Abstract
A vexing problem in cystic fibrosis (CF) pathogenesis has been to explain the high prevalence of Pseudomonas aeruginosa biofilms in CF airways. We speculated that airway surface liquid (ASL) hyperabsorption generates a concentrated airway mucus that interacts with P. aeruginosa to promote biofilms. To model CF vs. normal airway infections, normal (2.5% solids) and CF-like concentrated (8% solids) mucus were prepared, placed in flat chambers, and infected with an ≈5 × 103 strain PAO1 P. aeruginosa. Although bacteria grew to 1010 cfu/ml in both mucus concentrations, macrocolony formation was detected only in the CF-like (8% solids) mucus. Biophysical and functional measurements revealed that concentrated mucus exhibited properties that restrict bacterial motility and small molecule diffusion, resulting in high local bacterial densities with high autoinducer concentrations. These properties also rendered secondary forms of antimicrobial defense, e.g., lactoferrin, ineffective in preventing biofilm formation in a CF-like mucus environment. These data link airway surface liquid hyperabsorption to the high incidence of P. aeruginosa biofilms in CF via changes in the hydration-dependent physical–chemical properties of mucus and suggest that the thickened mucus gel model will be useful to develop therapies of P. aeruginosa biofilms in CF airways.
Keywords: mucus, rheology
Cystic fibrosis (CF) lung disease reflects the chronic bacterial infection of intrapulmonary airways with Pseudomonas aeruginosa biofilms (1, 2). P. aeruginosa biofilms have mostly been studied in flow chambers (3–7) that are good models for the biofilms that form on venous or urethral catheters under conditions of high flow rates and relatively high oxygen tensions. However, biofilms in CF airways form in thickened (concentrated) mucus gels that are relatively hypoxic and adherent to airway surfaces (see Fig. 1A) (8, 9). Recently, Sriramulu et al. (10) investigated the role autoregulators and amino acids play in the tightness of biofilm formation in a mucus stimulant of constant hydration. For the present study, we designed a culture system to investigate whether dehydration of the CF mucus environment may predispose to P. aeruginosa biofilm formation.
Fig. 1.
Growth of P. aeruginosa strain PAO1 in model systems for mucus plaques and plugs in CF airways. (A) Bacterial culture chambers mimicking mucus plaques and plugs of CF airways. (i) Plaque of thickened mucus covering a CF airway surface was mimicked with mucus placed in a 1-mm-deep plastic chamber in a humidified Petri dish, open to oxygen supply from the lumen (inset). (ii) Mucus plugs in CF airways were mimicked with mucus placed in a 1- mm-deep chamber with a plastic lid sealing the top to limit oxygen supply (inset). (B) Composition of 2.5% and 8% mucus samples. Mucin concentration was measured in normal (2.5% solids) and CF-like (8% solids) mucus by differential refractometry. Other molecules are defined as DNA, cellular debris, and other proteins [unpublished data from the Sheehan laboratory (University of North Carolina)]. (C) Bacterial growth curve in normal and CF-like mucus. Approximately 5 × 103 P. aeruginosa (PAO1) were deposited onto 2.5% and 8% solid mucus in open (i) and closed (ii) chambers. Bacterial number was counted at 0, 6, 24, 48, and 72 h; n = 3. (D) Oxygen partial pressure of P. aeruginosa-infected mucus. Oxygen partial pressure was measured at the bottom of bacterial cultures with oxygen-sensitive fluorescent probe; n = 5.
A key aspect of the model was the selection of mucus concentrations that mimic normal and CF mucus. Although measurements of mucus concentration, i.e., the percentage of solids content, from CF subjects before infection have not been reported, estimates from cell cultures (11) and sputum (12–18) suggest that CF mucus is at least three or four times more concentrated than normal. Therefore, mucus was obtained from well differentiated human airway cultures and was isotonically concentrated (1) to produce mucus of normal (2.5% solids wt/wt) and CF-like (8%) concentrations (Fig. 1B). Aliquots of each were deposited in (i) an open chamber to model a mucus plaque adherent to CF airway surfaces with a residual lumen allowing airflow and (ii) a closed chamber to mimic a mucus plug occluding a CF airway (Fig. 1A). P. aeruginosa [PAO1 strain stably expressing green fluorescent protein (GFP-PAO1)] was then deposited in 1-μl droplets (≈5 × 103 cfu) into mucus of the two concentrations to mimic the aerosol droplet infection that is thought to transmit P. aeruginosa in vivo.
Results
P. aeruginosa Growth and Growth Patterns in 2.5% vs. 8% Mucus.
P. aeruginosa grew and within 48 h reached the stationary phase at ≈1010 cfu/ml for 2.5% and 8% mucus in both open and closed chambers (Fig. 1C). In closed chambers, pO2 plunged below 5% ≈9 h after bacterial inoculation and remained low. In open chambers, pO2 remained higher in 2.5% mucus but was <5% at 24 h in 8% mucus (Fig. 1D). These data suggest that P. aeruginosa grew well in human airway mucus under hypoxic as well as normoxic environments, as previously reported (9, 19).
