Cooperative motility, force generation and mechanosensing in a foraging non-photosynthetic diatom.

Diatoms are ancestrally photosynthetic microalgae. However, some underwent a major evolutionary transition, losing photosynthesis to become obligate heterotrophs. The molecular and physiological basis for this transition is unclear. Here, we isolate and characterize new strains of non-photosynthetic diatoms from the coastal waters of Singapore. These diatoms occupy diverse ecological niches and display glucose-mediated catabolite repression, a classical feature of bacterial and fungal heterotrophs. Live-cell imaging reveals deposition of secreted extracellular polymeric substance (EPS). Diatoms moving on pre-existing EPS trails (runners) move faster than those laying new trails (blazers). This leads to cell-to-cell coupling where runners can push blazers to make them move faster. Calibrated micropipettes measure substantial single-cell pushing forces, which are consistent with high-order myosin motor cooperativity. Collisions that impede forward motion induce reversal, revealing navigation-related force sensing. Together, these data identify aspects of metabolism and motility that are likely to promote and underpin diatom heterotrophy.

A computational model for the cancer field effect.

Introduction: The Cancer Field Effect describes an area of pre-cancerous cells that results from continued exposure to carcinogens. Cells in the cancer field can easily develop into cancer. Removal of the main tumor mass might leave the cancer field behind, increasing risk of recurrence. Methods: The model we propose for the cancer field effect is a hybrid cellular automaton (CA), which includes a multi-layer perceptron (MLP) to compute the effects of the carcinogens on the gene expression of the genes related to cancer development. We use carcinogen interactions that are typically associated with smoking and alcohol consumption and their effect on cancer fields of the tongue. Results: Using simulations we support the understanding that tobacco smoking is a potent carcinogen, which can be reinforced by alcohol consumption. The effect of alcohol alone is significantly less than the effect of tobacco. We further observe that pairing tumor excision with field removal delays recurrence compared to tumor excision alone. We track cell lineages and find that, in most cases, a polyclonal field develops, where the number of distinct cell lineages decreases over time as some lineages become dominant over others. Finally, we find tumor masses rarely form via monoclonal origin.

Personalized Virus Load Curves for Acute Viral Infections.

We introduce an explicit function that describes virus-load curves on a patient-specific level. This function is based on simple and intuitive model parameters. It allows virus load analysis of acute viral infections without solving a full virus load dynamic model. We validate our model on data from mice influenza A, human rhinovirus data, human influenza A data, and monkey and human SARS-CoV-2 data. We find wide distributions for the model parameters, reflecting large variability in the disease outcomes between individuals. Further, we compare the virus load function to an established target model of virus dynamics, and we provide a new way to estimate the exponential growth rates of the corresponding infection phases. The virus load function, the target model, and the exponential approximations show excellent fits for the data considered. Our virus-load function offers a new way to analyze patient-specific virus load data, and it can be used as input for higher level models for the physiological effects of a virus infection, for models of tissue damage, and to estimate patient risks.

HSP70 chaperones RNA-free TDP-43 into anisotropic intranuclear liquid spherical shells.

The RNA binding protein TDP-43 forms intranuclear or cytoplasmic aggregates in age-related neurodegenerative diseases. In this study, we found that RNA binding-deficient TDP-43 (produced by neurodegeneration-causing mutations or posttranslational acetylation in its RNA recognition motifs) drove TDP-43 demixing into intranuclear liquid spherical shells with liquid cores. These droplets, which we named "anisosomes", have shells that exhibit birefringence, thus indicating liquid crystal formation. Guided by mathematical modeling, we identified the primary components of the liquid core to be HSP70 family chaperones, whose adenosine triphosphate (ATP)-dependent activity maintained the liquidity of shells and cores. In vivo proteasome inhibition within neurons, to mimic aging-related reduction of proteasome activity, induced TDP-43-containing anisosomes. These structures converted to aggregates when ATP levels were reduced. Thus, acetylation, HSP70, and proteasome activities regulate TDP-43 phase separation and conversion into a gel or solid phase.

Spatial heterogeneity of the cytosol revealed by machine learning-based 3D particle tracking.

