Name: quantifying the effects of antimicrobials on in vitro biofilm architecture using comstat software
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Description: Watch this Scientific Journal Video about Quantifying the Effects of Antimicrobials on In vitro Biofilm Architecture using COMSTAT Software at JoVE.com

The authors would like to acknowledge Cystic Fibrosis Foundation for providing funding for this research.

1. Bacterial isolate collection
<ol>
	<li>Obtain P. aeruginosa isolates from a cohort of pediatric patients with CF undergoing eradication treatment with inhaled tobramycin at SickKids (Toronto). Freeze isolates at -80 &#176;C in glycerol citrate and sub-culture at least three times prior to use.</li>
</ol>
2. In vitro biofilm formation
NOTE: Use a chambered coverglass method1 for in vitro biofilm formation with modific...

<ol>
	<li>Flemming, H. C., Wingender, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+biofilm+matrix.">The biofilm matrix.</a> Nature Reviews Microbiology. 8, 623-633 (2010).</li><li>Flemming, H. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofilms:+an+emergent+form+of+bacterial+life.">Biofilms: an emergent form of bacterial life.</a> Nature Reviews Microbiology. 14, 563-575 (2016).</li><li>Rybtke, M., Hultqvist, L. D., Givskov, M., Tolker-Nielsen, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pseudomonas+aeruginosa+biofilm+infections:+community+structure,+antimicrobial+tolerance+and+immune+response.">Pseudomonas aeruginosa biofilm infections: community structure, antimicrobial tolerance and immune response.</a> Journal of Molecular Biology. 427, 3628-3645 (2015).</li><li>Wendel, A. F., Ressina, S., Kolbe-Busch, S., Pfeffer, K., MacKenzie, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Species+diversity+of+environmental+GIM-1-producing+bacteria+collected+during+a+long-term+outbreak.">Species diversity of environmental GIM-1-producing bacteria collected during a long-term outbreak.</a> Applied and Environmental Microbiology. 82, 3605-3610 (2016).</li><li>Costerton, J. W., Stewart, P. S., Greenberg, E. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bacterial+biofilms:+a+common+cause+of+persistent+infections.">Bacterial biofilms: a common cause of persistent infections.</a> Science. 284, 1318-1322 (1999).</li><li>Powell, L. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeted+disruption+of+the+extracellular+polymeric+network+of+Pseudomonas+aeruginosa+biofilms+by+alginate+oligosaccharides.">Targeted disruption of the extracellular polymeric network of Pseudomonas aeruginosa biofilms by alginate oligosaccharides.</a> NPJ Biofilms and Microbiomes. 4, 1-10 (2018).</li><li>Ciofu, O., Tolker-Nielsen, T., Jensen, P. &. #. 2. 1. 6. ;., Wang, H., H&#248;iby, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antimicrobial+resistance,+respiratory+tract+infections+and+role+of+biofilms+in+lung+infections+in+cystic+fibrosis+patients.">Antimicrobial resistance, respiratory tract infections and role of biofilms in lung infections in cystic fibrosis patients.</a> Advanced Drug Delivery Reviews. 85, 7-23 (2015).</li><li>Landry, R. M., An, D., Hupp, J. T., Singh, P. K., Parsek, M. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mucin-Pseudomonas+aeruginosa+interactions+promote+biofilm+formation+and+antibiotic+resistance.">Mucin-Pseudomonas aeruginosa interactions promote biofilm formation and antibiotic resistance.</a> Molecular Microbiology. 59, 142-151 (2006).</li><li>Beaudoin, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Staphylococcus+aureus+interaction+with+Pseudomonas+aeruginosa+biofilm+enhances+tobramycin+resistance.">Staphylococcus aureus interaction with Pseudomonas aeruginosa biofilm enhances tobramycin resistance.</a> NPJ Biofilms and Microbiomes. 3, 1-9 (2017).</li><li>Rojo-Molinero, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sequential+treatment+of+biofilms+with+aztreonam+and+tobramycin+is+a+novel+strategy+for+combating+Pseudomonas+aeruginosa+chronic+respiratory+infections.">Sequential treatment of biofilms with aztreonam and tobramycin is a novel strategy for combating Pseudomonas aeruginosa chronic respiratory infections.</a> Antimicrobial Agents and Chemotherapy. 60, 2912-2922 (2016).</li><li>Hentzer, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Alginate+overproduction+affects+Pseudomonas+aeruginosa+biofilm+structure+and+function.">Alginate overproduction affects Pseudomonas aeruginosa biofilm structure and function.</a> Journal of Bacteriology. 183, 5395-5401 (2001).</li><li>Tolker-Nielsen, T., Sternberg, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growing+and+analyzing+biofilms+in+flow+chambers.">Growing and analyzing biofilms in flow chambers.</a> Current Protocols in Microbiology. 21, 1-17 (2011).</li><li>Luo, T. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Sensitive+thresholding+method+for+confocal+laser+scanning+microscope+image+stacks+of+microbial+biofilms.">A Sensitive thresholding method for confocal laser scanning microscope image stacks of microbial biofilms.</a> Scientific Reports. 8, 1-14 (2018).</li><li>Beaudoin, T., Kennedy, S., Yau, Y., Waters, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visualizing+the+effects+of+sputum+on+biofilm+development+using+a+chambered+coverglass+model.">Visualizing the effects of sputum on biofilm development using a chambered coverglass model.</a> Journal of Visualized Experiments. (118), e54819 (2016).</li><li>DiGiandomenico, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+broadly+protective+human+antibodies+to+Pseudomonas+aeruginosa+exopolysaccharide+Psl+by+phenotypic+screening.">Identification of broadly protective human antibodies to Pseudomonas aeruginosa exopolysaccharide Psl by phenotypic screening.</a> Journal of Experimental Medicine. 209, 1273-1287 (2012).</li><li>Heydorn, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+biofilm+structures+by+the+novel+computer+program+COMSTAT.">Quantification of biofilm structures by the novel computer program COMSTAT.</a> Microbiology. 146, 2395-2407 (2000).