation is mainly due to cytoskeletal tension that cells apply to the matrix, causing adaptable thioester bonds to rearrange, leading to degradation. To verify this, we inhibited cytoskeletal tension using blebbistatin, a myosin-II inhibitor. Blebbistatin-treated cells can degrade these networks only by secreting enzymes including esterases. Esterases hydrolyze thioester bonds, which generate free thiols, leading to bond exchange. Around treated cells, we measure a decrease in the extent of pericellular degradation. We also compare cell area, eccentricity, and speed of untreated and treated cells. Inhibiting cytoskeletal tension results in significantly smaller cell area, more rounded cells, and lower cell speeds when compared to untreated cells. Overall, this work shows that cytoskeletal tension plays a major role in hMSC-mediated degradation of thioester networks. Cytoskeletal tension is also important for the spreading and motility of hMSCs in these networks. This work informs the design of thioester scaffolds for tissue regeneration and cell delivery.

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.

Direct measurements & simplified models of colloidal interactions & diffusion with adsorbed macromolecules

We report total internal reflection microscopy measurements of 3D trajectories of ensembles of micron sized colloidal particles near interfaces with and without adsorbed macromolecules. Evanescent wave scattering reveals nanometer scale motion normal to planar surfaces and sub-diffraction limit lateral motion is resolved via image analysis. Equilibrium and non-equilibrium analyses of particle trajectories reveal self-consistent position dependent energies (energy landscapes) and position dependent diffusivities (diffusivity landscapes) both perpendicular and parallel to interfaces. For bare colloids and surfaces, electrostatic and hydrodynamic interactions are accurately quantified with established analytical theories. For colloids and surfaces with adsorbed macromolecules, conservative forces are accurately quantified with models for interactions between brush layers, whereas directly measured position dependent diffusivities require novel models of spatially varying permeability within adsorbed layers. Agreement between spatially resolved interactions and diffusivities and rigorous simplified models provide a basis to consistently interpret, predict, and design colloidal transport in the presence of adsorbed macromolecules for diverse applications.

A Rheological Study on the Effect of Tethering Pro- and Anti-Inflammatory Cytokines into Hydrogels on Human Mesenchymal Stem Cell Migration, Degradation, and Morphology

Polymer-peptide hydrogels are being designed as implantable materials that deliver human mesenchymal stem cells (hMSCs) to treat wounds. Most wounds can progress through the healing process without intervention. During the normal healing process, cytokines are released from the wound to create a concentration gradient, which causes directed cell migration from the native niche to the wound site. Our work takes inspiration from this process and uniformly tethers cytokines into the scaffold to measure changes in cell-mediated degradation and motility. This is the first step in designing cytokine concentration gradients into the material to direct cell migration. We measure changes in rheological properties, encapsulated cell-mediated pericellular degradation and migration in a hydrogel scaffold with covalently tethered cytokines, either tumor necrosis factor-α (TNF-α) or transforming growth factor-β (TGF-β). TNF-α is expressed in early stages of wound healing causing an inflammatory response. TGF-β is released in later stages of wound healing causing an anti-inflammatory response in the surrounding tissue. Both cytokines cause directed cell migration. We measure no statistically significant difference in modulus or the critical relaxation exponent when tethering either cytokine in the polymeric network without encapsulated hMSCs. This indicates that the scaffold structure and rheology is unchanged by the addition of tethered cytokines. Increases in hMSC motility, morphology and cell-mediated degradation are measured using a combination of multiple particle tracking microrheology (MPT) and live-cell imaging in hydrogels with tethered cytokines. We measure that tethering TNF-α into the hydrogel increases cellular remodeling on earlier days postencapsulation and tethering TGF-β into the scaffold increases cellular remodeling on later days. We measure tethering either TGF-β or TNF-α enhances cell stretching and, subsequently, migration. This work provides rheological characterization that can be used to design new materials that present chemical cues in the pericellular region to direct cell migration.

Trajectory Analysis in Single-Particle Tracking: From Mean Squared Displacement to Machine Learning Approaches

Single-particle tracking is a powerful technique to investigate the motion of molecules or particles. Here, we review the methods for analyzing the reconstructed trajectories, a fundamental step for deciphering the underlying mechanisms driving the motion. First, we review the traditional analysis based on the mean squared displacement (MSD), highlighting the sometimes-neglected factors potentially affecting the accuracy of the results. We then report methods that exploit the distribution of parameters other than displacements, e.g., angles, velocities, and times and probabilities of reaching a target, discussing how they are more sensitive in characterizing heterogeneities and transient behaviors masked in the MSD analysis. Hidden Markov Models are also used for this purpose, and these allow for the identification of different states, their populations and the switching kinetics. Finally, we discuss a rapidly expanding field-trajectory analysis based on machine learning. Various approaches, from random forest to deep learning, are used to classify trajectory motions, which can be identified by motion models or by model-free sets of trajectory features, either previously defined or automatically identified by the algorithms. We also review free software available for some of the analysis methods. We emphasize that approaches based on a combination of the different methods, including classical statistics and machine learning, may be the way to obtain the most informative and accurate results.

The viscoelasticity of high concentration monoclonal antibodies using particle tracking microrheology

The viscoelasticity of monoclonal antibodies (mAbs) is important during their production, formulation, and drug delivery. High concentration mAbs can provide higher efficacy therapeutics (e.g., during immunotherapy) and improved efficiency during their production (economy of scale during processing). Two humanized mAbs were studied (mAb-1 and mAb-2) with differing isoelectric points. Using high speed particle tracking microrheology, we demonstrated that the mAb solutions have significant viscoelasticities above concentrations of 40 mg/ml. Power law viscoelasticity was observed over the range of time scales (10 - 4 -1 s) probed for the high concentration mAb suspensions. The terminal viscosity demonstrated an exponential dependence on mAb concentration (a modified Mooney relationship) as expected for charged stabilized Brownian colloids. Gelation of the mAbs was explored by lowering the pH of the buffer and a power law scaling of the gelation transition was observed, i.e., the exponent of the anomalous diffusion of the probe particles scaled inversely with the gelation time.

