A high-throughput and machine learning resistance monitoring system to determine the point of resistance for Escherichia coli with tetracycline: Combining UV-visible spectrophotometry with principal component analysis.

UV-visible spectroscopy (UV-Vis) is routinely used in microbiology as a tool to check the optical density (OD) pertaining to the growth stages of microbial cultures at the single wavelength of 600 nm, better known as the OD600 . Typically, modern UV-Vis spectrophotometers can scan in the region of approximately 200-1000 nm in the electromagnetic spectrum, where users do not extend the use of the instrument's full capability in a laboratory. In this study, the full potential of UV-Vis spectrophotometry (multiwavelength collection) was used to examine bacterial growth phases when treated with antibiotics showcasing the ability to understand the point of resistance when an antibiotic is introduced into the media and therefore understand the biochemical changes of the infectious pathogens. A multiplate reader demonstrated a high throughput experiment (96 samples) to understand the growth of Escherichia coli when varied concentrations of the antibiotic tetracycline was added into the well plates. Principal component analysis (PCA) and partial least squares discriminant analysis were then used as the data mining techniques to interpret the UV-Vis spectral data and generate machine learning "proof of principle" for the UV-Vis spectrophotometer plate reader. Results from this study showed that the PCA analysis provides an accurate yet simple visual classification and the recognition of E. coli samples belonging to each treatment. These data show significant advantages when compared to the traditional OD600 method where we can now understand biochemical changes in the system rather than a mere optical density measurement. Due to the unique experimental setup and procedure that involves indirect use of antibiotics, the same test could be used for obtaining practical information on the type, resistance, and dose of antibiotic necessary to establish the optimum diagnosis, treatment, and decontamination strategies for pathogenic and antibiotic resistant species.

The influence of nano-scale surface roughness on bacterial adhesion to ultrafine-grained titanium.

We discuss the effect of extreme grain refinement in the bulk of commercial purity titanium (CP, Grade-2) on bacterial attachment to the mechano-chemically polished surfaces of the material. The ultrafine crystallinity of the bulk was achieved by severe plastic deformation by means of equal channel angular pressing (ECAP). The chemical composition, wettability, surface topography and roughness of titanium surfaces were characterized using X-ray photoelectron spectroscopy (XPS) and water contact angle (WCA) measurements, as well as atomic force microscopy (AFM) with 3D interactive visualization of the titanium surface morphology. It was found that physico-chemical surface characteristics of the as-received and the ECAP-modified CP titanium did not differ in any significant way, while the surface roughness at the nano-scale did. Optical profilometry performed on large scanning areas of approximately 225 mum x 300 mum showed that there was no significant difference between the roughness parameters R(a) and R(q) for surfaces in the two conditions, the overall level of roughness being lower for the ECAP-processed one. By contrast, topographic profile analysis at the nano-scale by AFM did reveal a difference in these parameters. This difference was sensitive to the size of the scanned surface area. A further two surface roughness parameters, skewness (R(skw)) and kurtosis (R(kur)), were also used to describe the morphology of titanium surfaces. It was found that the bacterial strains used in this study as adsorbates, viz. Staphylococcus aureus CIP 65.8 and Pseudomonas aeruginosa ATCC 9025, showed preference for surfaces of ECAP-processed titanium. S. aureus cells were found to have a greater propensity for attachment to surfaces of ECAP-modified titanium, while the attachment of P. aeruginosa, while also showing some preference for the ECAP-processed material, was less sensitive to the ECAP processing.