Multicolour digital image analysis system for identification of bacteria and concurrent assessment of their respiratory activity.
OBJECTIVE
To develop a rapid and simple multicolour digital image analysis system for simultaneous identification of bacteria and assessment of their metabolic activity.


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.


CONCLUSIONS
The multicolour digital image analysis system described here was able to quantify active pathogenic micro-organisms within 2 h.


CONCLUSIONS
This multicolour image analysis allows the rapid and simultaneous quantification of bacteria, identification of species and assessment of metabolic activity.
Ogawa
M
M
Environmental Science and Microbiology, Graduate School of Pharmaceutical Sciences, Osaka University, Osaka, Japan.
Tani
K
K
Ochiai
A
A
Yamaguchi
N
N
Nasu
M
M
D000818:Animals; D002417:Cattle; D015169:Colony Count, Microbial; D003116:Color; D019453:Escherichia coli O157 / Q000302:isolation & purification*; D005516:Food Microbiology; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D008856:Microscopy, Fluorescence; D008892:Milk / Q000382:microbiology*; D013194:Staining and Labeling