However, the growth pattern of P. aeruginosa (GFP-PAO1) was distinctly different in 2.5% vs. 8% mucus (Fig. 2). Epifluorescence and confocal microscopy studies of the open-chamber model of CF airway mucus plaques revealed that P. aeruginosa grew as macrocolonies within 8% mucus gels (Fig. 2 B and D). These macrocolonies contained both live and dead cells, and some macrocolonies exhibited band-like patterns of live and dead cells (Fig. 2E). In contrast, no macrocolonies were detected within 2.5% mucus gels, and only small bacterial aggregations were observed on the plastic surface (Fig. 2 A and C). To estimate colony volume, the total fluorescence intensity of P. aeruginosa colonies was measured and was significantly greater in 8% mucus than in 2.5% mucus (Fig. 2Fi). Importantly, the difference in the colony size between 2.5% mucus and 8% mucus was not due to bacterial growth (number of bacteria, Fig. 1C) but was due to growth pattern (planktonic vs. macrocolony).
Fig. 2.
P. aeruginosa macrocolony formation in mucus. (A–D) Bacteria GFP-PAO1 (≈5 × 103) were deposited into mucus of 2.5% solids (A and C) and 8% solids (B and D) placed in open chambers and photographed on days 1, 2, and 3 by epifluorescence (A and B) (×10 objective) and x–z confocal (C and D) (×40 objective) microscopy. (Scale bars = 200 μm in A and C and 50 μm in B and D.) Representative of n = 10 experiments. (E) Live and dead staining of P. aeruginosa macrocolonies. Pseudomonas macrocolonies in 8% mucus were photographed with x–y (i) and x–z (ii) scanning by confocal microscopy (green = GFP, red propidium iodide). (Scale bar = 50 μm.) (F) Quantitation of macrocolony size. Macrocolony size was expressed as the total fluorescence intensity of a single macrocolony, reflecting the number of bacteria forming a macrocolony. (i) open chamber, (ii) closed chamber; n = 3.
In the closed-chamber model of mucus plugs, intramucus macrocolonies were again detected in 8% mucus, whereas in 2.5% mucus, small colonies were only detected on plastic surfaces (not shown). The size of the macrocolonies developed in 8% mucus was smaller than in open chambers (Fig. 2Fii), suggesting that oxygen supply can affect macrocolony dimensions, in agreement with previous studies (9).
Because it is possible that CF mucus exhibits features other than increased concentration that promote biofilm formation, we studied 2.5% and 8% mucus from CF cultures. In both the open and closed systems, macrocolonies again were found in 8% but not in 2.5% CF mucus (Fig. 3A), suggesting that the concentration of mucus, rather than the source, was the critical variable. These data are consistent with previous data demonstrating no differences in the biochemical properties between the CF vs. normal mucins, the major component of mucus (20).
Fig. 3.
Variables influencing macrocolony development in mucus. (A) P. aeruginosa macrocolony formation in CF mucus. GFP-PAO1 (≈5 × 103 cfu) deposited in CF mucus exhibited macrocolony formation in 8% mucus (ii) but not in 2.5% mucus (i) 48 h after inoculation. (Scale bar = 200 μm.) (B) Effects of lasI gene mutation. Wild-type PAO1 (i) but not lasI mutants (ii) developed macrocolonies 48 h after inoculation with ≈5 × 103 bacteria. (Scale bar = 200 μm.) x–y (iii) and x–z (iv) scanning by confocal microscopy detected homogeneous distribution of planktonic single bacteria (lasI mutant) within mucus of 8% solids. (Scale bar = 50 μm.) The defective macrocolony formation was rescued by addition of 10 μM 3-oxo C12 HSL (v). (Scale bar = 200 μm.)
Development of P. aeruginosa biofilms is known to require the LasR-LasI quorum sensing system (4). To test whether the macrocolonies observed in airway surface liquid (ASL) were biofilms rather than loose aggregates of bacteria with low motility, we incubated lasI mutants of PAO1 in 8% mucus. These lasI mutants grew similarly to wild-type PAO1 in 8% mucus (≈1010 cfu/ml) (data not shown). x–y and x–z scanning confocal microscopy demonstrated planktonic single lasI mutant bacteria, but not macrocolonies, within 8% mucus (Fig. 3B iii and iv). The macrocolony phenotype was rescued with the addition of 10 μM N-(3-oxododecanoyl)-l-homoserine lactone (3-oxo C12 HSL) to 8% mucus (Fig. 3Bv). These data demonstrate that the macrocolonies in 8% mucus gels share genetic features with biofilms studied in other systems.
Biophysical Properties of Mucus Gels.
