Literature DB >> 24632515

Quantification of confocal images of biofilms grown on irregular surfaces.

Stacy Sommerfeld Ross1, Mai Han Tu1, Megan L Falsetta2, Margaret R Ketterer2, Megan R Kiedrowski2, Alexander R Horswill2, Michael A Apicella2, Joseph M Reinhardt3, Jennifer Fiegel4.   

Abstract

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.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biofilm; COMSTAT; Confocal microscopy; Quantification; Surface; Tissue

Mesh:

Year:  2014        PMID: 24632515      PMCID: PMC4041150          DOI: 10.1016/j.mimet.2014.02.020

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


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