Contribution of different macromolecules to the diffusion of a 40 nm particle in Escherichia coli

Due to the high concentration of proteins, nucleic acids, and other macromolecules, the bacterial cytoplasm is typically described as a crowded environment. However, the extent to which each of these macromolecules individually affects the mobility of macromolecular complexes, and how this depends on growth conditions, is presently unclear. In this study, we sought to quantify the crowding experienced by an exogenous 40 nm fluorescent particle in the cytoplasm of E. coli under different growth conditions. By performing single-particle tracking measurements in cells selectively depleted of DNA and/or mRNA, we determined the contribution to crowding of mRNA, DNA, and remaining cellular components, i.e., mostly proteins and ribosomes. To estimate this contribution to crowding, we quantified the difference of the particle's diffusion coefficient in conditions with and without those macromolecules. We found that the contributions of the three classes of components were of comparable magnitude, being largest in the case of proteins and ribosomes. We further found that the contributions of mRNA and DNA to crowding were significantly larger than expected based on their volumetric fractions alone. Finally, we found that the crowding contributions change only slightly with the growth conditions. These results reveal how various cellular components partake in crowding of the cytoplasm and the consequences this has for the mobility of large macromolecular complexes.

Effects of monovalent and divalent cations on the rheology of entangled DNA

In this paper we investigate the effects of varying cation valency and concentration on the rheology of entangled λDNA solutions. We show that monovalent cations moderately increase the viscoelasticty of the solutions mainly by stabilising linear concatenation of λDNA "monomers" via hybridisation of their sticky ends. On the contrary, divalent cations have a far more complex and dramatic effect on the rheology of the solution and we observe evidence of inter-molecular DNA-DNA bridging by Mg2+. We argue that these results may be interesting in the context of dense solutions of single and double stranded DNA, e.g. in vivo or in biotechnology applications such as DNA origami and DNA hydrogels.

Impact of temporal resolution in single particle tracking analysis

Temporal resolution is a key parameter in the observation of dynamic processes, as in the case of single molecules motions visualized in real time in two-dimensions by wide field (fluorescence) microscopy, but a systematic investigation of its effects in all the single particle tracking analysis steps is still lacking. Here we present tools to quantify its impact on the estimation of diffusivity and of its distribution using one of the most popular tracking software for biological applications on simulated data and movies. We found important shifts and different widths for diffusivity distributions, depending on the interplay of temporal sampling conditions with various parameters, such as simulated diffusivity, density of spots, signal-to-noise ratio, lengths of trajectories, and kind of boundaries in the simulation. We examined conditions starting from the ones of experiments on the fluorescently labelled receptor p75NTR, a relatively fast-diffusing membrane receptor (diffusivity around 0.5-1 µm2/s), visualized by TIRF microscopy on the basal membrane of living cells. From the analysis of the simulations, we identified the best conditions in cases similar to these ones; considering also the experiments, we could confirm a range of values of temporal resolution suitable for obtaining reliable diffusivity results. The procedure we present can be exploited in different single particle/molecule tracking applications to find an optimal temporal resolution.

Macromolecular interactions and geometrical confinement determine the 3D diffusion of ribosome-sized particles in live Escherichia coli cells

The crowded bacterial cytoplasm is comprised of biomolecules that span several orders of magnitude in size and electrical charge. This complexity has been proposed as the source of the rich spatial organization and apparent anomalous diffusion of intracellular components, although this has not been tested directly. Here, we use biplane microscopy to track the 3D motion of self-assembled bacterial Genetically Encoded Multimeric nanoparticles (bGEMs) with tunable size (20 to 50 nm) and charge (-2160 to +1800 e) in live Escherichia coli cells. To probe intermolecular details at spatial and temporal resolutions beyond experimental limits, we also developed a colloidal whole-cell model that explicitly represents the size and charge of cytoplasmic macromolecules and the porous structure of the bacterial nucleoid. Combining these techniques, we show that bGEMs spatially segregate by size, with small 20-nm particles enriched inside the nucleoid, and larger and/or positively charged particles excluded from this region. Localization is driven by entropic and electrostatic forces arising from cytoplasmic polydispersity, nucleoid structure, geometrical confinement, and interactions with other biomolecules including ribosomes and DNA. We observe that at the timescales of traditional single molecule tracking experiments, motion appears sub-diffusive for all particle sizes and charges. However, using computer simulations with higher temporal resolution, we find that the apparent anomalous exponents are governed by the region of the cell in which bGEMs are located. Molecular motion does not display anomalous diffusion on short time scales and the apparent sub-diffusion arises from geometrical confinement within the nucleoid and by the cell boundary.

4Pi MINFLUX arrangement maximizes spatio-temporal localization precision of fluorescence emitter

We introduce MINFLUX localization with interferometric illumination through opposing objective lenses for maximizing the attainable precision in 3D-localization of single inelastic scatterers, such as fluorophores. Our 4Pi optical configuration employs three sequentially tilted counter-propagating beam pairs for illumination, each providing a narrow interference minimum of illumination intensity at the focal point. The localization precision is additionally improved by adding the inelastically scattered or fluorescence photons collected through both objective lenses. Our 4Pi configuration yields the currently highest precision per detected photon among all localization schemes. Tracking gold nanoparticles as non-blinking inelastic scatterers rendered a position uncertainty <0.4 nm3 in volume at a localization frequency of 2.9 kHz. We harnessed the record spatio-temporal precision of our 4Pi MINFLUX approach to examine the diffusion of single fluorophores and fluorescent nanobeads in solutions of sucrose in water, revealing local heterogeneities at the nanoscale. Our results show the applicability of 4Pi MINFLUX to study molecular nano-environments of diffusion and its potential for quantifying rapid movements of molecules in cells and other material composites.

Microrheological characterisation of Cyanoflan in human blood plasma

Naturally occurring polysaccharidic biopolymers released by marine cyanobacteria are of great interest for numerous biomedical applications, such as wound healing and drug delivery. Such polymers generally exhibit high molecular weight and an entangled structure that impact the rheology of biological fluids. However, biocompatibility tests focus not so much on rheological properties as on immune response. In the present study, the rheological behaviour of native blood plasma as a function of the concentration of a cyanobacterium biopolymer is investigated via multiple particle tracking microrheology, which measures the Brownian motion of probes embedded in a sample, and cryogenic scanning electron microscope microstructural characterisation. We use Cyanoflan as the biopolymer of choice, and profit from our knowledge of its chemical structure and its exciting potential for biotechnological applications. A sol-gel transition is identified using time-concentration superposition and the power-law behaviour of the incipient network's viscoelastic response is observed in a variety of microrheological data. Our results point to rheology-based principles for blood compatibility tests by facilitating the assignment of quantitative values to specific properties, as opposed to more heuristic approaches.

