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Multicolour digital image analysis system for identification of bacteria and concurrent assessment of their respiratory activity
Author(s) -
Ogawa M.,
Tani K.,
Ochiai A.,
Yamaguchi N.,
Nasu M.
Publication year - 2005
Publication title -
journal of applied microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.889
H-Index - 156
eISSN - 1365-2672
pISSN - 1364-5072
DOI - 10.1111/j.1365-2672.2005.02551.x
Subject(s) - bacteria , biology , stain , analyser , enumeration , identification (biology) , digital image , digital camera , microbiology and biotechnology , staining , chromatography , image processing , artificial intelligence , chemistry , image (mathematics) , genetics , computer science , botany , mathematics , combinatorics
Aims: To develop a rapid and simple multicolour digital image analysis system for simultaneous identification of bacteria and assessment of their metabolic activity. Methods and Results: We developed an image analyser capable of distinguishing triple‐stained bacterial cells. Bacteria were stained with a nucleic acid stain, a fluorescent antibody and a fluorescent metabolic indicator for enumeration, species identification and assessment of metabolic activity. This multicolour image analyser was used to simultaneously identify Escherichia coli O157:H7 in milk samples and assess their respiratory activity. The images of the triple‐stained bacteria were captured using a combination of blue light and u.v. excitation and an epifluorescence microscope and were processed by our image analyser. We found a good correlation between the counts of actively respiring ( r = 0·93) and total ( r = 0·94) E. coli O157:H7 measured by digital image analysis and visual observation. Conclusion: The multicolour digital image analysis system described here was able to quantify active pathogenic micro‐organisms within 2 h. Significance and Impact of the Study: This multicolour image analysis allows the rapid and simultaneous quantification of bacteria, identification of species and assessment of metabolic activity.