A biophysical basis for mucus solids concentration as a candidate biomarker for airways disease

Abstract

In human airways diseases, including cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD), host defense is compromised and airways inflammation and infection often result. Mucus clearance and trapping of inhaled pathogens constitute key elements of host defense. Clearance rates are governed by mucus viscous and elastic moduli at physiological driving frequencies, whereas transport of trapped pathogens in mucus layers is governed by diffusivity. There is a clear need for simple and effective clinical biomarkers of airways disease that correlate with these properties. We tested the hypothesis that mucus solids concentration, indexed as weight percent solids (wt%), is such a biomarker. Passive microbead rheology was employed to determine both diffusive and viscoelastic properties of mucus harvested from human bronchial epithelial (HBE) cultures. Guided by sputum from healthy (1.5-2.5 wt%) and diseased (COPD, CF; 5 wt%) subjects, mucus samples were generated in vitro to mimic in vivo physiology, including intermediate range wt% to represent disease progression. Analyses of microbead datasets showed mucus diffusive properties and viscoelastic moduli scale robustly with wt%. Importantly, prominent changes in both biophysical properties arose at ∼4 wt%, consistent with a gel transition (from a more viscous-dominated solution to a more elastic-dominated gel). These findings have significant implications for: (1) penetration of cilia into the mucus layer and effectiveness of mucus transport; and (2) diffusion vs. immobilization of micro-scale particles relevant to mucus barrier properties. These data provide compelling evidence for mucus solids concentration as a baseline clinical biomarker of mucus barrier and clearance functions.

Figure 1. Concentration (wt% solids including salts) of sputum for normal, COPD, and cystic fibrosis samples.

The data yields: for normal sputum, 1.7±0.56 wt% from 17 samples; for COPD sputum, 3.7±2.3 wt% from 47 samples; and for cystic fibrosis, 7.0%±2.3 wt% from 21 samples. The red lines on the figure at 1.5% and 5% show the range of HBE mucus solids concentrations assayed in this study.

Figure 2. Diffusivity properties of HBE mucus.

A) Particle trajectories of 1 µm diameter particles for four concentrations over 30 s. B) Ensemble-averaged MSD versus lag time for different mucus solids concentrations. The dashed line represents a viscous fluid; any smaller slope indicates sub-diffusive scaling. C) Individual or path-wise MSD (iMSD) for particles embedded in mucus samples color-coded by solids concentration, for 1.5, 2.0, 3.0 wt%. D) iMSD for particles embedded in mucus samples color-coded by solids concentration, for 3.0, 4.0, 5.0 wt%. Note the vertical scale disparity with Figure 2C .

Figure 3. Autocorrelation function data of diffusive particle in mucus.

A) Typical autocorrelation function (ACF) for a bead diffusing in mucus with 2.5 wt% solids. B) Individual, ensemble averaged and theoretical ACF for 2.5 wt% solids mucus. The equation for the theoretical ACF is given in the Materials and Methods section, from which the value of is obtained from Figure 3A . This plot is for the ACF in the x-coordinate, the ACF in the y-coordinate looks similar.

Figure 4. Scaling of the MSD versus mucus solids concentration, where .

A) Power law exponent. Squares represent the averaged values of and the vertical bands represent its range over all particle paths. The goodness of fit metric for the linear relationship is . B) Scaling of the MSD pre-factor, , with goodness of fit . C) Rough estimates of mean passage times of 1 micron particles through a 25 micron mucus layer versus wt% solids, based on scaling behavior from Figures 4A&B .

Figure 5. Frequency Dependent viscoelastic properties of mucus.

A) Frequency-dependent complex viscosity versus frequency for different mucus solids concentrations. B) The slope of the power law, , is indicated for each wt% solids, both numerically and with a rise vs. run plot. C) Storage, , and Loss, , moduli vs. frequency for mucus with 1.5 to 3.0 wt% solids. D), and vs. frequency for mucus with 3.0 to 5.0 wt% solids.

Figure 6. Mucus Gel Point.

A) Cartoon illustrating the mucus network changes for increasing macromolecule (mucin) concentration. The gel point (GP) is the point at which the strength of the chains interacting with one another engenders the elastic moduli () to be comparable in magnitude to the viscous moduli (). B) Master curve of ensemble-averaged MSDs. The solids concentration for sol-gel transition is obtained following , in this case breaking of the slope in the master curve indicates the sol-gel transition occurs at a solids concentration between 4.0 and 5.0 wt%.

Figure 7. Concentration dependent viscoelastic properties of mucus at key frequencies.

A) Elastic (storage) modulus, , versus mucus solids concentration for three representative frequencies (from cilia to tidal breathing). B) Viscous (loss) modulus, , versus mucus solids concentration for three representative frequencies.