The nanopattern on the surface of Clanger cicada (Psaltoda claripennis) wings represents the first example of a new class of biomaterials that can kill bacteria on contact based solely on their physical surface structure. The wings provide a model for the development of novel functional surfaces that possess an increased resistance to bacterial contamination and infection. We propose a biophysical model of the interactions between bacterial cells and cicada wing surface structures, and show that mechanical properties, in particular cell rigidity, are key factors in determining bacterial resistance/sensitivity to the bactericidal nature of the wing surface. We confirmed this experimentally by decreasing the rigidity of surface-resistant strains through microwave irradiation of the cells, which renders them susceptible to the wing effects. Our findings demonstrate the potential benefits of incorporating cicada wing nanopatterns into the design of antibacterial nanomaterials.

Despite the volume of work that has been conducted on the topic, the role of surface topography in mediating bacterial cell adhesion is not well understood. The primary reason for this lack of understanding is the relatively limited extent of topographical characterisation employed in many studies. In the present study, the topographies of three sub-nanometrically smooth titanium (Ti) surfaces were comprehensively characterised, using nine individual parameters that together describe the height, shape and distribution of their surface features. This topographical analysis was then correlated with the adhesion behaviour of the pathogenic bacteria Staphylococcus aureus and Pseudomonas aeruginosa, in an effort to understand the role played by each aspect of surface architecture in influencing bacterial attachment. While P. aeruginosa was largely unable to adhere to any of the three sub-nanometrically smooth Ti surfaces, the extent of S. aureus cell attachment was found to be greater on surfaces with higher average, RMS and maximum roughness and higher surface areas. The cells also attached in greater numbers to surfaces that had shorter autocorrelation lengths and skewness values that approached zero, indicating a preference for less ordered surfaces with peak heights and valley depths evenly distributed around the mean plane. Across the sub-nanometrically smooth range of surfaces tested, it was shown that S. aureus more easily attached to surfaces with larger features that were evenly distributed between peaks and valleys, with higher levels of randomness. This study demonstrated that the traditionally employed amplitudinal roughness parameters are not the only determinants of bacterial adhesion, and that spatial parameters can also be used to predict the extent of attachment.

The surface nanotopography and architecture of medical implant devices are important factors that can control the extent of bacterial attachment. The ability to prevent bacterial attachment substantially reduces the possibility of a patient receiving an implant contracting an implant-borne infection. We now demonstrated that two bacterial strains, Staphylococcus aureus and Pseudomonas aeruginosa, exhibited different attachment affinities towards two types of molecularly smooth titanium surfaces each possessing a different nanoarchitecture. It was found that the attachment of S. aureus cells was not restricted on surfaces that had an average roughness (S a) less than 0.5 nm. In contrast, P. aeruginosa cells were found to be unable to colonise surfaces possessing an average roughness below 1 nm, unless sharp nanoprotrusions of approximately 20 nm in size and spaced 35.0 nm apart were present. It is postulated that the enhanced attachment of P. aeruginosa onto the surfaces possessing these nanoprotrusions was facilitated by the ability of the cell membrane to stretch over the tips of the nanoprotrusions as confirmed through computer simulation, together with a concomitant increase in the level of extracellular polymeric substance (EPS) being produced by the bacterial cells.

There has been a growing interest in understanding the ways in which bacteria interact with nano-structured surfaces. As a result, there is a need for innovative approaches to enable researchers to visualize the biological processes taking place, despite the fact that it is not possible to directly observe these processes. We present a novel approach for the three-dimensional visualization of bacterial interactions with nano-structured surfaces using the software package Autodesk Maya. Our approach comprises a semi-automated stage, where actual surface topographic parameters, obtained using an atomic force microscope, are imported into Maya via a custom Python script, followed by a ‘creative stage', where the bacterial cells and their interactions with the surfaces are visualized using available experimental data. The ‘Dynamics' and ‘nDynamics' capabilities of the Maya software allowed the construction and visualization of plausible interaction scenarios. This capability provides a practical aid to knowledge discovery, assists in the dissemination of research results, and provides an opportunity for an improved public understanding. We validated our approach by graphically depicting the interactions between the two bacteria being used for modeling purposes, Staphylococcus aureus and Pseudomonas aeruginosa, with different titanium substrate surfaces that are routinely used in the production of biomedical devices.

The design of biomaterial surfaces relies heavily on the ability to accurately measure and visualize the three-dimensional surface nanoarchitecture of substrata. Here, we present a technique for producing three-dimensional surface models using displacement maps that are based on the data obtained from two-dimensional analyses. This technique is particularly useful when applied to scanning electron micrographs that have been calibrated using atomic force microscopy (AFM) roughness data. The evaluation of four different surface types, including thin titanium films, silicon wafers, polystyrene cell culture dishes and dragonfly wings confirmed that this technique is particularly effective for the visualization of conductive surfaces such as metallic titanium. The technique is particularly useful for visualizing surfaces that cannot be easily analyzed using AFM. The speed and ease with which electron micrographs can be recorded, combined with a relatively simple process for generating displacement maps, make this technique useful for the assessment of the surface topography of biomaterials.