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 bi...
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Published in | Journal of microbiological methods Vol. 100; pp. 111 - 120 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
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Elsevier B.V
01.05.2014
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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.
•Quantify connected-biofilm bacteria grown on visible irregular surfaces•Introduce modified connected volume filtration algorithm•Novel modified substratum coverage parameter assesses bacteria coverage on surface.•Quantify percent bacteria associated with visible surface (fluorescent/reflective) |
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AbstractList | 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. 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. •Quantify connected-biofilm bacteria grown on visible irregular surfaces•Introduce modified connected volume filtration algorithm•Novel modified substratum coverage parameter assesses bacteria coverage on surface.•Quantify percent bacteria associated with visible surface (fluorescent/reflective) 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. |
Author | Kiedrowski, Megan R. Ketterer, Margaret R. Falsetta, Megan L. Tu, Mai Han Horswill, Alexander R. Apicella, Michael A. Fiegel, Jennifer Reinhardt, Joseph M. Sommerfeld Ross, Stacy |
AuthorAffiliation | b The University of Iowa, Department of Microbiology, Iowa City, IA 52242, United States a The University of Iowa, Department of Pharmaceutical Sciences and Translational Therapeutics, S215 PHAR, 115 S. Grand Ave, Iowa City, IA 52242, United States d The University of Iowa, Department of Chemical and Biochemical Engineering, Iowa City, IA 52242, United States c The University of Iowa, Department of Biomedical Engineering, Iowa City, IA 52242, United States |
AuthorAffiliation_xml | – name: b The University of Iowa, Department of Microbiology, Iowa City, IA 52242, United States – name: c The University of Iowa, Department of Biomedical Engineering, Iowa City, IA 52242, United States – name: d The University of Iowa, Department of Chemical and Biochemical Engineering, Iowa City, IA 52242, United States – name: a The University of Iowa, Department of Pharmaceutical Sciences and Translational Therapeutics, S215 PHAR, 115 S. Grand Ave, Iowa City, IA 52242, United States |
Author_xml | – sequence: 1 givenname: Stacy surname: Sommerfeld Ross fullname: Sommerfeld Ross, Stacy organization: The University of Iowa, Department of Pharmaceutical Sciences and Experimental Therapeutics, S215 PHAR, 115 S. Grand Ave, Iowa City, IA 52242, United States – sequence: 2 givenname: Mai Han surname: Tu fullname: Tu, Mai Han organization: The University of Iowa, Department of Pharmaceutical Sciences and Experimental Therapeutics, S215 PHAR, 115 S. Grand Ave, Iowa City, IA 52242, United States – sequence: 3 givenname: Megan L. surname: Falsetta fullname: Falsetta, Megan L. organization: The University of Iowa, Department of Microbiology, Iowa City, IA 52242, United States – sequence: 4 givenname: Margaret R. surname: Ketterer fullname: Ketterer, Margaret R. organization: The University of Iowa, Department of Microbiology, Iowa City, IA 52242, United States – sequence: 5 givenname: Megan R. surname: Kiedrowski fullname: Kiedrowski, Megan R. organization: The University of Iowa, Department of Microbiology, Iowa City, IA 52242, United States – sequence: 6 givenname: Alexander R. surname: Horswill fullname: Horswill, Alexander R. organization: The University of Iowa, Department of Microbiology, Iowa City, IA 52242, United States – sequence: 7 givenname: Michael A. surname: Apicella fullname: Apicella, Michael A. organization: The University of Iowa, Department of Microbiology, Iowa City, IA 52242, United States – sequence: 8 givenname: Joseph M. surname: Reinhardt fullname: Reinhardt, Joseph M. organization: The University of Iowa, Department of Biomedical Engineering, Iowa City, IA 52242, United States – sequence: 9 givenname: Jennifer surname: Fiegel fullname: Fiegel, Jennifer email: jennifer-fiegel@uiowa.edu organization: The University of Iowa, Department of Pharmaceutical Sciences and Experimental Therapeutics, S215 PHAR, 115 S. Grand Ave, Iowa City, IA 52242, United States |
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SubjectTerms | Biofilm Biofilms - growth & development Cell Line COMSTAT Confocal microscopy Epithelial Cells - microbiology Humans Image Processing, Computer-Assisted - methods Microscopy, Confocal - methods Neisseria gonorrhoeae Neisseria gonorrhoeae - physiology Pseudomonas aeruginosa Pseudomonas aeruginosa - physiology Quantification Staphylococcus aureus Staphylococcus aureus - physiology Surface Surface Properties Tissue |
Title | Quantification of confocal images of biofilms grown on irregular surfaces |
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