</li><li>Vorregaard, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comstat2+-+a+modern+3D+image+analysis+environment+for+biofilms,+in+Informatics+and+Mathematical+Modelling.">Comstat2 - a modern 3D image analysis environment for biofilms, in Informatics and Mathematical Modelling.</a> Technical University of Denmark. , (2008).</li><li>Hashemi, M. A., Khaddour, G., Fran&#231;ois, B., Massart, T. J., Salager, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+tomographic+imagery+segmentation+methodology+for+three-phase+geomaterials+based+on+simultaneous+region+growing.">A tomographic imagery segmentation methodology for three-phase geomaterials based on simultaneous region growing.</a> Acta Geotechnica. 9, 831-846 (2014).</li><li>Rogowska, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Overview+and+fundamentals+of+medical+image+segmentation.">Overview and fundamentals of medical image segmentation.</a> Handbook of Medical Image Processing and Analysis. , 73-90 (2009).</li><li>Webb, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessing+technician+effects+when+extracting+quantities+from+microscope+images.">Assessing technician effects when extracting quantities from microscope images.</a> Journal of Microbiological Methods. 53, 97-106 (2003).</li><li>Azeredo, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Critical+review+on+biofilm+methods.">Critical review on biofilm methods.</a> Critical Reviews in Microbiology. 43, 313-351 (2017).</li><li>Xavier, J. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Objective+threshold+selection+procedure+(OTS)+for+segmentation+of+scanning+laser+confocal+microscope+images.">Objective threshold selection procedure (OTS) for segmentation of scanning laser confocal microscope images.</a> Journal of Microbiological Methods. 47, 169-180 (2001).</li><li>Arena, E. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitating+the+cell:+turning+images+into+numbers+with+ImageJ.">Quantitating the cell: turning images into numbers with ImageJ.</a> Wiley Interdisciplinary Reviews: Developmental Biology. 6, 260 (2017).</li><li>Daims, H., Wagner, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+uncultured+microorganisms+by+fluorescence+microscopy+and+digital+image+analysis.">Quantification of uncultured microorganisms by fluorescence microscopy and digital image analysis.</a> Applied Microbiology and Biotechnology. 75, 237-248 (2007).</li><li>Yerly, J., Hu, Y., Jones, S. M., Martinuzzi, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+two-step+procedure+for+automatic+and+accurate+segmentation+of+volumetric+CLSM+biofilm+images.">A two-step procedure for automatic and accurate segmentation of volumetric CLSM biofilm images.</a> Journal of Microbiological Methods. 70, 424-433 (2007).</li><li>Lee, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Heterogeneity+of+biofilms+formed+by+nonmucoid+Pseudomonas+aeruginosa+isolates+from+patients+with+cystic+fibrosis.">Heterogeneity of biofilms formed by nonmucoid Pseudomonas aeruginosa isolates from patients with cystic fibrosis.</a> Journal of Clinical Microbiology. 43, 5247-5255 (2005).</li><li>Stapper, A. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Alginate+production+affects+Pseudomonas+aeruginosa+biofilm+development+and+architecture,+but+is+not+essential+for+biofilm+formation.">Alginate production affects Pseudomonas aeruginosa biofilm development and architecture, but is not essential for biofilm formation.</a> Journal of Medical Microbiology. 53, 679-690 (2004).</li><li>Reichhardt, C., Parsek, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Confocal+laser+scanning+microscopy+for+analysis+of+Pseudomonas+aeruginosa+biofilm+architecture+and+matrix+localization.">Confocal laser scanning microscopy for analysis of Pseudomonas aeruginosa biofilm architecture and matrix localization.</a> Frontiers in Microbiology. 10, 677 (2019).</li><li>Yang, X., Beyenal, H., Harkin, G., Lewandowski, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+biofilm+structure+using+image+analysis.">Quantifying biofilm structure using image analysis.</a> Journal of Microbiological Methods. 39, 109-119 (2000).</li><li>Yang, X., Beyenal, H., Harkin, G., Lewandowski, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+biofilm+image+thresholding+methods.">Evaluation of biofilm image thresholding methods.</a> Water Research. 35, 1149-1158 (2001).</li><li>Ross, S. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+confocal+images+of+biofilms+grown+on+irregular+surfaces.">Quantification of confocal images of biofilms grown on irregular surfaces.</a> Journal of Microbiological Methods. 100, 111-120 (2014).</li><li>Ma, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assembly+and+development+of+the+Pseudomonas+aeruginosa+biofilm+matrix.">Assembly and development of the Pseudomonas aeruginosa biofilm matrix.</a> PLoS Pathogens. 5, (2009).</li><li>Mah, T. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+genetic+basis+for+Pseudomonas+aeruginosa+biofilm+antibiotic+resistance.">A genetic basis for Pseudomonas aeruginosa biofilm antibiotic resistance.</a> Nature. 426, 306-310 (2003).</li><li>Srinandan, C. S., Jadav, V., Cecilia, D., Nerurkar, A. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nutrients+determine+the+spatial+architecture+of+Paracoccus+sp.+biofilm.">Nutrients determine the spatial architecture of Paracoccus sp. biofilm.</a> Biofouling. 26, 449-459 (2010).</li><li>Ramos, I., Dietrich, L. E., Price-Whelan, A., Newman, D. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenazines+affect+biofilm+formation+by+Pseudomonas+aeruginosa+in+similar+ways+at+various+scales.">Phenazines affect biofilm formation by Pseudomonas aeruginosa in similar ways at various scales.</a> Research in Microbiology. 161, 187-191 (2010).</li><li>Ma, L., Jackson, K. D., Landry, R. M., Parsek, M. R., Wozniak, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+Pseudomonas+aeruginosa+conditional+psl+variants+reveals+roles+for+the+psl+polysaccharide+in+adhesion+and+maintaining+biofilm+structure+postattachment.">Analysis of Pseudomonas aeruginosa conditional psl variants reveals roles for the psl polysaccharide in adhesion and maintaining biofilm structure postattachment.</a> Journal of Bacteriology. 188, 8213-8221 (2006).</li></ol>

