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Applied and Environmental Microbiology, May 2007, p. 2956-2962, Vol. 73, No. 9
0099-2240/07/$08.00+0     doi:10.1128/AEM.02954-06
Copyright © 2007, American Society for Microbiology. All Rights Reserved.

Automated Image Analysis for Quantitative Fluorescence In Situ Hybridization with Environmental Samples{triangledown} ,{dagger}

Zhi Zhou,1 Marie Noëlle Pons,2 Lutgarde Raskin,1,{ddagger} and Julie L. Zilles1*

Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 North Mathews Avenue, Urbana, Illinois 61801,1 Laboratoire des Sciences du Génie Chimique, CNRS-ENSIC-INPL, 1 rue Grandville, BP 20451, F-54001 Nancy, France2

Received 20 December 2006/ Accepted 26 February 2007

When fluorescence in situ hybridization (FISH) analyses are performed with complex environmental samples, difficulties related to the presence of microbial cell aggregates and nonuniform background fluorescence are often encountered. The objective of this study was to develop a robust and automated quantitative FISH method for complex environmental samples, such as manure and soil. The method and duration of sample dispersion were optimized to reduce the interference of cell aggregates. An automated image analysis program that detects cells from 4',6'-diamidino-2-phenylindole (DAPI) micrographs and extracts the maximum and mean fluorescence intensities for each cell from corresponding FISH images was developed with the software Visilog. Intensity thresholds were not consistent even for duplicate analyses, so alternative ways of classifying signals were investigated. In the resulting method, the intensity data were divided into clusters using fuzzy c-means clustering, and the resulting clusters were classified as target (positive) or nontarget (negative). A manual quality control confirmed this classification. With this method, 50.4, 72.1, and 64.9% of the cells in two swine manure samples and one soil sample, respectively, were positive as determined with a 16S rRNA-targeted bacterial probe (S-D-Bact-0338-a-A-18). Manual counting resulted in corresponding values of 52.3, 70.6, and 61.5%, respectively. In two swine manure samples and one soil sample 21.6, 12.3, and 2.5% of the cells were positive with an archaeal probe (S-D-Arch-0915-a-A-20), respectively. Manual counting resulted in corresponding values of 22.4, 14.0, and 2.9%, respectively. This automated method should facilitate quantitative analysis of FISH images for a variety of complex environmental samples.

* Corresponding author. Mailing address: 3204 Newmark Civil Engineering Laboratory, MC250, 205 North Mathews Avenue, Urbana, IL 61801. Phone: (217) 244-2925. Fax: (217) 333-6968. E-mail: jzilles{at}uiuc.edu

{triangledown} Published ahead of print on 9 March 2007.

{dagger} Supplemental material for this article may be found at http://aem.asm.org/.

{ddagger} Present address: Department of Civil and Environmental Engineering, University of Michigan, 1351 Beal Ave., Ann Arbor, MI 48109.

Applied and Environmental Microbiology, May 2007, p. 2956-2962, Vol. 73, No. 9
0099-2240/07/$08.00+0     doi:10.1128/AEM.02954-06
Copyright © 2007, American Society for Microbiology. All Rights Reserved.



This article has been cited by other articles:

  • Zhou, Z., Raskin, L., Zilles, J. L. (2009). Macrolide Resistance in Microorganisms at Antimicrobial-Free Swine Farms. Appl. Environ. Microbiol. 75: 5814-5820 [Abstract] [Full Text]  
  • Li, X., Morgenroth, E., Raskin, L. (2008). Quantitative rRNA-Targeted Solution-Based Hybridization Assay Using Peptide Nucleic Acid Molecular Beacons. Appl. Environ. Microbiol. 74: 7297-7305 [Abstract] [Full Text]  


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