Interactions of ferulic acid and ferulic acid methyl ester with endogenous proteins: Determination using the multi-methods

Ferulic acid (FA) and ferulic acid methyl ester (FAM) are important phenolic compounds in Baijiu. In this study, the interaction of FA and FAM with human serum albumin (HSA) and lysozyme (LZM) was investigated using multispectral methods and molecular dynamics simulation. FA and FAM could interact with HSA and LZM, changing the conformation and hydrophilicity of the protein. The quenching mechanisms of FA-HSA, FA-LZM, FAM-HSA, and FAM-LZM were all static-quenching. In the FA-HSA, FAM-HSA, and FA-LZM systems, the interaction forces were mainly hydrophobic interactions and hydrogen bonding. In the FAM-LZM system, the interaction forces were mainly hydrophobic interactions, hydrogen bonding, and van der Waals force. Common metal ions such as K+, Ca2+, Cu2+, Mg2+, and Mn2+ could affect the binding ability of FA and FAM to HSA and LZM. Moreover, FA and FAM could increase the stability of HSA and LZM, and the protein bound to FA/FAM was more stable than the free protein. FA and FAM had varying degrees of impact on the physiological activities of HSA and LZM. This study provides relevant information on the interactions and metabolic mechanisms of FA and its derivatives with endogenous proteins.

Optimal calibration of optical tweezers with arbitrary integration time and sampling frequencies: a general framework [Invited]

Optical tweezers (OT) have become an essential technique in several fields of physics, chemistry, and biology as precise micromanipulation tools and microscopic force transducers. Quantitative measurements require the accurate calibration of the trap stiffness of the optical trap and the diffusion constant of the optically trapped particle. This is typically done by statistical estimators constructed from the position signal of the particle, which is recorded by a digital camera or a quadrant photodiode. The finite integration time and sampling frequency of the detector need to be properly taken into account. Here, we present a general approach based on the joint probability density function of the sampled trajectory that corrects exactly the biases due to the detector's finite integration time and limited sampling frequency, providing theoretical formulas for the most widely employed calibration methods: equipartition, mean squared displacement, autocorrelation, power spectral density, and force reconstruction via maximum-likelihood-estimator analysis (FORMA). Our results, tested with experiments and Monte Carlo simulations, will permit users of OT to confidently estimate the trap stiffness and diffusion constant, extending their use to a broader set of experimental conditions.

Statistical Methods for Microrheology of Airway Mucus with Extreme Heterogeneity

The mucus lining of the human airway epithelium contains two gel-forming mucins, MUC5B and MUC5AC. During progression of cystic fibrosis (CF), mucus hyper-concentrates as its mucin ratio changes, coinciding with formation of insoluble, dense mucus flakes. We explore rheological heterogeneity of this pathology with reconstituted mucus matching three stages of CF progression and particle-tracking of 200 nm and 1 micron diameter beads. We introduce statistical data analysis methods specific to low signal-to-noise data within flakes. Each bead time series is decomposed into: (i) a fractional Brownian motion (fBm) classifier of the pure time-series signal; (ii) high-frequency static and dynamic noise; and (iii) low-frequency deterministic drift. Subsequent analysis focuses on the denoised fBm classifier ensemble from each mucus sample and bead diameter. Every ensemble fails a homogeneity test, compelling clustering methods to assess levels of heterogeneity. The first binary level detects beads within vs. outside flakes. A second binary level detects within-flake bead signals that can vs. cannot be disentangled from the experimental noise floor. We show all denoised ensembles, within- and outside-flakes, fail a homogeneity test, compelling additional clustering; next, all clusters with sufficient data fail a homogeneity test. These levels of heterogeneity are consistent with outcomes from a stochastic phase-separation process, and dictate applying the generalized Stokes-Einstein relation to each bead per cluster per sample, then frequency-domain averaging to assess rheological heterogeneity. Flakes exhibit a spectrum of gel-like and sol-like domains, outside-flake solutions a spectrum of sol-like domains, painting a rheological signature of the phase-separation process underlying flake-burdened mucus.

The power of weak, transient interactions across biology: A paradigm of emergent behavior

A growing list of diverse biological systems and their equally diverse functionalities provides realizations of a paradigm of emergent behavior. In each of these biological systems, pervasive ensembles of weak, short-lived, spatially local interactions act autonomously to convey functionalities at larger spatial and temporal scales. In this article, a range of diverse systems and functionalities are presented in a cursory manner with literature citations for further details. Then two systems and their properties are discussed in more detail: yeast chromosome biology and human respiratory mucus.

Live-cell imaging uncovers the relationship between histone acetylation, transcription initiation, and nucleosome mobility

Histone acetylation and RNA polymerase II phosphorylation are associated with transcriptionally active chromatin, but their spatiotemporal relationship in live cells remains poorly understood. To address this problem, we combine Fab-based labeling of endogenous protein modifications with single-molecule tracking to quantify the dynamics of chromatin enriched with histone H3 lysine-27 acetylation (H3K27ac) and RNA polymerase II serine-5 phosphorylation (RNAP2-Ser5ph). Our analysis reveals that chromatin enriched with these two modifications is generally separate. In these separated sites, we show that the two modifications are inversely correlated with one another on the minutes time scale and that single nucleosomes within each region display distinct and opposing dynamics on the subsecond time scale. While nucleosomes diffuse ~15% faster in chromatin enriched with H3K27ac, they diffuse ~15% slower in chromatin enriched with RNAP2-Ser5ph. These results argue that high levels of H3K27ac and RNAP2-Ser5ph are not often present together at the same place and time, but rather each marks distinct transcriptionally poised or active sites, respectively.

