Mucus concentration-dependent biophysical abnormalities unify submucosal gland and superficial airway dysfunction in cystic fibrosis

Cystic fibrosis (CF) is characterized by abnormal transepithelial ion transport. However, a description of CF lung disease pathophysiology unifying superficial epithelial and submucosal gland (SMG) dysfunctions has remained elusive. We hypothesized that biophysical abnormalities associated with CF mucus hyperconcentration provide a unifying mechanism. Studies of the anion secretion-inhibited pig airway model of CF revealed elevated SMG mucus concentrations, osmotic pressures, and SMG mucus accumulation. Human airway studies revealed hyperconcentrated CF SMG mucus with raised osmotic pressures and cohesive forces predicted to limit SMG mucus secretion/release. Using proline-rich protein 4 (PRR4) as a biomarker of SMG secretion, CF sputum proteomics analyses revealed markedly lower PRR4 levels compared to healthy and bronchiectasis controls, consistent with a failure of CF SMGs to secrete mucus onto airway surfaces. Raised mucus osmotic/cohesive forces, reflecting mucus hyperconcentration, provide a unifying mechanism that describes disease-initiating mucus accumulation on airway surfaces and in SMGs of the CF lung.

GlycoGrip: Cell Surface-Inspired Universal Sensor for Betacoronaviruses

Inspired by the role of cell-surface glycoproteins as coreceptors for pathogens, we report the development of GlycoGrip: a glycopolymer-based lateral flow assay for detecting SARS-CoV-2 and its variants. GlycoGrip utilizes glycopolymers for primary capture and antispike antibodies labeled with gold nanoparticles for signal-generating detection. A lock-step integration between experiment and computation has enabled efficient optimization of GlycoGrip test strips which can selectively, sensitively, and rapidly detect SARS-CoV-2 and its variants in biofluids. Employing the power of the glycocalyx in a diagnostic assay has distinct advantages over conventional immunoassays as glycopolymers can bind to antigens in a multivalent capacity and are highly adaptable for mutated strains. As new variants of SARS-CoV-2 are identified, GlycoGrip will serve as a highly reconfigurable biosensor for their detection. Additionally, via extensive ensemble-based docking simulations which incorporate protein and glycan motion, we have elucidated important clues as to how heparan sulfate and other glycocalyx components may bind the spike glycoprotein during SARS-CoV-2 host-cell infection. GlycoGrip is a promising and generalizable alternative to costly, labor-intensive RT-PCR, and we envision it will be broadly useful, including for rural or low-income populations that are historically undertested and under-reported in infection statistics.

Molecular Dynamics Simulations to Explore the Structure and Rheological Properties of Normal and Hyperconcentrated Airway Mucus

We develop the first molecular dynamics model of airway mucus based on the detailed physical properties and chemical structure of the predominant gel-forming mucin MUC5B. Our airway mucus model leverages the LAMMPS open-source code [https://lammps.sandia.gov], based on the statistical physics of polymers, from single molecules to networks. On top of the LAMMPS platform, the chemical structure of MUC5B is used to superimpose proximity-based, non-covalent, transient interactions within and between the specific domains of MUC5B polymers. We explore feasible ranges of hydrophobic and electrostatic interaction strengths between MUC5B domains with 9 nanometer spatial and 1 nanosecond temporal resolution. Our goal here is to propose and test a mechanistic hypothesis for a striking clinical observation with respect to airway mucus: a 10-fold increase in non-swellable, dense structures called flakes during progression of cystic fibrosis disease. Among the myriad possible effects that might promote self-organization of MUC5B networks into flake structures, we hypothesize and confirm that the clinically confirmed increase in mucin concentration, from 1.5 to 5 mg/mL, alone is sufficient to drive the structure changes observed with scanning electron microscopy images from experimental samples. We post-process the LAMMPS simulated datasets at 1.5 and 5 mg/mL, both to image the structure transition and compare with scanning electron micrographs and to show that the 3.33-fold increase in concentration induces closer proximity of interacting electrostatic and hydrophobic domains, thereby amplifying the proximity-based strength of the interactions.

