Antibody-Mediated Immobilization of Virions in Mucus

Tethering of soluble immune effectors to mucin and chitin reflects a convergent and dynamic role in gut immunity

The immune system employs soluble effectors to shape luminal spaces. Antibodies are soluble molecules that effect immunological responses, including neutralization, opsonization, antibody-dependent cytotoxicity and complement activation. These molecules are comprised of immunoglobulin (Ig) domains. The N-terminal Ig domains recognize antigen, and the C-terminal domains facilitate their elimination through phagocytosis (opsonization). A less-recognized function mediated by the C-terminal Ig domains of the IgG class of antibodies (Fc region) involves the formation of multiple low-affinity bonds with the mucus matrix. This association anchors the antibody molecule to the matrix to entrap potential pathogens. Even though invertebrates are not known to have antibodies, protochordates have a class of secreted molecules containing Ig domains that can bind bacteria and potentially serve a similar purpose. The VCBPs (V region-containing chitin-binding proteins) possess a C-terminal chitin-binding domain that helps tether them to chitin-rich mucus gels, mimicking the IgG-mediated Fc trapping of microbes in mucus. The broad functional similarity of these structurally divergent, Ig-containing, secreted effectors makes a case for a unique form of convergent evolution within chordates. This opinion essay highlights emerging evidence that divergent secreted immune effectors with Ig-like domains evolved to manage immune recognition at mucosal surfaces in strikingly similar ways. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.

Hidden Markov modeling of single-particle diffusion with stochastic tethering

The statistics of the diffusive motion of particles often serve as an experimental proxy for their interaction with the environment. However, inferring the physical properties from the observed trajectories is challenging. Inspired by a recent experiment, here we analyze the problem of particles undergoing two-dimensional Brownian motion with transient tethering to the surface. We model the problem as a hidden Markov model where the physical position is observed and the tethering state is hidden. We develop an alternating maximization algorithm to infer the hidden state of the particle and estimate the physical parameters of the system. The crux of our method is a saddle-point-like approximation, which involves finding the most likely sequence of hidden states and estimating the physical parameters from it. Extensive numerical tests demonstrate that our algorithm reliably finds the model parameters and is insensitive to the initial guess. We discuss the different regimes of physical parameters and the algorithm's performance in these regimes. We also provide a free software implementation of our algorithm.

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.

Antibody protection from SARS-CoV-2 respiratory tract exposure and infection

The COVID-19 pandemic has underscored the need to understand the dynamics of SARS-CoV-2 respiratory infection and protection provided by the immune response. SARS-CoV-2 infections are characterized by a particularly high viral load, and further by the small number of inhaled virions sufficient to generate a high viral titer in the nasal passage a few days after exposure. SARS-CoV-2 specific antibodies (Ab), induced from vaccines, previous infection, or inhaled monoclonal Ab, have proven effective against SARS-CoV-2 infection. Our goal in this work is to model the protective mechanisms that Ab can provide and to assess the degree of protection from individual and combined mechanisms at different locations in the respiratory tract. Neutralization, in which Ab bind to virion spikes and inhibit them from binding to and infecting target cells, is one widely reported protective mechanism. A second mechanism of Ab protection is muco-trapping, in which Ab crosslink virions to domains on mucin polymers, effectively immobilizing them in the mucus layer. When muco-trapped, the continuous clearance of the mucus barrier by coordinated ciliary propulsion entrains the trapped viral load toward the esophagus to be swallowed. We model and simulate the protection provided by either and both mechanisms at different locations in the respiratory tract, parametrized by the Ab titer and binding-unbinding rates of Ab to viral spikes and mucin domains. Our results illustrate limits in the degree of protection by neutralizing Ab alone, the powerful protection afforded by muco-trapping Ab, and the potential for dual protection by muco-trapping and neutralizing Ab to arrest a SARS-CoV-2 infection. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Inhalation of virus-loaded droplets as a clinically plausible pathway to deep lung infection

Respiratory viruses, such as SARS-CoV-2, preliminarily infect the nasopharyngeal mucosa. The mechanism of infection spread from the nasopharynx to the deep lung-which may cause a severe infection-is, however, still unclear. We propose a clinically plausible mechanism of infection spread to the deep lung through droplets, present in the nasopharynx, inhaled and transported into the lower respiratory tract. A coupled mathematical model of droplet, virus transport and virus infection kinetics is exercised to demonstrate clinically observed times to deep lung infection. The model predicts, in agreement with clinical observations, that severe infection can develop in the deep lung within 2.5-7 days of initial symptom onset. Results indicate that while fluid dynamics plays an important role in transporting the droplets, infection kinetics and immune responses determine infection growth and resolution. Immune responses, particularly antibodies and T-lymphocytes, are observed to be critically important for preventing infection severity. This reinforces the role of vaccination in preventing severe infection. Managing aerosolization of infected nasopharyngeal mucosa is additionally suggested as a strategy for minimizing infection spread and severity.