What is unique about an 8% vs. 2.5% mucus gel? The predominant macromolecules in airway mucus are the high-molecular-weight mucin polymers. These polymers form a gel-like mesh in ASL that exhibits an apparent mesh pore width and viscoelastic properties as a function of their concentration. We used a microbead rheological technique that probes an environment in which tracer particles are placed by tracking their thermally driven Brownian motion to characterize the biophysical (mesh, viscoelastic) properties of 8% vs. 2.5% mucus gels. This method provides an excellent insight into the physical environment observed by micrometer-sized particles (21–26) and, thus, is an appropriate method to characterize the environment experienced by P. aeruginosa [0.5 × 1.5 μm (27)].
The thermally driven motion of microbeads greatly depends on the percentage of solids of the mucus sample in which they diffused. At the long time scales (≈5 sec), the means squared displacement curve, Δr2, of 1-μm beads is 50 times greater in 2.5% mucus than in 8% mucus (Fig. 4A). The slope of the means squared displacement curve, α (see Methods), indicates that the fluid is liquid-like (purely viscous) when α = 1 and is solid-like (purely elastic) when α = 0. In 8% mucus, α was ≈0.2, whereas in 2.5% mucus, α was ≈0.8 (Fig. 4A), suggesting that the 8% mucus is highly elastic in nature.
Fig. 4.
Mechanisms of macrocolony development. (A) Mean squared displacement of 1-μm beads in 2.5% and 8% mucus. (B) Mean squared displacement times radius of 200-nm, 1-μm, and 3-μm beads in 2.5% and 8% mucus. (C) P. aeruginosa motility in mucus of 2.5% and 8% solids. (D) Diffusion of 3-oxo C12 HSL in 2.5% vs. 8% mucus; n = 6.
Tracking motion of beads of varying sizes provides information about the mesh properties of mucus (28, 29). In 2.5% mucus, 200-nm beads diffused over much greater distances than in 1- and 3-μm beads, even when corrected for bead radius (Fig. 4B). These results indicate that the effective “mesh size” within the 2.5% mucus is between 0.2 and 1 μm. In 8% mucus, all three bead sizes were effectively trapped (Fig. 4B), indicating that all were trapped in a tight mesh smaller than 200 nm. This tighter mesh is also reflected in the decreased slope of the means squared displacement curve for 8% mucus in Fig. 4A.
Interaction of P. aeruginosa with Mucus Gel.
We tested predictions from the biophysical characterization of mucus in a series of microbiological experiments. First, consistent with analyses of mesh size and bead motility, swimming (flagellar) motility of PAO1 was found to be greatly reduced in 8% vs. 2.5% mucus (Fig. 4C). Second, consistent with a measured mesh size of 0.2–1 μm, an immobile PAO1 mutant (without pili and flagella) placed in 2.5% mucus sedimented out of mucus onto the plastic surface (data not shown). Third, it is predicted that small molecules (much smaller than mesh size) will have equivalent diffusion in both mucus concentrations. However, 3-oxo C12 HSL (estimated to be smaller than 1 nm) diffused 10 times more slowly in 8% mucus vs. 2.5% mucus (calculated diffusion coefficient was 4.8 × 10−10 m2/s in 2.5% mucus and 4.9 × 10−11 m2/s in 8% mucus) (Fig. 4D). We speculate that the slower diffusion reflects either increased interactions between the hydrophobic 3-oxo C12 HSL molecules and the hydrophobic sites of the mucin mesh or HSL binding to mobile proteins larger than mesh size.
Effect of Mucus Gel on Soluble Innate Defense Molecules.
Finally, we asked whether there were unique aspects of thickened mucus that allow P. aeruginosa macrocolonies to evade soluble secondary-defense mechanisms that protect airway surfaces. Because of reports that lactoferrin was effective in inhibiting P. aeruginosa biofilm formation in well oxygenated, flow-through abiotic chamber surfaces (7), we studied lactoferrin effectiveness in 8% mucus gels.
Although the iron content (42.9 μM) of 8% mucus was in the range reported for CF mucus (17–134 μM) (30), we prepared low-iron mucus (8.4–12.3 μM) so that the iron-chelating capacity of physiological concentrations of lactoferrin (1 mg/ml, ≈22 μM) (31) was not exceeded. Pseudomonas formed macrocolonies in low-iron mucus (Fig. 5A), and this process was not inhibited by lactoferrin addition in concentrations predicted to be sufficient to chelate all iron (1 and 10 mg/ml) (Fig. 5B). A high concentration of conalbumin (10 mg/ml), reported to inhibit Pseudomonas macrocolony development (7), also had no effect on macrocolony formation in concentrated airway mucus (Fig. 5C). These results appear to mimic the condition in CF airways in vivo when biofilms form, despite apparently high concentrations of lactoferrin (2, 32). We also measured diffusion of fluorescently labeled lactoferrin from a point source in shallow chambers filled with either 2.5% or 8% mucus, mimicking submucosal gland secretion of lactoferrin into a mucus layer in the normal and CF airways. Like HSL, lactoferrin diffusion was markedly slowed in 8% mucus gels (Fig. 5D).