Catching COVID: Engineering Peptide-Modified Surface-Enhanced Raman Spectroscopy Sensors for SARS-CoV-2

COVID-19 remains an ongoing issue across the globe, highlighting the need for a rapid, selective, and accurate sensor for SARS-CoV-2 and its emerging variants. The chemical specificity and signal amplification of surface-enhanced Raman spectroscopy (SERS) could be advantageous for developing a quantitative assay for SARS-CoV-2 with improved speed and accuracy over current testing methods. Here, we have tackled the challenges associated with SERS detection of viruses. As viruses are large, multicomponent species, they can yield different SERS signals, but also other abundant biomolecules present in the sample can generate undesired signals. To improve selectivity in complex biological environments, we have employed peptides as capture probes for viral proteins and developed an angiotensin-converting enzyme 2 (ACE2) mimetic peptide-based SERS sensor for SARS-CoV-2. The unique vibrational signature of the spike protein bound to the peptide-modified surface is identified and used to construct a multivariate calibration model for quantification. The sensor demonstrates a 300 nM limit of detection and high selectivity in the presence of excess bovine serum albumin. This work provides the basis for designing a SERS-based assay for the detection of SARS-CoV-2 as well as engineering SERS biosensors for other viruses in the future.

Catching COVID: Engineering Peptide-Modified Surface-Enhanced Raman Spectroscopy Sensors for SARS-CoV-2

COVID-19 remains an ongoing issue across the globe, highlighting the need for a rapid, selective, and accurate sensor for SARS-CoV-2 and its emerging variants. The chemical specificity and signal amplification of surface-enhanced Raman spectroscopy (SERS) could be advantageous for developing a quantitative assay for SARS-CoV-2 with improved speed and accuracy over current testing methods. Here, we have tackled the challenges associated with SERS detection of viruses. As viruses are large, multicomponent species, they can yield different SERS signals, but also other abundant biomolecules present in the sample can generate undesired signals. To improve selectivity in complex biological environments, we have employed peptides as capture probes for viral proteins and developed an angiotensin-converting enzyme 2 (ACE2) mimetic peptide-based SERS sensor for SARS-CoV-2. The unique vibrational signature of the spike protein bound to the peptide-modified surface is identified and used to construct a multivariate calibration model for quantification. The sensor demonstrates a 300 nM limit of detection and high selectivity in the presence of excess bovine serum albumin. This work provides the basis for designing a SERS-based assay for the detection of SARS-CoV-2 as well as engineering SERS biosensors for other viruses in the future.

A Programmable Toolkit to Dynamically Signal Cells Using Peptide Strand Displacement

The native extracellular matrix communicates and interacts with cells by dynamically displaying signals to control their behavior. Mimicking this dynamic environment in vitro is essential in order to unravel how cell-matrix interactions guide cell fate. Here, we present a synthetic platform for the temporal display of cell-adhesive signals using coiled-coil peptides. By designing an integrin-engaging coiled-coil pair to have a toehold (unpaired domain), we were able to use a peptide strand displacement reaction to remove the cell cue from the surface. This allowed us to test how the user-defined display of RGDS ligands at variable duration and periodicity of ligand exposure influence cell spreading degree and kinetics. Transient display of α_Vβ₃-selective ligands instructed fibroblast cells to reversibly spread and contract in response to changes in ligand exposure over multiple cycles, exhibiting a universal kinetic response. Also, cells that were triggered to spread and contract repeatedly exhibited greater enrichment of integrins in focal adhesions versus cells cultured on persistent RGDS-displaying surfaces. This dynamic platform will allow us to uncover the molecular code by which cells sense and respond to changes in their environment and will provide insights into ways to program cellular behavior.