The spatial structure and physical properties of the cytosol are not well understood. Measurements of the material state of the cytosol are challenging due to its spatial and temporal heterogeneity. Recent development of genetically encoded multimeric nanoparticles (GEMs) has opened up study of the cytosol at the length scales of multiprotein complexes (20-60 nm). We developed an image analysis pipeline for 3D imaging of GEMs in the context of large, multinucleate fungi where there is evidence of functional compartmentalization of the cytosol for both the nuclear division cycle and branching. We applied a neural network to track particles in 3D and then created quantitative visualizations of spatially varying diffusivity. Using this pipeline to analyze spatial diffusivity patterns, we found that there is substantial variability in the properties of the cytosol. We detected zones where GEMs display especially low diffusivity at hyphal tips and near some nuclei, showing that the physical state of the cytosol varies spatially within a single cell. Additionally, we observed significant cell-to-cell variability in the average diffusivity of GEMs. Thus, the physical properties of the cytosol vary substantially in time and space and can be a source of heterogeneity within individual cells and across populations.

LPS-binding IgG arrests actively motile Salmonella Typhimurium in gastrointestinal mucus.

The gastrointestinal (GI) mucosa is coated with a continuously secreted mucus layer that serves as the first line of defense against invading enteric bacteria. We have previously shown that antigen-specific immunoglobulin G (IgG) can immobilize viruses in both human airway and genital mucus secretions through multiple low-affinity bonds between the array of virion-bound IgG and mucins, thereby facilitating their rapid elimination from mucosal surfaces and preventing mucosal transmission. Nevertheless, it remains unclear whether weak IgG-mucin crosslinks could reinforce the mucus barrier against the permeation of bacteria driven by active flagella beating, or in predominantly MUC2 mucus gel. Here, we performed high-resolution multiple particle tracking to capture the real-time motion of hundreds of individual fluorescent Salmonella Typhimurium in fresh, undiluted GI mucus from Rag1-/- mice, and analyzed the motion using a hidden Markov model framework. In contrast to control IgG, the addition of anti-lipopolysaccharide IgG to GI mucus markedly reduced the progressive motility of Salmonella by lowering the swim speed and retaining individual bacteria in an undirected motion state. Effective crosslinking of Salmonella to mucins was dependent on Fc N-glycans. Our findings implicate IgG-mucin crosslinking as a broadly conserved function that reduces mucous penetration of both bacterial and viral pathogens.

Limited processivity of single motors improves overall transport flux of self-assembled motor-cargo complexes.

Single kinesin molecular motors can processively move along a microtubule (MT) a few micrometers on average before dissociating. However, cellular length scales over which transport occurs are several hundred microns and more. Why seemingly unreliable motors are used to transport cellular cargo remains poorly understood. We propose a theory for how low processivity, the average length of a single bout of directed motion, can enhance cellular transport when motors and cargos must first diffusively self-assemble into complexes. We employ stochastic modeling to determine the effect of processivity on overall cargo transport flux. We show that, under a wide range of physiologically relevant conditions, possessing "infinite" processivity does not maximize flux along MTs. Rather, we find that lowering processivity, i.e., weaker binding of motors to MTs, can improve transport flux. These results shed light on the relationship between processivity and transport efficiency and offer a theory for the physiological benefits of low motor processivity.

Modeling Barrier Properties of Intestinal Mucus Reinforced with IgG and Secretory IgA against Motile Bacteria.

The gastrointestinal (GI) tract is lined with a layer of viscoelastic mucus gel, characterized by a dense network of entangled and cross-linked mucins together with an abundance of antibodies (Ab). Secretory IgA (sIgA), the predominant Ab isotype in the GI tract, is a dimeric molecule with 4 antigen-binding domains capable of inducing efficient clumping of bacteria, or agglutination. IgG, another common Ab at mucosal surfaces, can cross-link individual viruses to the mucin mesh through multiple weak bonds between IgG-Fc and mucins, a process termed muco-trapping. Relative contributions by agglutination versus muco-trapping in blocking permeation of motile bacteria through mucus remain poorly understood. Here, we developed a mathematical model that takes into account physiologically relevant spatial dimensions and time scales, binding and unbinding rates between Ab and bacteria as well as between Ab and mucins, the diffusivities of Ab, and run-tumble motion of active bacteria. Our model predicts both sIgA and IgG can accumulate on the surface of individual bacteria at sufficient quantities and rates to enable trapping individual bacteria in mucins before they penetrate the mucus layer. Furthermore, our model predicts that agglutination only modestly improves the ability for antibodies to block bacteria permeation through mucus. These results suggest that while sIgA is the most potent Ab isotype overall at stopping bacterial penetration, IgG may represent a practical alternative for mucosal prophylaxis and therapy. Our work improves the mechanistic understanding of Ab-enhanced barrier properties of mucus and highlights the ability for muco-trapping Ab to protect against motile pathogens at mucosal surfaces.