Characterizing rheological properties and microstructure of thioester networks during degradation

Covalent adaptable networks are designed for applications including cell and drug delivery and tissue regeneration. These applications require network degradation at physiological conditions and on a physiological timescale with microstructures that can: (1) support, protect and deliver encapsulated cells or molecules and (2) provide structure to surrounding tissue. Due to this, the evolving microstructure and rheological properties during scaffold degradation must be characterized. In this work, we characterize degradation of covalent adaptable poly(ethylene glycol) (PEG)-thioester networks with different amounts of excess thiol. Networks are formed between PEG-thiol and PEG-thioester norbornene using photopolymerization. These networks are adaptable because of a thioester exchange reaction that takes place in the presence of excess thiol. We measure degradation of PEG-thioester networks with L-cysteine using multiple particle tracking microrheology (MPT). MPT measures the Brownian motion of fluorescent probe particles embedded in a material and relates this motion to rheological properties. Using time-cure superposition (TCS), we characterize the microstructure of these networks at the gel-sol phase transition by calculating the critical relaxation exponent, n, for each network with different amounts of excess thiol. Based on the measured n values, networks formed with 0% and 50% excess thiol are tightly cross-linked and elastic in nature. While networks formed with 100% excess are similar to ideal, percolated networks, which have equal viscous and elastic components. MPT measurements during degradation of these networks also measure a non-monotonic increase in probe motility. We hypothesize that this is network rearrangement near the phase transition. We then measure macroscopic material properties including the equilibrium modulus and stress relaxation. We measure a trend in bulk network properties that agrees with the values of n. Elastic modulus and stress relaxation measurements show that networks with 50% excess thiol are more elastic compared to the other two networks. As the amount of excess thiol is increased from 0% to 50%, the networks become more elastic. Further increasing excess thiol to 100% reduces the elastically effective cross-links. We hypothesize that these properties are due to network non-idealities, resulting in networks with 50% excess thiol that are more elastic. This work characterizes dynamic rheological properties during degradation, which mimics processes that could occur during implantation. This work provides information that can be used in the future design of implantable materials enabling both the rheological properties and timescale of degradation to be specified.

Experimental observations of fractal landscape dynamics in a dense emulsion

Many soft and biological materials display so-called 'soft glassy' dynamics; their constituents undergo anomalous random motions and complex cooperative rearrangements. A recent simulation model of one soft glassy material, a coarsening foam, suggested that the random motions of its bubbles are due to the system configuration moving over a fractal energy landscape in high-dimensional space. Here we show that the salient geometrical features of such high-dimensional fractal landscapes can be explored and reliably quantified, using empirical trajectory data from many degrees of freedom, in a model-free manner. For a mayonnaise-like dense emulsion, analysis of the observed trajectories of oil droplets quantitatively reproduces the high-dimensional fractal geometry of the configuration path and its associated local energy minima generated using a computational model. That geometry in turn drives the droplets' complex random motion observed in real space. Our results indicate that experimental studies can elucidate whether the similar dynamics in different soft and biological materials may also be due to fractal landscape dynamics.

Characterizing Phase Transitions of Microfibrillated Cellulose Induced by Anionic and Cationic Surfactants

Rheological modifiers are used to tune rheology or induce phase transitions of products. Microfibrillated cellulose (MFC), a renewable material, has the potential to be used for rheological modification. However, the lack of studies on the evolution in rheological properties and structure during its phase transitions has prevented MFC from being added to consumer, fabric, and home care products. In this work, we characterize surface-oxidized MFC (OMFC), a negatively charged colloidal rod suspension. We measure the rheological properties and structure of OMFC during sol-gel phase transitions induced by either anionic or cationic surfactant using multiple particle tracking microrheology (MPT). MPT tracks the Brownian motion of fluorescent probe particles embedded in a sample, which is related to the sample's rheological properties. Using MPT, we measure that OMFC gelation evolution is dependent on the charge of the surfactant that induces the phase transition. OMFC gelation is gradual in anionic surfactant. In cationic surfactant, gelation is rapid followed by length scale-dependent colloidal fiber rearrangement. Initial OMFC concentration is directly related to how tightly associated the network is at the phase transition, with an increase in concentration resulting in a more tightly associated network with smaller pores. Bulk rheology measures that OMFC forms a stiffer structure but yields at lower strains in cationic surfactant than in anionic surfactant. This study characterizes the role of surfactant in inducing phase transitions, which can be used as a guide for designing future products.

Dynamic switching of transcriptional regulators between two distinct low-mobility chromatin states

How chromatin dynamics relate to transcriptional activity remains poorly understood. Using single-molecule tracking, coupled with machine learning, we show that histone H2B and multiple chromatin-bound transcriptional regulators display two distinct low-mobility states. Ligand activation results in a marked increase in the propensity of steroid receptors to bind in the lowest-mobility state. Mutational analysis revealed that interactions with chromatin in the lowest-mobility state require an intact DNA binding domain and oligomerization domains. These states are not spatially separated as previously believed, but individual H2B and bound-TF molecules can dynamically switch between them on time scales of seconds. Single bound-TF molecules with different mobilities exhibit different dwell time distributions, suggesting that the mobility of TFs is intimately coupled with their binding dynamics. Together, our results identify two unique and distinct low-mobility states that appear to represent common pathways for transcription activation in mammalian cells.

Modulating the Viscoelastic Properties of Covalently Crosslinked Protein Hydrogels

Protein engineering allows for the programming of specific building blocks to form functional and novel materials with customisable physical properties suitable for tailored engineering applications. We have successfully designed and programmed engineered proteins to form covalent molecular networks with defined physical characteristics. Our hydrogel design incorporates the SpyTag (ST) peptide and SpyCatcher (SC) protein that spontaneously form covalent crosslinks upon mixing. This genetically encodable chemistry allowed us to easily incorporate two stiff and rod-like recombinant proteins in the hydrogels and modulate the resulting viscoelastic properties. We demonstrated how differences in the composition of the microscopic building blocks change the macroscopic viscoelastic properties of the hydrogels. We specifically investigated how the identity of the protein pairs, the molar ratio of ST:SC, and the concentration of the proteins influence the viscoelastic response of the hydrogels. By showing tuneable changes in protein hydrogel rheology, we increased the capabilities of synthetic biology to create novel materials, allowing engineering biology to interface with soft matter, tissue engineering, and material science.

Maximum likelihood-based estimation of diffusion coefficient is quick and reliable method for analyzing estradiol actions on surface receptor movements

The rapid effects of estradiol on membrane receptors are in the focus of the estradiol research field, however, the molecular mechanisms of these non-classical estradiol actions are poorly understood. Since the lateral diffusion of membrane receptors is an important indicator of their function, a deeper understanding of the underlying mechanisms of non-classical estradiol actions can be achieved by investigating receptor dynamics. Diffusion coefficient is a crucial and widely used parameter to characterize the movement of receptors in the cell membrane. The aim of this study was to investigate the differences between maximum likelihood-based estimation (MLE) and mean square displacement (MSD) based calculation of diffusion coefficients. In this work we applied both MSD and MLE to calculate diffusion coefficients. Single particle trajectories were extracted from simulation as well as from α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor tracking in live estradiol-treated differentiated PC12 (dPC12) cells. The comparison of the obtained diffusion coefficients revealed the superiority of MLE over the generally used MSD analysis. Our results suggest the use of the MLE of diffusion coefficients because as it has a better performance, especially for large localization errors or slow receptor movements.

