Automated microbiological systems provider Synbiosis has introduced a software module for the ProtoCOL 3 automated colony counter, a commercial automatic microbial identification and counter of colonies cultured on CHROMagar plates.
With minimal training, microbiologists can use the system to rapidly identify and enumerate all key clinical, water and food-borne pathogens.
The new software module, which was developed in partnership with major media manufacturer CHROMagar, ensures that the ProtoCOL 3 system can accurately identify any bacteria or yeast cultured on a CHROMagar plate in less than a minute, saving microbiologists hours of visually inspecting colonies, and manually recording results.
The system performs these tasks by utilising unique, patented red, blue and green lighting to capture a life-like color image of the colonies on the plates.
The new software module analyses the image and it can distinguish between rose pink and dusty pink, as well as turquoise from steel blue.
This allows precise identification of common pathogens, including Salmonella spp., Staphylococcus aureus, Candida albicans, E.coli, Group B Streptococci, Listeria spp., Vibrio spp and Pseudomonas spp.
The system also simultaneously enumerates the different colored colonies of each species, providing objective, consistent data and reducing operator errors, to generate accurate results which can be stored as images and Excel spreadsheets.
“When manually processing large numbers of plates, microbiologists find identifying and counting microbes time consuming, repetitive tasks and have often requested a system that can automate these,” says applications specialist Kate George.
“Accurately identifying microbial pathogens, as well as enumerating so many types of colonies on different agars is difficult. However, we have worked extensively for several years with CHROMagar and are delighted with the resulting powerful analytical software because it makes the ProtoCOL 3 the only commercial system that can perform this seemingly impossible rapid microbial identification task.”