Hydrodynamics of transient cell-cell contact: The role of membrane permeability and active protrusion length.

In many biological settings, two or more cells come into physical contact to form a cell-cell interface. In some cases, the cell-cell contact must be transient, forming on timescales of seconds. One example is offered by the T cell, an immune cell which must attach to the surface of other cells in order to decipher information about disease. The aspect ratio of these interfaces (tens of nanometers thick and tens of micrometers in diameter) puts them into the thin-layer limit, or "lubrication limit", of fluid dynamics. A key question is how the receptors and ligands on opposing cells come into contact. What are the relative roles of thermal undulations of the plasma membrane and deterministic forces from active filopodia? We use a computational fluid dynamics algorithm capable of simulating 10-nanometer-scale fluid-structure interactions with thermal fluctuations up to seconds- and microns-scales. We use this to simulate two opposing membranes, variously including thermal fluctuations, active forces, and membrane permeability. In some regimes dominated by thermal fluctuations, proximity is a rare event, which we capture by computing mean first-passage times using a Weighted Ensemble rare-event computational method. Our results demonstrate a parameter regime in which the time it takes for an active force to drive local contact actually increases if the cells are being held closer together (e.g., by nonspecific adhesion), a phenomenon we attribute to the thin-layer effect. This leads to an optimal initial cell-cell separation for fastest receptor-ligand binding, which could have relevance for the role of cellular protrusions like microvilli. We reproduce a previous experimental observation that fluctuation spatial scales are largely unaffected, but timescales are dramatically slowed, by the thin-layer effect. We also find that membrane permeability would need to be above physiological levels to abrogate the thin-layer effect.

Partial demixing of RNA-protein complexes leads to intradroplet patterning in phase-separated biological condensates.

An emerging mechanism for intracellular organization is liquid-liquid phase separation (LLPS). Found in both the nucleus and the cytoplasm, liquidlike droplets condense to create compartments that are thought to promote and inhibit specific biochemistry. In this work, a multiphase, Cahn-Hilliard diffuse interface model is used to examine RNA-protein interactions driving LLPS. We create a bivalent system that allows for two different species of protein-RNA complexes and model the competition that arises for a shared binding partner, free protein. With this system we demonstrate that the binding and unbinding of distinct RNA-protein complexes leads to diverse spatial pattern formation and dynamics within droplets. Both the initial formation and transient behavior of spatial patterning are subject to the exchange of free proteins between RNA-protein complexes. This study illustrates that spatiotemporal heterogeneity can emerge within phase-separated biological condensates with simple binding reactions and competition. Intradroplet patterning may influence droplet composition and, subsequently, cellular organization on a larger scale.

Engineering Polymer-Binding Bispecific Antibodies for Enhanced Pretargeted Delivery of Nanoparticles to Mucus-Covered Epithelium.

Mucus represents a major barrier to sustained and targeted drug delivery to mucosal epithelium. Ideal drug carriers should not only rapidly diffuse across mucus, but also bind the epithelium. Unfortunately, ligand-conjugated particles often exhibit poor penetration across mucus. In this work, we explored a two-step "pretargeting" approach through engineering a bispecific antibody that binds both cell-surface ICAM-1 and polyethylene glycol (PEG) on the surface of nanoparticles, thereby effectively decoupling cell targeting from particle design and formulation. When tested in a mucus-coated Caco-2 culture model that mimics the physiological process of mucus clearance, pretargeting increased the amount of PEGylated particles binding to cells by around 2-fold or more compared to either non-targeted or actively targeted PEGylated particles. Pretargeting also markedly enhanced particle retention in mouse intestinal tissues. Our work underscores pretargeting as a promising strategy to improve the delivery of therapeutics to mucosal surfaces.