Spherical PEG/SiO2 promising agents for Lamivudine antiviral drug delivery, a molecular dynamics simulation study

Spherical nanocarriers can lead to a bright future to lessen problems of virus infected people. Spherical polyethylene glycol (PEG) and spherical silica (SiO₂) are novel attractive nanocarriers as drug delivery agents, especially they are recently noticed to be reliable for antiviral drugs like anti-HIV, anti-covid-19, etc. Lamivudine (3TC) is used as a first line drug for antiviral therapy and the atomic view of 3TC-PEG/SiO₂ complexes enable scientist to help improve treatment of patients with viral diseases. This study investigates the interactions of 3TC with Spherical PEG/SiO₂, using molecular dynamics simulations. The mechanism of adsorption, the stability of systems and the drug concentration effect are evaluated by analyzing the root mean square deviation, the solvent accessible surface area, the radius of gyration, the number of hydrogen bonds, the radial distribution function, and Van der Waals energy. Analyzed data show that the compression of 3TC is less on PEG and so the stability is higher than SiO₂; the position and intensity of the RDF peaks approve this stronger binding of 3TC to PEG as well. Our studies show that PEG and also SiO₂ are suitable for loading high drug concentrations and maintaining their stability; therefore, spherical PEG/SiO₂ can reduce drug dosage efficiently.

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.

Synergistic Effects of Multiple Excipients on Controlling Viscosity of Concentrated Protein Dispersions

Viscosity control is essential for the manufacturing and delivery of concentrated therapeutic proteins. Limited availability of the precious protein-based drugs hinders the characterization and screening of the formulation conditions with new types or different combinations of excipients. In this work, a droplet-based microfluidic device with incorporated multiple particle tracking microrheology (MPT) is developed to quantify the effects of two excipients, arginine hydrochloride (ArgHCl) and caffeine, on the viscosity of concentrated bovine gamma globulin (BGG) dispersions at two different values of pH. The effectiveness of both ArgHCl and caffeine show dependence on the BGG concentration and solution pH. The data set with high compositional resolution provides useful information to guide formulation with multiple viscosity-reducing excipients and quantification appropriate to start elucidating the connection to protein-protein interaction mechanisms. Overall, this work has demonstrated that the developed microfluidic approach has the potential to effectively assess the impact of multiple excipients on the viscosity and provide data for computational methods to predict viscosity for high concentration protein formulations.

Fitting an active Brownian particle's mean-squared displacement with improved parameter estimation

The active Brownian particle (ABP) model is widely used to describe the dynamics of active matter systems, such as Janus microswimmers. In particular, the analytical expression for an ABP's mean-squared displacement (MSD) is useful as it provides a means to describe the essential physics of a self-propelled, spherical Brownian particle. However, the truncated or "short-time" form of the MSD equation is typically fitted, which can lead to significant problems in parameter estimation. Furthermore, heteroscedasticity and the often statistically dependent observations of an ABP's MSD lead to a situation where standard ordinary least-squares regression leads to biased estimates and unreliable confidence intervals. Instead, we propose here to revert to always fitting the full expression of an ABP's MSD at short timescales, using bootstrapping to construct confidence intervals of the fitted parameters. Additionally, after comparison between different fitting strategies, we propose to extract the physical parameters of an ABP using its mean logarithmic squared displacement. These steps improve the estimation of an ABP's physical properties and provide more reliable confidence intervals, which are critical in the context of a growing interest in the interactions of microswimmers with confining boundaries and the influence on their motion.

Quantifying transport dynamics with three-dimensional single-particle tracking in adherent cells

Intracellular transport plays an important role in maintaining the physiological functions of cells. Here, we describe a protocol for 3D single-particle tracking within living cells. We detail the use of a two-focal imaging system and the analytical steps for quantifying 3D transport dynamics. This protocol can be used to characterize the intracellular diffusion and trafficking of macromolecules, nanoparticles, and endocytic vesicles in adherent cells. For complete details on the use and execution of this protocol, please refer to Jiang et al. (2022).

A particulate blood analogue based on artificial viscoelastic blood plasma and RBC-like microparticles at a concentration matching the human haematocrit

There has been enormous interest in the production of fluids with rheological properties similar to those of real blood over the last few years. Application fields range from biomicrofluidics (microscale) to forensic science (macroscale). The inclusion of flexible microparticles in blood analogue fluids has been demonstrated to be essential in order to reproduce the behaviour of blood flow in these fields. Here, we describe a protocol to produce a whole human blood analogue composed of a proposed plasma analogue and flexible spherical microparticles that mimic the key structural attributes of RBCs (size and mechanical properties), at a concentration matching the human haematocrit (∼42% by volume). Polydimethylsiloxane (PDMS) flexible microparticles were used to mimic RBCs, whose capability to deform is tunable by means of the mixing ratio of the PDMS precursor. Their flow through glass micronozzles allowed us to find the appropriate mixing ratio of PDMS to have approximately the same Young's modulus (E) as that exhibited by real RBCs. Shear and extensional rheology and microrheology techniques were used to match the properties exhibited by human plasma and whole blood at body temperature (37 °C). Finally, we study the flow of our proposed fluid through a microfluidic channel, showing the in vitro reproduction of the multiphase flow effects taking place in the human microcirculatory system, such as the cell-free layer (CFL) and the Fåhræus-Lindqvist effect. A macroscale application in the field of forensic science is also presented, concerning the impact of our blood analogue droplets on a solid surface for bloodstain pattern analysis.

Single-Particle Tracking and Trajectory Analysis of Fluorescent Nanodiamonds in Cell-Free Environment and Live Cells

Diamond magnetometry can provide new insights on the production of free radicals inside live cells due to its high sensitivity and spatial resolution. However, the measurements often lack intracellular context for the recorded signal. In this paper, the possible use of single-particle tracking and trajectory analysis of fluorescent nanodiamonds (FNDs) to bridge that gap is explored. It starts with simulating a set of different possible scenarios of a particle's movement, reflecting different modes of motion, degrees of confinement, as well as shapes and sizes of that confinement. Then, the insights from the analysis of the simulated trajectories are applied to describe the movement of FNDs in glycerol solutions. It is shown that the measurements are in good agreement with the previously reported findings and that trajectory analysis yields meaningful results, when FNDs are tracked in a simple environment. Then the much more complex situation of FNDs moving inside a live cell is focused. The behavior of the particles after different incubation times is analyzed, and the possible intracellular localization of FNDs is deducted from their trajectories. Finally, this approach is combined with long-term magnetometry methods to obtain maps of the spin relaxation dynamics (or T1) in live cells, as FNDs move through the cytosol.