There is no prescribed method for quantitatively comparing three-dimensional images of in vitro biofilm structures, and procedures described in this context are often difficult to standardize due to inter-operator variability20. Thus, this protocol offers a simple and reproducible framework for COMSTAT applications seeking to quantify changes in in vitro biofilm architecture under varying antimicrobial conditions. The strengths of this technique are modeled using a CF P. aeru...

Biofilms are aggregates of microorganisms oriented in a matrix of self-produced extracellular polymeric substances (EPS). The EPS matrix is very complex, consisting primarily of bacterial cells, water, proteins, polysaccharides, lipids, and nucleic acids1, all of which make biofilms distinctly different from free-living planktonic cells. Biofilm EPS are adherent to each other and various surfaces. The EPS matrix has properties that mediate cell-to-cell exchange of metabolites, genetic material, and compounds used for intercellular signaling and defense2. These properties collectively provide biofilms structural integrity and protection against external stressors, contributing to immune evasion and antimicrobial resistance3.
Pseudomonas aeruginosa is a well-recognized nosocomial pathogen, known to adopt an evasive biofilm growth strategy in response to antimicrobials. A prime example of this occurs in patients with the recessive genetic disorder, cystic fibrosis (CF). Biofilms play a pivotal role in the development of antimicrobial-resistant P. aeruginosa4 and permit the establishment of chronic pulmonary infection in patients with CF, causing accelerated decline in lung function and premature mortality5. Hence, in vitro biofilm studies are performed to test the efficacy of antibiotics and new anti-infective agents against P. aeruginosa isolates obtained from patients with CF6,7. Following biofilm formation, antimicrobials are applied externally to the structure, and confocal laser scanning microscopy (CLSM) is used to generate high-resolution, three-dimensional reconstructions of biofilm segments. It is common practice to then use the computer software, COMSTAT, as a plugin to ImageJ, to quantify changes in biofilm architecture8,9,10,11.
Although COMSTAT is&#160;useful&#160;for quantifying biofilm structure, the reproducibility and standardization of image analysis&#160;is less commonly addressed. For example, the image-processing procedure, performed prior to running COMSTAT, is objective, but contains an element of subjectivity when setting image thresholds12,13. In a similar manner, the COMSTAT program allows the operator to choose from basic to advanced conditions and parameters for image segmentation as well as ten quantitative analysis functions (e.g., thickness distribution, surface area, biomass, dimensionless roughness coefficient). The multitude of user options, compounded with varying operator expertise levels, may result in misguided reporting of biofilm behavior.
Thus, the goal of this protocol is to present a relatively simple method for the quantitative comparison of in vitro biofilm structures using COMSTAT. Herein, three-dimensional images of biofilm segments from a CF P. aeruginosa isolate are captured via CLSM using the chambered coverglass model14&#8212;an established technique used to perform reproducible in vitro biofilm experiments. Utilizing COMSTAT as a plugin to ImageJ, this method allows for researchers to quantitatively identify changes in biofilm architecture in the presence of antimicrobials under varying conditions. Overall, this method aims to eliminate subjective variations associated with the manual operation of COMSTAT, thereby facilitating the standardization of protocols across centers.