Convolutional neural networks automate detection for tracking of submicron-scale particles in 2D and 3D.

Particle tracking is a powerful biophysical tool that requires conversion of large video files into position time series, i.e., traces of the species of interest for data analysis. Current tracking methods, based on a limited set of input parameters to identify bright objects, are ill-equipped to handle the spectrum of spatiotemporal heterogeneity and poor signal-to-noise ratios typically presented by submicron species in complex biological environments. Extensive user involvement is frequently necessary to optimize and execute tracking methods, which is not only inefficient but introduces user bias. To develop a fully automated tracking method, we developed a convolutional neural network for particle localization from image data, comprising over 6,000 parameters, and used machine learning techniques to train the network on a diverse portfolio of video conditions. The neural network tracker provides unprecedented automation and accuracy, with exceptionally low false positive and false negative rates on both 2D and 3D simulated videos and 2D experimental videos of difficult-to-track species.

ZMapp Reinforces the Airway Mucosal Barrier Against Ebola Virus.

Filoviruses, including Ebola, have the potential to be transmitted via virus-laden droplets deposited onto mucus membranes. Protecting against such emerging pathogens will require understanding how they may transmit at mucosal surfaces and developing strategies to reinforce the airway mucus barrier. Here, we prepared Ebola pseudovirus (with Zaire strain glycoproteins) and used high-resolution multiple-particle tracking to track the motions of hundreds of individual pseudoviruses in fresh and undiluted human airway mucus isolated from extubated endotracheal tubes. We found that Ebola pseudovirus readily penetrates human airway mucus. Addition of ZMapp, a cocktail of Ebola-binding immunoglobulin G antibodies, effectively reduced mobility of Ebola pseudovirus in the same mucus secretions. Topical delivery of ZMapp to the mouse airways also facilitated rapid elimination of Ebola pseudovirus. Our work demonstrates that antibodies can immobilize virions in airway mucus and reduce access to the airway epithelium, highlighting topical delivery of pathogen-specific antibodies to the lungs as a potential prophylactic or therapeutic approach against emerging viruses or biowarfare agents.

Control of septin filament flexibility and bundling by subunit composition and nucleotide interactions.

Septins self-assemble into heteromeric rods and filaments to act as scaffolds and modulate membrane properties. How cells tune the biophysical properties of septin filaments to control filament flexibility and length, and in turn the size, shape, and position of higher-order septin structures, is not well understood. We examined how rod composition and nucleotide availability influence physical properties of septins such as annealing, fragmentation, bundling, and bending. We found that septin complexes have symmetric termini, even when both Shs1 and Cdc11 are coexpressed. The relative proportion of Cdc11/Shs1 septin complexes controls the biophysical properties of filaments and influences the rate of annealing, fragmentation, and filament flexibility. Additionally, the presence and apparent exchange of guanine nucleotide also alters filament length and bundling. An Shs1 mutant that is predicted to alter nucleotide hydrolysis has altered filament length and dynamics in cells and impacts cell morphogenesis. These data show that modulating filament properties through rod composition and nucleotide binding can control formation of septin assemblies that have distinct physical properties and functions.

Technological strategies to estimate and control diffusive passage times through the mucus barrier in mucosal drug delivery.