Measuring human mesenchymal stem cell remodeling in hydrogels with a step-change in elastic modulus

Human mesenchymal stem cells (hMSCs) are instrumental in the wound healing process. They migrate to wounds from their native niche in response to chemical signals released during the inflammatory phase of healing. At the wound, hMSCs downregulate inflammation and regulate tissue regeneration. Delivering additional hMSCs to wounds using cell-laden implantable hydrogels has the potential to improve healing outcomes and restart healing in chronic wounds. For these materials to be effective, cells must migrate from the scaffold into the native tissue. This requires cells to traverse a step-change in material properties at the implant-tissue interface. Migration of cells in material with highly varying properties is not well characterized. We measure 3D encapsulated hMSC migration and remodeling in a well-characterized hydrogel with a step-change in stiffness. This cell-degradable hydrogel is composed of 4-arm poly(ethylene glycol)-norbornene cross-linked with an enzymatically-degradable peptide. The scaffold is made with two halves of different stiffnesses separated by an interface where stiffness changes rapidly. We characterize changes in structure and rheology of the pericellular region using multiple particle tracking microrheology (MPT). MPT measures Brownian motion of embedded particles and relates it to material rheology. We measure more remodeling in the soft region of the hydrogel than the stiff region on day 1 post-encapsulation and similar remodeling everywhere on day 6. In the interface region, we measure hMSC-mediated remodeling along the interface and migration towards the stiff side of the scaffold. These results can improve materials designed for cell delivery from implants to a wound to enhance healing.

Heterogeneous nanoscopic lipid diffusion in the live cell membrane and its dependency on cholesterol

Cholesterol plays a unique role in the regulation of membrane organization and dynamics by modulating the membrane phase transition at the nanoscale. Unfortunately, due to their small sizes and dynamic nature, the effects of cholesterol-mediated membrane nanodomains on membrane dynamics remain elusive. Here, using ultrahigh-speed single-molecule tracking with advanced optical microscope techniques, we investigate the diffusive motion of single phospholipids in the live cell plasma membrane at the nanoscale and its dependency on the cholesterol concentration. We find that both saturated and unsaturated phospholipids undergo anomalous subdiffusion on the length scale of 10-100 nm. The diffusion characteristics exhibit considerable variations in space and in time, indicating that the nanoscopic lipid diffusion is highly heterogeneous. Importantly, through the statistical analysis, apparent dual-mobility subdiffusion is observed from the mixed diffusion behaviors. The measured subdiffusion agrees well with the hop diffusion model that represents a diffuser moving in a compartmentalized membrane created by the cytoskeleton meshwork. Cholesterol depletion diminishes the lipid mobility with an apparently smaller compartment size and a stronger confinement strength. Similar results are measured with temperature reduction, suggesting that the more heterogeneous and restricted diffusion is connected to the nanoscopic membrane phase transition. Our conclusion supports the model that cholesterol depletion induces the formation of gel-phase, solid-like membrane nanodomains. These nanodomains undergo restricted diffusion and act as diffusion obstacles to the membrane molecules that are excluded from the nanodomains. This work provides the experimental evidence that the nanoscopic lipid diffusion in the cell plasma membrane is heterogeneous and sensitive to the cholesterol concentration and temperature, shedding new light on the regulation mechanisms of nanoscopic membrane dynamics.

Rheology and Viscoelasticity of Proteins and Nucleic Acids Condensates

Phase separation is as familiar as watching vinegar separating from oil in vinaigrette. The observation that phase separation of proteins and nucleic acids is widespread in living cells has opened an entire field of research into the biological significance and the biophysical mechanisms of phase separation and protein condensation in biology. Recent evidence indicates that certain proteins and nucleic acids condensates are not simple liquids and instead display both viscous and elastic behaviors, which in turn may have biological significance. The aim of this Perspective is to review the state-of-the-art of this quickly emerging field focusing on the material and rheological properties of protein condensates. Finally, we discuss the different techniques that can be employed to quantify the viscoelasticity of condensates and highlight potential future directions and opportunities for interdisciplinary cross-talk between chemists, physicists, and biologists.

Passive and Active Microrheology for Biomedical Systems

Microrheology encompasses a range of methods to measure the mechanical properties of soft materials. By characterizing the motion of embedded microscopic particles, microrheology extends the probing length scale and frequency range of conventional bulk rheology. Microrheology can be characterized into either passive or active methods based on the driving force exerted on probe particles. Tracer particles are driven by thermal energy in passive methods, applying minimal deformation to the assessed medium. In active techniques, particles are manipulated by an external force, most commonly produced through optical and magnetic fields. Small-scale rheology holds significant advantages over conventional bulk rheology, such as eliminating the need for large sample sizes, the ability to probe fragile materials non-destructively, and a wider probing frequency range. More importantly, some microrheological techniques can obtain spatiotemporal information of local microenvironments and accurately describe the heterogeneity of structurally complex fluids. Recently, there has been significant growth in using these minimally invasive techniques to investigate a wide range of biomedical systems both in vitro and in vivo. Here, we review the latest applications and advancements of microrheology in mammalian cells, tissues, and biofluids and discuss the current challenges and potential future advances on the horizon.

Probing local chromatin dynamics by tracking telomeres

Chromatin dynamics is key for cell viability and replication. In interphase, chromatin is decondensed, allowing the transcription machinery to access a plethora of DNA loci. Yet, decondensed chromatin occupies almost the entire nucleus, suggesting that DNA molecules can hardly move. Recent reports have even indicated that interphase chromatin behaves like a solid body on mesoscopic scales. To explore the local chromatin dynamics, we have performed single-particle tracking on telomeres under varying conditions. We find that mobile telomeres feature in all conditions a strongly subdiffusive, anti-persistent motion that is consistent with the monomer motion of a Rouse polymer in viscoelastic media. In addition, telomere trajectories show intermittent accumulations in local niches at physiological conditions, suggesting the surrounding chromatin to reorganize on these time scales. Reducing the temperature or exposing cells to osmotic stress resulted in a significant reduction of mobile telomeres and the number of visited niches. Altogether, our data indicate a vivid local chromatin dynamics, akin to a semi-dilute polymer solution, unless perturbations enforce a more rigid or entangled state of chromatin.

