Quantification of confocal images of biofilms grown on irregular surfaces.

Bacterial biofilms grow on many types of surfaces, including flat surfaces such as glass and metal and irregular surfaces such as rocks, biological tissues and polymers. While laser scanning confocal microscopy can provide high-resolution images of biofilms grown on any surface, quantification of biofilm-associated bacteria is currently limited to bacteria grown on flat surfaces. This can limit researchers studying irregular surfaces to qualitative analysis or quantification of only the total bacteria in an image. In this work, we introduce a new algorithm called modified connected volume filtration (MCVF) to quantify bacteria grown on top of an irregular surface that is fluorescently labeled or reflective. Using the MCVF algorithm, two new quantification parameters are introduced. The modified substratum coverage parameter enables quantification of the connected-biofilm bacteria on top of the surface and on the imaging substratum. The utility of MCVF and the modified substratum coverage parameter were shown with Pseudomonas aeruginosa and Staphylococcus aureus biofilms grown on human airway epithelial cells. A second parameter, the percent association, provides quantified data on the colocalization of the bacteria with a labeled component, including bacteria within a labeled tissue. The utility of quantifying the bacteria associated with the cell cytoplasm was demonstrated with Neisseria gonorrhoeae biofilms grown on cervical epithelial cells. This algorithm provides more flexibility and quantitative ability to researchers studying biofilms grown on a variety of irregular substrata.

Nutrient dispersion enhances conventional antibiotic activity against Pseudomonas aeruginosa biofilms.

Bacterial biofilms cause significant infections in the medical field. Antibiotics commonly used to treat these infections often do not achieve complete bacterial eradication. New approaches to eliminate biofilms have focused on dispersion compounds to entice the bacteria to actively escape or disperse from the biofilm, where the bacteria may become more susceptible to antibiotics. The aim of this study was to demonstrate that combining antibiotics with nutrient dispersion compounds can synergistically decrease the viability of Pseudomonas aeruginosa biofilms. The effects of various co-treatments were studied on mature biofilms through qualitative and quantitative confocal microscopy. Combined treatment of P. aeruginosa biofilms with antibiotic and dispersion compounds resulted in a significant reduction in the live bacterial population compared with the untreated control in all cases, with four combinations displaying synergistic action (citrate with amikacin disulphate, colistin methanesulphonate or erythromycin, and succinic acid with colistin methanesulphonate).

Enhanced analysis of bacteria susceptibility in connected biofilms.

A common method for visualizing bacterial biofilms is through confocal laser scanning microscopy images. Current software packages separate connected-biofilm bacteria from unconnected bacteria, such as planktonic or dispersed bacteria, but do not save both image sequences, making interpretation of the two bacterial populations difficult. Thus we report the development of an algorithm to save separate image sequences and enable qualitative and quantitative evaluation of each bacterial population. To improve bacterial viability assessment using a membrane integrity dye, a colocalization algorithm was also developed. This assigns colocalized pixels to the dead bacteria population, rather than to both the live and dead bacteria groups. Visually, this makes it clearer to distinguish a green live bacteria pixel from a yellow colocalized dead bacteria pixel. This algorithm also aids in the quantification of viability for connected-biofilm bacteria and unconnected bacteria to investigate susceptibility of each population to antimicrobials. The utility of these algorithms was demonstrated with Pseudomonas aeruginosa biofilms treated with ciprofloxacin hydrochloride. Results from this study indicate that quantification with colocalization adjustment can prevent underestimation of dead bacteria. These improvements in image processing will enable researchers to visually differentiate connected-biofilm and unconnected bacteria in a single image and to quantify these populations independently for viability without double counting the colocalized image pixels.