Fig. 5.
Absence of effects of lactoferrin on P. aeruginosa macrocolony development in 8% mucus. Mucus was infected with ≈5 × 103 PAO1 as above, and images were obtained by fluorescence microscopy 48 h later. (A) Low-iron mucus control. (B) Low-iron mucus with 10 mg/ml lactoferrin. (C) Low-iron mucus with 10 mg/ml conalbumin. (Scale bar = 200 μm.) (D) Diffusion of fluorescently labeled lactoferrin in mucus. Fluorescence intensity ratio between highest and lowest regions in 2.5% vs. 8% mucus after lactoferrin deposition as a point source was measured at 0, 3, 18, 24, and 48 h; n = 3.
Discussion
Our goal was to establish a simple model that mimics the interactions of inhaled Pseudomonas with a central feature of the CF lung, i.e., dehydrated, adherent mucus plaques (33). This simple model revealed two aspects of concentrated mucus gels characteristic of CF that may yield insights into the mode of P. aeruginosa growth in the CF lung.
First, our data suggest that the concentrated mucus (8%), regardless of source (i.e., CF vs. normal), generates a unique environment in which bacteria are confined spatially so that multiplication at a site of droplet deposition outstrips the capacity of bacteria to leave the site by their normal means of motility. The mucin concentration-specific effect on mucus mesh size produces high local concentrations of autoinducers by limiting 3-oxo C12 HSL diffusion away from the site of bacterial replication, producing an environment that favors biofilm (macrocolony) formation. Note that our experimental system is designed to mimic the acquisition of infection in CF, i.e., we use concentrated mucus from noninfected cultures exposed to droplets containing bacteria. Dawson et al. (28), however, have used the microbead technology to characterize biophysical features of infected CF sputum. The identification of similar biophysical properties suggests that infected, but still concentrated, CF sputum also favors biofilm formation.
Second, multiple features of thickened CF mucus gels may account for the ineffectiveness of a major endogenous antimicrobial substance in mucus, i.e., lactoferrin, to inhibit biofilm formation in CF airway mucus as compared with its effectiveness in flow-through chambers/abiotic surfaces. First, the reported effects of lactoferrin to increase twitch motility in flow chambers (7) are likely less important when motility is restricted by a mucus gel of 8% solids rather than intrinsic bacterial motility. Second, lactoferrin may inhibit bacterial growth/biofilms by direct interactions with bacteria. This activity may be reduced in concentrated mucus as lactoferrin becomes bound (or diffusion limited) and not freely available. Third, in vivo in CF airways, lactoferrin secreted from submucosal glands would be predicted (Fig. 5D) to diffuse poorly into the stationary thickened mucus, containing P. aeruginosa biofilms, on airway surfaces.
Pseudomonas infection leads to a deterioration in the clinical course of CF patients (34–36), but the unique predisposing features that produce a persistent Pseudomonas infection in the CF airway have been unclear. Previously, it had been reported that ASL hyperabsorption in CF produces periciliary liquid depletion and mucus stasis that favor acquisition of infection (1, 33). Our data suggest that this common event, i.e., ASL hyperabsorption, produces a concentrated mucus gel that promotes P. aeruginosa to grow as macrocolony-like biofilms due to the physical properties of a tight mucin mesh, and increased viscoelastic properties that limit bacterial motility and 3-oxo C12 HSL diffusion. Further, our data add to an understanding of how concentrated, dehydrated CF mucus impairs the host defense. Previous studies have shown that the reduced mesh pore size produced by mucus concentration reduces the effectiveness of neutrophils to penetrate and kill P. aeruginosa residing in concentrated, but not “normal,” mucus gels (37). The present study demonstrates that the activity of a soluble host defense factor, i.e., lactoferrin, is also degraded in concentrated, CF-like gels. Among the therapies suggested by these studies, perhaps the most direct is to rehydrate thickened mucus to normalize mesh pore size.
Methods
Preparation of Concentrated Mucus.
Human tracheo–bronchial epithelial cells (CF and normal) were isolated and cultured under air–liquid conditions as previously described (38). Mucus harvested from ≈200 concurrent cultures was pooled and stored at 4°C. The mucus samples were placed in dialysis tubes (molecular weight of CO = 3,500; Spectrum Laboratories, Rancho Dominguez, CA) and concentrated with a polymer absorbent (Spectra/Gel; Spectrum Laboratories) for 1–5 days at 4°C. The concentrated mucus was dialyzed against PBS (3 liters, four times) containing 500 μM MgCl2 and 800 μM CaCl2 at 4°C. The percent dry weight of mucus was calculated by measuring the wet and dry weights with a microbalance before and after drying the sample at 80°C overnight (39). Because of the difficulty in depleting harvested mucus samples of exact volumes, a 10% difference from the target concentration was allowed.