Effect of Multivalency on Phase-Separated Droplets Consisting of Poly(PR) Dipeptide Repeats and RNA at the Solid/Liquid Interface

Dipeptide repeat proteins (DRPs) are considered a significant cause of amyotrophic lateral sclerosis (ALS), and their liquid-liquid phase separation (LLPS) formation with other biological molecules has been studied both in vitro and in vivo. The immobilization and wetting of the LLPS droplets on glass surfaces are technically crucial for the measurement with optical microscopy. In this work, we characterized the surface diffusion of LLPS droplets of the DRPs with different lengths to investigate the multivalent effect on the interactions of their LLPS droplets with the glass surface. Using fluorescence microscopy and the single-particle tracking method, we observed that the large multivalency drastically changed the surface behavior of the droplets. The coalescence and wetting of the droplets were accelerated by increasing the multivalency of peptides in the LLPS system. Our findings on the effect of multivalency on interactions between droplets and glass surfaces could provide a new insight to enhance the understanding of LLPS formation and biophysical properties related to the solid/liquid interface.

Receptor tyrosine kinase MET ligand-interaction classified via machine learning from single-particle tracking data

Internalin B-mediated activation of the membrane-bound receptor tyrosine kinase MET is accompanied by a change in receptor mobility. Conversely, it should be possible to infer from receptor mobility whether a cell has been treated with internalin B. Here, we propose a method based on hidden Markov modeling and explainable artificial intelligence that machine-learns the key differences in MET mobility between internalin B-treated and -untreated cells from single-particle tracking data. Our method assigns receptor mobility to three diffusion modes (immobile, slow, and fast). It discriminates between internalin B-treated and -untreated cells with a balanced accuracy of >99% and identifies three parameters that are most affected by internalin B treatment: a decrease in the mobility of slow molecules (1) and a depopulation of the fast mode (2) caused by an increased transition of fast molecules to the slow mode (3). Our approach is based entirely on free software and is readily applicable to the analysis of other membrane receptors.

Gelation phase diagrams of colloidal rod systems measured over a large composition space

Rheological modifiers tune product rheology with a small amount of material. To effectively use rheological modifiers, characterizing the rheology of the system at different compositions is crucial. Two colloidal rod system, hydrogenated castor oil and polyamide, are characterized in a formulation that includes a surfactant (linear alkylbenzene sulfonate) and a depletant (polyethylene oxide). We characterize both rod systems using multiple particle tracking microrheology (MPT) and bulk rheology and build phase diagrams over a large component composition space. In MPT, fluorescent particles are embedded in the sample and their Brownian motion is measured and related to rheological properties. From MPT, we determine that in both systems: (1) microstructure is not changed with increasing colloid concentration, (2) materials undergo a sol–gel transition as depletant concentration increases and (3) the microstructure changes but does not undergo a phase transition as surfactant concentration increases in the absence of depletant. When comparing MPT and bulk rheology results different trends are measured. Using bulk rheology we observe: (1) elasticity of both systems increase as colloid concentration increases and (2) the storage modulus does not change when PEO or LAS concentration is increased. The differences measured with MPT and bulk rheology are likely due to differences in sensitivity and measurement method. This work shows the utility of using both techniques together to fully characterize rheological properties over a large composition space. These gelation phase diagrams will provide a guide to determine the composition needed for desired rheological properties and eliminate trial-and-error experiments during product formulation.

Colloidal rod systems used as rheological modifiers are characterized over a large composition space with microrheology and bulk rheology. Phase diagrams are built that enable identification of compositions with desired properties eliminating trial-and-error experiments.

High-throughput microscopy to determine morphology, microrheology, and phase boundaries applied to phase separating coacervates

Evolution of composition, rheology, and morphology during phase separation in complex fluids is highly coupled to rheological and mass transport processes within the emerging phases, and understanding this coupling is critical for materials design of multiphase complex fluids. Characterizing these dependencies typically requires careful measurement of a large number of equilibrium and transport properties that are difficult to measure in situ as phase separation proceeds. Here, we propose and demonstrate a high-throughput microscopy platform to achieve simultaneous, in situ mapping of time-evolving morphology and microrheology in phase separating complex fluids over a large compositional space. The method was applied to a canonical example of polyelectrolyte complex coacervation, whereby mixing of oppositely charged species leads to liquid-liquid phase separation into distinct solute-dense and dilute phases. Morphology and rheology were measured simultaneously and kinetically after mixing to track the progression of phase separation. Once equilibrated, the dense phase viscosity was determined to high compositional accuracy using passive probe microrheology, and the results were used to derive empirical relationships between the composition and viscosity. These relationships were inverted to reconstruct the dense phase boundary itself, and further extended to other mixture compositions. The resulting predictions were validated by independent equilibrium compositional measurements. This platform paves the way for rapid screening and formulation of complex fluids and (bio)macromolecular materials, and serves as a critical link between formulation and rheology for multi-phase material discovery.

ATP-responsive biomolecular condensates tune bacterial kinase signaling

Biomolecular condensates formed via liquid-liquid phase separation enable spatial and temporal organization of enzyme activity. Phase separation in many eukaryotic condensates has been shown to be responsive to intracellular adenosine triphosphate (ATP) levels, although the consequences of these mechanisms for enzymes sequestered within the condensates are unknown. Here, we show that ATP depletion promotes phase separation in bacterial condensates composed of intrinsically disordered proteins. Enhanced phase separation promotes the sequestration and activity of a client kinase enabling robust signaling and maintenance of viability under the stress posed by nutrient scarcity. We propose that a diverse repertoire of condensates can serve as control knobs to tune enzyme sequestration and reactivity in response to the metabolic state of bacterial cells.

Anomalous diffusion, aging, and nonergodicity of scaled Brownian motion with fractional Gaussian noise: overview of related experimental observations and models

How does a systematic time-dependence of the diffusion coefficient $D (t)$ affect the ergodic and statistical characteristics of fractional Brownian motion (FBM)? Here, we examine how the behavior of the...