Numerical computation of effective thermal equilibria in stochastically switching Langevin systems

Stochastically switching force terms appear frequently in models of biological systems under the action of active agents such as proteins. The interaction of switching forces and Brownian motion can create an "effective thermal equilibrium," even though the system does not obey a potential function. In order to extend the field of energy landscape analysis to understand stability and transitions in switching systems, we derive the quasipotential that defines this effective equilibrium for a general overdamped Langevin system with a force switching according to a continuous-time Markov chain process. Combined with the string method for computing most-probable transition paths, we apply our method to an idealized system and show the appearance of previously unreported numerical challenges. We present modifications to the algorithms to overcome these challenges and show validity by demonstrating agreement between our computed quasipotential barrier and asymptotic Monte Carlo transition times in the system.

Modeling insights into SARS-CoV-2 respiratory tract infections prior to immune protection

Mechanistic insights into human respiratory tract (RT) infections from SARS-CoV-2 can inform public awareness as well as guide medical prevention and treatment for COVID-19 disease. Yet the complexity of the RT and the inability to access diverse regions pose fundamental roadblocks to evaluation of potential mechanisms for the onset and progression of infection (and transmission). We present a model that incorporates detailed RT anatomy and physiology, including airway geometry, physical dimensions, thicknesses of airway surface liquids (ASLs), and mucus layer transport by cilia. The model further incorporates SARS-CoV-2 diffusivity in ASLs and best-known data for epithelial cell infection probabilities, and, once infected, duration of eclipse and replication phases, and replication rate of infectious virions. We apply this baseline model in the absence of immune protection to explore immediate, short-term outcomes from novel SARS-CoV-2 depositions onto the air-ASL interface. For each RT location, we compute probability to clear versus infect; per infected cell, we compute dynamics of viral load and cell infection. Results reveal that nasal infections are highly likely within 1-2 days from minimal exposure, and alveolar pneumonia occurs only if infectious virions are deposited directly into alveolar ducts and sacs, not via retrograde propagation to the deep lung. Furthermore, to infect just 1% of the 140 m2 of alveolar surface area within 1 week, either 103 boluses each with 106 infectious virions or 106 aerosols with one infectious virion, all physically separated, must be directly deposited. These results strongly suggest that COVID-19 disease occurs in stages: a nasal/upper RT infection, followed by self-transmission of infection to the deep lung. Two mechanisms of self-transmission are persistent aspiration of infected nasal boluses that drain to the deep lung and repeated rupture of nasal aerosols from infected mucosal membranes by speaking, singing, or cheering that are partially inhaled, exhaled, and re-inhaled, to the deep lung.

The Microbiome as a Key Regulator of Female Genital Tract Barrier Function

The microbiome, the collection of microbial species at a site or compartment, has been an underappreciated realm of human health up until the last decade. Mounting evidence suggests the microbiome has a critical role in regulating the female genital tract (FGT) mucosa's function as a barrier against sexually transmitted infections (STIs) and pathogens. In this review, we provide the most recent experimental systems and studies for analyzing the interplay between the microbiome and host cells and soluble factors with an influence on barrier function. Key components, such as microbial diversity, soluble factors secreted by host and microbe, as well as host immune system, all contribute to both the physical and immunologic aspects of the FGT mucosal barrier. Current gaps in what is known about the effects of the microbiome on FGT mucosal barrier function are compared and contrasted with the literature of the gut and respiratory mucosa. This review article presents evidence supporting that the vaginal microbiome, directly and indirectly, contributes to how well the FGT protects against infection.

Enhancing nanoparticle penetration through airway mucus to improve drug delivery efficacy in the lung

Introduction: Airway mucus gel layer serves as a key delivery barrier that limits the performance of inhaled drug delivery nanoparticles. Conventional nanoparticles are readily trapped by the airway mucus and rapidly cleared from the lung via mucus clearance mechanisms. These nanoparticles cannot distribute throughout the lung airways, long-reside in the lung and/or reach the airway epithelium. To address this challenge, strategies to enhance particle penetration through the airway mucus have been developed and proof-of-concept has been established using mucus model systems..Areas covered: In this review, we first overview the biochemical and biophysical characteristics that render the airway mucus a challenging delivery barrier. We then introduce strategies to improve particle penetration through the airway mucus. Specifically, we walk through two classes of approaches, including modification of physicochemical properties of nanoparticles and modulation of barrier properties of airway mucus.Expert opinion: State-of-the-art strategies to overcome the airway mucus barrier have been introduced and experimentally validated. However, data should be interpreted in the comprehensive context of therapeutic delivery from the site of administration to the final destination to determine clinically-relevant approaches. Further, safety should be carefully monitored, particularly when it comes to mucus-altering strategies that may perturb physiological functions of airway mucus.