PMID- 17351099
OWN - NLM
STAT- MEDLINE
DCOM- 20071213
LR  - 20240413
IS  - 0099-2240 (Print)
IS  - 1098-5336 (Electronic)
IS  - 0099-2240 (Linking)
VI  - 73
IP  - 9
DP  - 2007 May
TI  - Automated image analysis for quantitative fluorescence in situ hybridization with 
      environmental samples.
PG  - 2956-62
AB  - 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.
FAU - Zhou, Zhi
AU  - Zhou Z
AD  - Department of Civil and Environmental Engineering, University of Illinois at 
      Urbana-Champaign, Urbana, IL 61801, USA.
FAU - Pons, Marie Noelle
AU  - Pons MN
FAU - Raskin, Lutgarde
AU  - Raskin L
FAU - Zilles, Julie L
AU  - Zilles JL
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20070309
PL  - United States
TA  - Appl Environ Microbiol
JT  - Applied and environmental microbiology
JID - 7605801
RN  - 0 (Indoles)
RN  - 0 (Manure)
RN  - 47165-04-8 (DAPI)
SB  - IM
MH  - Animals
MH  - *Environmental Microbiology
MH  - Image Processing, Computer-Assisted/*methods
MH  - In Situ Hybridization, Fluorescence/*methods
MH  - Indoles
MH  - Manure/analysis/microbiology
MH  - Soil Microbiology
MH  - Swine
PMC - PMC1892889
EDAT- 2007/03/14 09:00
MHDA- 2007/12/14 09:00
PMCR- 2007/09/01
CRDT- 2007/03/14 09:00
PHST- 2007/03/14 09:00 [pubmed]
PHST- 2007/12/14 09:00 [medline]
PHST- 2007/03/14 09:00 [entrez]
PHST- 2007/09/01 00:00 [pmc-release]
AID - AEM.02954-06 [pii]
AID - 2954-06 [pii]
AID - 10.1128/AEM.02954-06 [doi]
PST - ppublish
SO  - Appl Environ Microbiol. 2007 May;73(9):2956-62. doi: 10.1128/AEM.02954-06. Epub 
      2007 Mar 9.