Determination of Mucin Concentration.
The concentration of mucins in mucus was assessed by differential refractometry (40). A 500-μl sample was chromatographed on a Sepharose CL-2B column (Amersham Pharmacia, Piscataway, NJ), which was eluted with 200 mM sodium chloride/10 mM EDTA at a flow rate 0.3 ml/min. The column effluent was passed through an in-line Dawn EOS laser photometer coupled to a Wyatt/Optilab DSP inferometric refractometer to measure light scattering and sample concentration, respectively. The concentration of the mucins was calculated by integrating the refractive index peak associated with the material eluted in the void volume of the column and employing a value for the refractive-index increment (dn/dc) of 0.165 ml/g, which has been measured previously at 650 nm. The reproducibility of this procedure was within 5%.
Preparation of Bacteria and Autoinducers 3-oxo C12 HSL.
P. aeruginosa PAO1 (41), an isogenic lasI mutant (42), and a nonpiliated, nonflagellated mutant (PAO-NPNF, kind gift from A. Prince) were maintained on trypticase soy agar (Becton-Dickinson, Sparks, MD) with appropriate antibiotics as needed (gentamycin, 50 μg/ml; Sigma). In addition, the plasmid pTdK-gfp (43) was introduced by using electroporation (44) into these strains to allow visualization of the bacteria. Overnight cultures of bacteria were prepared for each assay with appropriate antibiotics when needed (200 μg/ml carbenicillin; Sigma). Autoinducer 3-oxo C12 HSL was synthesized and purified as previously reported (45) and used as received.
Bacterial Culture in Mucus.
To measure bacterial growth, ≈5 × 103 PAO1 were deposited on 270 μl of mucus of varying concentrations in a plastic flat chamber (1 mm in depth, 20 mm in diameter) with or without a plastic lid. At 0, 6, 24, 48, and 72 h later, bacteria in mucus were collected, diluted with PBS containing 10 mM DTT, and plated on tryptic soy agar plates after serial dilution. DTT treatment disaggregated the bacteria and did not affect the viability of the bacteria.
To measure macrocolony development, ≈5 × 103 GFP-PAO1 were deposited onto mucus in the same plastic chambers and observed by epifluorescent (Nikon TE300) or confocal (Zeiss 510) microscopy at 24, 48, and 72 h. For quantitation, five pictures for each culture were digitally acquired and analyzed by using the Metamorph image analysis system (Universal Image). A bacterial colony was defined as a structure with a discrete edge and size larger than 50 μm2. Dead bacteria were stained at day 3 with 5 μg/ml propidium iodide (molecular probes), which is impermeable into intact bacteria. The resolution of these images was too low to determine the internal structures of the biofilms.
Measurement of Oxygen.
Oxygen partial pressure was measured with an oxygen-sensitive fluorescent probe, the ruthenium complex Tris(4,7-diphenyl-1,10-phenanthroline)-ruthenium hexafluorophosphate (Sigma–Aldrich, St. Louis, MO). The ruthenium complex, adsorbed onto silica particles (1–5 μm; Sigma), was embedded in silicone rubber (silicone II; GE) and pasted onto glass slides (46). The coated glass slides were then used as the bottom of the bacterial culture chamber (Fig. 1B). Fluorescence intensity was measured by confocal microscopy at 3, 6, 9, 24, and 48 h to calculate oxygen partial pressure. Each glass-slide probe was calibrated with uninfected mucus for 21% pO2 and with saturated sodium sulfite solution for 0% pO2 at time 0. At each time point, artificial fluctuation of fluorescence intensity, caused partly by laser power instability, was corrected by measuring fluorescence intensity of distilled water (pO2 = 21%) and sodium sulfite solution (pO2 = 0%).
Bacterial Motility in Mucus.
GFP-PAO1 was deposited onto mucus (2.5% and 8% solids) in the plastic chamber and photographed by epifluorescent microscope with a ×40 objective at an interval of 0.25–1 sec. Only planktonic bacteria observed to undergo unidirectional motion were used to calculate bacterial velocity.
Diffusion of 3-oxo C12 HSL in Mucus.
A 10 mM 3-oxo C12 HSL solution in DMSO was mixed with a 10× volume of mucus (2.5% or 8% solids) to prepare the source of HSL. Capillary tubes (40 mm in length, 25-μl capacity; Statspin Technologies, Norwood, MA) containing 2.5% or 8% mucus were placed in the tubes containing HSL in an equivalent mucus concentration and had the free end sealed with silicone. After 24 h at 37°C, the capillary tubes with mucus were frozen and cut into eight pieces to measure the 3-oxo C12 HSL concentration in each section.
