(643b) Soft Membrane Model As an Anti-Biofilm Formation Design Strategy Based On Topographical Cues

Adhesion of bacteria to surfaces is the
starting point for formation of biofilms, which tend to be significantly less
responsive to antibiotics and antimicrobial stressors, compared with planktonic
bacteria. Nosocomial infections are the fourth leading cause of death in the
U.S. with 2 million cases per annum [1]. About 60?70% of the reported infection
cases are associated with implanted medical devices [1]. Thus, there is a
compelling need for new anti-biofilm biomaterials to effectively minimize
bacterial adhesion and colony formation on biomedical surfaces. The
physicochemical properties of natural anti-biofilm surfaces of marine organisms
are being actively studied to develop bioinspired anti-biofilm strategies. It
has been shown that majority of natural anti-biofilm surfaces have well
organized micro/nanoscale surfaces features. The work presented here aims to
advance the current understanding of the role of surface features in cell-textured
surface interactions with the ultimate goal of developing an anti-biofilm
design framework based on topographical cues.

 
METHODOLOGY

Pseudomonas aeruginosa (P. aeruginosa) PAO1, a rod-shaped (length (L_b)
≈ 1800 nm, diameter (D_b) ≈ 500 nm) opportunistic
human pathogen used as the model organism. Highly aligned Polystyrene (PS)
nanofibers were deposited on PS substrates (arithmetic mean roughness: R_a
< 2 nm) using the previously developed Spinneret based Tunable Engineered
Parameters (STEP) technique [2]. Considering the diameter of the bacteria,
three different fiber diameters (D_f) were selected and
entitled as small diameter (SD, D_f < D_b),
medium diameter (MD, D_f ≈ D_b), and
large diameter (LD, D_f > D_b) with the
average fiber diameters of 91±17 nm, 482±52 nm, 971±151 nm, respectively.
Fibers were deposited at spacing (shown as S_f in Fig. 1) from nearly
0 nm to several microns all on the same substrate. Considering the two main
characteristic lengths of the bacteria body (L_b and D_b),
the spacing between the fibers was categorized according to the following: (1) S_f
< D_b (S_f ≤ 300 nm), (2) S_f
≈ D_b (300 nm < S_f ≤ 600 nm),
(3) D_b < S_f ≤ L_b:
(600 nm < S_f ≤ 1800 nm), and (4) S_f
> L_b (S_f> 1800 nm).

Figure
1: The illustration of the geometrical parameters of A: fiber and B: bacteria.
C: Four dominant modes of the rod-shaped cell-fiber interactions. All scale
bars in the SEM images represent 500 nm.

Static retention assays were conducted by
placing triplicates of each surface in a suspension of P. aeruginosa
bacteria in phosphate buffered saline (PBS) with the starting optical density,
OD_600nm = 0.3 for 2.5 hours at 37 ^oC. In all assays
samples were suspended horizontally and face-down to eliminate the effect of
gravitational sedimentation.

Four dominant modes of interaction between
the bacteria and the parallel nanofibers were identified as follow (Figure
1-A3): CF (crossed the fiber), AS (aligned with the
spacing), CS (crossed the spacing), and AF (aligned with the fiber). Scanning electron microscope (SEM) imaging was
utilized to quantify modal density of adhesion of bacteria (number of
bacteria/fiber length) for each mode of adhesion for all 12 possible
combinations of D_f and S_f. For each
combination of the fiber diameter and spacing, the total density of adhesion
was calculated as the sum of the four modal densities. The statistical
differences between different situations were analyzed using one way ANOVA
followed by Tukey test.

 
RESULTS

The results demonstrated the presence of a minimum
experimental total adhesion density which occurs for samples with MD fibers at
spacing less than the bacterial diameter (Fig. 2). Comparing to the bare
surface this geometrical combination reduces bacterial adhesion by 40%.
Additionally, our experimental results show that bacteria developed
microcolonies (onset of biofilm formation) on the bare samples while the
engineered surface inhibited colony formation.

Figure
2. Distribution of the total adhesion
density of bacteria to the PS nanofiber textured surfaces as a function of
fiber diameter (D_f) and spacing (S_f).