<table>
	<tbody>
		<tr>
			<td>Anti-Psl mAb, Psl0096</td>
			<td>Medimmune</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Blood Agar (TSA with 5 % Sheep Blood) Medium</td>
			<td>Fisher Scientific</td>
			<td>R01200</td>
			<td></td>
		</tr>
		<tr>
			<td>Eight-well Chambered Coverglass w/ non-removable wells</td>
			<td>Thermo Fisher Scientific</td>
			<td>155411</td>
			<td></td>
		</tr>
		<tr>
			<td>Invitrogen SYTO 9 Green Fluorescent Nucleic Acid Stain</td>
			<td>Thermo Fisher Scientific</td>
			<td>S34854</td>
			<td></td>
		</tr>
		<tr>
			<td>LB BROTH (LENNOX), Liquid Autoclave Sterilized</td>
			<td>BioShop Canada</td>
			<td>LBL666</td>
			<td></td>
		</tr>
		<tr>
			<td>Tobramycin, 900 &#181;g/mg</td>
			<td>Alfa Aesar by Thermo Fisher Scientific</td>
			<td>J66040</td>
			<td>It is recommended to perform a minimal inhibitory concentration (MIC) test for every batch made to ensure quality control of antimicrobial potency</td>
		</tr>
		<tr>
			<td>Quorum Volocity 6.3</td>
			<td>Quorum Technologies</td>
			<td></td>
			<td>Image analysis software</td>
		</tr>
	</tbody>
</table>

quantifying the effects of antimicrobials on in vitro biofilm architecture using comstat software

Biofilms are aggregates of microorganisms that rely on a self-produced matrix of extracellular polymeric substance for protection and structural integrity. The nosocomial pathogen, Pseudomonas aeruginosa, is known to adopt a biofilm mode of growth, causing chronic pulmonary infection in patients with cystic fibrosis (CF). The computer program, COMSTAT, is a useful tool for quantifying antimicrobial-induced changes in P. aeruginosa biofilm architecture by extracting data from three-dimensional confocal images. However, standardized operation of the software is less commonly addressed, which is important for optimal reporting of biofilm behavior and cross-center comparison. Thus, the aim of this protocol is to provide a simple and reproducible framework for quantifying in vitro biofilm structures under varying antimicrobial conditions via COMSTAT. The technique is modeled using a CF P. aeruginosa isolate, grown in the form of biofilm replicates, and exposed to tobramycin and the anti-Psl monoclonal antibody, Psl0096. The step-by-step approach aims to reduce user ambiguity and minimize the chance of overlooking crucial image-processing steps. Specifically, the protocol emphasizes the elimination of subjective variations associated with the manual operation of COMSTAT, including image segmentation and the selection of appropriate quantitative analysis functions. Although this method requires users to spend additional time processing confocal images prior to running COMSTAT, it helps minimize misrepresented biofilm heterogenicity in automated outputs.

A P. aeruginosa isolate cultured from an infected&#160;patient with CF is used to demonstrate the strengths of this approach in accurately quantifying antimicrobial-induced changes in in vitro biofilm architecture. The overall workflow of this model is represented in Figure 1. The image-processing and COMSTAT analysis procedure&#160;in ImageJ is shown in&#160;Figure 2. A simple histogram thresholding approach for image segmentation in ImageJ, a...

Watch this Scientific Journal Video about Quantifying the Effects of Antimicrobials on In vitro Biofilm Architecture using COMSTAT Software at JoVE.com

Quantifying the Effects of Antimicrobials on In vitro Biofilm Architecture using COMSTAT Software

Antimicrobial-induced changes to Pseudomonas aeruginosa biofilm architecture differ among clinical isolates cultured from patients with cystic fibrosis and chronic pulmonary infection. Following confocal microscopy, COMSTAT software can be utilized to quantify variations in biofilm architecture (e.g., surface area, thickness, biomass) for individual isolates to assess the efficacy of anti-infective agents.

Quantifying the Effects of Antimicrobials on In vitro Biofilm Architecture using COMSTAT Software

Biofilms are aggregates of microorganisms that rely on a self-produced matrix of extracellular polymeric substance for protection and structural ...