Autoinducer was extracted from each mucus cross-section by using ethyl acetate (J. T. Baker) acidified with 0.001% glacial acetic acid (J. T. Baker) as previously described (47) with the following modifications. Twice the sample volume of acidified ethyl acetate was added to the mucus sample suspended in 100 μl of PBS in a 1.5- ml Eppendorf tube. Samples were subsequently vortexed for 3 min, and the two phases were separated by centrifugation at 10,000 × g for 10 min. The ethyl acetate phase was then transferred to a clean 1.5-ml Eppendorf tube. The extraction process was repeated once more, and the ethyl acetate phases were pooled. The concentration of 3-oxo C12 HSL was assayed in each sample by using the previously described bioassay (47). The number of moles of 3-oxo C12 HSL in each sample was then normalized to the total number of moles of 3-oxo C12 HSL extracted from all samples in each assay and reported as percent occurrence. Each experiment was repeated in quadruplicate.
The diffusion coefficient was calculated by fitting a Gaussian to data collected for the distribution of radioactive molecules in 1D dimension. The distribution was defined by:
(48), where D is the diffusion coefficient and t is the time over which diffusion has occurred.
Microbead Rheology.
MyOne 1-μm-diameter carboxylated beads (Dynal), 2.9-μm-diameter yellow-green fluorescent carboxylated beads (Polysciences), and 200-nm-diameter red fluorescent carboxylated beads (Polysciences) were added to mucus samples, and their diffusion was recorded at 120 frames per second with a Pulnix PTM-6710 8-bit grayscale video camera (Jai-Pulnix) on a Nikon Eclipse TE2000-E inverted microscope with a ×60 water immersion objective (NA = 1.2). Beads were tracked in postprocessing by using Video Spot Tracker (software available for free download at http://www.cs.unc.edu/Research/nano/cismm/download/spottracker/video_spot_tracker.html). The average noise signal of a fixed bead was 5 nm.
Eq. 1 is used to calculate the mean squared displacement of particles undergoing Brownian motion within the fluid, Δr̄2(τ), over three decades of data (where τ is the time interval between measurements) (24).
![]() |
The slope of the mean squared displacement curve in log–log space,
ranges between 0 for purely elastic fluids and 1 for purely viscous fluids and is used to characterize the degree of elasticity measured in a fluid (24).
Effects of Lactoferrin on Pseudomonas Macrocolony Formation.
GFP-PAO1 was deposited onto concentrated mucus of 8% solids containing lactoferrin (iron-unsaturated, Sigma) or conalbumin (Sigma) (final concentrations, 1 and 10 mg/ml). Macrocolony formation was monitored as mentioned above at days 1, 2, and 3.
Measurement of Iron in Mucus Samples.
Total iron content of mucus samples was measured after trichloroacetic acid precipitation (20%, 1:1) with a flame atomic absorption spectrometer (49) (AAnalyst 100; Perkin–Elmer, Wellesley, MA).
Diffusion of Lactoferrin.
One microliter of human lactoferrin solution labeled with Oregon Green (1 mg/ml; Molecular Probes) was deposited at four points onto an open chamber containing 270 μl of mucus (2.5% or 8% solids). After 0, 3, 18, 24, and 48 h of incubation at 37°C, fluorescent intensity was measured at the brightest and dimmest points, by using Nikon TE300 with a ×4 objective. Fluorescence intensities were normalized against control images of mucus with no lactoferrin.
Acknowledgments
We thank K. Burns and Dr. John K Sheehan for expert technical assistance and the members of the University of North Carolina Virtual Lung Group for many useful discussions. This study was supported by National Institutes of Health Grants HL33242 and NIH P50 HL060280 (to H.M. and R.C.B.), NIH R37AI37713 (to B.H.I.), and NIH P41 EB002025-21 (to R.S. and R.M.T.) and the Cystic Fibrosis Foundation.
Abbreviation
- CF
cystic fibrosis.
Footnotes
The authors declare no conflict of interest.
This article is a PNAS direct submission.