In mucosal drug delivery, two design goals are desirable: 1) insure drug passage through the mucosal barrier to the epithelium prior to drug removal from the respective organ via mucus clearance; and 2) design carrier particles to achieve a prescribed arrival time and drug uptake schedule at the epithelium. Both goals are achievable if one can control "one-sided" diffusive passage times of drug carrier particles: from deposition at the mucus interface, through the mucosal barrier, to the epithelium. The passage time distribution must be, with high confidence, shorter than the timescales of mucus clearance to maximize drug uptake. For 100nm and smaller drug-loaded nanoparticulates, as well as pure drug powders or drug solutions, diffusion is normal (i.e., Brownian) and rapid, easily passing through the mucosal barrier prior to clearance. Major challenges in quantitative control over mucosal drug delivery lie with larger drug-loaded nanoparticulates that are comparable to or larger than the pores within the mucus gel network, for which diffusion is not simple Brownian motion and typically much less rapid; in these scenarios, a timescale competition ensues between particle passage through the mucus barrier and mucus clearance from the organ. In the lung, as a primary example, coordinated cilia and air drag continuously transport mucus toward the trachea, where mucus and trapped cargo are swallowed into the digestive tract. Mucus clearance times in lung airways range from minutes to hours or significantly longer depending on deposition in the upper, middle, lower airways and on lung health, giving a wide time window for drug-loaded particle design to achieve controlled delivery to the epithelium. We review the physical and chemical factors (of both particles and mucus) that dictate particle diffusion in mucus, and the technological strategies (theoretical and experimental) required to achieve the design goals. First we describe an idealized scenario - a homogeneous viscous fluid of uniform depth with a particle undergoing passive normal diffusion - where the theory of Brownian motion affords the ability to rigorously specify particle size distributions to meet a prescribed, one-sided, diffusive passage time distribution. Furthermore, we describe how the theory of Brownian motion provides the scaling of one-sided diffusive passage times with respect to mucus viscosity and layer depth, and under reasonable caveats, one can also prescribe passage time scaling due to heterogeneity in viscosity and layer depth. Small-molecule drugs and muco-inert, drug-loaded carrier particles 100nm and smaller fall into this class of rigorously controllable passage times for drug delivery. Second we describe the prevalent scenarios in which drug-loaded carrier particles in mucus violate simple Brownian motion, instead exhibiting anomalous sub-diffusion, for which all theoretical control over diffusive passage times is lost, and experiments are prohibitive if not impossible to measure one-sided passage times. We then discuss strategies to overcome these roadblocks, requiring new particle-tracking experiments and emerging advances in theory and computation of anomalous, sub-diffusive processes that are necessary to predict and control one-sided particle passage times from deposition at the mucosal interface to epithelial uptake. We highlight progress to date, remaining hurdles, and prospects for achieving the two design goals for 200nm and larger, drug-loaded, non-dissolving, nanoparticulates.

A blueprint for robust crosslinking of mobile species in biogels with weakly adhesive molecular anchors.

Biopolymeric matrices can impede transport of nanoparticulates and pathogens by entropic or direct adhesive interactions, or by harnessing "third-party" molecular anchors to crosslink nanoparticulates to matrix constituents. The trapping potency of anchors is dictated by association rates and affinities to both nanoparticulates and matrix; the popular dogma is that long-lived, high-affinity bonds to both species facilitate optimal trapping. Here we present a contrasting paradigm combining experimental evidence (using IgG antibodies and Matrigel®), a theoretical framework (based on multiple timescale analysis), and computational modeling. Anchors that bind and unbind rapidly from matrix accumulate on nanoparticulates much more quickly than anchors that form high-affinity, long-lived bonds with matrix, leading to markedly greater trapping potency of multiple invading species without saturating matrix trapping capacity. Our results provide a blueprint for engineering molecular anchors with finely tuned affinities to effectively enhance the barrier properties of biogels against diverse nanoparticulate species.Biological polymeric matrices often use molecular anchors, such as antibodies, to trap nanoparticulates. Here, the authors find that anchor-matrix bonds that are weak and short-lived confer superior trapping potency, contrary to the prevailing belief that effective molecular anchors should form strong bonds to both the matrix and the nanoparticulates.

Uniform asymptotic approximation of diffusion to a small target: Generalized reaction models.