The significance of this protocol is that it offers a simple and reproducible framework for quantifying in vitro biofilm structures under varying antimicrobial conditions. The main advantage of this technique is that it helps eliminate subjective variations associated with the manual operation of COMSTAT, which ultimately facilitates the standardization and transparency of experiments across research centers. To image the Pseudomonas aeruginosa cultures, place the plate onto the stage of a confocal microscope, equipped with the appropriate laser excitation wavelengths and filter sets.And use a 20 to 25x water immersion lens to capture at least six layered z-stack images from the substratum to the top of each biofilm segment in 0.3 micrometer increments. Then save the images as OME-TIFFs for COMSTAT analysis. When all the images have been acquired, open the COMSTAT2 package in ImageJ and create a source folder on the desktop.Add a single OME-TIFF to the folder and open OME-TIFF from the source folder. Delete any empty layers containing no biomass. Select File, Import, and Image Sequence to import the file into ImageJ.Locate and highlight the source folder without opening it and click Select. A sequence options window will appear, click OK.Select Image, Transform, and Flip Z to flip the orientation of the biofilm so that the substratum is at the top of the stack. To define the image properties, select Image and Properties, a source window will appear.Specify the unit of length as micron, define the voxel depth as 0.3, and click OK.Select Image, Adjust, and Threshold. To adjust the image threshold in the threshold window, position the lower slider to the far right to manually set the maximum threshold value and use the upper slider to set the minimum threshold. Then use the slider in the image window to scroll through each layer to ensure that the background noise is sufficiently removed throughout the stack, and select Set to fix the lower threshold value.In the set threshold levels window, select OK, and set and fix the maximum threshold value similarly. Select Apply, click OK in the convert stack to binary window that appears, and exit the threshold window. Select Plugins, Bio-Formats, and Bio-Formats Exporter to save the file with a new file name in the source folder.A Bio-Formats Exporter multiple files window will appear, select OK.A Bio-Formats Exporter options window will appear, select OK again. To run COMSTAT, select plugins and COMSTAT2, an about window will appear, select OK.In the Observed Directories window, select Add, locate and highlight the source folder, highlight and click Choose. An Images in Directories window will appear that lists the OME-TIFFs to be analyzed.On the COMSTAT2.1 window, deselect Automatic Thresholding Otsu's Method and Connected Volume Filtering to ensure that the software uses preset threshold values for individual OME-TIFFs. In the COMSTAT2.1 window, select Biomass, Thickness Distribution and Surface Area, and click Go to run the program. The output data will be shown in the log window.The measurements will be automatically saved as TXT files in the source folder. In this representative analysis, a Pseudomonas aeruginosa isolate, cultured from an infected cystic fibrosis patient, was used to demonstrate the strengths of this approach, inaccurately quantifying antimicrobial induced changes in in vitro biofilm architecture. Live cell imaging can also visualize changes in Pseudomonas aeruginosa biofilm structure before and after biofilm specific monoclonal and tobramycin treatment.COMSTAT data analysis revealed significant differences between treated biofilm structures compared to control cultures. In tobramycin-treated cultures, a clear reduction in the average thickness and biomass was observed. However, in the presence of antibodies, the P.aeruginosa biofilm was resistant to these tobramycin-induced structural changes.When examining the surface to bio volume ratio, a significant reduction was observed in the presence of antibodies in both tobramycin-exposed and unexposed biofilms, indicating the formation of aggregates in antibody treated cultures. This procedure can be performed to quantitatively assess or compare the effects of different antimicrobials used to disrupt biofilm matrices. Using this technique as a general framework, researchers can explore different ways to refine the protocol to include new mathematical models and algorithmic plugins in ImageJ to better depict biofilm heterogenecy.

quantifying-effects-antimicrobials-on-vitro-biofilm-architecture

Research

JoVE Journal

Immunology and Infection

In vitro Biofilm Formation in an 8-well Chamber Slide

The chronic nature of many diseases is attributed to the formation of bacterial biofilms which are recalcitrant to traditional antibiotic therapy. Biofilms are community-associated bacteria attached to a surface and encased in a matrix. The role of the extracellular matrix is multifaceted, including facilitating nutrient acquisition, and offers significant protection against environmental stresses (e.g. host immune responses). In an effort to acquire a better understanding as to how the bacteria within a biofilm respond to environmental stresses we have used a protocol wherein we visualize bacterial biofilms which have formed in an 8-well chamber slide. The biofilms were stained with the BacLight Live/Dead stain and examined using a confocal microscope to characterize the relative biofilm size, and structure under varying incubation conditions. Z-stack images were collected via confocal microscopy and analyzed by COMSTAT. This protocol can be used to help elucidate the mechanism and kinetics by which biofilms form, as well as identify components that are important to biofilm structure and stability.

In vitro Biofilm Formation in an 8-well Chamber Slide

This article describes the procedure for the formation and visualization of a bacterial biofilm grown within an 8-well chamber slide

The chronic nature of many diseases is attributed to the formation of bacterial biofilms which are recalcitrant to traditional antibiotic therapy. ...