Investigating the trends of the modal adhesion
densities reveals the main reason behind the observed optimum geometrical
conditions. Figure 3 presents the effect of the fiber diameter on the modal
adhesion densities for the optimum spacing (S_f< D_b).
It can be seen that bacteria predominantly cross the spacing between the fibers
(CS mode) for SD fibers. Increasing the fiber diameter promotes the density of
bacteria aligned in the spacing between two fibers (AS mode, p < 0.05) but
conversely demotes the adhesion density of the CS mode. These trends result in
the minimum total adhesion density (summation of the modal adhesion densities)
for the MD fibers and emergence of a critical fiber diameter (D_cr)
below which the preferred mode of adhesion changes from AS to the CS mode. Finding the intersection of the linear (R²
= 0.97) and power law curves (R² = 0.92) fitted to the modal
adhesion density of AS and CS respectively, we estimate that this critical
diameter would be D_cr ~ 313 nm, which is slightly smaller than bacteria diameter. Theoretically, D_cr supports minimum
total adhesion density (summation of
model adhesion density).

Modal adhesion density data disclose strong similarity
between bacteria - surface interactions and vesicle? surface interactions. When
a vesicle comes in contact with a rigid surface, it deforms. Its final shape
and state of the adhesion could be predicted by minimizing the total free
energy of adhesion: Total free energy of adhesion (DG_total)
= Gain in adhesion energy (DG_A) ? Cost terms arise from
the energy required for deformation (DG_D) which can be
attributed to different sources such as the curvature energy associated with
the bending the membrane, tension energy associated with increase of the
surface area, and the pressure energy associated with increase in volume.

Here, we use this concept to interpret our
experimental results on the interaction between the rigid cylindrical particle
(fiber) and the cylindrical vesicle (bacterium). For example, our experimental
results for the AF mode show that regardless of the spacing between two fibers,
this mode was never observed for MD fibers. Based on the aforementioned
thermodynamic principles, this observation can be explained as reducing the
fiber diameter increases the local curvature and consequently the cost of
deformation, resulting in weak adhesion or desorption of the vesicle [3]. We
observed adhesion in the AF mode for the LD fibers and not for the MD fibers,
because the lower curvature of the LD fibers results in lower cost of deformation
compared with the MD fiber. The AF mode was also observed for the SD fibers
because the small diameter of SD fibers makes it possible for bacteria to
interact with the flat substrate underneath the fibers and gain energy by
adhesion to the flat substrate along sides of the fiber, as shown in the SEM
image of the AF mode in Fig. 1.

Figure
3. Effect of the fiber diameter (D_f) on the modal density of
adhesion for S_f< D_b. AS, CS, CF are the
modes of adhesion illustrated in Figure 1. AF mode attachment density is insignificant
and is not included in the figure.

Following the above energy-based analysis, MD fibers
are less favorable than LD fibers because they provide less contact area and
also increase the cost of adhesion. Adhesion to SD fibers in CF mode is
favorable as it supports adhesion to the flat substrate
underneath the fiber which leads to energy gained due to adhesion. For
separation distances less than bacterial diameter (S_f < D_b)
the MD fibers support bacterial adhesion less than SD fibers since they prevent
direct contact of bacteria to

 
CONCLUSIONS

We have utilized nanofiber-textured model surfaces to
study the effect of topographical feature size, spacing, and local curvature on
the adhesion of bacteria at single cell level. We have experimentally
demonstrated the presence of an optimum antifouling topographical geometry. The
thermodynamic principles governing the vesicle-rigid surface interactions were
used to interpret the experimental data. A systematic design methodology for
empirical determination of the optimum antifouling topographical condition for
nanofiber textured surfaces is outlined using an energy-based approach. We
conclude that an appropriately designed local curvature of surface
topographical feature is not only able to reduce the gain in adhesion process
by providing less available binding sites (in all possible adhesion modes) but
also through increasing the cost of deformation. In future, we plan to utilize
the STEP fiber manufacturing platform to generate multi-scale assemblies of
controlled topographical features on surfaces in order to repel microorganisms
of different sizes.

 
REFERENCES

1.       
Bryers JD., Biotechnology and Bioengineering,
2008; 100, pp. 1-18.

2.       
A.S. Nain et al., Macromolecular
Rapid Communications,
2009, 30, pp. 1406-1412.

3.      Chen
JZY et al.,
Physical
Review E, 2010, 81, pp. 0119041-9.