The diffusion of a reactant to a binding target plays a key role in many biological processes. The reaction radius at which the reactant and target may interact is often a small parameter relative to the diameter of the domain in which the reactant diffuses. We develop uniform in time asymptotic expansions in the reaction radius of the full solution to the corresponding diffusion equations for two separate reactant-target interaction mechanisms: the Doi or volume reactivity model and the Smoluchowski-Collins-Kimball partial-absorption surface reactivity model. In the former, the reactant and target react with a fixed probability per unit time when within a specified separation. In the latter, upon reaching a fixed separation, they probabilistically react or the reactant reflects away from the target. Expansions of the solution to each model are constructed by projecting out the contribution of the first eigenvalue and eigenfunction to the solution of the diffusion equation and then developing matched asymptotic expansions in Laplace-transform space. Our approach offers an equivalent, but alternative, method to the pseudopotential approach we previously employed [Isaacson and Newby, Phys. Rev. E 88, 012820 (2013)PLEEE81539-375510.1103/PhysRevE.88.012820] for the simpler Smoluchowski pure-absorption reaction mechanism. We find that the resulting asymptotic expansions of the diffusion equation solutions are identical with the exception of one parameter: the diffusion-limited reaction rates of the Doi and partial-absorption models. This demonstrates that for biological systems in which the reaction radius is a small parameter, properly calibrated Doi and partial-absorption models may be functionally equivalent.

The Binding Site Barrier Elicited by Tumor-Associated Fibroblasts Interferes Disposition of Nanoparticles in Stroma-Vessel Type Tumors.

The binding site barrier (BSB) was originally proposed to describe the binding behavior of antibodies to cells peripheral to blood vessels, preventing their further penetration into the tumors. Yet, it is revisited herein to describe the intratumoral cellular disposition of nanoparticles (NPs). Specifically, the BSB limits NP diffusion and results in unintended internalization of NPs by stroma cells localized near blood vessels. This not only limits the therapeutic outcome but also promotes adverse off-target effects. In the current study, it was shown that tumor-associated fibroblast cells (TAFs) are the major component of the BSB, particularly in tumors with a stroma-vessel architecture where the location of TAFs aligns with blood vessels. Specifically, TAF distance to blood vessels, expression of receptor proteins, and binding affinity affect the intensity of the BSB. The physical barrier elicited by extracellular matrix also prolongs the retention of NPs in the stroma, potentially contributing to the BSB. The influence of particle size on the BSB was also investigated. The strongest BSB effect was found with small (∼18 nm) NPs targeted with the anisamide ligand. The uptake of these NPs by TAFs was about 7-fold higher than that of the other cells 16 h post-intravenous injection. This was because TAFs also expressed the sigma receptor under the influence of TGF-ß secreted by the tumor cells. Overall, the current study underscores the importance of BSBs in the delivery of nanotherapeutics and provides a rationale for exploiting BSBs to target TAFs.

First-Passage Time to Clear the Way for Receptor-Ligand Binding in a Crowded Environment.

Certain biological reactions, such as receptor-ligand binding at cell-cell interfaces and macromolecules binding to biopolymers, require many smaller molecules crowding a reaction site to be cleared. Examples include the T-cell interface, a key player in immunological information processing. Diffusion sets a limit for such cavitation to occur spontaneously, thereby defining a time scale below which active mechanisms must take over. We consider N independent diffusing particles in a closed domain, containing a subregion with N_{0} particles, on average. We investigate the time until the subregion is empty, allowing a subsequent reaction to proceed. The first-passage time is computed using an efficient exact simulation algorithm and an asymptotic approximation in the limit that cavitation is rare. In this limit, we find that the mean first-passage time is subexponential, T∝e^{N_{0}}/N_{0}^{2}. For the case of T-cell receptors, we find that stochastic cavitation is exceedingly slow, 10^{9} s at physiological densities; however, it can be accelerated to occur within 5 s with only a fourfold dilution.

Path integrals and large deviations in stochastic hybrid systems.

We construct a path-integral representation of solutions to a stochastic hybrid system, consisting of one or more continuous variables evolving according to a piecewise-deterministic dynamics. The differential equations for the continuous variables are coupled to a set of discrete variables that satisfy a continuous-time Markov process, which means that the differential equations are only valid between jumps in the discrete variables. Examples of stochastic hybrid systems arise in biophysical models of stochastic ion channels, motor-driven intracellular transport, gene networks, and stochastic neural networks. We use the path-integral representation to derive a large deviation action principle for a stochastic hybrid system. Minimizing the associated action functional with respect to the set of all trajectories emanating from a metastable state (assuming that such a minimization scheme exists) then determines the most probable paths of escape. Moreover, evaluating the action functional along a most probable path generates the so-called quasipotential used in the calculation of mean first passage times. We illustrate the theory by considering the optimal paths of escape from a metastable state in a bistable neural network.