Investigating the Effects of Probiotics on Pneumococcal Colonization Using an In Vitro Adherence Assay

Adherence of Streptococcus pneumoniae (the pneumococcus) to the epithelial lining of the nasopharynx can result in colonization and is considered a prerequisite for pneumococcal infections such as pneumonia and otitis media. In vitro adherence assays can be used to study the attachment of pneumococci to epithelial cell monolayers and to investigate potential interventions, such as the use of probiotics, to inhibit pneumococcal&#160;colonization.&#160;The protocol described here is used to investigate the effects of the probiotic Streptococcus salivarius on the adherence of pneumococci to the human epithelial cell line CCL-23 (sometimes referred to as HEp-2 cells). The assay involves three main steps: 1) preparation of epithelial and bacterial cells, 2) addition of bacteria to epithelial cell monolayers, and 3) detection of adherent pneumococci by viable counts (serial dilution and plating) or quantitative real-time PCR (qPCR). This technique is relatively straightforward and does not require specialized equipment other than a tissue culture setup. The assay can be used to test other probiotic species and/or potential inhibitors of pneumococcal colonization and can be easily modified to address other scientific questions regarding pneumococcal adherence and invasion.

Investigating the Effects of Probiotics on Pneumococcal Colonization Using an In Vitro Adherence Assay

In vitro adherence assays can be used to study the attachment of Streptococcus pneumoniae to epithelial cell monolayers and to investigate potential interventions such as the use of probiotics for inhibiting pneumococcal colonization.

Adherence of Streptococcus pneumoniae (the pneumococcus) to the epithelial lining of the nasopharynx can result in colonization and is considered a ...

Analyzing the Effects of Stromal Cells on the Recruitment of Leukocytes from Flow

Stromal cells regulate the recruitment of circulating leukocytes during inflammation through cross-talk with neighboring endothelial cells. Here we describe two in vitro &#8220;vascular&#8221; models for studying the recruitment of circulating neutrophils from flow by inflamed endothelial cells. A major advantage of these models is the ability to analyze each step in the leukocyte adhesion cascade in order, as would occur in vivo. We also describe how both models can be adapted to study the role of stromal cells, in this case mesenchymal stem cells (MSC), in regulating leukocyte recruitment.
Primary endothelial cells were cultured alone or together with human MSC in direct contact on Ibidi microslides or on opposite sides of a Transwell filter for 24 hr. Cultures were stimulated with tumor necrosis factor alpha (TNF&#945;) for 4 hr and incorporated into a flow-based adhesion assay. A bolus of neutrophils was perfused over the endothelium for 4 min. The capture of flowing neutrophils and their interactions with the endothelium was visualized by phase-contrast microscopy.
In both models, cytokine-stimulation increased endothelial recruitment of flowing neutrophils in a dose-dependent manner. Analysis of the behavior of recruited neutrophils showed a dose-dependent decrease in rolling and a dose-dependent increase in transmigration through the endothelium. In co-culture, MSC suppressed neutrophil adhesion to TNF&#945;-stimulated endothelium.
Our flow based-adhesion models mimic the initial phases of leukocyte recruitment from the circulation. In addition to leukocytes, they can be used to examine the recruitment of other cell types, such as therapeutically administered MSC or circulating tumor cells. Our multi-layered co-culture models have shown that MSC communicate with endothelium to modify their response to pro-inflammatory cytokines, altering the recruitment of neutrophils. Further research using such models is required to fully understand how stromal cells from different tissues and conditions (inflammatory disorders or cancer) influence the recruitment of leukocytes during inflammation.

The ability of inflamed endothelium to recruit leukocytes from flow is regulated by mesenchymal stromal cells. We describe two in vitro models incorporating primary human cells that can be used to assess neutrophil recruitment from flow and examine the role that mesenchymal stromal cells play in regulating this process.

Stromal cells regulate the recruitment of circulating leukocytes during inflammation through cross-talk with neighboring endothelial cells. Here we ...

Qualitative and Quantitative Assays for Detection and Characterization of Protein Antimicrobials

Initial evaluations of large microbial libraries for potential producers of novel antimicrobial proteins require both qualitative and quantitative methods to screen for target enzymes prior to investing greater research effort and resources. The goal of this protocol is to demonstrate two complementary assays for conducting these initial evaluations. The microslide diffusion assay provides an initial or simple detection screen to enable the qualitative and rapid assessment of proteolytic activity against an array of both viable and heat-killed bacterial target substrates. As a counterpart, the increased sensitivity and reproducibility of the dye-release assay provides a quantitative platform for evaluating and comparing environmental influences affecting the hydrolytic activity of protein antimicrobials. The ability to label specific heat-killed cell culture substrates with Remazol brilliant blue R dye expands this capability to tailor the dye-release assay to characterize enzymatic activity of interest.

Here, we present protocols to rapidly screen and characterize enzymes for antimicrobial activity. The microslide diffusion assay and the dye-release assay utilize target bacterial substrates for qualitative and quantitative enzymatic activity evaluation.

Initial evaluations of large microbial libraries for potential producers of novel antimicrobial proteins require both qualitative and quantitative methods ...