Dynamics of Bacterial Chromosomes by Locus Tracking in Fluorescence Microscopy

In the last two decades, it has been shown that bacterial chromosomes have remarkable spatial organization at various scales, and they display well-defined movements during the cell cycle, for example to reliably segregate daughter chromosomes. More recently, various labs have begun investigating also the short time dynamics (displacements during time intervals of 0.1 s-100 s), which should be related to the molecular structure. Probing these dynamics is analogous to "microrheology" approaches that have been applied successfully to study mechanical response of complex fluids. These studies of chromosome fluctuation dynamics have revealed differences of fluctuation amplitude across the chromosome, and different characters of motion depending on the time window of interest. Different fluctuation amplitudes have also been observed for the same chromosomal loci under antibiotic treatments, with magnitudes that are correlated to changes in intracellular density and thus crowding. We describe how to carry out tracking experiments of single loci and how to analyze locus motility. We point out the importance of considering in the analysis the number of GFP molecules per fluorescent locus, as well as the nature of the protein they are fused to, and also how to measure intracellular density.

Diffusion State Transitions in Single-Particle Trajectories of MET Receptor Tyrosine Kinase Measured in Live Cells

Single-particle tracking enables the analysis of the dynamics of biomolecules in living cells with nanometer spatial and millisecond temporal resolution. This technique reports on the mobility of membrane proteins and is sensitive to the molecular state of a biomolecule and to interactions with other biomolecules. Trajectories describe the mobility of single particles over time and provide information such as the diffusion coefficient and diffusion state. Changes in particle dynamics within single trajectories lead to segmentation, which allows to extract information on transitions of functional states of a biomolecule. Here, mean-squared displacement analysis is developed to classify trajectory segments into immobile, confined diffusing, and freely diffusing states, and to extract the occurrence of transitions between these modes. We applied this analysis to single-particle tracking data of the membrane receptor MET in live cells and analyzed state transitions in single trajectories of the un-activated receptor and the receptor bound to the ligand internalin B. We found that internalin B-bound MET shows an enhancement of transitions from freely and confined diffusing states into the immobile state as compared to un-activated MET. Confined diffusion acts as an intermediate state between immobile and free, as this state is most likely to change the diffusion state in the following segment. This analysis can be readily applied to single-particle tracking data of other membrane receptors and intracellular proteins under various conditions and contribute to the understanding of molecular states and signaling pathways.

Measuring the Effects of Cytokines on the Modification of Pericellular Rheology by Human Mesenchymal Stem Cells

Implantable hydrogels are designed to treat wounds by providing structure and delivering additional cells to damaged tissue. These materials must consider how aspects of the native wound, including environmental chemical cues, affect and instruct delivered cells. One cell type researchers are interested in delivering are human mesenchymal stem cells (hMSCs) due to their importance in healing. Wound healing involves recruiting and coordinating a variety of cells to resolve a wound. hMSCs coordinate the cellular response and are signaled to the wound by cytokines, including transforming growth factor-β (TGF-β) and tumor necrosis factor-α (TNF-α), present in vivo. These cytokines change hMSC secretions, regulating material remodeling. TGF-β, present from inflammation through remodeling, directs hMSCs to reorganize collagen, increasing extracellular matrix (ECM) structure. TNF-α, present primarily during inflammation, cues hMSCs to clear debris and degrade ECM. Because cytokines change how hMSCs degrade their microenvironment and are naturally present in the wound, they also affect how hMSCs migrate out of the scaffold to conduct healing. Therefore, the effects of cytokines on hMSC remodeling are important when designing materials for cell delivery. In this work, we encapsulate hMSCs in a polymer-peptide hydrogel and incubate the scaffolds in media with TGF-β or TNF-α at concentrations similar to those in wounds. Multiple particle tracking microrheology (MPT) measures hMSC-mediated scaffold degradation in response to these cytokines, which mimics aspects of the in vivo microenvironment post-implantation. MPT uses video microscopy to measure Brownian motion of particles in a material, quantifying structure and rheology. Using MPT, we measure increased hMSC-mediated remodeling when cells are exposed to TNF-α and decreased remodeling after exposure to TGF-β when compared to untreated hMSCs. This agrees with previous studies that measure: (1) TNF-α encourages matrix reorganization and (2) TGF-β signals the formation of new matrix. These results enable material design that anticipates changes in remodeling after implantation, improving control over hMSC delivery and healing.

Droplet-Based Microfluidic Tool to Quantify Viscosity of Concentrating Protein Solutions

PURPOSE

Measurement of the viscosity of concentrated protein solutions is vital for the manufacture and delivery of protein therapeutics. Conventional methods for viscosity measurements require large solution volumes, creating a severe limitation during the early stage of protein development. The goal of this work is to develop a robust technique that requires minimal sample.

METHODS

In this work, a droplet-based microfluidic device is developed to quantify the viscosity of protein solutions while concentrating in micrometer-scale droplets. The technique requires only microliters of sample. The corresponding viscosity is characterized by multiple particle tracking microrheology (MPT).

RESULTS

We show that the viscosities quantified in the microfluidic device are consistent with macroscopic results measured by a conventional rheometer for poly(ethylene) glycol (PEG) solutions. The technique was further applied to quantify viscosities of well-studied lysozyme and bovine serum albumin (BSA) solutions. Comparison to both macroscopic measurements and models (Krieger-Dougherty model) demonstrate the validity of the approach.

CONCLUSION

The droplet-based microfluidic device provides accurate quantitative values of viscosity over a range of concentrations for protein solutions with small sample volumes (~ μL) and high compositional resolution. This device will be extended to study the effect of different excipients and other additives on the viscosity of protein solutions.

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.

Two-dimensional Brownian motion of anisotropic dimers

We study the two-dimensional motion of colloidal dimers by single-particle tracking and compare the experimental observations obtained by bright-field microscopy to theoretical predictions for anisotropic diffusion. The comparison is based on the mean-square displacements in the laboratory and particle frame as well as generalizations of the self-intermediate scattering functions, which provide insights into the rotational dynamics of the dimer. The diffusional anisotropy leads to a measurable translational-rotational coupling that becomes most prominent by aligning the coordinate system with the initial orientation of the particles. In particular, we find a splitting of the time-dependent diffusion coefficients parallel and perpendicular to the long axis of the dimer which decays over the orientational relaxation time. Deviations of the self-intermediate scattering functions from pure exponential relaxation are small but can be resolved experimentally. The theoretical predictions and experimental results agree quantitatively.