References
- 1.Matsui H, Grubb BR, Tarran R, Randell SH, Gatzy JT, Davis CW, Boucher RC. Cell. 1998;95:1005–1015. doi: 10.1016/s0092-8674(00)81724-9. [DOI] [PubMed] [Google Scholar]
- 2.Pedersen SS. APMIS Suppl. 1992;28:1–79. [PubMed] [Google Scholar]
- 3.Christensen BB, Sternberg C, Andersen JB, Palmer RJ, Nielsen AT, Givskov M, Molin S. In: Biofilms. Abelson JN, Simon MI, editors. Vol 310. San Diego: Academic; 1999. pp. 20–42. [Google Scholar]
- 4.Davies DG, Parsek MR, Pearson JP, Iglewski BH, Costerton JW, Greenberg EP. Science. 1998;280:295–298. doi: 10.1126/science.280.5361.295. [DOI] [PubMed] [Google Scholar]
- 5.Donlan RM, Costerton JW. Clin Microbiol Rev. 2002;15:167–193. doi: 10.1128/CMR.15.2.167-193.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Drenkard E, Ausubel FM. Nature. 2002;416:740–743. doi: 10.1038/416740a. [DOI] [PubMed] [Google Scholar]
- 7.Singh PK, Parsek MR, Greenberg EP, Welsh MJ. Nature. 2002;417:552–555. doi: 10.1038/417552a. [DOI] [PubMed] [Google Scholar]
- 8.Baltimore RS, Christie CDC, Smith GJW. Am Rev Respir Dis. 1989;140:1650–1661. doi: 10.1164/ajrccm/140.6.1650. [DOI] [PubMed] [Google Scholar]
- 9.Worlitzsch D, Tarran R, Ulrich M, Schwab U, Cekici A, Meyer KC, Birrer P, Bellon G, Berger J, Weiss T, et al. J Clin Invest. 2002;109:317–325. doi: 10.1172/JCI13870. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Sriramulu DD, Lunsdorf H, Lam JS, Romling U. J Med Microbiol. 2005;54:667–676. doi: 10.1099/jmm.0.45969-0. [DOI] [PubMed] [Google Scholar]
- 11.Tarran R, Grubb BR, Parsons D, Picher M, Hirsh AJ, Davis CW, Boucher RC. Mol Cell. 2001;8:149–158. doi: 10.1016/s1097-2765(01)00286-6. [DOI] [PubMed] [Google Scholar]
- 12.Chernick WS, Barbero GJ. Pediatrics. 1959;24:739–745. [PubMed] [Google Scholar]
- 13.Deneuville E, PerrotMinot C, Pennaforte F, Roussey M, Zahm JM, Clavel C, Puchelle E, deBentzmann S. Am J Respir Crit Care Med. 1997;156:166–172. doi: 10.1164/ajrccm.156.1.9606123. [DOI] [PubMed] [Google Scholar]
- 14.Lopezvidriero MT, Reid L. Br Med Bull. 1978;34:63–74. doi: 10.1093/oxfordjournals.bmb.a071461. [DOI] [PubMed] [Google Scholar]
- 15.Matthews LW, Potter JL, Lemm J, Spector S. Am Rev Respir Dis. 1963;88:199–204. doi: 10.1164/arrd.1963.88.2.199. [DOI] [PubMed] [Google Scholar]
- 16.Puchelle E, Zahm JM, de Bentzmann S, Gaillard D. In: Airway Mucus. Rodgers DF, Lethem MI, editors. Basel: Birkhsueser; 1997. [Google Scholar]
- 17.Tomkiewicz RP, App EM, Zayas JG, Ramirez O, Church N, Boucher RC, Knowles MR, King M. Am Rev Respir Dis. 1993;148:1002–1007. doi: 10.1164/ajrccm/148.4_Pt_1.1002. [DOI] [PubMed] [Google Scholar]
- 18.Trout L, King M, Feng W, Inglis SK, Ballard ST. Am J Physiol. 1998;18:L258–L263. doi: 10.1152/ajplung.1998.274.2.L258. [DOI] [PubMed] [Google Scholar]
- 19.Yoon SS, Hennigan RF, Hilliard GM, Ochsner UA, Parvatiyar K, Kamani MC, Allen HL, DeKievit TR, Gardner PR, Schwab U, et al. Dev Cell. 2002;3:593–603. doi: 10.1016/s1534-5807(02)00295-2. [DOI] [PubMed] [Google Scholar]
- 20.Holmen JM, Karlsson NG, Abdullah LH, Randell SH, Sheehan JK, Hansson GC, Davis CW. Am J Physiol Lung Cell Mol Physiol. 2004;287:L824–L834. doi: 10.1152/ajplung.00108.2004. [DOI] [PubMed] [Google Scholar]
- 21.Apgar J, Tseng Y, Fedorov E, Herwig MB, Almo SC, Wirtz D. Biophys J. 2000;79:1095–1106. doi: 10.1016/S0006-3495(00)76363-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Mason TG, Ganesan K, vanZanten JH, Wirtz D, Kuo SC. Phys Rev Lett. 1997;79:3282–3285. [Google Scholar]
- 23.Gittes F, Schnurr B, Olmsted PD, MacKintosh FC, Schmidt CF. Phys Rev Lett. 1997;79:3286–3289. [Google Scholar]
- 24.Mason TG. Rheol Acta. 2000;39:371–378. [Google Scholar]