An In Vitro Model of the Blood-brain Barrier Using Impedance Spectroscopy: A Focus on T Cell-endothelial Cell Interaction

Breakdown of the blood-brain barrier (BBB) is a critical step in the development of autoimmune diseases such as multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE). This process is characterized by the transmigration of activated T cells across brain endothelial cells (ECs), the main constituents of the BBB. However, the consequences on brain EC function upon interaction with such T cells are largely unknown. Here we describe an assay that allows for the evaluation of primary mouse brain microvascular EC (MBMEC) function and barrier integrity during the interaction with T cells over time. The assay makes use of impedance cell spectroscopy, a powerful tool for studying EC monolayer integrity and permeability, by measuring changes in transendothelial electrical resistance (TEER) and cell layer capacitance (Ccl). In direct contact with ECs, stimulated but not na&#239;ve T cells are capable of inducing EC monolayer dysfunction, as visualized by a decrease in TEER and an increase in Ccl. The assay records changes in EC monolayer integrity in a continuous and automated fashion. It is sensitive enough to distinguish between different strengths of stimuli and levels of T cell activation and it enables the investigation of the consequences of a targeted modulation of T cell-EC interaction using a wide range of substances such as antibodies, pharmacological reagents and cytokines. The technique can also be used as a quality control for EC integrity in in vitro T-cell transmigration assays. These applications make it a versatile tool for studying BBB properties under physiological and pathophysiological conditions.

An In Vitro Model of the Blood-brain Barrier Using Impedance Spectroscopy: A Focus on T Cell-endothelial Cell Interaction

Here, we describe an in vitro murine model of the blood-brain barrier that makes use of impedance cell spectroscopy, with a focus on the consequences on endothelial cell integrity and permeability upon interaction with activated T cells.

Breakdown of the blood-brain barrier (BBB) is a critical step in the development of autoimmune diseases such as multiple sclerosis (MS) and its animal ...

Flow Cytometric Analysis of Particle-bound Bet v 1 Allergen in PM10

Flow cytometry is a method widely used to quantify suspended solids such as cells or bacteria in a size range from 0.5 to several tens of micrometers in diameter. In addition to a characterization of forward and sideward scatter properties, it enables the use of fluorescent labeled markers like antibodies to detect respective structures. Using indirect antibody staining, flow cytometry is employed here to quantify birch pollen allergen (precisely Bet v 1)-loaded particles of 0.5 to 10 &#181;m in diameter in inhalable particulate matter (PM10, particle size &#8804;10 &#181;m in diameter). PM10 particles may act as carriers of adsorbed allergens possibly transporting them to the lower respiratory tract, where they could trigger allergic reactions.
So far the allergen content of PM10 has been studied by means of enzyme linked immunosorbent assays (ELISAs) and scanning electron microscopy. ELISA measures the dissolved and not the particle-bound allergen. Compared to scanning electron microscopy, which can visualize allergen-loaded particles, flow cytometry may additionally quantify them. As allergen content of ambient air can deviate from birch pollen count, allergic symptoms might perhaps correlate better with allergen exposure than with pollen count. In conjunction with clinical data, the presented method offers the opportunity to test in future experiments whether allergic reactions to birch pollen antigens are associated with the Bet v 1 allergen content of PM10 particles &#62;0.5 &#181;m.

Here, we present a protocol to quantify allergen-loaded particles by flow cytometry. Ambient particulate matter particles may act as carriers of adsorbed allergens. We show here that flow cytometry, a method widely used to characterize suspended solids &#62;0.5 &#181;m in diameter, can be used to measure these allergen-loaded particles.

Flow cytometry is a method widely used to quantify suspended solids such as cells or bacteria in a size range from 0.5 to several tens of micrometers in ...

Visualizing the Effects of Sputum on Biofilm Development Using a Chambered Coverglass Model

Biofilms consist of groups of bacteria encased in a self-secreted matrix. They play an important role in industrial contamination as well as in the development and persistence of many health related infections. One of the most well described and studied biofilms in human disease occurs in chronic pulmonary infection of cystic fibrosis patients. When studying biofilms in the context of the host, many factors can impact biofilm formation and development. In order to identify how host factors may affect biofilm formation and development, we used a static chambered coverglass method to grow biofilms in the presence of host-derived factors in the form of sputum supernatants. Bacteria are seeded into chambers and exposed to sputum filtrates. Following 48 hr of growth, biofilms are stained with a commercial biofilm viability kit prior to confocal microscopy and analysis. Following image acquisition, biofilm properties can be assessed using different software platforms. This method allows us to visualize key properties of biofilm growth in presence of different substances including antibiotics.

This protocol describes the visualization of biofilm development following exposure to host-factors using a slide chamber model. This model allows for direct visualization of biofilm development as well as analysis of biofilm parameters using computer software programs.

Biofilms consist of groups of bacteria encased in a self-secreted matrix. They play an important role in industrial contamination as well as in the ...

