An In Vitro Model to Study the Effect of 5-Aminolevulinic Acid-mediated Photodynamic Therapy on Staphylococcus aureus Biofilm.

Staphylococcus aureus (S. aureus) is a common human pathogen, which causes pyogenic and systemic infections. S. aureus infections are difficult to eradicate not only due to the emergence of antibiotic-resistant strains but also its ability to form biofilms. Recently, photodynamic therapy (PDT) has been indicated as one of the potential treatments for controlling biofilm infections. However, further studies are required to improve our knowledge of its effect on bacterial biofilms, as well as the underlying mechanisms. This manuscript describes an in vitro model of PDT with 5-aminolevulinic acid (5-ALA), a precursor of the actual photosensitizer, protoporphyrin IX (PpIX). Briefly, mature S. aureus biofilms were incubated with ALA and then exposed to light. Subsequently, the antibacterial effect of ALA-PDT on S. aureus biofilm was quantified by calculating the colony forming units (CFUs) and visualized by viability fluorescent staining via confocal laser scanning microscopy (CLSM). Representative results demonstrated a strong antibacterial effect of ALA-PDT on S. aureus biofilms. This protocol is simple and can be used to develop an in vitro model to study the treatment of S. aureus biofilms with ALA-PDT. In the future, it could also be referenced in PDT studies utilizing other photosensitizers for different bacterial strains with minimal adjustments.

A combination dimensionality reduction approach to codon position patterns of eubacteria based on their complete genomes.

Graphical techniques have become powerful tools for the visualization and analysis of complicated biological systems. However, we cannot give such a graphical representation in a 2D/3D space when the dimensions of the represented data are more than three dimensions. The proposed method, a combination dimensionality reduction approach (CDR), consists of two parts: (i) principal component analysis (PCA) with a newly defined parameter ρ and (ii) locally linear embedding (LLE) with a proposed graphical selection for its optional parameter k. The CDR approach with ρ and k not only avoids loss of principal information, but also sufficiently well preserves the global high-dimensional structures in low-dimensional space such as 2D or 3D. The applications of the CDR on characteristic analysis at different codon positions in genome show that the method is a useful tool by which biologists could find useful biological knowledge.