- 25.McGrath JL, Hartwig JH, Kuo SC. Biophys J. 2000;79:3258–3266. doi: 10.1016/S0006-3495(00)76558-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Valentine MT, Kaplan PD, Thota D, Crocker JC, Gisler T, Prud'homme RK, Beck M, Weitz DA. Phys Rev E Stat Nonlin Soft Matter Phys. 2001:6406. doi: 10.1103/PhysRevE.64.061506. [DOI] [PubMed] [Google Scholar]
- 27.Schneider WR, Doetsch RN. J Bacteriol. 1974;117:696–701. doi: 10.1128/jb.117.2.696-701.1974. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Dawson M, Wirtz D, Hanes J. J Biol Chem. 2003;278:50393–50401. doi: 10.1074/jbc.M309026200. [DOI] [PubMed] [Google Scholar]
- 29.Raynal BDE, Hardingham TE, Sheehan JK, Thornton DJ. J Biol Chem. 2003;278:28703–28710. doi: 10.1074/jbc.M304632200. [DOI] [PubMed] [Google Scholar]
- 30.Reid DW, Withers NJ, Francis L, Wilson JW, Kotsimbos TC. Chest. 2002;121:48–54. doi: 10.1378/chest.121.1.48. [DOI] [PubMed] [Google Scholar]
- 31.Ganz T. J Clin Invest. 2002;109:693–697. doi: 10.1172/JCI15218. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Singh PK, Schaefer AL, Parsek MR, Moninger TO, Welsh MJ, Greenberg EP. Nature. 2000;407:762–764. doi: 10.1038/35037627. [DOI] [PubMed] [Google Scholar]
- 33.Mall M, Grubb BR, Harkema JR, O'Neal WK, Boucher RC. Nature Medicine. 2004;10:487–493. doi: 10.1038/nm1028. [DOI] [PubMed] [Google Scholar]
- 34.Emerson J, Rosenfeld M, McNamara S, Ramsey B, Gibson RL. Pediatr Pulmonol. 2002;34:91–100. doi: 10.1002/ppul.10127. [DOI] [PubMed] [Google Scholar]
- 35.Henry RL, Mellis CM, Petrovic L. Pediatr Pulmonol. 1992;12:158–161. doi: 10.1002/ppul.1950120306. [DOI] [PubMed] [Google Scholar]
- 36.Schaedel C, de Monestrol I, Hjelte L, Johannesson M, Kornfalt R, Lindblad A, Strandvik B, Wahlgren L, Holmberg L. Pediatr Pulmonol. 2002;33:483–491. doi: 10.1002/ppul.10100. [DOI] [PubMed] [Google Scholar]
- 37.Matsui H, Verghese MW, Kesimer M, Schwab UE, Randell SH, Sheehan JK, Grubb BR, Boucher RC. J Immunol. 2005;175:1090–1099. doi: 10.4049/jimmunol.175.2.1090. [DOI] [PubMed] [Google Scholar]
- 38.Matsui H, Randell SH, Peretti SW, Davis CW, Boucher RC. J Clin Invest. 1998;102:1125–1131. doi: 10.1172/JCI2687. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Knowles MR, Robinson JM, Wood RE, Pue CA, Mentz WM, Wager GC, Gatzy JT, Boucher RC. J Clin Invest. 1997;100:2588–2595. doi: 10.1172/JCI119802. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Kirkham S, Sheehan JK, Knight D, Richardson PS, Thornton DJ. Biochem J. 2002;361:537–546. doi: 10.1042/0264-6021:3610537. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Holloway BW, Krishnapillai V, Morgan AF. Microbiol Rev. 1979;43:73–102. doi: 10.1128/mr.43.1.73-102.1979. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Pearson JP, Pesci EC, Iglewski BH. J Bacteriol. 1997;179:5756–5767. doi: 10.1128/jb.179.18.5756-5767.1997. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.De Kievit TR, Gillis R, Marx S, Brown C, Iglewski BH. Appl Environ Microbiol. 2001;67:1865–1873. doi: 10.1128/AEM.67.4.1865-1873.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Smith AW, Iglewski BH. Nucleic Acids Res. 1989;17:10509. doi: 10.1093/nar/17.24.10509. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Kline T, Bowman J, Iglewski BH, de Kievit T, Kakai Y, Passador L. Bioorg Med Chem Lett. 1999;9:3447–3452. doi: 10.1016/s0960-894x(99)00626-5. [DOI] [PubMed] [Google Scholar]
- 46.Itoh T, Yaegashi K, Kosaka T, Kinoshita T, Morimoto T. Am J Physiol. 1994;36:H2068–H2078. doi: 10.1152/ajpheart.1994.267.5.H2068. [DOI] [PubMed] [Google Scholar]
- 47.Pearson JP, Gray KM, Passador L, Tucker KD, Eberhard A, Iglewski BH, Greenberg EP. Proc Natl Acad Sci USA. 1994;91:197–201. doi: 10.1073/pnas.91.1.197. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Kittel C, Froemer H. Thermal Physics. New York: WH Freeman and Company; 1980. [Google Scholar]
- 49.Olson AD, Hamlin WB. Clin Chem. 1969;15:438–444. [PubMed] [Google Scholar]