Noninvasive Sampling of Mucosal Lining Fluid for the Quantification of In Vivo Upper Airway Immune-mediator Levels

This protocol describes noninvasive sampling of undisturbed upper airway mucosal lining fluid. It also details the extraction procedure used prior to the analysis of immune mediators in fluid eluates for the study of the airway topical immune signature, without the need for stimulation procedures (often used by other techniques). The mucosal lining fluid is sampled on a strip of filter paper placed at the anterior part of the inferior turbinate and left for 2 min of absorption. Analytes are eluted from the filter papers, and the extracted protein-based eluates are analyzed by an electrochemiluminescence-based immunoassay, allowing for the high-sensitivity quantification of low- and high-level analytes in the same sample. We measured the in vivo levels of 20 preselected immune mediators related to specific immune signaling pathways in the upper airway mucosa, but the technique is not limited to that specific panel or sampling site. The technique was first implemented in 7-year-old children from the Copenhagen Prospective Studies on Asthma in Childhood2000 (COPSAC2000) cohort with allergic rhinitis. It was thereafter used in the longitudinal COPSAC2010 birth cohort, sampled at 1 month, 2 years, and 6 years of age and at instances of acute respiratory symptoms. We successfully obtained and analyzed samples from 620 (89%) of 700 1-month-old children; a few samples were below the assay detection limit (reported as the median (Inter-Quartile Range (IQR)). The number of samples below the detection limit (i.e.&#160;from 0 to the set point for the lower limit of detection) for each mediator was 29 (7.25 - 119.5). This technique enables the quantification of the in vivo airway mucosal immune profile from birth, can be applied longitudinally, and can be applied to studies on the effect of genetics and early-life environmental exposures, pathophysiology, endotyping, and monitoring of respiratory diseases, and development and evaluation of novel therapeutics.

Noninvasive Sampling of Mucosal Lining Fluid for the Quantification of In Vivo Upper Airway Immune-mediator Levels

This protocol describes a noninvasive technique for the sampling of undisturbed mucosal lining fluid from the upper airways. It can be used to perform the quantification of in vivo levels of protein mediators, such as cytokines and chemokines, in subjects of all ages.

This protocol describes noninvasive sampling of undisturbed upper airway mucosal lining fluid. It also details the extraction procedure used prior to the ...

Quantifying Human Monocyte Chemotaxis In Vitro and Murine Lymphocyte Trafficking In Vivo

Chemotaxis is migration along a specific chemical gradient1. Chemokines are chemotactic cytokines that promote cellular trafficking with anatomic and temporal specificity2. Chemotaxis is a critical function of lymphocytes and other immune cells that can be quantitatively assessed in vitro. This manuscript describes methods that permit the evaluation of chemotaxis, both in vitro and in vivo, for diverse cell types including cell lines and native cells. The in vitro, plate-based format permits the comparison of several conditions simultaneously in real-time, and can be completed within 1-4 h. In vitro assay conditions can be manipulated to introduce agonists and antagonists, as well as differentiate chemotaxis from chemokinesis, which is random movement. For in vivo trafficking assessments, immune cells can be labeled with multiple fluorescent dyes and used for adoptive transfer. The differential labeling of cells allows for mixed cell populations to be introduced into the same animal, thereby decreasing variance and reducing the number of animals required for an adequately powered experiment. Migration into lymphoid tissue occurs in as little as 1 h, and multiple tissue compartments can be sampled. Flow cytometry following tissue harvest allows for a rapid and quantitative analysis of the migratory patterns of multiple cell types.

Quantifying Human Monocyte Chemotaxis In Vitro and Murine Lymphocyte Trafficking In Vivo

Protocols for quantitative assessment of lymphocyte chemotaxis and migration are important tools for immunology research. Here, an in vitro protocol is described that permits real-time, multiplexed evaluation of cell migration, as well as a complementary in vivo technique enabling tracking of native cells to spleen.

Chemotaxis is migration along a specific chemical gradient1. Chemokines are chemotactic cytokines that promote cellular trafficking with anatomic and ...

Visualization of Biofilm Formation in Candida albicans Using an Automated Microfluidic Device

Candida albicans is the most common fungal pathogen of humans, causing about 15% of hospital-acquired sepsis cases. A major virulence attribute of C. albicans is its ability to form biofilms, structured communities of cells attached to biotic and abiotic surfaces. C. albicans biofilms can form on host tissues, such as mucosal layers, and on medical devices, such as catheters, pacemakers, dentures, and joint prostheses. Biofilms pose significant clinical challenges because they are highly resistant to physical and chemical perturbations, and can act as reservoirs to seed disseminated infections. Various in vitro assays have been utilized to study C. albicans biofilm formation, such as microtiter plate assays, dry weight measurements, cell viability assays, and confocal scanning laser microscopy. All of these assays are single end-point assays, where biofilm formation is assessed at a specific time point. Here, we describe a protocol to study biofilm formation in real-time using an automated microfluidic device under laminar flow conditions. This method allows for the observation of biofilm formation as the biofilm develops over time, using customizable conditions that mimic those of the host, such as those encountered in vascular catheters. This protocol can be used to assess the biofilm defects of genetic mutants as well as the inhibitory effects of antimicrobial agents on biofilm development in real-time.

Visualization of Biofilm Formation in Candida albicans Using an Automated Microfluidic Device

This protocol describes the use of a customizable automated microfluidic device to visualize biofilm formation in Candida albicans under host physiological conditions.

Candida albicans is the most common fungal pathogen of humans, causing about 15% of hospital-acquired sepsis cases. A major virulence attribute of C. ...